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Paolo Giordani

Not to be confused with: Paolo E. Giordani

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.

Working papers

  1. Giordani, Paolo & Jacobson, Tor & von Schedvin , Erik & Villani, Mattias, 2011. "Taking the Twists into Account: Predicting Firm Bankruptcy Risk with Splines of Financial Ratios," Working Paper Series 256, Sveriges Riksbank (Central Bank of Sweden).

    Cited by:

    1. Cathcart, Lara & Dufour, Alfonso & Rossi, Ludovico & Varotto, Simone, 2020. "The differential impact of leverage on the default risk of small and large firms," Journal of Corporate Finance, Elsevier, vol. 60(C).
    2. Gunawan, David & Dang, Khue-Dung & Quiroz, Matias & Kohn, Robert & Tran, Minh-Ngoc, 2019. "Subsampling Sequential Monte Carlo for Static Bayesian Models," Working Paper Series 371, Sveriges Riksbank (Central Bank of Sweden).
    3. Xueyan Dong & Kam C. Chan & Yujia Cui & Jenny Xinjiao Guan, 2021. "Strategic deviance and cash holdings," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 48(3-4), pages 742-782, March.
    4. Niklas Amberg & Tor Jacobson & Erik von Schedvin & Robert Townsend, 2021. "Curbing Shocks to Corporate Liquidity: The Role of Trade Credit," Journal of Political Economy, University of Chicago Press, vol. 129(1), pages 182-242.
    5. Koresh Galil & Neta Gilat, 2019. "Predicting Default More Accurately: To Proxy or Not to Proxy for Default?," International Review of Finance, International Review of Finance Ltd., vol. 19(4), pages 731-758, December.
    6. Muhammad Zubair Mumtaz & Zachary Alexander Smith, 2018. "IPOs in the U.S. from 2005 to 2015: Using the Spline Regression Technique to Estimate Aggregate Issuance and Performance," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 68(2), pages 165-199, April.
    7. Michel Alexandre & Gilberto Tadeu Lima & Luca Riccetti & Alberto Russo, 2022. "The financial network channel of monetary policy transmission: An agent-based model," Working Papers 2022/01, Economics Department, Universitat Jaume I, Castellón (Spain).
    8. Lee, Kangbok & Joo, Sunghoon & Baik, Hyeoncheol & Han, Sumin & In, Joonhwan, 2020. "Unbalanced data, type II error, and nonlinearity in predicting M&A failure," Journal of Business Research, Elsevier, vol. 109(C), pages 271-287.
    9. Villani, Mattias & Kohn, Robert & Nott, David J., 2012. "Generalized smooth finite mixtures," Journal of Econometrics, Elsevier, vol. 171(2), pages 121-133.
    10. Ida Nervik Hjelseth & Arvid Raknerud & Bjørn H. Vatne, 2022. "A bankruptcy probability model for assessing credit risk on corporate loans with automated variable selection," Working Paper 2022/7, Norges Bank.
    11. Péter Bauer & Marianna Endrész, 2016. "Modelling Bankruptcy Using Hungarian Firm-Level Data," MNB Occasional Papers 2016/122, Magyar Nemzeti Bank (Central Bank of Hungary).
    12. Ken Li, 2024. "Liquidity ratios and corporate failures," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(1), pages 1111-1134, March.
    13. Quiroz, Matias & Villani, Mattias & Kohn, Robert, 2015. "Speeding Up Mcmc By Efficient Data Subsampling," Working Paper Series 297, Sveriges Riksbank (Central Bank of Sweden).
    14. Dang, Khue-Dung & Quiroz, Matias & Kohn, Robert & Tran, Minh-Ngoc & Villani, Mattias, 2019. "Hamiltonian Monte Carlo with Energy Conserving Subsampling," Working Paper Series 372, Sveriges Riksbank (Central Bank of Sweden).
    15. 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.
    16. Quiroz, Matias & Villani, Mattias, 2013. "Dynamic mixture-of-experts models for longitudinal and discrete-time survival data," Working Paper Series 268, Sveriges Riksbank (Central Bank of Sweden).
    17. Georgios Sermpinis & Serafeim Tsoukas & Ping Zhang, 2019. "What influences a bank's decision to go public?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(4), pages 1464-1485, October.

  2. Strid, Ingvar & Giordani, Paolo & Kohn, Robert, 2010. "Adaptive hybrid Metropolis-Hastings samplers for DSGE models," SSE/EFI Working Paper Series in Economics and Finance 724, Stockholm School of Economics.

    Cited by:

    1. Edward P. Herbst & Frank Schorfheide, 2012. "Sequential Monte Carlo sampling for DSGE models," Working Papers 12-27, Federal Reserve Bank of Philadelphia.
    2. Pasanisi, Alberto & Fu, Shuai & Bousquet, Nicolas, 2012. "Estimating discrete Markov models from various incomplete data schemes," Computational Statistics & Data Analysis, Elsevier, vol. 56(9), pages 2609-2625.
    3. Jesús Fernández-Villaverde & Pablo A. Guerrón-Quintana, 2021. "Estimating DSGE Models: Recent Advances and Future Challenges," Annual Review of Economics, Annual Reviews, vol. 13(1), pages 229-252, August.
    4. 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.

  3. Giordani, Paolo & Villani, Mattias, 2009. "Forecasting Macroeconomic Time Series With Locally Adaptive Signal Extraction," Working Paper Series 234, Sveriges Riksbank (Central Bank of Sweden).

    Cited by:

    1. Huber, Florian, 2016. "Density forecasting using Bayesian global vector autoregressions with stochastic volatility," International Journal of Forecasting, Elsevier, vol. 32(3), pages 818-837.
    2. 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.
    3. 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.
    4. Luiz Renato Regis de Oliveira Lima & Wagner Piazza Gaglianone, 2012. "Constructing Optimal Density Forecasts from Point Forecast Combinations," Série Textos para Discussão (Working Papers) 5, Programa de Pós-Graduação em Economia - PPGE, Universidade Federal da Paraíba.
    5. Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2020. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 17-33, March.
    6. Florian Huber, 2014. "Density Forecasting using Bayesian Global Vector Autoregressions with Common Stochastic Volatility," Department of Economics Working Papers wuwp179, Vienna University of Economics and Business, Department of Economics.
    7. Bulkley, George & Giordani, Paolo, 2011. "Structural breaks, parameter uncertainty, and term structure puzzles," Journal of Financial Economics, Elsevier, vol. 102(1), pages 222-232, October.
    8. Garratt, Anthony & Mise, Emi, 2014. "Forecasting exchange rates using panel model and model averaging," Economic Modelling, Elsevier, vol. 37(C), pages 32-40.
    9. Mohammad Arashi & Mohammad Mahdi Rounaghi, 2022. "Analysis of market efficiency and fractal feature of NASDAQ stock exchange: Time series modeling and forecasting of stock index using ARMA-GARCH model," Future Business Journal, Springer, vol. 8(1), pages 1-12, December.
    10. Liu, Yuelin & Morley, James, 2014. "Structural evolution of the postwar U.S. economy," Journal of Economic Dynamics and Control, Elsevier, vol. 42(C), pages 50-68.
    11. 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.
    12. Daniele Bianchi & Massimo Guidolin & Francesco Ravazzolo, 2015. "Macroeconomic Factors Strike Back: A Bayesian Change-Point Model of Time-Varying Risk Exposures and Premia in the U.S. Cross-Section," Working Papers 550, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    13. 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.
    14. Vasiliy Zubakin & Oleg Kosorukov & Nikita Moiseev, 2015. "Improvement of Regression Forecasting Models," Modern Applied Science, Canadian Center of Science and Education, vol. 9(6), pages 344-344, June.

  4. Villani, Mattias & Kohn, Robert & Giordani, Paolo, 2007. "Nonparametric Regression Density Estimation Using Smoothly Varying Normal Mixtures," Working Paper Series 211, Sveriges Riksbank (Central Bank of Sweden).

    Cited by:

    1. Villani, Mattias & Kohn, Robert & Giordani, Paolo, 2009. "Regression density estimation using smooth adaptive Gaussian mixtures," Journal of Econometrics, Elsevier, vol. 153(2), pages 155-173, December.
    2. Denzil G. Fiebig & Michael P. Keane & Jordan Louviere & Nada Wasi, 2010. "The Generalized Multinomial Logit Model: Accounting for Scale and Coefficient Heterogeneity," Marketing Science, INFORMS, vol. 29(3), pages 393-421, 05-06.
    3. Chib, Siddhartha & Greenberg, Edward, 2010. "Additive cubic spline regression with Dirichlet process mixture errors," Journal of Econometrics, Elsevier, vol. 156(2), pages 322-336, June.

  5. Giordani, Paolo & Kohn, Robert, 2006. "Efficient Bayesian Inference for Multiple Change-Point and Mixture Innovation Models," Working Paper Series 196, Sveriges Riksbank (Central Bank of Sweden).

    Cited by:

