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Siddhartha Chib

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. Siddhartha Chib & Minchul Shin & Anna Simoni, 2024. "Testing for Endogeneity: A Moment-Based Bayesian Approach," Working Papers 24-19, Federal Reserve Bank of Philadelphia.

    Cited by:

    1. Nguyen, Lam, 2025. "Bayesian inference in proxy SVARs with incomplete identification: Re-evaluating the validity of monetary policy instruments," Journal of Monetary Economics, Elsevier, vol. 155(C).

  2. Siddhartha Chib & Kenichi Shimizu, 2023. "Scalable Estimation of Multinomial Response Models with Random Consideration Sets," Papers 2308.12470, arXiv.org, revised Sep 2025.

    Cited by:

    1. Zhentong Lu & Kenichi Shimizu, 2025. "Estimating Discrete Choice Demand Models with Sparse Market-Product Shocks," Papers 2501.02381, arXiv.org, revised Jul 2025.

  3. Siddhartha Chib & Edward Greenberg & Anna Simoni, 2022. "Nonparametric Bayes Analysis Of The Sharp And Fuzzy Regression Discontinuity Designs," Post-Print hal-04976308, HAL.

    Cited by:

    1. Justin L. Tobias, 2025. "Adaptive Bayesian Nonparametric Regression via Stationary Smoothness Priors," Mathematics, MDPI, vol. 13(7), pages 1-19, March.
    2. Antonio R. Linero, 2023. "Prior and posterior checking of implicit causal assumptions," Biometrics, The International Biometric Society, vol. 79(4), pages 3153-3164, December.

  4. Siddhartha Chib & Minchul Shin & Fei Tan, 2021. "DSGE-SVt: An Econometric Toolkit for High-Dimensional DSGE Models with SV and t Errors," Working Papers 21-02, Federal Reserve Bank of Philadelphia.

    Cited by:

    1. Li, Bing & Pei, Pei & Tan, Fei, 2021. "Financial distress and fiscal inflation," Journal of Macroeconomics, Elsevier, vol. 70(C).
    2. Chang, Yoosoon & Maih, Junior & Tan, Fei, 2021. "Origins of monetary policy shifts: A New approach to regime switching in DSGE models," Journal of Economic Dynamics and Control, Elsevier, vol. 133(C).
    3. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2021. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," Working Papers 21-02R, Federal Reserve Bank of Cleveland, revised 09 Aug 2021.
    4. Siddhartha Chib & Fei Tan, 2025. "Learning the Macroeconomic Language," Papers 2512.21031, arXiv.org, revised Dec 2025.

  5. Siddhartha Chib & Minchul Shin & Anna Simoni, 2021. "Bayesian Estimation and Comparison of Conditional Moment Models," Papers 2110.13531, arXiv.org.

    Cited by:

    1. Chung, Ray S.W. & So, Mike K.P. & Chu, Amanda M.Y. & Chan, Thomas W.C., 2020. "Regularization of Bayesian quasi-likelihoods constructed from complex estimating functions," Computational Statistics & Data Analysis, Elsevier, vol. 150(C).
    2. Christis Katsouris, 2023. "High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods," Papers 2308.16192, arXiv.org.
    3. 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.
    4. Zhichao Liu & Catherine Forbes & Heather Anderson, 2017. "Robust Bayesian exponentially tilted empirical likelihood method," Monash Econometrics and Business Statistics Working Papers 21/17, Monash University, Department of Econometrics and Business Statistics.

  6. Siddhartha Chib & Minchul Shin & Anna Simoni, 2018. "Bayesian Estimation and Comparison of Moment Condition Models," Post-Print hal-03089882, HAL.

    Cited by:

    1. Siddhartha Chib & Minchul Shin & Anna Simoni, 2021. "Bayesian Estimation and Comparison of Conditional Moment Models," Papers 2110.13531, arXiv.org.
    2. Gyuhyeong Goh & Jisang Yu, 2022. "Causal inference with some invalid instrumental variables: A quasi‐Bayesian approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(6), pages 1432-1451, December.
    3. Gregor Steiner & Jeremie Houssineau & Mark F. J. Steel, 2025. "Possibilistic Instrumental Variable Regression," Papers 2511.16029, arXiv.org, revised Jan 2026.
    4. Victor Chernozhukov & Christian B. Hansen & Lingwei Kong & Weining Wang, 2025. "Plausible GMM: A Quasi-Bayesian Approach," Bristol Economics Discussion Papers 25/817, School of Economics, University of Bristol, UK.
    5. Chung, Ray S.W. & So, Mike K.P. & Chu, Amanda M.Y. & Chan, Thomas W.C., 2020. "Regularization of Bayesian quasi-likelihoods constructed from complex estimating functions," Computational Statistics & Data Analysis, Elsevier, vol. 150(C).
    6. Sweata Sen & Damitri Kundu & Kiranmoy Das, 2023. "Variable selection for categorical response: a comparative study," Computational Statistics, Springer, vol. 38(2), pages 809-826, June.
    7. Max Breitenlechner & Georgios Georgiadis & Ben Schumann, 2021. "What goes around comes around: How large are spillbacks from US monetary policy?," GRU Working Paper Series GRU_2021_003, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    8. Bedoui, Adel & Lazar, Nicole A., 2020. "Bayesian empirical likelihood for ridge and lasso regressions," Computational Statistics & Data Analysis, Elsevier, vol. 145(C).
    9. Luo, Yu & Graham, Daniel J. & McCoy, Emma J., 2023. "Semiparametric Bayesian doubly robust causal estimation," LSE Research Online Documents on Economics 117944, London School of Economics and Political Science, LSE Library.
    10. Gallant, A. Ronald & Hong, Han & Leung, Michael P. & Li, Jessie, 2022. "Constrained estimation using penalization and MCMC," Journal of Econometrics, Elsevier, vol. 228(1), pages 85-106.
    11. Farzana Jahan & Daniel W Kennedy & Earl W Duncan & Kerrie L Mengersen, 2022. "Evaluation of spatial Bayesian Empirical Likelihood models in analysis of small area data," PLOS ONE, Public Library of Science, vol. 17(5), pages 1-27, May.
    12. Petrova, Katerina, 2022. "Asymptotically valid Bayesian inference in the presence of distributional misspecification in VAR models," Journal of Econometrics, Elsevier, vol. 230(1), pages 154-182.
    13. 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.
    14. Rong Tang & Yun Yang, 2022. "Bayesian inference for risk minimization via exponentially tilted empirical likelihood," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1257-1286, September.
    15. Qiao, Zhuo & Wang, Yan & Lam, Keith S.K., 2022. "New evidence on Bayesian tests of global factor pricing models," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 160-172.
    16. Christopher D. Walker, 2024. "Semiparametric Bayesian Inference for a Conditional Moment Equality Model," Papers 2410.16017, arXiv.org, revised Mar 2026.
    17. Zhichao Liu & Catherine Forbes & Heather Anderson, 2017. "Robust Bayesian exponentially tilted empirical likelihood method," Monash Econometrics and Business Statistics Working Papers 21/17, Monash University, Department of Econometrics and Business Statistics.
    18. Arnab Kumar Maity & Sanjib Basu & Santu Ghosh, 2021. "Bayesian criterion‐based variable selection," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 835-857, August.
    19. Gael M. Martin & David T. Frazier & Christian P. Robert, 2021. "Approximating Bayes in the 21st Century," Monash Econometrics and Business Statistics Working Papers 24/21, Monash University, Department of Econometrics and Business Statistics.
    20. Kline, Brendan, 2024. "Classical p-values and the Bayesian posterior probability that the hypothesis is approximately true," Journal of Econometrics, Elsevier, vol. 240(1).

  7. Siddharta Chib & Minchul Shin & Anna Simoni, 2016. "Bayesian Empirical Likelihood Estimation and Comparison of Moment Condition Models," Working Papers 2016-21, Center for Research in Economics and Statistics.

    Cited by:

    1. Zhichao Liu & Catherine Forbes & Heather Anderson, 2017. "Robust Bayesian exponentially tilted empirical likelihood method," Monash Econometrics and Business Statistics Working Papers 21/17, Monash University, Department of Econometrics and Business Statistics.

  8. Chib, Siddhartha & Jacobi, Liana, 2011. "Returns to Compulsory Schooling in Britain: Evidence from a Bayesian Fuzzy Regression Discontinuity Analysis," IZA Discussion Papers 5564, IZA Network @ LISER.

    Cited by:

    1. Hart, Robert A & Moro, Mirko & Roberts, J Elizabeth, 2012. "Date of birth, family background, and the 11 plus exam: short- and long-term consequences of the 1944 secondary education reforms in England and W ales," Stirling Economics Discussion Papers 2012-10, University of Stirling, Division of Economics.

  9. Siddhartha Chib & Yasuhiro Omori & Manabu Asai, 2007. "Multivariate stochastic volatility," CIRJE F-Series CIRJE-F-488, CIRJE, Faculty of Economics, University of Tokyo.

