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Monte Carlo Smoothing for Nonlinear Time Series

Citations

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Cited by:

  1. 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.
  2. Norris I. Bruce, 2008. "Pooling and Dynamic Forgetting Effects in Multitheme Advertising: Tracking the Advertising Sales Relationship with Particle Filters," Marketing Science, INFORMS, vol. 27(4), pages 659-673, 07-08.
  3. Charles S. Bos, 2008. "Model-based Estimation of High Frequency Jump Diffusions with Microstructure Noise and Stochastic Volatility," Tinbergen Institute Discussion Papers 08-011/4, Tinbergen Institute.
  4. Creal, Drew D. & Wu, Jing Cynthia, 2015. "Estimation of affine term structure models with spanned or unspanned stochastic volatility," Journal of Econometrics, Elsevier, vol. 185(1), pages 60-81.
  5. Chau, Thi Tuyet Trang & Ailliot, Pierre & Monbet, Valérie, 2021. "An algorithm for non-parametric estimation in state–space models," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).
  6. Jiawen Xu & Pierre Perron, 2015. "Forecasting in the presence of in and out of sample breaks," Boston University - Department of Economics - Working Papers Series wp2015-012, Boston University - Department of Economics.
  7. Andrea Beccarini, 2016. "Bias correction through filtering omitted variables and instruments," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(4), pages 754-766, March.
  8. Ioannis Bournakis & Mike Tsionas, 2024. "A Non‐parametric Estimation of Productivity with Idiosyncratic and Aggregate Shocks: The Role of Research and Development (R&D) and Corporate Tax," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(3), pages 641-671, June.
  9. Lange, Rutger-Jan, 2024. "Bellman filtering and smoothing for state–space models," Journal of Econometrics, Elsevier, vol. 238(2).
  10. Dunham, Kylee & Grand, James B., 2016. "Effects of model complexity and priors on estimation using sequential importance sampling/resampling for species conservation," Ecological Modelling, Elsevier, vol. 340(C), pages 28-36.
  11. Siddhartha Chib & Yasuhiro Omori & Manabu Asai, 2007. "Multivariate stochastic volatility (Revised in May 2007, Handbook of Financial Time Series (Published in "Handbook of Financial Time Series" (eds T.G. Andersen, R.A. Davis, Jens-Peter Kreiss and T. Mikosch), 365-400. Springer-Verlag: New Yo," CARF F-Series CARF-F-094, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
  12. Jiawen Xu & Pierre Perron, 2015. "Forecasting in the presence of in and out of sample breaks," Boston University - Department of Economics - Working Papers Series wp2015-012, Boston University - Department of Economics.
  13. Born, Benjamin & Pfeifer, Johannes, 2014. "Policy risk and the business cycle," Journal of Monetary Economics, Elsevier, vol. 68(C), pages 68-85.
  14. Martin Møller Andreasen, 2008. "Non-linear DSGE Models, The Central Difference Kalman Filter, and The Mean Shifted Particle Filter," CREATES Research Papers 2008-33, Department of Economics and Business Economics, Aarhus University.
  15. Carlos Carvalho & Stefano Eusepi & Emanuel Moench & Bruce Preston, 2023. "Anchored Inflation Expectations," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(1), pages 1-47, January.
  16. 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).
  17. Matteo Cacciatore & Federico Ravenna, 2021. "Uncertainty, Wages and the Business Cycle," The Economic Journal, Royal Economic Society, vol. 131(639), pages 2797-2823.
  18. Doh, Taeyoung, 2011. "Yield curve in an estimated nonlinear macro model," Journal of Economic Dynamics and Control, Elsevier, vol. 35(8), pages 1229-1244, August.
  19. Delis, Manthos D. & Kazakis, Pantelis & Zopounidis, Constantin, 2023. "Management and takeover decisions," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1256-1268.
  20. Marco J. Lombardi & Simon J. Godsill, 2004. "On-line Bayesian estimation of AR signals in symmetric alpha-stable noise," Econometrics Working Papers Archive wp2004_05, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
  21. Tsionas, Mike G. & Mallick, Sushanta K., 2019. "A Bayesian semiparametric approach to stochastic frontiers and productivity," European Journal of Operational Research, Elsevier, vol. 274(1), pages 391-402.
  22. Laurent-Emmanuel Calvet & Veronika Czellar, 2011. "State-Observation Sampling and the Econometrics of Learning Models," Working Papers hal-00625500, HAL.
