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Bayesian Inference Based Only On Simulated Likelihood: Particle Filter Analysis Of Dynamic Economic Models

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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. Guofang Huang & Hong Luo & Jing Xia, 2019. "Invest in Information or Wing It? A Model of Dynamic Pricing with Seller Learning," Management Science, INFORMS, vol. 65(12), pages 5556-5583, December.
  3. Martin T. Bohl & Nicole Branger & Mark Trede, 2022. "Measurement errors in index trader positions data: Is the price pressure hypothesis still invalid?," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 44(3), pages 1534-1553, September.
  4. Phoebe Koundouri & Nikolaos Englezos & Xanthi Kartala & Mike Tsionas, 2019. "A Decision-Analytic Framework to explore the water-energy-food nexus in complex and transboundary water resources systems, with Climate Change Uncertainty," DEOS Working Papers 1907, Athens University of Economics and Business.
  5. Bauwens, Luc & Dufays, Arnaud & Rombouts, Jeroen V.K., 2014. "Marginal likelihood for Markov-switching and change-point GARCH models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 508-522.
  6. Papp, Tamás K. & Reiter, Michael, 2020. "Estimating linearized heterogeneous agent models using panel data," Journal of Economic Dynamics and Control, Elsevier, vol. 115(C).
  7. 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.
  8. Joshua C.C. Chan & Rodney Strachan, 2014. "The Zero Lower Bound: Implications for Modelling the Interest Rate," Working Paper series 42_14, Rimini Centre for Economic Analysis.
  9. 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.
  10. Tsionas, Mike G. & Malikov, Emir & Kumbhakar, Subal C., 2020. "Endogenous dynamic efficiency in the intertemporal optimization models of firm behavior," European Journal of Operational Research, Elsevier, vol. 284(1), pages 313-324.
  11. Fernández-Villaverde, Jesús & Guerrón-Quintana, Pablo & Rubio-Ramírez, Juan F., 2015. "Estimating dynamic equilibrium models with stochastic volatility," Journal of Econometrics, Elsevier, vol. 185(1), pages 216-229.
  12. Bidder, R.M. & Smith, M.E., 2018. "Doubts and variability: A robust perspective on exotic consumption series," Journal of Economic Theory, Elsevier, vol. 175(C), pages 689-712.
  13. Creal, Drew D. & Tsay, Ruey S., 2015. "High dimensional dynamic stochastic copula models," Journal of Econometrics, Elsevier, vol. 189(2), pages 335-345.
  14. Andrew Binning & Junior Maih, 2015. "Sigma point filters for dynamic nonlinear regime switching models," Working Paper 2015/10, Norges Bank.
  15. 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.
  16. Giacomini, Raffaella & Ragusa, Giuseppe & Gallant, A. Ronald, 2013. "Generalized Method of Moments with Latent Variables," CEPR Discussion Papers 9692, C.E.P.R. Discussion Papers.
  17. Matthew Smith, 2012. "Estimating Nonlinear Economic Models Using Surrogate Transitions," 2012 Meeting Papers 494, Society for Economic Dynamics.
  18. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 527-724, Elsevier.
  19. Pablo Cuba‐Borda & Luca Guerrieri & Matteo Iacoviello & Molin Zhong, 2019. "Likelihood evaluation of models with occasionally binding constraints," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1073-1085, November.
  20. Chan, Joshua & Strachan, Rodney, 2012. "Estimation in Non-Linear Non-Gaussian State Space Models with Precision-Based Methods," MPRA Paper 39360, University Library of Munich, Germany.
  21. Elmar Mertens & James M. Nason, 2020. "Inflation and professional forecast dynamics: An evaluation of stickiness, persistence, and volatility," Quantitative Economics, Econometric Society, vol. 11(4), pages 1485-1520, November.
  22. Wolf, Elias, 2022. "Estimating growth at risk with skewed stochastic volatility models," Discussion Papers 2022/2, Free University Berlin, School of Business & Economics.