    Cited by:

    1. Manabu Asai & Michael McAleer, 2011. "Dynamic Conditional Correlations for Asymmetric Processes," Documentos de Trabajo del ICAE 2011-30, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    2. Gianni Amisano & Roberto Casarin, 2008. "Particle Filters for Markov-Switching Stochastic-Correlation Models," Working Papers 0814, University of Brescia, Department of Economics.
    3. Da Fonseca José & Grasselli Martino & Ielpo Florian, 2014. "Estimating the Wishart Affine Stochastic Correlation Model using the empirical characteristic function," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(3), pages 253-289, May.
    4. João Caldeira & Guilherme Moura & André A.P. Santos, 2012. "Portfolio optimization using a parsimonious multivariate GARCH model: application to the Brazilian stock market," Economics Bulletin, AccessEcon, vol. 32(3), pages 1848-1857.
    5. Casas, Isabel & Gao, Jiti, 2008. "Econometric estimation in long-range dependent volatility models: Theory and practice," Journal of Econometrics, Elsevier, vol. 147(1), pages 72-83, November.
    6. Asai, M. & McAleer, M.J. & Medeiros, M.C., 2010. "Asymmetry and Long Memory in Volatility Modelling," Econometric Institute Research Papers EI 2010-60, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Manabu Asai & Michael McAleer, 2013. "Leverage and Feedback Effects on Multifactor Wishart Stochastic Volatility for Option Pricing," KIER Working Papers 840, Kyoto University, Institute of Economic Research.
    8. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.
    9. Tsyplakov, Alexander, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models," MPRA Paper 25511, University Library of Munich, Germany.
    10. Gregory Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Staff Working Papers 07-20, Bank of Canada.
    11. Asai, Manabu & McAleer, Michael & de Veiga, Bernardo, 2008. "Portfolio single index (PSI) multivariate conditional and stochastic volatility models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 209-214.
    12. Benjamin Poignard & Manabu Asaiz, 2020. "A Penalised OLS Framework for High-Dimensional Multivariate Stochastic Volatility Models," Discussion Papers in Economics and Business 20-02, Osaka University, Graduate School of Economics.
    13. Roberto Casarin & Marco Tronzano & Domenico Sartore, 2013. "Bayesian Markov Switching Stochastic Correlation Models," Working Papers 2013:11, Department of Economics, University of Venice "Ca' Foscari".
    14. Manabu Asai & Michael McAleer, 2013. "A Fractionally Integrated Wishart Stochastic Volatility Model," Tinbergen Institute Discussion Papers 13-025/III, Tinbergen Institute.
    15. Michael McAleer & Bernardo da Veiga, 2008. "Single-index and portfolio models for forecasting value-at-risk thresholds," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(3), pages 217-235.
    16. Christian Hafner & Philip Hans Franses, 2009. "A Generalized Dynamic Conditional Correlation Model: Simulation and Application to Many Assets," Econometric Reviews, Taylor & Francis Journals, vol. 28(6), pages 612-631.
    17. Asai, Manabu & Brugal, Ivan, 2013. "Forecasting volatility via stock return, range, trading volume and spillover effects: The case of Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 202-213.
    18. Sujay Mukhoti & Pritam Ranjan, 2017. "A New Class of Discrete-time Stochastic Volatility Model with Correlated Errors," Papers 1703.06603, arXiv.org.
    19. Anders Johansson, 2009. "Stochastic volatility and time-varying country risk in emerging markets," The European Journal of Finance, Taylor & Francis Journals, vol. 15(3), pages 337-363.
    20. Massimiliano Caporin & Michael McAleer, 2010. "Ranking Multivariate GARCH Models by Problem Dimension," CARF F-Series CARF-F-219, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    21. Bastian Gribisch, 2018. "A latent dynamic factor approach to forecasting multivariate stock market volatility," Empirical Economics, Springer, vol. 55(2), pages 621-651, September.
    22. Nguyen, Hoang & Virbickaitė, Audronė, 2023. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Energy Economics, Elsevier, vol. 124(C).
    23. Asai, Manabu & McAleer, Michael & Medeiros, Marcelo C., 2012. "Modelling and forecasting noisy realized volatility," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 217-230, January.
    24. Casas, Isabel & Lopes Moreira da Veiga, María Helena, 2019. "Exploring option pricing and hedging via volatility asymmetry," DES - Working Papers. Statistics and Econometrics. WS 28234, Universidad Carlos III de Madrid. Departamento de Estadística.
    25. McAleer, M.J., 2008. "The ten commandments for optimizing value-at-risk and daily capital charges," Econometric Institute Research Papers EI 2008-32, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    26. Cees Diks & Valentyn Panchenko & Oleg Sokolinskiy, & Dick van Dijk, 2013. "Comparing the Accuracy of Copula-Based Multivariate Density Forecasts in Selected Regions of Support," Tinbergen Institute Discussion Papers 13-061/III, Tinbergen Institute.
    27. Manabu Asai & Michael McAleer & Marcelo C. Medeiros, 2009. "Asymmetry and Leverage in Realized Volatility," CARF F-Series CARF-F-167, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    28. Chen, J. & Kobayashi, M. & McAleer, M.J., 2017. "Testing for Volatility Co-movement in Bivariate Stochastic Volatility Models," Econometric Institute Research Papers TI 2017-022/III, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    29. Bastian Gribisch, 2016. "Multivariate Wishart stochastic volatility and changes in regime," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 100(4), pages 443-473, October.
    30. Manabu Asai & Michael McAleer, 2014. "Forecasting Co-Volatilities via Factor Models with Asymmetry and Long Memory in Realized Covariance," Tinbergen Institute Discussion Papers 14-037/III, Tinbergen Institute.
    31. Haroon Mumtaz & Konstantinos Theodoridis, 2012. "The international transmission of volatility shocks: an empirical analysis," Bank of England working papers 463, Bank of England.
    32. Weber, Enzo, 2013. "Simultaneous stochastic volatility transmission across American equity markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 53(1), pages 53-60.
    33. Yu, Jun, 2012. "A semiparametric stochastic volatility model," Journal of Econometrics, Elsevier, vol. 167(2), pages 473-482.
    34. Kobayashi, Masahito, 2009. "Testing for jumps in the stochastic volatility models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2597-2608.
    35. Asai, M. & Chang, C-L. & McAleer, M.J., 2017. "Realized Stochastic Volatility with General Asymmetry and Long Memory," Econometric Institute Research Papers TI 2017-038/III, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    36. Armine Bagyan & Donald Richards, 2023. "Hoffmann-Jørgensen Inequalities for Random Walks on the Cone of Positive Definite Matrices," Journal of Theoretical Probability, Springer, vol. 36(2), pages 1181-1202, June.
    37. Vo, Minh, 2011. "Oil and stock market volatility: A multivariate stochastic volatility perspective," Energy Economics, Elsevier, vol. 33(5), pages 956-965, September.
    38. Alexandre Subbotin, 2009. "Volatility Models: from Conditional Heteroscedasticity to Cascades at Multiple Horizons," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 15(3), pages 94-138.
    39. Xin Jin & John M. Maheu, 2014. "Bayesian Semiparametric Modeling of Realized Covariance Matrices," Working Paper series 34_14, Rimini Centre for Economic Analysis.
    40. Tsunehiro Ishihara & Yasuhiro Omori, 2009. "Efficient Bayesian estimation of a multivariate stochastic volatility model with cross leverage and heavy-tailed errors," CARF F-Series CARF-F-198, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    41. Michael McAleer & Marcelo C. Medeiros, 2009. "Forecasting Realized Volatility with Linear and Nonlinear Models," CIRJE F-Series CIRJE-F-686, CIRJE, Faculty of Economics, University of Tokyo.
    42. Mike K. P. So & C. Y. Choi, 2009. "A threshold factor multivariate stochastic volatility model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(8), pages 712-735.
    43. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," CREATES Research Papers 2011-37, Department of Economics and Business Economics, Aarhus University.
    44. Barigozzi, Matteo & Hallin, Marc, 2017. "Generalized dynamic factor models and volatilities: estimation and forecasting," Journal of Econometrics, Elsevier, vol. 201(2), pages 307-321.
    45. Gribisch, Bastian, 2013. "A latent dynamic factor approach to forecasting multivariate stock market volatility," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79823, Verein für Socialpolitik / German Economic Association.
    46. Chiriac, Roxana & Voev, Valeri, 2008. "Modelling and forecasting multivariate realized volatility," CoFE Discussion Papers 08/06, University of Konstanz, Center of Finance and Econometrics (CoFE).
    47. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2011. "Multivariate High-Frequency-Based Volatility (HEAVY) Models," Economics Papers 2011-W01, Economics Group, Nuffield College, University of Oxford.
    48. Caporin, M. & McAleer, M.J., 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," Econometric Institute Research Papers EI2012-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    49. Jiří Witzany, 2011. "Estimating Correlated Jumps and Stochastic Volatilities," Working Papers IES 2011/35, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Nov 2011.
    50. Mukhoti, Sujay, 2014. "Non-Stationary Stochastic Volatility Model for Dynamic Feedback and Skewness," MPRA Paper 62532, University Library of Munich, Germany.
    51. Jinghui Chen & Masahito Kobayashi & Michael McAleer, 2016. "Testing for a Common Volatility Process and Information Spillovers in Bivariate Financial Time Series Models," Documentos de Trabajo del ICAE 2016-04, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    52. Amendola, Alessandra & Braione, Manuela & Candila, Vincenzo & Storti, Giuseppe, 2020. "A Model Confidence Set approach to the combination of multivariate volatility forecasts," International Journal of Forecasting, Elsevier, vol. 36(3), pages 873-891.
    53. Trojan, Sebastian, 2014. "Multivariate Stochastic Volatility with Dynamic Cross Leverage," Economics Working Paper Series 1424, University of St. Gallen, School of Economics and Political Science.
    54. Juan-Angel Jimenez-Martin & Michael McAleer & Teodosio Pérez-Amaral, 2009. "The Ten Commandments for Managing Value-at-Risk Under the Basel II Accord," Documentos de Trabajo del ICAE 2009-12, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    55. Hiroaki Hata & Jun Sekine, 2017. "Risk-Sensitive Asset Management in a Wishart-Autoregressive Factor Model with Jumps," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 24(3), pages 221-252, September.
    56. Huang, Shian-Chang, 2011. "Wavelet-based multi-resolution GARCH model for financial spillover effects," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(11), pages 2529-2539.
    57. João Caldeira & Guilherme Moura & André Santos, 2015. "Measuring Risk in Fixed Income Portfolios using Yield Curve Models," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 65-82, June.
    58. Hassanniakalager, Arman & Baker, Paul L. & Platanakis, Emmanouil, 2024. "A False Discovery Rate approach to optimal volatility forecasting model selection," International Journal of Forecasting, Elsevier, vol. 40(3), pages 881-902.
    59. McAleer, Michael & Medeiros, Marcelo C., 2008. "A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries," Journal of Econometrics, Elsevier, vol. 147(1), pages 104-119, November.
    60. Asai, M. & Caporin, M. & McAleer, M.J., 2012. "Forecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Models," Econometric Institute Research Papers EI 2012-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    61. Bauer, Gregory H. & Vorkink, Keith, 2011. "Forecasting multivariate realized stock market volatility," Journal of Econometrics, Elsevier, vol. 160(1), pages 93-101, January.
    62. Andre Lucas & Anne Opschoor, 2016. "Fractional Integration and Fat Tails for Realized Covariance Kernels and Returns," Tinbergen Institute Discussion Papers 16-069/IV, Tinbergen Institute, revised 07 Jul 2017.
    63. Hartwig, Benny, 2020. "Robust Inference in Time-Varying Structural VAR Models: The DC-Cholesky Multivariate Stochastic Volatility Model," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224528, Verein für Socialpolitik / German Economic Association.
    64. 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.
    65. Kurose, Yuta & Omori, Yasuhiro, 2020. "Multiple-block dynamic equicorrelations with realized measures, leverage and endogeneity," Econometrics and Statistics, Elsevier, vol. 13(C), pages 46-68.
    66. Alexander Subbotin & Thierry Chauveau & Kateryna Shapovalova, 2009. "Volatility Models: from GARCH to Multi-Horizon Cascades," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00390636, HAL.
    67. Barigozzi, Matteo & Hallin, Mark, 2015. "Generalized dynamic factor models and volatilities: recovering the market volatility shocks," LSE Research Online Documents on Economics 60980, London School of Economics and Political Science, LSE Library.
    68. Athanasios Tsagkanos & Konstantinos Gkillas & Christoforos Konstantatos & Christos Floros, 2021. "Does Trading Volume Drive Systemic Banks’ Stock Return Volatility? Lessons from the Greek Banking System," IJFS, MDPI, vol. 9(2), pages 1-13, April.
    69. Bonato, Matteo & Caporin, Massimiliano & Ranaldo, Angelo, 2013. "Risk spillovers in international equity portfolios," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 121-137.
    70. Caporin, Massimiliano, 2013. "Equity and CDS sector indices: Dynamic models and risk hedging," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 261-275.
    71. Asai, Manabu, 2009. "Bayesian analysis of stochastic volatility models with mixture-of-normal distributions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2579-2596.
    72. Gao, Jiti & McAleer, Michael & Allen, David E., 2008. "Econometric modelling in finance and risk management: An overview," Journal of Econometrics, Elsevier, vol. 147(1), pages 1-4, November.
    73. Mao, Xiuping & Czellar, Veronika & Ruiz, Esther & Veiga, Helena, 2020. "Asymmetric stochastic volatility models: Properties and particle filter-based simulated maximum likelihood estimation," Econometrics and Statistics, Elsevier, vol. 13(C), pages 84-105.
    74. Li, Weiming & Gao, Jing & Li, Kunpeng & Yao, Qiwei, 2016. "Modelling multivariate volatilities via latent common factors," LSE Research Online Documents on Economics 68121, London School of Economics and Political Science, LSE Library.
    75. Yao Axel Ehouman, 2020. "Volatility transmission between oil prices and banks’ stock prices as a new source of instability: Lessons from the United States experience," Post-Print hal-02960571, HAL.
    76. Tsunehiro Ishihara & Yasuhiro Omori & Manabu Asai, 2014. "Matrix Exponential Stochastic Volatility with Cross Leverage," CIRJE F-Series CIRJE-F-932, CIRJE, Faculty of Economics, University of Tokyo.
    77. Michael Weylandt & Yu Han & Katherine B. Ensor, 2019. "Multivariate Modeling of Natural Gas Spot Trading Hubs Incorporating Futures Market Realized Volatility," Papers 1907.10152, arXiv.org.
    78. Matteo Barigozzi & Marc Hallin, 2018. "Generalized Dynamic Factor Models and Volatilities: Consistency, rates, and prediction intervals," Papers 1811.10045, arXiv.org, revised Jul 2019.
    79. Yuta Kurose & Yasuhiro Omori, 2014. "Dynamic Equicorrelation Stochastic Volatility," CIRJE F-Series CIRJE-F-941, CIRJE, Faculty of Economics, University of Tokyo.
    80. Michael Smith & Andrew Pitts, 2006. "Foreign Exchange Intervention by the Bank of Japan: Bayesian Analysis Using a Bivariate Stochastic Volatility Model," Econometric Reviews, Taylor & Francis Journals, vol. 25(2-3), pages 425-451.
    81. Nadia Boussaha & Faycal Hamdi & Saïd Souam, 2018. "Multivariate Periodic Stochastic Volatility Models: Applications to Algerian dinar exchange rates and oil prices modeling," EconomiX Working Papers 2018-14, University of Paris Nanterre, EconomiX.
    82. Hoti, Suhejla, 2005. "Modelling country spillover effects in country risk ratings," Emerging Markets Review, Elsevier, vol. 6(4), pages 324-345, December.
    83. Manabu Asai & Chia-Lin Chang & Michael McAleer, 2016. "Realized Matrix-Exponential Stochastic Volatility with Asymmetry, Long Memory and Spillovers," Documentos de Trabajo del ICAE 2016-15, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    84. Moura, Guilherme V. & Santos, André A. P. & Ruiz Ortega, Esther, 2019. "Comparing Forecasts of Extremely Large Conditional Covariance Matrices," DES - Working Papers. Statistics and Econometrics. WS 29291, Universidad Carlos III de Madrid. Departamento de Estadística.
    85. Hans J. Skaug & Jun Yu, 2009. "Automated Likelihood Based Inference for Stochastic Volatility Models," Working Papers 15-2009, Singapore Management University, School of Economics.
    86. H. Peter Boswijk & Giuseppe Cavaliere & Luca De Angelis & A. M. Robert Taylor, 2022. "Adaptive information-based methods for determining the co-integration rank in heteroskedastic VAR models," Papers 2202.02532, arXiv.org.
    87. Moawia Alghalith & Christos Floros & Konstantinos Gkillas, 2020. "Estimating Stochastic Volatility under the Assumption of Stochastic Volatility of Volatility," Risks, MDPI, vol. 8(2), pages 1-15, April.
    88. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
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    162. G.K. Chetan Kumar & K.B. Rangappa & S. Suchitra, 2022. "Normative analysis of the impact of Covid-19 on prominent sectors of Indian economy by using ARCH Model," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(2(631), S), pages 151-164, Summer.
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  10. Yasuhiro Omori & Siddhartha Chib & Neil Shephard & Jouchi Nakajima, 2004. "Stochastic volatility with leverage: fast likelihood inference," Economics Papers 2004-W19, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Yuriy Kitsul & Jonathan H. Wright, 2012. "The Economics of Options-Implied Inflation Probability Density Functions," Economics Working Paper Archive 600, The Johns Hopkins University,Department of Economics.
    2. Toshitaka Sekine, 2006. "Time-varying exchange rate pass-through: experiences of some industrial countries," BIS Working Papers 202, Bank for International Settlements.
    3. Fruhwirth-Schnatter, Sylvia & Fruhwirth, Rudolf, 2007. "Auxiliary mixture sampling with applications to logistic models," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3509-3528, April.
    4. Hans J. Skaug & Jun Yu, 2009. "Automated Likelihood Based Inference for Stochastic Volatility Models," Working Papers 15-2009, Singapore Management University, School of Economics.
    5. Fulvia Focker & Umberto Triacca, 2006. "A new proxy of the average volatility of a basket of returns: A Monte Carlo study," Economics Bulletin, AccessEcon, vol. 3(15), pages 1-14.
    6. Tsunehiro Ishihara & Yasuhiro Omori & Manabu Asai, 2013. "Matrix Exponential Stochastic Volatility with Cross Leverage," CIRJE F-Series CIRJE-F-904, CIRJE, Faculty of Economics, University of Tokyo.