    1. Drew Creal & Siem Jan Koopman & Eric Zivot, 2008. "The Effect of the Great Moderation on the U.S. Business Cycle in a Time-varying Multivariate Trend-cycle Model," Tinbergen Institute Discussion Papers 08-069/4, Tinbergen Institute.
    2. Daniele Bianchi & Massimo Guidolin & Francesco Ravazzolo, 2018. "Dissecting the 2007–2009 Real Estate Market Bust: Systematic Pricing Correction or Just a Housing Fad?," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 34-62.
    3. Markus Jochmann & Gary Koop & Roberto Leon-Gonzalez & Rodney W. Strachan, 2009. "Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy," Working Paper series 44_09, Rimini Centre for Economic Analysis.
    4. Dimitris Korobilis, 2009. "Assessing the Transmission of Monetary Policy Shocks Using Dynamic Factor Models," Working Paper series 35_09, Rimini Centre for Economic Analysis.
    5. Francesco Ravazzolo & Shaun P. Vahey, 2010. "Forecast densities for economic aggregates from disaggregate ensembles," Working Paper 2010/02, Norges Bank.
    6. Dionne, Georges & Maalaoui Chun, Olfa, 2013. "Default and liquidity regimes in the bond market during the 2002-2012 period," Working Papers 13-4, HEC Montreal, Canada Research Chair in Risk Management.
    7. Geweke, John & Jiang, Yu, 2011. "Inference and prediction in a multiple-structural-break model," Journal of Econometrics, Elsevier, vol. 163(2), pages 172-185, August.
    8. Korobilis, Dimitris & Koop, Gary, 2020. "Bayesian dynamic variable selection in high dimensions," MPRA Paper 100164, University Library of Munich, Germany.
    9. Smith, Simon C., 2017. "Equity premium estimates from economic fundamentals under structural breaks," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 49-61.
    10. Mark Fisher & Mark J. Jensen, 2018. "Bayesian Inference and Prediction of a Multiple-Change-Point Panel Model with Nonparametric Priors," FRB Atlanta Working Paper 2018-2, Federal Reserve Bank of Atlanta.
    11. Koop, Gary & Korobilis, Dimitris, 2018. "Variational Bayes inference in high-dimensional time-varying parameter models," MPRA Paper 87972, University Library of Munich, Germany.
    12. Gary Koop & Simon M. Potter, 2009. "Prior Elicitation In Multiple Change-Point Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(3), pages 751-772, August.
    13. Massimo Guidolin & Francesco Ravazzolo & Andrea Tortora, 2014. "Myths and Facts about the Alleged Over-Pricing of U.S. Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 49(4), pages 477-523, November.
    14. Giordani, Paolo & Villani, Mattias, 2009. "Forecasting Macroeconomic Time Series With Locally Adaptive Signal Extraction," Working Paper Series 234, Sveriges Riksbank (Central Bank of Sweden).
    15. John M. Maheu & Stephen Gordon, 2004. "Learning, Forecasting and Structural Breaks," Cahiers de recherche 0422, CIRPEE.
    16. Lennart Hoogerheide & Richard Kleijn & Francesco Ravazzolo & Herman K. Van Dijk & Marno Verbeek, 2010. "Forecast accuracy and economic gains from Bayesian model averaging using time-varying weights," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 251-269.
    17. Eo, Yunjong & Kim, Chang-Jin, 2012. "Markov-Switching Models with Evolving Regime-Specific Parameters: Are Post-War Booms or Recessions All Alike?," Working Papers 2012-04, University of Sydney, School of Economics.
    18. Fiorentini, G. & Planas, C. & Rossi, A., 2012. "The marginal likelihood of dynamic mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 56(9), pages 2650-2662.
    19. Joshua C.C. Chan & Garry Koop & Roberto Leon Gonzales & Rodney W. Strachan, 2010. "Time Varying Dimension Models," ANU Working Papers in Economics and Econometrics 2010-523, Australian National University, College of Business and Economics, School of Economics.
    20. Crespo Cuaresma, Jesus & Doppelhofer, Gernot & Feldkircher, Martin & Huber, Florian, 2018. "Spillovers from US monetary policy: Evidence from a time-varying parameter GVAR model," Working Papers in Economics 2018-6, University of Salzburg.
    21. Koop, Gary & Leon-Gonzalez, Roberto & Strachan, Rodney W., 2009. "On the evolution of the monetary policy transmission mechanism," Journal of Economic Dynamics and Control, Elsevier, vol. 33(4), pages 997-1017, April.
    22. Drew Creal & Siem Jan Koopman & Eric Zivot, 2010. "Extracting a robust US business cycle using a time-varying multivariate model-based bandpass filter," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 695-719.
    23. Gary Koop & Roberto Leon-Gonzalez & Rodney W. Strachan, 2008. "On the Evolution of Monetary Policy," Working Paper series 24_08, Rimini Centre for Economic Analysis.
    24. Georges Dionne & Olfa Maalaoui Chun, 2013. "Presidential Address: Default and liquidity regimes in the bond market during the 2002–2012 period," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 46(4), pages 1160-1195, November.
    25. 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.
    26. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    27. Hou, Chenghan, 2017. "Infinite hidden markov switching VARs with application to macroeconomic forecast," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1025-1043.
    28. Dufays, Arnaud & Rombouts, Jeroen V.K., 2020. "Relevant parameter changes in structural break models," Journal of Econometrics, Elsevier, vol. 217(1), pages 46-78.
    29. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    30. Korobilis, D, 2017. "Forecasting with many predictors using message passing algorithms," Essex Finance Centre Working Papers 19565, University of Essex, Essex Business School.
    31. Eo, Yunjong, 2015. "Structural Changes in Inflation Dynamics: Multiple Breaks at Different Dates for Different Parameters," Working Papers 2015-18, University of Sydney, School of Economics, revised Nov 2015.
    32. Jesús Crespo Cuaresma & Gernot Doppelhofer & Martin Feldkircher & Florian Huber, 2019. "Spillovers from US monetary policy: evidence from a time varying parameter global vector auto‐regressive model," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(3), pages 831-861, June.
    33. Guidolin, Massimo & Hansen, Erwin & Pedio, Manuela, 2019. "Cross-asset contagion in the financial crisis: A Bayesian time-varying parameter approach," Journal of Financial Markets, Elsevier, vol. 45(C), pages 83-114.
    34. He, Zhongfang, 2009. "Forecasting output growth by the yield curve: the role of structural breaks," MPRA Paper 28208, University Library of Munich, Germany.
    35. Bulkley, George & Giordani, Paolo, 2011. "Structural breaks, parameter uncertainty, and term structure puzzles," Journal of Financial Economics, Elsevier, vol. 102(1), pages 222-232, October.
    36. Polemis, Michael & Stengos, Thanasis, 2017. "Does Competition Prevent Industrial Pollution? Evidence from a Panel Threshold Model," MPRA Paper 85177, University Library of Munich, Germany.
    37. Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
    38. Nalan Baştürk & Cem Çakmakli & S. Pinar Ceyhan & Herman K. Van Dijk, 2014. "Posterior‐Predictive Evidence On Us Inflation Using Extended New Keynesian Phillips Curve Models With Non‐Filtered Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(7), pages 1164-1182, November.
    39. Ardia, David & Dufays, Arnaud & Ordás Criado, Carlos, 2023. "Linking Frequentist and Bayesian Change-Point Methods," MPRA Paper 119486, University Library of Munich, Germany.
    40. Sjoerd van den Hauwe & Richard Paap & Dick J.C. van Dijk, 2011. "An Alternative Bayesian Approach to Structural Breaks in Time Series Models," Tinbergen Institute Discussion Papers 11-023/4, Tinbergen Institute.
    41. Jonas Dovern & Ulrich Fritsche & Jiri Slacalek, 2012. "Disagreement Among Forecasters in G7 Countries," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1081-1096, November.
    42. Guidolin, Massimo & Ravazzolo, Francesco & Tortora, Andrea Donato, 2013. "Alternative econometric implementations of multi-factor models of the U.S. financial markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 53(2), pages 87-111.
    43. Luc Bauwens & Gary Koop & Dimitris Korobilis & Jeroen Rombouts, 2011. "A comparison of Forecasting Procedures for Macroeconomic Series: The Contribution of Structural Break Models," Working Papers 1113, University of Strathclyde Business School, Department of Economics.
    44. 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.
    45. Samuel F. Onipede & Nafiu A. Bashir & Jamaladeen Abubakar, 2023. "Small open economies and external shocks: an application of Bayesian global vector autoregression model," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 1673-1699, April.
    46. Dr. James Mitchell, 2009. "Macro Modelling with Many Models," National Institute of Economic and Social Research (NIESR) Discussion Papers 337, National Institute of Economic and Social Research.
    47. Massimo Guidolin & Francesco Ravazzolo & Andrea Donato Tortora, 2011. "Myths and Facts about the Alleged Over-Pricing of U.S. Real Estate. Evidence from Multi-Factor Asset Pricing Models of REIT Returns," Working Papers 416, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    48. Liu, Laura & Moon, Hyungsik Roger & Schorfheide, Frank, 2021. "Panel forecasts of country-level Covid-19 infections," Journal of Econometrics, Elsevier, vol. 220(1), pages 2-22.
    49. Nalan Basturk & Pinar Ceyhan & Herman K. van Dijk, 2014. "Bayesian Forecasting of US Growth using Basic Time Varying Parameter Models and Expectations Data," Tinbergen Institute Discussion Papers 14-119/III, Tinbergen Institute, revised 14 Sep 2014.
    50. Liu, Yuelin & Morley, James, 2014. "Structural evolution of the postwar U.S. economy," Journal of Economic Dynamics and Control, Elsevier, vol. 42(C), pages 50-68.
    51. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    52. Huang Yu-Fan, 2021. "An effcient exact Bayesian method For state space models with stochastic volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-10, April.
    53. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2013. "Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 13-191/III, Tinbergen Institute.
    54. Maximo Camacho & María Dolores Gadea & Ana Gómez Loscos, 2022. "A New Approach to Dating the Reference Cycle," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 66-81, January.
    55. 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.
    56. John M. Maheu & Thomas H. McCurdy, 2007. "How useful are historical data for forecasting the long-run equity return distribution?," Working Paper series 19_07, Rimini Centre for Economic Analysis.
    57. Moussa, Zakaria, 2010. "The Japanese Quantitative Easing Policy under Scrutiny: A Time-Varying Parameter Factor-Augmented VAR Model," MPRA Paper 29429, University Library of Munich, Germany.
    58. Smith Aaron, 2012. "Markov Breaks in Regression Models," Journal of Time Series Econometrics, De Gruyter, vol. 4(1), pages 1-35, May.
    59. Giuseppe Pagano Giorgianni & Valeria Patella, 2024. "Belief distortions and Disagreement about Inflation," Working Paper series 24-08, Rimini Centre for Economic Analysis.
    60. BAUWENS, Luc & DE BACKER, Bruno & DUFAYS, Arnaud, 2014. "A Bayesian method of change-point estimation with recurrent regimes: application to GARCH models," LIDAM Reprints CORE 2641, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    61. Abolghasemi, Mahdi & Hurley, Jason & Eshragh, Ali & Fahimnia, Behnam, 2020. "Demand forecasting in the presence of systematic events: Cases in capturing sales promotions," International Journal of Production Economics, Elsevier, vol. 230(C).
    62. Jiawen Xu & Pierre Perron, 2023. "Forecasting in the presence of in-sample and out-of-sample breaks," Empirical Economics, Springer, vol. 64(6), pages 3001-3035, June.
    63. Daniele Bianchi & Massimo Guidolin & Francesco Ravazzolo, 2015. "Macroeconomic Factors Strike Back: A Bayesian Change-Point Model of Time-Varying Risk Exposures and Premia in the U.S. Cross-Section," Working Papers 550, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    64. Mehmet Balcilar & Riza Demirer & Festus V. Bekun, 2021. "Flexible Time-Varying Betas in a Novel Mixture Innovation Factor Model with Latent Threshold," Mathematics, MDPI, vol. 9(8), pages 1-20, April.
    65. Planas, C. & Roeger, W. & Rossi, A., 2013. "The information content of capacity utilization for detrending total factor productivity," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 577-590.
    66. Wensheng Kang & Ronald A. Ratti & Kyung Hwan Yoon, 2015. "Time-varying effect of oil market shocks on the stock market," CAMA Working Papers 2015-35, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    67. Jhonatan Portilla & Gabriel Rodríguez & Paul Castillo B., 2022. "Evolution of Monetary Policy in Peru: An Empirical Application Using a Mixture Innovation TVP-VAR-SV Model [Metas de Inflación en Una Economía Dolarizada: La Experencia Del Perú]," CESifo Economic Studies, CESifo Group, vol. 68(1), pages 98-126.
    68. MeiChi Huang, 2022. "Time‐varying roles of housing risk factors in state‐level housing markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4660-4683, October.
    69. Chao Du & Chu-Lan Michael Kao & S. C. Kou, 2016. "Stepwise Signal Extraction via Marginal Likelihood," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(513), pages 314-330, March.
    70. Venkata Jandhyala & Stergios Fotopoulos & Ian MacNeill & Pengyu Liu, 2013. "Inference for single and multiple change-points in time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(4), pages 423-446, July.
    71. Lu Shaochuan, 2023. "Scalable Bayesian Multiple Changepoint Detection via Auxiliary Uniformisation," International Statistical Review, International Statistical Institute, vol. 91(1), pages 88-113, April.
    72. Bala Dahiru Abdullahi, 2016. "Time-Varying VAR with Stochastic Volatility and Monetary Policy Dynamics in Nigeria," Economics Bulletin, AccessEcon, vol. 36(4), pages 2237-2249.
    73. Nalan Basturk & Cem Cakmakli & Pinar Ceyhan & Herman K. van Dijk, 2013. "Posterior-Predictive Evidence on US Inflation using Phillips Curve Models with Non-Filtered Time Series," Tinbergen Institute Discussion Papers 13-011/III, Tinbergen Institute.
    74. Alexeev, Vitali & Dungey, Mardi & Yao, Wenying, 2017. "Time-varying continuous and jump betas: The role of firm characteristics and periods of stress," Journal of Empirical Finance, Elsevier, vol. 40(C), pages 1-19.
    75. Gary Koop & Simon Potter, 2010. "A flexible approach to parametric inference in nonlinear and time varying time series models," Post-Print hal-00732535, HAL.
    76. Chiara Lattanzi & Manuele Leonelli, 2019. "A changepoint approach for the identification of financial extreme regimes," Papers 1902.09205, arXiv.org.
    77. Chiara Perricone, 2013. "Clustering Macroeconomic Variables," CEIS Research Paper 283, Tor Vergata University, CEIS, revised 11 Jun 2013.
    78. DESCHAMPS, Philippe J., 2016. "Bayesian Semiparametric Forecasts of Real Interest Rate Data," LIDAM Discussion Papers CORE 2016050, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    79. Niko Hauzenberger & Daniel Kaufmann & Rebecca Stuart & Cédric Tille, 2022. "What Drives Long-Term Interest Rates? Evidence from the Entire Swiss Franc History 1852-2020," IRENE Working Papers 22-03, IRENE Institute of Economic Research.
    80. Christopher A. Sims & Daniel F. Waggoner & Tao Zha, 2006. "Methods for inference in large multiple-equation Markov-switching models," FRB Atlanta Working Paper 2006-22, Federal Reserve Bank of Atlanta.
    81. Jiawen Xu & Pierre Perron, 2017. "Forecasting in the presence of in and out of sample breaks," Boston University - Department of Economics - Working Papers Series WP2018-014, Boston University - Department of Economics, revised Nov 2018.
    82. Arnaud Dufays & Zhuo Li & Jeroen V.K. Rombouts & Yong Song, 2021. "Sparse change‐point VAR models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 703-727, September.
    83. Jordi Maas, 2014. "Forecasting inflation using time-varying Bayesian model averaging," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(3), pages 149-182, August.
    84. Manfred M. Fischer & Niko Hauzenberger & Florian Huber & Michael Pfarrhofer, 2021. "General Bayesian time-varying parameter VARs for predicting government bond yields," Papers 2102.13393, arXiv.org.
    85. Simon C. Smith, 2020. "Equity premium prediction and structural breaks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(3), pages 412-429, July.
    86. Huiqin Li & Shuai Guan & Yongfu Liu, 2022. "Analysis on the Steady Growth Effect of China’s Fiscal Policy from a Dynamic Perspective," Sustainability, MDPI, vol. 14(13), pages 1-15, June.
    87. 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.
    88. Sang Gil Kang & Woo Dong Lee & Yongku Kim, 2021. "Bayesian Multiple Change-Points Detection in a Normal Model with Heterogeneous Variances," Computational Statistics, Springer, vol. 36(2), pages 1365-1390, June.
    89. Gary Koop & Simon M. Potter, 2007. "A flexible approach to parametric inference in nonlinear time series models," Staff Reports 285, Federal Reserve Bank of New York.
    90. Ko, Stanley I. M. & Chong, Terence T. L. & Ghosh, Pulak, 2014. "Dirichlet Process Hidden Markov Multiple Change-point Model," MPRA Paper 57871, University Library of Munich, Germany.
    91. He, Feng & Ma, Feng & Wang, Ziwei & Yang, Bohan, 2021. "Asymmetric volatility spillover between oil-importing and oil-exporting countries' economic policy uncertainty and China's energy sector," International Review of Financial Analysis, Elsevier, vol. 75(C).

  6. Giordani, Paolo & Söderlind, Paul, 2003. "Is There Evidence of Pessimism and Doubt in Subjective Distributions? A Comment on Abel," SIFR Research Report Series 19, Institute for Financial Research.

