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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. Moench, Emanuel & Soofi-Siavash, Soroosh, 2022. "What moves treasury yields?," Journal of Financial Economics, Elsevier, vol. 146(3), pages 1016-1043.
    2. Efrem Castelnuovo, 2019. "Yield Curve and Financial Uncertainty: Evidence Based on US Data," "Marco Fanno" Working Papers 0234, Dipartimento di Scienze Economiche "Marco Fanno".
    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. 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. 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.
    2. 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.
    3. 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.
    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, October –.
    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.

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

    Cited by:

    1. 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.
    2. 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.
    3. Jonas Dovern & Hans Manner, 2018. "Order Invariant Tests for Proper Calibration of Multivariate Density Forecasts," CESifo Working Paper Series 7023, CESifo.
    4. Tan, Fei, 2018. "A Frequency-Domain Approach to Dynamic Macroeconomic Models," MPRA Paper 90487, University Library of Munich, Germany.
    5. Florian Eckert & Rob J Hyndman & Anastasios Panagiotelis, 2019. "Forecasting Swiss Exports Using Bayesian Forecast Reconciliation," Monash Econometrics and Business Statistics Working Papers 14/19, Monash University, Department of Econometrics and Business Statistics.
    6. Ross Askanazi & Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2018. "On the Comparison of Interval Forecasts," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 953-965, November.
    7. Laura Liu, 2018. "Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective," Papers 1805.04178, arXiv.org, revised Oct 2021.
    8. Florian Huber & Gregor Kastner & Martin Feldkircher, 2016. "Should I stay or should I go? A latent threshold approach to large-scale mixture innovation models," Papers 1607.04532, arXiv.org, revised Jul 2018.
    9. Čapek, Jan & Crespo Cuaresma, Jesús & Hauzenberger, Niko & Reichel, Vlastimil, 2023. "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1820-1838.
    10. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian vector autoregressions," LSE Research Online Documents on Economics 87393, London School of Economics and Political Science, LSE Library.
    11. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Paper 2019/2, Norges Bank.
    12. 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.
    13. Marco Del Negro & Raiden B. Hasegawa & Frank Schorfheide, 2014. "Dynamic Prediction Pools: An Investigation of Financial Frictions and Forecasting Performance," PIER Working Paper Archive 14-034, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    14. Christian Hotz-Behofsits & Florian Huber & Thomas O. Zorner, 2018. "Predicting crypto-currencies using sparse non-Gaussian state space models," Papers 1801.06373, arXiv.org, revised Feb 2018.
    15. 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).
    16. Chiu, Ching-Wai (Jeremy) & Mumtaz, Haroon & Pintér, Gábor, 2017. "Forecasting with VAR models: Fat tails and stochastic volatility," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1124-1143.
    17. Warne, Anders, 2023. "DSGE model forecasting: rational expectations vs. adaptive learning," Working Paper Series 2768, European Central Bank.
    18. Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," Working Papers 21-06, Federal Reserve Bank of Philadelphia.
    19. 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.
    20. Ho, Paul & Lubik, Thomas A. & Matthes, Christian, 2024. "Averaging impulse responses using prediction pools," Journal of Monetary Economics, Elsevier, vol. 146(C).
    21. 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.
    22. 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.
    23. Marcellino, Massimiliano & Abbate, Angela, 2016. "Point, interval and density forecasts of exchange rates with time-varying parameter models," CEPR Discussion Papers 11559, C.E.P.R. Discussion Papers.
    24. 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.
    25. Hauber, Philipp, 2022. "Real-time nowcasting with sparse factor models," EconStor Preprints 251551, ZBW - Leibniz Information Centre for Economics.
    26. Loria, Francesca & Matthes, Christian & Wang, Mu-Chun, 2022. "Economic theories and macroeconomic reality," Journal of Monetary Economics, Elsevier, vol. 126(C), pages 105-117.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. 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.
    32. 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.
    33. McAdam, Peter & Warne, Anders, 2018. "Euro area real-time density forecasting with financial or labor market frictions," Working Paper Series 2140, European Central Bank.
    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. 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.
    36. 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.
    37. Drachal, Krzysztof, 2021. "Forecasting crude oil real prices with averaging time-varying VAR models," Resources Policy, Elsevier, vol. 74(C).

  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 Foerster & Juan F. Rubio-Ramirez & Daniel F. Waggoner & Tao Zha, 2013. "Perturbation methods for Markov-switching DSGE models," FRB Atlanta Working Paper 2013-01, Federal Reserve Bank of Atlanta.
    2. Gianni Amisano & Oreste Tristani, 2019. "Uncertainty Shocks, Monetary Policy and Long-Term Interest Rates," Finance and Economics Discussion Series 2019-024, Board of Governors of the Federal Reserve System (U.S.).
    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. Paolo Andreini & Cosimo Izzo & Giovanni Ricco, 2020. "Deep Dynamic Factor Models," Papers 2007.11887, arXiv.org, revised May 2023.
    5. Andrew Foerster & Juan F. Rubio‐Ramírez & Daniel F. Waggoner & Tao Zha, 2016. "Perturbation methods for Markov‐switching dynamic stochastic general equilibrium models," Quantitative Economics, Econometric Society, vol. 7(2), pages 637-669, July.
    6. 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.
    7. Viktors Ajevskis, 2013. "Non-Local Solutions to Dynamic Equilibrium Models: the Approximate Stable Manifolds Approach," Working Papers 2013/03, Latvijas Banka.
    8. Hall, Jamie, 2012. "Rapid estimation of nonlinear DSGE models," MPRA Paper 41218, University Library of Munich, Germany.
    9. 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.
    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. Gianni Amisano & Oreste Tristani, 2023. "Monetary policy and long‐term interest rates," Quantitative Economics, Econometric Society, vol. 14(2), pages 689-716, May.
    13. 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.
    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 21/13, Institute for Fiscal Studies.
    16. 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.

  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. Anders Warne & Günter Coenen & Kai Christoffel, 2017. "Marginalized Predictive Likelihood Comparisons of Linear Gaussian State‐Space Models with Applications to DSGE, DSGE‐VAR, and VAR Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 103-119, January.
    4. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    5. Kolasa, Marcin & Rubaszek, Michał, 2014. "Forecasting with DSGE models with financial frictions," Dynare Working Papers 40, CEPREMAP.
    6. Erlan Konebayev, 2022. "Forecasting a commodity-exporting small open developing economy using DSGE and DSGE-BVAR," NAC Analytica Working Paper 24, NAC Analytica, Nazarbayev University, revised May 2022.
    7. Waggoner, Daniel F. & Zha, Tao, 2012. "Confronting model misspecification in macroeconomics," Journal of Econometrics, Elsevier, vol. 171(2), pages 167-184.
    8. McAdam, Peter & Warne, Anders, 2018. "Euro area real-time density forecasting with financial or labor market frictions," Working Paper Series 2140, European Central Bank.

