IDEAS home Printed from https://ideas.repec.org/e/c/pam27.html
   My authors  Follow this author

Gianni Amisano

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Gianni Amisano & Andreas Beyer & Michele Lenza, 2010. "Enhancing monetary analysis," Research Bulletin, European Central Bank, vol. 11, pages 2-6.

    Mentioned in:

    1. > Econometrics > Time Series Models > VAR Models > Bayesian Vector autoregressions (BVARs)

Working papers

  1. Amisano, Gianni & Tristani, Oreste, 2019. "Uncertainty shocks, monetary policy and long-term interest rates," Working Paper Series 2279, European Central Bank.

    Cited by:

    1. Efrem Castelnuovo, 2019. "Yield Curve and Financial Uncertainty: Evidence Based on US Data," CESifo Working Paper Series 7697, CESifo.
    2. Moench, Emanuel & Soofi Siavash, Soroosh, 2022. "What Moves Treasury Yields?," CEPR Discussion Papers 15978, C.E.P.R. Discussion Papers.
    3. Costantini, Mauro & Sousa, Ricardo M., 2022. "What uncertainty does to euro area sovereign bond markets: Flight to safety and flight to quality," Journal of International Money and Finance, Elsevier, vol. 122(C).

  2. Gianni Amisano & Roberta Colavecchio & Gabriel Fagan, 2014. "A money-based indicator for deflation risk," Macroeconomics and Finance Series 201403, University of Hamburg, Department of Socioeconomics.

    Cited by:

    1. Gerdesmeier, Dieter & Reimers, Hans-Eggert & Roffia, Barbara, 2015. "Consumer and asset prices: Some recent evidence," Wismar Discussion Papers 01/2015, Hochschule Wismar, Wismar Business School.

  3. Amisano, Gianni & Geweke, John, 2013. "Prediction using several macroeconomic models," Working Paper Series 1537, European Central Bank.

    Cited by:

    1. Eckert, Florian & Hyndman, Rob J. & Panagiotelis, Anastasios, 2021. "Forecasting Swiss exports using Bayesian forecast reconciliation," European Journal of Operational Research, Elsevier, vol. 291(2), pages 693-710.
    2. Christian Hotz‐Behofsits & Florian Huber & Thomas Otto Zörner, 2018. "Predicting crypto‐currencies using sparse non‐Gaussian state space models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(6), pages 627-640, September.
    3. Bańbura, Marta & Brenna, Federica & Paredes, Joan & Ravazzolo, Francesco, 2021. "Combining Bayesian VARs with survey density forecasts: does it pay off?," Working Paper Series 2543, European Central Bank.
    4. Götz, Thomas B. & Hecq, Alain & Urbain, Jean-Pierre, 2016. "Combining forecasts from successive data vintages: An application to U.S. growth," International Journal of Forecasting, Elsevier, vol. 32(1), pages 61-74.
    5. Markku Lanne & Jani Luoto, 2015. "Estimation of DSGE Models under Diffuse Priors and Data-Driven Identification Constraints," CREATES Research Papers 2015-37, Department of Economics and Business Economics, Aarhus University.
    6. Angela Abbate & Massimiliano Marcellino, 2018. "Point, interval and density forecasts of exchange rates with time varying parameter models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(1), pages 155-179, January.
    7. R. V. Fattakhov & M. M. Nizamutdinov & V. V. Oreshnikov, 2020. "Assessment of the Attractiveness of Large Russian Cities for Residents, Tourists, and Business," Regional Research of Russia, Springer, vol. 10(4), pages 538-548, October.
    8. Laura Liu, 2020. "Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective," CAEPR Working Papers 2020-003, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    9. Adam J. Check & Anna K Nolan & Tyler C. Schipper, 2019. "Forecasting GDP Growth using Disaggregated GDP Revisions," Economics Bulletin, AccessEcon, vol. 39(4), pages 2580-2588.
    10. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2021. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Working Papers 2021-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    11. Jan Capek & Jesus Crespo Cuaresma & Niko Hauzenberger & Vlastimil Reichel, 2020. "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," Department of Economics Working Papers wuwp305, Vienna University of Economics and Business, Department of Economics.
    12. Silvia Miranda Agrippino & Giovanni Ricco, 2018. "Bayesian vector autoregressions," SciencePo Working papers Main hal-03458277, HAL.
    13. Götz, T.B. & Hecq, A.W. & Urbain, J.R.Y.J., 2014. "Combining distributions of real-time forecasts: An application to U.S. growth," Research Memorandum 027, Maastricht University, Graduate School of Business and Economics (GSBE).
    14. Suh, Hyunduk & Walker, Todd B., 2016. "Taking financial frictions to the data," Journal of Economic Dynamics and Control, Elsevier, vol. 64(C), pages 39-65.
    15. Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2018. "Combined Density Nowcasting in an Uncertain Economic Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 131-145, January.
    16. Ouysse, Rachida, 2016. "Bayesian model averaging and principal component regression forecasts in a data rich environment," International Journal of Forecasting, Elsevier, vol. 32(3), pages 763-787.
    17. Florian Huber & Gregor Kastner & Martin Feldkircher, 2016. "Should I stay or should I go? Bayesian inference in the threshold time varying parameter (TTVP) model," Department of Economics Working Papers wuwp235, Vienna University of Economics and Business, Department of Economics.
    18. Francesco Bianchi & Sydney C. Ludvigson & Sai Ma, 2022. "Belief Distortions and Macroeconomic Fluctuations," American Economic Review, American Economic Association, vol. 112(7), pages 2269-2315, July.
    19. Ching-Wai (Jeremy) Chiu & Haroon Mumtaz & Gabor Pinter, 2015. "Forecasting with VAR Models: Fat Tails and Stochastic Volatility," CReMFi Discussion Papers 2, CReMFi, School of Economics and Finance, QMUL.
    20. Jonas Dovern & Hans Manner, 2018. "Order Invariant Tests for Proper Calibration of Multivariate Density Forecasts," CESifo Working Paper Series 7023, CESifo.
    21. Tan, Fei, 2018. "A Frequency-Domain Approach to Dynamic Macroeconomic Models," MPRA Paper 90487, University Library of Munich, Germany.
    22. Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone In?ation and Real Interest Rates," PIER Working Paper Archive 21-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    23. Del Negro, Marco & Hasegawa, Raiden B. & Schorfheide, Frank, 2016. "Dynamic prediction pools: An investigation of financial frictions and forecasting performance," Journal of Econometrics, Elsevier, vol. 192(2), pages 391-405.
    24. A. Ford Ramsey & Yong Liu, 2023. "Linear pooling of potentially related density forecasts in crop insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 90(3), pages 769-788, September.
    25. Peter McAdam & Anders Warne, 2024. "Density forecast combinations: The real‐time dimension," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1153-1172, August.
    26. Ross Askanazi & Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2018. "On the Comparison of Interval Forecasts," PIER Working Paper Archive 18-013, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 02 Aug 2018.
    27. Mohammad R. Jahan-Parvar & Charles Knipp & Pawel J. Szerszen, 2024. "Trend-Cycle Decomposition and Forecasting Using Bayesian Multivariate Unobserved Components," Finance and Economics Discussion Series 2024-100, Board of Governors of the Federal Reserve System (U.S.).
    28. Низамутдинов М.М. & Орешников В.В., 2016. "Определение Параметров Управления Региональным Развитием На Основе Алгоритмов Нечеткой Логики," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 52(2), pages 30-39, апрель.
    29. Hauber, Philipp, 2022. "Real-time nowcasting with sparse factor models," EconStor Preprints 251551, ZBW - Leibniz Information Centre for Economics.
    30. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2020. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(531), pages 1092-1110, July.
    31. McAdam, Peter & Warne, Anders, 2018. "Euro area real-time density forecasting with financial or labor market frictions," Working Paper Series 2140, European Central Bank.
    32. Drachal, Krzysztof, 2021. "Forecasting crude oil real prices with averaging time-varying VAR models," Resources Policy, Elsevier, vol. 74(C).
    33. Florian Huber & Gregor Kastner & Martin Feldkircher, 2019. "Should I stay or should I go? A latent threshold approach to large‐scale mixture innovation models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(5), pages 621-640, August.
    34. Knut Are Aastveit & James Mitchell & Francesco Ravazzolo & Herman van Dijk, 2018. "The Evolution of Forecast Density Combinations in Economics," Tinbergen Institute Discussion Papers 18-069/III, Tinbergen Institute.
    35. Warne, Anders, 2023. "DSGE model forecasting: rational expectations vs. adaptive learning," Working Paper Series 2768, European Central Bank.
    36. Ho, Paul & Lubik, Thomas A. & Matthes, Christian, 2024. "Averaging impulse responses using prediction pools," Journal of Monetary Economics, Elsevier, vol. 146(C).
    37. Loria, Francesca & Matthes, Christian & Wang, Mu-Chun, 2021. "Economic theories and macroeconomic reality," Discussion Papers 56/2021, Deutsche Bundesbank.
    38. Carlos Henrique Dias Cordeiro de Castro & Fernando Antonio Lucena Aiube, 2023. "Forecasting inflation time series using score‐driven dynamic models and combination methods: The case of Brazil," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 369-401, March.
    39. Ellington, Michael, 2018. "Financial market illiquidity shocks and macroeconomic dynamics: Evidence from the UK," Journal of Banking & Finance, Elsevier, vol. 89(C), pages 225-236.
    40. Lasha Kavtaradze & Manouchehr Mokhtari, 2018. "Factor Models And Time†Varying Parameter Framework For Forecasting Exchange Rates And Inflation: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 302-334, April.

  4. Gianni Amisano & Roberta Colavecchio, 2013. "Money Growth and Inflation: evidence from a Markov Switching Bayesian VAR," Macroeconomics and Finance Series 201304, University of Hamburg, Department of Socioeconomics.

    Cited by:

    1. Colavecchio, Roberta & Amisano, Gianni & Fagan, Gabriel, 2014. "A money-based indicator for deflation risk," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100595, Verein für Socialpolitik / German Economic Association.
    2. Eltejaei , Ebrahim & Montazeri Shoorekchali , Jalal, 2021. "Investigating the Relationship between Money Growth and Inflation in Turkey: A Nonlinear Causality Approach," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 16(3), pages 305-322, September.
    3. Markku Lanne & Jani Luoto & Henri Nyberg, 2014. "Is the Quantity Theory of Money Useful in Forecasting U.S. Inflation?," CREATES Research Papers 2014-26, Department of Economics and Business Economics, Aarhus University.
    4. Claudio Borio & Marco Jacopo Lombardi & James Yetman & Egon Zakrajsek, 2023. "The two-regime view of inflation," BIS Papers, Bank for International Settlements, number 133.
    5. Cuneyt Dumrul & Yasemin Dumrul, 2015. "Price-Money Relationship after Infl ation Targeting: Co-integration Test with Structural Breaks for Turkey and Brazil," International Journal of Economics and Financial Issues, Econjournals, vol. 5(3), pages 701-708.

  5. Tristani, Oreste & Amisano, Gianni, 2011. "Exact likelihood computation for nonlinear DSGE models with heteroskedastic innovations," Working Paper Series 1341, European Central Bank.

    Cited by:

    1. Andrew T. Foerster & Juan F. Rubio-Ramirez & Daniel F. Waggoner & Tao Zha, 2013. "Perturbation methods for Markov-switching DSGE model," Research Working Paper RWP 13-01, Federal Reserve Bank of Kansas City.
    2. Gianni Amisano & Oreste Tristani, 2023. "Monetary policy and long‐term interest rates," Quantitative Economics, Econometric Society, vol. 14(2), pages 689-716, May.
    3. Negro, Marco Del & Schorfheide, Frank, 2013. "DSGE Model-Based Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 57-140, Elsevier.
    4. Viktors Ajevskis, 2015. "Nonlocal Solutions to Dynamic Equilibrium Models: The Approximate Stable Manifolds Approach," Papers 1506.02521, arXiv.org.
    5. Raffaella Giacomini, 2013. "The relationship between DSGE and VAR models," CeMMAP working papers 21/13, Institute for Fiscal Studies.
    6. Amisano, Gianni & Tristani, Oreste, 2019. "Uncertainty shocks, monetary policy and long-term interest rates," Working Paper Series 2279, European Central Bank.
    7. Hall, Jamie, 2012. "Rapid estimation of nonlinear DSGE models," MPRA Paper 41218, University Library of Munich, Germany.
    8. Maddalena Cavicchioli, 2020. "Invertibility and VAR Representations of Time-Varying Dynamic Stochastic General Equilibrium Models," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 61-86, January.
    9. Horváth, Roman & Maršál, Aleš, 2014. "The term structure of interest rates in a small open economy DSGE model with Markov switching," FinMaP-Working Papers 22, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    10. Pablo A. Cuba-Borda & Luca Guerrieri & Matteo Iacoviello & Molin Zhong, 2019. "Likelihood Evaluation of Models with Occasionally Binding Constraints," Finance and Economics Discussion Series 2019-028, Board of Governors of the Federal Reserve System (U.S.).
    11. Luisa Corrado & Stefano Grassi & Aldo Paolillo, 2021. "Modelling and Estimating Large Macroeconomic Shocks During the Pandemic," CREATES Research Papers 2021-08, Department of Economics and Business Economics, Aarhus University.
    12. Luisa Corrado & Stefano Grassi & Aldo Paolillo, 2021. "Identifying Economic Shocks in a Rare Disaster Environment," CEIS Research Paper 517, Tor Vergata University, CEIS, revised 18 Jul 2024.
    13. Paolo Andreini & Cosimo Izzo & Giovanni Ricco, 2023. "Deep Dynamic Factor Models," Working Papers 2023-08, Center for Research in Economics and Statistics.
    14. Hall, Jamie, 2012. "Consumption dynamics in general equilibrium," MPRA Paper 43933, University Library of Munich, Germany.
    15. Raffaella Giacomini, 2013. "The relationship between DSGE and VAR models," CeMMAP working papers CWP21/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

  6. Amisano, Gianni & Geweke, John, 2011. "Analysis of variance for bayesian inference," Working Paper Series 1409, European Central Bank.

    Cited by:

    1. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2021. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Working Papers 2021-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    2. Mike Tsionas & Marwan Izzeldin & Lorenzo Trapani, 2019. "Bayesian estimation of large dimensional time varying VARs using copulas," Papers 1912.12527, arXiv.org.
    3. Erlan Konebayev, 2023. "Forecasting a Commodity-Exporting Small Open Developing Economy Using DSGE and DSGE-BVAR," International Economic Journal, Taylor & Francis Journals, vol. 37(1), pages 39-70, January.
    4. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2014. "Marginalized predictive likelihood comparisons of linear Gaussian state-space models with applications to DSGE, DSGEVAR, and VAR models," CFS Working Paper Series 478, Center for Financial Studies (CFS).
    5. Daniel F. Waggoner & Tao Zha, 2012. "Confronting Model Misspecification in Macroeconomics," NBER Working Papers 17791, National Bureau of Economic Research, Inc.
    6. Michał Rubaszek & Marcin Kolasa, 2013. "Forecasting with DSGE models with financial frictions," EcoMod2013 5100, EcoMod.
    7. McAdam, Peter & Warne, Anders, 2018. "Euro area real-time density forecasting with financial or labor market frictions," Working Paper Series 2140, European Central Bank.
    8. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).

  7. Amisano, Gianni & Fagan, Gabriel, 2010. "Money growth and inflation: a regime switching approach," Working Paper Series 1207, European Central Bank.

    Cited by:

    1. Colavecchio, Roberta & Amisano, Gianni & Fagan, Gabriel, 2014. "A money-based indicator for deflation risk," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100595, Verein für Socialpolitik / German Economic Association.
    2. Egorov D.A. (Егоров, Д.А.) & Perevyshina E.A. (Перевышина, Е.А.), 2016. "Modelling of Inflationary Processes in Russia [Моделирование Инфляционных Процессов В России]," Working Papers 2138, Russian Presidential Academy of National Economy and Public Administration.
    3. Boris Blagov & Michael Funke, 2016. "The Credibility of Hong Kong's Currency Board System: Looking Through the Prism of MS-VAR Models with Time-Varying Transition Probabilities," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(6), pages 895-914, December.
    4. Alexander Jung, 2018. "Have money and credit data releases helped markets to predict the interest rate decisions of the European Central Bank?," Scottish Journal of Political Economy, Scottish Economic Society, vol. 65(1), pages 39-67, February.
    5. Mandler, Martin & Scharnagl, Michael, 2014. "Money growth and consumer price inflation in the euro area: A wavelet analysis," Discussion Papers 33/2014, Deutsche Bundesbank.
    6. Piergiorgio Alessandri & Haroon Mumtaz, 2014. "Financial conditions and density forecasts for US output and inflation," CReMFi Discussion Papers 1, CReMFi, School of Economics and Finance, QMUL.
    7. Ringwald, Leopold & Zörner, Thomas O., 2023. "The money-inflation nexus revisited," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 293-333.
    8. Christopher CRUZ & Claire MAPA, 2013. "An Early Warning System For Inflation In The Philippines Using Markov-Switching And Logistic Regression Models," Theoretical and Practical Research in the Economic Fields, ASERS Publishing, vol. 4(2), pages 136-150.
    9. Antonio N. Bojanic, 2021. "A Markov-Switching Model of Inflation in Bolivia," Economies, MDPI, vol. 9(1), pages 1-18, March.
    10. Niko Hauzenberger & Florian Huber, 2020. "Model instability in predictive exchange rate regressions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 168-186, March.
    11. Luisa Corrado & Stefano Grassi & Enrico Minnella, 2021. "The Transmission Mechanism of Quantitative Easing: A Markov-Switching FAVAR Approach," CEIS Research Paper 520, Tor Vergata University, CEIS, revised 21 Oct 2021.
    12. Eltejaei , Ebrahim & Montazeri Shoorekchali , Jalal, 2021. "Investigating the Relationship between Money Growth and Inflation in Turkey: A Nonlinear Causality Approach," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 16(3), pages 305-322, September.
    13. Wang, Yu-Min & Lin, Che-Chun & Tsai, I-Chun, 2023. "State transformation of information spillover in asset markets and effective dynamic hedging strategies," International Review of Financial Analysis, Elsevier, vol. 89(C).
    14. Shashank Gupta & Shalini Gupta, 2017. "Modeling economic system using fuzzy cognitive maps," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 1472-1486, November.
    15. Huber, Florian & Fischer, Manfred M., 2015. "A Markov switching factor-augmented VAR model for analyzing US business cycles and monetary policy," Department of Economics Working Paper Series 201, WU Vienna University of Economics and Business.
    16. Piergiorgio Alessandri & Haroon Mumtaz, 2017. "Online Appendix to "Financial conditions and density forecasts for US output and inflation"," Online Appendices 14-103, Review of Economic Dynamics.
    17. Wojciech W. Charemza & Svetlana Makarova & Imran Shah, 2013. "Making the Most of High Inflation," UCL SSEES Economics and Business working paper series 124, UCL School of Slavonic and East European Studies (SSEES).
    18. Sylvia Kaufmann, 2011. "K-state switching models with endogenous transition distributions," Working Papers 2011-13, Swiss National Bank.
    19. Krzysztof DRACHAL, 2020. "Forecasting the Inflation Rate in Poland and U.S. Using Dynamic Model Averaging (DMA) and Google Queries," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 18-34, July.
    20. Smith, Michael Stanley & Maneesoonthorn, Worapree, 2018. "Inversion copulas from nonlinear state space models with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 34(3), pages 389-407.
    21. Bekiros Stelios & Muzaffar Ahmed T. & Uddin Gazi S. & Vidal-García Javier, 2017. "Money supply and inflation dynamics in the Asia-Pacific economies: a time-frequency approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(3), pages 1-12, June.
    22. Abdorasoul Sadeghi & Hussein Marzban & Ali Hussein Samadi & Karim Azarbaiejani & Parviz Rostamzadeh, 2022. "Financial intermediaries and speculation in the foreign exchange market: the role of monetary policy in Iran’s economy," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 11(1), pages 1-26, December.
    23. Jung, Alexander, 2024. "The quantity theory of money, 1870-2020," Working Paper Series 2940, European Central Bank.
    24. Eugene Msizi Buthelezi, 2023. "Impact of Money Supply in Different States of Inflation and Economic Growth in South Africa," Economies, MDPI, vol. 11(2), pages 1-22, February.
    25. Luca Sessa, 2012. "Economic (in)stability under monetary targeting," Temi di discussione (Economic working papers) 858, Bank of Italy, Economic Research and International Relations Area.
    26. Claude Hillinger & Bernd Süssmuth & Marco Sunder, 2015. "The Quantity Theory of Money: Valid Only for High and Medium Inflation?," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot GmbH, Berlin, vol. 61(4), pages 315-329.
    27. Hyun Hak Kim & Na Kyeong Lee, 2025. "State-Dependent Phillips Curve," Economies, MDPI, vol. 13(1), pages 1-14, January.
    28. Kaufmann, Sylvia, 2015. "K-state switching models with time-varying transition distributions—Does loan growth signal stronger effects of variables on inflation?," Journal of Econometrics, Elsevier, vol. 187(1), pages 82-94.
    29. Serdar Ongan, Ismet Gocer, Ayse Ongan, 2022. "Revisiting the quantity theory of money in Euro Area: the case of Greece," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 19(1), pages 63-77, June.
    30. Gianni Amisano & Roberta Colavecchio, 2025. "Monetary aggregates and inflation: A new view on an old relationship," BCL working papers 195, Central Bank of Luxembourg.
    31. Goodarzi, Milad & Meinerding, Christoph, 2023. "Asset allocation with recursive parameter updating and macroeconomic regime identifiers," Discussion Papers 06/2023, Deutsche Bundesbank.
    32. Fédéric Holm-Hadulla & Kirstin Hubrich, 2017. "Macroeconomic Implications of Oil Price Fluctuations : A Regime-Switching Framework for the Euro Area," Finance and Economics Discussion Series 2017-063, Board of Governors of the Federal Reserve System (U.S.).
    33. Gabriel Rodriguez-Rondon, 2024. "Underlying Core Inflation with Multiple Regimes," Papers 2411.12845, arXiv.org.
    34. Scott A. Brave & Jose A. Lopez, 2018. "Calibrating Macroprudential Policy to Forecasts of Financial Stability," Working Paper Series 2017-17, Federal Reserve Bank of San Francisco.
    35. Niko Hauzenberger & Florian Huber & Michael Pfarrhofer & Thomas O. Zorner, 2018. "Stochastic model specification in Markov switching vector error correction models," Papers 1807.00529, arXiv.org, revised Sep 2019.
    36. Garcés Díaz Daniel, 2016. "Changes in Inflation Predictability in Major Latin American Countries," Working Papers 2016-20, Banco de México.
    37. Claudiu Tiberiu Albulescu & Daniel Goyeau & Cornel Oros, 2015. "On the Long Run Money-Prices Relationship in CEE Countries," Post-Print hal-01257389, HAL.
    38. Claudio Borio & Marco Jacopo Lombardi & James Yetman & Egon Zakrajsek, 2023. "The two-regime view of inflation," BIS Papers, Bank for International Settlements, number 133.
    39. Kai Zheng & Yuying Li & Weidong Xu, 2021. "Regime switching model estimation: spectral clustering hidden Markov model," Annals of Operations Research, Springer, vol. 303(1), pages 297-319, August.
    40. Kumar, Utkarsh & Ahmad, Wasim & Uddin, Gazi Salah, 2024. "Bayesian Markov switching model for BRICS currencies' exchange rates," LSE Research Online Documents on Economics 122816, London School of Economics and Political Science, LSE Library.
    41. Murdipi, Rafiqa & Law, Siong Hook, 2016. "Dynamic Linkages between Price Indices and Inflation in Malaysia," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 50(1), pages 41-52.
    42. Eller, Markus & Hauzenberger, Niko & Huber, Florian & Schuberth, Helene & Vashold, Lukas, 2021. "The impact of macroprudential policies on capital flows in CESEE," Journal of International Money and Finance, Elsevier, vol. 119(C).
    43. O. Evans, 2019. "Money, Inflation and Output in Nigeria and South Africa: Could Friedman and Schwartz Be Right?," Journal of African Business, Taylor & Francis Journals, vol. 20(3), pages 392-406, July.
    44. Sánchez García, Javier & Galdeano Gómez, Emilio & Cruz Rambaud, Salvador, 2024. "Drivers of inflationary shocks and spillovers between Europe and the United States," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).
    45. Niko Hauzenberger & Florian Huber & Karin Klieber & Massimiliano Marcellino, 2022. "Bayesian Neural Networks for Macroeconomic Analysis," Papers 2211.04752, arXiv.org, revised Apr 2024.
    46. Wang, Zanxin & Wei, Wei & Luo, Junwen & Calderon, Margaret, 2019. "The effects of petroleum product price regulation on macroeconomic stability in China," Energy Policy, Elsevier, vol. 132(C), pages 96-105.
    47. Hülya Saygılı & Aysun Türkvatan, 2023. "Tradable and non-tradable inflation in Turkey: asymmetric responses to global factors," Empirical Economics, Springer, vol. 65(2), pages 973-1006, August.
    48. Dreger, Christian & Wolters, Jürgen, 2014. "Money demand and the role of monetary indicators in forecasting euro area inflation," International Journal of Forecasting, Elsevier, vol. 30(2), pages 303-312.
    49. Cuneyt Dumrul & Yasemin Dumrul, 2015. "Price-Money Relationship after Infl ation Targeting: Co-integration Test with Structural Breaks for Turkey and Brazil," International Journal of Economics and Financial Issues, Econjournals, vol. 5(3), pages 701-708.
    50. Zolotoy, Leon & Frederickson, James R. & Lyon, John D., 2017. "Aggregate earnings and stock market returns: The good, the bad, and the state-dependent," Journal of Banking & Finance, Elsevier, vol. 77(C), pages 157-175.
    51. Gerdesmeier, Dieter & Reimers, Hans-Eggert & Roffia, Barbara, 2015. "Consumer and asset prices: Some recent evidence," Wismar Discussion Papers 01/2015, Hochschule Wismar, Wismar Business School.
    52. Sehati , Elham & Mousavi Jahromi , Yeganeh & Mehrara , Mohsen & Najafizadeh , Abbas, 2018. "Non-Linear Inflationary Dynamics based on the Concept of Missing Money in Iran," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 13(2), pages 221-243, April.
    53. Jung, Alexander, 2016. "Have monetary data releases helped markets to predict the interest rate decisions of the European Central Bank?," Working Paper Series 1926, European Central Bank.

  8. Oreste Tristani & Gianni Amisano, 2010. "A nonlinear DSGE model of the term structure with regime shifts," 2010 Meeting Papers 234, Society for Economic Dynamics.

    Cited by:

    1. Ales Marsal, 2018. "Government Spending and the Term Structure of Interest Rates in a DSGE Model," 2018 Meeting Papers 107, Society for Economic Dynamics.
    2. James Staveley-O'Carroll & Olena M. Staveley-O'Carroll, 2016. "Impact of Pension System Structure on International Financial Capital Allocation," Working Papers 1601, College of the Holy Cross, Department of Economics.
    3. Carboni, Giacomo, 2014. "Term premia implications of macroeconomic regime changes," Working Paper Series 1694, European Central Bank.
    4. Asiye Aydilek & Harun Aydilek, 2020. "An optimization model of retiree decisions under recursive utility with housing," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 44(2), pages 258-277, April.

  9. Amisano, Gianni & Giammarioli, Nicola & Stracca, Livio, 2009. "EMU and the adjustment to asymmetric shocks: the case of Italy," Working Paper Series 1128, European Central Bank.