  11. Neil Shephard & Siddhartha Chib & Olin School of Business & Washington University & Michael K. Pitt & Department of Economics & University of Warwick, 2004. "Likelihood based inference for diffusion driven models," Economics Series Working Papers 2004-FE-17, University of Oxford, Department of Economics.

    Cited by:

    1. Nicolas Chopin & Mathieu Gerber, 2017. "Sequential quasi-Monte Carlo: Introduction for Non-Experts, Dimension Reduction, Application to Partly Observed Diffusion Processes," Working Papers 2017-35, Center for Research in Economics and Statistics.
    2. Marcin Mider & Paul A. Jenkins & Murray Pollock & Gareth O. Roberts, 2022. "The Computational Cost of Blocking for Sampling Discretely Observed Diffusions," Methodology and Computing in Applied Probability, Springer, vol. 24(4), pages 3007-3027, December.
    3. Matthew M. Graham & Alexandre H. Thiery & Alexandros Beskos, 2022. "Manifold Markov chain Monte Carlo methods for Bayesian inference in diffusion models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1229-1256, September.
    4. Osnat Stramer & Jun Yan, 2007. "Asymptotics of an Efficient Monte Carlo Estimation for the Transition Density of Diffusion Processes," Methodology and Computing in Applied Probability, Springer, vol. 9(4), pages 483-496, December.
    5. Martin J. Lenardon & Anna Amirdjanova, 2006. "Interaction between stock indices via changepoint analysis," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 22(5‐6), pages 573-586, September.
    6. 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.
    7. Peavoy, Daniel & Franzke, Christian L.E. & Roberts, Gareth O., 2015. "Systematic physics constrained parameter estimation of stochastic differential equations," Computational Statistics & Data Analysis, Elsevier, vol. 83(C), pages 182-199.
    8. S. C. Kou & Benjamin P. Olding & Martin Lysy & Jun S. Liu, 2012. "A Multiresolution Method for Parameter Estimation of Diffusion Processes," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(500), pages 1558-1574, December.