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

    Cited by:

    1. Hauzenberger, Niko & Huber, Florian, 2018. "Model instability in predictive exchange rate regressions," Department of Economics Working Paper Series 276, WU Vienna University of Economics and Business.
    2. 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.
    3. 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.
    4. Florian Huber & Manfred M. Fischer, 2018. "A Markov Switching Factor‐Augmented VAR Model for Analyzing US Business Cycles and Monetary Policy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(3), pages 575-604, June.
    5. 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.
    6. 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.).
    7. Claudiu Tiberiu Albulescu & Daniel Goyeau & Cornel Oros, 2015. "On the Long Run Money-Prices Relationship in CEE Countries," Post-Print hal-01257389, HAL.
    8. 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).
    9. Scott A. Brave & Jose A. Lopez, 2019. "Calibrating Macroprudential Policy to Forecasts of Financial Stability," International Journal of Central Banking, International Journal of Central Banking, vol. 15(1), pages 1-59, March.
    10. Cruz, Christopher John & Mapa, Dennis, 2013. "An Early Warning System for Inflation in the Philippines Using Markov-Switching and Logistic Regression Models," MPRA Paper 50078, University Library of Munich, Germany.
    11. 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.
    12. 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.
    13. Utkarsh Kumar & Wasim Ahmad & Gazi Salah Uddin, 2024. "Bayesian Markov switching model for BRICS currencies' exchange rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2322-2340, September.
    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. 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.
    16. 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.
    17. Garcés Díaz Daniel, 2016. "Changes in Inflation Predictability in Major Latin American Countries," Working Papers 2016-20, Banco de México.
    18. Wojciech Charemza & Svetlana Makarova & Imran Shah, 2015. "Making the most of high inflation," Applied Economics, Taylor & Francis Journals, vol. 47(34-35), pages 3723-3739, July.
    19. Sylvia Kaufmann, 2011. "K-state switching models with endogenous transition distributions," Working Papers 2011-13, Swiss National Bank.
    20. Jung, Alexander, 2024. "The quantity theory of money, 1870-2020," Working Paper Series 2940, European Central Bank.
    21. Piergiorgio Alessandri & Haroon Mumtaz, 2017. "Financial conditions and density forecasts for US output and inflation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 24, pages 66-78, March.
    22. 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.
    23. Goodarzi, Milad & Meinerding, Christoph, 2023. "Asset allocation with recursive parameter updating and macroeconomic regime identifiers," Discussion Papers 06/2023, Deutsche Bundesbank.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. Hauzenberger Niko & Huber Florian & Pfarrhofer Michael & Zörner Thomas O., 2021. "Stochastic model specification in Markov switching vector error correction models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-17, April.
    29. Mandler, Martin & Scharnagl, Michael, 2014. "Money growth and consumer price inflation in the euro area: A wavelet analysis," Discussion Papers 33/2014, Deutsche Bundesbank.
    30. 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.
    31. 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.
    32. 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.
    33. 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.
    34. 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.
    35. 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.
    36. Claudio Borio & Marco Jacopo Lombardi & James Yetman & Egon Zakrajsek, 2023. "The two-regime view of inflation," BIS Papers, Bank for International Settlements, number 133, October –.
    37. Blagov, Boris & Funke, Michael, 2014. "The credibility of Hong Kong's currency board system: Looking through the prism of MS-VAR models with time-varying transition probabilities," BOFIT Discussion Papers 15/2014, Bank of Finland Institute for Emerging Economies (BOFIT).
    38. 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.
    39. 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).
    40. 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.
    41. Hauzenberger , Niko & Huber, Florian & Klieber, Karin & Marcellino, Massimiliano, 2024. "Bayesian Neural Networks for Macroeconomic Analysis," CEPR Discussion Papers 19381, C.E.P.R. Discussion Papers.
    42. 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.
    43. Gabriel Rodriguez-Rondon, 2024. "Underlying Core Inflation with Multiple Regimes," Papers 2411.12845, arXiv.org.
    44. 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.
    45. 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.
    46. Ringwald, Leopold & Zörner, Thomas O., 2023. "The money-inflation nexus revisited," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 293-333.
    47. Antonio N. Bojanic, 2021. "A Markov-Switching Model of Inflation in Bolivia," Economies, MDPI, vol. 9(1), pages 1-18, March.
    48. 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.
    49. 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.