    Cited by:

    1. Timo Bettendorf, 2017. "Idiosyncratic and international transmission of shocks in the G7: Does EMU matter?," Review of International Economics, Wiley Blackwell, vol. 25(4), pages 856-890, September.
    2. Volha Audzei & Frantisek Brazdik, 2015. "Monetary Policy and Exchange Rate Dynamics: The Exchange Rate as a Shock Absorber," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 65(5), pages 391-410, October.
    3. Sergio Sola, 2013. "Temporary and Persistent Fiscal Policy Shocks," IHEID Working Papers 06-2013, Economics Section, The Graduate Institute of International Studies.
    4. António Afonso & Jaromír Baxa & Michal Slavík, 2018. "Fiscal developments and financial stress: a threshold VAR analysis," Empirical Economics, Springer, vol. 54(2), pages 395-423, March.
    5. Audzei, Volha & Brázdik, František, 2018. "Exchange rate dynamics and their effect on macroeconomic volatility in selected CEE countries," Economic Systems, Elsevier, vol. 42(4), pages 584-596.
    6. Brzoza-Brzezina, Michał & Makarski, Krzysztof & Wesołowski, Grzegorz, 2014. "Would it have paid to be in the eurozone?," Economic Modelling, Elsevier, vol. 41(C), pages 66-79.
    7. Volha Audzei & Frantisek Brazdik, 2015. "Exchange Rate Dynamics and its Effect on Macroeconomic Volatility in Selected CEE Countries," Working Papers 2015/07, Czech National Bank.
    8. Serati, Massimiliano & Venegoni, Andrea, 2019. "The cross-country impact of ECB policies: Asymmetries in – Asymmetries out?," Journal of International Money and Finance, Elsevier, vol. 90(C), pages 118-141.
    9. Andrea Venegoni & Massimiliano Serati, 2017. "The Symmetry of ECB Monetary Policy Impact Under Scrutiny: An Assessment," LIUC Papers in Economics 306, Cattaneo University (LIUC).

  10. Amisano, Gianni & Geweke, John, 2009. "Optimal Prediction Pools," Working Paper Series 1017, European Central Bank.

    Cited by:

    1. Paolo Gorgi, 2020. "Beta–negative binomial auto‐regressions for modelling integer‐valued time series with extreme observations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(5), pages 1325-1347, December.
    2. Laurent Ferrara & Matteo Mogliani & Jean-Guillaume Sahuc, 2020. "High-frequency monitoring of growth-at-risk," CAMA Working Papers 2020-97, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. Arčabić, Vladimir & Panovska, Irina & Tica, Josip, 2024. "Business cycle synchronization and asymmetry in the European Union," Economic Modelling, Elsevier, vol. 139(C).
    4. N. Fawcett & G. Kapetanios & J. Mitchell & S. Price, 2014. "Generalised Density Forecast Combinations," CAMA Working Papers 2014-24, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    5. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-scale portfolio allocation under transaction costs and model uncertainty," CFS Working Paper Series 582, Center for Financial Studies (CFS).
    6. Xu Cheng & Bruce E. Hansen, 2012. "Forecasting with Factor-Augmented Regression: A Frequentist Model Averaging Approach," PIER Working Paper Archive 12-046, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    7. Anthony Garratt & Ivan Petrella, 2022. "Commodity prices and inflation risk," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 392-414, March.
    8. Joscha Beckmann & Rainer Schüssler, 2014. "Forecasting Exchange Rates under Model and Parameter Uncertainty," CQE Working Papers 3214, Center for Quantitative Economics (CQE), University of Muenster.
    9. Shaun P Vahey & Elizabeth C Wakerly, 2013. "Moving towards probability forecasting," BIS Papers chapters, in: Bank for International Settlements (ed.), Globalisation and inflation dynamics in Asia and the Pacific, volume 70, pages 3-8, Bank for International Settlements.
    10. Li, Li & Kang, Yanfei & Li, Feng, 2023. "Bayesian forecast combination using time-varying features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1287-1302.
    11. Chen, Yi-Ting & Liu, Chu-An, 2023. "Model averaging for asymptotically optimal combined forecasts," Journal of Econometrics, Elsevier, vol. 235(2), pages 592-607.
    12. Bańbura, Marta & Brenna, Federica & Paredes, Joan & Ravazzolo, Francesco, 2021. "Combining Bayesian VARs with survey density forecasts: does it pay off?," Working Paper Series 2543, European Central Bank.
    13. Hansen, Lars Peter & Sargent, Thomas J., 2022. "Structured ambiguity and model misspecification," Journal of Economic Theory, Elsevier, vol. 199(C).
    14. Krüger, Fabian & Nolte, Ingmar, 2016. "Disagreement versus uncertainty: Evidence from distribution forecasts," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 172-186.
    15. Emilio Zanetti Chini, 2017. "Generalizing Smooth Transition Autoregressions," DEM Working Papers Series 138, University of Pavia, Department of Economics and Management.
    16. Mogliani, Matteo & Simoni, Anna, 2021. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Journal of Econometrics, Elsevier, vol. 222(1), pages 833-860.
    17. Tsionas, Mike & Parmeter, Christopher F. & Zelenyuk, Valentin, 2023. "Bayesian Artificial Neural Networks for frontier efficiency analysis," Journal of Econometrics, Elsevier, vol. 236(2).
    18. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    19. Elliott, Graham & Timmermann, Allan G, 2016. "Forecasting in Economics and Finance," University of California at San Diego, Economics Working Paper Series qt6z55v472, Department of Economics, UC San Diego.
    20. Markku Lanne & Jani Luoto, 2015. "Estimation of DSGE Models under Diffuse Priors and Data-Driven Identification Constraints," CREATES Research Papers 2015-37, Department of Economics and Business Economics, Aarhus University.
    21. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty: Adaptive Mixing of High- and Low-Frequency Information," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168222, Verein für Socialpolitik / German Economic Association.
    22. Blasques, F. & Gorgi, P. & Koopman, S.J., 2019. "Accelerating score-driven time series models," Journal of Econometrics, Elsevier, vol. 212(2), pages 359-376.
    23. Martina Hengge, 2019. "Uncertainty as a Predictor of Economic Activity," IHEID Working Papers 19-2019, Economics Section, The Graduate Institute of International Studies.
    24. Anne Sofie Jore & James Mitchell & Shaun P. Vahey, 2010. "Combining forecast densities from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 621-634.
    25. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2021. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Working Papers 2021-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    26. G. Kenny, 2014. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 500-504, October.
    27. Gong, Xiao-Li & Liu, Xi-Hua & Xiong, Xiong & Zhuang, Xin-Tian, 2019. "Non-Gaussian VARMA model with stochastic volatility and applications in stock market bubbles," Chaos, Solitons & Fractals, Elsevier, vol. 121(C), pages 129-136.
    28. Jin, Xin & Maheu, John M. & Yang, Qiao, 2022. "Infinite Markov pooling of predictive distributions," Journal of Econometrics, Elsevier, vol. 228(2), pages 302-321.
    29. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 527-724, Elsevier.
    30. Kenny, Geoff & Kostka, Thomas & Masera, Federico, 2013. "Can macroeconomists forecast risk? Event-based evidence from the euro area SPF," Working Paper Series 1540, European Central Bank.
    31. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    32. Eo, Yunjong & Kang, Kyu Ho, 2020. "The effects of conventional and unconventional monetary policy on forecasting the yield curve," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    33. Kenichiro McAlinn & Kosaku Takanashi, 2019. "Mean-shift least squares model averaging," Papers 1912.01194, arXiv.org.
    34. Piergiorgio Alessandri & Haroon Mumtaz, 2014. "Financial conditions and density forecasts for US output and inflation," CReMFi Discussion Papers 1, CReMFi, School of Economics and Finance, QMUL.
    35. Guofu Zhou, 2018. "Measuring Investor Sentiment," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 239-259, November.
    36. Stanislav Anatolyev & Renat Khabibullin & Artem Prokhorov, 2013. "Reconstructing high dimensional dynamic distributions from distributions of lower dimension," Working Papers w0167, New Economic School (NES).
    37. Jan Capek & Jesus Crespo Cuaresma & Niko Hauzenberger & Vlastimil Reichel, 2020. "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," Department of Economics Working Papers wuwp305, Vienna University of Economics and Business, Department of Economics.
    38. Krüger, Fabian & Clark, Todd E. & Ravazzolo, Francesco, 2015. "Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113077, Verein für Socialpolitik / German Economic Association.
    39. Silvia Miranda Agrippino & Giovanni Ricco, 2018. "Bayesian vector autoregressions," SciencePo Working papers Main hal-03458277, HAL.
    40. Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," DEM Working Papers Series 145, University of Pavia, Department of Economics and Management.
    41. Buncic, Daniel & Müller, Oliver, 2017. "Measuring the output gap in Switzerland with linear opinion pools," Economic Modelling, Elsevier, vol. 64(C), pages 153-171.
    42. Hilde C. Bjornland & Francesco Ravazzolo & Leif Anders Thorsrud, 2016. "Forecasting GDP with global components. This time is different," CAMA Working Papers 2016-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    43. Perricone, Chiara, 2018. "Clustering macroeconomic variables," Structural Change and Economic Dynamics, Elsevier, vol. 44(C), pages 23-33.
    44. Gianni Amisano & John Geweke, 2017. "Prediction Using Several Macroeconomic Models," The Review of Economics and Statistics, MIT Press, vol. 99(5), pages 912-925, December.
    45. Tim Oliver Berg & Steffen Henzel, 2014. "Point and Density Forecasts for the Euro Area Using Bayesian VARs," CESifo Working Paper Series 4711, CESifo.
    46. Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2018. "Combined Density Nowcasting in an Uncertain Economic Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 131-145, January.
    47. Hirano, Keisuke & Wright, Jonathan H., 2022. "Analyzing cross-validation for forecasting with structural instability," Journal of Econometrics, Elsevier, vol. 226(1), pages 139-154.
    48. Xu Cheng & Bruce E. Hansen, 2012. "Forecasting with Factor-Augmented Regression: A Frequentist Model Averaging Approach, Second Version," PIER Working Paper Archive 13-061, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 03 Sep 2013.
    49. Rui Liu, 2019. "Forecasting Bond Risk Premia with Unspanned Macroeconomic Information," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 9(01), pages 1-62, March.
    50. Richard K. Crump & Miro Everaert & Domenico Giannone & Sean Hundtofte, 2018. "Changing Risk-Return Profiles," Staff Reports 850, Federal Reserve Bank of New York.
    51. Garratt, Anthony & Henckel, Timo & Vahey, Shaun P., 2023. "Empirically-transformed linear opinion pools," International Journal of Forecasting, Elsevier, vol. 39(2), pages 736-753.
    52. Knut Are Aastveit & Jamie Cross & Herman K. van Dijk, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Tinbergen Institute Discussion Papers 21-053/III, Tinbergen Institute.
    53. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    54. Daniele Bianchi & Kenichiro McAlinn, 2018. "Large-Scale Dynamic Predictive Regressions," Papers 1803.06738, arXiv.org.
    55. Tim Oliver Berg & Steffen Henzel, 2013. "Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?," ifo Working Paper Series 155, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    56. Zhao, Weigang & Wang, Jianzhou & Lu, Haiyan, 2014. "Combining forecasts of electricity consumption in China with time-varying weights updated by a high-order Markov chain model," Omega, Elsevier, vol. 45(C), pages 80-91.
    57. Filippo di Mauro & Filippo di Mauro, Fabio Fornari, 2014. "Going granular: The importance of firm-level equity information in anticipating economic activity," EcoMod2014 6809, EcoMod.
    58. Graziano Moramarco, 2021. "Regime-Switching Density Forecasts Using Economists' Scenarios," Papers 2110.13761, arXiv.org, revised Feb 2024.
    59. Ching-Wai (Jeremy) Chiu & Haroon Mumtaz & Gabor Pinter, 2015. "Forecasting with VAR Models: Fat Tails and Stochastic Volatility," CReMFi Discussion Papers 2, CReMFi, School of Economics and Finance, QMUL.
    60. Kourentzes, Nikolaos & Barrow, Devon & Petropoulos, Fotios, 2019. "Another look at forecast selection and combination: Evidence from forecast pooling," International Journal of Production Economics, Elsevier, vol. 209(C), pages 226-235.
    61. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    62. Cross, Jamie & Poon, Aubrey, 2016. "Forecasting structural change and fat-tailed events in Australian macroeconomic variables," Economic Modelling, Elsevier, vol. 58(C), pages 34-51.
    63. Risse, Marian & Ohl, Ludwig, 2017. "Using dynamic model averaging in state space representation with dynamic Occam’s window and applications to the stock and gold market," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 158-176.
    64. Fabio Canova & Christian Matthes, 2021. "Dealing with misspecification in structural macroeconometric models," Quantitative Economics, Econometric Society, vol. 12(2), pages 313-350, May.
    65. Tsionas, Mike G., 2022. "Random and Markov switching exponential smoothing models," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    66. Joffre Swait & Fred Feinberg, 2014. "Deciding how to decide: an agenda for multi-stage choice modelling research in marketing," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 26, pages 649-660, Edward Elgar Publishing.
    67. Sean Langcake & Tim Robinson, 2013. "An Empirical BVAR-DSGE Model of the Australian Economy," RBA Research Discussion Papers rdp2013-07, Reserve Bank of Australia.
    68. Pauwels, Laurent & Vasnev, Andrey, 2011. "Forecast combination for discrete choice models: predicting FOMC monetary policy decisions," Working Papers 11/2011, University of Sydney Business School, Discipline of Business Analytics.
    69. Tan, Fei, 2018. "A Frequency-Domain Approach to Dynamic Macroeconomic Models," MPRA Paper 90487, University Library of Munich, Germany.
    70. Silvia Figini & Roberto Savona & Marika Vezzoli, 2016. "Corporate Default Prediction Model Averaging: A Normative Linear Pooling Approach," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 23(1-2), pages 6-20, January.
    71. Qian, Wei & Rolling, Craig A. & Cheng, Gang & Yang, Yuhong, 2022. "Combining forecasts for universally optimal performance," International Journal of Forecasting, Elsevier, vol. 38(1), pages 193-208.
    72. Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone In?ation and Real Interest Rates," PIER Working Paper Archive 21-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    73. Cristiano Cantore & Paul Levine & Joseph Pearlman & Bo Yang, 2014. "CES Technology and Business Cycle Fluctuations," School of Economics Discussion Papers 0414, School of Economics, University of Surrey.
    74. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2010. "Forecasting with DSGE models," Working Paper Series 1185, European Central Bank.
    75. Ohtsuka, Yoshihiro & Oga, Takashi & Kakamu, Kazuhiko, 2010. "Forecasting electricity demand in Japan: A Bayesian spatial autoregressive ARMA approach," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2721-2735, November.
    76. Piergiorgio Alessandri & Haroon Mumtaz, 2017. "Online Appendix to "Financial conditions and density forecasts for US output and inflation"," Online Appendices 14-103, Review of Economic Dynamics.
    77. Del Negro, Marco & Hasegawa, Raiden B. & Schorfheide, Frank, 2016. "Dynamic prediction pools: An investigation of financial frictions and forecasting performance," Journal of Econometrics, Elsevier, vol. 192(2), pages 391-405.
    78. Davide Pettenuzzo & Antonio Gargano & Allan Timmermann, 2014. "Bond Return Predictability: Economic Value and Links to the Macroeconomy," Working Papers 75R, Brandeis University, Department of Economics and International Business School, revised Jul 2016.
    79. Alessandra Canepa & Emilio Zanetti Chini & Huthaifa Alqaralleh, 2022. "Global Cities and Local Challenges: Booms and Busts in the London Real Estate Market," The Journal of Real Estate Finance and Economics, Springer, vol. 64(1), pages 1-29, January.
    80. P. Gorgi & Siem Jan (S.J.) Koopman & R. Lit, 2018. "The analysis and forecasting of ATP tennis matches using a high-dimensional dynamic model," Tinbergen Institute Discussion Papers 18-009/III, Tinbergen Institute.
    81. A. Ford Ramsey & Yong Liu, 2023. "Linear pooling of potentially related density forecasts in crop insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 90(3), pages 769-788, September.
    82. Knut Are Aastveit & Karsten R. Gerdrup & Anne Sofie Jore & Leif Anders Thorsrud, 2014. "Nowcasting GDP in Real Time: A Density Combination Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(1), pages 48-68, January.
    83. Pettenuzzo, Davide & Timmermann, Allan & Valkanov, Rossen, 2016. "A MIDAS approach to modeling first and second moment dynamics," Journal of Econometrics, Elsevier, vol. 193(2), pages 315-334.
    84. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2014. "Marginalized predictive likelihood comparisons of linear Gaussian state-space models with applications to DSGE, DSGEVAR, and VAR models," CFS Working Paper Series 478, Center for Financial Studies (CFS).
    85. Geweke, John & Amisano, Gianni, 2010. "Comparing and evaluating Bayesian predictive distributions of asset returns," International Journal of Forecasting, Elsevier, vol. 26(2), pages 216-230, April.
    86. Edward S. Knotek & Saeed Zaman, 2020. "Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach," Working Papers 20-31, Federal Reserve Bank of Cleveland.
    87. Steel, Mark F. J., 2017. "Model Averaging and its Use in Economics," MPRA Paper 81568, University Library of Munich, Germany.
    88. Fabio Busetti, 2014. "Quantile aggregation of density forecasts," Temi di discussione (Economic working papers) 979, Bank of Italy, Economic Research and International Relations Area.
    89. Paolo Gorgi & Siem Jan (S.J.) Koopman & Mengheng Li, 2018. "Forecasting economic time series using score-driven dynamic models with mixed-data sampling," Tinbergen Institute Discussion Papers 18-026/III, Tinbergen Institute.
    90. Martin Feldkircher & Nico Hauzenberger, 2019. "How useful are time-varying parameter models for forecasting economic growth in CESEE?," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q1/19, pages 29-48.
    91. Szabolcs Deák & Paul Levine & Afrasiab Mirza & Joseph Pearlman, 2019. "Designing Robust Monetary Policy Using Prediction Pools," School of Economics Discussion Papers 1219, School of Economics, University of Surrey.
    92. Carlos Carvalho & Jared D. Fisher & Davide Pettenuzzo, 2018. "Optimal Asset Allocation with Multivariate Bayesian Dynamic Linear Models," Working Papers 123, Brandeis University, Department of Economics and International Business School.
    93. Thompson, Ryan & Qian, Yilin & Vasnev, Andrey L., 2024. "Flexible global forecast combinations," Omega, Elsevier, vol. 126(C).
    94. Luca Onorante & Adrian E. Raftery, 2014. "Dynamic Model Averaging in Large Model Spaces Using Dynamic Occam's Window," Papers 1410.7799, arXiv.org.
    95. Tony Chernis & Gary Koop & Emily Tallman & Mike West, 2024. "Decision Synthesis in Monetary Policy," Staff Working Papers 24-30, Bank of Canada.
    96. Pierre Guérin & Danilo Leiva-Leon, 2017. "Model averaging in markov-switching models: predicting national recessions with regional data," Working Papers 1727, Banco de España.
    97. Jarociński, Marek & Maćkowiak, Bartosz, 2013. "Granger-causal-priority and choice of variables in vector autoregressions," Working Paper Series 1600, European Central Bank.
    98. Panayotis Michaelides & Mike Tsionas & Panos Xidonas, 2020. "A Bayesian Signals Approach for the Detection of Crises," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 551-585, September.
    99. Daniel F. Waggoner & Tao Zha, 2012. "Confronting Model Misspecification in Macroeconomics," NBER Working Papers 17791, National Bureau of Economic Research, Inc.
    100. Mengheng Li & Siem Jan Koopman, 2021. "Unobserved components with stochastic volatility: Simulation‐based estimation and signal extraction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 614-627, August.
    101. Danilo Leiva‐León & Gabriel Perez Quiros & Eyno Rots, 2024. "Real‐time weakness of the global economy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 813-832, August.
    102. Roberto Leon-Gonzalez & Blessings Majon, 2024. "Exact Likelihood for Inverse Gamma Stochastic Volatility Models," GRIPS Discussion Papers 24-03, National Graduate Institute for Policy Studies.
    103. Anthony Garratt & James Mitchell & Shaun P. Vahey, 2011. "Measuring Output Gap Nowcast Uncertainty," CAMA Working Papers 2011-16, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    104. Yusupova, Alisa & Pavlidis, Nicos G. & Pavlidis, Efthymios G., 2023. "Dynamic linear models with adaptive discounting," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1925-1944.
    105. Francisco (F.) Blasques & Paolo Gorgi & Siem Jan (S.J.) Koopman, 2017. "Accelerating GARCH and Score-Driven Models: Optimality, Estimation and Forecasting," Tinbergen Institute Discussion Papers 17-059/III, Tinbergen Institute.
    106. Michał Rubaszek & Marcin Kolasa, 2013. "Forecasting with DSGE models with financial frictions," EcoMod2013 5100, EcoMod.
    107. Pauwels, Laurent & Radchenko, Peter & Vasnev, Andrey, 2019. "Higher Moment Constraints for Predictive Density Combinations," Working Papers BAWP-2019-01, University of Sydney Business School, Discipline of Business Analytics.
    108. Joshua C.C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2018. "Composite likelihood methods for large Bayesian VARs with stochastic volatility," CAMA Working Papers 2018-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    109. Peter McAdam & Anders Warne, 2024. "Density forecast combinations: The real‐time dimension," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1153-1172, August.
    110. Anne Opschoor & Dick van Dijk & Michel van der Wel, 2014. "Improving Density Forecasts and Value-at-Risk Estimates by Combining Densities," Tinbergen Institute Discussion Papers 14-090/III, Tinbergen Institute.
    111. Roberto Gómez‐Cram, 2022. "Late to Recessions: Stocks and the Business Cycle," Journal of Finance, American Finance Association, vol. 77(2), pages 923-966, April.
    112. Gael M. Martin & Rub'en Loaiza-Maya & David T. Frazier & Worapree Maneesoonthorn & Andr'es Ram'irez Hassan, 2020. "Optimal probabilistic forecasts: When do they work?," Papers 2009.09592, arXiv.org.
    113. Chung, Tsz-Kin & Iiboshi, Hirokuni, 2015. "Prediction of Term Structure with Potentially Misspecified Macro-Finance Models near the Zero Lower Bound," MPRA Paper 85709, University Library of Munich, Germany.
    114. Beckmann, Joscha & Schüssler, Rainer, 2016. "Forecasting exchange rates under parameter and model uncertainty," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 267-288.
    115. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    116. Pauwels, Laurent L. & Vasnev, Andrey L., 2016. "A note on the estimation of optimal weights for density forecast combinations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 391-397.
    117. Di Fonzo, Tommaso & Girolimetto, Daniele, 2024. "Forecast combination-based forecast reconciliation: Insights and extensions," International Journal of Forecasting, Elsevier, vol. 40(2), pages 490-514.
    118. Ruben Loaiza‐Maya & Gael M. Martin & David T. Frazier, 2021. "Focused Bayesian prediction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 517-543, August.
    119. Kenichiro McAlinn, 2021. "Mixed‐frequency Bayesian predictive synthesis for economic nowcasting," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1143-1163, November.
    120. Paolo Gorgi & Siem Jan Koopman, 2020. "Beta observation-driven models with exogenous regressors: a joint analysis of realized correlation and leverage effects," Tinbergen Institute Discussion Papers 20-004/III, Tinbergen Institute.
    121. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2018. "Quantile forecast combination using stochastic dominance," Empirical Economics, Springer, vol. 55(4), pages 1717-1755, December.
    122. Trapero, Juan R. & Cardós, Manuel & Kourentzes, Nikolaos, 2019. "Quantile forecast optimal combination to enhance safety stock estimation," International Journal of Forecasting, Elsevier, vol. 35(1), pages 239-250.
    123. Conflitti, Cristina & De Mol, Christine & Giannone, Domenico, 2015. "Optimal combination of survey forecasts," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1096-1103.
    124. Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2020. "On an integer-valued stochastic intensity model for time series of counts," MPRA Paper 105406, University Library of Munich, Germany.
    125. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2020. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(531), pages 1092-1110, July.
    126. Ciccarelli, Matteo & Darracq Pariès, Matthieu & Priftis, Romanos & Angelini, Elena & Bańbura, Marta & Bokan, Nikola & Fagan, Gabriel & Gumiel, José Emilio & Kornprobst, Antoine & Lalik, Magdalena & Mo, 2024. "ECB macroeconometric models for forecasting and policy analysis," Occasional Paper Series 344, European Central Bank.
    127. Fabian Krüger & Ingmar Nolte, 2011. "Disagreement, Uncertainty and the True Predictive Density," Working Paper Series of the Department of Economics, University of Konstanz 2011-43, Department of Economics, University of Konstanz.
    128. Tsionas, Mike G., 2021. "Optimal combinations of stochastic frontier and data envelopment analysis models," European Journal of Operational Research, Elsevier, vol. 294(2), pages 790-800.
    129. Roberto Casarin & Federico Bassetti & Francesco Ravazzolo, 2015. "Bayesian Nonparametric Calibration and Combination of Predictive Distributions," Working Papers 2015:04, Department of Economics, University of Venice "Ca' Foscari".
    130. Hauzenberger, Niko & Huber, Florian & Klieber, Karin, 2023. "Real-time inflation forecasting using non-linear dimension reduction techniques," International Journal of Forecasting, Elsevier, vol. 39(2), pages 901-921.
    131. McAdam, Peter & Warne, Anders, 2018. "Euro area real-time density forecasting with financial or labor market frictions," Working Paper Series 2140, European Central Bank.
    132. Christian Kascha & Francesco Ravazzolo, 2008. "Combining inflation density forecasts," Working Paper 2008/22, Norges Bank.
    133. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal Portfolio Choice under Decision-Based Model Combinations," Working Papers 80, Brandeis University, Department of Economics and International Business School.
    134. Geoff Kenny & Thomas Kostka & Federico Masera, 2011. "How Informative are the Subjective Density Forecasts of Macroeconomists?," CESifo Working Paper Series 3671, CESifo.
    135. Allan Timmermann, 2018. "Forecasting Methods in Finance," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 449-479, November.
    136. Petropoulos, Fotios & Spiliotis, Evangelos & Panagiotelis, Anastasios, 2023. "Model combinations through revised base rates," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1477-1492.
    137. Davide Pettenuzzo & Rossen Valkanov & Allan Timmermann, 2014. "A Bayesian MIDAS Approach to Modeling First and Second Moment Dynamics," Working Papers 76, Brandeis University, Department of Economics and International Business School.
    138. Adam Check & Jeremy Piger, 2021. "Structural Breaks in U.S. Macroeconomic Time Series: A Bayesian Model Averaging Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(8), pages 1999-2036, December.
    139. Elliott, Graham & Gargano, Antonio & Timmermann, Allan, 2013. "Complete subset regressions," University of California at San Diego, Economics Working Paper Series qt1st3n7z7, Department of Economics, UC San Diego.
    140. Feng Li & Mattias Villani, 2013. "Efficient Bayesian Multivariate Surface Regression," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(4), pages 706-723, December.
    141. Emilio Zanetti Chini, 2018. "Forecasting dynamically asymmetric fluctuations of the U.S. business cycle," CREATES Research Papers 2018-13, Department of Economics and Business Economics, Aarhus University.
    142. Timmermann, Allan & Pettenuzzo, Davide, 2016. "Forecasting Macroeconomic Variables under Model Instability," CEPR Discussion Papers 11355, C.E.P.R. Discussion Papers.
    143. Matteo Mogliani & Anna Simoni, 2024. "Bayesian Bi-level Sparse Group Regressions for Macroeconomic Density Forecasting," Papers 2404.02671, arXiv.org, revised Nov 2024.
    144. Angelini, Giovanni & Gorgi, Paolo, 2018. "DSGE Models with observation-driven time-varying volatility," Economics Letters, Elsevier, vol. 171(C), pages 169-171.
    145. Pauwels, Laurent, 2019. "Predicting China’s Monetary Policy with Forecast Combinations," Working Papers BAWP-2019-07, University of Sydney Business School, Discipline of Business Analytics.
    146. Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
    147. Roberto Casarin & Fabrizio Leisen & German Molina & Enrique Ter Horst, 2014. "A Bayesian Beta Markov Random Field calibration of the term structure of implied risk neutral densities," Working Papers 2014:22, Department of Economics, University of Venice "Ca' Foscari".
    148. George Papadopoulos & Savas Papadopoulos & Thomas Sager, 2016. "Credit risk stress testing for EU15 banks: a model combination approach," Working Papers 203, Bank of Greece.
    149. Knut Are Aastveit & James Mitchell & Francesco Ravazzolo & Herman van Dijk, 2018. "The Evolution of Forecast Density Combinations in Economics," Tinbergen Institute Discussion Papers 18-069/III, Tinbergen Institute.
    150. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
    151. Enrique Moral-Benito, 2015. "Model Averaging In Economics: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 46-75, February.
    152. Alessandra Canepa, & Karanasos, Menelaos & Paraskevopoulos, Athanasios & Chini, Emilio Zanetti, 2022. "Forecasting Ination: A GARCH-in-Mean-Level Model with Time Varying Predictability," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202212, University of Turin.
    153. Mike G. Tsionas, 2023. "Linex and double-linex regression for parameter estimation and forecasting," Annals of Operations Research, Springer, vol. 323(1), pages 229-245, April.
    154. Ard Reijer & Andreas Johansson, 2019. "Nowcasting Swedish GDP with a large and unbalanced data set," Empirical Economics, Springer, vol. 57(4), pages 1351-1373, October.
    155. Ho, Paul & Lubik, Thomas A. & Matthes, Christian, 2024. "Averaging impulse responses using prediction pools," Journal of Monetary Economics, Elsevier, vol. 146(C).
    156. Knüppel, Malte & Krüger, Fabian, 2017. "Forecast Uncertainty, Disagreement, and Linear Pools of Density Forecasts," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168294, Verein für Socialpolitik / German Economic Association.
    157. Gospodinov, Nikolay & Maasoumi, Esfandiar, 2021. "Generalized aggregation of misspecified models: With an application to asset pricing," Journal of Econometrics, Elsevier, vol. 222(1), pages 451-467.
    158. Chen, Yizhong & He, Li & Li, Jing & Cheng, Xi & Lu, Hongwei, 2016. "An inexact bi-level simulation–optimization model for conjunctive regional renewable energy planning and air pollution control for electric power generation systems," Applied Energy, Elsevier, vol. 183(C), pages 969-983.
    159. Saurabh Bansal & Genaro J. Gutierrez, 2020. "Estimating Uncertainties Using Judgmental Forecasts with Expert Heterogeneity," Operations Research, INFORMS, vol. 68(2), pages 363-380, March.
    160. Boriss Siliverstovs, 2013. "Do business tendency surveys help in forecasting employment?: A real-time evidence for Switzerland," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 129-151.
    161. Aleksandra Nocoń, 2020. "Sustainable Approach to the Normalization Process of the UK’s Monetary Policy," Sustainability, MDPI, vol. 12(21), pages 1-14, November.
    162. Mike Tsionas & Christopher F. Parmeter & Valentin Zelenyuk, 2021. "Bridging the Divide? Bayesian Artificial Neural Networks for Frontier Efficiency Analysis," CEPA Working Papers Series WP082021, School of Economics, University of Queensland, Australia.
    163. James Morley, 2014. "Measuring economic slack in Asia and the Pacific," BIS Papers chapters, in: Bank for International Settlements (ed.), Globalisation, inflation and monetary policy in Asia and the Pacific, volume 77, pages 35-50, Bank for International Settlements.
    164. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2013. "Predictive likelihood comparisons with DSGE and DSGE-VAR models," Working Paper Series 1536, European Central Bank.
    165. Nikolay Gospodinov & Esfandiar Maasoumi, 2017. "General Aggregation of Misspecified Asset Pricing Models," FRB Atlanta Working Paper 2017-10, Federal Reserve Bank of Atlanta.
    166. K=osaku Takanashi & Kenichiro McAlinn, 2019. "Equivariant online predictions of non-stationary time series," Papers 1911.08662, arXiv.org, revised Jun 2023.
    167. Tsionas, Mike G., 2021. "Bayesian forecasting with the structural damped trend model," International Journal of Production Economics, Elsevier, vol. 234(C).
    168. di Mauro, Filippo & Fornari, Fabio & Mannucci, Dario, 2011. "Stock market firm-level information and real economic activity," Working Paper Series 1366, European Central Bank.
    169. Li, Bing & Pei, Pei & Tan, Fei, 2021. "Financial distress and fiscal inflation," Journal of Macroeconomics, Elsevier, vol. 70(C).
    170. Ryan Cumings-Menon & Minchul Shin, 2020. "Probability Forecast Combination via Entropy Regularized Wasserstein Distance," Working Papers 20-31/R, Federal Reserve Bank of Philadelphia.
    171. Anatolyev, Stanislav & Khabibullin, Renat & Prokhorov, Artem, 2014. "An algorithm for constructing high dimensional distributions from distributions of lower dimension," Economics Letters, Elsevier, vol. 123(3), pages 257-261.
    172. Deniz Igan & Thomas Lambert & Prachi Mishra & Eden Zhang, 2024. "The Politics of the Paycheck Protection Program," Working Papers 133, Ashoka University, Department of Economics.
    173. Mansoor Maitah & Daniel Toth & Elena Kuzmenko & Karel r dl & Helena Rezbov & Petra nov, 2016. "Forecast of Employment in Switzerland: The Macroeconomic View," International Journal of Economics and Financial Issues, Econjournals, vol. 6(1), pages 132-138.
    174. Roberto Casarin & Giulia Mantoan & Francesco Ravazzolo, 2016. "Bayesian Calibration of Generalized Pools of Predictive Distributions," Econometrics, MDPI, vol. 4(1), pages 1-24, March.
    175. Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2019. "Density Forecasting," BEMPS - Bozen Economics & Management Paper Series BEMPS59, Faculty of Economics and Management at the Free University of Bozen.
    176. Paolo Vidoni, 2018. "A note on predictive densities based on composite likelihood methods," METRON, Springer;Sapienza Università di Roma, vol. 76(1), pages 31-48, April.
    177. Loria, Francesca & Matthes, Christian & Wang, Mu-Chun, 2021. "Economic theories and macroeconomic reality," Discussion Papers 56/2021, Deutsche Bundesbank.
    178. Caldeira, João F. & Moura, Guilherme V. & Santos, André A.P., 2016. "Predicting the yield curve using forecast combinations," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 79-98.
    179. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
    180. Andrés Ramírez-Hassan, 2020. "Dynamic variable selection in dynamic logistic regression: an application to Internet subscription," Empirical Economics, Springer, vol. 59(2), pages 909-932, August.
    181. Thorey, J. & Chaussin, C. & Mallet, V., 2018. "Ensemble forecast of photovoltaic power with online CRPS learning," International Journal of Forecasting, Elsevier, vol. 34(4), pages 762-773.
    182. Iiboshi, Hirokuni, 2016. "A multiple DSGE-VAR approach: Priors from a combination of DSGE models and evidence from Japan," Japan and the World Economy, Elsevier, vol. 40(C), pages 1-8.
    183. Giovanni Angelini & Paolo Gorgi, 2018. "DSGE Models with Observation-Driven Time-Varying parameters," Tinbergen Institute Discussion Papers 18-030/III, Tinbergen Institute.
    184. Timmermann, Allan, 2018. "Forecasting Methods in Finance," CEPR Discussion Papers 12692, C.E.P.R. Discussion Papers.
    185. Chin, Kuo-Hsuan & Li, Xue, 2019. "Bayesian forecast combination in VAR-DSGE models," Journal of Macroeconomics, Elsevier, vol. 59(C), pages 278-298.
    186. Wang, Shengjie & Kang, Yanfei & Petropoulos, Fotios, 2024. "Combining probabilistic forecasts of intermittent demand," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1038-1048.
    187. Michael S. O’Doherty & N. E. Savin & Ashish Tiwari, 2016. "Evaluating Hedge Funds with Pooled Benchmarks," Management Science, INFORMS, vol. 62(1), pages 69-89, January.
    188. Wada, Tatsuma, 2022. "Out-of-sample forecasting of foreign exchange rates: The band spectral regression and LASSO," Journal of International Money and Finance, Elsevier, vol. 128(C).
    189. Li, Yong & Yu, Jun & Zeng, Tao, 2020. "Deviance information criterion for latent variable models and misspecified models," Journal of Econometrics, Elsevier, vol. 216(2), pages 450-493.
    190. Paolo Vidoni, 2021. "Boosting multiplicative model combination," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(3), pages 761-789, September.
    191. Gelain, Paolo & Iskrev, Nikolay & J. Lansing, Kevin & Mendicino, Caterina, 2019. "Inflation dynamics and adaptive expectations in an estimated DSGE model," Journal of Macroeconomics, Elsevier, vol. 59(C), pages 258-277.
    192. Joscha Beckmann & Rainer Schüssler, 2014. "Forecasting Equity Premia using Bayesian Dynamic Model Averaging," CQE Working Papers 2914, Center for Quantitative Economics (CQE), University of Muenster.
    193. Doron Avramov & Si Cheng & Lior Metzker & Stefan Voigt, 2023. "Integrating Factor Models," Journal of Finance, American Finance Association, vol. 78(3), pages 1593-1646, June.
    194. Dimitrakopoulos, Stefanos & Tsionas, Mike, 2019. "Ordinal-response GARCH models for transaction data: A forecasting exercise," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1273-1287.
    195. Hasumi, Ryo & Iiboshi, Hirokuni & Matsumae, Tatsuyoshi & Nakamura, Daisuke, 2019. "Does a financial accelerator improve forecasts during financial crises? Evidence from Japan with prediction-pooling methods," Journal of Asian Economics, Elsevier, vol. 60(C), pages 45-68.
    196. Bernaciak, Dawid & Griffin, Jim E., 2024. "A loss discounting framework for model averaging and selection in time series models," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1721-1733.
    197. Blasques, Francisco & van Brummelen, Janneke & Gorgi, Paolo & Koopman, Siem Jan, 2024. "Maximum Likelihood Estimation for Non-Stationary Location Models with Mixture of Normal Distributions," Journal of Econometrics, Elsevier, vol. 238(1).
    198. McAlinn, Kenichiro & West, Mike, 2019. "Dynamic Bayesian predictive synthesis in time series forecasting," Journal of Econometrics, Elsevier, vol. 210(1), pages 155-169.
    199. Dimitrakopoulos, Stefanos & Tsionas, Mike G. & Aknouche, Abdelhakim, 2020. "Ordinal-response models for irregularly spaced transactions: A forecasting exercise," MPRA Paper 103250, University Library of Munich, Germany, revised 01 Oct 2020.
    200. Markku Lanne & Jani Luoto, 2018. "Data†Driven Identification Constraints for DSGE Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(2), pages 236-258, April.
    201. Gergely Akos Ganics, 2017. "Optimal density forecast combinations," Working Papers 1751, Banco de España.
    202. Hasumi, Ryo & Iiboshi, Hirokuni & Matsumae, Tatsuyoshi & Nakamura, Daisuke, 2018. "Does a financial accelerator improve forecasts during financial crises?: Evidence from Japan with Prediction Pool Methods," MPRA Paper 85523, University Library of Munich, Germany.
    203. Roberto Casarin & Domenico Sartore & Marco Tronzano, 2018. "A Bayesian Markov-Switching Correlation Model for Contagion Analysis on Exchange Rate Markets," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 101-114, January.