    Cited by:

    1. Joseph Engelberg & Charles F. Manski & Jared Williams, 2006. "Comparing the Point Predictions and Subjective Probability Distributions of Professional Forecasters," NBER Working Papers 11978, National Bureau of Economic Research, Inc.
    2. Jouini, Elyes & Napp, Clotilde, 2006. "Heterogeneous beliefs and asset pricing in discrete time: An analysis of pessimism and doubt," Journal of Economic Dynamics and Control, Elsevier, vol. 30(7), pages 1233-1260, July.
    3. Verma, Rahul & Soydemir, Gökçe, 2009. "The impact of individual and institutional investor sentiment on the market price of risk," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(3), pages 1129-1145, August.
    4. Hermalin, Benjamin E. & Weisbach, Michael S., 2009. "Information Disclosure and Corporate Governance," Working Paper Series 2008-17, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    5. Dreber, Anna & Rand, David G. & Garcia, Justin R. & Wernerfelt, Nils & Lum, J. Koji & Zeckhauser, Richard, 2010. "Dopamine and Risk Preferences in Different Domains," Working Paper Series rwp10-012, Harvard University, John F. Kennedy School of Government.
    6. Elyès Jouini & Clotilde Napp, 2008. "On Abel's Concept of Doubt and Pessimism," Post-Print halshs-00176611, HAL.
    7. Rydqvist, Kristian, 2010. "Tax Arbitrage with Risk and Effort Aversion - Swedish Lottery Bonds 1970-1990," SIFR Research Report Series 70, Institute for Financial Research.
    8. Olivier Armantier & Nicolas Treich, 2006. "Overbidding in Independant Private-Values Auctions and Misperception of Probabilities," CIRANO Working Papers 2006s-15, CIRANO.

  7. Giordani, Paolo & Söderlind, Paul, 2002. "Solution of Macromodels with Hansen-Sargent Robust Policies: Some Extensions," SSE/EFI Working Paper Series in Economics and Finance 499, Stockholm School of Economics, revised 15 May 2003.

    Cited by:

    1. Kwon, Hyosung & Miao, Jianjun, 2019. "Woodford'S Approach To Robust Policy Analysis In A Linear-Quadratic Framework," Macroeconomic Dynamics, Cambridge University Press, vol. 23(5), pages 1895-1920, July.
    2. Chatelain, Jean-Bernard & Ralf, Kirsten, 2017. "Can we Identify the Fed's Preferences?," MPRA Paper 76831, University Library of Munich, Germany.
    3. Marine Charlotte André & Meixing Dai, 2016. "Learning, robust monetray policy and the merit of precaution," Working Papers of BETA 2016-54, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    4. Luo, Yulei & Nie, Jun & Young, Eric, 2014. "Model Uncertainty and Intertemporal Tax Smoothing," MPRA Paper 54268, University Library of Munich, Germany.
    5. Leitemo, Kai & Söderström, Ulf, 2005. "Robust monetary policy in a small open economy," Bank of Finland Research Discussion Papers 20/2005, Bank of Finland.
    6. Tetlow, Robert J. & von zur Muehlen, Peter, 2006. "Robustifying learnability," Working Paper Series 593, European Central Bank.
    7. Adam – Nelu ALTĂR – SAMUEL, 2008. "Robust Monetary Policy," Journal of Information Systems & Operations Management, Romanian-American University, vol. 2(2), pages 475-486, November.
    8. Dennis, Richard & Leitemo, Kai & Söderström, Ulf, 2009. "Methods for robust control," Journal of Economic Dynamics and Control, Elsevier, vol. 33(8), pages 1604-1616, August.
    9. Li Qin & Moïse SIDIROPOULOS & Eleftherios Spyromitros, 2009. "Robust Monetary Policy under Model Uncertainty and Inflation Persistence," Working Papers of BETA 2009-09, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    10. Juha Kilponen, 2004. "A positive theory of monetary policy and robust control," Macroeconomics 0404036, University Library of Munich, Germany.
    11. Michael Paetz, 2007. "Robust Control and Persistence in the New Keynesian Economy," Quantitative Macroeconomics Working Papers 20711, Hamburg University, Department of Economics.
    12. Jean-Bernard Chatelain & Kirsten Ralf, 2020. "Policy Maker's Credibility with Predetermined Instruments for Forward-Looking Targets," Papers 2012.02806, arXiv.org.
    13. Chatelain, Jean-Bernard & Ralf, Kirsten, 2021. "Hopf Bifurcation From New-Keynesian Taylor Rule To Ramsey Optimal Policy," Macroeconomic Dynamics, Cambridge University Press, vol. 25(8), pages 2204-2236, December.
    14. Richhild Moessner, 2006. "Optimal discretionary policy in rational expectations models with regime switching," Bank of England working papers 299, Bank of England.
    15. Kwon, Hyosung & Miao, Jianjun, 2017. "Three types of robust Ramsey problems in a linear-quadratic framework," Journal of Economic Dynamics and Control, Elsevier, vol. 76(C), pages 211-231.
    16. Roberto M. Billi, 2006. "The Optimal Long-Run Inflation Rate for the U.S. Economy," Computing in Economics and Finance 2006 72, Society for Computational Economics.
    17. Roberto M. Billi, 2005. "The Optimal Inflation Buffer with a Zero Bound on Nominal Interest Rates," Computing in Economics and Finance 2005 25, Society for Computational Economics.
    18. Li Qin & Moïse Sidiropoulos & Eleftherios Spyromitros, 2010. "Robust Monetary Policy Under Uncertainty About Central Bank Preferences," Bulletin of Economic Research, Wiley Blackwell, vol. 62(2), pages 197-208, April.
    19. Matthew Canzoneri & Robert Cumby & Behzad Diba, 2015. "Monetary Policy and the Natural Rate of Interest," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(2-3), pages 383-414, March.
    20. Dai, Meixing & Spyromitros, Eleftherios, 2012. "A Note On Monetary Policy, Asset Prices, And Model Uncertainty," Macroeconomic Dynamics, Cambridge University Press, vol. 16(5), pages 777-790, November.
    21. Levine, Paul & Pearlman, Joseph, 2010. "Robust monetary rules under unstructured model uncertainty," Journal of Economic Dynamics and Control, Elsevier, vol. 34(3), pages 456-471, March.
    22. Kilponen, Juha & Leitemo, Kai, 2006. "Robustness in monetary policymaking: a case for the Friedman rule," Bank of Finland Research Discussion Papers 4/2006, Bank of Finland.
    23. Burkhard Heer & Stefan Rohrbacher & Christian Scharrer, 2014. "Aging, the Great Moderation and Business-Cycle Volatility in a Life-Cycle Model," CESifo Working Paper Series 4584, CESifo.
    24. Kohei Hasui, 2021. "How robustness can change the desirability of speed limit policy," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(5), pages 553-570, November.
    25. A. Hakan Kara, 2003. "Optimal Monetary Policy, Commitment, and Imperfect Credibility," Working Papers 0301, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    26. Jean-Bernard Chatelain & Kirsten Ralf, 2018. "The Indeterminacy of Determinacy with Fiscal, Macro-prudential or Taylor Rules," PSE Working Papers halshs-01877766, HAL.
    27. Arnulfo Rodriguez & Pedro N. Rodriguez, 2006. "Recursive Thick Modeling and the Choice of Monetary Policy in Mexico," Computing in Economics and Finance 2006 30, Society for Computational Economics.
    28. Araújo, Eurilton, 2013. "Robust monetary policy with the consumption-wealth channel," Journal of Economic Dynamics and Control, Elsevier, vol. 37(1), pages 296-311.
    29. Eleftherios SPYROMITROS & Li QIN, 2006. "Central bank transparency about model uncertainty and wage setters," Economics Bulletin, AccessEcon, vol. 5(18), pages 1-5.
    30. Meixing Dai, 2020. "La réponse de la BCE face à la pandémie de Covid-19," Post-Print hal-04080460, HAL.
    31. Ida, Daisuke & Okano, Mitsuhiro, 2023. "Optimal monetary policy delegation in a small-open new Keynesian model with robust control," Economic Modelling, Elsevier, vol. 120(C).
    32. Kai Leitemo & Ulf Soderstrom, 2004. "Robust Monetary Policy in the New-Keynesian Framework," Working Papers 273, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    33. Richard Dennis, 2013. "Imperfect Credibility and Robust Monetary Policy," Working Papers 2013_14, Business School - Economics, University of Glasgow.
    34. Peter Tillmann, 2009. "Robust Monetary Policy with the Cost Channel," Economica, London School of Economics and Political Science, vol. 76(303), pages 486-504, July.
    35. Traficante, Guido, 2013. "Monetary policy, parameter uncertainty and welfare," Journal of Macroeconomics, Elsevier, vol. 35(C), pages 73-80.
    36. Gino Cateau, 2017. "Price‐level versus inflation targeting under model uncertainty," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 50(2), pages 522-540, May.
    37. Paulo Vieira & Celsa Machado & Ana Paula Ribeiro, 2016. "Optimal Fiscal Simple Rules for Small and Large Countries of a Monetary Union," EcoMod2016 9685, EcoMod.
    38. Amélie Barbier-Gauchard & Meixing Dai & Claire Mainguy & Jamel Saadaoui & Moïse Sidiropoulos & Isabelle Terraz & Jamel Trabelsi, 2020. "Towards a more resilient European Union after the COVID-19 crisis," Working Papers of BETA 2020-33, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    39. Kantur, Zeynep & Özcan, Gülserim, 2019. "Optimal Policy Implications of Financial Uncertainty," MPRA Paper 95920, University Library of Munich, Germany.
    40. Fatemeh Labafi Feriz & Saeed Samadi & khadijeh Nasrollahi & Rasul Bakhshi Dastjerdi, 2018. "Robust Discretionary Monetary Policy under Cost-Push Shock Uncertainty of Iran’s Economy," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 22(2), pages 503-526, Spring.
    41. Bursian Dirk & Roth Markus, 2014. "Optimal policy and Taylor rule cross-checking under parameter uncertainty," The B.E. Journal of Macroeconomics, De Gruyter, vol. 14(1), pages 301-324, January.
    42. Rodríguez Arnulfo & González Fidel & González García Jesús R., 2007. "Uncertainty about the Persistence of Cost-Push Shocks and the Optimal Reaction of the Monetary Authority," Working Papers 2007-05, Banco de México.
    43. Abhijit Sen Gupta, 2010. "Robust monetary policies in small open economies," Oxford Economic Papers, Oxford University Press, vol. 62(2), pages 350-373, April.
    44. Jean-Guillaume Sahuc, 2003. "Robust European Monetary Policy Rules," Documents de recherche 03-06, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
    45. Dai, Meixing & Spyromitros, Eleftherios, 2012. "Inflation contract, central bank transparency and model uncertainty," Economic Modelling, Elsevier, vol. 29(6), pages 2371-2381.
    46. Richard Dennis, 2007. "Model uncertainty and monetary policy," Working Paper Series 2007-09, Federal Reserve Bank of San Francisco.
    47. Matthew Canzoneri & Robert Cumby, 2014. "Optimal Exchange Intervention in an Inflation Targeting Regime: Some Cautionary Tales," Open Economies Review, Springer, vol. 25(3), pages 429-450, July.
    48. Moisă ALTĂR & Alexie ALUPOAIEI & Adam ALTĂR-SAMUEL, 2017. "Dynamics in a New-Keynesian Model with Financial Accelerator and Uncertainty," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 51(2), pages 5-22.
    49. Richard Dennis, 2005. "Robust control with commitment: a modification to Hansen-Sargent," Working Paper Series 2005-20, Federal Reserve Bank of San Francisco.
    50. Tillmann Peter, 2009. "Does Model Uncertainty Justify Conservatism? Robustness and the Delegation of Monetary Policy," The B.E. Journal of Macroeconomics, De Gruyter, vol. 9(1), pages 1-28, June.
    51. Kilponen, Juha, 2004. "Robust expectations and uncertain models: a robust contol approach with application to the new Keynesian economy," Bank of Finland Research Discussion Papers 5/2004, Bank of Finland.
    52. Hasui, Kohei, 2020. "A Note On Robust Monetary Policy And Non-Zero Trend Inflation," Macroeconomic Dynamics, Cambridge University Press, vol. 24(6), pages 1574-1594, September.
    53. Giuseppe Diana & Moise Sidiropoulos, 2006. "Robust Control and Monetary Policy Delegation," Working Papers of BETA 2006-26, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    54. Heer, Burkhard & Scharrer, Christian, 2018. "The age-specific burdens of short-run fluctuations in government spending," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 45-75.
    55. André Marine Charlotte & Medina Espidio Sebastián, 2022. "Optimal Robust Monetary Policy in a Small Open Economy," Working Papers 2022-17, Banco de México.
    56. Juha Kilponen & Kai Leitemo, 2008. "Model Uncertainty and Delegation: A Case for Friedman's k‐Percent Money Growth Rule?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(2‐3), pages 547-556, March.
    57. Li Qin & Elefterios Spyromitros & Moïse Sidiropoulos, 2006. "Does Model Uncertainty Lead to Less Central Bank Transparency?," Working Papers of BETA 2006-22, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    58. Adam Altar-Samuel, 2008. "Robust Monetary Policy," Advances in Economic and Financial Research - DOFIN Working Paper Series 21, Bucharest University of Economics, Center for Advanced Research in Finance and Banking - CARFIB.
    59. Taro Ikeda, 2013. "Asymmetric forecasting and commitment policy in a robust control problem," Discussion Papers 1306, Graduate School of Economics, Kobe University.
    60. Vitale, Paolo, 2018. "Optimal monetary policy for a pessimistic central bank," Journal of Macroeconomics, Elsevier, vol. 58(C), pages 39-59.
    61. Francesco Giuli, 2007. "Robust control in a Sticky information economy," Working Papers in Public Economics 98, Department of Economics and Law, Sapienza University of Roma.
    62. Hansen, Lars Peter & Sargent, Thomas J., 2012. "Three types of ambiguity," Journal of Monetary Economics, Elsevier, vol. 59(5), pages 422-445.
    63. van der Ploeg, Frederick, 2009. "Prudent monetary policy and prediction of the output gap," Journal of Macroeconomics, Elsevier, vol. 31(2), pages 217-230, June.
    64. Gerke, Rafael & Hammermann, Felix & Lewis, Vivien, 2012. "Robust monetary policy in a model with financial distress," Journal of Macroeconomics, Elsevier, vol. 34(2), pages 318-325.
    65. Kirdan Lees, 2006. "What do robust policies look like for open economy inflation targeters?," Reserve Bank of New Zealand Discussion Paper Series DP2006/08, Reserve Bank of New Zealand.
    66. Adam – Nelu Altăr-Samuel, 2008. "Robust Monetary Policy," Romanian Economic Business Review, Romanian-American University, vol. 3(2), pages 19-28, June.
    67. Hasui Kohei, 2021. "Trend Growth and Robust Monetary Policy," The B.E. Journal of Macroeconomics, De Gruyter, vol. 21(2), pages 449-472, June.
    68. Sánchez, Marcelo, 2011. "Robust central banking under wage bargaining: Is monetary policy transparency beneficial?," Economic Modelling, Elsevier, vol. 28(1-2), pages 432-438, January.
    69. Tsasa Vangu, Jean-Paul Kimbambu, 2014. "Diagnostic de la politique monétaire en Rép. Dém. Congo – Approche par l’Equilibre Général Dynamique Stochastique," Dynare Working Papers 38, CEPREMAP.
    70. Marcelo Sánchez, 2013. "On the Limits of Transparency: The Role of Imperfect Central Bank Knowledge," International Finance, Wiley Blackwell, vol. 16(2), pages 245-271, June.
    71. André Marine Charlotte & Dai Meixing, 2020. "The limits to robust monetary policy in a small open economy with learning agents," Working Papers 2020-12, Banco de México.
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    73. Meixing DAI & Eleftherios SPYROMITROS, 2008. "Monetary policy, asset prices and model uncertainty," Working Papers of BETA 2008-15, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    74. Olalla, Myriam García & Gómez, Alejandro Ruiz, 2011. "Robust control and central banking behaviour," Economic Modelling, Elsevier, vol. 28(3), pages 1265-1278, May.
    75. Lee, Sang Seok & Luk, Paul, 2018. "The Asian Financial Crisis and international reserve accumulation: A robust control approach," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 284-309.