  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. 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.
    2. Ales Marsal & Lorant Kaszab & Roman Horvath, 2017. "Government Spending and the Term Structure of Interest Rates in a DSGE Model," Working and Discussion Papers WP 3/2017, Research Department, National Bank of Slovakia.
    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. 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.
    2. 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.
    3. António Afonso & Jaromír Baxa & Michal Slavík, 2011. "Fiscal developments and financial stress: a threshold VAR analysis," Working Papers IES 2011/16, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Aug 2011.
    4. 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.
    5. 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.
    6. Sergio Sola, 2013. "Temporary and Persistent Fiscal Policy Shocks," IHEID Working Papers 06-2013, Economics Section, The Graduate Institute of International Studies.
    7. Michal Brzoza-Brzezina & Krzysztof Makarski & Grzegorz Wesolowski, 2013. "Would it have paid to be in the eurozone?," Working Papers 70, Department of Applied Econometrics, Warsaw School of Economics.
    8. 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.
    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. 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).
    2. 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.
    3. Hansen, Lars Peter & Sargent, Thomas J., 2022. "Structured ambiguity and model misspecification," Journal of Economic Theory, Elsevier, vol. 199(C).
    4. 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.
    5. Buncic, Daniel & Müller, Oliver, 2017. "Measuring the output gap in Switzerland with linear opinion pools," Economic Modelling, Elsevier, vol. 64(C), pages 153-171.
    6. Mike Tsionas & Christopher F. Parmeter & Valentin Zelenyuk, 2023. "Bayesian Artificial Neural Networks for Frontier Efficiency Analysis," CEPA Working Papers Series WP012023, School of Economics, University of Queensland, Australia.
    7. Tan, Fei, 2018. "A Frequency-Domain Approach to Dynamic Macroeconomic Models," MPRA Paper 90487, University Library of Munich, Germany.
    8. 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.
    9. 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.
    10. Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," CREATES Research Papers 2018-01, Department of Economics and Business Economics, Aarhus University.
    11. 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.
    12. 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.
    13. Anders Warne & Günter Coenen & Kai Christoffel, 2017. "Marginalized Predictive Likelihood Comparisons of Linear Gaussian State‐Space Models with Applications to DSGE, DSGE‐VAR, and VAR Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 103-119, January.
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    22. 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".
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    38. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Paper 2019/2, Norges Bank.
    39. Cristina Conflitti & Christine De Mol & Domenico Giannone, 2012. "Optimal Combination of Survey Forecasts," Working Papers ECARES ECARES 2012-023, ULB -- Universite Libre de Bruxelles.
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    43. Guofu Zhou, 2018. "Measuring Investor Sentiment," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 239-259, November.
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    46. Jean-Guillaume Sahuc & Matteo Mogliani & Laurent Ferrara, 2022. "High-frequency monitoring of growth at risk," Post-Print hal-03361425, HAL.
    47. 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.
    48. Marco Del Negro & Raiden B. Hasegawa & Frank Schorfheide, 2014. "Dynamic Prediction Pools: An Investigation of Financial Frictions and Forecasting Performance," PIER Working Paper Archive 14-034, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    49. Guérin, Pierre & Leiva-Leon, Danilo, 2017. "Model averaging in Markov-switching models: Predicting national recessions with regional data," Economics Letters, Elsevier, vol. 157(C), pages 45-49.
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    51. 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.
    52. Cheng, Xu & Hansen, Bruce E., 2015. "Forecasting with factor-augmented regression: A frequentist model averaging approach," Journal of Econometrics, Elsevier, vol. 186(2), pages 280-293.
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    147. 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.
    148. 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.
    149. Graziano Moramarco, 2021. "Regime-Switching Density Forecasts Using Economists' Scenarios," Papers 2110.13761, arXiv.org, revised Feb 2024.
    150. Tsionas, Mike G., 2022. "Random and Markov switching exponential smoothing models," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    151. 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.
    152. Canepa, Alessandra & Zanetti Chini, Emilio & Alqaralleh, Huthaifa, 2020. "Global Cities and Local Challenges: Booms and Busts in the London Real Estate Market," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202011, University of Turin.
    153. 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.
    154. Kenichiro McAlinn & Kosaku Takanashi, 2019. "Mean-shift least squares model averaging," Papers 1912.01194, arXiv.org.
    155. 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.
    156. 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.
    157. McAdam, Peter & Warne, Anders, 2018. "Euro area real-time density forecasting with financial or labor market frictions," Working Paper Series 2140, European Central Bank.
    158. 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.
    159. 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.
    160. 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.
    161. 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.
    162. 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.
    163. 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.
    164. Martina Hengge, 2019. "Uncertainty as a Predictor of Economic Activity," IHEID Working Papers 19-2019, Economics Section, The Graduate Institute of International Studies.
    165. 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.
    166. 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.
    167. Sean Langcake & Tim Robinson, 2013. "An Empirical BVAR-DSGE Model of the Australian Economy," RBA Research Discussion Papers rdp2013-07, Reserve Bank of Australia.
    168. 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.
    169. 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.
    170. 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.
    171. Christian Kascha & Francesco Ravazzolo, 2008. "Combining inflation density forecasts," Working Paper 2008/22, Norges Bank.
    172. 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.
    173. Elliott, Graham & Gargano, Antonio & Timmermann, Allan, 2013. "Complete subset regressions," Journal of Econometrics, Elsevier, vol. 177(2), pages 357-373.
    174. 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.
    175. 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.
    176. 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.
    177. 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.
    178. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2010. "Forecasting with DSGE models," Working Paper Series 1185, European Central Bank.
    179. 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.
    180. 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.
    181. Allan Timmermann, 2018. "Forecasting Methods in Finance," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 449-479, November.
    182. Enrique Moral-Benito, 2015. "Model Averaging In Economics: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 46-75, February.
    183. Saurabh Bansal & Genaro J. Gutierrez, 2020. "Estimating Uncertainties Using Judgmental Forecasts with Expert Heterogeneity," Operations Research, INFORMS, vol. 68(2), pages 363-380, March.
    184. Nikolay Gospodinov & Esfandiar Maasoumi, 2017. "General Aggregation of Misspecified Asset Pricing Models," FRB Atlanta Working Paper 2017-10, Federal Reserve Bank of Atlanta.
    185. 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.
    186. 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.
    187. Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
    188. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2013. "Predictive likelihood comparisons with DSGE and DSGE-VAR models," Working Paper Series 1536, European Central Bank.
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  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. 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".
    2. 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).
    3. Martin Meier & Enrico Minelli & Herakles Polemarchakis, 2009. "Competitive Markets with Private Information on Both Sides," Working Papers 0917, University of Brescia, Department of Economics.
    4. 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.
    5. Hafner, Christian & Manner H., 2012. "Dynamic stochastic copula models: Estimation, inference and applications," LIDAM Reprints ISBA 2012022, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Rosella Levaggi & Francesco Menoncin, 2009. "Decentralized provision of merit and impure public goods," Working Papers 0909, University of Brescia, Department of Economics.
    7. Alberto Bisin & John Geanakoplos & Piero Gottardi & Enrico Minelli & Heracles Polemarchakis, 2009. "Markets and Contracts," Working Papers 0915, University of Brescia, Department of Economics.
    8. Francesco Menoncin & Paolo Panteghini, 2009. "Retrospective Capital Gains taxation in the real world," Working Papers 0910, University of Brescia, Department of Economics.
    9. Alessandra Del Boca & Michele Fratianni & Franco Spinelli & Carmine Trecroci, 2009. "The Phillips curve and the Italian lira, 1861-1998," Working Papers 0908, University of Brescia, Department of Economics.
    10. 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.
    11. 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.

  12. 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. 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).
    2. Martin Meier & Enrico Minelli & Herakles Polemarchakis, 2009. "Competitive Markets with Private Information on Both Sides," Working Papers 0917, University of Brescia, Department of Economics.
    3. 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.
    4. Rosella Levaggi & Francesco Menoncin, 2009. "Decentralized provision of merit and impure public goods," Working Papers 0909, University of Brescia, Department of Economics.
    5. Alberto Bisin & John Geanakoplos & Piero Gottardi & Enrico Minelli & Heracles Polemarchakis, 2009. "Markets and Contracts," Working Papers 0915, 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. Alessandra Del Boca & Michele Fratianni & Franco Spinelli & Carmine Trecroci, 2009. "The Phillips curve and the Italian lira, 1861-1998," Working Papers 0908, University of Brescia, Department of Economics.
    8. 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.
    9. 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.