  23. Laura Liu & Mikkel Plagborg-M{o}ller, 2021. "Full-Information Estimation of Heterogeneous Agent Models Using Macro and Micro Data," Papers 2101.04771, arXiv.org, revised Jun 2022.
  24. Neil Shephard, 2013. "Martingale unobserved component models," Economics Series Working Papers 644, University of Oxford, Department of Economics.
  25. Yumiao Tian & Maorong Ge & Frank Neitzel, 2020. "Variance Reduction of Sequential Monte Carlo Approach for GNSS Phase Bias Estimation," Mathematics, MDPI, vol. 8(4), pages 1-15, April.
  26. A. Ronald Gallant & Han Hong & Ahmed Khwaja, 2012. "Bayesian Estimation of a Dynamic Game with Endogenous, Partially Observed, Serially Correlated State," Working Papers 12-01, Duke University, Department of Economics.
  27. Nonejad Nima, 2015. "Particle Gibbs with ancestor sampling for stochastic volatility models with: heavy tails, in mean effects, leverage, serial dependence and structural breaks," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(5), pages 561-584, December.
  28. Neil Shephard & Arnaud Doucet, 2012. "Robust inference on parameters via particle filters and sandwich covariance matrices," Economics Series Working Papers 606, University of Oxford, Department of Economics.
  29. Angelo Marsiglia Fasolo, 2012. "A Note on Particle Filters Applied to DSGE Models," Working Papers Series 281, Central Bank of Brazil, Research Department.
  30. Cameron Fen, 2022. "Fast Simulation-Based Bayesian Estimation of Heterogeneous and Representative Agent Models using Normalizing Flow Neural Networks," Papers 2203.06537, arXiv.org.
  31. Nonejad, Nima, 2014. "Particle Markov Chain Monte Carlo Techniques of Unobserved Component Time Series Models Using Ox," MPRA Paper 55662, University Library of Munich, Germany.
  32. 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).
  33. Man Chung Fung & Gareth W. Peters & Pavel V. Shevchenko, 2016. "A unified approach to mortality modelling using state-space framework: characterisation, identification, estimation and forecasting," Papers 1605.09484, arXiv.org.
  34. Roberto Leon-Gonzalez & Blessings Majoni, 2023. "Exact Likelihood for Inverse Gamma Stochastic Volatility Models," Working Paper series 23-11, Rimini Centre for Economic Analysis.
  35. Nima Nonejad, 2013. "Particle Markov Chain Monte Carlo Techniques of Unobserved Component Time Series Models Using Ox," CREATES Research Papers 2013-27, Department of Economics and Business Economics, Aarhus University.
  36. Delis, Manthos D. & Tsionas, Mike G., 2018. "Measuring management practices," International Journal of Production Economics, Elsevier, vol. 199(C), pages 65-77.
  37. Luisa Corrado & Stefano Grassi & Aldo Paolillo, 2021. "Modelling and Estimating Large Macroeconomic Shocks During the Pandemic," CREATES Research Papers 2021-08, Department of Economics and Business Economics, Aarhus University.
  38. 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.
  39. 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.
  40. Malik, Sheheryar & Pitt, Michael K., 2011. "Particle filters for continuous likelihood evaluation and maximisation," Journal of Econometrics, Elsevier, vol. 165(2), pages 190-209.
  41. Guay, François & Schwenkler, Gustavo, 2021. "Efficient estimation and filtering for multivariate jump–diffusions," Journal of Econometrics, Elsevier, vol. 223(1), pages 251-275.
  42. Tsionas, Mike G. & Michaelides, Panayotis G., 2017. "Neglected chaos in international stock markets: Bayesian analysis of the joint return–volatility dynamical system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 95-107.
  43. 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.
  44. Scharth, Marcel & Kohn, Robert, 2016. "Particle efficient importance sampling," Journal of Econometrics, Elsevier, vol. 190(1), pages 133-147.