  8. Favara, Giovanni & Giordani, Paolo, 2002. "Reconsidering the Role of Money for Output, Prices and Interest Rates," SSE/EFI Working Paper Series in Economics and Finance 514, Stockholm School of Economics.

    Cited by:

    1. Alessandro Gobbi & Tim Willems, 2011. "Identifying US Monetary Policy Shocks through Sign Restrictions in Dollarized Countries," Tinbergen Institute Discussion Papers 11-145/2, Tinbergen Institute.
    2. Maral Kichian, 2012. "Financial Conditions and the Money-Output Relationship in Canada," Staff Working Papers 12-33, Bank of Canada.
    3. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with heteroskedasticity: A review of different volatility models," Econometrics and Statistics, Elsevier, vol. 1(C), pages 2-18.
    4. Barthélemy, Jean & Clerc, Laurent & Marx, Magali, 2011. "A two-pillar DSGE monetary policy model for the euro area," Economic Modelling, Elsevier, vol. 28(3), pages 1303-1316, May.
    5. Fabio Canova & Tobias Menz, 2009. "Does money matter in shaping domestic business cycles? An international investigation (with appendices)," Economics Working Papers 1242, Department of Economics and Business, Universitat Pompeu Fabra, revised Nov 2010.
    6. Efrem Castelnuovo, 2009. "Estimating the Evolution of Money's Role in the U.S. Monetary Business Cycle," "Marco Fanno" Working Papers 0103, Dipartimento di Scienze Economiche "Marco Fanno".
    7. Giovanni Caggiano & Efrem Castelnuovo & Olivier Damette & Antoine Parent & Giovanni Pellegrino, 2017. "Liquidity traps and large-scale financial crises," Post-Print halshs-01675562, HAL.
    8. Seitz, Franz & Albuquerque, Bruno & Baumann, Ursel, 2015. "The Information Content Of Money And Credit For US Activity," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113066, Verein für Socialpolitik / German Economic Association.
    9. El-Shagi, Makram & Kelly, Logan, 2019. "What can we learn from country-level liquidity in the EMU?," Journal of Financial Stability, Elsevier, vol. 42(C), pages 75-83.
    10. Karanassou, Marika & Sala, Hector, 2010. "The US inflation-unemployment trade-off revisited: New evidence for policy-making," Journal of Policy Modeling, Elsevier, vol. 32(6), pages 758-777, November.
    11. Caraiani, Petre, 2016. "Money and output causality: A structural approach," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 220-236.
    12. Poilly, Céline, 2010. "Does money matter for the identification of monetary policy shocks: A DSGE perspective," Journal of Economic Dynamics and Control, Elsevier, vol. 34(10), pages 2159-2178, October.
    13. Mariano Kulish & Stephen Elias, 2013. "Direct effects of money on aggregate demand: another look at the evidence," Applied Economics, Taylor & Francis Journals, vol. 45(27), pages 3801-3809, September.
    14. Paolo Zagaglia, 2011. "Forecasting Long-Term Interest Rates with a Dynamic General Equilibrium Model of the Euro Area: The Role of the Feedback," Working Paper series 19_11, Rimini Centre for Economic Analysis.
    15. Robert F. Mulligan, 2016. "An Empirical Comparison of Canadian-American Business Cycle Fluctuations with Special Reference to the Phillips Curve," Advances in Austrian Economics, in: Studies in Austrian Macroeconomics, volume 20, pages 163-194, Emerald Group Publishing Limited.
    16. Petre Caraiani, 2014. "Do money and financial variables help forecasting output in emerging European Economies?," Empirical Economics, Springer, vol. 46(2), pages 743-763, March.
    17. Lindé, Jesper, 2003. "Monetary Policy Shocks and Business Cycle Fluctuations in a Small Open Economy: Sweden 1986-2002," Working Paper Series 153, Sveriges Riksbank (Central Bank of Sweden).
    18. Araújo, Eurilton, 2015. "Monetary policy objectives and Money’s role in U.S. business cycles," Journal of Macroeconomics, Elsevier, vol. 45(C), pages 85-107.
    19. Edward Nelson, 2008. "Why money growth determines inflation in the long run: answering the Woodford critique," Working Papers 2008-013, Federal Reserve Bank of St. Louis.
    20. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with smooth transition in variances," Journal of Economic Dynamics and Control, Elsevier, vol. 84(C), pages 43-57.
    21. Qureshi, Irfan, 2018. "Money Aggregates and Determinacy : A Reinterpretation of Monetary Policy During the Great Inflation," The Warwick Economics Research Paper Series (TWERPS) 1156, University of Warwick, Department of Economics.
    22. Vespignani, Joaquin L. & Ratti, Ronald A., 2013. "International monetary transmission to the Euro area: Evidence from the U.S., Japan and China," MPRA Paper 49153, University Library of Munich, Germany.
    23. Helmut Lütkepohl & Aleksei Netsunajev, 2014. "Structural Vector Autoregressions with Smooth Transition in Variances: The Interaction between U.S. Monetary Policy and the Stock Market," Discussion Papers of DIW Berlin 1388, DIW Berlin, German Institute for Economic Research.
    24. Rasool, Haroon & Adil, Masudul Hasan & Tarique, Md, 2018. "An Empirical Evidence of Dynamic Interaction among price level, interest rate, money supply and real income: The case of the Indian Economy," MPRA Paper 87452, University Library of Munich, Germany.
    25. Chevapatrakul, Thanaset & Kim, Tae-Hwan & Mizen, Paul, 2012. "Monetary information and monetary policy decisions: Evidence from the euroarea and the UK," Journal of Macroeconomics, Elsevier, vol. 34(2), pages 326-341.
    26. Donato Masciandaro, 2023. "How Elastic and Predictable Money Should Be: Flexible Monetary Policy Rules from the Great Moderation to the New Normal Times (1993-2023)," BAFFI CAREFIN Working Papers 23196, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    27. Ahrens, Steffen & Snower, Dennis J., 2014. "Envy, guilt, and the Phillips curve," Journal of Economic Behavior & Organization, Elsevier, vol. 99(C), pages 69-84.
    28. Lioui, Abraham & Poncet, Patrice, 2012. "On model ambiguity and money neutrality," Journal of Macroeconomics, Elsevier, vol. 34(4), pages 1020-1033.
    29. Wang, Ling, 2022. "The dynamics of money supply determination under asset purchase programs: A market-based versus a bank-based financial system," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    30. D. Masciandaro, 2019. "What Bird Is That? Central Banking And Monetary Policy In The Last Forty Years," BAFFI CAREFIN Working Papers 19127, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    31. Jagjit S. Chadha & Luisa Corrado & Sean Holly, 2013. "A Note on Money and the Conduct of Monetary Policy," Cambridge Working Papers in Economics 1329, Faculty of Economics, University of Cambridge.
    32. Fabio Canova & Tobias Menz, 2011. "Does Money Matter in Shaping Domestic Business Cycles? An International Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(4), pages 577-607, June.
    33. Helmut Lütkepohl & Aleksei Netšunajev, 2015. "Structural Vector Autoregressions with Heteroskedasticity - A Comparison of Different Volatility Models," CESifo Working Paper Series 5308, CESifo.
    34. Sousa, Ricardo M., 2010. "Housing wealth, financial wealth, money demand and policy rule: Evidence from the euro area," The North American Journal of Economics and Finance, Elsevier, vol. 21(1), pages 88-105, March.
    35. Zanetti, Francesco, 2012. "Banking and the role of money in the business cycle," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 87-94.
    36. Marika Karanassou & Hector Sala, 2009. "The US Inflation-Unemployment Tradeoff: Methodological Issues and Further Evidence," Working Papers 647, Queen Mary University of London, School of Economics and Finance.
    37. Barigozzi, Matteo, 2018. "On the stability of euro area money demand and its implications for monetary policy," LSE Research Online Documents on Economics 87283, London School of Economics and Political Science, LSE Library.
    38. Zagaglia, Paolo, 2009. "Forecasting with a DSGE Model of the term Structure of Interest Rates: The Role of the Feedback," Research Papers in Economics 2009:14, Stockholm University, Department of Economics.
    39. Claus Brand & Hans-Eggert Reimers & Franz Seitz, 2003. "Narrow Money and the Business Cycle: Theoretical aspects and euro area evdence," Macroeconomics 0303012, University Library of Munich, Germany.
    40. Dmitry Kulikov & Aleksei Netsunajev, 2016. "Identifying Shocks in Structural VAR models via heteroskedasticity: a Bayesian approach," Bank of Estonia Working Papers wp2015-8, Bank of Estonia, revised 19 Feb 2016.
    41. S. Boragan Aruoba & Frank Schorfheide, 2009. "Sticky Prices Versus Monetary Frictions: An Estimation of Policy Trade-offs," NBER Working Papers 14870, National Bureau of Economic Research, Inc.
    42. Andrea Vaona, 2015. "Anomalous empirical evidence on money long-run super-neutrality and the vertical long-run Phillips curve," Working Papers 17/2015, University of Verona, Department of Economics.
    43. Qureshi, Irfan A., 2021. "The Role Of Money In Federal Reserve Policy," Macroeconomic Dynamics, Cambridge University Press, vol. 25(8), pages 2037-2057, December.
    44. Victor Song & Libo Xu, 2023. "Do Monetary Policy Shocks Have Asymmetric Effects on Stock Market?," Open Economies Review, Springer, vol. 34(5), pages 1063-1078, November.
    45. Di Bartolomeo Giovanni & Tirelli Patrizio & Acocella Nicola, 2011. "Trend inflation, the labor market wedge, and the non-vertical Phillips curve," wp.comunite 0081, Department of Communication, University of Teramo.
    46. Dmitry Kulikov & Aleksei Netsunajev, 2013. "Identifying monetary policy shocks via heteroskedasticity: a Bayesian approach," Bank of Estonia Working Papers wp2013-9, Bank of Estonia, revised 09 Dec 2013.
    47. Mr. Helge Berger & Mr. Henning Weber, 2012. "Money As Indicator for the Natural Rate of Interest," IMF Working Papers 2012/006, International Monetary Fund.
    48. Fredj Jawadi & Sushanta K. Mallick & Ricardo M. Sousa, 2011. "Monetary Policy Rules in the BRICS: How Important is Nonlinearity?," NIPE Working Papers 18/2011, NIPE - Universidade do Minho.
    49. Aviral Kumar Tiwari & Olaolu Richard Olayeni & Reza Sherafatian-Jahromi & Olofin Sodik Adejonwo, 2019. "Output Gap, Money Growth and Interest Rate in Japan: Evidence from Wavelet Analysis," Arthaniti: Journal of Economic Theory and Practice, , vol. 18(2), pages 171-184, December.
    50. Donato Masciandaro & Romano Vincenzo Tarsia, 2021. "Society, Politicians, Climate Change and Central Banks: An Index of Green Activism," BAFFI CAREFIN Working Papers 21167, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
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    1. D. Masciandaro, 2019. "What Bird Is That? Central Banking And Monetary Policy In The Last Forty Years," BAFFI CAREFIN Working Papers 19127, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    2. Masciandaro, Donato, 2022. "Independence, conservatism, and beyond: Monetary policy, central bank governance and central banker preferences (1981–2021)," Journal of International Money and Finance, Elsevier, vol. 122(C).
    3. Bernd Hayo & Carsten Hefeker, 2001. "Do We Really Need Central Bank Independence? A Critical Re- examination," Macroeconomics 0103006, University Library of Munich, Germany.
    4. Hayo, Bernd & Hefeker, Carsten, 2002. "Reconsidering central bank independence," European Journal of Political Economy, Elsevier, vol. 18(4), pages 653-674, November.