  12. Siddhartha Chib & Michael J. Dueker, 2004. "Non-Markovian regime switching with endogenous states and time-varying state strengths," Working Papers 2004-030, Federal Reserve Bank of St. Louis.

    Cited by:

    1. Chotipong Charoensom, 2024. "An Estimation of Regime Switching Models with Nonlinear Endogenous Switching," PIER Discussion Papers 217, Puey Ungphakorn Institute for Economic Research.
    2. Sylvia Kaufmann, 2014. "K-state switching models with time-varying transition distributions – Does credit growth signal stronger effects of variables on inflation?," Working Papers 14.04, Swiss National Bank, Study Center Gerzensee.
    3. Chang, Yoosoon & Maih, Junior & Tan, Fei, 2021. "Origins of monetary policy shifts: A New approach to regime switching in DSGE models," Journal of Economic Dynamics and Control, Elsevier, vol. 133(C).
    4. Kaufmann, Sylvia, 2015. "K-state switching models with time-varying transition distributions—Does loan growth signal stronger effects of variables on inflation?," Journal of Econometrics, Elsevier, vol. 187(1), pages 82-94.
    5. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combination Schemes for Turning Point Predictions," Tinbergen Institute Discussion Papers 11-123/4, Tinbergen Institute.
    6. Xin Wei, 2020. "Dynamic Expectations Formation and U.S. Monetary Policy Regime Change," CAEPR Working Papers 2020-007, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    7. Billio Monica & Casarin Roberto, 2011. "Beta Autoregressive Transition Markov-Switching Models for Business Cycle Analysis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(4), pages 1-32, September.
    8. Andrei A. Sirchenko, 2017. "An endogenous regime-switching model of ordered choice with an application to federal funds rate target," 2017 Papers psi424, Job Market Papers.
    9. Judex Hyppolite & Pravin Trivedi, 2012. "Alternative Approaches For Econometric Analysis Of Panel Count Data Using Dynamic Latent Class Models (With Application To Doctor Visits Data)," Health Economics, John Wiley & Sons, Ltd., vol. 21(S1), pages 101-128, June.
    10. Sinclair Tara M, 2009. "Asymmetry in the Business Cycle: Friedman's Plucking Model with Correlated Innovations," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(1), pages 1-31, December.
    11. Chaojun Li & Yan Liu, 2020. "Asymptotic Properties of the Maximum Likelihood Estimator in Regime-Switching Models with Time-Varying Transition Probabilities," Papers 2010.04930, arXiv.org, revised Dec 2021.
    12. Mark W. French, 2005. "A nonlinear look at trend MFP growth and the business cycle: result from a hybrid Kalman/Markov switching model," Finance and Economics Discussion Series 2005-12, Board of Governors of the Federal Reserve System (U.S.).

  13. Siddhartha Chib & Michael K Pitt & Neil Shephard, 2004. "Likelihood based inference for diffusion driven models," Economics Papers 2004-W20, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Nicolas Chopin & Mathieu Gerber, 2017. "Sequential quasi-Monte Carlo: Introduction for Non-Experts, Dimension Reduction, Application to Partly Observed Diffusion Processes," Working Papers 2017-35, Center for Research in Economics and Statistics.
    2. Marcin Mider & Paul A. Jenkins & Murray Pollock & Gareth O. Roberts, 2022. "The Computational Cost of Blocking for Sampling Discretely Observed Diffusions," Methodology and Computing in Applied Probability, Springer, vol. 24(4), pages 3007-3027, December.
    3. Matthew M. Graham & Alexandre H. Thiery & Alexandros Beskos, 2022. "Manifold Markov chain Monte Carlo methods for Bayesian inference in diffusion models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1229-1256, September.
    4. Osnat Stramer & Jun Yan, 2007. "Asymptotics of an Efficient Monte Carlo Estimation for the Transition Density of Diffusion Processes," Methodology and Computing in Applied Probability, Springer, vol. 9(4), pages 483-496, December.
    5. Martin J. Lenardon & Anna Amirdjanova, 2006. "Interaction between stock indices via changepoint analysis," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 22(5‐6), pages 573-586, September.
    6. 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.
    7. Peavoy, Daniel & Franzke, Christian L.E. & Roberts, Gareth O., 2015. "Systematic physics constrained parameter estimation of stochastic differential equations," Computational Statistics & Data Analysis, Elsevier, vol. 83(C), pages 182-199.
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    1. Stan Hurn & J.Jeisman & K.A. Lindsay, 2006. "Seeing the wood for the trees: A critical evaluation of methods to estimate the parameters of stochastic differential equations," Stan Hurn Discussion Papers 2006, School of Economics and Finance, Queensland University of Technology.
    2. Stan Hurn & J.Jeisman & K.A. Lindsay, 2006. "Seeing the Wood for the Trees: A Critical Evaluation of Methods to Estimate the Parameters of Stochastic Differential Equations. Working paper #2," NCER Working Paper Series 2, National Centre for Econometric Research.

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    131. Ruijun Bu & Ludovic Giet & Kaddour Hadri & Michel Lubrano, 2009. "Modelling Multivariate Interest Rates using Time-Varying Copulas and Reducible Non-Linear Stochastic Differential," Economics Working Papers 09-02, Queen's Management School, Queen's University Belfast.
    132. Marcos Massaki Abe & Eui Jung Chang & Benjamin Miranda Tabak, 2007. "Forecasting Exchange Rate Density Using Parametric Models: the Case of Brazil," Brazilian Review of Finance, Brazilian Society of Finance, vol. 5(1), pages 29-39.

  16. Siddhartha Chib & Edward Greenberg & Yuxin Chen, 1998. "MCMC Methods for Fitting and Comparing Multinomial Response Models," Econometrics 9802001, University Library of Munich, Germany, revised 06 May 1998.

    Cited by:

    1. Rub'en Loaiza-Maya & Didier Nibbering, 2022. "Fast variational Bayes methods for multinomial probit models," Papers 2202.12495, arXiv.org, revised Oct 2022.
    2. Duncan Fong & Sunghoon Kim & Zhe Chen & Wayne DeSarbo, 2016. "A Bayesian Multinomial Probit MODEL FOR THE ANALYSIS OF PANEL CHOICE DATA," Psychometrika, Springer;The Psychometric Society, vol. 81(1), pages 161-183, March.
    3. Luiz Moutinho & Graeme D. Hutcheson, 2006. "Store Patronage: The Utility Of A Multi-Method, Multi-Nomial Logistic Regression Model For Predicting Store Choice," Portuguese Journal of Management Studies, ISEG, Universidade de Lisboa, vol. 0(1), pages 5-25.
    4. Hoshino, Takahiro, 2008. "A Bayesian propensity score adjustment for latent variable modeling and MCMC algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1413-1429, January.
    5. Kajal Lahiri & Jian Gao, 2001. "Bayesian Analysis of Nested Logit Model by Markov Chain Monte Carlo," Discussion Papers 01-14, University at Albany, SUNY, Department of Economics.
    6. Daziano, Ricardo A., 2013. "Conditional-logit Bayes estimators for consumer valuation of electric vehicle driving range," Resource and Energy Economics, Elsevier, vol. 35(3), pages 429-450.
    7. Minjung Kyung & Jeff Gill & George Casella, 2011. "Sampling schemes for generalized linear Dirichlet process random effects models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(3), pages 259-290, August.
    8. McCulloch, Robert E. & Polson, Nicholas G. & Rossi, Peter E., 2000. "A Bayesian analysis of the multinomial probit model with fully identified parameters," Journal of Econometrics, Elsevier, vol. 99(1), pages 173-193, November.
    9. Patil, Priyadarshan N. & Dubey, Subodh K. & Pinjari, Abdul R. & Cherchi, Elisabetta & Daziano, Ricardo & Bhat, Chandra R., 2017. "Simulation evaluation of emerging estimation techniques for multinomial probit models," Journal of choice modelling, Elsevier, vol. 23(C), pages 9-20.
    10. Zhehan Jiang & Jonathan Templin, 2019. "Gibbs Samplers for Logistic Item Response Models via the Pólya–Gamma Distribution: A Computationally Efficient Data-Augmentation Strategy," Psychometrika, Springer;The Psychometric Society, vol. 84(2), pages 358-374, June.

  17. Siddhartha Chib & Edward Greenberg & Rainer Winkelmann, 1996. "Posterior Simulation and Bayes Factors in Panel Count Data Models," Econometrics 9608003, University Library of Munich, Germany, revised 25 Nov 1996.