  11. Gianni Amisano & Roberto Casarin, 2008. "Particle Filters for Markov-Switching Stochastic-Correlation Models," Working Papers 0814, University of Brescia, Department of Economics.

    Cited by:

    1. Del Boca, Alessandra & Fratianni, Michele & Spinelli, Franco & Trecroci, Carmine, 2010. "The Phillips curve and the Italian lira, 1861-1998," The North American Journal of Economics and Finance, Elsevier, vol. 21(2), pages 182-197, August.
    2. Alessandro Fedele & Raffaele Miniaci, 2010. "Do Social Enterprises Finance Their Investments Differently from For-profit Firms? The Case of Social Residential Services in Italy," Journal of Social Entrepreneurship, Taylor & Francis Journals, vol. 1(2), pages 174-189, October.
    3. Alessandro Fedele & Paolo Panteghini & Sergio Vergalli, 2009. "Optimal investment and financial strategies under tax rate uncertainty," Working Papers 0912, University of Brescia, Department of Economics.
    4. Francesco Menoncin & Paolo Panteghini, 2009. "Retrospective Capital Gains taxation in the real world," Working Papers 0910, University of Brescia, Department of Economics.
    5. Alessandro Fedele & Francesco Liucci & Andrea Mantovani, 2009. "Credit availability in the crisis: the European investment bank group," Working Papers 0913, University of Brescia, Department of Economics.
    6. Martin Meier & Enrico Minelli & Herakles Polemarchakis, 2009. "Competitive Markets with Private Information on Both Sides," Working Papers 0917, University of Brescia, Department of Economics.
    7. Bisin, A. & Geanakoplos, J.D. & Gottardi, P. & Minelli, E. & Polemarchakis, H., 2011. "Markets and contracts," Journal of Mathematical Economics, Elsevier, vol. 47(3), pages 279-288.
    8. Hafner, C.M. & Manner, H., 2008. "Dynamic stochastic copula models: estimation, inference and applications," Research Memorandum 043, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    9. Rosella Levaggi & Francesco Menoncin, 2009. "Decentralized provision of merit and impure public goods," Working Papers 0909, University of Brescia, Department of Economics.
    10. Monica Billio & Roberto Casarin, 2010. "Bayesian Estimation of Stochastic-Transition Markov-Switching Models for Business Cycle Analysis," Working Papers 1002, University of Brescia, Department of Economics.
    11. Roberto Casarin & Marco Tronzano & Domenico Sartore, 2013. "Bayesian Markov Switching Stochastic Correlation Models," Working Papers 2013:11, Department of Economics, University of Venice "Ca' Foscari".

  12. Amisano, Gianni & Geweke, John, 2008. "Comparing and evaluating Bayesian predictive distributions of assets returns," Working Paper Series 969, European Central Bank.

    Cited by:

    1. Joseph P. Byrne & Dimitris Korobilis & Pinho J. Ribeiro, 2014. "On the Sources of Uncertainty in Exchange Rate Predictability," Working Papers 2014_16, Business School - Economics, University of Glasgow.
    2. Koki, Constandina & Leonardos, Stefanos & Piliouras, Georgios, 2022. "Exploring the predictability of cryptocurrencies via Bayesian hidden Markov models," Research in International Business and Finance, Elsevier, vol. 59(C).
    3. N. Fawcett & G. Kapetanios & J. Mitchell & S. Price, 2014. "Generalised Density Forecast Combinations," CAMA Working Papers 2014-24, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Andrea Monticini & Francesco Ravazzolo, 2011. "Forecasting the intraday market price of money," Working Paper 2011/06, Norges Bank.
    5. Allayioti, Anastasia & Venditti, Fabrizio, 2024. "The role of comovement and time-varying dynamics in forecasting commodity prices," Working Paper Series 2901, European Central Bank.
    6. Jason Ng & Catherine S. Forbes & Gael M. Martin & Brendan P.M. McCabe, 2011. "Non-Parametric Estimation of Forecast Distributions in Non-Gaussian, Non-linear State Space Models," Monash Econometrics and Business Statistics Working Papers 11/11, Monash University, Department of Econometrics and Business Statistics.
    7. Zhang, Yixiao & Yu, Cindy L. & Li, Haitao, 2022. "Nowcasting GDP Using Dynamic Factor Model with Unknown Number of Factors and Stochastic Volatility: A Bayesian Approach," Econometrics and Statistics, Elsevier, vol. 24(C), pages 75-93.
    8. Maheu, John & Song, Yong, 2012. "A new structural break model with application to Canadian inflation forecasting," MPRA Paper 36870, University Library of Munich, Germany.
    9. Li, Li & Kang, Yanfei & Li, Feng, 2023. "Bayesian forecast combination using time-varying features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1287-1302.
    10. Christian Hotz‐Behofsits & Florian Huber & Thomas Otto Zörner, 2018. "Predicting crypto‐currencies using sparse non‐Gaussian state space models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(6), pages 627-640, September.
    11. Hernández, Juan R., 2020. "Covered Interest Parity: A Stochastic Volatility Approach to Estimate the Neutral Band," MPRA Paper 100744, University Library of Munich, Germany.
    12. Gianfreda, Angelica & Ravazzolo, Francesco & Rossini, Luca, 2020. "Comparing the forecasting performances of linear models for electricity prices with high RES penetration," International Journal of Forecasting, Elsevier, vol. 36(3), pages 974-986.
    13. Holzmann, Hajo & Schwaiger, Florian, 2016. "Testing for the number of states in hidden Markov models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 318-330.
    14. KOROBILIS, Dimitris, 2011. "Hierarchical shrinkage priors for dynamic regressions with many predictors," LIDAM Discussion Papers CORE 2011021, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2012. "Time-varying Combinations of Predictive Densities using Nonlinear Filtering," Tinbergen Institute Discussion Papers 12-118/III, Tinbergen Institute.
    16. Del Brio, Esther B. & Ñíguez, Trino-Manuel & Perote, Javier, 2011. "Multivariate semi-nonparametric distributions with dynamic conditional correlations," International Journal of Forecasting, Elsevier, vol. 27(2), pages 347-364, April.
    17. Ardia, David & Lennart, Hoogerheide & Nienke, Corré, 2011. "Stock index returns’ density prediction using GARCH models: Frequentist or Bayesian estimation?," MPRA Paper 28259, University Library of Munich, Germany.
    18. Worapree Maneesoonthorn & Catherine S. Forbes & Gael M. Martin, 2013. "Inference on Self-Exciting Jumps in Prices and Volatility using High Frequency Measures," Monash Econometrics and Business Statistics Working Papers 28/13, Monash University, Department of Econometrics and Business Statistics.
    19. Mike G. Tsionas, 2016. "Alternatives to large VAR, VARMA and multivariate stochastic volatility models," Working Papers 217, Bank of Greece.
    20. Çakmaklı, Cem & Paap, Richard & van Dijk, Dick, 2013. "Measuring and predicting heterogeneous recessions," Journal of Economic Dynamics and Control, Elsevier, vol. 37(11), pages 2195-2216.
    21. Benjamin K. Johannsen & Elmar Mertens, 2016. "A Time Series Model of Interest Rates With the Effective Lower Bound," Finance and Economics Discussion Series 2016-033, Board of Governors of the Federal Reserve System (U.S.).
    22. Roberto Leon-Gonzalez & Blessings Majon, 2024. "Approximate Factor Models with a Common Multiplicative Factor for Stochastic Volatility," GRIPS Discussion Papers 24-02, National Graduate Institute for Policy Studies.
    23. P. Byrne, Joseph & Cao, Shuo & Korobilis, Dimitris, 2015. "Term Structure Dynamics, Macro-Finance Factors and Model Uncertainty," SIRE Discussion Papers 2015-71, Scottish Institute for Research in Economics (SIRE).
    24. Markku Lanne & Jani Luoto, 2015. "Estimation of DSGE Models under Diffuse Priors and Data-Driven Identification Constraints," CREATES Research Papers 2015-37, Department of Economics and Business Economics, Aarhus University.
    25. Angela Abbate & Massimiliano Marcellino, 2018. "Point, interval and density forecasts of exchange rates with time varying parameter models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(1), pages 155-179, January.
    26. Tim Oliver Berg, 2015. "Forecast Accuracy of a BVAR under Alternative Specifications of the Zero Lower Bound," ifo Working Paper Series 203, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    27. Nalan Basturk & Cem Cakmakli & Pinar Ceyhan & Herman K. van Dijk, 2013. "Posterior-Predictive Evidence on US Inflation using Phillips Curve Models with Non-Filtered Time Series," Tinbergen Institute Discussion Papers 13-011/III, Tinbergen Institute.
    28. Dubiel-Teleszynski, Tomasz & Kalogeropoulos, Konstantinos & Karouzakis, Nikolaos, 2024. "Sequential learning and economic benefits from dynamic term structure models," LSE Research Online Documents on Economics 123659, London School of Economics and Political Science, LSE Library.
    29. Laura Liu, 2020. "Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective," CAEPR Working Papers 2020-003, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    30. Bitto, Angela & Frühwirth-Schnatter, Sylvia, 2019. "Achieving shrinkage in a time-varying parameter model framework," Journal of Econometrics, Elsevier, vol. 210(1), pages 75-97.
    31. Pelin Ilbas & Øistein Røisland & Tommy Sveen, 2013. "The Influence of the Taylor rule on US monetary policy," Working Paper Research 241, National Bank of Belgium.
    32. Elnura Baiaman kyzy & Roberto Leon-Gonzalez, 2024. "Estimation of Nonlinear DSGE Models Through Laplace Based Solutions," GRIPS Discussion Papers 24-06, National Graduate Institute for Policy Studies.
    33. Koop, Gary & Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Bayesian compressed vector autoregressions," Journal of Econometrics, Elsevier, vol. 210(1), pages 135-154.
    34. David Harris & Gael M. Martin & Indeewara Perera & Don S. Poskitt, 2017. "Construction and visualization of optimal confidence sets for frequentist distributional forecasts," Monash Econometrics and Business Statistics Working Papers 9/17, Monash University, Department of Econometrics and Business Statistics.
    35. Carriero, Andrea & Mumtaz, Haroon & Theophilopoulou, Angeliki, 2015. "Macroeconomic information, structural change, and the prediction of fiscal aggregates," International Journal of Forecasting, Elsevier, vol. 31(2), pages 325-348.
    36. Karlsson, Sune & Mazur, Stepan & Nguyen, Hoang, 2021. "Vector autoregression models with skewness and heavy tails," Working Papers 2021:8, Örebro University, School of Business.
    37. Abdymomunov, Azamat & Kang, Kyu Ho & Kim, Ki Jeong, 2016. "Can credit spreads help predict a yield curve?," Journal of International Money and Finance, Elsevier, vol. 64(C), pages 39-61.
    38. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "No-Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," Working Papers 20-27, Federal Reserve Bank of Cleveland.
    39. Song, Yong & Shi, Shuping, 2012. "Identifying speculative bubbles with an in finite hidden Markov model," MPRA Paper 36455, University Library of Munich, Germany.
    40. Piergiorgio Alessandri & Haroon Mumtaz, 2014. "Financial conditions and density forecasts for US output and inflation," CReMFi Discussion Papers 1, CReMFi, School of Economics and Finance, QMUL.
    41. Mark J Jensen & John M Maheu, 2012. "Estimating a Semiparametric Asymmetric Stochastic Volatility Model with a Dirichlet Process Mixture," Working Papers tecipa-453, University of Toronto, Department of Economics.
    42. Gianni Amisano & John Geweke, 2017. "Prediction Using Several Macroeconomic Models," The Review of Economics and Statistics, MIT Press, vol. 99(5), pages 912-925, December.
    43. Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2019. "Forecasting daily electricity prices with monthly macroeconomic variables," Working Paper Series 2250, European Central Bank.
    44. Tim Oliver Berg & Steffen Henzel, 2014. "Point and Density Forecasts for the Euro Area Using Bayesian VARs," CESifo Working Paper Series 4711, CESifo.
    45. Niko Hauzenberger & Florian Huber, 2020. "Model instability in predictive exchange rate regressions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 168-186, March.
    46. Fabrizio Leisen & Luca Rossini & Cristiano Villa, 2020. "Loss-based approach to two-piece location-scale distributions with applications to dependent data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(2), pages 309-333, June.
    47. Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2018. "Combined Density Nowcasting in an Uncertain Economic Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 131-145, January.
    48. Todd E. Clark & Taeyoung Doh, 2011. "A Bayesian evaluation of alternative models of trend inflation," Research Working Paper RWP 11-16, Federal Reserve Bank of Kansas City.
    49. Deschamps, P., 2015. "Alternative Formulation of the Leverage Effect in a Stochastic Volatility Model with Asymmetric Heavy-Tailed Errors," LIDAM Discussion Papers CORE 2015020, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    50. Roberto Casarin, 2014. "A Note on Tractable State-Space Model for Symmetric Positive-Definite Matrices," Working Papers 2014:23, Department of Economics, University of Venice "Ca' Foscari".
    51. Panagiotidis, Theodore & Papapanagiotou, Georgios & Stengos, Thanasis, 2022. "On the volatility of cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 62(C).
    52. Markku Lanne & Jani Luoto, 2014. "Noncausal Bayesian Vector Autoregression," CREATES Research Papers 2014-07, Department of Economics and Business Economics, Aarhus University.
    53. Rangan Gupta & Florian Huber & Philipp Piribauer, 2018. "Predicting International Equity Returns: Evidence from Time-Varying Parameter Vector Autoregressive Models," Working Papers 201826, University of Pretoria, Department of Economics.
    54. Florian Huber & Tamás Krisztin & Philipp Piribauer, 2017. "Forecasting Global Equity Indices Using Large Bayesian Vars," Bulletin of Economic Research, Wiley Blackwell, vol. 69(3), pages 288-308, July.
    55. Florian Huber & Gregor Kastner & Martin Feldkircher, 2016. "Should I stay or should I go? Bayesian inference in the threshold time varying parameter (TTVP) model," Department of Economics Working Papers wuwp235, Vienna University of Economics and Business, Department of Economics.
    56. Florian Huber, 2017. "Structural breaks in Taylor rule based exchange rate models - Evidence from threshold time varying parameter models," Department of Economics Working Papers wuwp244, Vienna University of Economics and Business, Department of Economics.
    57. Tim Oliver Berg & Steffen Henzel, 2013. "Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?," ifo Working Paper Series 155, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    58. Hoogerheide, Lennart F. & Ardia, David & Corré, Nienke, 2012. "Density prediction of stock index returns using GARCH models: Frequentist or Bayesian estimation?," Economics Letters, Elsevier, vol. 116(3), pages 322-325.
    59. Darjus Hosszejni & Gregor Kastner, 2019. "Modeling Univariate and Multivariate Stochastic Volatility in R with stochvol and factorstochvol," Papers 1906.12123, arXiv.org, revised Feb 2021.
    60. Kelly Trinh & Bo Zhang & Chenghan Hou, 2025. "Macroeconomic real‐time forecasts of univariate models with flexible error structures," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(1), pages 59-78, January.
    61. Damian Stelmasiak & Grzegorz Szafrański, 2016. "Forecasting the Polish Inflation Using Bayesian VAR Models with Seasonality," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(1), pages 21-42, March.
    62. Davidovic, Milivoje, 2021. "From pandemic to financial contagion: High-frequency risk metrics and Bayesian volatility analysis," Finance Research Letters, Elsevier, vol. 42(C).
    63. Huber, Florian & Onorante, Luca & Pfarrhofer, Michael, 2024. "Forecasting euro area inflation using a huge panel of survey expectations," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1042-1054.
    64. Gregor Kastner, 2016. "Sparse Bayesian time-varying covariance estimation in many dimensions," Papers 1608.08468, arXiv.org, revised Nov 2017.
    65. Karsten R. Gerdrup & Anne Sofie Jore & Christie Smith & Leif Anders Thorsrud, 2009. "Evaluating ensemble density combination - forecasting GDP and inflation," Working Paper 2009/19, Norges Bank.
    66. Boyuan Zhang, 2020. "Forecasting with Bayesian Grouped Random Effects in Panel Data," Papers 2007.02435, arXiv.org, revised Oct 2020.
    67. Dimitris Korobilis & Davide Pettenuzzo, 2018. "Adaptive Hierarchical Priors for High-Dimensional Vector Autoregressions," Working Paper series 18-21, Rimini Centre for Economic Analysis.
    68. O'Brien, Martin & Velasco, Sofia, 2020. "Unobserved components models with stochastic volatility for extracting trends and cycles in credit," Research Technical Papers 09/RT/20, Central Bank of Ireland.
    69. Yong Tan & Mike G. Tsionas, 2022. "Modelling sustainability efficiency in banking," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3754-3772, July.
    70. Anna Pajor & Justyna Wróblewska, 2022. "Forecasting performance of Bayesian VEC-MSF models for financial data in the presence of long-run relationships," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 427-448, September.
    71. Tsionas, Mike G., 2022. "Random and Markov switching exponential smoothing models," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    72. Catania, Leopoldo & Grassi, Stefano & Ravazzolo, Francesco, 2019. "Forecasting cryptocurrencies under model and parameter instability," International Journal of Forecasting, Elsevier, vol. 35(2), pages 485-501.
    73. Dovern, Jonas & Feldkircher, Martin & Huber, Florian, 2016. "Does joint modelling of the world economy pay off? Evaluating global forecasts from a Bayesian GVAR," Journal of Economic Dynamics and Control, Elsevier, vol. 70(C), pages 86-100.
    74. Martin Magris & Mostafa Shabani & Alexandros Iosifidis, 2022. "Bayesian Bilinear Neural Network for Predicting the Mid-price Dynamics in Limit-Order Book Markets," Papers 2203.03613, arXiv.org, revised Jan 2023.
    75. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 837-862, October.
    76. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2012. "Common Drifting Volatility in Large Bayesian VARs," CEPR Discussion Papers 8894, C.E.P.R. Discussion Papers.
    77. Florian Huber & Manfred M. Fischer & Philipp Piribauer, 2017. "The role of US based FDI flows for global output dynamics," Department of Economics Working Papers wuwp239, Vienna University of Economics and Business, Department of Economics.
    78. Piergiorgio Alessandri & Haroon Mumtaz, 2017. "Online Appendix to "Financial conditions and density forecasts for US output and inflation"," Online Appendices 14-103, Review of Economic Dynamics.
    79. Florian Huber & Michael Pfarrhofer & Philipp Piribauer, 2020. "A multi‐country dynamic factor model with stochastic volatility for euro area business cycle analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 911-926, September.
    80. Huber, Florian & Zörner, Thomas O., 2019. "Threshold cointegration in international exchange rates:A Bayesian approach," International Journal of Forecasting, Elsevier, vol. 35(2), pages 458-473.
    81. Wu, Ping, 2024. "Should I open to forecast? Implications from a multi-country unobserved components model with sparse factor stochastic volatility," International Journal of Forecasting, Elsevier, vol. 40(3), pages 903-917.
    82. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2012. "Combining predictive densities using Bayesian filtering with applications to US economic data," Working Papers 2012_16, Department of Economics, University of Venice "Ca' Foscari".
    83. Todd E. Clark & Francesco Ravazzolo, 2012. "The macroeconomic forecasting performance of autoregressive models with alternative specifications of time-varying volatility," Working Paper 2012/09, Norges Bank.
    84. Phella, Anthoulla & Gabriel, Vasco J. & Martins, Luis F., 2024. "Predicting tail risks and the evolution of temperatures," Energy Economics, Elsevier, vol. 131(C).
    85. Davide Pettenuzzo & Antonio Gargano & Allan Timmermann, 2014. "Bond Return Predictability: Economic Value and Links to the Macroeconomy," Working Papers 75R, Brandeis University, Department of Economics and International Business School, revised Jul 2016.
    86. Luiz Renato Regis de Oliveira Lima & Wagner Piazza Gaglianone, 2012. "Constructing Optimal Density Forecasts from Point Forecast Combinations," Série Textos para Discussão (Working Papers) 5, Programa de Pós-Graduação em Economia - PPGE, Universidade Federal da Paraíba.
    87. Tsionas, Mike G. & Philippas, Dionisis & Philippas, Nikolaos, 2022. "Multivariate stochastic volatility for herding detection: Evidence from the energy sector," Energy Economics, Elsevier, vol. 109(C).
    88. Pettenuzzo, Davide & Timmermann, Allan & Valkanov, Rossen, 2016. "A MIDAS approach to modeling first and second moment dynamics," Journal of Econometrics, Elsevier, vol. 193(2), pages 315-334.
    89. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2014. "Marginalized predictive likelihood comparisons of linear Gaussian state-space models with applications to DSGE, DSGEVAR, and VAR models," CFS Working Paper Series 478, Center for Financial Studies (CFS).
    90. Boyuan Zhang, 2022. "Incorporating Prior Knowledge of Latent Group Structure in Panel Data Models," Papers 2211.16714, arXiv.org, revised Oct 2023.
    91. Dimitris Korobilis., 2015. "Quantile forecasts of inflation under model uncertainty," Working Papers 2015_09, Business School - Economics, University of Glasgow.
    92. Martin Feldkircher & Nico Hauzenberger, 2019. "How useful are time-varying parameter models for forecasting economic growth in CESEE?," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q1/19, pages 29-48.
    93. Trujillo-Barrera, Andres & Pennings, Joost M.E., 2013. "Energy and Food Commodity Prices Linkage: An Examination with Mixed-Frequency Data," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150465, Agricultural and Applied Economics Association.
    94. Minchul Shin & Molin Zhong, 2013. "Does realized volatility help bond yield density prediction?," PIER Working Paper Archive 13-064, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    95. Francesco Ravazzolo & Shaun P Vahey, 2010. "Measuring Core Inflation in Australia with Disaggregate Ensembles," RBA Annual Conference Volume (Discontinued), in: Renée Fry & Callum Jones & Christopher Kent (ed.),Inflation in an Era of Relative Price Shocks, Reserve Bank of Australia.
    96. Maciej Kostrzewski & Jadwiga Kostrzewska, 2021. "The Impact of Forecasting Jumps on Forecasting Electricity Prices," Energies, MDPI, vol. 14(2), pages 1-17, January.
    97. Jensen, Mark J. & Maheu, John M., 2010. "Bayesian semiparametric stochastic volatility modeling," Journal of Econometrics, Elsevier, vol. 157(2), pages 306-316, August.
    98. Garland Durham & John Geweke, 2013. "Adaptive Sequential Posterior Simulators for Massively Parallel Computing Environments," Working Paper Series 9, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    99. M. Bernardi & L. Petrella, 2014. "Interconnected risk contributions: an heavy-tail approach to analyse US financial sectors," Papers 1401.6408, arXiv.org, revised Apr 2014.
    100. Luca Onorante & Adrian E. Raftery, 2014. "Dynamic Model Averaging in Large Model Spaces Using Dynamic Occam's Window," Papers 1410.7799, arXiv.org.
    101. Cobb, Marcus P A, 2017. "Aggregate Density Forecasting from Disaggregate Components Using Large VARs," MPRA Paper 76849, University Library of Munich, Germany.
    102. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2022. "A Flexible Predictive Density Combination for Large Financial Data Sets in Regular and Crisis Periods," Tinbergen Institute Discussion Papers 22-053/III, Tinbergen Institute.
    103. Reif Magnus, 2021. "Macroeconomic uncertainty and forecasting macroeconomic aggregates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-20, April.
    104. Panayotis Michaelides & Mike Tsionas & Panos Xidonas, 2020. "A Bayesian Signals Approach for the Detection of Crises," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 551-585, September.
    105. Jaeho Kim & Sora Chon, 2022. "Bayesian estimation of the long-run trend of the US economy," Empirical Economics, Springer, vol. 62(2), pages 461-485, February.
    106. Roberto Leon-Gonzalez & Blessings Majon, 2024. "Exact Likelihood for Inverse Gamma Stochastic Volatility Models," GRIPS Discussion Papers 24-03, National Graduate Institute for Policy Studies.
    107. Ellington, Michael, 2022. "Fat tails, serial dependence, and implied volatility index connections," European Journal of Operational Research, Elsevier, vol. 299(2), pages 768-779.
    108. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2021. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," Working Papers 21-02R, Federal Reserve Bank of Cleveland, revised 09 Aug 2021.
    109. Daniele Bianchi & Massimo Guidolin & Francesco Ravazzolo, 2015. "Macroeconomic Factors Strike Back: A Bayesian Change-Point Model of Time-Varying Risk Exposures and Premia in the U.S. Cross-Section," Working Papers 550, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    110. Pauwels, Laurent & Radchenko, Peter & Vasnev, Andrey, 2019. "Higher Moment Constraints for Predictive Density Combinations," Working Papers BAWP-2019-01, University of Sydney Business School, Discipline of Business Analytics.
    111. Mike G. Tsionas, 2016. "Alternative Bayesian compression in Vector Autoregressions and related models," Working Papers 216, Bank of Greece.
    112. Manfred M. Fischer & Niko Hauzenberger & Florian Huber & Michael Pfarrhofer, 2021. "General Bayesian time-varying parameter VARs for predicting government bond yields," Papers 2102.13393, arXiv.org.
    113. Marcus P. A. Cobb, 2020. "Aggregate density forecasting from disaggregate components using Bayesian VARs," Empirical Economics, Springer, vol. 58(1), pages 287-312, January.
    114. Juan R. Hernández, 2024. "Covered interest parity: a forecasting approach to estimate the neutral band," BIS Working Papers 1206, Bank for International Settlements.
    115. Byrne, Joseph P. & Cao, Shuo & Korobilis, Dimitris, 2017. "Forecasting the term structure of government bond yields in unstable environments," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 209-225.
    116. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    117. Huber, Florian, 2018. "Dealing with heterogeneity in panel VARs using sparse finite mixtures," Department of Economics Working Paper Series 262, WU Vienna University of Economics and Business.
    118. Michael Pfarrhofer, 2020. "Forecasts with Bayesian vector autoregressions under real time conditions," Papers 2004.04984, arXiv.org.
    119. Ardia, David & Bluteau, Keven & Boudt, Kris & Catania, Leopoldo, 2018. "Forecasting risk with Markov-switching GARCH models:A large-scale performance study," International Journal of Forecasting, Elsevier, vol. 34(4), pages 733-747.
    120. Ellis W. Tallman & Saeed Zaman, 2015. "Forecasting Inflation: Phillips Curve Effects on Services Price Measures," Working Papers (Old Series) 1519, Federal Reserve Bank of Cleveland.
    121. Deschamps, Philippe J., 2011. "Bayesian estimation of an extended local scale stochastic volatility model," Journal of Econometrics, Elsevier, vol. 162(2), pages 369-382, June.
    122. Zeyyad Mandalinci, 2015. "Forecasting Inflation in Emerging Markets: An Evaluation of Alternative Models," CReMFi Discussion Papers 3, CReMFi, School of Economics and Finance, QMUL.
    123. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman van Dijk, 2022. "A Flexible Predictive Density Combination Model for Large Financial Data Sets in Regular and Crisis Periods," Tinbergen Institute Discussion Papers 22-013/III, Tinbergen Institute.
    124. Paul J. Northrop & Nicolas Attalides & Philip Jonathan, 2017. "Cross-validatory extreme value threshold selection and uncertainty with application to ocean storm severity," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(1), pages 93-120, January.
    125. Florian Huber & Tam'as Krisztin & Michael Pfarrhofer, 2018. "A Bayesian panel VAR model to analyze the impact of climate change on high-income economies," Papers 1804.01554, arXiv.org, revised Feb 2021.
    126. Claudia Foroni & Francesco Ravazzolo & Luca Rossini, 2020. "Are low frequency macroeconomic variables important for high frequency electricity prices?," Papers 2007.13566, arXiv.org, revised Dec 2022.
    127. Karapanagiotidis, Paul, 2012. "Improving Bayesian VAR density forecasts through autoregressive Wishart Stochastic Volatility," MPRA Paper 38885, University Library of Munich, Germany.
    128. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
    129. Miescu, Mirela & Mumtaz, Haroon & Theodoridis, Konstantinos, 2024. "Non-linear Dynamics of Oil Supply News Shocks," Cardiff Economics Working Papers E2024/18, Cardiff University, Cardiff Business School, Economics Section.
    130. Antonello D'Agostino & Domenico Giannone & Michele Lenza & Michele Modugno, 2015. "Nowcasting Business Cycles: a Bayesian Approach to Dynamic Heterogeneous Factor Models," Finance and Economics Discussion Series 2015-66, Board of Governors of the Federal Reserve System (U.S.).
    131. Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman & Herman van Dijk, 2019. "Partially Censored Posterior for Robust and Efficient Risk Evaluation," Tinbergen Institute Discussion Papers 19-057/III, Tinbergen Institute.
    132. Petre Caraiani, 2014. "Do money and financial variables help forecasting output in emerging European Economies?," Empirical Economics, Springer, vol. 46(2), pages 743-763, March.
    133. Anna Kormilitsina & Sarah Zubairy, 2016. "Propagation Mechanisms for Government Spending Shocks: A Bayesian Comparison," Departmental Working Papers 1608, Southern Methodist University, Department of Economics.
    134. Gregor Kastner, 2019. "Dealing with Stochastic Volatility in Time Series Using the R Package stochvol," Papers 1906.12134, arXiv.org.
    135. Ravazzolo Francesco & Rothman Philip, 2016. "Oil-price density forecasts of US GDP," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 441-453, September.
    136. Roberto Casarin & Federico Bassetti & Francesco Ravazzolo, 2015. "Bayesian Nonparametric Calibration and Combination of Predictive Distributions," Working Papers 2015:04, Department of Economics, University of Venice "Ca' Foscari".
    137. Hong Wang & Catherine S. Forbes & Jean-Pierre Fenech & John Vaz, 2018. "The determinants of bank loan recovery rates in good times and bad - new evidence," Papers 1804.07022, arXiv.org.
    138. Hauzenberger, Niko & Huber, Florian & Klieber, Karin, 2023. "Real-time inflation forecasting using non-linear dimension reduction techniques," International Journal of Forecasting, Elsevier, vol. 39(2), pages 901-921.
    139. Anna Pajor & Justyna Wróblewska & Łukasz Kwiatkowski & Jacek Osiewalski, 2024. "Hybrid SV‐GARCH, t‐GARCH and Markov‐switching covariance structures in VEC models—Which is better from a predictive perspective?," International Statistical Review, International Statistical Institute, vol. 92(1), pages 62-86, April.
    140. George Athanasopoulos & Puwasala Gamakumara & Anastasios Panagiotelis & Rob J Hyndman & Mohamed Affan, 2019. "Hierarchical Forecasting," Monash Econometrics and Business Statistics Working Papers 2/19, Monash University, Department of Econometrics and Business Statistics.
    141. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87, May.
    142. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal Portfolio Choice under Decision-Based Model Combinations," Working Papers 80, Brandeis University, Department of Economics and International Business School.
    143. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2013. "Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 13-191/III, Tinbergen Institute.
    144. Bobeica, Elena & Hartwig, Benny, 2023. "The COVID-19 shock and challenges for inflation modelling," International Journal of Forecasting, Elsevier, vol. 39(1), pages 519-539.
    145. Niko Hauzenberger & Florian Huber & Michael Pfarrhofer & Thomas O. Zorner, 2018. "Stochastic model specification in Markov switching vector error correction models," Papers 1807.00529, arXiv.org, revised Sep 2019.
    146. Davide Pettenuzzo & Rossen Valkanov & Allan Timmermann, 2014. "A Bayesian MIDAS Approach to Modeling First and Second Moment Dynamics," Working Papers 76, Brandeis University, Department of Economics and International Business School.
    147. Chew Lian Chua & Sandy Suardi & Sarantis Tsiaplias, 2011. "Predicting Short-Term Interest Rates: Does Bayesian Model Averaging Provide Forecast Improvement?," Melbourne Institute Working Paper Series wp2011n01, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    148. Florian Huber & Gregor Kastner & Martin Feldkircher, 2019. "Should I stay or should I go? A latent threshold approach to large‐scale mixture innovation models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(5), pages 621-640, August.
    149. Laura Liu, 2017. "Density Forecasts in Panel Models: A semiparametric Bayesian Perspective," PIER Working Paper Archive 17-006, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 28 Apr 2017.
    150. Chua, Chew Lian & Suardi, Sandy & Tsiaplias, Sarantis, 2013. "Predicting short-term interest rates using Bayesian model averaging: Evidence from weekly and high frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 442-455.
    151. Consolo, Agostino & Foroni, Claudia & Martínez Hernández, Catalina, 2021. "A mixed frequency BVAR for the euro area labour market," Working Paper Series 2601, European Central Bank.
    152. Timmermann, Allan & Pettenuzzo, Davide, 2016. "Forecasting Macroeconomic Variables under Model Instability," CEPR Discussion Papers 11355, C.E.P.R. Discussion Papers.
    153. Oliver Pfante & Nils Bertschinger, 2019. "Volatility Inference And Return Dependencies In Stochastic Volatility Models," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(03), pages 1-44, May.
    154. Goldman, Elena, 2023. "Uncertainty in systemic risks rankings: Bayesian and frequentist analysis," Finance Research Letters, Elsevier, vol. 56(C).
    155. Fischer, Manfred M. & Hauzenberger, Niko & Huber, Florian & Pfarrhofer, Michael, 2022. "General Bayesian time-varying parameter VARs for modeling government bond yields," Working Papers in Regional Science 2021/01, WU Vienna University of Economics and Business.
    156. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combining Predictive Densities using Nonlinear Filtering with Applications to US Economics Data," Tinbergen Institute Discussion Papers 11-172/4, Tinbergen Institute.
    157. Florian Huber & Michael Pfarrhofer, 2020. "Dynamic shrinkage in time-varying parameter stochastic volatility in mean models," Papers 2005.06851, arXiv.org.
    158. Angela Abbate & Massimiliano Marcellino, 2017. "Macroeconomic activity and risk indicators: an unstable relationship," BAFFI CAREFIN Working Papers 1756, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    159. Boriss Siliverstovs, 2020. "Assessing nowcast accuracy of US GDP growth in real time: the role of booms and busts," Empirical Economics, Springer, vol. 58(1), pages 7-27, January.
    160. Tamás Kiss & Hoang Nguyen & Pär Österholm, 2023. "Modelling Okun’s law: Does non-Gaussianity matter?," Empirical Economics, Springer, vol. 64(5), pages 2183-2213, May.
    161. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    162. Haroon Mumtaz & Laura Sunder-Plassmann, 2017. "Non-linear effects of government spending shocks in the US. Evidence from state-level data," Working Papers 841, Queen Mary University of London, School of Economics and Finance.
    163. Federico Bassetti & Roberto Casarin & Fabrizio Leisen, 2013. "Beta-Product Dependent Pitman-Yor Processes for Bayesian Inference," Working Papers 2013:13, Department of Economics, University of Venice "Ca' Foscari".
    164. Knut Are Aastveit & James Mitchell & Francesco Ravazzolo & Herman van Dijk, 2018. "The Evolution of Forecast Density Combinations in Economics," Tinbergen Institute Discussion Papers 18-069/III, Tinbergen Institute.
    165. Li, Feng & Kang, Yanfei, 2018. "Improving forecasting performance using covariate-dependent copula models," International Journal of Forecasting, Elsevier, vol. 34(3), pages 456-476.
    166. Ilya Archakov & Peter Reinhard Hansen & Asger Lunde, 2020. "A Multivariate Realized GARCH Model," Papers 2012.02708, arXiv.org, revised Feb 2025.
    167. Maneesoonthorn, Worapree & Martin, Gael M. & Forbes, Catherine S. & Grose, Simone D., 2012. "Probabilistic forecasts of volatility and its risk premia," Journal of Econometrics, Elsevier, vol. 171(2), pages 217-236.
    168. Kang, Kyu Ho, 2015. "The predictive density simulation of the yield curve with a zero lower bound," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 51-66.
    169. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
    170. DESCHAMPS, Philippe J., 2016. "Bayesian Semiparametric Forecasts of Real Interest Rate Data," LIDAM Discussion Papers CORE 2016050, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    171. Boriss Siliverstovs, 2021. "New York FED Staff Nowcasts and Reality: What Can We Learn about the Future, the Present, and the Past?," Econometrics, MDPI, vol. 9(1), pages 1-25, March.
    172. Manfred M. Fischer & Niko Hauzenberger & Florian Huber & Michael Pfarrhofer, 2023. "General Bayesian time‐varying parameter vector autoregressions for modeling government bond yields," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(1), pages 69-87, January.
    173. Leopoldo Catania & Stefano Grassi & Francesco Ravazzolo, 2018. "Forecasting Cryptocurrencies Financial Time Series," Working Papers No 5/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    174. Agostino Consolo & Claudia Foroni & Catalina Martínez Hernández, 2023. "A Mixed Frequency BVAR for the Euro Area Labour Market," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(5), pages 1048-1082, October.
    175. Tsionas, Mike G., 2021. "Bayesian analysis of static and dynamic Hurst parameters under stochastic volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    176. Roberto Leon-Gonzalez & Fuyu Yang, 2014. "Bayesian Inference and Forecasting in the Stationary Bilinear Model," University of East Anglia Applied and Financial Economics Working Paper Series 055, School of Economics, University of East Anglia, Norwich, UK..
    177. Nalan Baştürk & Cem Çakmakli & S. Pinar Ceyhan & Herman K. Van Dijk, 2014. "Posterior‐Predictive Evidence On Us Inflation Using Extended New Keynesian Phillips Curve Models With Non‐Filtered Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(7), pages 1164-1182, November.
    178. Bernardi, Mauro & Maruotti, Antonello & Petrella, Lea, 2017. "Multiple risk measures for multivariate dynamic heavy–tailed models," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 1-32.
    179. Ellington, Michael & Fu, Xi & Zhu, Yunyi, 2023. "Real estate illiquidity and returns: A time-varying regional perspective," International Journal of Forecasting, Elsevier, vol. 39(1), pages 58-72.
    180. Dellaportas, Petros & Titsias, Michalis K. & Petrova, Katerina & Plataniotis, Anastasios, 2023. "Scalable inference for a full multivariate stochastic volatility model," Journal of Econometrics, Elsevier, vol. 232(2), pages 501-520.
    181. Camilla Muglia & Luca Santabarbara & Stefano Grassi, 2019. "Is Bitcoin a Relevant Predictor of Standard & Poor’s 500?," JRFM, MDPI, vol. 12(2), pages 1-10, May.
    182. Justyna Wróblewska & Anna Pajor, 2019. "One-period joint forecasts of Polish inflation, unemployment and interest rate using Bayesian VEC-MSF models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 11(1), pages 23-45, March.
    183. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2013. "Predictive likelihood comparisons with DSGE and DSGE-VAR models," Working Paper Series 1536, European Central Bank.
    184. Niko Hauzenberger & Florian Huber & Luca Onorante, 2020. "Combining Shrinkage and Sparsity in Conjugate Vector Autoregressive Models," Papers 2002.08760, arXiv.org, revised Aug 2020.
    185. Boriss Siliverstovs, 2021. "Gauging the Effect of Influential Observations on Measures of Relative Forecast Accuracy in a Post-COVID-19 Era: Application to Nowcasting Euro Area GDP Growth," Working Papers 2021/01, Latvijas Banka.
    186. Patrick Leung & Catherine S. Forbes & Gael M Martin & Brendan McCabe, 2019. "Forecasting Observables with Particle Filters: Any Filter Will Do!," Monash Econometrics and Business Statistics Working Papers 22/19, Monash University, Department of Econometrics and Business Statistics.
    187. Deschamps, Philippe J., 2012. "Bayesian estimation of generalized hyperbolic skewed student GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3035-3054.
    188. Yong Song, 2012. "Modelling Regime Switching and Structural Breaks with an Infinite Hidden Markov Model," Working Paper series 28_12, Rimini Centre for Economic Analysis.
    189. Jochen Krause & Marc S. Paolella, 2014. "A Fast, Accurate Method for Value-at-Risk and Expected Shortfall," Econometrics, MDPI, vol. 2(2), pages 1-25, June.
    190. Jia Liu & John M. Maheu & Yong Song, 2024. "Identification and forecasting of bull and bear markets using multivariate returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 723-745, August.
    191. Gregor Kastner & Florian Huber, 2020. "Sparse Bayesian vector autoregressions in huge dimensions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1142-1165, November.
    192. Rafal Weron, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," HSC Research Reports HSC/14/07, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    193. Cem Çakmakli, 2012. "Bayesian Semiparametric Dynamic Nelson-Siegel Model," Working Paper series 59_12, Rimini Centre for Economic Analysis, revised Sep 2012.
    194. Roberto Casarin & Giulia Mantoan & Francesco Ravazzolo, 2016. "Bayesian Calibration of Generalized Pools of Predictive Distributions," Econometrics, MDPI, vol. 4(1), pages 1-24, March.
    195. Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2019. "Density Forecasting," BEMPS - Bozen Economics & Management Paper Series BEMPS59, Faculty of Economics and Management at the Free University of Bozen.
    196. Byrne, Joseph & Fu, Rong, 2016. "Stock Return Prediction with Fully Flexible Models and Coefficients," MPRA Paper 75366, University Library of Munich, Germany.
    197. Topaloglou, Nikolas & Tsionas, Mike G., 2020. "Stochastic dominance tests," Journal of Economic Dynamics and Control, Elsevier, vol. 112(C).
    198. Markus Heinrich & Magnus Reif, 2018. "Forecasting using mixed-frequency VARs with time-varying parameters," ifo Working Paper Series 273, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    199. Luis Gruber & Gregor Kastner, 2022. "Forecasting macroeconomic data with Bayesian VARs: Sparse or dense? It depends!," Papers 2206.04902, arXiv.org, revised Feb 2025.
    200. Korobilis, Dimitris, 2017. "Quantile regression forecasts of inflation under model uncertainty," International Journal of Forecasting, Elsevier, vol. 33(1), pages 11-20.
    201. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
    202. Follett, Lendie & Yu, Cindy, 2019. "Achieving parsimony in Bayesian vector autoregressions with the horseshoe prior," Econometrics and Statistics, Elsevier, vol. 11(C), pages 130-144.
    203. Leonardo N. Ferreira, 2021. "Forecasting with VAR-teXt and DFM-teXt Models:exploring the predictive power of central bank communication," Working Papers Series 559, Central Bank of Brazil, Research Department.
    204. Carlos Henrique Dias Cordeiro de Castro & Fernando Antonio Lucena Aiube, 2023. "Forecasting inflation time series using score‐driven dynamic models and combination methods: The case of Brazil," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 369-401, March.
    205. Huurman, Christian & Ravazzolo, Francesco & Zhou, Chen, 2012. "The power of weather," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3793-3807.
    206. Martin Feldkircher & Luis Gruber & Florian Huber & Gregor Kastner, 2024. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian vector autoregressions?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2126-2145, September.
    207. Piergiorgio Alessandri & Haroon Mumtaz, 2014. "Financial indicators and density forecasts for US output and inflation," Temi di discussione (Economic working papers) 977, Bank of Italy, Economic Research and International Relations Area.
    208. Antonio Pacifico, 2023. "Obesity and labour market outcomes in Italy: a dynamic panel data evidence with correlated random effects," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 24(4), pages 557-574, June.
    209. Constandina Koki & Stefanos Leonardos & Georgios Piliouras, 2020. "Exploring the Predictability of Cryptocurrencies via Bayesian Hidden Markov Models," Papers 2011.03741, arXiv.org, revised Dec 2020.
    210. Nalan Basturk & Cem Cakmakli & Pinar Ceyhan & Herman K. van Dijk, 2013. "Posterior-Predictive Evidence on US Inflation using Extended Phillips Curve Models with non-filtered Data," Koç University-TUSIAD Economic Research Forum Working Papers 1321, Koc University-TUSIAD Economic Research Forum.
    211. Angelos Alexopoulos & Petros Dellaportas & Omiros Papaspiliopoulos, 2019. "Bayesian prediction of jumps in large panels of time series data," Papers 1904.05312, arXiv.org, revised Apr 2021.
    212. Spyros Makridakis & Andreas Merikas & Anna Merika & Mike G. Tsionas & Marwan Izzeldin, 2020. "A novel forecasting model for the Baltic dry index utilizing optimal squeezing," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 56-68, January.
    213. Markku Lanne & Jani Luoto, 2018. "Data†Driven Identification Constraints for DSGE Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(2), pages 236-258, April.
    214. Dimitrios P. Louzis, 2017. "Macroeconomic and credit forecasts during the Greek crisis using Bayesian VARs," Empirical Economics, Springer, vol. 53(2), pages 569-598, September.
    215. Roberto Casarin & Domenico Sartore & Marco Tronzano, 2018. "A Bayesian Markov-Switching Correlation Model for Contagion Analysis on Exchange Rate Markets," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 101-114, January.

  13. Amisano, Gianni & Savona, Roberto, 2008. "Imperfect predictability and mutual fund dynamics. How managers use predictors in changing systematic risk," Working Paper Series 881, European Central Bank.