  10. Giordani, Paolo, 2001. "An Alternative Explanation of the Price Puzzle," Working Paper Series 125, Sveriges Riksbank (Central Bank of Sweden).

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    1. Khalfaoui, Rabeh & Padhan, Hemachandra & Tiwari, Aviral Kumar & Hammoudeh, Shawkat, 2020. "Understanding the time-frequency dynamics of money demand, oil prices and macroeconomic variables: The case of India," Resources Policy, Elsevier, vol. 68(C).
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    4. Balázs Égert & Ronald MacDonald, 2009. "Monetary Transmission Mechanism In Central And Eastern Europe: Surveying The Surveyable," Journal of Economic Surveys, Wiley Blackwell, vol. 23(2), pages 277-327, April.
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    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.
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    146. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Economic Uncertainty: A Geometric Indicator of Discrepancy Among Experts’ Expectations," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(1), pages 95-114, May.
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    151. Dovern, Jonas, 2015. "A multivariate analysis of forecast disagreement: Confronting models of disagreement with survey data," European Economic Review, Elsevier, vol. 80(C), pages 16-35.
    152. Clements, Michael P., 2008. "Consensus and uncertainty: Using forecast probabilities of output declines," International Journal of Forecasting, Elsevier, vol. 24(1), pages 76-86.
    153. Alessandro Barbera & Dora Xia & Sonya Zhu, 2023. "The term structure of inflation forecasts disagreement and monetary policy transmission," BIS Working Papers 1114, Bank for International Settlements.
    154. Lieven Baele & Geert Bekaert & Koen Inghelbrecht, 2007. "The determinants of stock and bond return comovements," Working Paper Research 119, National Bank of Belgium.
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    156. Cem Cakmakli & Hamza Demircan, 2020. "Using Survey Information for Improving the Density Nowcasting of US GDP with a Focus on Predictive Performance during Covid-19 Pandemic," Koç University-TUSIAD Economic Research Forum Working Papers 2016, Koc University-TUSIAD Economic Research Forum.
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Articles

  1. Giordani, Paolo & Jacobson, Tor & Schedvin, Erik von & Villani, Mattias, 2014. "Taking the Twists into Account: Predicting Firm Bankruptcy Risk with Splines of Financial Ratios," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(4), pages 1071-1099, August.
    See citations under working paper version above.
  2. Pitt, Michael K. & Silva, Ralph dos Santos & Giordani, Paolo & Kohn, Robert, 2012. "On some properties of Markov chain Monte Carlo simulation methods based on the particle filter," Journal of Econometrics, Elsevier, vol. 171(2), pages 134-151.

    Cited by:

    1. Leopoldo Catania & Nima Nonejad, 2016. "Density Forecasts and the Leverage Effect: Some Evidence from Observation and Parameter-Driven Volatility Models," Papers 1605.00230, arXiv.org, revised Nov 2016.
    2. Douc, Randal & Olsson, Jimmy & Roueff, François, 2020. "Posterior consistency for partially observed Markov models," Stochastic Processes and their Applications, Elsevier, vol. 130(2), pages 733-759.
    3. Jonathan Benchimol & Sergey Ivashchenko, 2020. "Switching Volatility in a Nonlinear Open Economy," CFDS Discussion Paper Series 2020/8, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China.
    4. Golightly Andrew & Wilkinson Darren J., 2015. "Bayesian inference for Markov jump processes with informative observations," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 14(2), pages 169-188, April.
    5. Brix, Anne Floor & Lunde, Asger & Wei, Wei, 2018. "A generalized Schwartz model for energy spot prices — Estimation using a particle MCMC method," Energy Economics, Elsevier, vol. 72(C), pages 560-582.
    6. James M. Nason & Gregor W. Smith, 2013. "Measuring The Slowly Evolving Trend In Us Inflation With Professional Forecasts," Working Paper 1316, Economics Department, Queen's University.
    7. Matias Quiroz & Mattias Villani & Robert Kohn & Minh-Ngoc Tran & Khue-Dung Dang, 2018. "Subsampling MCMC - an Introduction for the Survey Statistician," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 80(1), pages 33-69, December.
    8. Tsionas, Mike G. & Malikov, Emir & Kumbhakar, Subal C., 2019. "Endogenous Dynamic Efficiency in the Intertemporal Optimization Models of Firm Behavior," MPRA Paper 97780, University Library of Munich, Germany.
    9. Wei Wei & Asger Lunde, 2023. "Identifying Risk Factors and Their Premia: A Study on Electricity Prices," Journal of Financial Econometrics, Oxford University Press, vol. 21(5), pages 1647-1679.
    10. Emmanuel C. Mamatzakis & Mike G. Tsionas, 2021. "A Bayesian panel stochastic volatility measure of financial stability," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5363-5384, October.
    11. Hall, Jamie, 2012. "Rapid estimation of nonlinear DSGE models," MPRA Paper 41218, University Library of Munich, Germany.
    12. Rubio-Ramírez, Juan Francisco & Schorfheide, Frank & Fernández-Villaverde, Jesús, 2015. "Solution and Estimation Methods for DSGE Models," CEPR Discussion Papers 11032, C.E.P.R. Discussion Papers.
    13. Gael M. Martin & David T. Frazier & Christian P. Robert, 2022. "Computing Bayes: From Then `Til Now," Monash Econometrics and Business Statistics Working Papers 14/22, Monash University, Department of Econometrics and Business Statistics.
    14. Jonathan U Harrison & Ruth E Baker, 2018. "The impact of temporal sampling resolution on parameter inference for biological transport models," PLOS Computational Biology, Public Library of Science, vol. 14(6), pages 1-30, June.
    15. Johan Dahlin & Thomas B. Schon, 2015. "Getting Started with Particle Metropolis-Hastings for Inference in Nonlinear Dynamical Models," Papers 1511.01707, arXiv.org, revised Mar 2019.
    16. Gareth W. Peters & Rodrigo S. Targino & Mario V. Wüthrich, 2017. "Bayesian Modelling, Monte Carlo Sampling and Capital Allocation of Insurance Risks," Risks, MDPI, vol. 5(4), pages 1-51, September.
    17. Elmar Mertens & James M. Nason, 2018. "Inflation and professional forecast dynamics: an evaluation of stickiness, persistence, and volatility," BIS Working Papers 713, Bank for International Settlements.
    18. Edward P. Herbst & Frank Schorfheide, 2016. "Tempered Particle Filtering," Finance and Economics Discussion Series 2016-072, Board of Governors of the Federal Reserve System (U.S.).
    19. Lux, Thomas, 2020. "Bayesian estimation of agent-based models via adaptive particle Markov chain Monte Carlo," Economics Working Papers 2020-01, Christian-Albrechts-University of Kiel, Department of Economics.
    20. Neil Shephard, 2013. "Martingale unobserved component models," Economics Papers 2013-W01, Economics Group, Nuffield College, University of Oxford.
    21. Chen, Ji & Yang, Xinglin & Liu, Xiliang, 2022. "Learning, disagreement and inflation forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    22. Audrone Virbickaite & Hedibert F. Lopes & Maria Concepción Ausín & Pedro Galeano, 2018. "Particle Learning for Bayesian Semi-Parametric Stochastic Volatility Model," DEA Working Papers 88, Universitat de les Illes Balears, Departament d'Economía Aplicada.
    23. Johan Dahlin & Mattias Villani & Thomas B. Schon, 2015. "Bayesian optimisation for fast approximate inference in state-space models with intractable likelihoods," Papers 1506.06975, arXiv.org, revised Jun 2017.
    24. Panayotis G. Michaelides & Efthymios G. Tsionas & Angelos T. Vouldis & Konstantinos N. Konstantakis & Panagiotis Patrinos, 2018. "A Semi-Parametric Non-linear Neural Network Filter: Theory and Empirical Evidence," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 637-675, March.
    25. István Barra & Lennart Hoogerheide & Siem Jan Koopman & André Lucas, 2017. "Joint Bayesian Analysis of Parameters and States in Nonlinear non‐Gaussian State Space Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(5), pages 1003-1026, August.
    26. Mamatzakis, Emmanuel C. & Tsionas, Mike G., 2021. "Making inference of British household's happiness efficiency: A Bayesian latent model," European Journal of Operational Research, Elsevier, vol. 294(1), pages 312-326.
    27. Arnaud Doucet & Neil Shephard, 2012. "Robust inference on parameters via particle filters and sandwich covariance matrices," Economics Papers 2012-W05, Economics Group, Nuffield College, University of Oxford.
    28. Gael M. Martin & David T. Frazier & Christian P. Robert, 2020. "Computing Bayes: Bayesian Computation from 1763 to the 21st Century," Monash Econometrics and Business Statistics Working Papers 14/20, Monash University, Department of Econometrics and Business Statistics.
    29. Hall, Jamie, 2012. "Consumption dynamics in general equilibrium," MPRA Paper 43933, University Library of Munich, Germany.
    30. Tsionas, Mike & Patel, Pankaj C. & Guedes, Maria João, 2022. "Endogenous efficiency of the dynamic profit maximization in the intertemporal production models of venture behavior," International Journal of Production Economics, Elsevier, vol. 246(C).
    31. Fulop, Andras & Li, Junye, 2013. "Efficient learning via simulation: A marginalized resample-move approach," Journal of Econometrics, Elsevier, vol. 176(2), pages 146-161.
    32. Cheng, Jing & Chan, Ngai Hang, 2019. "Efficient inference for nonlinear state space models: An automatic sample size selection rule," Computational Statistics & Data Analysis, Elsevier, vol. 138(C), pages 143-154.
    33. Pratiti Chatterjee & David Gunawan & Robert Kohn, 2020. "The Interaction Between Credit Constraints and Uncertainty Shocks," Papers 2004.14719, arXiv.org.
    34. An, Dawn & Choi, Joo-Ho & Kim, Nam Ho, 2013. "Prognostics 101: A tutorial for particle filter-based prognostics algorithm using Matlab," Reliability Engineering and System Safety, Elsevier, vol. 115(C), pages 161-169.
    35. Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman, 2019. "Bayesian Risk Forecasting for Long Horizons," Tinbergen Institute Discussion Papers 19-018/III, Tinbergen Institute.
    36. Chris Sherlock, 2016. "Optimal Scaling for the Pseudo-Marginal Random Walk Metropolis: Insensitivity to the Noise Generating Mechanism," Methodology and Computing in Applied Probability, Springer, vol. 18(3), pages 869-884, September.
    37. Delis, Manthos D. & Tsionas, Mike G., 2018. "Measuring management practices," International Journal of Production Economics, Elsevier, vol. 199(C), pages 65-77.
    38. Golightly, Andrew & Bradley, Emma & Lowe, Tom & Gillespie, Colin S., 2019. "Correlated pseudo-marginal schemes for time-discretised stochastic kinetic models," Computational Statistics & Data Analysis, Elsevier, vol. 136(C), pages 92-107.
    39. Martin, Gael M. & Frazier, David T. & Maneesoonthorn, Worapree & Loaiza-Maya, Rubén & Huber, Florian & Koop, Gary & Maheu, John & Nibbering, Didier & Panagiotelis, Anastasios, 2024. "Bayesian forecasting in economics and finance: A modern review," International Journal of Forecasting, Elsevier, vol. 40(2), pages 811-839.
    40. Fredrik Lindsten & Randal Douc & Eric Moulines, 2015. "Uniform Ergodicity of the Particle Gibbs Sampler," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(3), pages 775-797, September.
    41. 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.
    42. Nicolas Chopin & Sumeetpal S. Singh, 2013. "On the Particle Gibbs Sampler," Working Papers 2013-41, Center for Research in Economics and Statistics.
    43. Tsionas, Mike G. & Michaelides, Panayotis G., 2017. "Neglected chaos in international stock markets: Bayesian analysis of the joint return–volatility dynamical system," LSE Research Online Documents on Economics 80749, London School of Economics and Political Science, LSE Library.
    44. Joshua Chan & Eric Eisenstat & Xuewen Yu, 2022. "Large Bayesian VARs with Factor Stochastic Volatility: Identification, Order Invariance and Structural Analysis," Papers 2207.03988, arXiv.org.
    45. Quiroz, Matias & Villani, Mattias & Kohn, Robert, 2015. "Speeding Up Mcmc By Efficient Data Subsampling," Working Paper Series 297, Sveriges Riksbank (Central Bank of Sweden).
    46. Tsionas, Mike G. & Michaelides, Panayotis G., 2017. "Bayesian analysis of chaos: The joint return-volatility dynamical system," MPRA Paper 80632, University Library of Munich, Germany.
    47. Dang, Khue-Dung & Quiroz, Matias & Kohn, Robert & Tran, Minh-Ngoc & Villani, Mattias, 2019. "Hamiltonian Monte Carlo with Energy Conserving Subsampling," Working Paper Series 372, Sveriges Riksbank (Central Bank of Sweden).
    48. Wei Wei & Asger Lunde, 2020. "Identifying Risk Factors and Their Premia: A Study on Electricity Prices," Monash Econometrics and Business Statistics Working Papers 10/20, Monash University, Department of Econometrics and Business Statistics.
    49. Scharth, Marcel & Kohn, Robert, 2016. "Particle efficient importance sampling," Journal of Econometrics, Elsevier, vol. 190(1), pages 133-147.
    50. Asger Lunde & Anne Floor Brix & Wei Wei, 2015. "A Generalized Schwartz Model for Energy Spot Prices - Estimation using a Particle MCMC Method," CREATES Research Papers 2015-46, Department of Economics and Business Economics, Aarhus University.
    51. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    52. Kim, Jaeho, 2015. "Bayesian Inference in a Non-linear/Non-Gaussian Switching State Space Model: Regime-dependent Leverage Effect in the U.S. Stock Market," MPRA Paper 67153, University Library of Munich, Germany.
    53. Wolf, Elias, 2023. "Estimating Growth at Risk with Skewed Stochastic Volatility Models," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage" 277696, Verein für Socialpolitik / German Economic Association.
    54. Nikolaos Englezos & Xanthi Kartala & Phoebe Koundouri & Mike Tsionas & Angelos Alamanos, 2021. "A Novel Hydro - Economic - Econometric Approach for Integrated Transboundary Water Management under Uncertainty," DEOS Working Papers 2101, Athens University of Economics and Business.
    55. 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.
    56. Emmanuel Mamatzakis & Mike Tsionas, 2018. "A Bayesian dynamic model to test persistence in funds' performance," Working Paper series 18-23, Rimini Centre for Economic Analysis.
    57. Sergey Ivashchenko & Semih Emre Cekin & Rangan Gupta & Chien-Chiang Lee, 2022. "Real-Time Forecast of DSGE Models with Time-Varying Volatility in GARCH Form," Working Papers 202204, University of Pretoria, Department of Economics.
    58. Patrick Leung & Catherine S. Forbes & Gael M. Martin & Brendan McCabe, 2016. "Data-driven particle Filters for particle Markov Chain Monte Carlo," Monash Econometrics and Business Statistics Working Papers 17/16, Monash University, Department of Econometrics and Business Statistics.
    59. Virbickaitė, Audronė & Frey, Christoph & Macedo, Demian N., 2020. "Bayesian sequential stock return prediction through copulas," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    60. Takashi Kamihigashi & Hiroyuki Watanabe, 2016. "A Multiple-Try Extension of the Particle Marginal Metropolis-Hastings (PMMH) Algorithm with an Independent Proposal," Discussion Paper Series DP2016-36, Research Institute for Economics & Business Administration, Kobe University.
    61. Kleppe, Tore Selland & Oglend, Atle, 2017. "Estimating the competitive storage model: A simulated likelihood approach," Econometrics and Statistics, Elsevier, vol. 4(C), pages 39-56.
    62. Wiqvist, Samuel & Golightly, Andrew & McLean, Ashleigh T. & Picchini, Umberto, 2021. "Efficient inference for stochastic differential equation mixed-effects models using correlated particle pseudo-marginal algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
    63. Deschamps, P., 2015. "Alternative Formulation of the Leverage Effect in a Stochastic Volatility Model with Asymmetric Heavy-Tailed Errors," LIDAM Discussion Papers CORE 2015020, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    64. Beatrice Franzolini & Alexandros Beskos & Maria De Iorio & Warrick Poklewski Koziell & Karolina Grzeszkiewicz, 2022. "Change point detection in dynamic Gaussian graphical models: the impact of COVID-19 pandemic on the US stock market," Papers 2208.00952, arXiv.org, revised May 2023.
    65. Fileccia, Gaetano & Sgarra, Carlo, 2018. "A particle filtering approach to oil futures price calibration and forecasting," Journal of Commodity Markets, Elsevier, vol. 9(C), pages 21-34.
    66. Matti Vihola & Jouni Helske & Jordan Franks, 2020. "Importance sampling type estimators based on approximate marginal Markov chain Monte Carlo," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(4), pages 1339-1376, December.
    67. Sanha Noh, 2020. "Posterior Inference on Parameters in a Nonlinear DSGE Model via Gaussian-Based Filters," Computational Economics, Springer;Society for Computational Economics, vol. 56(4), pages 795-841, December.
    68. Nonejad, Nima, 2017. "Parameter instability, stochastic volatility and estimation based on simulated likelihood: Evidence from the crude oil market," Economic Modelling, Elsevier, vol. 61(C), pages 388-408.
    69. 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.
    70. Thomas Lux, 2022. "Bayesian Estimation of Agent-Based Models via Adaptive Particle Markov Chain Monte Carlo," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 451-477, August.
    71. Murray, Lawrence M., 2015. "Bayesian State-Space Modelling on High-Performance Hardware Using LibBi," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i10).
    72. Quiroz, Matias & Villani, Mattias & Kohn, Robert, 2015. "Scalable Mcmc For Large Data Problems Using Data Subsampling And The Difference Estimator," Working Paper Series 306, Sveriges Riksbank (Central Bank of Sweden).
    73. Gallant, A. Ronald & Hong, Han & Khwaja, Ahmed, 2018. "A Bayesian approach to estimation of dynamic models with small and large number of heterogeneous players and latent serially correlated states," Journal of Econometrics, Elsevier, vol. 203(1), pages 19-32.