    Cited by:

    1. Tong Li & Xiaoyong Zheng, 2006. "Entry and competition effects in first-price auctions: theory and evidence from procurement auctions," CeMMAP working papers CWP13/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Griffith, Daniel A. & Fischer, Manfred M. & LeSage, James P., 2016. "The spatial autocorrelation problem in spatial interaction modelling: a comparison of two common solutions," MPRA Paper 78264, University Library of Munich, Germany.
    3. B.P.M. McCabe & G.M. Martin, 2003. "Coherent Predictions of Low Count Time Series," Monash Econometrics and Business Statistics Working Papers 8/03, Monash University, Department of Econometrics and Business Statistics.
    4. Emilio Augusto Coelho-Barros & Jorge Alberto Achcar & Josmar Mazucheli, 2010. "Longitudinal Poisson modeling: an application for CD4 counting in HIV-infected patients," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(5), pages 865-880.
    5. Anita Castledine & Klaus Moeltner & Michael Price & Shawn Stoddard, 2014. "Free to Choose: Promoting Conservation by Relaxing Outdoor Watering Restrictions," NBER Working Papers 20362, National Bureau of Economic Research, Inc.
    6. McCabe, B.P.M. & Martin, G.M., 2005. "Bayesian predictions of low count time series," International Journal of Forecasting, Elsevier, vol. 21(2), pages 315-330.
    7. Fruhwirth-Schnatter, Sylvia & Fruhwirth, Rudolf, 2007. "Auxiliary mixture sampling with applications to logistic models," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3509-3528, April.
    8. Florenz Plassmann & Neha Khanna, 2007. "Assessing the Precision of Turning Point Estimates in Polynomial Regression Functions," Econometric Reviews, Taylor & Francis Journals, vol. 26(5), pages 503-528.
    9. Klaus Moeltner & James J. Murphy & John K. Stranlund & Maria Alejandra Velez, 2013. "Institutional heterogeneity in social dilemma games: a Bayesian examination," Chapters, in: John A. List & Michael K. Price (ed.), Handbook on Experimental Economics and the Environment, chapter 2, pages 67-88, Edward Elgar Publishing.
    10. Birgit Schrödle & Leonhard Held & Håvard Rue, 2012. "Assessing the Impact of a Movement Network on the Spatiotemporal Spread of Infectious Diseases," Biometrics, The International Biometric Society, vol. 68(3), pages 736-744, September.
    11. Huang, Ho-Chuan (River), 1999. "Estimation of the SUR Tobit model via the MCECM algorithm," Economics Letters, Elsevier, vol. 64(1), pages 25-30, July.
    12. Wong, Timothy, 2014. "Lights, camera, legal action! The effectiveness of red light cameras on collisions in Los Angeles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 69(C), pages 165-182.
    13. Mikołaj Czajkowski & Marek Giergiczny & Jakub Kronenberg & Jeffrey Englin, 2019. "The Individual Travel Cost Method with Consumer-Specific Values of Travel Time Savings," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(3), pages 961-984, November.
    14. Chunling Wang & Xiaoyan Lin, 2022. "Bayesian Semiparametric Regression Analysis of Multivariate Panel Count Data," Stats, MDPI, vol. 5(2), pages 1-17, May.
    15. Du Juan, 2012. "Formal and Informal Care: An Empirical Bayesian Analysis Using the Two-part Model," Forum for Health Economics & Policy, De Gruyter, vol. 15(1), pages 1-42, November.
    16. Tatsushi Oka & Wei Wei & Dan Zhu, 2020. "A Spatial Stochastic SIR Model for Transmission Networks with Application to COVID-19 Epidemic in China," Papers 2008.06051, arXiv.org, revised Aug 2020.
    17. Li, Tong & Zheng, Xiaoyong, 2012. "Information acquisition and/or bid preparation: A structural analysis of entry and bidding in timber sale auctions," Journal of Econometrics, Elsevier, vol. 168(1), pages 29-46.
    18. Perrakis, Konstantinos & Ntzoufras, Ioannis & Tsionas, Efthymios G., 2014. "On the use of marginal posteriors in marginal likelihood estimation via importance sampling," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 54-69.
    19. Jianhong Wang & Xiaoyan Lin, 2020. "A Bayesian approach for semiparametric regression analysis of panel count data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(2), pages 402-420, April.
    20. Gholamreza Hajargasht & Prasada Rao, 2018. "Multilateral Index Number Systems for International Price Comparisons: Properties, Existence and Uniqueness," Papers 1811.04197, arXiv.org, revised Dec 2018.
    21. Munkin, Murat K., 2003. "The MCMC and SML estimation of a self-selection model with two outcomes," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 403-424, March.
    22. Chib, Siddhartha, 2004. "Markov Chain Monte Carlo Technology," Papers 2004,22, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    23. Herriges, Joseph A. & Phaneuf, Daniel J. & Tobias, Justin L., 2008. "Estimating demand systems when outcomes are correlated counts," Journal of Econometrics, Elsevier, vol. 147(2), pages 282-298, December.
    24. Hruschka, Harald, 2010. "Considering endogeneity for optimal catalog allocation in direct marketing," European Journal of Operational Research, Elsevier, vol. 206(1), pages 239-247, October.
    25. William Greene, 2001. "Fixed and Random Effects in Nonlinear Models," Working Papers 01-01, New York University, Leonard N. Stern School of Business, Department of Economics.
    26. Dimitrakopoulos, Stefanos, 2018. "Accounting for persistence in panel count data models. An application to the number of patents awarded," Economics Letters, Elsevier, vol. 171(C), pages 245-248.
    27. Hikaru Hasegawa & Kazuhiro Ueda & Kunie Mori, 2008. "Estimation of Engel Curves from Survey Data with Zero Expenditures," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(4), pages 535-558, August.
    28. Hübler, Olaf, 2005. "Panel Data Econometrics: Modelling and Estimation," Hannover Economic Papers (HEP) dp-319, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    29. Munkin, Murat K. & Trivedi, Pravin K., 2003. "Bayesian analysis of a self-selection model with multiple outcomes using simulation-based estimation: an application to the demand for healthcare," Journal of Econometrics, Elsevier, vol. 114(2), pages 197-220, June.
    30. Siddhartha Chib & Michael Dueker & Anatoliy Belaygorod, 2005. "Structural Breaks in Estimated DSGE Models with Indeterminacy," Computing in Economics and Finance 2005 357, Society for Computational Economics.
    31. Andrew D. Martin, 2003. "Bayesian Inference for Heterogeneous Event Counts," Sociological Methods & Research, , vol. 32(1), pages 30-63, August.

  18. Siddhartha Chib & Edward Greenberg, 1996. "Bayesian Analysis of Multivariate Probit Models," Econometrics 9608002, University Library of Munich, Germany.

    Cited by:

    1. Kajal Lahiri & Jian Gao, 2001. "Bayesian Analysis of Nested Logit Model by Markov Chain Monte Carlo," Discussion Papers 01-14, University at Albany, SUNY, Department of Economics.

  19. Siddhartha Chib & Edward Greenberg, 1994. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometrics 9408001, University Library of Munich, Germany, revised 23 Feb 1995.

    Cited by:

    1. Alex Ilek & Tanya Suchoy & Nir Klein, 2006. "Estimating the premium implicit in the yields of Treasury Bills," Israel Economic Review, Bank of Israel, vol. 4(2), pages 53-83.
    2. Hautsch, Nikolaus & Yang, Fuyu, 2010. "Bayesian inference in a stochastic volatility Nelson-Siegel Model," SFB 649 Discussion Papers 2010-004, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    3. Sylvia Kaufmann, 2001. "Is there an asymmetric effect on monetary policy over time? A bayesian analysis using Austrian data," Working Papers 45, Oesterreichische Nationalbank (Austrian Central Bank).
    4. Kajal Lahiri & Chuanming Gao, 2001. "A Comparison of Some Recent Bayesian and Classical Procedures for Simultaneous Equation Models with Weak Instruments," Discussion Papers 01-15, University at Albany, SUNY, Department of Economics.
    5. Barnett, William A. & Serletis, Apostolos, 2008. "Consumer preferences and demand systems," MPRA Paper 8413, University Library of Munich, Germany.
    6. Moshe Buchinsky & Denis Fougère & Francis Kramarz & Rusty Tchernis, 2008. "Interfirm Mobility, Wages, and the Returns to Seniority and Experience in the U.S," CAEPR Working Papers 2008-006, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    7. Chua, Chew Lian & Tsiaplias, Sarantis, 2011. "Predicting economic contractions and expansions with the aid of professional forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 438-451, April.
    8. Nunzio Cappuccio & Diego Lubian & Davide Raggi, 2003. "MCMC Bayesian Estimation of a Skew-GED Stochastic Volatily Model," Working Papers 07/2003, University of Verona, Department of Economics.
    9. Otrok, Christopher, 2001. "On measuring the welfare cost of business cycles," Journal of Monetary Economics, Elsevier, vol. 47(1), pages 61-92, February.
    10. Miazhynskaia, Tatiana & Fruhwirth-Schnatter, Sylvia & Dorffner, Georg, 2006. "Bayesian testing for non-linearity in volatility modeling," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 2029-2042, December.
    11. Michiel D. de Pooter & René Segers & Herman K. van Dijk, 2006. "On the Practice of Bayesian Inference in Basic Economic Time Series Models using Gibbs Sampling," Tinbergen Institute Discussion Papers 06-076/4, Tinbergen Institute.
    12. Tsyplakov, Alexander, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models," MPRA Paper 25511, University Library of Munich, Germany.
    13. Eliana González & . Luis F. Melo & Viviana Monroy & Brayan Rojas, 2009. "A Dynamic Factor Model for the Colombian Inflation," Borradores de Economia 549, Banco de la Republica de Colombia.
    14. Will Davis & Alexander Gordan & Rusty Tchernis, 2021. "Measuring the spatial distribution of health rankings in the United States," Health Economics, John Wiley & Sons, Ltd., vol. 30(11), pages 2921-2936, November.
    15. Koji Miyawaki & Yasuhiro Omori & Akira Hibiki, 2009. "Bayesian Estimation of Demand Functions under Block Rate Pricing," CIRJE F-Series CIRJE-F-631, CIRJE, Faculty of Economics, University of Tokyo.
    16. Christopher J. O'Donnell & Alicia N. Rambaldi & Howard E. Doran, 2001. "Estimating economic relationships subject to firm- and time-varying equality and inequality constraints," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(6), pages 709-726.
    17. Waggoner, Daniel F. & Zha, Tao, 2003. "A Gibbs sampler for structural vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 28(2), pages 349-366, November.
    18. Marsh, Thomas L. & Featherstone, Allen M. & Garrett, Thomas A., 2003. "Input Inefficiency in Commercial Banks: A Normalized Quadratic Input Distance Approach," 2003 Regional Committee NCT-194, October 6-7, 2003; Kansas City, Missouri 132520, Regional Research Committee NC-1014: Agricultural and Rural Finance Markets in Transition.
    19. Ana B. Galvão & Michael T. Owyang, 2014. "Financial stress regimes and the macroeconomy," Working Papers 2014-20, Federal Reserve Bank of St. Louis.
    20. Carmen Fernandez & Eduardo Ley & Mark Steel, 1999. "Model uncertainty in cross-country growth regressions," Econometrics 9903003, University Library of Munich, Germany, revised 06 Oct 2001.
    21. Peng Chen & Shu Wu, 2013. "On international stock market co-movements and macroeconomic risks," Applied Economics Letters, Taylor & Francis Journals, vol. 20(10), pages 978-982, July.
    22. Sandor, Zsolt & Andras, P.Peter, 2004. "Alternative sampling methods for estimating multivariate normal probabilities," Journal of Econometrics, Elsevier, vol. 120(2), pages 207-234, June.
    23. Koopman, S.J.M. & Shephard, N. & Doornik, J.A., 1998. "Statistical Algorithms for Models in State Space Using SsfPack 2.2," Other publications TiSEM 8fe36759-6517-4c66-86fa-e, Tilburg University, School of Economics and Management.
    24. Grace H.Y. Lee, 2009. "Aggregate Shocks Decomposition For Eight East Asian Countries," Monash Economics Working Papers 17-09, Monash University, Department of Economics.
    25. Chou, Pin-Huang, 1997. "A Gibbs sampling approach to the estimation of linear regression models under daily price limits," Pacific-Basin Finance Journal, Elsevier, vol. 5(1), pages 39-62, February.
    26. Chen, Peng, 2015. "Global oil prices, macroeconomic fundamentals and China's commodity sector comovements," Energy Policy, Elsevier, vol. 87(C), pages 284-294.
    27. Nakajima, Jouchi & Omori, Yasuhiro, 2009. "Leverage, heavy-tails and correlated jumps in stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2335-2353, April.
    28. Sanford, Andrew D. & Martin, Gael M., 2005. "Simulation-based Bayesian estimation of an affine term structure model," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 527-554, April.
    29. Sergio Rey & Guy West & Mark Janikas, 2004. "Uncertainty in Integrated Regional Models," Economic Systems Research, Taylor & Francis Journals, vol. 16(3), pages 259-277.
    30. John Geweke, 1998. "Using simulation methods for Bayesian econometric models: inference, development, and communication," Staff Report 249, Federal Reserve Bank of Minneapolis.
    31. Gary Chamberlain & Guido W. Imbens, 1996. "Hierarchical Bayes Models with Many Instrumental Variables," NBER Technical Working Papers 0204, National Bureau of Economic Research, Inc.
    32. Gerhard Arminger & Bengt Muthén, 1998. "A Bayesian approach to nonlinear latent variable models using the Gibbs sampler and the metropolis-hastings algorithm," Psychometrika, Springer;The Psychometric Society, vol. 63(3), pages 271-300, September.
    33. James D. Hamilton & Daniel F. Waggoner & Tao Zha, 2004. "Normalization in econometrics," FRB Atlanta Working Paper 2004-13, Federal Reserve Bank of Atlanta.
    34. Wolfgang Aussenegg & Tatiana Miazhynskaia, 2006. "Uncertainty in Value-at-risk Estimates under Parametric and Non-parametric Modeling," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 20(3), pages 243-264, September.
    35. M. Ayhan Kose & Christopher Otrok & Charles H. Whiteman, 2003. "International Business Cycles: World, Region, and Country-Specific Factors," American Economic Review, American Economic Association, vol. 93(4), pages 1216-1239, September.
    36. Griffiths, William E. & O'Donnell, Christopher J. & Cruz, Agustina Tan, 2000. "Imposing regularity conditions on a system of cost and factor share equations," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 44(01), pages 1-21.
    37. Christopher Otrok & Charles H. Whiteman, 1996. "Baynesian Leading Indicators: Measuring and Predicting Economic Conditions," Macroeconomics 9610002, University Library of Munich, Germany.
    38. Jouchi Nakajima & Yasuhiro Omori, 2007. "Leverage, Heavy-Tails and Correlated Jumps in Stochastic Volatility Models (Revised in January 2008; Published in "Computational Statistics and Data Analysis", 53-6, 2335-2353. April 2009. )," CARF F-Series CARF-F-107, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    39. Ryo Nakajima, 2004. "Measuring Peer Effects on Youth Smoking Behavior," ISER Discussion Paper 0600, Institute of Social and Economic Research, The University of Osaka.
    40. 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.
    41. A. Onofri & L. Fulginiti, 2008. "Rejoinder," Journal of Productivity Analysis, Springer, vol. 30(1), pages 81-85, August.
    42. Michael J. Dueker & Laura E. Jackson & Michael T. Owyang & Martin Sola, 2010. "A Time-Varying Threshold STAR Model with Applications," Working Papers 2010-029, Federal Reserve Bank of St. Louis, revised 10 Aug 2022.
    43. Anatoliy Belaygorod & Michael J. Dueker, 2005. "Discrete monetary policy changes and changing inflation targets in estimated dynamic stochastic general equilibrium models," Review, Federal Reserve Bank of St. Louis, vol. 87(Nov), pages 719-734.
    44. Wayne Taylor & Anand Bodapati, 2024. "The Effect of Gambling Outcomes on Casino Return Times with Scalable DDC," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 11(1), pages 1-28, December.
    45. Krzysztof Beck & Karen Jackson, 2024. "International trade fluctuations: Global versus regional factors," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 57(1), pages 331-358, February.
    46. Hasan Isomitdinov & Vladimir Arčabić & Junsoo Lee & Youngjin Yun & James E. Payne, 2024. "International comovements of public debt," Economic Inquiry, Western Economic Association International, vol. 62(2), pages 722-747, April.
    47. Andrew D. Sanford & Gael Martin, 2004. "Bayesian Analysis of Continuous Time Models of the Australian Short Rate," Monash Econometrics and Business Statistics Working Papers 11/04, Monash University, Department of Econometrics and Business Statistics.
    48. Christopher S. Jones, 2003. "Nonlinear Mean Reversion in the Short-Term Interest Rate," The Review of Financial Studies, Society for Financial Studies, vol. 16(3), pages 793-843, July.
    49. Gael Martin, 2001. "Bayesian Analysis Of A Fractional Cointegration Model," Econometric Reviews, Taylor & Francis Journals, vol. 20(2), pages 217-234.
    50. Doron Avramov & Guofu Zhou, 2010. "Bayesian Portfolio Analysis," Annual Review of Financial Economics, Annual Reviews, vol. 2(1), pages 25-47, December.
    51. Chih‐Sheng Hsieh & Lung‐Fei Lee & Vincent Boucher, 2020. "Specification and estimation of network formation and network interaction models with the exponential probability distribution," Quantitative Economics, Econometric Society, vol. 11(4), pages 1349-1390, November.
    52. Eleonora Patacchini & Edoardo Rainone, 2014. "The Word on Banking - Social Ties, Trust, and the Adoption of Financial Products," EIEF Working Papers Series 1404, Einaudi Institute for Economics and Finance (EIEF), revised Jul 2014.
    53. Francisco Peñaranda, 2004. "Are Vector Autoregressions an Accurate Model for Dynamic Asset Allocation?," Working Papers wp2004_0419, CEMFI.
    54. Chris M Strickland & Gael Martin & Catherine S Forbes, 2006. "Parameterisation and Efficient MCMC Estimation of Non-Gaussian State Space Models," Monash Econometrics and Business Statistics Working Papers 22/06, Monash University, Department of Econometrics and Business Statistics.
    55. Kaufmann Sylvia & Scheicher Martin, 2006. "A Switching ARCH Model for the German DAX Index," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(4), pages 1-37, December.
    56. 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.
    57. Stock, James H. & Watson, Mark, 2011. "Dynamic Factor Models," Scholarly Articles 28469541, Harvard University Department of Economics.
    58. Scruggs, John T., 2007. "Estimating the cross-sectional market response to an endogenous event: Naked vs. underwritten calls of convertible bonds," Journal of Empirical Finance, Elsevier, vol. 14(2), pages 220-247, March.
    59. Aikaterini Karadimitropoulou & Miguel León-Ledesma, 2013. "World, Country, and Sector Factors in International Business Cycles," University of East Anglia Applied and Financial Economics Working Paper Series 045, School of Economics, University of East Anglia, Norwich, UK..
    60. Anna Mikusheva, 2014. "Estimation of dynamic stochastic general equilibrium models (in Russian)," Quantile, Quantile, issue 12, pages 1-21, February.
    61. Chib, Siddhartha, 1998. "Estimation and comparison of multiple change-point models," Journal of Econometrics, Elsevier, vol. 86(2), pages 221-241, June.
    62. John Geweke & Gautam Gowrisankaran & Robert J. Town, 2002. "Bayesian Inference for Hospital Quality in a Selection Model," Working Paper Series 2002-18, Federal Reserve Bank of San Francisco.
    63. Antonio Pacifico, 2023. "Obesity and labour market outcomes in Italy: a dynamic panel data evidence with correlated random effects," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 24(4), pages 557-574, June.
    64. Shyh-Wei Chen & Chung-Hua Shen, 2007. "Evidence of the duration-dependence from the stock markets in the Pacific Rim economies," Applied Economics, Taylor & Francis Journals, vol. 39(11), pages 1461-1474.
    65. Patacchini, Eleonora & Arduini, Tiziano, 2016. "Residential choices of young Americans," Journal of Housing Economics, Elsevier, vol. 34(C), pages 69-81.
    66. Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2006. "Analysis of high dimensional multivariate stochastic volatility models," Journal of Econometrics, Elsevier, vol. 134(2), pages 341-371, October.
    67. Lee, Grace H.Y. & Azali, M., 2012. "Is East Asia an optimum currency area?," Economic Modelling, Elsevier, vol. 29(2), pages 87-95.
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    70. Hoogerheide, L.F. & Kaashoek, J.F. & van Dijk, H.K., 2004. "Neural network based approximations to posterior densities: a class of flexible sampling methods with applications to reduced rank models," Econometric Institute Research Papers EI 2004-19, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    71. Chib, Siddhartha & Hamilton, Barton H., 2002. "Semiparametric Bayes analysis of longitudinal data treatment models," Journal of Econometrics, Elsevier, vol. 110(1), pages 67-89, September.
    72. Tsiaplias, Sarantis, 2008. "Factor estimation using MCMC-based Kalman filter methods," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 344-353, December.
    73. Luis Quintero, "undated". "MCMC Approach to Classical Estimation with Overidentifying Restrictions," GSIA Working Papers 2013-E13, Carnegie Mellon University, Tepper School of Business.
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    75. Aikaterini Karadimitropoulou, 2017. "Advanced economies and emerging markets: Dissecting the drivers of business cycle synchronization," University of East Anglia School of Economics Working Paper Series 2017-05, School of Economics, University of East Anglia, Norwich, UK..
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    1. L W Hepple, 1995. "Bayesian Techniques in Spatial and Network Econometrics: 2. Computational Methods and Algorithms," Environment and Planning A, , vol. 27(4), pages 615-644, April.
    2. L W Hepple, 1995. "Bayesian Techniques in Spatial and Network Econometrics: 1. Model Comparison and Posterior Odds," Environment and Planning A, , vol. 27(3), pages 447-469, March.