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

    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. Panagiotidis, Theodore & Papapanagiotou, Georgios & Stengos, Thanasis, 2022. "On the volatility of cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 62(C).
    5. Jonas Dovern & Martin Feldkircher & Florian Huber, 2015. "Does Joint Modelling of the World Economy Pay Off? Evaluating Global Forecasts from a Bayesian GVAR," Working Papers 200, Oesterreichische Nationalbank (Austrian Central Bank).
    6. Ng, Jason & Forbes, Catherine S. & Martin, Gael M. & McCabe, Brendan P.M., 2013. "Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models," International Journal of Forecasting, Elsevier, vol. 29(3), pages 411-430.
    7. Huber, Florian, 2017. "Structural breaks in Taylor rule based exchange rate models — Evidence from threshold time varying parameter models," Economics Letters, Elsevier, vol. 150(C), pages 48-52.
    8. Mark J. Jensen & John M. Maheu, 2008. "Bayesian semiparametric stochastic volatility modeling," FRB Atlanta Working Paper 2008-15, Federal Reserve Bank of Atlanta.
    9. 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.
    10. Anders Warne & Günter Coenen & Kai Christoffel, 2017. "Marginalized Predictive Likelihood Comparisons of Linear Gaussian State‐Space Models with Applications to DSGE, DSGE‐VAR, and VAR Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 103-119, January.
    11. 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.
    12. 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.).
    13. 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.
    14. Berg, Tim O. & Henzel, Steffen R., 2015. "Point and density forecasts for the euro area using Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
    15. Timmermann, Allan & Pettenuzzo, Davide, 2016. "Forecasting Macroeconomic Variables under Model Instability," CEPR Discussion Papers 11355, C.E.P.R. Discussion Papers.
    16. 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.
    17. 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.
    18. 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.
    19. Roberto Leon-Gonzalez & Fuyu Yang, 2017. "Bayesian inference and forecasting in the stationary bilinear model," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(20), pages 10327-10347, October.
    20. Hauzenberger, Niko & Huber, Florian, 2018. "Model instability in predictive exchange rate regressions," Department of Economics Working Paper Series 276, WU Vienna University of Economics and Business.
    21. 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.
    22. Anna Kormilitsina & Sarah Zubairy, 2015. "Propagation Mechanisms for Government Spending Shocks: A Bayesian Comparison," EcoMod2015 8646, EcoMod.
    23. Laura Liu, 2018. "Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective," Papers 1805.04178, arXiv.org, revised Oct 2021.
    24. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    25. Florian Huber & Gregor Kastner & Martin Feldkircher, 2016. "Should I stay or should I go? A latent threshold approach to large-scale mixture innovation models," Papers 1607.04532, arXiv.org, revised Jul 2018.
    26. Koop, Gary & Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Bayesian compressed vector autoregressions," Journal of Econometrics, Elsevier, vol. 210(1), pages 135-154.
    27. 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.
    28. Boyuan Zhang, 2022. "Incorporating Prior Knowledge of Latent Group Structure in Panel Data Models," Papers 2211.16714, arXiv.org, revised Oct 2023.
    29. Minchul Shin & Molin Zhong, 2015. "Does Realized Volatility Help Bond Yield Density Prediction?," Finance and Economics Discussion Series 2015-115, Board of Governors of the Federal Reserve System (U.S.).
    30. Timmermann, Allan & Pettenuzzo, Davide & Gargano, Antonio, 2014. "Bond Return Predictability: Economic Value and Links to the Macroeconomy," CEPR Discussion Papers 10104, C.E.P.R. Discussion Papers.
    31. Wagner Piazza Gaglianone & Luiz Renato Lima, 2014. "Constructing Optimal Density Forecasts From Point Forecast Combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 736-757, August.
    32. Michael Pfarrhofer, 2024. "Forecasts with Bayesian vector autoregressions under real time conditions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 771-801, April.
    33. 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.
    34. Goldman, Elena, 2023. "Uncertainty in systemic risks rankings: Bayesian and frequentist analysis," Finance Research Letters, Elsevier, vol. 56(C).
    35. Byrne, Joseph & Cao, Shuo & Korobilis, Dimitris, 2015. "Term Structure Dynamics, Macro-Finance Factors and Model Uncertainty," MPRA Paper 63844, University Library of Munich, Germany.
    36. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    37. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2012. "Real-time nowcasting with a Bayesian mixed frequency model with stochastic volatility," Working Papers (Old Series) 1227, Federal Reserve Bank of Cleveland.
    38. Marcellino, Massimiliano & Clark, Todd & Carriero, Andrea & Mertens, Elmar, 2021. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," CEPR Discussion Papers 15964, C.E.P.R. Discussion Papers.
    39. 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.
    40. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2012. "Common drifting volatility in large Bayesian VARs," Working Papers (Old Series) 1206, Federal Reserve Bank of Cleveland.
    41. Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Adaptive hierarchical priors for high-dimensional vector autoregressions," Journal of Econometrics, Elsevier, vol. 212(1), pages 241-271.
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    180. 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.
    181. 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).
    182. Yong Song, 2014. "Modelling Regime Switching And Structural Breaks With An Infinite Hidden Markov Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 825-842, August.
    183. 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.
    184. Karapanagiotidis, Paul, 2012. "Improving Bayesian VAR density forecasts through autoregressive Wishart Stochastic Volatility," MPRA Paper 38885, University Library of Munich, Germany.
    185. 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.
    186. 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.
    187. 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.
    188. 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.
    189. 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.
    190. 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.
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    193. 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.
    194. 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.
    195. 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.
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    198. 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.
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    200. 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.
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    1. 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.
    2. Mike Tsionas & Christopher F. Parmeter & Valentin Zelenyuk, 2023. "Bayesian Artificial Neural Networks for Frontier Efficiency Analysis," CEPA Working Papers Series WP012023, School of Economics, University of Queensland, Australia.
    3. 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.
    4. Joshua C.C. Chan & Angelia L. Grant, 2016. "Reconciling output gaps: unobserved components model and Hodrick-Prescott filter," CAMA Working Papers 2016-44, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    5. Gary Koop & Roberto Leon-Gonzalez & Rodney Strachan, 2011. "Bayesian Inference in the Time Varying Cointegration Model," Working Papers 1121, University of Strathclyde Business School, Department of Economics.
    6. Joshua C.C. Chan & Gary Koop & Roberto Leon-Gonzalez & Rodney W. Strachan, 2010. "Time Varying Dimension Models," Working Paper series 44_10, Rimini Centre for Economic Analysis.
    7. 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.
    8. 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.
    9. 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.
    10. Francesco Giancaterini & Alain Hecq & Claudio Morana, 2022. "Is climate change time reversible?," Papers 2205.07579, arXiv.org, revised Nov 2022.
    11. 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.
    12. 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.
    13. 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.
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    15. 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.
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    17. Gary Koop & Dimitris Korobilis, 2012. "Forecasting Inflation Using Dynamic Model Averaging," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(3), pages 867-886, August.
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    21. Pelenis, Justinas, 2012. "Bayesian Semiparametric Regression," Economics Series 285, Institute for Advanced Studies.
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    23. 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.
    24. 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.
    25. Tsionas, Mike G., 2021. "Bayesian forecasting with the structural damped trend model," International Journal of Production Economics, Elsevier, vol. 234(C).
    26. 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).
    27. Koop, Gary & Korobilis, Dimitris, 2009. "UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?," SIRE Discussion Papers 2009-40, Scottish Institute for Research in Economics (SIRE).
    28. Rangan Gupta & Shawkat Hammoudeh & Won Joong Kim & Beatrice D. Simo-Kengne, 2013. "Forecasting China’s Foreign Exchange Reserves Using Dynamic Model Averaging: The Role of Macroeconomic Fundamentals, Financial Stress and Economic Uncertainty," Working Papers 201338, University of Pretoria, Department of Economics.
    29. 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.