  3. Paolo Giordani & Xiuyan Mun & Robert Kohn, 2012. "Efficient Estimation of Covariance Matrices using Posterior Mode Multiple Shrinkage," Journal of Financial Econometrics, Oxford University Press, vol. 11(1), pages 154-192, December.

    Cited by:

    1. Martin Burda & Artem Prokhorov, 2012. "Copula Based Factorization in Bayesian Multivariate Infinite Mixture Models," Working Papers 12012, Concordia University, Department of Economics.

  4. Bulkley, George & Giordani, Paolo, 2011. "Structural breaks, parameter uncertainty, and term structure puzzles," Journal of Financial Economics, Elsevier, vol. 102(1), pages 222-232, October.

    Cited by:

    1. Karsten Schweikert, 2022. "Detecting Multiple Structural Breaks in Systems of Linear Regression Equations with Integrated and Stationary Regressors," Papers 2201.05430, arXiv.org, revised Sep 2024.
    2. Ono, Sadayuki, 2019. "Term structure dynamics in a monetary economy with learning," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 730-745.

  5. Giordani, Paolo & Villani, Mattias, 2010. "Forecasting macroeconomic time series with locally adaptive signal extraction," International Journal of Forecasting, Elsevier, vol. 26(2), pages 312-325, April.
    See citations under working paper version above.
  6. Villani, Mattias & Kohn, Robert & Giordani, Paolo, 2009. "Regression density estimation using smooth adaptive Gaussian mixtures," Journal of Econometrics, Elsevier, vol. 153(2), pages 155-173, December.

    Cited by:

    1. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    2. Mike G. Tsionas, 2017. "“When, Where, and How” of Efficiency Estimation: Improved Procedures for Stochastic Frontier Modeling," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 948-965, July.
    3. Gregor Kastner, 2016. "Sparse Bayesian time-varying covariance estimation in many dimensions," Papers 1608.08468, arXiv.org, revised Nov 2017.
    4. Li, Feng & Kang, Yanfei, 2018. "Improving forecasting performance using covariate-dependent copula models," International Journal of Forecasting, Elsevier, vol. 34(3), pages 456-476.
    5. Paolo Giordani & Xiuyan Mun & Robert Kohn, 2012. "Efficient Estimation of Covariance Matrices using Posterior Mode Multiple Shrinkage," Journal of Financial Econometrics, Oxford University Press, vol. 11(1), pages 154-192, December.
    6. Valentin Zelenyuk & Valentyn Panchenko, 2023. "Bayesian Artificial Neural Networks for Frontier Efficiency Analysis," CEPA Working Papers Series WP022023, School of Economics, University of Queensland, Australia.
    7. Michael P. Keane & Jonathan D. Ketcham & Nicolai V. Kuminoff & Timothy Neal, 2019. "Evaluating Consumers' Choices of Medicare Part D Plans: A Study in Behavioral Welfare Economics," NBER Working Papers 25652, National Bureau of Economic Research, Inc.
    8. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2015. "Dynamic predictive density combinations for large data sets in economics and finance," Working Paper 2015/12, Norges Bank.
    9. Villani, Mattias & Kohn, Robert & Nott, David J., 2012. "Generalized smooth finite mixtures," Journal of Econometrics, Elsevier, vol. 171(2), pages 121-133.
    10. Yanfei Kang & Rob J Hyndman & Feng Li, 2018. "Efficient generation of time series with diverse and controllable characteristics," Monash Econometrics and Business Statistics Working Papers 15/18, Monash University, Department of Econometrics and Business Statistics.
    11. Meitz, Mika & Saikkonen, Pentti, 2021. "Testing for observation-dependent regime switching in mixture autoregressive models," Journal of Econometrics, Elsevier, vol. 222(1), pages 601-624.
    12. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2020. "A Bayesian Dynamic Compositional Model for Large Density Combinations in Finance," Working Paper series 20-27, Rimini Centre for Economic Analysis.
    13. Mike Tsionas & Christopher F. Parmeter & Valentin Zelenyuk, 2021. "Bridging the Divide? Bayesian Artificial Neural Networks for Frontier Efficiency Analysis," CEPA Working Papers Series WP082021, School of Economics, University of Queensland, Australia.
    14. Mike Tsionas & Marwan Izzeldin & Lorenzo Trapani, 2019. "Bayesian estimation of large dimensional time varying VARs using copulas," Papers 1912.12527, arXiv.org.
    15. Tim Salimans, 2011. "Variable Selection and Functional Form Uncertainty in Cross-Country Growth Regressions," Tinbergen Institute Discussion Papers 11-012/4, Tinbergen Institute.
    16. Kalli, Maria & Griffin, Jim E., 2018. "Bayesian nonparametric vector autoregressive models," Journal of Econometrics, Elsevier, vol. 203(2), pages 267-282.
    17. Kalliovirta, Leena & Meitz, Mika & Saikkonen, Pentti, 2016. "Gaussian mixture vector autoregression," Journal of Econometrics, Elsevier, vol. 192(2), pages 485-498.
    18. Talagala, Thiyanga S. & Li, Feng & Kang, Yanfei, 2022. "FFORMPP: Feature-based forecast model performance prediction," International Journal of Forecasting, Elsevier, vol. 38(3), pages 920-943.
    19. Norets, Andriy, 2015. "Bayesian regression with nonparametric heteroskedasticity," Journal of Econometrics, Elsevier, vol. 185(2), pages 409-419.
    20. Norets, Andriy & Pelenis, Justinas, 2012. "Bayesian modeling of joint and conditional distributions," Journal of Econometrics, Elsevier, vol. 168(2), pages 332-346.
    21. Cozzini, Alberto & Jasra, Ajay & Montana, Giovanni & Persing, Adam, 2014. "A Bayesian mixture of lasso regressions with t-errors," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 84-97.
    22. Cheng Peng & Stanislav Uryasev, 2023. "Factor Model of Mixtures," Papers 2301.13843, arXiv.org, revised Mar 2023.
    23. Marco Berrettini & Giuliano Galimberti & Saverio Ranciati, 2023. "Semiparametric finite mixture of regression models with Bayesian P-splines," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 17(3), pages 745-775, September.
    24. Norets, Andriy & Pelenis, Justinas, 2022. "Adaptive Bayesian estimation of conditional discrete-continuous distributions with an application to stock market trading activity," Journal of Econometrics, Elsevier, vol. 230(1), pages 62-82.
    25. Quiroz, Matias & Villani, Mattias, 2013. "Dynamic mixture-of-experts models for longitudinal and discrete-time survival data," Working Paper Series 268, Sveriges Riksbank (Central Bank of Sweden).

  7. Favara, Giovanni & Giordani, Paolo, 2009. "Reconsidering the role of money for output, prices and interest rates," Journal of Monetary Economics, Elsevier, vol. 56(3), pages 419-430, April.
    See citations under working paper version above.
  8. Giordani, Paolo & Kohn, Robert, 2008. "Efficient Bayesian Inference for Multiple Change-Point and Mixture Innovation Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 66-77, January.
    See citations under working paper version above.
  9. Giordani, Paolo & Kohn, Robert & van Dijk, Dick, 2007. "A unified approach to nonlinearity, structural change, and outliers," Journal of Econometrics, Elsevier, vol. 137(1), pages 112-133, March.