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    Cited by:

    1. L W Hepple, 1995. "Bayesian Techniques in Spatial and Network Econometrics: 2. Computational Methods and Algorithms," Environment and Planning A, , vol. 27(4), pages 615-644, April.
    2. L W Hepple, 1995. "Bayesian Techniques in Spatial and Network Econometrics: 1. Model Comparison and Posterior Odds," Environment and Planning A, , vol. 27(3), pages 447-469, March.
    3. N/A, 1996. "Obituary—Glenda H Laws, 1959–1996," Environment and Planning A, , vol. 28(10), pages 1909-1909, October.
    4. Carmen Fernandez & Eduardo Ley & Mark F.J. Steel, 1998. "Benchmark Priors for Bayesian Model Averaging," Econometrics 9804001, University Library of Munich, Germany, revised 08 Oct 2001.

  22. Chib, S. & Osiewalski, J. & Steel, M., 1990. "Posterior Inference On The Degrees Of Freedom Parameter In Multivariate-T Regression Models," Papers 9043, Tilburg - Center for Economic Research.

    Cited by:

    1. Osiewalski, Jacek & Steel, Mark F.J., 1992. "Posterior moments of scale parameters in elliptical regression models," UC3M Working papers. Economics 10879, Universidad Carlos III de Madrid. Departamento de Economía.
    2. Nadarajah Saralees, 2007. "A Truncated Bivariate t Distribution," Stochastics and Quality Control, De Gruyter, vol. 22(2), pages 303-313, January.
    3. Osiewalski, Jacek & Steel, Mark F.J., 1992. "Bayesian marginal equivalence of elliptical regression models," UC3M Working papers. Economics 10950, Universidad Carlos III de Madrid. Departamento de Economía.
    4. James Berger & Elías Moreno & Luis Pericchi & M. Bayarri & José Bernardo & Juan Cano & Julián Horra & Jacinto Martín & David Ríos-Insúa & Bruno Betrò & A. Dasgupta & Paul Gustafson & Larry Wasserman &, 1994. "An overview of robust Bayesian analysis," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 3(1), pages 5-124, June.

  23. Sangjoon Kim, Neil Shephard & Siddhartha Chib, "undated". "Stochastic volatility: likelihood inference and comparison with ARCH models," Economics Papers W26, revised version of W, Economics Group, Nuffield College, University of Oxford.

    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. Antonio A. F. Santos, 2021. "Bayesian Estimation for High-Frequency Volatility Models in a Time Deformed Framework," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 455-479, February.
    3. Takaishi, Tetsuya, 2018. "Bias correction in the realized stochastic volatility model for daily volatility on the Tokyo Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 139-154.
    4. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 1999. "Range-Based Estimation of Stochastic Volatility Models or Exchange Rate Dynamics are More Interesting Than You Think," Center for Financial Institutions Working Papers 00-28, Wharton School Center for Financial Institutions, University of Pennsylvania.
    5. Brenda Guevara & Gabriel Rodríguez & Lorena Yamuca Salvatierra, 2024. "External Shocks and Economic Fluctuations in Peru: Empirical Evidence using Mixture Innovation TVP-VAR-SV Models," Documentos de Trabajo / Working Papers 2024-529, Departamento de Economía - Pontificia Universidad Católica del Perú.
    6. Audrino, Francesco & Fengler, Matthias, 2013. "Are classical option pricing models consistent with observed option second-order moments? Evidence from high-frequency data," Economics Working Paper Series 1311, University of St. Gallen, School of Economics and Political Science.
    7. Martin Iseringhausen & Hauke Vierke, 2018. "What Drives Output Volatility? The Role of Demographics and Government Size Revisited," European Economy - Discussion Papers 075, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    8. Jesús Fernández-Villaverde & Pablo Guerrón-Quintana & Juan F. Rubio-Ramírez, 2010. "Fortune or Virtue: Time-Variant Volatilities Versus Parameter Drifting in U.S. Data," NBER Working Papers 15928, National Bureau of Economic Research, Inc.
    9. 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.
    10. Ball, Clifford A. & Torous, Walter N., 2000. "Stochastic correlation across international stock markets," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 373-388, November.
    11. Punzi, Maria Teresa, 2016. "Financial cycles and co-movements between the real economy, finance and asset price dynamics in large-scale crises," FinMaP-Working Papers 61, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    12. Hautsch, Nikolaus & Yang, Fuyu, 2010. "Bayesian inference in a stochastic volatility Nelson-Siegel Model," SFB 649 Discussion Papers 2010-004, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
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    Cited by:

    1. Guanhao Feng & Wei Lan & Hansheng Wang & Jun Zhang, 2026. "Selecting and Testing Asset Pricing Models: A Stepwise Approach," Papers 2601.10279, arXiv.org.
    2. Yuxiao Jiao & Guofu Zhou & Wu Zhu & Yingzi Zhu, 2025. "Interpretable Factors of Firm Characteristics," Papers 2508.02253, arXiv.org.

  2. Siddhartha Chib & Minchul Shin & Fei Tan, 2023. "DSGE-SVt: An Econometric Toolkit for High-Dimensional DSGE Models with SV and t Errors," Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 69-111, January.
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  3. Chib, Siddhartha & Greenberg, Edward & Simoni, Anna, 2023. "Nonparametric Bayes Analysis Of The Sharp And Fuzzy Regression Discontinuity Designs," Econometric Theory, Cambridge University Press, vol. 39(3), pages 481-533, June.
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  4. Siddhartha Chib & Minchul Shin & Anna Simoni, 2022. "Bayesian estimation and comparison of conditional moment models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(3), pages 740-764, July.
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  5. Siddhartha Chib & Xiaming Zeng, 2020. "Which Factors are Risk Factors in Asset Pricing? A Model Scan Framework," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(4), pages 771-783, October.

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    1. Siddhartha Chib & Minchul Shin & Anna Simoni, 2021. "Bayesian Estimation and Comparison of Conditional Moment Models," Papers 2110.13531, arXiv.org.
    2. Jonathan Fletcher, 2024. "AN examination of linear factor models in U.K. stock returns in the presence of dynamic trading," Review of Quantitative Finance and Accounting, Springer, vol. 63(3), pages 1121-1147, October.
    3. Thuy Duong Dang & Fabian Hollstein & Marcel Prokopczuk & Zhiguo He, 2023. "Which Factors for Corporate Bond Returns?," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 13(4), pages 615-652.
    4. Simos Meintanis & Bojana Milošević & Marko Obradović & Mirjana Veljović, 2024. "Goodness‐of‐fit tests for the multivariate Student‐t distribution based on i.i.d. data, and for GARCH observations," Journal of Time Series Analysis, Wiley Blackwell, vol. 45(2), pages 298-319, March.
    5. Siddhartha Chib & Simon C. Smith, 2024. "Factor Selection and Structural Breaks," Finance and Economics Discussion Series 2024-037, Board of Governors of the Federal Reserve System (U.S.).
    6. Qiao, Zhuo & Wang, Yan & Lam, Keith S.K., 2022. "New evidence on Bayesian tests of global factor pricing models," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 160-172.
    7. Wang, Kai Y.K. & Chen, Cathy W.S. & So, Mike K.P., 2023. "Quantile three-factor model with heteroskedasticity, skewness, and leptokurtosis," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    8. Siddhartha Chib & Minchul Shin & Fei Tan, 2023. "DSGE-SVt: An Econometric Toolkit for High-Dimensional DSGE Models with SV and t Errors," Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 69-111, January.

  6. Siddhartha Chib & Xiaming Zeng & Lingxiao Zhao, 2020. "On Comparing Asset Pricing Models," Journal of Finance, American Finance Association, vol. 75(1), pages 551-577, February.