    30. Martin Meier & Enrico Minelli & Herakles Polemarchakis, 2009. "Competitive Markets with Private Information on Both Sides," Working Papers 0917, University of Brescia, Department of Economics.
    31. 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.
    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. Joshua C. C. Chan, 2020. "Large Bayesian VARs: A Flexible Kronecker Error Covariance Structure," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 68-79, January.
    34. Mauro Bernardi & Lea Petrella, 2015. "Interconnected Risk Contributions: A Heavy-Tail Approach to Analyze U.S. Financial Sectors," JRFM, MDPI, vol. 8(2), pages 1-29, April.
    35. 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.
    36. Hou, Chenghan, 2017. "Infinite hidden markov switching VARs with application to macroeconomic forecast," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1025-1043.
    37. 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.
    38. Amisano, Gianni & Geweke, John, 2008. "Comparing and evaluating Bayesian predictive distributions of assets returns," Working Paper Series 969, European Central Bank.
    39. 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.
    40. Chan, Joshua C.C., 2013. "Moving average stochastic volatility models with application to inflation forecast," Journal of Econometrics, Elsevier, vol. 176(2), pages 162-172.
    41. Rosella Levaggi & Francesco Menoncin, 2009. "Decentralized provision of merit and impure public goods," Working Papers 0909, University of Brescia, Department of Economics.
    42. Jochmann, Markus & Koop, Gary & Strachan, Rodney W., 2010. "Bayesian forecasting using stochastic search variable selection in a VAR subject to breaks," International Journal of Forecasting, Elsevier, vol. 26(2), pages 326-347, April.
    43. Alberto Bisin & John Geanakoplos & Piero Gottardi & Enrico Minelli & Heracles Polemarchakis, 2009. "Markets and Contracts," Working Papers 0915, University of Brescia, Department of Economics.
    44. Omokolade Akinsomi & Goodness C. Aye & Vassilios Babalos & Fotini Economou & Rangan Gupta, 2016. "Real estate returns predictability revisited: novel evidence from the US REITs market," Empirical Economics, Springer, vol. 51(3), pages 1165-1190, November.
    45. Francesco Menoncin & Paolo Panteghini, 2009. "Retrospective Capital Gains taxation in the real world," Working Papers 0910, University of Brescia, Department of Economics.
    46. Joshua C.C. Chan & Gary Koop, 2013. "Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables," ANU Working Papers in Economics and Econometrics 2013-603, Australian National University, College of Business and Economics, School of Economics.
    47. 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.
    48. 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.
    49. Luis A. Gil-Alana & Rangan Gupta & Olusanya E. Olubusoye & OlaOluwa S. Yaya, 2015. "Time Series Analysis of Persistence in Crude Oil Price Volatility across Bull and Bear Regimes," Working Papers 201580, University of Pretoria, Department of Economics.
    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. Bai, Jushan & Wang, Peng, 2011. "Conditional Markov chain and its application in economic time series analysis," MPRA Paper 33369, University Library of Munich, Germany.
    52. Alessandra Del Boca & Michele Fratianni & Franco Spinelli & Carmine Trecroci, 2009. "The Phillips curve and the Italian lira, 1861-1998," Working Papers 0908, University of Brescia, Department of Economics.
    53. Anderson, Richard G. & Binner, Jane M. & Schmidt, Vincent A., 2012. "Connectionist-based rules describing the pass-through of individual goods prices into trend inflation in the United States," Economics Letters, Elsevier, vol. 117(1), pages 174-177.
    54. 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.
    55. 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.
    56. Jan Prüser, 2021. "Forecasting US inflation using Markov dimension switching," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 481-499, April.
    57. Roberto Leon-Gonzalez & Blessings Majoni, 2023. "Exact Likelihood for Inverse Gamma Stochastic Volatility Models," Working Paper series 23-11, Rimini Centre for Economic Analysis.
    58. Pelenis, Justinas, 2014. "Bayesian regression with heteroscedastic error density and parametric mean function," Journal of Econometrics, Elsevier, vol. 178(P3), pages 624-638.
    59. Jeff Fleming & Chris Kirby, 2013. "Component-Driven Regime-Switching Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 11(2), pages 263-301, March.
    60. 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.
    61. 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.
    62. 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.
    63. 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.
    64. 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.
    65. Stylianos Asimakopoulos & Marco Lorusso & Francesco Ravazzolo, 2023. "A Bayesian DSGE Approach to Modelling Cryptocurrency"," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 51, pages 1012-1035, December.
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    67. Luis Uzeda, 2022. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 25-53, Emerald Group Publishing Limited.
    68. 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.
    69. 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.
    70. 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.
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    72. 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.
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    1. 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.
    2. 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.
    3. 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.
    4. Malik, Sheheryar & Pitt, Michael K., 2011. "Particle filters for continuous likelihood evaluation and maximisation," Journal of Econometrics, Elsevier, vol. 165(2), pages 190-209.
    5. 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.
    6. 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).
    7. 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.
    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. Tommaso Proietti & Alessandra Luati, 2013. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 15, pages 334-362, Edward Elgar Publishing.
    10. 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," PSE Working Papers hal-04219920, HAL.
      • 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.
    11. 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).
    12. 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.
    13. Martin Meier & Enrico Minelli & Herakles Polemarchakis, 2009. "Competitive Markets with Private Information on Both Sides," Working Papers 0917, University of Brescia, Department of Economics.
    14. 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.
    15. 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.
    16. 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.
    17. Viktors Ajevskis, 2013. "Non-Local Solutions to Dynamic Equilibrium Models: the Approximate Stable Manifolds Approach," Working Papers 2013/03, Latvijas Banka.
    18. Hall, Jamie, 2012. "Rapid estimation of nonlinear DSGE models," MPRA Paper 41218, University Library of Munich, Germany.
    19. 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.
    20. 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.
    21. Winschel, Viktor & Krätzig, Markus, 2008. "Solving, estimating and selecting nonlinear dynamic models without the curse of dimensionality," SFB 649 Discussion Papers 2008-018, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    22. 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.
    23. Rosella Levaggi & Francesco Menoncin, 2009. "Decentralized provision of merit and impure public goods," Working Papers 0909, University of Brescia, Department of Economics.
    24. Alberto Bisin & John Geanakoplos & Piero Gottardi & Enrico Minelli & Heracles Polemarchakis, 2009. "Markets and Contracts," Working Papers 0915, University of Brescia, Department of Economics.
    25. Francesco Menoncin & Paolo Panteghini, 2009. "Retrospective Capital Gains taxation in the real world," Working Papers 0910, University of Brescia, Department of Economics.
    26. Fleischhacker, Jan, 2024. "Fiscal policy and the business cycle: An argument for non-linear policy rules," MPRA Paper 122497, University Library of Munich, Germany.
    27. 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.
    28. 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.
    29. 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.
    30. Alessandra Del Boca & Michele Fratianni & Franco Spinelli & Carmine Trecroci, 2009. "The Phillips curve and the Italian lira, 1861-1998," Working Papers 0908, University of Brescia, Department of Economics.
    31. 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.
    32. 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.
    33. 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.
    34. 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.
    35. 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 Sep 2024.
    36. 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.
    37. 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.
    38. Yang, Yuan & Wang, Lu, 2015. "An Improved Auxiliary Particle Filter for Nonlinear Dynamic Equilibrium Models," Dynare Working Papers 47, CEPREMAP.
    39. Taeyoung Doh, 2009. "Yield curve in an estimated nonlinear macro model," Research Working Paper RWP 09-04, Federal Reserve Bank of Kansas City.
    40. 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.
    41. 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.
    42. 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.
    43. Yang, Yuan & Wang, Lu, 2016. "An auxiliary particle filter for nonlinear dynamic equilibrium models," Economics Letters, Elsevier, vol. 144(C), pages 112-114.
    44. 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.
    45. Hall, Jamie, 2012. "Consumption dynamics in general equilibrium," MPRA Paper 43933, University Library of Munich, Germany.
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    Cited by:

    1. 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.
    2. 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.
    3. Winschel, Viktor & Krätzig, Markus, 2008. "Solving, estimating and selecting nonlinear dynamic models without the curse of dimensionality," SFB 649 Discussion Papers 2008-018, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. 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.
    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. 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).
    3. 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.
    4. 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.
    5. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    6. 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.
    7. 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.
    8. Delle Monache, Davide & Petrella, Ivan, 2017. "Adaptive models and heavy tails with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 33(2), pages 482-501.
    9. Jonas Dovern & Martin Feldkircher & Florian Huber, 2015. "Does Joint Modelling of the World Economy Pay Off? Evaluating Global Forecasts from a Bayesian GVAR," Working Papers 200, Oesterreichische Nationalbank (Austrian Central Bank).
    10. Michael Clements, 2016. "Are Macroeconomic Density Forecasts Informative?," ICMA Centre Discussion Papers in Finance icma-dp2016-02, Henley Business School, University of Reading.
    11. 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.
    12. Ng, Jason & Forbes, Catherine S. & Martin, Gael M. & McCabe, Brendan P.M., 2013. "Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models," International Journal of Forecasting, Elsevier, vol. 29(3), pages 411-430.
    13. Huber, Florian, 2017. "Structural breaks in Taylor rule based exchange rate models — Evidence from threshold time varying parameter models," Economics Letters, Elsevier, vol. 150(C), pages 48-52.
    14. 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.
    15. Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," CREATES Research Papers 2018-01, Department of Economics and Business Economics, Aarhus University.
    16. 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.
    17. 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.
    18. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
    19. Barbara Rossi & Tatevik Sekhposyan, 2015. "Alternative Tests for Correct Specification of Conditional Predictive Densities," Working Papers 758, Barcelona School of Economics.
    20. Mackowiak, Bartosz & Jarocinski, Marek, 2013. "Granger-Causal-Priority and Choice of Variables in Vector Autoregressions," CEPR Discussion Papers 9686, C.E.P.R. Discussion Papers.
    21. Giacomini, Raffaella & Ragusa, Giuseppe & Altavilla, Carlo, 2013. "Anchoring the Yield Curve Using Survey Expectations," CEPR Discussion Papers 9738, C.E.P.R. Discussion Papers.
    22. Rossi, Barbara & Odendahl, Florens & Sekhposyan, Tatevik, 2020. "Comparing Forecast Performance with State Dependence," CEPR Discussion Papers 15217, C.E.P.R. Discussion Papers.
    23. 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.
    24. Berg, Tim O. & Henzel, Steffen R., 2015. "Point and density forecasts for the euro area using Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
    25. 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.
    26. 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.
    27. Timmermann, Allan & Pettenuzzo, Davide, 2016. "Forecasting Macroeconomic Variables under Model Instability," CEPR Discussion Papers 11355, C.E.P.R. Discussion Papers.
    28. Guglielmo Maria Caporale & Luca Onorante & Paolo Paesani, 2009. "Inflation and Inflation Uncertainty in the Euro Area," CESifo Working Paper Series 2720, CESifo.
    29. 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.
    30. 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.
    31. Anne Opschoor & André Lucas, 2019. "Time-varying tail behavior for realized kernels," Tinbergen Institute Discussion Papers 19-051/IV, Tinbergen Institute.
    32. 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.
    33. Rossi, Barbara & Sekhposyan, Tatevik, 2013. "Conditional predictive density evaluation in the presence of instabilities," Journal of Econometrics, Elsevier, vol. 177(2), pages 199-212.
    34. Buncic, Daniel, 2009. "Understanding forecast failure in ESTAR models of real exchange rates," MPRA Paper 13121, University Library of Munich, Germany.
    35. 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.
    36. Gian Piero Aielli, 2011. "Dynamic Conditional Correlation: On properties and estimation," "Marco Fanno" Working Papers 0142, Dipartimento di Scienze Economiche "Marco Fanno".
    37. Giacomini, Raffaella, 2014. "Economic theory and forecasting: lessons from the literature," CEPR Discussion Papers 10201, C.E.P.R. Discussion Papers.
    38. Laura Liu, 2018. "Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective," Papers 1805.04178, arXiv.org, revised Oct 2021.
    39. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    40. Francesco Ravazzolo & Shaun P. Vahey, 2010. "Forecast densities for economic aggregates from disaggregate ensembles," Working Paper 2010/02, Norges Bank.
    41. 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.
    42. 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.
    43. Algieri, Bernardina & Leccadito, Arturo & Tunaru, Diana, 2021. "Risk premia in electricity derivatives markets," Energy Economics, Elsevier, vol. 100(C).
    44. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Post-Print halshs-02505861, HAL.
    45. Fabio Busetti & Michele Caivano & Davide Delle Monache & Claudia Pacella, 2020. "The time-varying risk of Italian GDP," Temi di discussione (Economic working papers) 1288, Bank of Italy, Economic Research and International Relations Area.
    46. Gloria Gonzalez-Rivera & Yingying Sun, 2016. "Density Forecast Evaluation in Unstable Environments," Working Papers 201606, University of California at Riverside, Department of Economics.
    47. Florens Odendahl & Barbara Rossi & Tatevik Sekhposyan, 2021. "Evaluating Forecast Performance with State Dependence," Working Papers 1295, Barcelona School of Economics.
    48. Marco J. Lombardi & Francesco Ravazzolo, 2012. "Oil price density forecasts: exploring the linkages with stock markets," Working Paper 2012/24, Norges Bank.
    49. 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.
    50. Giacomini, Raffaella & Ragusa, Giuseppe, 2011. "Incorporating theoretical restrictions into forecasting by projection methods," CEPR Discussion Papers 8604, C.E.P.R. Discussion Papers.
    51. 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.
    52. 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.
    53. Čapek, Jan & Crespo Cuaresma, Jesús & Hauzenberger, Niko & Reichel, Vlastimil, 2023. "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1820-1838.
    54. Minchul Shin & Molin Zhong, 2015. "Does Realized Volatility Help Bond Yield Density Prediction?," Finance and Economics Discussion Series 2015-115, Board of Governors of the Federal Reserve System (U.S.).
    55. Barbara Rossi & Tatevik Sekhposyan, 2013. "Evaluating predictive densities of U.S. output growth and inflation in a large macroeconomic data set," Economics Working Papers 1370, Department of Economics and Business, Universitat Pompeu Fabra.
    56. 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.
    57. Paulo Mauricio Sánchez Beltrán & Luis Fernando Melo Velandia, 2013. "Combinación de brechas del producto colombiano," Borradores de Economia 10973, Banco de la Republica.
    58. Francesco Ravazzolo & Philip Rothman, 2011. "Oil and US GDP: A Real-Time out-of Sample Examination," Working Papers No 2/2011, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    59. Wagner Piazza Gaglianone & Luiz Renato Lima, 2014. "Constructing Optimal Density Forecasts From Point Forecast Combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 736-757, August.
    60. 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.
    61. 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.
    62. 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.
    63. Philippe de Peretti & Oren Tapiero, 2014. "A GARCH analysis of dark-pool trades," Post-Print hal-00984834, HAL.
    64. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2012. "Real-time nowcasting with a Bayesian mixed frequency model with stochastic volatility," Working Papers (Old Series) 1227, Federal Reserve Bank of Cleveland.
    65. Florian Ielpo & Benoît Sévi, 2014. "Forecasting the density of oil futures," Working Papers 2014-601, Department of Research, Ipag Business School.
    66. 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.
    67. Lombardi, Marco J. & Ravazzolo, Francesco, 2016. "On the correlation between commodity and equity returns: Implications for portfolio allocation," Journal of Commodity Markets, Elsevier, vol. 2(1), pages 45-57.
    68. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Paper 2019/2, Norges Bank.
    69. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2012. "Common drifting volatility in large Bayesian VARs," Working Papers (Old Series) 1206, Federal Reserve Bank of Cleveland.
    70. 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.
    71. Lee Tae-Hwy & Wang He & Xi Zhou & Zhang Ru, 2023. "Density Forecast of Financial Returns Using Decomposition and Maximum Entropy," Journal of Econometric Methods, De Gruyter, vol. 12(1), pages 57-83, January.
    72. Cristina Conflitti & Christine De Mol & Domenico Giannone, 2012. "Optimal Combination of Survey Forecasts," Working Papers ECARES ECARES 2012-023, ULB -- Universite Libre de Bruxelles.
    73. 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.
    74. Niko Hauzenberger & Florian Huber & Luca Onorante, 2021. "Combining shrinkage and sparsity in conjugate vector autoregressive models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(3), pages 304-327, April.
    75. Georgios Anastasiades & Patrick McSharry, 2013. "Quantile Forecasting of Wind Power Using Variability Indices," Energies, MDPI, vol. 6(2), pages 1-34, February.
    76. Allayioti, Anastasia & Venditti, Fabrizio, 2024. "The role of comovement and time-varying dynamics in forecasting commodity prices," Working Paper Series 2901, European Central Bank.
    77. 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.
    78. 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.
    79. 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.
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    81. 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.
    82. 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.
    83. 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.
    84. Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2023. "Are low frequency macroeconomic variables important for high frequency electricity prices?," Economic Modelling, Elsevier, vol. 120(C).
    85. 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.
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    88. Massimiliano Caporin & Michael McAleer, 2010. "Ranking Multivariate GARCH Models by Problem Dimension," "Marco Fanno" Working Papers 0124, Dipartimento di Scienze Economiche "Marco Fanno".
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    90. 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.
    91. Chin, Kuo-Hsuan & Li, Xue, 2019. "Bayesian forecast combination in VAR-DSGE models," Journal of Macroeconomics, Elsevier, vol. 59(C), pages 278-298.
    92. 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.
    93. 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).
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    245. Kenichiro McAlinn & Kosaku Takanashi, 2019. "Mean-shift least squares model averaging," Papers 1912.01194, arXiv.org.
    246. Carlo Altavilla & Riccardo Costantini & Raffaella Giacomini, 2013. "Bond returns and market expectations," CeMMAP working papers 20/13, Institute for Fiscal Studies.
    247. 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.
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    249. 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.
    250. 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).
    251. 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.
    252. Kolassa, Stephan, 2016. "Evaluating predictive count data distributions in retail sales forecasting," International Journal of Forecasting, Elsevier, vol. 32(3), pages 788-803.
    253. McAdam, Peter & Warne, Anders, 2018. "Euro area real-time density forecasting with financial or labor market frictions," Working Paper Series 2140, European Central Bank.
    254. Aslanidis, Nektarios & Martinez, Oscar, 2021. "Correlation regimes in international equity and bond returns," Economic Modelling, Elsevier, vol. 97(C), pages 397-410.
    255. 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.
    256. 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.
    257. 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.
    258. 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.
    259. 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.
    260. 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.
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    262. 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.
    263. Kyungchul Song, 2011. "Testing Predictive Ability and Power Robustification," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 288-296, October.
    264. Rehab OSMAN, 2010. "SADC EPAs with the EU: the Right or a Blight Way for Development," EcoMod2010 259600127, EcoMod.
    265. 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.
    266. Christian Kascha & Francesco Ravazzolo, 2008. "Combining inflation density forecasts," Working Paper 2008/22, Norges Bank.
    267. 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.
    268. 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.
    269. 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.
    270. 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.
    271. 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.
    272. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2010. "Forecasting with DSGE models," Working Paper Series 1185, European Central Bank.
    273. Raffaella Giacomini, 2014. "Economic theory and forecasting: lessons from the literature," CeMMAP working papers 41/14, Institute for Fiscal Studies.
    274. 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.
    275. Gaglianone, Wagner Piazza & Marins, Jaqueline Terra Moura, 2017. "Evaluation of exchange rate point and density forecasts: An application to Brazil," International Journal of Forecasting, Elsevier, vol. 33(3), pages 707-728.
    276. 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.
    277. Giacomini, Raffaella & Ragusa, Giuseppe, 2014. "Theory-coherent forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 145-155.
    278. 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.
    279. 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.
    280. Francisco Blasques & Vladimir Holy & Petra Tomanova, 2019. "Zero-Inflated Autoregressive Conditional Duration Model for Discrete Trade Durations with Excessive Zeros," Tinbergen Institute Discussion Papers 19-004/III, Tinbergen Institute.
    281. Caraiani, Petre, 2016. "The role of money in DSGE models: a forecasting perspective," Journal of Macroeconomics, Elsevier, vol. 47(PB), pages 315-330.
    282. 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.
    283. 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.
    284. Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.
    285. 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.
    286. 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.
    287. 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.
    288. Liu, Li & Wang, Yudong & Yang, Li, 2018. "Predictability of crude oil prices: An investor perspective," Energy Economics, Elsevier, vol. 75(C), pages 193-205.
    289. Szabolcs Blazsek & Han-Chiang Ho, 2017. "Markov regime-switching Beta--EGARCH," Applied Economics, Taylor & Francis Journals, vol. 49(47), pages 4793-4805, October.
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    292. Mathieu Gatumel & Florian Ielpo, 2011. "The Number of Regimes Across Asset Returns: Identification and Economic Value," Post-Print halshs-00658540, HAL.
    293. 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.
    294. Domit, Sílvia & Monti, Francesca & Sokol, Andrej, 2016. "A Bayesian VAR benchmark for COMPASS," Bank of England working papers 583, Bank of England.
    295. 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.
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    301. Saeed Zaman, 2021. "A Unified Framework to Estimate Macroeconomic Stars," Working Papers 21-23R2, Federal Reserve Bank of Cleveland, revised 31 May 2024.