    Cited by:

    1. Alessandra Del Boca & Michele Fratianni & Franco Spinelli & Carmine Trecroci, 2008. "The Phillips Curve and the Italian Lira, 1861-1998," Mo.Fi.R. Working Papers 8, Money and Finance Research group (Mo.Fi.R.) - Univ. Politecnica Marche - Dept. Economic and Social Sciences.
    2. Alessandro Fedele & Paolo Panteghini & Sergio Vergalli, 2010. "Optimal Investment and Financial Strategies under Tax Rate Uncertainty," CESifo Working Paper Series 3017, CESifo.
    3. Rosella Levaggi & Francesco Menoncin, 2009. "Decentralized provision of merit and impure public goods," Working Papers 0909, University of Brescia, Department of Economics.
    4. Alessandro Fedele & Raffaele Miniaci, 2010. "Do Social Enterprises Finance Their Investments Differently from For-profit Firms? The Case of Social Residential Services in Italy," Journal of Social Entrepreneurship, Taylor & Francis Journals, vol. 1(2), pages 174-189, October.
    5. Monica Billio & Roberto Casarin, 2010. "Bayesian Estimation of Stochastic-Transition Markov-Switching Models for Business Cycle Analysis," Working Papers 1002, University of Brescia, Department of Economics.
    6. Francesco Menoncin & Paolo Panteghini, 2009. "Retrospective Capital Gains taxation in the real world," Working Papers 0910, University of Brescia, Department of Economics.
    7. Martin Meier & Enrico Minelli & Herakles Polemarchakis, 2014. "Competitive markets with private information on both sides," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 55(2), pages 257-280, February.
    8. Alessandro Fedele & Francesco Liucci & Andrea Mantovani, 2009. "Credit availability in the crisis: the European investment bank group," Working Papers 0913, University of Brescia, Department of Economics.
    9. Alberto Bisin & John Geanakoplos & Piero Gottardi & Enrico Minelli & Herakles Polemarchakis, 2010. "Markets and contracts," Economics Working Papers ECO2010/29, European University Institute.

  14. Tristani, Oreste & Amisano, Giovanni, 2007. "Euro Area Inflation Persistence in an Estimated Nonlinear DSGE Model," CEPR Discussion Papers 6373, C.E.P.R. Discussion Papers.

    Cited by:

    1. Malik, Sheheryar & Pitt, Michael K., 2011. "Particle filters for continuous likelihood evaluation and maximisation," Journal of Econometrics, Elsevier, vol. 165(2), pages 190-209.
    2. Martin Meier & Enrico Minelli & Herakles Polemarchakis, 2014. "Competitive markets with private information on both sides," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 55(2), pages 257-280, February.
    3. Fedele, Alessandro & Panteghini, Paolo M. & Vergalli, Sergio, 2010. "Optimal Investment and Financial Strategies under Tax Rate Uncertainty," Institutions and Markets Papers 91001, Fondazione Eni Enrico Mattei (FEEM).
    4. Alessandra Del Boca & Michele Fratianni & Franco Spinelli & Carmine Trecroci, 2008. "The Phillips Curve and the Italian Lira, 1861-1998," Mo.Fi.R. Working Papers 8, Money and Finance Research group (Mo.Fi.R.) - Univ. Politecnica Marche - Dept. Economic and Social Sciences.
    5. Alessandro Fedele & Francesco Liucci & Andrea Mantovani, 2009. "Credit availability in the crisis: the European investment bank group," Working Papers 0913, University of Brescia, Department of Economics.
    6. YANO Koiti, 2010. "Time-varying Analysis of Dynamic Stochastic General Equilibrium Models Based on Sequential Monte Carlo Methods," ESRI Discussion paper series 231, Economic and Social Research Institute (ESRI).
    7. Stéphane Adjemian & Houtan Bastani & Michel Juillard & Frédéric Karamé & Ferhat Mihoubi & Willi Mutschler & Johannes Pfeifer & Marco Ratto & Sébastien Villemot & Normann Rion, 2023. "Dynare: Reference Manual Version 5," PSE Working Papers hal-04219920, HAL.
      • Adjemian, Stéphane & Bastani, Houtan & Juillard, Michel & Karamé, Fréderic & Mihoubi, Ferhat & Mutschler, Willi & Pfeifer, Johannes & Ratto, Marco & Rion, Normann & Villemot, Sébastien, 2022. "Dynare: Reference Manual Version 5," Dynare Working Papers 72, CEPREMAP, revised Mar 2023.
      • Stéphane Adjemian & Houtan Bastani & Michel Juillard & Frédéric Karamé & Ferhat Mihoubi & Willi Mutschler & Johannes Pfeifer & Marco Ratto & Sébastien Villemot & Normann Rion, 2023. "Dynare: Reference Manual Version 5," Working Papers hal-04219920, HAL.
    8. Jonathan A. Attey & Casper G. de Vries, 2016. "Monetary Policy in the Presence of Random Wage Indexation," Tinbergen Institute Discussion Papers 16-086/VI, Tinbergen Institute.
    9. Sanha Noh & Ingul Baek, 2022. "What are the Driving Forces of the Economic Downturn in Korea during COVID-19? (Covid-19 Special Issue)," Korean Economic Review, Korean Economic Association, vol. 38, pages 285-322.
    10. Hall, Jamie, 2012. "Consumption dynamics in general equilibrium," MPRA Paper 43933, University Library of Munich, Germany.
    11. Hall, Jamie, 2012. "Rapid estimation of nonlinear DSGE models," MPRA Paper 41218, University Library of Munich, Germany.
    12. Tristani, Oreste & Amisano, Gianni, 2011. "Exact likelihood computation for nonlinear DSGE models with heteroskedastic innovations," Working Paper Series 1341, European Central Bank.
    13. Andrew Binning & Junior Maih, 2015. "Sigma Point Filters For Dynamic Nonlinear Regime Switching Models," Working Papers No 4/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    14. Vines, David & Luk, Paul, 2015. "Optimal Monetary and Fiscal Policy in an Economy with Endogenous Public Debt," CEPR Discussion Papers 10580, C.E.P.R. Discussion Papers.
    15. Ajevskis, Viktors, 2019. "Nonlocal Solutions To Dynamic Equilibrium Models: The Approximate Stable Manifolds Approach," Macroeconomic Dynamics, Cambridge University Press, vol. 23(6), pages 2544-2571, September.
    16. Viktor Winschel & Markus Kr‰tzig, 2010. "Solving, Estimating, and Selecting Nonlinear Dynamic Models Without the Curse of Dimensionality," Econometrica, Econometric Society, vol. 78(2), pages 803-821, March.
    17. Yossi Yakhin, 2022. "Breaking the UIP: A Model‐Equivalence Result," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(6), pages 1889-1904, September.
    18. Doh, Taeyoung, 2011. "Yield curve in an estimated nonlinear macro model," Journal of Economic Dynamics and Control, Elsevier, vol. 35(8), pages 1229-1244, August.
    19. Strid, Ingvar, 2008. "Metropolis-Hastings prefetching algorithms," SSE/EFI Working Paper Series in Economics and Finance 706, Stockholm School of Economics, revised 02 Dec 2009.
    20. Tommaso, Proietti & Alessandra, Luati, 2012. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," MPRA Paper 39600, University Library of Munich, Germany.
    21. Maddalena Cavicchioli, 2020. "Invertibility and VAR Representations of Time-Varying Dynamic Stochastic General Equilibrium Models," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 61-86, January.
    22. Fleischhacker, Jan, 2024. "Fiscal policy and the business cycle: An argument for non-linear policy rules," MPRA Paper 122497, University Library of Munich, Germany.
    23. Alessandro Fedele & Raffaele Miniaci, 2009. "Do social enterprises finance their investments differently from for-profit firms? The case of social residential services in Italy," Working Papers 0911, University of Brescia, Department of Economics.
    24. Abdul Jalil, 2021. "Drivers of Inflation: From Roots to Regressions," PIDE Knowledge Brief 2021:38, Pakistan Institute of Development Economics.
    25. Rosella Levaggi & Francesco Menoncin, 2009. "Decentralized provision of merit and impure public goods," Working Papers 0909, University of Brescia, Department of Economics.
    26. Grazzini, Jakob & Richiardi, Matteo, 2015. "Estimation of ergodic agent-based models by simulated minimum distance," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 148-165.
    27. Hall, Jamie & Pitt, Michael K. & Kohn, Robert, 2014. "Bayesian inference for nonlinear structural time series models," Journal of Econometrics, Elsevier, vol. 179(2), pages 99-111.
    28. Adjemian, Stéphane & Juillard, Michel & Karamé, Fréderic & Mutschler, Willi & Pfeifer, Johannes & Ratto, Marco & Rion, Normann & Villemot, Sébastien, 2024. "Dynare: Reference Manual, Version 6," Dynare Working Papers 80, CEPREMAP, revised Feb 2025.
    29. Strid, Ingvar, 2010. "Efficient parallelisation of Metropolis-Hastings algorithms using a prefetching approach," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2814-2835, November.
    30. YANO Koiti, 2009. "Dynamic Stochastic General Equilibrium Models Under a Liquidity Trap and Self-organizing State Space Modeling," ESRI Discussion paper series 206, Economic and Social Research Institute (ESRI).
    31. Yang, Yuan & Wang, Lu, 2016. "An auxiliary particle filter for nonlinear dynamic equilibrium models," Economics Letters, Elsevier, vol. 144(C), pages 112-114.
    32. Rangan Gupta & Charl Jooste & Omid Ranjbar, 2017. "South Africa’s inflation persistence: a quantile regression framework," Economic Change and Restructuring, Springer, vol. 50(4), pages 367-386, November.
    33. Luisa Corrado & Stefano Grassi & Aldo Paolillo, 2021. "Modelling and Estimating Large Macroeconomic Shocks During the Pandemic," CREATES Research Papers 2021-08, Department of Economics and Business Economics, Aarhus University.
    34. Martin M. Andreasen, 2010. "Non-linear DSGE Models and The Optimized Particle Filter," CREATES Research Papers 2010-05, Department of Economics and Business Economics, Aarhus University.
    35. Lombardi, Marco J. & Sgherri, Silvia, 2007. "(Un)naturally low? Sequential Monte Carlo tracking of the US natural interest rate," Working Paper Series 794, European Central Bank.
    36. Monica Billio & Roberto Casarin, 2010. "Bayesian Estimation of Stochastic-Transition Markov-Switching Models for Business Cycle Analysis," Working Papers 1002, University of Brescia, Department of Economics.
    37. Alberto Bisin & John Geanakoplos & Piero Gottardi & Enrico Minelli & Herakles Polemarchakis, 2010. "Markets and contracts," Economics Working Papers ECO2010/29, European University Institute.
    38. Takefumi Yamazaki, 2018. "Financial friction sources in emerging economies: Structural estimation of sovereign default models," Discussion papers ron303, Policy Research Institute, Ministry of Finance Japan.
    39. Andreasen, Martin M., 2011. "Non-linear DSGE models and the optimized central difference particle filter," Journal of Economic Dynamics and Control, Elsevier, vol. 35(10), pages 1671-1695, October.
    40. Rangan Gupta & Charl Jooste & Omid Ranjbar, 2015. "The Changing Dynamics of South Africa's Inflation Persistence: Evidence from a Quantile Regression Framework," Working Papers 201563, University of Pretoria, Department of Economics.
    41. Yang, Yuan & Wang, Lu, 2015. "An Improved Auxiliary Particle Filter for Nonlinear Dynamic Equilibrium Models," Dynare Working Papers 47, CEPREMAP.
    42. Sergey Ivashchenko, 2014. "Forecasting in a Non-Linear DSGE Model," EUSP Department of Economics Working Paper Series 2014/02, European University at St. Petersburg, Department of Economics.
    43. Francesco Menoncin & Paolo Panteghini, 2009. "Retrospective Capital Gains Taxation in the Real World," CESifo Working Paper Series 2674, CESifo.
    44. Pichler Paul, 2008. "Forecasting with DSGE Models: The Role of Nonlinearities," The B.E. Journal of Macroeconomics, De Gruyter, vol. 8(1), pages 1-35, July.
    45. Kühl, Michael, 2014. "Mitigating financial stress in a bank-financed economy: Equity injections into banks or purchases of assets?," Discussion Papers 19/2014, Deutsche Bundesbank.
    46. Lux, Thomas, 2018. "Estimation of agent-based models using sequential Monte Carlo methods," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 391-408.
    47. Luisa Corrado & Stefano Grassi & Aldo Paolillo, 2021. "Identifying Economic Shocks in a Rare Disaster Environment," CEIS Research Paper 517, Tor Vergata University, CEIS, revised 18 Jul 2024.
    48. Amedeo Fossati & Rosella Levaggi, 2008. "Delay is not the answer: waiting time in health care & income redistribution," Working Papers 0801, University of Brescia, Department of Economics.
    49. Andrew Phiri, 2012. "Threshold effects and inflation persistence in South Africa," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 4(3), pages 247-269, July.
    50. Lux, Thomas, 2017. "Estimation of agent-based models using sequential Monte Carlo methods," Economics Working Papers 2017-07, Christian-Albrechts-University of Kiel, Department of Economics.
    51. Sanha Noh, 2020. "Posterior Inference on Parameters in a Nonlinear DSGE Model via Gaussian-Based Filters," Computational Economics, Springer;Society for Computational Economics, vol. 56(4), pages 795-841, December.
    52. Liu, Shih-Fu & Hwang, Yu-Ning & Lai, Ching-Chong, 2017. "Internal imbalances in the monetary union with asymmetric openness," International Review of Economics & Finance, Elsevier, vol. 52(C), pages 380-401.
    53. Caiani, Alessandro & Godin, Antoine & Caverzasi, Eugenio & Gallegati, Mauro & Kinsella, Stephen & Stiglitz, Joseph E., 2016. "Agent based-stock flow consistent macroeconomics: Towards a benchmark model," Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 375-408.

  15. Amisano, Gianni & Geweke, John, 2007. "Hierarchical Markov normal mixture models with applications to financial asset returns," Working Paper Series 831, European Central Bank.

    Cited by:

    1. Tsionas, Mike G., 2021. "Optimal combinations of stochastic frontier and data envelopment analysis models," European Journal of Operational Research, Elsevier, vol. 294(2), pages 790-800.
    2. Rodney W. Strachan & Herman K. Van Dijk, 2013. "Evidence On Features Of A Dsge Business Cycle Model From Bayesian Model Averaging," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 54(1), pages 385-402, February.
    3. Alessandra Del Boca & Michele Fratianni & Franco Spinelli & Carmine Trecroci, 2008. "The Phillips Curve and the Italian Lira, 1861-1998," Mo.Fi.R. Working Papers 8, Money and Finance Research group (Mo.Fi.R.) - Univ. Politecnica Marche - Dept. Economic and Social Sciences.
    4. Francesco Giancaterini & Alain Hecq & Claudio Morana, 2022. "Is climate change time reversible?," Papers 2205.07579, arXiv.org, revised Nov 2022.
    5. Gary Koop & Joshua Chan, 2011. "Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables," Working Papers 1111, University of Strathclyde Business School, Department of Economics.
    6. Holzmann, Hajo & Schwaiger, Florian, 2016. "Testing for the number of states in hidden Markov models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 318-330.
    7. Luis Uzeda, 2018. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Staff Working Papers 18-14, Bank of Canada.
    8. Amisano, Gianni & Fagan, Gabriel, 2013. "Money growth and inflation: A regime switching approach," Journal of International Money and Finance, Elsevier, vol. 33(C), pages 118-145.
    9. Grant, Angelia L. & Chan, Joshua C.C., 2017. "Reconciling output gaps: Unobserved components model and Hodrick–Prescott filter," Journal of Economic Dynamics and Control, Elsevier, vol. 75(C), pages 114-121.
    10. Alessandro Fedele & Paolo Panteghini & Sergio Vergalli, 2010. "Optimal Investment and Financial Strategies under Tax Rate Uncertainty," CESifo Working Paper Series 3017, CESifo.
    11. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2013. "Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 13-191/III, Tinbergen Institute.
    12. Zeng, Songlin & Bec, Frédérique, 2015. "Do stock returns rebound after bear markets? An empirical analysis from five OECD countries," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 50-61.
    13. Bobeica, Elena & Hartwig, Benny, 2023. "The COVID-19 shock and challenges for inflation modelling," International Journal of Forecasting, Elsevier, vol. 39(1), pages 519-539.
    14. Cem Cakmakli & Richard Paap & Dick van Dijk, 2011. "Measuring and Predicting Heterogeneous Recessions," Tinbergen Institute Discussion Papers 11-154/4, Tinbergen Institute, revised 15 Nov 2011.
    15. Mehmet Balcilar & Rangan Gupta & Clement Kyei & Mark E. Wohar, 2016. "Does Economic Policy Uncertainty Predict Exchange Rate Returns and Volatility? Evidence from a Nonparametric Causality-in-Quantiles Test," Open Economies Review, Springer, vol. 27(2), pages 229-250, April.
    16. Tsionas, Mike & Parmeter, Christopher F. & Zelenyuk, Valentin, 2023. "Bayesian Artificial Neural Networks for frontier efficiency analysis," Journal of Econometrics, Elsevier, vol. 236(2).
    17. Koop, Gary & Leon-Gonzalez, Roberto & Strachan, Rodney W., 2008. "Bayesian Inference in the Time Varying Cointegration Model," SIRE Discussion Papers 2008-60, Scottish Institute for Research in Economics (SIRE).
    18. Gao, Shen & Hou, Chenghan & Nguyen, Bao H., 2020. "Forecasting natural gas prices using highly flexible time-varying parameter models," Working Papers 2020-01, University of Tasmania, Tasmanian School of Business and Economics.
    19. Joshua C C Chan, 2012. "Moving Average Stochastic Volatility Models with Application to Inflation Forecast," ANU Working Papers in Economics and Econometrics 2012-591, Australian National University, College of Business and Economics, School of Economics.
    20. Joshua Chan & Gary Koop & Roberto Leon-Gonzalez & Rodney Strachan, 2011. "Time Varying Dimension Models," Working Papers 1116, University of Strathclyde Business School, Department of Economics.
    21. Pelenis, Justinas, 2014. "Bayesian regression with heteroscedastic error density and parametric mean function," Journal of Econometrics, Elsevier, vol. 178(P3), pages 624-638.
    22. Koop, Gary & Korobilis, Dimitris, 2011. "Forecasting Inflation Using Dynamic Model Averaging," SIRE Discussion Papers 2011-40, Scottish Institute for Research in Economics (SIRE).
    23. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    24. Pelenis, Justinas, 2012. "Bayesian Semiparametric Regression," Economics Series 285, Institute for Advanced Studies.
    25. Rosella Levaggi & Francesco Menoncin, 2009. "Decentralized provision of merit and impure public goods," Working Papers 0909, University of Brescia, Department of Economics.
    26. Richard G. Anderson & Jane M. Binner & Vincent A. Schmidt, 2011. "Connectionist-based rules describing the pass-through of individual goods prices into trend inflation in the United States," Working Papers 2011-007, Federal Reserve Bank of St. Louis.
    27. Taamouti, Abderrahim, 2012. "Moments of multivariate regime switching with application to risk-return trade-off," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 292-308.
    28. Gao, Shen & Hou, Chenghan & Nguyen, Bao H., 2021. "Forecasting natural gas prices using highly flexible time-varying parameter models," Economic Modelling, Elsevier, vol. 105(C).
    29. Alessandro Fedele & Raffaele Miniaci, 2010. "Do Social Enterprises Finance Their Investments Differently from For-profit Firms? The Case of Social Residential Services in Italy," Journal of Social Entrepreneurship, Taylor & Francis Journals, vol. 1(2), pages 174-189, October.
    30. Fernandes, Mário Correia & Dutra, Tiago Mota & Dias, José Carlos & Teixeira, João C.A., 2023. "Modelling output gaps in the Euro Area with structural breaks: The COVID-19 recession," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 1046-1058.
    31. Goodness C. Aye & Rangan Gupta & Shawkat Hammoudeh & Won Joong Kim, 2014. "Forecasting the Price of Gold Using Dynamic Model Averaging," Working Papers 201415, University of Pretoria, Department of Economics.
    32. Monica Billio & Roberto Casarin, 2010. "Bayesian Estimation of Stochastic-Transition Markov-Switching Models for Business Cycle Analysis," Working Papers 1002, University of Brescia, Department of Economics.
    33. Catania, Leopoldo & Di Mari, Roberto, 2021. "Hierarchical Markov-switching models for multivariate integer-valued time-series," Journal of Econometrics, Elsevier, vol. 221(1), pages 118-137.
    34. Jamie L. Cross & Chenghan Hou & Bao H. Nguyen, 2018. "On the China factor in international oil markets: A regime switching approach," Working Papers No 11/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    35. Leopoldo Catania & Roberto Di Mari & Paolo Santucci de Magistris, 2019. "Dynamic discrete mixtures for high frequency prices," Discussion Papers 19/05, University of Nottingham, Granger Centre for Time Series Econometrics.
    36. Joshua C.C. Chan & Eric Eisenstat, 2013. "Gibbs Samplers for VARMA and Its Extensions," ANU Working Papers in Economics and Econometrics 2013-604, Australian National University, College of Business and Economics, School of Economics.
    37. Jeff Fleming & Chris Kirby, 2013. "Component-Driven Regime-Switching Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 11(2), pages 263-301, March.
    38. Sylvia Kaufmann, 2016. "Hidden Markov models in time series, with applications in economics," Working Papers 16.06, Swiss National Bank, Study Center Gerzensee.
    39. Kola Akinsomi & Goodness C. Aye & Vassilios Babalos & Fotini Economou & Rangan Gupta, 2014. "Real Estate Returns Predictability Revisited: Novel Evidence from the US REITs Market," Working Papers 201454, University of Pretoria, Department of Economics.
    40. Gefang, Deborah, 2014. "Bayesian doubly adaptive elastic-net Lasso for VAR shrinkage," International Journal of Forecasting, Elsevier, vol. 30(1), pages 1-11.
    41. Amisano, Gianni & Geweke, John, 2009. "Optimal Prediction Pools," Working Paper Series 1017, European Central Bank.
    42. Dong, Xiyong & Yoon, Seong-Min, 2019. "What global economic factors drive emerging Asian stock market returns? Evidence from a dynamic model averaging approach," Economic Modelling, Elsevier, vol. 77(C), pages 204-215.
    43. Frédérique Bec & Annabelle de Gaye, 2019. "Le modèle autorégressif autorégressif à seuil avec effet rebond : Une application aux rendements boursiers français et américains ," Working Papers hal-02014663, HAL.
    44. Amedeo Fossati & Rosella Levaggi, 2008. "Delay is not the answer: waiting time in health care & income redistribution," Working Papers 0801, University of Brescia, Department of Economics.
    45. Markus Jochmann & Gary Koop & Rodney W. Strachan, 2008. "Bayesian Forecasting using Stochastic Search Variable Selection in a VAR Subject to Breaks," Working Paper series 19_08, Rimini Centre for Economic Analysis.
    46. Gary Koop & Dimitris Korompilis, 2009. "UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?," Working Papers 0917, University of Strathclyde Business School, Department of Economics.
    47. Francesco Menoncin & Paolo Panteghini, 2009. "Retrospective Capital Gains taxation in the real world," Working Papers 0910, University of Brescia, Department of Economics.
    48. Aubrey Poon, 2018. "Assessing the Synchronicity and Nature of Australian State Business Cycles," The Economic Record, The Economic Society of Australia, vol. 94(307), pages 372-390, December.
    49. Xianguo HUANG & Roberto LEON-GONZALEZ & Somrasri YUPHO, 2013. "Financial Integration from a Time-Varying Cointegration Perspective," Asian Journal of Empirical Research, Asian Economic and Social Society, vol. 3(12), pages 1473-1487.
    50. Hyeyoen Kim & Doojin Ryu, 2013. "Forecasting Exchange Rate from Combination Taylor Rule Fundamental," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 49(S4), pages 81-92, September.
    51. Bernardi, Mauro & Maruotti, Antonello & Petrella, Lea, 2017. "Multiple risk measures for multivariate dynamic heavy–tailed models," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 1-32.
    52. Gil-Alana, Luis A. & Gupta, Rangan & Olubusoye, Olusanya E. & Yaya, OlaOluwa S., 2016. "Time series analysis of persistence in crude oil price volatility across bull and bear regimes," Energy, Elsevier, vol. 109(C), pages 29-37.
    53. Joshua C.C. Chan & Angelia L. Grant, 2015. "Modeling energy price dynamics: GARCH versus stochastic volatility," CAMA Working Papers 2015-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    54. Gianni Amisano & Roberta Colavecchio, 2013. "Money Growth and Inflation: evidence from a Markov Switching Bayesian VAR," Macroeconomics and Finance Series 201304, University of Hamburg, Department of Socioeconomics.
    55. Yin-Wong Cheung & Sang-Kuck Chung, 2011. "A Long Memory Model with Normal Mixture GARCH," Computational Economics, Springer;Society for Computational Economics, vol. 38(4), pages 517-539, November.
    56. Aijun Yang & Ju Xiang & Lianjie Shu & Hongqiang Yang, 2018. "Sparse Bayesian Variable Selection with Correlation Prior for Forecasting Macroeconomic Variable using Highly Correlated Predictors," Computational Economics, Springer;Society for Computational Economics, vol. 51(2), pages 323-338, February.
    57. Mike Tsionas & Christopher F. Parmeter & Valentin Zelenyuk, 2021. "Bridging the Divide? Bayesian Artificial Neural Networks for Frontier Efficiency Analysis," CEPA Working Papers Series WP082021, School of Economics, University of Queensland, Australia.
    58. Chen, Bin & Hong, Yongmiao, 2014. "A unified approach to validating univariate and multivariate conditional distribution models in time series," Journal of Econometrics, Elsevier, vol. 178(P1), pages 22-44.
    59. Joshua C.C. Chan, 2015. "Large Bayesian VARs: A flexible Kronecker error covariance structure," CAMA Working Papers 2015-41, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    60. Jan Prüser, 2021. "Forecasting US inflation using Markov dimension switching," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 481-499, April.
    61. Tsionas, Mike G., 2021. "Bayesian forecasting with the structural damped trend model," International Journal of Production Economics, Elsevier, vol. 234(C).
    62. Geweke, John & Amisano, Gianni, 2010. "Comparing and evaluating Bayesian predictive distributions of asset returns," International Journal of Forecasting, Elsevier, vol. 26(2), pages 216-230, April.
    63. Martin Meier & Enrico Minelli & Herakles Polemarchakis, 2014. "Competitive markets with private information on both sides," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 55(2), pages 257-280, February.
    64. Alessandro Fedele & Francesco Liucci & Andrea Mantovani, 2009. "Credit availability in the crisis: the European investment bank group," Working Papers 0913, University of Brescia, Department of Economics.
    65. M. Bernardi & L. Petrella, 2014. "Interconnected risk contributions: an heavy-tail approach to analyse US financial sectors," Papers 1401.6408, arXiv.org, revised Apr 2014.
    66. Stylianos Asimakopoulos & Marco Lorusso & Francesco Ravazzolo, 2023. "A Bayesian DSGE Approach to Modelling Cryptocurrency," Working Papers No 09/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    67. d’Addona, Stefano & Khanom, Najrin, 2022. "Estimating tail-risk using semiparametric conditional variance with an application to meme stocks," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 241-260.
    68. BenSaïda, Ahmed, 2015. "The frequency of regime switching in financial market volatility," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 63-79.
    69. Gupta, Rangan & Hammoudeh, Shawkat & Kim, Won Joong & Simo-Kengne, Beatrice D., 2014. "Forecasting China's foreign exchange reserves using dynamic model averaging: The roles of macroeconomic fundamentals, financial stress and economic uncertainty," The North American Journal of Economics and Finance, Elsevier, vol. 28(C), pages 170-189.
    70. Roberto Leon-Gonzalez & Blessings Majon, 2024. "Exact Likelihood for Inverse Gamma Stochastic Volatility Models," GRIPS Discussion Papers 24-03, National Graduate Institute for Policy Studies.
    71. Joshua C. C. Chan, 2017. "The Stochastic Volatility in Mean Model With Time-Varying Parameters: An Application to Inflation Modeling," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 17-28, January.
    72. Michael O’Grady, 2019. "Estimating the Output, Inflation and Unemployment Gaps in Ireland using Bayesian Model Averaging," The Economic and Social Review, Economic and Social Studies, vol. 50(1), pages 35-76.
    73. Xiong, Yingge & Tobias, Justin L. & Mannering, Fred L., 2014. "The analysis of vehicle crash injury-severity data: A Markov switching approach with road-segment heterogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 109-128.
    74. Byrne, Joseph & Fu, Rong, 2016. "Stock Return Prediction with Fully Flexible Models and Coefficients," MPRA Paper 75366, University Library of Munich, Germany.
    75. David Gunawan & William Griffths & Anatasios Panagiotelis and Duangkamon Chotikapanich, 2017. "Bayesian Weighted Inference from Surveys "Abstract: Data from large surveys are often supplemented with sampling weights that are designed to reflect unequal probabilities of response and selecti," Department of Economics - Working Papers Series 2030, The University of Melbourne.
    76. Bisin, A. & Geanakoplos, J.D. & Gottardi, P. & Minelli, E. & Polemarchakis, H., 2011. "Markets and contracts," Journal of Mathematical Economics, Elsevier, vol. 47(3), pages 279-288.
    77. Joshua C. C. Chan, 2019. "Large Bayesian vector autoregressions," CAMA Working Papers 2019-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    78. Jamie L. Cross & Chenghan Hou & Aubrey Poon, 2018. "International Transmission of Macroeconomic Uncertainty in Small Open Economies: An Empirical Approach," Working Papers No 12/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    79. Jamie L. Cross & Aubrey Poon, 2020. "On the contribution of international shocks in Australian business cycle fluctuations," Empirical Economics, Springer, vol. 59(6), pages 2613-2637, December.
    80. Jianxi Su & Edward Furman, 2016. "Multiple risk factor dependence structures: Distributional properties," Papers 1607.04739, arXiv.org.
    81. Jushan Bai & Peng Wang, 2011. "Conditional Markov chain and its application in economic time series analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(5), pages 715-734, August.
    82. Joshua C.C. Chan & Eric Eisenstat, 2015. "Efficient estimation of Bayesian VARMAs with time-varying coefficients," CAMA Working Papers 2015-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    83. Aknouche, Abdelhakim & Almohaimeed, Bader & Dimitrakopoulos, Stefanos, 2020. "Forecasting transaction counts with integer-valued GARCH models," MPRA Paper 101779, University Library of Munich, Germany, revised 11 Jul 2020.
    84. Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2020. "On an integer-valued stochastic intensity model for time series of counts," MPRA Paper 105406, University Library of Munich, Germany.
    85. Hou, Chenghan, 2017. "Infinite hidden markov switching VARs with application to macroeconomic forecast," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1025-1043.