  23. Branislav Rudić & Markus Pichler-Scheder & Dmitry Efrosinin, 2025. "Recursive Bayesian Decoding in State Observation Models: Theory and Application in Quantum-Based Inference," Mathematics, MDPI, vol. 13(12), pages 1-24, June.
  24. Creal, Drew D. & Tsay, Ruey S., 2015. "High dimensional dynamic stochastic copula models," Journal of Econometrics, Elsevier, vol. 189(2), pages 335-345.
  25. Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez, 2008. "How Structural Are Structural Parameters?," NBER Chapters, in: NBER Macroeconomics Annual 2007, Volume 22, pages 83-137, National Bureau of Economic Research, Inc.
  26. Scharth, Marcel & Kohn, Robert, 2016. "Particle efficient importance sampling," Journal of Econometrics, Elsevier, vol. 190(1), pages 133-147.
  27. 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.
  28. 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.
  29. Xudan Chen & Guoxun Ji & Xinli Sun & Zhen Li, 2019. "Inverse Gaussian–based model with measurement errors for degradation analysis," Journal of Risk and Reliability, , vol. 233(6), pages 1086-1098, December.
  30. Tsionas, Mike G., 2022. "Convex non-parametric least squares, causal structures and productivity," European Journal of Operational Research, Elsevier, vol. 303(1), pages 370-387.
  31. 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.
  32. Matthieu Lemoine & Christophe Mougin, 2010. "The Growth-Volatility Relationship: New Evidence Based on Stochastic Volatility in Mean Models," Working papers 285, Banque de France.
  33. Nicolas Chopin, 2007. "Dynamic Detection of Change Points in Long Time Series," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 59(2), pages 349-366, June.
  34. Manthos D. Delis & Pantelis Kazakis & Constantin Zopounidis, 2021. "Management Practices and Takeover Decisions," Working Papers 2021_10, Business School - Economics, University of Glasgow.
  35. 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.
  36. 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.
  37. 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.
  38. J. O. Ramsay & G. Hooker & D. Campbell & J. Cao, 2007. "Parameter estimation for differential equations: a generalized smoothing approach," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(5), pages 741-796, November.
  39. Linlin Niu, 2013. "An Affine Term Structure Model with Auxiliary Stochastic Volatility-Covolatility," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
  40. Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez, 2007. "Estimating Macroeconomic Models: A Likelihood Approach," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 74(4), pages 1059-1087.
  41. Mike G. Tsionas & Subal C. Kumbhakar, 2023. "Productivity and Performance: A GMM approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(2), pages 331-344, April.
  42. Di Zhang & Qiang Niu & Youzhou Zhou, 2022. "Modeling Randomly Walking Volatility with Chained Gamma Distributions," Papers 2207.01151, arXiv.org, revised Oct 2022.
  43. 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.
  44. Pratiti Chatterjee & David Gunawan & Robert Kohn, 2020. "The Interaction Between Credit Constraints and Uncertainty Shocks," Papers 2004.14719, arXiv.org.
  45. Anzuini, Alessio & Rossi, Luca & Tommasino, Pietro, 2020. "Fiscal policy uncertainty and the business cycle: Time series evidence from Italy," Journal of Macroeconomics, Elsevier, vol. 65(C).
  46. Jeongeun Kim & David S. Stoffer, 2008. "Fitting Stochastic Volatility Models in the Presence of Irregular Sampling via Particle Methods and the EM Algorithm," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(5), pages 811-833, September.
  47. Di Zhang & Youzhou Zhou, 2025. "Fast Computation of Randomly Walking Volatility with Chained Gamma Distributions," Computational Economics, Springer;Society for Computational Economics, vol. 66(3), pages 2199-2223, September.
  48. Ballarin, Giovanni & Dellaportas, Petros & Grigoryeva, Lyudmila & Hirt, Marcel & van Huellen, Sophie & Ortega, Juan-Pablo, 2024. "Reservoir computing for macroeconomic forecasting with mixed-frequency data," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1206-1237.
  49. Tomiyuki Kitamura, 2010. "Measuring Monetary Policy Under Zero Interest Rates With a Dynamic Stochastic General Equilibrium Model: An Application of a Particle Filter," Bank of Japan Working Paper Series 10-E-10, Bank of Japan.