  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. Monastiriotis, Vassilis, 2006. "Macro-determinants of UK regional unemployment and the role of employment flexibility," MPRA Paper 44, University Library of Munich, Germany.
    2. Ghafar, Aiman & Masih, Mansur, 2017. "The unemployment rate and its determinants: the Malaysian case," MPRA Paper 110220, University Library of Munich, Germany.
    3. 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.
    4. 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).
    5. 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(1), January.
    6. Massimiliano Serati & Gianni Amisano, 2003. "Unemployment and labour taxation: an econometric analysis," LIUC Papers in Economics 122, Cattaneo University (LIUC).
    7. Alexius, Annika & Holmlund, Bertil, 2007. "Monetary Policy and Swedish Unemployment Fluctuations," Working Paper Series 2007:17, Uppsala University, Department of Economics.
    8. Juan José Echavarría & Enrique López & Sergio Ocampo & Norberto Rodríguez, 2011. "Choques, instituciones laborales y desempleo en Colombia," Borradores de Economia 9154, Banco de la Republica.
    9. 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.
    10. Vaona, Andrea, 2016. "Anomalous empirical evidence on money long-run super-neutrality and the vertical long-run Phillips curve," Kiel Working Papers 2038, Kiel Institute for the World Economy (IfW Kiel).
    11. Arshad, Sumera & Ali, Amjad, 2016. "Trade-off between Inflation, Interest and Unemployment Rate of Pakistan: Revisited," MPRA Paper 78101, University Library of Munich, Germany.
    12. 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.
    13. 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.
    14. Andrea Bassanini & Romain Duval, 2006. "The Determinants of Unemployment across OECD Countries," Post-Print halshs-00120584, HAL.
    15. 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).
    16. 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.