  16. Gianni Amisano & Oreste Tristani, 2006. "Euro area inflation persistence in an estimated nonlinear," Computing in Economics and Finance 2006 347, Society for Computational Economics.

    Cited by:

    1. Viktor Winschel & Markus Kr‰tzig, 2010. "Solving, Estimating, and Selecting Nonlinear Dynamic Models Without the Curse of Dimensionality," Econometrica, Econometric Society, vol. 78(2), pages 803-821, March.
    2. Lombardi, Marco J. & Sgherri, Silvia, 2007. "(Un)naturally low? Sequential Monte Carlo tracking of the US natural interest rate," Working Paper Series 794, European Central Bank.
    3. Rangan Gupta & Charl Jooste & Omid Ranjbar, 2015. "The Changing Dynamics of South Africa's Inflation Persistence: Evidence from a Quantile Regression Framework," Working Papers 201563, University of Pretoria, Department of Economics.
    4. Paul Pichler, 2007. "Forecasting with estimated dynamic stochastic general equilibrium models: The role of nonlinearities," Vienna Economics Papers vie0702, University of Vienna, Department of Economics.
    5. Jesus Fernandez-Villaverde & Juan F. Rubio-Ramirez, 2006. "The Research Agenda: Jesus Fernandez-Villaverde and Juan F. Rubio-Ramirez on Estimating DSGE Models," EconomicDynamics Newsletter, Review of Economic Dynamics, vol. 8(1), November.

  17. Gianni Amisano & Raffaella Giacomini, 2005. "Comparing Density Forecsts via Weighted Likelihood Ratio Tests," Working Papers ubs0504, University of Brescia, Department of Economics.

    Cited by:

    1. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2016. "Dynamic Predictive Density Combinations for Large Data Sets in Economics and Finance," Tinbergen Institute Discussion Papers 15-084/III, Tinbergen Institute, revised 03 Jul 2017.
    2. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2008. "Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails," Discussion Papers 2008-10, School of Economics, The University of New South Wales.
    3. Paulo M. Sánchez & Luis Fernando Melo, 2013. "Combinación de brechas del producto colombiano," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 31(72), pages 74-82, December.
    4. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-scale portfolio allocation under transaction costs and model uncertainty," CFS Working Paper Series 582, Center for Financial Studies (CFS).
    5. Allayioti, Anastasia & Venditti, Fabrizio, 2024. "The role of comovement and time-varying dynamics in forecasting commodity prices," Working Paper Series 2901, European Central Bank.
    6. Jason Ng & Catherine S. Forbes & Gael M. Martin & Brendan P.M. McCabe, 2011. "Non-Parametric Estimation of Forecast Distributions in Non-Gaussian, Non-linear State Space Models," Monash Econometrics and Business Statistics Working Papers 11/11, Monash University, Department of Econometrics and Business Statistics.
    7. Carlo Altavilla & Raffaella Giacomini & Riccardo Costantini, 2014. "Bond Returns and Market Expectations," Journal of Financial Econometrics, Oxford University Press, vol. 12(4), pages 708-729.
    8. Domit, Sílvia & Monti, Francesca & Sokol, Andrej, 2019. "Forecasting the UK economy with a medium-scale Bayesian VAR," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1669-1678.
    9. Gianfreda, Angelica & Ravazzolo, Francesco & Rossini, Luca, 2020. "Comparing the forecasting performances of linear models for electricity prices with high RES penetration," International Journal of Forecasting, Elsevier, vol. 36(3), pages 974-986.
    10. Julien Chevallier & Mathieu Gatumel & Florian Ielpo, 2014. "Commodity markets through the business cycle," Quantitative Finance, Taylor & Francis Journals, vol. 14(9), pages 1597-1618, September.
    11. Michael McAleer & Massimiliano Caporin, 2011. "Ranking Multivariate GARCH Models by Problem Dimension:An Empirical Evaluation," KIER Working Papers 778, Kyoto University, Institute of Economic Research.
    12. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2012. "Time-varying Combinations of Predictive Densities using Nonlinear Filtering," Tinbergen Institute Discussion Papers 12-118/III, Tinbergen Institute.
    13. Wojciech CHAREMZA & Carlos DÍAZ & Svetlana MAKAROVA, 2019. "Conditional Term Structure of Inflation Forecast Uncertainty: The Copula Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 5-18, March.
    14. Emilio Zanetti Chini, 2017. "Generalizing Smooth Transition Autoregressions," DEM Working Papers Series 138, University of Pavia, Department of Economics and Management.
    15. Szabolcs Blazsek & Marco Villatoro, 2015. "Is Beta- t -EGARCH(1,1) superior to GARCH(1,1)?," Applied Economics, Taylor & Francis Journals, vol. 47(17), pages 1764-1774, April.
    16. Foltas, Alexander & Pierdzioch, Christian, 2020. "On the efficiency of German growth forecasts: An empirical analysis using quantile random forests," Working Papers 21, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    17. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    18. Odendahl, Florens & Rossi, Barbara & Sekhposyan, Tatevik, 2023. "Evaluating forecast performance with state dependence," Journal of Econometrics, Elsevier, vol. 237(2).
    19. Olmo, José & Sanso-Navarro, Marcos, 2012. "Forecasting the performance of hedge fund styles," Journal of Banking & Finance, Elsevier, vol. 36(8), pages 2351-2365.
    20. Philippe de Peretti & Oren Tapiero, 2014. "A GARCH analysis of dark-pool trades," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00984834, HAL.
    21. Enzo D'Innocenzo & André Lucas & Anne Opschoor & Xingmin Zhang, 2024. "Heterogeneity and dynamics in network models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 150-173, January.
    22. David Harris & Gael M. Martin & Indeewara Perera & Don S. Poskitt, 2017. "Construction and visualization of optimal confidence sets for frequentist distributional forecasts," Monash Econometrics and Business Statistics Working Papers 9/17, Monash University, Department of Econometrics and Business Statistics.
    23. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    24. Ricardo Crisóstomo & Lorena Couso, 2017. "Financial density forecasts: A comprehensive comparison of risk-neutral and historical schemes," CNMV Working Papers CNMV Working Papers no. 6, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
    25. Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.
    26. Piergiorgio Alessandri & Haroon Mumtaz, 2014. "Financial conditions and density forecasts for US output and inflation," CReMFi Discussion Papers 1, CReMFi, School of Economics and Finance, QMUL.
    27. Jan Capek & Jesus Crespo Cuaresma & Niko Hauzenberger & Vlastimil Reichel, 2020. "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," Department of Economics Working Papers wuwp305, Vienna University of Economics and Business, Department of Economics.
    28. Sebastiano Manzan & Dawit Zerom, 2015. "Asymmetric Quantile Persistence and Predictability: the Case of US Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(2), pages 297-318, April.
    29. Liu, Xiaochun, 2015. "Modeling time-varying skewness via decomposition for out-of-sample forecast," International Journal of Forecasting, Elsevier, vol. 31(2), pages 296-311.
    30. Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," DEM Working Papers Series 145, University of Pavia, Department of Economics and Management.
    31. Tingting Cheng & Jiti Gao & Xibin Zhang, 2014. "Semiparametric Localized Bandwidth Selection in Kernel Density Estimation," Monash Econometrics and Business Statistics Working Papers 14/14, Monash University, Department of Econometrics and Business Statistics.
    32. Dovern, Jonas & Feldkircher, Martin & Huber, Florian, 2015. "Does Joint Modelling of the World Economy Pay Off? Evaluating Multivariate Forecasts from a Bayesian GVAR," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112999, Verein für Socialpolitik / German Economic Association.
    33. Todd E. Clark & Taeyoung Doh, 2011. "A Bayesian evaluation of alternative models of trend inflation," Research Working Paper RWP 11-16, Federal Reserve Bank of Kansas City.
    34. Davide Delle Monache & Ivan Petrella, 2016. "Adaptive models and heavy tails with an application to inflation forecasting," BCAM Working Papers 1603, Birkbeck Centre for Applied Macroeconomics.
    35. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02505861, HAL.
    36. Noureldin, Diaa & Shephard, Neil & Sheppard, Kevin, 2014. "Multivariate rotated ARCH models," Journal of Econometrics, Elsevier, vol. 179(1), pages 16-30.
    37. John M Maheu & Thomas H McCurdy, 2008. "Do high-frequency measures of volatility improve forecasts of return distributions?," Working Papers tecipa-324, University of Toronto, Department of Economics.
    38. Florian Huber, 2017. "Structural breaks in Taylor rule based exchange rate models - Evidence from threshold time varying parameter models," Department of Economics Working Papers wuwp244, Vienna University of Economics and Business, Department of Economics.
    39. C. Alexander & M. Coulon & Y. Han & X. Meng, 2024. "Evaluating the discrimination ability of proper multi-variate scoring rules," Annals of Operations Research, Springer, vol. 334(1), pages 857-883, March.
    40. Tim Oliver Berg & Steffen Henzel, 2013. "Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?," ifo Working Paper Series 155, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    41. Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2020. "Nowcasting Norwegian household consumption with debit card transaction data," Working Paper 2020/17, Norges Bank.
    42. Petrella, Ivan & Delle Monache, Davide, 2016. "Adaptive models and heavy tails," Bank of England working papers 577, Bank of England.
    43. Fabian Krüger & Sebastian Lerch & Thordis Thorarinsdottir & Tilmann Gneiting, 2021. "Predictive Inference Based on Markov Chain Monte Carlo Output," International Statistical Review, International Statistical Institute, vol. 89(2), pages 274-301, August.
    44. Rui Fan & Stephen J. Taylor & Matteo Sandri, 2018. "Density forecast comparisons for stock prices, obtained from high‐frequency returns and daily option prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(1), pages 83-103, January.
    45. Andres Trujillo-Barrera & Philip Garcia & Mindy L Mallory, 2018. "Short-term price density forecasts in the lean hog futures market," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 45(1), pages 121-142.
    46. Anne Sofie Jore & James Mitchell & Shaun Vahey, 2008. "Combining Forecast Densities from VARs with Uncertain Instabilities," Reserve Bank of New Zealand Discussion Paper Series DP2008/18, Reserve Bank of New Zealand.
    47. Zdeněk Zmeškal & Dana Dluhošová & Karolina Lisztwanová & Antonín Pončík & Iveta Ratmanová, 2023. "Distribution Prediction of Decomposed Relative EVA Measure with Levy-Driven Mean-Reversion Processes: The Case of an Automotive Sector of a Small Open Economy," Forecasting, MDPI, vol. 5(2), pages 1-19, May.
    48. Marco Jacopo Lombardi, 2013. "On the correlation between commodity and equity returns: implications for portfolio allocation," BIS Working Papers 420, Bank for International Settlements.
    49. Sebastiano Manzan, 2015. "Forecasting the Distribution of Economic Variables in a Data-Rich Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 144-164, January.
    50. Michael McAleer & Massimiliano Caporin, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," KIER Working Papers 815, Kyoto University, Institute of Economic Research.
    51. Christophe Chorro & Dominique Guegan & Florian Ielpo & Hanjarivo Lalaharison, 2014. "Testing for Leverage Effects in the Returns of US Equities," Documents de travail du Centre d'Economie de la Sorbonne 14022r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Jan 2017.
    52. Jonas E. Arias & Juan F. Rubio-Ramirez & Minchul Shin, 2021. "Macroeconomic Forecasting and Variable Ordering in Multivariate Stochastic Volatility Models," Working Papers 21-21, Federal Reserve Bank of Philadelphia.
    53. Andrea Monticini & Francesco Ravazzolo, 2014. "Forecasting the intraday market price of money," DISCE - Working Papers del Dipartimento di Economia e Finanza def010, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    54. Dovern, Jonas & Feldkircher, Martin & Huber, Florian, 2016. "Does joint modelling of the world economy pay off? Evaluating global forecasts from a Bayesian GVAR," Journal of Economic Dynamics and Control, Elsevier, vol. 70(C), pages 86-100.
    55. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 837-862, October.
    56. Valentina Aprigliano & Simone Emiliozzi & Gabriele Guaitoli & Andrea Luciani & Juri Marcucci & Libero Monteforte, 2021. "The power of text-based indicators in forecasting the Italian economic activity," Temi di discussione (Economic working papers) 1321, Bank of Italy, Economic Research and International Relations Area.
    57. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2012. "Common Drifting Volatility in Large Bayesian VARs," CEPR Discussion Papers 8894, C.E.P.R. Discussion Papers.
    58. Angela Capolongo & Claudia Pacella, 2021. "Forecasting inflation in the euro area: countries matter!," Empirical Economics, Springer, vol. 61(5), pages 2477-2499, November.
    59. Krystian Jaworski, 2019. "Sentiment-induced regime switching in density forecasts of emerging markets’ exchange rates. Calibrated simulation trumps estimated autoregression," Bank i Kredyt, Narodowy Bank Polski, vol. 50(1), pages 83-106.
    60. Michael Clements, 2016. "Are Macroeconomic Density Forecasts Informative?," ICMA Centre Discussion Papers in Finance icma-dp2016-02, Henley Business School, University of Reading.
    61. Daniel Buncic, 2012. "Understanding forecast failure of ESTAR models of real exchange rates," Empirical Economics, Springer, vol. 43(1), pages 399-426, August.
    62. Łukasz Lenart, 2017. "Examination of Seasonal Volatility in HICP for Baltic Region Countries: Non-Parametric Test versus Forecasting Experiment," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(1), pages 29-67, March.
    63. Gianni Amisano & Roberta Colavecchio, 2013. "Money Growth and Inflation: evidence from a Markov Switching Bayesian VAR," Macroeconomics and Finance Series 201304, University of Hamburg, Department of Socioeconomics.
    64. Liu, Li & Wang, Yudong & Yang, Li, 2018. "Predictability of crude oil prices: An investor perspective," Energy Economics, Elsevier, vol. 75(C), pages 193-205.
    65. David I. Harvey & Stephen J. Leybourne & Yang Zu, 2024. "Tests for equal forecast accuracy under heteroskedasticity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 850-869, August.
    66. Carlo Altavilla & Raffaella Giacomini & Giuseppe Ragusa, 2013. "Anchoring the yield curve using survey expectations," CeMMAP working papers 52/13, Institute for Fiscal Studies.
    67. Boero, Gianna & Smith, Jeremy & Wallis, Kenneth F., 2011. "Scoring rules and survey density forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 379-393, April.
    68. Kwas, Marek & Paccagnini, Alessia & Rubaszek, Michał, 2022. "Common factors and the dynamics of cereal prices. A forecasting perspective," Journal of Commodity Markets, Elsevier, vol. 28(C).
    69. Tae-Hwy Lee & Yong Bao & Burak Saltoğlu, 2007. "Comparing density forecast models Previous versions of this paper have been circulated with the title, 'A Test for Density Forecast Comparison with Applications to Risk Management' since October 2003;," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(3), pages 203-225.
    70. Francesco Ravazzolo & Philip Rothman, 2010. "Oil and US GDP: A real-time out-of-sample examination," Working Paper 2010/18, Norges Bank.
    71. Szabolcs Blazsek & Han-Chiang Ho, 2017. "Markov regime-switching Beta--EGARCH," Applied Economics, Taylor & Francis Journals, vol. 49(47), pages 4793-4805, October.
    72. Geweke, John & Amisano, Gianni, 2010. "Comparing and evaluating Bayesian predictive distributions of asset returns," International Journal of Forecasting, Elsevier, vol. 26(2), pages 216-230, April.
    73. Matthieu Garcin & Clément Goulet, 2017. "Non-parametric news impact curve: a variational approach," Post-Print halshs-01244292, HAL.
    74. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2008. "Out-of-sample Comparison of Copula Specifications in Multivariate Density Forecasts," Tinbergen Institute Discussion Papers 08-105/4, Tinbergen Institute.
    75. Francesco Ravazzolo & Shaun P Vahey, 2010. "Measuring Core Inflation in Australia with Disaggregate Ensembles," RBA Annual Conference Volume (Discontinued), in: Renée Fry & Callum Jones & Christopher Kent (ed.),Inflation in an Era of Relative Price Shocks, Reserve Bank of Australia.
    76. Lei, Heng & Xue, Minggao & Liu, Huiling, 2022. "Probability distribution forecasting of carbon allowance prices: A hybrid model considering multiple influencing factors," Energy Economics, Elsevier, vol. 113(C).
    77. Barbara Rossi & Tatevik Sekhposyan, 2013. "Conditional predictive density evaluation in the presence of instabilities," Economics Working Papers 1368, Department of Economics and Business, Universitat Pompeu Fabra.
    78. Mr. Ananthakrishnan Prasad & Mr. Selim A Elekdag & Mr. Phakawa Jeasakul & Romain Lafarguette & Mr. Adrian Alter & Alan Xiaochen Feng & Changchun Wang, 2019. "Growth at Risk: Concept and Application in IMF Country Surveillance," IMF Working Papers 2019/036, International Monetary Fund.
    79. Jarociński, Marek & Maćkowiak, Bartosz, 2013. "Granger-causal-priority and choice of variables in vector autoregressions," Working Paper Series 1600, European Central Bank.
    80. Michael B. Gordy & Pawel J. Szerszen, 2015. "Bayesian Estimation of Time-Changed Default Intensity Models," Finance and Economics Discussion Series 2015-2, Board of Governors of the Federal Reserve System (U.S.).
    81. Kyungchul Song, 2009. "Testing Predictive Ability and Power Robustification," PIER Working Paper Archive 09-035, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    82. Roberto Leon-Gonzalez & Blessings Majon, 2024. "Exact Likelihood for Inverse Gamma Stochastic Volatility Models," GRIPS Discussion Papers 24-03, National Graduate Institute for Policy Studies.
    83. Anthony Garratt & James Mitchell & Shaun P. Vahey, 2011. "Measuring Output Gap Nowcast Uncertainty," CAMA Working Papers 2011-16, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    84. Joshua C. C. Chan, 2017. "The Stochastic Volatility in Mean Model With Time-Varying Parameters: An Application to Inflation Modeling," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 17-28, January.
    85. Tino Werner, 2022. "Elicitability of Instance and Object Ranking," Decision Analysis, INFORMS, vol. 19(2), pages 123-140, June.
    86. Anne Opschoor & Dewi Peerlings & Luca Rossini & Andre Lucas, 2024. "Density Forecasting for Electricity Prices under Tail Heterogeneity with the t-Riesz Distribution," Tinbergen Institute Discussion Papers 24-049/III, Tinbergen Institute.
    87. Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2022. "An automated prior robustness analysis in Bayesian model comparison," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 583-602, April.
    88. Michael W. McCracken, 2020. "Diverging Tests of Equal Predictive Ability," Econometrica, Econometric Society, vol. 88(4), pages 1753-1754, July.
    89. Barbara Rossi, 2015. "Evaluating Predictive Densities of US Output Growth and Inflation in a Large Macroeconomic Data Set," Working Papers 689, Barcelona School of Economics.
    90. Szabolcs Blazsek & Luis Antonio Monteros, 2017. "Dynamic conditional score models of degrees of freedom: filtering with score-driven heavy tails," Applied Economics, Taylor & Francis Journals, vol. 49(53), pages 5426-5440, November.
    91. Marcin Kolasa & Michał Rubaszek, 2014. "How frequently should we re-estimate DSGE models?," NBP Working Papers 194, Narodowy Bank Polski.
    92. Massimiliano Caporin & Juliusz Pres, 2010. "Modelling and forecasting wind speed intensity for weather risk management," "Marco Fanno" Working Papers 0106, Dipartimento di Scienze Economiche "Marco Fanno".
    93. Anne Opschoor & Dick van Dijk & Michel van der Wel, 2014. "Improving Density Forecasts and Value-at-Risk Estimates by Combining Densities," Tinbergen Institute Discussion Papers 14-090/III, Tinbergen Institute.
    94. Davide Pettenuzzo & Konstantinos Metaxoglou & Aaron Smith, 2016. "Option-Implied Equity Premium Predictions via Entropic TiltinG," Working Papers 99R, Brandeis University, Department of Economics and International Business School, revised Aug 2016.
    95. Kyungchul Song, 2011. "Testing Predictive Ability and Power Robustification," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 288-296, October.
    96. Marcus P. A. Cobb, 2020. "Aggregate density forecasting from disaggregate components using Bayesian VARs," Empirical Economics, Springer, vol. 58(1), pages 287-312, January.
    97. Gloria Gonzalez-Rivera & Yingying Sun, 2014. "Density Forecast Evaluation in Unstable Environments," Working Papers 201428, University of California at Riverside, Department of Economics.
    98. Ida Wolden Bache & James Mitchell & Francesco Ravazzolo & Shaun P. Vahey, 2009. "Macro modelling with many models," Working Paper 2009/15, Norges Bank.
    99. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    100. Szabolcs Blazsek & Vicente Mendoza, 2016. "QARMA-Beta- t -EGARCH versus ARMA-GARCH: an application to S&P 500," Applied Economics, Taylor & Francis Journals, vol. 48(12), pages 1119-1129, March.
    101. Knut Are Aastveit & Jamie L. Cross & Herman K. van Dijk, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Working Paper 2021/3, Norges Bank.
    102. Shackleton, Mark B. & Taylor, Stephen J. & Yu, Peng, 2010. "A multi-horizon comparison of density forecasts for the S&P 500 using index returns and option prices," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2678-2693, November.
    103. Bjørnland, Hilde C. & Ravazzolo, Francesco & Thorsrud, Leif Anders, 2017. "Forecasting GDP with global components: This time is different," International Journal of Forecasting, Elsevier, vol. 33(1), pages 153-173.
    104. Andre Lucas & Anne Opschoor & Luca Rossini, 2021. "Tail Heterogeneity for Dynamic Covariance Matrices: the F-Riesz Distribution," Tinbergen Institute Discussion Papers 21-010/III, Tinbergen Institute, revised 11 Jul 2023.
    105. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
    106. Zeyyad Mandalinci, 2015. "Forecasting Inflation in Emerging Markets: An Evaluation of Alternative Models," CReMFi Discussion Papers 3, CReMFi, School of Economics and Finance, QMUL.
    107. Manzan, Sebastiano & Zerom, Dawit, 2009. "Are Macroeconomic Variables Useful for Forecasting the Distribution of U.S. Inflation?," MPRA Paper 14387, University Library of Munich, Germany.
    108. Tatevik Sekhposyan & Barbara Rossi, 2015. "Alternative Tests for Correct Specification of Conditional Predictive Densities," Working Papers 758, Barcelona School of Economics.
    109. Rehab OSMAN, 2010. "SADC EPAs with the EU: the Right or a Blight Way for Development," EcoMod2010 259600127, EcoMod.
    110. Gary Koop & Luca Onorante, 2011. "Estimating Phillips Curves in Turbulent Times using the ECBs Survey of Professional Forecasters," Working Papers 1109, University of Strathclyde Business School, Department of Economics.
    111. Kuo‐Hsuan Chin, 2022. "Forecast evaluation of DSGE models: Linear and nonlinear likelihood," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1099-1130, September.
    112. Fabio Busetti, 2017. "Quantile Aggregation of Density Forecasts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(4), pages 495-512, August.
    113. Verbrugge, Randal & Zaman, Saeed, 2024. "Improving inflation forecasts using robust measures," International Journal of Forecasting, Elsevier, vol. 40(2), pages 735-745.
    114. Rossi, Barbara & Odendahl, Florens & Sekhposyan, Tatevik, 2020. "Comparing Forecast Performance with State Dependence," CEPR Discussion Papers 15217, C.E.P.R. Discussion Papers.
    115. Ramon de Punder & Timo Dimitriadis & Rutger-Jan Lange, 2024. "Kullback-Leibler-based characterizations of score-driven updates," Tinbergen Institute Discussion Papers 24-051/III, Tinbergen Institute, revised 22 Oct 2024.
    116. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2014. "No Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," CEPR Discussion Papers 9848, C.E.P.R. Discussion Papers.
    117. Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman & Herman van Dijk, 2019. "Partially Censored Posterior for Robust and Efficient Risk Evaluation," Tinbergen Institute Discussion Papers 19-057/III, Tinbergen Institute.
    118. Mathieu Gatumel & Florian Ielpo, 2011. "The Number of Regimes Across Asset Returns: Identification and Economic Value," Post-Print halshs-00658540, HAL.
    119. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2020. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(531), pages 1092-1110, July.
    120. Leonidas Tsiaras, 2010. "Dynamic Models of Exchange Rate Dependence Using Option Prices and Historical Returns," CREATES Research Papers 2010-35, Department of Economics and Business Economics, Aarhus University.
    121. Diks, Cees & Panchenko, Valentyn & Sokolinskiy, Oleg & van Dijk, Dick, 2014. "Comparing the accuracy of multivariate density forecasts in selected regions of the copula support," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 79-94.
    122. Alanya-Beltran, Willy, 2022. "Modelling stock returns volatility with dynamic conditional score models and random shifts," Finance Research Letters, Elsevier, vol. 45(C).
    123. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2019. "Forecasting with instabilities: an application to DSGE models with financial frictions," Temi di discussione (Economic working papers) 1234, Bank of Italy, Economic Research and International Relations Area.
    124. Gian Piero Aielli & Massimiliano Caporin, 2011. "Variance Clustering Improved Dynamic Conditional Correlation MGARCH Estimators," "Marco Fanno" Working Papers 0133, Dipartimento di Scienze Economiche "Marco Fanno".
    125. Christian Kascha & Francesco Ravazzolo, 2008. "Combining inflation density forecasts," Working Paper 2008/22, Norges Bank.
    126. Davide Pettenuzzo & Rossen Valkanov & Allan Timmermann, 2014. "A Bayesian MIDAS Approach to Modeling First and Second Moment Dynamics," Working Papers 76, Brandeis University, Department of Economics and International Business School.
    127. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combining Predictive Densities using Bayesian Filtering with Applications to US Economics Data," Tinbergen Institute Discussion Papers 11-003/4, Tinbergen Institute.
    128. Ayala, Astrid & Blazsek, Szabolcs, 2017. "Dynamic conditional score models with time-varying location, scale and shape parameters," UC3M Working papers. Economics 25043, Universidad Carlos III de Madrid. Departamento de Economía.
    129. Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2023. "Are low frequency macroeconomic variables important for high frequency electricity prices?," Economic Modelling, Elsevier, vol. 120(C).
    130. Christopher McDonald & Craig Thamotheram & Shaun P. Vahey & Elizabeth C. Wakerly, 2016. "Assessing the economic value of probabilistic forecasts in the presence of an inflation target," CAMA Working Papers 2016-40, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    131. Tingting Cheng & Jiti Gao & Xibin Zhang, 2016. "Nonparametric Localized Bandwidth Selection for Kernel Density Estimation," Monash Econometrics and Business Statistics Working Papers 7/16, Monash University, Department of Econometrics and Business Statistics.
    132. Timmermann, Allan & Pettenuzzo, Davide, 2016. "Forecasting Macroeconomic Variables under Model Instability," CEPR Discussion Papers 11355, C.E.P.R. Discussion Papers.
    133. Fawcett, Nicholas & Kapetanios, George & Mitchell, James & Price, Simon, 2014. "Generalised density forecast combinations," Bank of England working papers 492, Bank of England.
    134. Garcia, Márcio G.P. & Medeiros, Marcelo C. & Vasconcelos, Gabriel F.R., 2017. "Real-time inflation forecasting with high-dimensional models: The case of Brazil," International Journal of Forecasting, Elsevier, vol. 33(3), pages 679-693.
    135. Guglielmo Maria Caporale & Luca Onorante & Paolo Paesani, 2009. "Inflation and Inflation Uncertainty in the Euro Area," CESifo Working Paper Series 2720, CESifo.
    136. Busetti, Fabio & Caivano, Michele & Delle Monache, Davide & Pacella, Claudia, 2021. "The time-varying risk of Italian GDP," Economic Modelling, Elsevier, vol. 101(C).
    137. Chalmovianský, Jakub & Porqueddu, Mario & Sokol, Andrej, 2020. "Weigh(t)ing the basket: aggregate and component-based inflation forecasts for the euro area," Working Paper Series 2501, European Central Bank.
    138. Wolden Bache, Ida & Sofie Jore, Anne & Mitchell, James & Vahey, Shaun P., 2011. "Combining VAR and DSGE forecast densities," Journal of Economic Dynamics and Control, Elsevier, vol. 35(10), pages 1659-1670, October.
    139. Valentina Corradi & Norman R. Swanson, 2003. "A Test for Comparing Multiple Misspecified Conditional Distributions," Departmental Working Papers 200314, Rutgers University, Department of Economics.
    140. Anthony Garratt & James Mitchell & Shaun P. Vahey, 2009. "Measuring output gap uncertainty," Reserve Bank of New Zealand Discussion Paper Series DP2009/15, Reserve Bank of New Zealand.
    141. Liu, Yi & Liu, Huifang & Zhang, Lei, 2019. "Modeling and forecasting return jumps using realized variation measures," Economic Modelling, Elsevier, vol. 76(C), pages 63-80.
    142. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2011. "Multivariate High-Frequency-Based Volatility (HEAVY) Models," Economics Papers 2011-W01, Economics Group, Nuffield College, University of Oxford.
    143. Ilya Archakov & Peter Reinhard Hansen & Asger Lunde, 2020. "A Multivariate Realized GARCH Model," Papers 2012.02708, arXiv.org, revised Feb 2025.
    144. Davide Pettenuzzo & Francesco Ravazzolo, 2015. "Optimal Portfolio Choice under Decision-Based Model Combinations," Working Papers No 9/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    145. Jie Cheng, 2023. "Modelling and forecasting risk dependence and portfolio VaR for cryptocurrencies," Empirical Economics, Springer, vol. 65(2), pages 899-924, August.
    146. Ali Dib & Mohamed Gammoudi & Kevin Moran, 2006. "Forecasting Canadian Time Series With the New-Keynesian Model," Working Papers Central Bank of Chile 382, Central Bank of Chile.
    147. Dimitrios P. Louzis, 2019. "Steady‐state modeling and macroeconomic forecasting quality," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(2), pages 285-314, March.
    148. Tingting Cheng & Jiti Gao & Xibin Zhang, 2014. "Semiparametric Localized Bandwidth Selection for Kernel Density Estimation," Monash Econometrics and Business Statistics Working Papers 27/14, Monash University, Department of Econometrics and Business Statistics.
    149. Vacca, Gianmarco & Zoia, Maria Grazia & Bagnato, Luca, 2022. "Forecasting in GARCH models with polynomially modified innovations," International Journal of Forecasting, Elsevier, vol. 38(1), pages 117-141.
    150. Amisano, Gianni & Fagan, Gabriel, 2010. "Money growth and inflation: a regime switching approach," Working Paper Series 1207, European Central Bank.
    151. S. Bordignon & D. Raggi, 2010. "Long memory and nonlinearities in realized volatility: a Markov switching approach," Working Papers 694, Dipartimento Scienze Economiche, Universita' di Bologna.
    152. Ñíguez, Trino-Manuel & Perote, Javier, 2016. "Multivariate moments expansion density: Application of the dynamic equicorrelation model," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 216-232.
    153. Marcin Kolasa & Michal Rubaszek, 2016. "Does foreign sector help forecast domestic variables in DSGE models?," KAE Working Papers 2016-022, Warsaw School of Economics, Collegium of Economic Analysis.
    154. Massimiliano Caporin & Michael McAleer, 2010. "Ranking Multivariate GARCH Models by Problem Dimension," "Marco Fanno" Working Papers 0124, Dipartimento di Scienze Economiche "Marco Fanno".
    155. Yves Dominicy & Harry-Paul Vander Elst, 2015. "Macro-Driven VaR Forecasts: From Very High to Very Low Frequency Data," Working Papers ECARES ECARES 2015-41, ULB -- Universite Libre de Bruxelles.
    156. Lan Bai & Xiafei Li & Yu Wei & Guiwu Wei, 2022. "Does crude oil futures price really help to predict spot oil price? New evidence from density forecasting," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3694-3712, July.
    157. Raffaella Giacomini, 2014. "Economic theory and forecasting: lessons from the literature," CeMMAP working papers CWP41/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    158. Michael B. Gordy & Alexander J. McNeil, 2018. "Spectral Backtests of Forecast Distributions with Application to Risk Management," Finance and Economics Discussion Series 2018-021, Board of Governors of the Federal Reserve System (U.S.).
    159. Koop, Gary & Onorante, Luca, 2011. "Estimating Phillips Curves in Turbulent Times using the ECB’s Survey of Professional Forecasters," SIRE Discussion Papers 2011-19, Scottish Institute for Research in Economics (SIRE).
    160. Giovanni Bonaccolto & Massimiliano Caporin, 2016. "The Determinants of Equity Risk and Their Forecasting Implications: A Quantile Regression Perspective," JRFM, MDPI, vol. 9(3), pages 1-25, July.
    161. Da Fonseca José & Grasselli Martino & Ielpo Florian, 2014. "Estimating the Wishart Affine Stochastic Correlation Model using the empirical characteristic function," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(3), pages 253-289, May.
    162. Elena Andreou & Andros Kourtellos, 2018. "Scoring rules for simple forecasting models: The case of Cyprus GDP and its sectors," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 12(1), pages 59-73, June.
    163. Tommaso Proietti & Martyna Marczak & Gianluigi Mazzi, 2015. "EuroMInd-D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area," CREATES Research Papers 2015-12, Department of Economics and Business Economics, Aarhus University.
    164. Niko Hauzenberger & Florian Huber & Luca Onorante, 2020. "Combining Shrinkage and Sparsity in Conjugate Vector Autoregressive Models," Papers 2002.08760, arXiv.org, revised Aug 2020.
    165. Maheu, John M & Yang, Qiao & Song, Yong, 2018. "Oil Price Shocks and Economic Growth: The Volatility Link," MPRA Paper 83779, University Library of Munich, Germany.
    166. Anne Opschoor & André Lucas, 2019. "Time-varying tail behavior for realized kernels," Tinbergen Institute Discussion Papers 19-051/IV, Tinbergen Institute.
    167. Alex Tagliabracci, 2020. "Asymmetry in the conditional distribution of euro-area inflation," Temi di discussione (Economic working papers) 1270, Bank of Italy, Economic Research and International Relations Area.
    168. Knut Are Aastveit & Karsten R. Gerdrup & Anne Sofie Jore & Leif Anders Thorsrud, 2011. "Nowcasting GDP in real-time: A density combination approach," Working Paper 2011/11, Norges Bank.
    169. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2015. "Prior Selection for Vector Autoregressions," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 436-451, May.
    170. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2014. "Density forecasts with MIDAS models," Working Papers No 3/2014, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    171. Matteo Malavasi & Gareth W. Peters & Stefan Treuck & Pavel V. Shevchenko & Jiwook Jang & Georgy Sofronov, 2024. "Cyber Risk Taxonomies: Statistical Analysis of Cybersecurity Risk Classifications," Papers 2410.05297, arXiv.org.
    172. Wagner Piazza Gaglianone & Jaqueline Terra Moura Marins, 2016. "Evaluation of Exchange Rate Point and Density Forecasts: an application to Brazil," Working Papers Series 446, Central Bank of Brazil, Research Department.
    173. Anne Opschoor & André Lucas & István Barra & Dick van Dijk, 2021. "Closed-Form Multi-Factor Copula Models With Observation-Driven Dynamic Factor Loadings," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1066-1079, October.
    174. Garratt, Anthony & Mise, Emi, 2014. "Forecasting exchange rates using panel model and model averaging," Economic Modelling, Elsevier, vol. 37(C), pages 32-40.
    175. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2023. "Large Time‐Varying Volatility Models for Hourly Electricity Prices," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 545-573, June.
    176. Andrew Martinez, 2017. "Testing for Differences in Path Forecast Accuracy: Forecast-Error Dynamics Matter," Working Papers (Old Series) 1717, Federal Reserve Bank of Cleveland.
    177. Alexandridis, Antonios K. & Apergis, Iraklis & Panopoulou, Ekaterini & Voukelatos, Nikolaos, 2023. "Equity premium prediction: The role of information from the options market," Journal of Financial Markets, Elsevier, vol. 64(C).
    178. Chin, Kuo-Hsuan & Li, Xue, 2019. "Bayesian forecast combination in VAR-DSGE models," Journal of Macroeconomics, Elsevier, vol. 59(C), pages 278-298.
    179. Christophe Chorro & Dominique Guegan & Florian Ielpo, 2010. "Likelihood-Related Estimation Methods and Non-Gaussian GARCH Processes," Post-Print halshs-00523371, HAL.
    180. Gelfer, Sacha, 2024. "Examining business cycles and optimal monetary policy in a regional DSGE model," Economic Modelling, Elsevier, vol. 136(C).
    181. Piergiorgio Alessandri & Haroon Mumtaz, 2014. "Financial indicators and density forecasts for US output and inflation," Temi di discussione (Economic working papers) 977, Bank of Italy, Economic Research and International Relations Area.
    182. Domit, Sílvia & Monti, Francesca & Sokol, Andrej, 2016. "A Bayesian VAR benchmark for COMPASS," Bank of England working papers 583, Bank of England.
    183. Mathieu Gatumel & Florian Ielpo, 2011. "The Number of Regimes Across Asset Returns: Identification and Economic Value," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00658540, HAL.
    184. Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2014. "Combined Density Nowcasting in an Uncertain Economic Environment," Tinbergen Institute Discussion Papers 14-152/III, Tinbergen Institute.
    185. Chorro, Christophe & Ielpo, Florian & Sévi, Benoît, 2020. "The contribution of intraday jumps to forecasting the density of returns," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    186. Gian Piero Aielli, 2011. "Dynamic Conditional Correlation: On properties and estimation," "Marco Fanno" Working Papers 0142, Dipartimento di Scienze Economiche "Marco Fanno".
    187. Hasumi, Ryo & Iiboshi, Hirokuni & Matsumae, Tatsuyoshi & Nakamura, Daisuke, 2019. "Does a financial accelerator improve forecasts during financial crises? Evidence from Japan with prediction-pooling methods," Journal of Asian Economics, Elsevier, vol. 60(C), pages 45-68.
    188. Ilmari Juutilainen & Juha Roning, 2010. "How to compare interpretatively different models for the conditional variance function," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(6), pages 983-997.
    189. Laura Liu, 2018. "Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective," Papers 1805.04178, arXiv.org, revised Oct 2021.
    190. Christophe Chorro & Dominique Guegan & Florian Ielpo, 2012. "Option Pricing for GARCH-type Models with Generalized Hyperbolic Innovations," PSE-Ecole d'économie de Paris (Postprint) hal-00511965, HAL.
    191. Angelini, Elena & Lalik, Magdalena & Lenza, Michele & Paredes, Joan, 2019. "Mind the gap: a multi-country BVAR benchmark for the Eurosystem projections," Working Paper Series 2227, European Central Bank.
    192. Diks, Cees & Panchenko, Valentyn & van Dijk, Dick, 2011. "Likelihood-based scoring rules for comparing density forecasts in tails," Journal of Econometrics, Elsevier, vol. 163(2), pages 215-230, August.
    193. Francesco Ravazzolo & Shaun P. Vahey, 2010. "Forecast densities for economic aggregates from disaggregate ensembles," Working Paper 2010/02, Norges Bank.
    194. Alexander, Carol & Han, Yang & Meng, Xiaochun, 2023. "Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1078-1096.
    195. Moisan, Stella & Herrera, Rodrigo & Clements, Adam, 2018. "A dynamic multiple equation approach for forecasting PM2.5 pollution in Santiago, Chile," International Journal of Forecasting, Elsevier, vol. 34(4), pages 566-581.
    196. Algieri, Bernardina & Leccadito, Arturo & Tunaru, Diana, 2021. "Risk premia in electricity derivatives markets," Energy Economics, Elsevier, vol. 100(C).
    197. Gian Piero Aielli & Massimiliano Caporin, 2015. "Dynamic Principal Components: a New Class of Multivariate GARCH Models," "Marco Fanno" Working Papers 0193, Dipartimento di Scienze Economiche "Marco Fanno".
    198. Anthony Garratt & Ivan Petrella, 2022. "Commodity prices and inflation risk," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 392-414, March.
    199. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Post-Print halshs-02505861, HAL.
    200. Götz, Thomas B. & Hecq, Alain & Urbain, Jean-Pierre, 2016. "Combining forecasts from successive data vintages: An application to U.S. growth," International Journal of Forecasting, Elsevier, vol. 32(1), pages 61-74.
    201. Del Brio, Esther B. & Ñíguez, Trino-Manuel & Perote, Javier, 2011. "Multivariate semi-nonparametric distributions with dynamic conditional correlations," International Journal of Forecasting, Elsevier, vol. 27(2), pages 347-364, April.
    202. Cenesizoglu, Tolga & Timmermann, Allan, 2012. "Do return prediction models add economic value?," Journal of Banking & Finance, Elsevier, vol. 36(11), pages 2974-2987.
    203. Carriero, Andrea & Mumtaz, Haroon & Theophilopoulou, Angeliki, 2015. "Macroeconomic information, structural change, and the prediction of fiscal aggregates," International Journal of Forecasting, Elsevier, vol. 31(2), pages 325-348.
    204. Kenichiro McAlinn & Kosaku Takanashi, 2019. "Mean-shift least squares model averaging," Papers 1912.01194, arXiv.org.
    205. Lukasz Gatarek & Lennart Hoogerheide & Koen Hooning & Herman K. van Dijk, 2013. "Censored Posterior and Predictive Likelihood in Left-Tail Prediction for Accurate Value at Risk Estimation," Tinbergen Institute Discussion Papers 13-060/III, Tinbergen Institute, revised 06 Mar 2014.
    206. Götz, T.B. & Hecq, A.W. & Urbain, J.R.Y.J., 2014. "Combining distributions of real-time forecasts: An application to U.S. growth," Research Memorandum 027, Maastricht University, Graduate School of Business and Economics (GSBE).
    207. Szabolcs Blazsek & Hector Hernández, 2018. "Analysis of electricity prices for Central American countries using dynamic conditional score models," Empirical Economics, Springer, vol. 55(4), pages 1807-1848, December.
    208. Tim Oliver Berg & Steffen Henzel, 2014. "Point and Density Forecasts for the Euro Area Using Bayesian VARs," CESifo Working Paper Series 4711, CESifo.
    209. Diks, Cees & Fang, Hao, 2020. "Comparing density forecasts in a risk management context," International Journal of Forecasting, Elsevier, vol. 36(2), pages 531-551.
    210. Agosto, Arianna & Cavaliere, Giuseppe & Kristensen, Dennis & Rahbek, Anders, 2016. "Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 640-663.
    211. Ouysse, Rachida, 2016. "Bayesian model averaging and principal component regression forecasts in a data rich environment," International Journal of Forecasting, Elsevier, vol. 32(3), pages 763-787.
    212. Hoogerheide, Lennart F. & Ardia, David & Corré, Nienke, 2012. "Density prediction of stock index returns using GARCH models: Frequentist or Bayesian estimation?," Economics Letters, Elsevier, vol. 116(3), pages 322-325.
    213. Damian Stelmasiak & Grzegorz Szafrański, 2016. "Forecasting the Polish Inflation Using Bayesian VAR Models with Seasonality," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(1), pages 21-42, March.
    214. Marco J. Lombardi & Francesco Ravazzolo, 2012. "Oil price density forecasts: exploring the linkages with stock markets," Working Paper 2012/24, Norges Bank.
    215. Catania, Leopoldo & Grassi, Stefano & Ravazzolo, Francesco, 2019. "Forecasting cryptocurrencies under model and parameter instability," International Journal of Forecasting, Elsevier, vol. 35(2), pages 485-501.
    216. Janine Balter & Alexander J. McNeil, 2024. "Multivariate Spectral Backtests of Forecast Distributions under Unknown Dependencies," Risks, MDPI, vol. 12(1), pages 1-15, January.
    217. Tingting Cheng & Jiti Gao & Peter CB Phillips, 2016. "A Frequency Approach to Bayesian Asymptotics," Monash Econometrics and Business Statistics Working Papers 5/16, Monash University, Department of Econometrics and Business Statistics.
    218. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2010. "Forecasting with DSGE models," Working Paper Series 1185, European Central Bank.
    219. Raffaella Giacomini & Barbara Rossi, 2013. "Forecasting in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 17, pages 381-408, Edward Elgar Publishing.
    220. Luiz Renato Regis de Oliveira Lima & Wagner Piazza Gaglianone, 2012. "Constructing Optimal Density Forecasts from Point Forecast Combinations," Série Textos para Discussão (Working Papers) 5, Programa de Pós-Graduação em Economia - PPGE, Universidade Federal da Paraíba.
    221. Pettenuzzo, Davide & Timmermann, Allan & Valkanov, Rossen, 2016. "A MIDAS approach to modeling first and second moment dynamics," Journal of Econometrics, Elsevier, vol. 193(2), pages 315-334.
    222. Raffaella Giacomini, 2014. "Economic theory and forecasting: lessons from the literature," CeMMAP working papers 41/14, Institute for Fiscal Studies.
    223. Giacomini, Raffaella & Ragusa, Giuseppe, 2011. "Incorporating theoretical restrictions into forecasting by projection methods," CEPR Discussion Papers 8604, C.E.P.R. Discussion Papers.
    224. Anthony Garratt & James Mitchell & Shaun P. Vahey & Elizabeth C. Wakerly, 2010. "Real-time Inflation Forecast Densities from Ensemble Phillips Curves," CAMA Working Papers 2010-34, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    225. Minchul Shin & Molin Zhong, 2013. "Does realized volatility help bond yield density prediction?," PIER Working Paper Archive 13-064, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    226. Matthieu Garcin & Clément Goulet, 2017. "Non-parametric news impact curve: a variational approach," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01244292, HAL.
    227. Yoshibumi Makabe & Yoshihiko Norimasa, 2022. "The Term Structure of Inflation at Risk: A Panel Quantile Regression Approach," Bank of Japan Working Paper Series 22-E-4, Bank of Japan.
    228. Christophe Chorro & Dominique Guegan & Florian Ielpo, 2010. "Option pricing for GARCH-type models with generalized hyperbolic innovations," Post-Print halshs-00469529, HAL.
    229. Matei Demetrescu & Mu-Chun Wang, 2014. "Incorporating Asymmetric Preferences into Fan Charts and Path Forecasts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 287-297, April.
    230. Onno Kleen, 2024. "Scaling and measurement error sensitivity of scoring rules for distribution forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 833-849, August.
    231. Geir D. Berentsen & Jan Bulla & Antonello Maruotti & Bård Støve, 2022. "Modelling clusters of corporate defaults: Regime‐switching models significantly reduce the contagion source," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 698-722, June.
    232. Hallam, Mark & Olmo, Jose, 2014. "Forecasting daily return densities from intraday data: A multifractal approach," International Journal of Forecasting, Elsevier, vol. 30(4), pages 863-881.
    233. Michał Rubaszek & Marcin Kolasa, 2013. "Forecasting with DSGE models with financial frictions," EcoMod2013 5100, EcoMod.
    234. Kwas, Marek & Paccagnini, Alessia & Rubaszek, Michał, 2021. "Common factors and the dynamics of industrial metal prices. A forecasting perspective," Resources Policy, Elsevier, vol. 74(C).
    235. Peter McAdam & Anders Warne, 2024. "Density forecast combinations: The real‐time dimension," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1153-1172, August.
    236. Tsyplakov, Alexander, 2012. "Assessment of probabilistic forecasts: Proper scoring rules and moments," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 27(3), pages 115-132.
    237. Martinez-Martin Jaime & Morris Richard & Onorante Luca & Piersanti Fabio Massimo, 2024. "Merging Structural and Reduced-Form Models for Forecasting," The B.E. Journal of Macroeconomics, De Gruyter, vol. 24(1), pages 399-437, January.
    238. Raffaella Giacomini & Barbara Rossi, 2015. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Working Papers 819, Barcelona School of Economics.
    239. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01442618, HAL.
    240. Tae-Hwy Lee & He Wang & Zhou Xi & Ru Zhang, 2021. "Density Forecast of Financial Returns Using Decomposition and Maximum Entropy," Working Papers 202115, University of California at Riverside, Department of Economics.
    241. Alanya-Beltran Willy, 2023. "Modelling volatility dependence with score copula models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(5), pages 649-668, December.
    242. Brownlees, Christian & Souza, André B.M., 2021. "Backtesting global Growth-at-Risk," Journal of Monetary Economics, Elsevier, vol. 118(C), pages 312-330.
    243. M. Mogliani & T. Ferri re, 2016. "Rationality of announcements, business cycle asymmetry, and predictability of revisions. The case of French GDP," Working papers 600, Banque de France.
    244. Conlon, Thomas & Cotter, John & Kovalenko, Illia & Post, Thierry, 2023. "A financial modeling approach to industry exchange-traded funds selection," Journal of Empirical Finance, Elsevier, vol. 74(C).
    245. Diego Chicana & Rafael Nivin, 2021. "Evaluating Growth-at-Risk as a tool for monitoring macro-financial risks in the Peruvian economy," IHEID Working Papers 07-2021, Economics Section, The Graduate Institute of International Studies.
    246. Conflitti, Cristina & De Mol, Christine & Giannone, Domenico, 2015. "Optimal combination of survey forecasts," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1096-1103.
    247. Kolassa, Stephan, 2016. "Evaluating predictive count data distributions in retail sales forecasting," International Journal of Forecasting, Elsevier, vol. 32(3), pages 788-803.
    248. McAdam, Peter & Warne, Anders, 2018. "Euro area real-time density forecasting with financial or labor market frictions," Working Paper Series 2140, European Central Bank.
    249. Aslanidis, Nektarios & Martinez, Oscar, 2021. "Correlation regimes in international equity and bond returns," Economic Modelling, Elsevier, vol. 97(C), pages 397-410.
    250. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.
    251. Francisco Blasques & Vladim'ir Hol'y & Petra Tomanov'a, 2018. "Zero-Inflated Autoregressive Conditional Duration Model for Discrete Trade Durations with Excessive Zeros," Papers 1812.07318, arXiv.org, revised May 2024.
    252. Giacomini, Raffaella & Ragusa, Giuseppe, 2014. "Theory-coherent forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 145-155.
    253. Matteo Iacopini & Francesco Ravazzolo & Luca Rossini, 2020. "Proper scoring rules for evaluating asymmetry in density forecasting," Working Papers No 06/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    254. Emilio Zanetti Chini, 2018. "Forecasting dynamically asymmetric fluctuations of the U.S. business cycle," CREATES Research Papers 2018-13, Department of Economics and Business Economics, Aarhus University.
    255. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2019. "Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns," Journal of Econometrics, Elsevier, vol. 213(2), pages 493-515.
    256. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combining Predictive Densities using Nonlinear Filtering with Applications to US Economics Data," Tinbergen Institute Discussion Papers 11-172/4, Tinbergen Institute.
    257. Niango Ange Joseph Yapi, 2020. "Exchange rate predictive densities and currency risks: A quantile regression approach," EconomiX Working Papers 2020-16, University of Paris Nanterre, EconomiX.
    258. Tsyplakov, Alexander, 2014. "Theoretical guidelines for a partially informed forecast examiner," MPRA Paper 55017, University Library of Munich, Germany.
    259. Camehl, Annika, 2023. "Penalized estimation of panel vector autoregressive models: A panel LASSO approach," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1185-1204.
    260. Tingting Cheng & Jiti Gao & Peter CB Phillips, 2017. "Bayesian estimation based on summary statistics: Double asymptotics and practice," Monash Econometrics and Business Statistics Working Papers 4/17, Monash University, Department of Econometrics and Business Statistics.
    261. Philippe de Peretti & Oren Tapiero, 2014. "A GARCH analysis of dark-pool trades," Post-Print hal-00984834, HAL.
    262. Michał Rubaszek, 2019. "Forecasting crude oil prices with DSGE models," GRU Working Paper Series GRU_2019_024, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    263. Knut Are Aastveit & James Mitchell & Francesco Ravazzolo & Herman van Dijk, 2018. "The Evolution of Forecast Density Combinations in Economics," Tinbergen Institute Discussion Papers 18-069/III, Tinbergen Institute.
    264. Chiang, I-Hsuan Ethan & Liao, Yin & Zhou, Qing, 2021. "Modeling the cross-section of stock returns using sensible models in a model pool," Journal of Empirical Finance, Elsevier, vol. 60(C), pages 56-73.
    265. Alessandra Canepa, & Karanasos, Menelaos & Paraskevopoulos, Athanasios & Chini, Emilio Zanetti, 2022. "Forecasting Ination: A GARCH-in-Mean-Level Model with Time Varying Predictability," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202212, University of Turin.
    266. Warne, Anders, 2023. "DSGE model forecasting: rational expectations vs. adaptive learning," Working Paper Series 2768, European Central Bank.
    267. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2020. "Large Time-Varying Volatility Models for Electricity Prices," Working Papers No 05/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    268. Yan, Cheng & Cheng, Tingting, 2019. "In search of the optimal number of fund subgroups," Journal of Empirical Finance, Elsevier, vol. 50(C), pages 78-92.
    269. Christophe Chorro & Dominique Guegan & Florian Ielpo & Hanjarivo Lalaharison, 2017. "Testing for Leverage Effects in the Returns of US Equities," Post-Print halshs-00973922, HAL.
    270. Florian Ielpo & Benoît Sévi, 2014. "Forecasting the density of oil futures," Working Papers 2014-601, Department of Research, Ipag Business School.
    271. Boriss Siliverstovs, 2013. "Do business tendency surveys help in forecasting employment?: A real-time evidence for Switzerland," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 129-151.
    272. Valentina Aprigliano, 2020. "A large Bayesian VAR with a block‐specific shrinkage: A forecasting application for Italian industrial production," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1291-1304, December.
    273. Christophe Chorro & Dominique Guegan & Florian Ielpo & Hanjarivo Lalaharison, 2014. "Testing for Leverage Effect in Financial Returns," Documents de travail du Centre d'Economie de la Sorbonne 14022, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    274. Kaeck, Andreas & Rodrigues, Paulo & Seeger, Norman J., 2018. "Model Complexity and Out-of-Sample Performance: Evidence from S&P 500 Index Returns," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 1-29.
    275. Valentina Corradi & Norman Swanson, 2013. "A Survey of Recent Advances in Forecast Accuracy Comparison Testing, with an Extension to Stochastic Dominance," Departmental Working Papers 201309, Rutgers University, Department of Economics.
    276. K=osaku Takanashi & Kenichiro McAlinn, 2019. "Equivariant online predictions of non-stationary time series," Papers 1911.08662, arXiv.org, revised Jun 2023.
    277. Nesvold, Erik & Bratvold, Reidar B., 2022. "Debiasing probabilistic oil production forecasts," Energy, Elsevier, vol. 258(C).
    278. Jaqueline Terra Moura Marins, 2024. "Predictability of Exchange Rate Density Forecasts for Emerging Economies in the Short Run," Working Papers Series 588, Central Bank of Brazil, Research Department.
    279. Caraiani, Petre, 2016. "The role of money in DSGE models: a forecasting perspective," Journal of Macroeconomics, Elsevier, vol. 47(PB), pages 315-330.
    280. Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2024. "Nowcasting Norwegian household consumption with debit card transaction data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(7), pages 1220-1244, November.
    281. Cheng, Tingting & Gao, Jiti & Phillips, Peter C.B., 2018. "A frequentist approach to Bayesian asymptotics," Journal of Econometrics, Elsevier, vol. 206(2), pages 359-378.
    282. Boneva, Lena & Fawcett, Nicholas & Masolo, Riccardo M. & Waldron, Matt, 2019. "Forecasting the UK economy: Alternative forecasting methodologies and the role of off-model information," International Journal of Forecasting, Elsevier, vol. 35(1), pages 100-120.
    283. Cees Diks & Valentyn Panchenko & Oleg Sokolinskiy, & Dick van Dijk, 2013. "Comparing the Accuracy of Copula-Based Multivariate Density Forecasts in Selected Regions of Support," Tinbergen Institute Discussion Papers 13-061/III, Tinbergen Institute.
    284. Tsyplakov, Alexander, 2013. "Evaluation of Probabilistic Forecasts: Proper Scoring Rules and Moments," MPRA Paper 45186, University Library of Munich, Germany.
    285. León, Ángel & Ñíguez, Trino-Manuel, 2021. "The transformed Gram Charlier distribution: Parametric properties and financial risk applications," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 323-349.
    286. Ioannis Anagnostou & Drona Kandhai, 2019. "Risk Factor Evolution for Counterparty Credit Risk under a Hidden Markov Model," Risks, MDPI, vol. 7(2), pages 1-22, June.
    287. Wang, Yudong & Liu, Li & Ma, Feng & Wu, Chongfeng, 2016. "What the investors need to know about forecasting oil futures return volatility," Energy Economics, Elsevier, vol. 57(C), pages 128-139.
    288. Mathieu Gatumel & Florian Ielpo, 2014. "Commodity Markets through the business cycle," Post-Print hal-01302479, HAL.
    289. Matthieu Garcin & Clément Goulet, 2015. "A fully non-parametric heteroskedastic model," Documents de travail du Centre d'Economie de la Sorbonne 15086, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    290. Galvão, Ana Beatriz, 2017. "Data revisions and DSGE models," Journal of Econometrics, Elsevier, vol. 196(1), pages 215-232.
    291. Zhang, Feipeng & Gao, Hongfu & Yuan, Di, 2024. "The asymmetric effect of G7 stock market volatility on predicting oil price volatility: Evidence from quantile autoregression model," Journal of Commodity Markets, Elsevier, vol. 35(C).
    292. Michael S. O’Doherty & N. E. Savin & Ashish Tiwari, 2016. "Evaluating Hedge Funds with Pooled Benchmarks," Management Science, INFORMS, vol. 62(1), pages 69-89, January.
    293. Huurman, Christian & Ravazzolo, Francesco & Zhou, Chen, 2012. "The power of weather," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3793-3807.
    294. Christophe Chorro & Dominique Guegan & Florian Ielpo, 2012. "Option Pricing for GARCH-type Models with Generalized Hyperbolic Innovations," Post-Print hal-00511965, HAL.
    295. Rompolis, Leonidas S., 2010. "Retrieving risk neutral densities from European option prices based on the principle of maximum entropy," Journal of Empirical Finance, Elsevier, vol. 17(5), pages 918-937, December.
    296. Wagner Piazza Gaglianone & Jaqueline Terra Moura Marins, 2014. "Risk Assessment of the Brazilian FX Rate," Working Papers Series 344, Central Bank of Brazil, Research Department.
    297. Opschoor, Anne & Lucas, André, 2023. "Time-varying variance and skewness in realized volatility measures," International Journal of Forecasting, Elsevier, vol. 39(2), pages 827-840.
    298. Todd E. Clark & Michael W. McCracken, 2013. "Evaluating the accuracy of forecasts from vector autoregressions," Working Papers 2013-010, Federal Reserve Bank of St. Louis.
    299. Hua, Jian & Manzan, Sebastiano, 2013. "Forecasting the return distribution using high-frequency volatility measures," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4381-4403.
    300. Saeed Zaman, 2021. "A Unified Framework to Estimate Macroeconomic Stars," Working Papers 21-23R2, Federal Reserve Bank of Cleveland, revised 31 May 2024.
    301. Georgios Anastasiades & Patrick McSharry, 2013. "Quantile Forecasting of Wind Power Using Variability Indices," Energies, MDPI, vol. 6(2), pages 1-34, February.
    302. McAlinn, Kenichiro & West, Mike, 2019. "Dynamic Bayesian predictive synthesis in time series forecasting," Journal of Econometrics, Elsevier, vol. 210(1), pages 155-169.
    303. Dimitrios P. Louzis, 2017. "Macroeconomic and credit forecasts during the Greek crisis using Bayesian VARs," Empirical Economics, Springer, vol. 53(2), pages 569-598, September.
    304. Todd E. Clark & Michael W. McCracken, 2010. "Testing for unconditional predictive ability," Working Papers 2010-031, Federal Reserve Bank of St. Louis.
    305. Hasumi, Ryo & Iiboshi, Hirokuni & Matsumae, Tatsuyoshi & Nakamura, Daisuke, 2018. "Does a financial accelerator improve forecasts during financial crises?: Evidence from Japan with Prediction Pool Methods," MPRA Paper 85523, University Library of Munich, Germany.
    306. Jie Cheng, 2024. "Evaluating Density Forecasts Using Weighted Multivariate Scores in a Risk Management Context," Computational Economics, Springer;Society for Computational Economics, vol. 64(6), pages 3617-3643, December.