  50. Smith, J.Q. & Santos, Antonio A.F., 2006. "Second-Order Filter Distribution Approximations for Financial Time Series With Extreme Outliers," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 329-337, July.
  51. Ekaterini Skamnia & Eleni S. Bekri & Polychronis Economou, 2025. "Unraveling Meteorological Dynamics: A Two-Level Clustering Algorithm for Time Series Pattern Recognition with Missing Data Handling," Stats, MDPI, vol. 8(2), pages 1-39, May.
  52. Kien C. Tran & Panayotis G. Michaelides, 2025. "A class of generalized autoregressive score panel stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 64(3), pages 235-253, December.
  53. Angel L. Cedeño & Rodrigo A. González & Boris I. Godoy & Rodrigo Carvajal & Juan C. Agüero, 2023. "On Filtering and Smoothing Algorithms for Linear State-Space Models Having Quantized Output Data," Mathematics, MDPI, vol. 11(6), pages 1-25, March.
  54. Tsionas, Mike G., 2020. "On a model of environmental performance and technology gaps," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1141-1152.
  55. Matthew Klepacz, 2018. "Price Setting and Volatility: Evidence from Oil Price Volatility Shocks," 2018 Meeting Papers 145, Society for Economic Dynamics.
  56. Michael Patrick Curran & Adnan Velic, 2017. "Interest Rate Volatility And Macroeconomic Dynamics: A Cross-Country Analysis," Villanova School of Business Department of Economics and Statistics Working Paper Series 35, Villanova School of Business Department of Economics and Statistics.
  57. Emmanuel C. Mamatzakis & Steven Ongena & Mike G. Tsionas, 2023. "The response of household debt to COVID-19 using a neural networks VAR in OECD," Empirical Economics, Springer, vol. 65(1), pages 65-91, July.
  58. Jiawen Xu & Pierre Perron, 2024. "Forecasting in the presence of in-sample and out-of-sample breaks," Advanced Studies in Theoretical and Applied Econometrics, in: Subal C. Kumbhakar & Robin C. Sickles & Hung-Jen Wang (ed.), Advances in Applied Econometrics, pages 545-579, Springer.
  59. Smith, Michael Stanley & Maneesoonthorn, Worapree, 2018. "Inversion copulas from nonlinear state space models with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 34(3), pages 389-407.
  60. Rutger Jan Lange, 2020. "Bellman filtering for state-space models," Tinbergen Institute Discussion Papers 20-052/III, Tinbergen Institute, revised 19 May 2021.
  61. Giuliano De Rossi, 2010. "Maximum Likelihood Estimation of the Cox–Ingersoll–Ross Model Using Particle Filters," Computational Economics, Springer;Society for Computational Economics, vol. 36(1), pages 1-16, June.
  62. Christophe Andrieu & Arnaud Doucet & Roman Holenstein, 2010. "Particle Markov chain Monte Carlo methods," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(3), pages 269-342, June.
  63. Liu, Zongming & Shi, Wenhui, 2026. "Global oil supply risk and macro-financial downside risk: Can monetary policy mitigate the risk transmission?," Economic Modelling, Elsevier, vol. 154(C).
  64. Norris I. Bruce & Anand Krishnamoorthy & Ashutosh Prasad, 2022. "Advertising Cycling to Manage Exclusivity Loss in Fashion Styles," Operations Research, INFORMS, vol. 70(6), pages 3125-3142, November.
  65. Mäder, Nicolas, 2025. "Would an earlier inception of OMT by the ECB have prevented the 2012 Greek default?," International Review of Economics & Finance, Elsevier, vol. 103(C).
  66. repec:wyi:journl:002173 is not listed on IDEAS
  67. 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.
  68. Hammer, Hugo & Tjelmeland, Håkon, 2011. "Approximate forward-backward algorithm for a switching linear Gaussian model," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 154-167, January.
  69. Mike G. Tsionas & Nicholas Apergis, 2023. "Another look at contagion across United States and European financial markets: Evidence from the credit default swaps markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 1137-1155, January.
  70. Leippold, Markus & Yang, Hanlin, 2019. "Particle filtering, learning, and smoothing for mixed-frequency state-space models," Econometrics and Statistics, Elsevier, vol. 12(C), pages 25-41.
  71. Matthew T. Klepacz, 2021. "Price Setting and Volatility: Evidence from Oil Price Volatility Shocks," International Finance Discussion Papers 1316, Board of Governors of the Federal Reserve System (U.S.).
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