  45. 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.
  46. Drew Creal, 2012. "A Survey of Sequential Monte Carlo Methods for Economics and Finance," Econometric Reviews, Taylor & Francis Journals, vol. 31(3), pages 245-296.
  47. 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.
  48. 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.
  49. 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.
  50. N. Englezos & X. Kartala & P. Koundouri & M. Tsionas & A. Alamanos, 2023. "A Novel HydroEconomic - Econometric Approach for Integrated Transboundary Water Management Under Uncertainty," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 84(4), pages 975-1030, April.
  51. 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.
  52. 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.
  53. Gallant, A. Ronald & Giacomini, Raffaella & Ragusa, Giuseppe, 2017. "Bayesian estimation of state space models using moment conditions," Journal of Econometrics, Elsevier, vol. 201(2), pages 198-211.
  54. Celik, Nurcin & Son, Young-Jun, 2011. "State estimation of a shop floor using improved resampling rules for particle filtering," International Journal of Production Economics, Elsevier, vol. 134(1), pages 224-237, November.
  55. Martin T. Bohl & Nicole Branger & Mark Trede, 2019. "Measurement Errors in Index Trader Positions Data: Is the Price Pressure Hypothesis Still Invalid?," CQE Working Papers 8019, Center for Quantitative Economics (CQE), University of Muenster.
  56. 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.
  57. Andreasen, Martin & Meldrum, Andrew, 2013. "Likelihood inference in non-linear term structure models: the importance of the lower bound," Bank of England working papers 481, Bank of England.
  58. Laura Liu & Mikkel Plagborg‐Møller, 2023. "Full‐information estimation of heterogeneous agent models using macro and micro data," Quantitative Economics, Econometric Society, vol. 14(1), pages 1-35, January.
  59. Yang, Yuan & Wang, Lu, 2015. "An Improved Auxiliary Particle Filter for Nonlinear Dynamic Equilibrium Models," Dynare Working Papers 47, CEPREMAP.
  60. Laura Liu & Mikkel Plagborg-M{o}ller, 2021. "Full-Information Estimation of Heterogeneous Agent Models Using Macro and Micro Data," Papers 2101.04771, arXiv.org, revised Jun 2022.
  61. A. Ronald Gallant & Han Hong & Ahmed Khwaja, 2018. "The Dynamic Spillovers of Entry: An Application to the Generic Drug Industry," Management Science, INFORMS, vol. 64(3), pages 1189-1211, March.
  62. Martin M. Andreasen, 2010. "Non-linear DSGE Models and The Optimized Particle Filter," CREATES Research Papers 2010-05, Department of Economics and Business Economics, Aarhus University.
  63. Nonejad Nima, 2016. "Particle Markov Chain Monte Carlo Techniques of Unobserved Component Time Series Models Using Ox," Journal of Time Series Econometrics, De Gruyter, vol. 8(1), pages 55-90, January.
  64. Laurini, Márcio Poletti & Hotta, Luiz Koodi, 2013. "Indirect Inference in fractional short-term interest rate diffusions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 109-126.
  65. Luisa Corrado & Stefano Grassi & Aldo Paolillo, 2021. "Identifying Economic Shocks in a Rare Disaster Environment," CEIS Research Paper 517, Tor Vergata University, CEIS, revised 18 Jul 2024.
  66. Leland E. Farmer, 2021. "The discretization filter: A simple way to estimate nonlinear state space models," Quantitative Economics, Econometric Society, vol. 12(1), pages 41-76, January.
  67. 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.
  68. 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.
  69. Kjartan Kloster Osmundsen & Tore Selland Kleppe & Roman Liesenfeld & Atle Oglend, 2021. "Estimating the Competitive Storage Model with Stochastic Trends in Commodity Prices," Econometrics, MDPI, vol. 9(4), pages 1-24, November.
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