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. 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.
    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. 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.
    5. 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.
    6. 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.
    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. 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.
    9. Jiri Slacalek, 2013. "Wealth heterogeneity and the response of consumption to shocks," Research Bulletin, European Central Bank, vol. 19, pages 10-12.

  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. 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.
    2. 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.
    3. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2018. "Quantile forecast combination using stochastic dominance," Empirical Economics, Springer, vol. 55(4), pages 1717-1755, December.
    4. Berg, Tim O. & Henzel, Steffen R., 2015. "Point and density forecasts for the euro area using Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
    5. 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.
    6. George Papadopoulos & Savas Papadopoulos & Thomas Sager, 2016. "Credit risk stress testing for EU15 banks: a model combination approach," Working Papers 203, Bank of Greece.
    7. Wolters, Maik Hendrik, 2012. "Evaluating point and density forecasts of DSGE models," MPRA Paper 36147, University Library of Munich, Germany.
    8. Čapek, Jan & Crespo Cuaresma, Jesús & Hauzenberger, Niko & Reichel, Vlastimil, 2023. "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1820-1838.
    9. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Paper 2019/2, Norges Bank.
    10. Cristina Conflitti & Christine De Mol & Domenico Giannone, 2012. "Optimal Combination of Survey Forecasts," Working Papers ECARES ECARES 2012-023, ULB -- Universite Libre de Bruxelles.
    11. Thorsten Drautzburg, 2023. "A Structural Approach to Combining External and DSGE Model Forecasts," Working Papers 23-10, Federal Reserve Bank of Philadelphia.
    12. 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.
    13. 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.
    14. 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.
    15. 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).
    16. Ho, Paul & Lubik, Thomas A. & Matthes, Christian, 2024. "Averaging impulse responses using prediction pools," Journal of Monetary Economics, Elsevier, vol. 146(C).
    17. 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.
    18. McAlinn, Kenichiro & West, Mike, 2019. "Dynamic Bayesian predictive synthesis in time series forecasting," Journal of Econometrics, Elsevier, vol. 210(1), pages 155-169.
    19. 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.
    20. 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.
    21. Fawcett, Nicholas & Kapetanios, George & Mitchell, James & Price, Simon, 2014. "Generalised density forecast combinations," Bank of England working papers 492, Bank of England.
    22. Daniele Bianchi & Kenichiro McAlinn, 2018. "Large-Scale Dynamic Predictive Regressions," Papers 1803.06738, arXiv.org.
    23. 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.
    24. 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.
    25. Kenichiro McAlinn & Kosaku Takanashi, 2019. "Mean-shift least squares model averaging," Papers 1912.01194, arXiv.org.
    26. 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.
    27. Byrne, Joseph & Fu, Rong, 2016. "Stock Return Prediction with Fully Flexible Models and Coefficients," MPRA Paper 75366, University Library of Munich, Germany.
    28. 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.
    29. 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.
    30. 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.
    31. Nikolay Gospodinov & Esfandiar Maasoumi, 2017. "General Aggregation of Misspecified Asset Pricing Models," FRB Atlanta Working Paper 2017-10, Federal Reserve Bank of Atlanta.
    32. Chollete, Lor & Schmeidler, David, 2014. "Misspecification Aversion and Selection of Initial Priors," UiS Working Papers in Economics and Finance 2014/13, University of Stavanger.
    33. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2013. "Predictive likelihood comparisons with DSGE and DSGE-VAR models," Working Paper Series 1536, European Central Bank.
    34. 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.
    35. 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.
    36. 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.
    37. K=osaku Takanashi & Kenichiro McAlinn, 2019. "Equivariant online predictions of non-stationary time series," Papers 1911.08662, arXiv.org, revised Jun 2023.

  7. 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.
  8. 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.
  9. 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. Paolo Canofari & Giancarlo Marini & Giovanni Piersanti, 2015. "Expectations and systemic risk in EMU government bond spreads," Quantitative Finance, Taylor & Francis Journals, vol. 15(4), pages 711-724, April.
    2. Paolo Canofari & Giovanni Bartolomeo & Giovanni Piersanti, 2014. "Theory and Practice of Contagion in Monetary Unions: Domino Effects in EMU Mediterranean Countries," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 20(3), pages 259-267, August.
    3. Nikolaos Antonakakis & Christina Christou & Juncal Cunado & Rangan Gupta, 2016. "Convergence Patterns in Sovereign Bond Yield Spreads: Evidence from the Euro Area," Working Papers 201616, University of Pretoria, Department of Economics.
    4. 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.
    5. 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.
    6. 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.
    7. 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.

  10. 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.
  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. 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.
    2. 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.
    3. 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.
    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. 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.
    6. Bicchal, Motilal, 2022. "Central bank credibility and its effect on stabilization," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 73-94.

  12. 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.
  13. 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.
  14. Gianni Amisano & Andreas Beyer & Michele Lenza, 2010. "Enhancing monetary analysis," Research Bulletin, European Central Bank, vol. 11, pages 2-6.

    Cited by:

    1. 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.
    2. Giannone, Domenico & Lenza, Michele & Pill, Huw & Reichlin, Lucrezia, 2011. "Non-standard monetary policy measures and monetary developments," Working Paper Series 1290, European Central Bank.
    3. 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.

  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 & Cho, Yoonyoung & Heath, Rachel, 2023. "The effects of international scrutiny on manufacturing workers: Evidence from the Rana Plaza collapse in Bangladesh," Journal of Development Economics, Elsevier, vol. 163(C).

  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.
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