  18. Gianni Amisano & Marco Tronzano, 2005. "Assessing ECB?s Credibility During the First Years of the Eurosystem: A Bayesian Empirical Investigation," Working Papers ubs0512, University of Brescia, Department of Economics.

    Cited by:

    1. Laurence Fung & Ip-wing Yu, 2007. "Assessing the Credibility of The Convertibility Zone of The Hong Kong Dollar," Working Papers 0719, Hong Kong Monetary Authority.

  19. Gianni Amisano & Massimiliano Serati, 2002. "What goes up sometimes stays up: shocks and institutions as determinants of unemployment persistence," LIUC Papers in Economics 111, Cattaneo University (LIUC).

    Cited by:

    1. Alexius, Annika & Holmlund, Bertil, 2008. "Monetary policy and Swedish unemployment fluctuations," Working Paper Series 2008:5, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    2. Massimiliano Serati & Michela Martinoia, 2008. "The East-West migration in Europe: skill levels of migrants and their effects on the european labour market," LIUC Papers in Economics 208, Cattaneo University (LIUC).
    3. Sumera Arshad & Amajd Ali, 2016. "Trade-off between Inflation, Interest and Unemployment Rate of Pakistan: Revisited," Bulletin of Business and Economics (BBE), Research Foundation for Humanity (RFH), vol. 5(4), pages 193-209, December.
    4. Monastiriotis, Vassilis, 2006. "Macro-determinants of UK regional unemployment and the role of employment flexibility," MPRA Paper 44, University Library of Munich, Germany.
    5. Andrea Vaona, 2015. "Anomalous empirical evidence on money long-run super-neutrality and the vertical long-run Phillips curve," Working Papers 17/2015, University of Verona, Department of Economics.
    6. Tafirenyika SUNDE, 2015. "The effects of monetary policy on unemployment in Namibia," Journal of Economic and Social Thought, KSP Journals, vol. 2(4), pages 256-274, December.
    7. Juan José Echavarría & Enrique López & Sergio Ocampo & Norberto Rodríguez, 2011. "Choques, instituciones laborales y desempleo en Colombia," Borradores de Economia 682, Banco de la Republica de Colombia.
    8. Hjelm, Göran & Jönsson, Kristian, 2010. "In Search of a Method for Measuring the Output Gap of the Swedish Economy," Working Papers 115, National Institute of Economic Research.
    9. Ghafar, Aiman & Masih, Mansur, 2017. "The unemployment rate and its determinants: the Malaysian case," MPRA Paper 110220, University Library of Munich, Germany.
    10. Sunde, Tafirenyika & Akanbi, Olusegun Ayodele, 2015. "Sources of unemployment in Namibia: an application of the structural VAR approach," MPRA Paper 86578, University Library of Munich, Germany.
    11. Alexander Mihailov & Giovanni Razzu & Zhe Wang, 2019. "Heterogeneous effects of single monetary policy on unemployment rates in the largest EMU economies," Economics Discussion Papers em-dp2019-07, Department of Economics, University of Reading.
    12. BATTISTI,Michele, 2006. "Assessing persistence in the Italian rate of unemployment in presence of structural breaks and regional asymmetries, 1977 to 2004," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 6(3).
    13. Sunde, Tafirenyika & Akanbi, Olusegun Ayodele, 2016. "The Dynamic Effects of Monetary Policy on Real Variables in Namibia," African Journal of Economic Review, African Journal of Economic Review, vol. 4(01), January.
    14. Massimiliano Serati & Gianni Amisano, 2003. "Unemployment and labour taxation: an econometric analysis," LIUC Papers in Economics 122, Cattaneo University (LIUC).
    15. Andrea Bassanini & Romain Duval, 2006. "The Determinants of Unemployment across OECD Countries," Post-Print halshs-00120584, HAL.
    16. Bella Gabriel Di & Grigoli Francesco & Ramírez Francisco, 2020. "Is unemployment on steroids in advanced economies?," The B.E. Journal of Macroeconomics, De Gruyter, vol. 20(1), pages 1-17, January.

Articles

  1. Gianni Amisano & John Geweke, 2017. "Prediction Using Several Macroeconomic Models," The Review of Economics and Statistics, MIT Press, vol. 99(5), pages 912-925, December.
    See citations under working paper version above.
  2. Gianni Amisano & Roberto Savona, 2017. "Mutual Funds Dynamics and Economic Predictors," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 302-330.

    Cited by:

    1. Lambert, Marie & Platania, Federico, 2020. "The macroeconomic drivers in hedge fund beta management," Economic Modelling, Elsevier, vol. 91(C), pages 65-80.
    2. Dragomirescu-Gaina, Catalin & Philippas, Dionisis & Tsionas, Mike G., 2021. "Trading off accuracy for speed: Hedge funds' decision-making under uncertainty," International Review of Financial Analysis, Elsevier, vol. 75(C).

  3. John Geweke & Gianni Amisano, 2014. "Analysis of Variance for Bayesian Inference," Econometric Reviews, Taylor & Francis Journals, vol. 33(1-4), pages 270-288, June.
    See citations under working paper version above.
  4. Amisano, Gianni & Fagan, Gabriel, 2013. "Money growth and inflation: A regime switching approach," Journal of International Money and Finance, Elsevier, vol. 33(C), pages 118-145.
    See citations under working paper version above.
  5. Gianni Amisano & Maria Letizia Giorgetti, 2013. "Entry Into Pharmaceutical Submarkets: A Bayesian Panel Probit Analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(4), pages 667-701, June.

    Cited by:

    1. Lawrence Kessler & Murat Munkin, 2015. "Bayesian estimation of panel data fractional response models with endogeneity: an application to standardized test rates," Empirical Economics, Springer, vol. 49(1), pages 81-114, August.
    2. Jiri Slacalek, 2013. "Wealth heterogeneity and the response of consumption to shocks," Research Bulletin, European Central Bank, vol. 19, pages 10-12.
    3. Francesca DI IORIO & Maria Letizia GIORGETTI, 2017. "Entry and Patents: Evidence from the US Cardiovascular Pharmaceutical Sector," Departmental Working Papers 2017-07, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    4. Philipp Hartmann & Kirstin Hubrich & Manfred Kremer, 2013. "Introducing Systemic Financial instability into macroeconomics: how to meet the challenge?," Research Bulletin, European Central Bank, vol. 19, pages 2-9.
    5. Francesca Di Iorio & Maria Letizia Giorgietti, 2019. "Launch of a product and patents: evidence from the US cardiovascular pharmaceutical sector," DEM Working Papers Series 169, University of Pavia, Department of Economics and Management.
    6. Dimitris Christelis & Sébastien Pérez-Duarte, 2013. "The euro system household finance and consumption survey: an important resource for policy-makers and researchers," Research Bulletin, European Central Bank, vol. 19, pages 13-17.
    7. A. Ronald Gallant & Han Hong & Ahmed Khwaja, 2018. "The Dynamic Spillovers of Entry: An Application to the Generic Drug Industry," Management Science, INFORMS, vol. 64(3), pages 1189-1211, March.
    8. Tan, Yong & Lin, Faqin & Hu, Cui, 2016. "How continuing exporters set the price? Theory and empirical evidence from China," International Review of Economics & Finance, Elsevier, vol. 44(C), pages 91-102.
    9. Yong Tan, 2019. "Dynamic Entry With Demand And Supply Side Spillovers," Contemporary Economic Policy, Western Economic Association International, vol. 37(1), pages 86-101, January.

  6. John Geweke & Gianni Amisano, 2012. "Prediction with Misspecified Models," American Economic Review, American Economic Association, vol. 102(3), pages 482-486, May.

    Cited by:

    1. Eo, Yunjong & Kang, Kyu Ho, 2020. "The effects of conventional and unconventional monetary policy on forecasting the yield curve," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    2. Jan Capek & Jesus Crespo Cuaresma & Niko Hauzenberger & Vlastimil Reichel, 2020. "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," Department of Economics Working Papers wuwp305, Vienna University of Economics and Business, Department of Economics.
    3. Daniele Bianchi & Kenichiro McAlinn, 2018. "Large-Scale Dynamic Predictive Regressions," Papers 1803.06738, arXiv.org.
    4. Tim Oliver Berg & Steffen Henzel, 2013. "Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?," ifo Working Paper Series 155, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    5. Bianchi, Daniele & Tamoni, Andrea, 2016. "The dynamics of expected returns: evidence from multi-scale time series modelling," LSE Research Online Documents on Economics 118992, London School of Economics and Political Science, LSE Library.
    6. Silvia Figini & Roberto Savona & Marika Vezzoli, 2016. "Corporate Default Prediction Model Averaging: A Normative Linear Pooling Approach," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 23(1-2), pages 6-20, January.
    7. A. Ford Ramsey & Yong Liu, 2023. "Linear pooling of potentially related density forecasts in crop insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 90(3), pages 769-788, September.
    8. Merlo, Antonio & Palfrey, Thomas R., 2014. "External Validation of Voter Turnout Models by Concealed Parameter Recovery," Working Papers 14-015, Rice University, Department of Economics.
    9. Chollete, Lor & Schmeidler, David, 2014. "Misspecification Aversion and Selection of Initial Priors," UiS Working Papers in Economics and Finance 2014/13, University of Stavanger.
    10. Maik H. Wolters, 2015. "Evaluating Point and Density Forecasts of DSGE Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(1), pages 74-96, January.
    11. Chung, Tsz-Kin & Iiboshi, Hirokuni, 2015. "Prediction of Term Structure with Potentially Misspecified Macro-Finance Models near the Zero Lower Bound," MPRA Paper 85709, University Library of Munich, Germany.
    12. Knut Are Aastveit & Jamie L. Cross & Herman K. van Dijk, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Working Paper 2021/3, Norges Bank.
    13. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2018. "Quantile forecast combination using stochastic dominance," Empirical Economics, Springer, vol. 55(4), pages 1717-1755, December.
    14. Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman & Herman van Dijk, 2019. "Partially Censored Posterior for Robust and Efficient Risk Evaluation," Tinbergen Institute Discussion Papers 19-057/III, Tinbergen Institute.
    15. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2020. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(531), pages 1092-1110, July.
    16. Beckmann, J & Koop, G & Korobilis, D & Schüssler, R, 2017. "Exchange rate predictability and dynamic Bayesian learning," Essex Finance Centre Working Papers 20781, University of Essex, Essex Business School.
    17. Deak, S. & Levine, P. & Mirza, A. & Pearlman, J., 2019. "Designing Robust Monetary Policy Using Prediction Pools," Working Papers 19/11, Department of Economics, City University London.
    18. Fawcett, Nicholas & Kapetanios, George & Mitchell, James & Price, Simon, 2014. "Generalised density forecast combinations," Bank of England working papers 492, Bank of England.
    19. George Papadopoulos & Savas Papadopoulos & Thomas Sager, 2016. "Credit risk stress testing for EU15 banks: a model combination approach," Working Papers 203, Bank of Greece.
    20. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
    21. Ho, Paul & Lubik, Thomas A. & Matthes, Christian, 2024. "Averaging impulse responses using prediction pools," Journal of Monetary Economics, Elsevier, vol. 146(C).
    22. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2013. "Predictive likelihood comparisons with DSGE and DSGE-VAR models," Working Paper Series 1536, European Central Bank.
    23. James Morley, 2018. "The Econometric Analysis of Recurrent Events in Macroeconomics and Finance," The Economic Record, The Economic Society of Australia, vol. 94(306), pages 338-340, September.
    24. Thorsten Drautzburg, 2023. "A Structural Approach to Combining External and DSGE Model Forecasts," Working Papers 23-10, Federal Reserve Bank of Philadelphia.
    25. Markku Lanne & Jani Luoto, 2015. "Estimation of DSGE Models under Diffuse Priors and Data-Driven Identification Constraints," CREATES Research Papers 2015-37, Department of Economics and Business Economics, Aarhus University.
    26. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 527-724, Elsevier.
    27. Kenichiro McAlinn & Kosaku Takanashi, 2019. "Mean-shift least squares model averaging," Papers 1912.01194, arXiv.org.
    28. Tim Oliver Berg & Steffen Henzel, 2014. "Point and Density Forecasts for the Euro Area Using Bayesian VARs," CESifo Working Paper Series 4711, CESifo.
    29. Georgios Papadopoulos & Dionysios Chionis & Nikolaos P. Rachaniotis, 2018. "Macro-financial linkages during tranquil and crisis periods: evidence from stressed economies," Risk Management, Palgrave Macmillan, vol. 20(2), pages 142-166, May.
    30. Peter McAdam & Anders Warne, 2024. "Density forecast combinations: The real‐time dimension," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1153-1172, August.
    31. Conflitti, Cristina & De Mol, Christine & Giannone, Domenico, 2015. "Optimal combination of survey forecasts," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1096-1103.
    32. Ard Reijer & Andreas Johansson, 2019. "Nowcasting Swedish GDP with a large and unbalanced data set," Empirical Economics, Springer, vol. 57(4), pages 1351-1373, October.
    33. Gospodinov, Nikolay & Maasoumi, Esfandiar, 2021. "Generalized aggregation of misspecified models: With an application to asset pricing," Journal of Econometrics, Elsevier, vol. 222(1), pages 451-467.
    34. Nikolay Gospodinov & Esfandiar Maasoumi, 2017. "General Aggregation of Misspecified Asset Pricing Models," FRB Atlanta Working Paper 2017-10, Federal Reserve Bank of Atlanta.
    35. K=osaku Takanashi & Kenichiro McAlinn, 2019. "Equivariant online predictions of non-stationary time series," Papers 1911.08662, arXiv.org, revised Jun 2023.
    36. Byrne, Joseph & Fu, Rong, 2016. "Stock Return Prediction with Fully Flexible Models and Coefficients," MPRA Paper 75366, University Library of Munich, Germany.
    37. McAlinn, Kenichiro & West, Mike, 2019. "Dynamic Bayesian predictive synthesis in time series forecasting," Journal of Econometrics, Elsevier, vol. 210(1), pages 155-169.
    38. Markku Lanne & Jani Luoto, 2018. "Data†Driven Identification Constraints for DSGE Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(2), pages 236-258, April.
    39. Hasumi, Ryo & Iiboshi, Hirokuni & Matsumae, Tatsuyoshi & Nakamura, Daisuke, 2018. "Does a financial accelerator improve forecasts during financial crises?: Evidence from Japan with Prediction Pool Methods," MPRA Paper 85523, University Library of Munich, Germany.

  7. Giovanni Amisano & Oreste Tristani, 2011. "The euro area sovereign crisis: monitoring spillovers and contagion," Research Bulletin, European Central Bank, vol. 14, pages 2-4.

    Cited by:

    1. Canofari Paolo & Marini Giancarlo & Piersanti Giovanni, 2014. "Expectations and systemic risk in EMU government bond spreads," wp.comunite 0113, Department of Communication, University of Teramo.
    2. Canofari Paolo & Di Bartolomeo Giovanni & Piersanti Giovanni, 2014. "Theory and practice of contagion in monetary unions: Domino effects in EMU Mediterranean countries," wp.comunite 0109, Department of Communication, University of Teramo.
    3. Papafilis, Michalis-Panayiotis & Psillaki, Maria & Margaritis, Dimitris, 2020. "The effect of the PSI in the relationship between sovereign and bank credit risk: Evidence from the Euro Area," MPRA Paper 98182, University Library of Munich, Germany.
    4. Canofari Paolo & Di Bartolomeo Giovanni & Piersanti Giovanni, 2013. "Theory and practice of contagion in monetary unions. Domino effects in EU Mediterranean countries: The case of Greece, Italy and Spain," wp.comunite 0098, Department of Communication, University of Teramo.
    5. Antonakakis, Nikolaos & Christou, Christina & Cunado, Juncal & Gupta, Rangan, 2017. "Convergence patterns in sovereign bond yield spreads: Evidence from the Euro Area," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 49(C), pages 129-139.
    6. Ben Bouheni, Faten & Hasnaoui, Amir, 2017. "Cyclical behavior of the financial stability of eurozone commercial banks," Economic Modelling, Elsevier, vol. 67(C), pages 392-408.
    7. Vetlov, Igor & Attinasi, Maria Grazia & Lalik, Magdalena, 2017. "Fiscal spillovers in the euro area a model-based analysis," Working Paper Series 2040, European Central Bank.

  8. Amisano, Gianni & Tristani, Oreste, 2011. "Exact likelihood computation for nonlinear DSGE models with heteroskedastic innovations," Journal of Economic Dynamics and Control, Elsevier, vol. 35(12), pages 2167-2185.
    See citations under working paper version above.
  9. John Geweke & Gianni Amisano, 2011. "Hierarchical Markov normal mixture models with applications to financial asset returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(1), pages 1-29, January/F.
    See citations under working paper version above.
  10. Geweke, John & Amisano, Gianni, 2011. "Optimal prediction pools," Journal of Econometrics, Elsevier, vol. 164(1), pages 130-141, September.
    See citations under working paper version above.
  11. Gianni Amisano & Marco Tronzano, 2010. "Assessing European Central Bank'S Credibility During The First Years Of The Eurosystem: A Bayesian Empirical Investigation," Manchester School, University of Manchester, vol. 78(5), pages 437-459, September.

    Cited by:

    1. Flávio de Freitas Val & Wagner Piazza Gaglianone & Marcelo Cabus Klotzle & Antonio Carlos Figueiredo Pinto, 2017. "Estimating the Credibility of Brazilian Monetary Policy using Forward Measures and a State-Space Model," Working Papers Series 463, Central Bank of Brazil, Research Department.
    2. Cem Cakmakli & Selva Demiralp, 2020. "A Dynamic Evaluation of Central Bank Credibility," Koç University-TUSIAD Economic Research Forum Working Papers 2015, Koc University-TUSIAD Economic Research Forum.
    3. Bicchal, Motilal, 2022. "Central bank credibility and its effect on stabilization," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 73-94.
    4. Grégory Levieuge & Yannick Lucotte & Sébastien Ringuedé, 2015. "Central bank credibility and the expectations channel: Evidence based on a new credibility index," NBP Working Papers 209, Narodowy Bank Polski.
    5. de Freitas Val, Flávio & Klotzle, Marcelo Cabus & Pinto, Antonio Carlos Figueiredo & Gaglianone, Wagner Piazza, 2017. "Estimating the credibility of Brazilian monetary policy using a Kalman filter approach," Research in International Business and Finance, Elsevier, vol. 41(C), pages 37-53.
    6. Iris Biefang-Frisancho Mariscal & Woon Wong & Peter Howells, 2011. "Measuring the Policymaker’s Credibility: The Bank of England in ‘nice’ and ‘not-so-nice’ times," Working Papers 20111110, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.

  12. Gianni Amisano & Andreas Beyer & Michele Lenza, 2010. "Enhancing monetary analysis," Research Bulletin, European Central Bank, vol. 11, pages 2-6.

    Cited by:

    1. Giannone, Domenico & Lenza, Michele & Pill, Huw & Reichlin, Lucrezia, 2011. "Non-standard monetary policy measures and monetary developments," Working Paper Series 1290, European Central Bank.
    2. Rakesh Bissoondeeal & Michail Karoglou & Andy Mullineux, 2014. "Breaks in the UK Household Sector Money Demand Function," Manchester School, University of Manchester, vol. 82, pages 47-68, December.
    3. Hartmann, Philipp & Smets, Frank, 2018. "The first twenty years of the European Central Bank: monetary policy," CEPR Discussion Papers 13411, C.E.P.R. Discussion Papers.

  13. Amisano, Gianni & Tristani, Oreste, 2010. "Euro area inflation persistence in an estimated nonlinear DSGE model," Journal of Economic Dynamics and Control, Elsevier, vol. 34(10), pages 1837-1858, October.
    See citations under working paper version above.
  14. Geweke, John & Amisano, Gianni, 2010. "Comparing and evaluating Bayesian predictive distributions of asset returns," International Journal of Forecasting, Elsevier, vol. 26(2), pages 216-230, April.
    See citations under working paper version above.
  15. Amisano, Gianni & Giacomini, Raffaella, 2007. "Comparing Density Forecasts via Weighted Likelihood Ratio Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 177-190, April.
    See citations under working paper version above.
  16. Gianni Amisano & Alessandra Del Boca, 2004. "Profit related pay in Italy," International Journal of Manpower, Emerald Group Publishing Limited, vol. 25(5), pages 463-478, July.

    Cited by:

    1. Bossavie,Laurent Loic Yves & Cho,Yoonyoung & Heath,Rachel, 2019. "The Effects of International Scrutiny on Manufacturing Workers : Evidence from the Rana Plaza Collapse in Bangladesh," Policy Research Working Paper Series 9065, The World Bank.

  17. Amisano, Gianni, 2003. "Bayesian inference in cointegrated systems," Research in Economics, Elsevier, vol. 57(4), pages 287-314, December.

    Cited by:

    1. Chew Lian Chua & Peter Summers, 2004. "Structural Error Correction Model: A Bayesian Perspective," Econometric Society 2004 Far Eastern Meetings 702, Econometric Society.

  18. Gianni Amisano & Massimiliano Serati, 2003. "What goes up sometimes stays up: shocks and institutions as determinants of unemployment persistence," Scottish Journal of Political Economy, Scottish Economic Society, vol. 50(4), pages 440-470, September.
    See citations under working paper version above.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.