    Cited by:

    1. Pierre Perron & Tatsuma Wada, 2015. "Measuring Business Cycles with Structural Breaks and Outliers: Applications to International Data," Boston University - Department of Economics - Working Papers Series wp2015-016, Boston University - Department of Economics.
    2. Geweke, John & Jiang, Yu, 2011. "Inference and prediction in a multiple-structural-break model," Journal of Econometrics, Elsevier, vol. 163(2), pages 172-185, August.
    3. Erdenebat Bataa & Denise R. Osborn & Marianne Sensier & Dick van Dijk, 2008. "Identifying Changes in Mean, Seasonality, Persistence and Volatility for G7 and Euro Area Inflation," Centre for Growth and Business Cycle Research Discussion Paper Series 109, Economics, The University of Manchester.
    4. Markus Jochmann, 2015. "Modeling U.S. Inflation Dynamics: A Bayesian Nonparametric Approach," Econometric Reviews, Taylor & Francis Journals, vol. 34(5), pages 537-558, May.
    5. Jan J. J. Groen & Richard Paap & Francesco Ravazzolo, 2013. "Real-Time Inflation Forecasting in a Changing World," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 29-44, January.
    6. Maheu, John M & Song, Yong, 2017. "An Efficient Bayesian Approach to Multiple Structural Change in Multivariate Time Series," MPRA Paper 79211, University Library of Munich, Germany.
    7. GwanSeon Kim & Tyler Mark, 2017. "Impacts of corn price and imported beef price on domestic beef price in South Korea," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 5(1), pages 1-13, December.
    8. Lennart Hoogerheide & Richard Kleijn & Francesco Ravazzolo & Herman K. Van Dijk & Marno Verbeek, 2010. "Forecast accuracy and economic gains from Bayesian model averaging using time-varying weights," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 251-269.
    9. Siok Kun Sek, 2023. "A new look at asymmetric effect of oil price changes on inflation: Evidence from Malaysia," Energy & Environment, , vol. 34(5), pages 1524-1547, August.
    10. 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.
    11. Fiorentini, G. & Planas, C. & Rossi, A., 2012. "The marginal likelihood of dynamic mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 56(9), pages 2650-2662.
    12. Joshua C.C. Chan & Garry Koop & Roberto Leon Gonzales & Rodney W. Strachan, 2010. "Time Varying Dimension Models," ANU Working Papers in Economics and Econometrics 2010-523, Australian National University, College of Business and Economics, School of Economics.
    13. Rimstad, Kjartan & Omre, Henning, 2013. "Approximate posterior distributions for convolutional two-level hidden Markov models," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 187-200.
    14. Bernardi, Mauro & Della Corte, Giuseppe & Proietti, Tommaso, 2008. "Extracting the Cyclical Component in Hours Worked: a Bayesian Approach," MPRA Paper 8967, University Library of Munich, Germany.
    15. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    16. Catherine Doz & Laurent Ferrara & Pierre-Alain Pionnier, 2020. "Business cycle dynamics after the Great Recession: An Extended Markov-Switching Dynamic Factor Model," Working Papers halshs-02443364, HAL.
    17. Grossi, Luigi & Laurini, Fabrizio, 2009. "A robust forward weighted Lagrange multiplier test for conditional heteroscedasticity," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2251-2263, April.
    18. Altansukh, Gantungalag & Becker, Ralf & Bratsiotis, George J. & Osborn, Denise R., 2017. "What is the Globalisation of Inflation?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 74, pages 1-27.
    19. Giordani, Paolo & Kohn, Robert, 2008. "Efficient Bayesian Inference for Multiple Change-Point and Mixture Innovation Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 66-77, January.
    20. Huachen Li & Tiezheng Song, 2024. "Regime dependent dynamics of parallel and official exchange markets in China: evidence from cryptocurrency," Applied Economics, Taylor & Francis Journals, vol. 56(41), pages 4952-4973, September.
    21. Perron, Pierre & Wada, Tatsuma, 2009. "Let's take a break: Trends and cycles in US real GDP," Journal of Monetary Economics, Elsevier, vol. 56(6), pages 749-765, September.
    22. Shaun P Vahey & Elizabeth C Wakerly, 2013. "Moving towards probability forecasting," BIS Papers chapters, in: Bank for International Settlements (ed.), Globalisation and inflation dynamics in Asia and the Pacific, volume 70, pages 3-8, Bank for International Settlements.
    23. Cathy W. S. Chen & Richard H. Gerlach & Ann M. H. Lin, 2011. "Multi-regime nonlinear capital asset pricing models," Quantitative Finance, Taylor & Francis Journals, vol. 11(9), pages 1421-1438, April.
    24. Sjoerd van den Hauwe & Richard Paap & Dick J.C. van Dijk, 2011. "An Alternative Bayesian Approach to Structural Breaks in Time Series Models," Tinbergen Institute Discussion Papers 11-023/4, Tinbergen Institute.
    25. Tatsuma Wada & Pierre Perron, 2005. "An Alternative Trend-Cycle Decomposition using a State Space Model with Mixtures of Normals: Specifications and Applications to International Data," Boston University - Department of Economics - Working Papers Series WP2005-44, Boston University - Department of Economics.
    26. John M. Maheu & Yong Song, 2012. "A New Structural Break Model with Application to Canadian Inflation Forecasting," Working Paper series 27_12, Rimini Centre for Economic Analysis.
    27. Dr. James Mitchell, 2009. "Macro Modelling with Many Models," National Institute of Economic and Social Research (NIESR) Discussion Papers 337, National Institute of Economic and Social Research.
    28. Panayotis G. Michaelides & Efthymios G. Tsionas & Angelos T. Vouldis & Konstantinos N. Konstantakis & Panagiotis Patrinos, 2018. "A Semi-Parametric Non-linear Neural Network Filter: Theory and Empirical Evidence," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 637-675, March.
    29. Jaehee Kim & Chulwoo Jeong, 2016. "A Bayesian multiple structural change regression model with autocorrelated errors," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(9), pages 1690-1705, July.
    30. Didier Nibbering & Richard Paap & Michel van der Wel, 2016. "A Bayesian Infinite Hidden Markov Vector Autoregressive Model," Tinbergen Institute Discussion Papers 16-107/III, Tinbergen Institute, revised 13 Oct 2017.
    31. Massimo Guidolin & Francesco Ravazzolo & Andrea Donato Tortora, 2011. "Myths and Facts about the Alleged Over-Pricing of U.S. Real Estate. Evidence from Multi-Factor Asset Pricing Models of REIT Returns," Working Papers 416, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    32. Tatsuma Wada & Pierre Perron, 2006. "State Space Model with Mixtures of Normals: Specifications and Applications to International Data," Boston University - Department of Economics - Working Papers Series WP2006-029, Boston University - Department of Economics.
    33. Candelon, Bertrand & Metiu, Norbert & Straetmans, Stefan, 2013. "Disentangling economic recessions and depressions," Discussion Papers 43/2013, Deutsche Bundesbank.
    34. Grossi, Luigi & Nan, Fany, 2019. "Robust forecasting of electricity prices: Simulations, models and the impact of renewable sources," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 305-318.
    35. Abolghasemi, Mahdi & Hurley, Jason & Eshragh, Ali & Fahimnia, Behnam, 2020. "Demand forecasting in the presence of systematic events: Cases in capturing sales promotions," International Journal of Production Economics, Elsevier, vol. 230(C).
    36. 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.
    37. Jiawen Xu & Pierre Perron, 2023. "Forecasting in the presence of in-sample and out-of-sample breaks," Empirical Economics, Springer, vol. 64(6), pages 3001-3035, June.
    38. Daniele Bianchi & Massimo Guidolin & Francesco Ravazzolo, 2015. "Macroeconomic Factors Strike Back: A Bayesian Change-Point Model of Time-Varying Risk Exposures and Premia in the U.S. Cross-Section," Working Papers 550, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    39. Cathy W. S. Chen & Richard H. Gerlach & Ann M. H. Lin, 2010. "Falling and explosive, dormant, and rising markets via multiple‐regime financial time series models," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 26(1), pages 28-49, January.
    40. Maddalena Cavicchioli, 2016. "Weak VARMA representations of regime-switching state-space models," Statistical Papers, Springer, vol. 57(3), pages 705-720, September.
    41. Planas, C. & Roeger, W. & Rossi, A., 2013. "The information content of capacity utilization for detrending total factor productivity," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 577-590.
    42. Shirinbakhsh, Shamsollah & Moghaddas Bayat, Maryam, 2011. "An Evaluation of Asymmetric and Symmetric Effects of Oil Exports Shocks on Non-Tradable Sector of Iranian Economy," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 106-124, March.
    43. Ngene, Geoffrey M. & Mungai, Ann Nduati, 2022. "Stock returns, trading volume, and volatility: The case of African stock markets," International Review of Financial Analysis, Elsevier, vol. 82(C).
    44. Mahadeva, Lavan, 2007. "Monetary Policy and Data Uncertainty: A Case Study of Distribution, Hotels and Catering Growth," Discussion Papers 19, Monetary Policy Committee Unit, Bank of England.
    45. Gantungalag Altansukh & Ralf Becker & George Bratsiotis & Denise R. Osborn, 2018. "Structural Breaks in International Inflation Linkages for OECD Countries," Centre for Growth and Business Cycle Research Discussion Paper Series 240, Economics, The University of Manchester.
    46. Kim, Jaeho, 2015. "Bayesian Inference in a Non-linear/Non-Gaussian Switching State Space Model: Regime-dependent Leverage Effect in the U.S. Stock Market," MPRA Paper 67153, University Library of Munich, Germany.
    47. Luigi Grossi & Fany Nan, 2017. "Forecasting electricity prices through robust nonlinear models," Working Papers 06/2017, University of Verona, Department of Economics.
    48. Nalan Basturk & Cem Cakmakli & Pinar Ceyhan & Herman K. van Dijk, 2013. "Posterior-Predictive Evidence on US Inflation using Phillips Curve Models with Non-Filtered Time Series," Tinbergen Institute Discussion Papers 13-011/III, Tinbergen Institute.
    49. Cathy Chen & Richard Gerlach, 2013. "Semi-parametric quantile estimation for double threshold autoregressive models with heteroskedasticity," Computational Statistics, Springer, vol. 28(3), pages 1103-1131, June.
    50. Gary Koop & Simon Potter, 2010. "A flexible approach to parametric inference in nonlinear and time varying time series models," Post-Print hal-00732535, HAL.
    51. Davide Delle Monache & Stefano Grassi & Paolo Santucci de Magistris, 2017. "Does the ARFIMA really shift?," CREATES Research Papers 2017-16, Department of Economics and Business Economics, Aarhus University.
    52. Jiawen Xu & Pierre Perron, 2017. "Forecasting in the presence of in and out of sample breaks," Boston University - Department of Economics - Working Papers Series WP2018-014, Boston University - Department of Economics, revised Nov 2018.
    53. Lin, Edward M.H. & Chen, Cathy W.S. & Gerlach, Richard, 2012. "Forecasting volatility with asymmetric smooth transition dynamic range models," International Journal of Forecasting, Elsevier, vol. 28(2), pages 384-399.
    54. Bernardi Mauro & Della Corte Giuseppe & Proietti Tommaso, 2011. "Extracting the Cyclical Component in Hours Worked," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(3), pages 1-28, May.
    55. Luigi Grossi & Fany Nan, 2018. "The influence of renewables on electricity price forecasting: a robust approach," Working Papers 2018/10, Institut d'Economia de Barcelona (IEB).
    56. Johnson, Lorne D. & Sakoulis, Georgios, 2008. "Maximizing equity market sector predictability in a Bayesian time-varying parameter model," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3083-3106, February.
    57. Wali, Muammer & Chan, Felix & Manzur, Meher, 2017. "Nonlinear dependence in exchange rate returns: How do emerging Asian currencies compare with major currencies?," Journal of Asian Economics, Elsevier, vol. 50(C), pages 62-72.
    58. Pitt, Michael K. & Silva, Ralph dos Santos & Giordani, Paolo & Kohn, Robert, 2012. "On some properties of Markov chain Monte Carlo simulation methods based on the particle filter," Journal of Econometrics, Elsevier, vol. 171(2), pages 134-151.

  10. Giordani, Paolo & Soderlind, Paul, 2006. "Is there evidence of pessimism and doubt in subjective distributions? Implications for the equity premium puzzle," Journal of Economic Dynamics and Control, Elsevier, vol. 30(6), pages 1027-1043, June.

    Cited by:

    1. Fabrice Collard & Sujoy Mukerji & Kevin Sheppard & Jean-Marc Tallon, 2018. "Ambiguity and the historical equity premium," Post-Print halshs-01886571, HAL.
    2. Söderlind, Paul, 2005. "C-CAPM Without Ex Post Data," CEPR Discussion Papers 5407, C.E.P.R. Discussion Papers.
    3. Paul Söderlind, 2006. "C-CAPM Refinements and the Cross-Section of Returns," University of St. Gallen Department of Economics working paper series 2006 2006-07, Department of Economics, University of St. Gallen.
    4. Boero, Gianna & Smith, Jeremy & Wallis, Kenneth F., 2006. "Uncertainty and disagreement in economic prediction: the Bank of England Survey of External Forecasters," Economic Research Papers 269751, University of Warwick - Department of Economics.
    5. Xue-Zhong He & Lei Shi & Min Zheng, 2012. "Asset Pricing Under Keeping Up With the Joneses and Heterogeneous Beliefs," Research Paper Series 302, Quantitative Finance Research Centre, University of Technology, Sydney.
    6. Klaus Adam & Dmitry Matveev & Stefan Nagel, 2019. "Do Survey Expectations of Stock Returns Reflect Risk-Adjustments?," 2019 Meeting Papers 641, Society for Economic Dynamics.
    7. Clements, Michael P., 2012. "Subjective and Ex Post Forecast Uncertainty: US Inflation and Output Growth," Economic Research Papers 270629, University of Warwick - Department of Economics.
    8. Fernandes, Cecilia Melo, 2021. "ECB communication as a stabilization and coordination device: evidence from ex-ante inflation uncertainty," Working Paper Series 2582, European Central Bank.
    9. Isaac Kleshchelski & Nicolas Vincent, 2009. "Robust Equilibrium Yield Curves," Cahiers de recherche 0907, CIRPEE.
    10. Geoff Kenny & Thomas Kostka & Federico Masera, 2015. "Density characteristics and density forecast performance: a panel analysis," Empirical Economics, Springer, vol. 48(3), pages 1203-1231, May.
    11. Lei Shi, 2010. "Portfolio Analysis and Equilibrium Asset Pricing with Heterogeneous Beliefs," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2010, January-A.
    12. Emilio Barucci & Marco Casna, 2014. "On the Market Selection Hypothesis in a Mean Reverting Environment," Computational Economics, Springer;Society for Computational Economics, vol. 44(1), pages 101-126, June.
    13. Pfajfar, Damjan & Žakelj, Blaž, 2016. "Uncertainty in forecasting inflation and monetary policy design: Evidence from the laboratory," International Journal of Forecasting, Elsevier, vol. 32(3), pages 849-864.
    14. Casey, Eddie, 2021. "Are professional forecasters overconfident?," International Journal of Forecasting, Elsevier, vol. 37(2), pages 716-732.
    15. Elyes Jouini & Clotilde Napp, 2015. "Gurus and belief manipulation," Post-Print halshs-01250251, HAL.
    16. Minwook Kang & Lei Sandy Ye, 2021. "Can Optimism be a Remedy for Present Bias?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(1), pages 201-231, February.
    17. Alfranseder, Emanuel & zhang, Xiang, 2015. "The Effect of Pessimism and Doubt on the Equity Premium," Knut Wicksell Working Paper Series 2015/5, Lund University, Knut Wicksell Centre for Financial Studies.
    18. Alexander Ludwig & Alexander Zimper, 2013. "Biased Bayesian learning with an application to the risk-free rate puzzle," Working Papers 201366, University of Pretoria, Department of Economics.
    19. Alexander Glas & Matthias Hartmann, 2020. "Uncertainty measures from partially rounded probabilistic forecast surveys," Working Papers 427, University of Milano-Bicocca, Department of Economics, revised Jan 2020.
    20. Michael Clements, 2016. "Are Macroeconomic Density Forecasts Informative?," ICMA Centre Discussion Papers in Finance icma-dp2016-02, Henley Business School, University of Reading.
    21. Wolfgang Breuer & Michael Riesener & Astrid Juliane Salzmann, 2014. "Risk aversion vs. individualism: what drives risk taking in household finance?," The European Journal of Finance, Taylor & Francis Journals, vol. 20(5), pages 446-462, May.
    22. Selima Mansour & Elyès Jouini & Clotilde Napp, 2006. "Is There a “Pessimisticâ€\x9D Bias in Individual Beliefs? Evidence from a Simple Survey," Theory and Decision, Springer, vol. 61(4), pages 345-362, December.
    23. Elyès Jouini & Clotilde Napp, 2008. "On Abel's Concept of Doubt and Pessimism," Post-Print halshs-00176611, HAL.
    24. Xue-Zhong He & Lei Shi, 2010. "Differences in Opinion and Risk Premium," Research Paper Series 271, Quantitative Finance Research Centre, University of Technology, Sydney.
    25. Geoff Kenny & Thomas Kostka & Federico Masera, 2015. "Can Macroeconomists Forecast Risk? Event-Based Evidence from the Euro-Area SPF," International Journal of Central Banking, International Journal of Central Banking, vol. 11(4), pages 1-46, December.
    26. Elyès Jouini & Selima Ben Mansour & Clotilde Napp & Jean-Michel Marin & Christian P. Robert, 2008. "Are Risk Averse Agents More Optimistic? A Bayesian Estimation Approach," Post-Print halshs-00176629, HAL.
    27. Glas, Alexander, 2020. "Five dimensions of the uncertainty–disagreement linkage," International Journal of Forecasting, Elsevier, vol. 36(2), pages 607-627.
    28. Kim, Sei-Wan & Krausz, Joshua & Nam, Kiseok, 2013. "Revisiting asset pricing under habit formation in an overlapping-generations economy," Journal of Banking & Finance, Elsevier, vol. 37(1), pages 132-138.
    29. Goudarzi, Fatemeh (Sahar) & Olaru, Doina & Bergey, Paul, 2023. "Beyond risk attitude: Unpacking behavioral drivers of supply chain contracts," International Journal of Production Economics, Elsevier, vol. 255(C).
    30. Víctor Alberto Pena & Alina Gómez-Mejía, 2019. "Effect of the anchoring and adjustment heuristic and optimism bias in stock market forecasts," Revista Finanzas y Politica Economica, Universidad Católica de Colombia, vol. 11(2), pages 389-409, November.
    31. P. Schanbacher, 2014. "Measuring and adjusting for overconfidence," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 37(2), pages 423-452, October.

  11. Paolo Giordani, 2006. "A cautionary note on outlier robust estimation of threshold models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(1), pages 37-47.

    Cited by:

    1. Grossi, Luigi & Nan, Fany, 2019. "Robust forecasting of electricity prices: Simulations, models and the impact of renewable sources," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 305-318.
    2. Luigi Grossi & Fany Nan, 2017. "Forecasting electricity prices through robust nonlinear models," Working Papers 06/2017, University of Verona, Department of Economics.
    3. Luigi Grossi & Fany Nan, 2018. "The influence of renewables on electricity price forecasting: a robust approach," Working Papers 2018/10, Institut d'Economia de Barcelona (IEB).
    4. Zhang, Li-Xin & Chan, Wai-Sum & Cheung, Siu-Hung & Hung, King-Chi, 2009. "A note on the consistency of a robust estimator for threshold autoregressive processes," Statistics & Probability Letters, Elsevier, vol. 79(6), pages 807-813, March.

  12. Giordani, Paolo & Soderlind, Paul, 2004. "Solution of macromodels with Hansen-Sargent robust policies: some extensions," Journal of Economic Dynamics and Control, Elsevier, vol. 28(12), pages 2367-2397, December.
    See citations under working paper version above.
  13. Giordani, Paolo, 2004. "An alternative explanation of the price puzzle," Journal of Monetary Economics, Elsevier, vol. 51(6), pages 1271-1296, September.
    See citations under working paper version above.
  14. Paolo Giordani, 2004. "Evaluating New‐Keynesian Models of a Small Open Economy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(s1), pages 713-733, September.

    Cited by:

    1. Melecky, Ales & Melecky, Martin, 2008. "From Inflation to Exchange Rate Targeting: Estimating the Stabilization Effects," MPRA Paper 10844, University Library of Munich, Germany.
    2. Barišić, Patrik & Kovač, Tibor & Arčabić, Vladimir, 2023. "More than just supply and demand: Macroeconomic shock decomposition in Croatia during and after the transition period," Structural Change and Economic Dynamics, Elsevier, vol. 67(C), pages 420-438.
    3. Martin Melecky & Evgenij Najdov, 2010. "Comparing constraints to economic stabilization in Macedonia and Slovakia: macroestimates with micronarratives," Applied Financial Economics, Taylor & Francis Journals, vol. 20(9), pages 681-699.
    4. Bas Aarle & Harry Garretsen & Cindy Moons, 2008. "Accession to the euro-area: a stylized analysis using a NK model," International Economics and Economic Policy, Springer, vol. 5(1), pages 5-24, July.
    5. Daniel Buncic & Martin Melecky, 2008. "An Estimated New Keynesian Policy Model for Australia," The Economic Record, The Economic Society of Australia, vol. 84(264), pages 1-16, March.
    6. Jovanovic, Branimir & Petreski, Marjan, 2012. "Monetary policy in a small open economy with fixed exchange rate: The case of Macedonia," Economic Systems, Elsevier, vol. 36(4), pages 594-608.
    7. Martin Melecky, 2008. "A Structural Investigation of Third‐Currency Shocks to Bilateral Exchange Rates," International Finance, Wiley Blackwell, vol. 11(1), pages 19-48, May.
    8. Jang, Tae-Seok & Okano, Eiji, 2013. "Productivity shocks and monetary policy in a two-country model," Dynare Working Papers 29, CEPREMAP.
    9. Tunc, Cengiz & Kılınç, Mustafa, 2016. "Exchange Rate Pass-Through in a Small Open Economy: A Structural VAR Approach," MPRA Paper 72770, University Library of Munich, Germany, revised 28 Jul 2016.
    10. Lindé, Jesper, 2003. "Monetary Policy Shocks and Business Cycle Fluctuations in a Small Open Economy: Sweden 1986-2002," Working Paper Series 153, Sveriges Riksbank (Central Bank of Sweden).
    11. Horvath Roman & Rusnak Marek, 2009. "How Important Are Foreign Shocks in a Small Open Economy? The Case of Slovakia," Global Economy Journal, De Gruyter, vol. 9(1), pages 1-17, March.
    12. Borek Vasícek, 2009. "Monetary policy rules and inflation process in open emerging economies: evidence for 12 new EU members," Working Papers wpdea0903, Department of Applied Economics at Universitat Autonoma of Barcelona.
    13. Mardi Dungey & Adrian Pagan, 2008. "Extending an SVAR Model of the Australian Economy," NCER Working Paper Series 21, National Centre for Econometric Research.
    14. Mustafa Kilinc & Cengiz Tunc, 2014. "Identification of Monetary Policy Shocks in Turkey: A Structural VAR Approach," Working Papers 1423, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    15. Melecky, Martin, 2012. "Macroeconomic dynamics in Macedonia and Slovakia: Structural estimation and comparison," Economic Modelling, Elsevier, vol. 29(4), pages 1377-1387.
    16. Moons, Cindy & Garretsen, Harry & van Aarle, Bas & Fornero, Jorge, 2007. "Monetary policy in the New-Keynesian model: An application to the Euro Area," Journal of Policy Modeling, Elsevier, vol. 29(6), pages 879-902.
    17. Bank for International Settlements, 2016. "Inflation mechanisms, expectations and monetary policy," BIS Papers, Bank for International Settlements, number 89, October –.
    18. Heidari, Hassan, 2010. "An Estimated Small Open Economy New-Keynesian Model of the Australian Economy," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 7-15, December.
    19. Bojaj, Martin M. & Muhadinovic, Milica & Bracanovic, Andrej & Mihailovic, Andrej & Radulovic, Mladen & Jolicic, Ivan & Milosevic, Igor & Milacic, Veselin, 2022. "Forecasting macroeconomic effects of stablecoin adoption: A Bayesian approach," Economic Modelling, Elsevier, vol. 109(C).
    20. Gordana Djurovic & Vasilije Djurovic & Martin M. Bojaj, 2020. "The macroeconomic effects of COVID-19 in Montenegro: a Bayesian VARX approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-16, December.
    21. Mustafa Kılınç & Cengiz Tunç & Mehmet Yörükoğlu, 2016. "Twin stability problem: joint issue of high current account deficit and high inflation," BIS Papers chapters, in: Bank for International Settlements (ed.), Inflation mechanisms, expectations and monetary policy, volume 89, pages 361-371, Bank for International Settlements.
    22. Juselius, Mikael, 2008. "Testing the New Keynesian Model on U.S. and Euro Area Data," Economics Discussion Papers 2008-23, Kiel Institute for the World Economy (IfW Kiel).
    23. Fousseni Chabi-Yo & Jun Yang, 2007. "A No-Arbitrage Analysis of Macroeconomic Determinants of Term Structures and the Exchange Rate," Staff Working Papers 07-21, Bank of Canada.
    24. Melecky, Ales & Melecky, Martin, 2010. "From inflation to exchange rate targeting: Estimating the stabilization effects for a small open economy," Economic Systems, Elsevier, vol. 34(4), pages 450-468, December.

  15. Giordani, Paolo & Soderlind, Paul, 2003. "Inflation forecast uncertainty," European Economic Review, Elsevier, vol. 47(6), pages 1037-1059, December.
    See citations under working paper version above.
  16. Giordani Paolo, 2003. "On Modeling the Effects of Inflation Shocks: Comments and Some Further Evidence," The B.E. Journal of Macroeconomics, De Gruyter, vol. 3(1), pages 1-15, January.

    Cited by:

    1. Hillinger, Claude & Süssmuth, Bernd, 2008. "The Quantity Theory of Money is Valid. The New Keynesians are Wrong!," Discussion Papers in Economics 6987, University of Munich, Department of Economics.
    2. Paolo Giordani, 2004. "Evaluating New‐Keynesian Models of a Small Open Economy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(s1), pages 713-733, September.
    3. Gaffeo, Edoardo & Canzian, Giulia, 2011. "The psychology of inflation, monetary policy and macroeconomic instability," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 40(5), pages 660-670.
    4. Barbara Annicchiarico & Alessandro Piergallini, 2006. "Inflation shocks and interest rate rules," Economics Bulletin, AccessEcon, vol. 5(19), pages 1-7.
    5. Mr. Shaun K. Roache & Alexander P. Attie, 2009. "Inflation Hedging for Long-Term Investors," IMF Working Papers 2009/090, International Monetary Fund.

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