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    2. Li, Sicong & DeMiguel, Victor & Martín-Utrera, Alberto, 2024. "Comparing factor models with price-impact costs," Journal of Financial Economics, Elsevier, vol. 162(C).
    3. Wang, Jinzhe & Zhu, Yifeng, 2024. "A comparison of factor models in China," Journal of Empirical Finance, Elsevier, vol. 79(C).
    4. Svetlana Bryzgalova & Jiantao Huang & Christian Julliard, 2023. "Bayesian Solutions for the Factor Zoo: We Just Ran Two Quadrillion Models," Journal of Finance, American Finance Association, vol. 78(1), pages 487-557, February.
    5. Jonathan Fletcher, 2024. "AN examination of linear factor models in U.K. stock returns in the presence of dynamic trading," Review of Quantitative Finance and Accounting, Springer, vol. 63(3), pages 1121-1147, October.
    6. Thuy Duong Dang & Fabian Hollstein & Marcel Prokopczuk & Zhiguo He, 2023. "Which Factors for Corporate Bond Returns?," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 13(4), pages 615-652.
    7. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2022. "Cryptocurrency returns under empirical asset pricing," International Review of Financial Analysis, Elsevier, vol. 82(C).
    8. Siddhartha Chib & Simon C. Smith, 2024. "Factor Selection and Structural Breaks," Finance and Economics Discussion Series 2024-037, Board of Governors of the Federal Reserve System (U.S.).
    9. Massa, Massimo & O'Donovan, James & Zhang, Hong, 2022. "International asset pricing with strategic business groups1," Journal of Financial Economics, Elsevier, vol. 145(2), pages 339-361.
    10. Hansen, Erwin, 2022. "Economic evaluation of asset pricing models under predictability," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 50-66.
    11. Hanauer, Matthias X. & Jansen, Maarten & Swinkels, Laurens & Zhou, Weili, 2024. "Factor models for Chinese A-shares," International Review of Financial Analysis, Elsevier, vol. 91(C).
    12. Qiao, Zhuo & Wang, Yan & Lam, Keith S.K., 2022. "New evidence on Bayesian tests of global factor pricing models," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 160-172.
    13. Doron Avramov & Si Cheng & Lior Metzker & Stefan Voigt, 2023. "Integrating Factor Models," Journal of Finance, American Finance Association, vol. 78(3), pages 1593-1646, June.
    14. Hollstein, Fabian & Prokopczuk, Marcel, 2022. "Testing Factor Models in the Cross-Section," Journal of Banking & Finance, Elsevier, vol. 145(C).
    15. Smith, Simon C., 2021. "International stock return predictability," International Review of Financial Analysis, Elsevier, vol. 78(C).
    16. Smith, Simon C., 2022. "Time-variation, multiple testing, and the factor zoo," International Review of Financial Analysis, Elsevier, vol. 84(C).
    17. Yuxiao Jiao & Guofu Zhou & Wu Zhu & Yingzi Zhu, 2025. "Interpretable Factors of Firm Characteristics," Papers 2508.02253, arXiv.org.
    18. Wang, Kai Y.K. & Chen, Cathy W.S. & So, Mike K.P., 2023. "Quantile three-factor model with heteroskedasticity, skewness, and leptokurtosis," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    19. Engsted, Tom & Schneider, Jesper W., 2023. "Non-Experimental Data, Hypothesis Testing, and the Likelihood Principle: A Social Science Perspective," SocArXiv nztk8, Center for Open Science.
    20. Kan, Raymond & Wang, Xiaolu & Zheng, Xinghua, 2024. "In-sample and out-of-sample Sharpe ratios of multi-factor asset pricing models," Journal of Financial Economics, Elsevier, vol. 155(C).
    21. Amit K. Sinha, 2021. "The reliability of geometric Brownian motion forecasts of S&P500 index values," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1444-1462, December.
    22. Massa, Massimo & O'Donovan, James & Zhang, Hong, 2021. "International Asset Pricing with Strategic Business Groups," CEPR Discussion Papers 15746, C.E.P.R. Discussion Papers.

  7. Siddhartha Chib & Minchul Shin & Anna Simoni, 2018. "Bayesian Estimation and Comparison of Moment Condition Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(524), pages 1656-1668, October.
    See citations under working paper version above.
  8. Siddhartha Chib & Liana Jacobi, 2016. "Bayesian Fuzzy Regression Discontinuity Analysis and Returns to Compulsory Schooling," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(6), pages 1026-1047, September.

    Cited by:

    1. Jacek Liwiński, 2020. "The Impact of Compulsory Schooling on Hourly Wage: Evidence From the 1999 Education Reform in Poland," Evaluation Review, , vol. 44(5-6), pages 437-470, October.
    2. Liwiński, Jacek, 2018. "The Impact of Compulsory Schooling on Earnings. Evidence from the 1999 Education Reform in Poland," GLO Discussion Paper Series 253, Global Labor Organization (GLO).
    3. Kamila Cygan‐Rehm, 2022. "Are there no wage returns to compulsory schooling in Germany? A reassessment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 218-223, January.
    4. Ximing Wu, 2021. "Hierarchical Gaussian Process Models for Regression Discontinuity/Kink under Sharp and Fuzzy Designs," Papers 2110.00921, arXiv.org, revised Feb 2022.
    5. Stefani Milovanska-Farrington & Stephen Farrington, 2023. "Compulsory education and fertility: evidence from Poland’s education reform in 1956," International Economics and Economic Policy, Springer, vol. 20(1), pages 139-161, February.
    6. Gregory Clark & Christian Abildgaard Nielsen, 2024. "The Returns to Education: A Meta-study," Working Papers 0249, European Historical Economics Society (EHES).
    7. Matias D. Cattaneo & Luke Keele & Rocio Titiunik, 2021. "Covariate Adjustment in Regression Discontinuity Designs," Papers 2110.08410, arXiv.org, revised Aug 2022.
    8. Arendt, Jacob Nielsen & Christensen, Mads Lybech & Hjorth-Trolle, Anders, 2021. "Maternal education and child health: Causal evidence from Denmark," Journal of Health Economics, Elsevier, vol. 80(C).
    9. Liwiński, Jacek, 2018. "The Impact of Compulsory Education on Employment and Earnings in a Transition Economy," GLO Discussion Paper Series 193, Global Labor Organization (GLO).
    10. Adamecz-Völgyi, Anna, 2022. "Oktatási reformok hatása kérdőíves adatokon. Befolyásolják-e a reformok a részvételt, a lemorzsolódást és a válaszadást? [Education reforms as instrumental variables for education using survey data: effects on survey participation, attrition and n," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(11), pages 1298-1323.

  9. Siddhartha Chib & Srikanth Ramamurthy, 2014. "DSGE Models with Student- t Errors," Econometric Reviews, Taylor & Francis Journals, vol. 33(1-4), pages 152-171, June.

    Cited by:

    1. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
    2. Lin, Yi Chun, 2021. "Business cycle fluctuations in Taiwan — A Bayesian DSGE analysis," Journal of Macroeconomics, Elsevier, vol. 70(C).
    3. Dave, Chetan & Malik, Samreen, 2017. "A tale of fat tails," European Economic Review, Elsevier, vol. 100(C), pages 293-317.
    4. Lindé, Jesper & Smets, Frank & Wouters, Rafael, 2016. "Challenges for Central Banks´ Macro Models," Working Paper Series 323, Sveriges Riksbank (Central Bank of Sweden).
    5. Lianfeng Song & Hongxia Wang & Huanshui Zhang & Hongdan Li, 2023. "Rational Expectations Models with Multiplicative Noise," Journal of Optimization Theory and Applications, Springer, vol. 199(1), pages 233-257, October.
    6. Chiu, Ching-Wai (Jeremy) & Mumtaz, Haroon & Pintér, Gábor, 2017. "Forecasting with VAR models: Fat tails and stochastic volatility," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1124-1143.
    7. Marlène Isoré & Urszula Szczerbowicz, 2015. "Disaster Risk and Preference Shifts in a New Keynesian Model," Working Papers 2015-16, CEPII research center.
    8. Herwartz, Helmut & Lange, Alexander & Maxand, Simone, 2019. "Statistical identification in SVARs - Monte Carlo experiments and a comparative assessment of the role of economic uncertainties for the US business cycle," University of Göttingen Working Papers in Economics 375, University of Goettingen, Department of Economics.
    9. Ching-Wai (Jeremy) Chiu & Haroon Mumtaz & Gabor Pinter, 2016. "Bayesian Vector Autoregressions with Non-Gaussian Shocks," CReMFi Discussion Papers 5, CReMFi, School of Economics and Finance, QMUL.
    10. Willi Mutschler, 2015. "Higher-order statistics for DSGE models," CQE Working Papers 4315, Center for Quantitative Economics (CQE), University of Muenster.
    11. Bobeica, Elena & Hartwig, Benny, 2023. "The COVID-19 shock and challenges for inflation modelling," International Journal of Forecasting, Elsevier, vol. 39(1), pages 519-539.
    12. Sune Karlsson & Stepan Mazur & Hoang Nguyen, 2021. "Vector autoregression models with skewness and heavy tails," Papers 2105.11182, arXiv.org.
    13. Bobeica, Elena & Hartwig, Benny, 2021. "The COVID-19 shock and challenges for time series models," Working Paper Series 2558, European Central Bank.
    14. Markus K. Brunnermeier & Darius Palia & Karthik A. Sastry & Christopher A. Sims, 2019. "Feedbacks: Financial Markets and Economic Activity," Working Papers 257, Princeton University, Department of Economics, Center for Economic Policy Studies..
    15. Chen, Ji & Yang, Xinglin & Liu, Xiliang, 2022. "Learning, disagreement and inflation forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    16. Gong, Xiao-Li & Liu, Xi-Hua & Xiong, Xiong & Zhuang, Xin-Tian, 2019. "Non-Gaussian VARMA model with stochastic volatility and applications in stock market bubbles," Chaos, Solitons & Fractals, Elsevier, vol. 121(C), pages 129-136.
    17. Nelimarkka, Jaakko, 2017. "Evidence on News Shocks under Information Deficiency," MPRA Paper 80850, University Library of Munich, Germany.
    18. Puonti, Päivi, 2019. "Data-driven structural BVAR analysis of unconventional monetary policy," Journal of Macroeconomics, Elsevier, vol. 61(C), pages 1-1.
    19. Helmut Herwartz & Alexander Lange & Simone Maxand, 2022. "Data‐driven identification in SVARs—When and how can statistical characteristics be used to unravel causal relationships?," Economic Inquiry, Western Economic Association International, vol. 60(2), pages 668-693, April.
    20. Dalheimer, Bernhard & Herwartz, Helmut & Lange, Alexander, 2021. "The threat of oil market turmoils to food price stability in Sub-Saharan Africa," Energy Economics, Elsevier, vol. 93(C).
    21. Markku Lanne, 2013. "Noncausality and Inflation Persistence," Discussion Papers of DIW Berlin 1286, DIW Berlin, German Institute for Economic Research.
    22. Vasco Curdia & Marco Del Negro & Daniel L. Greenwald, 2012. "Rare shocks, great recessions," Staff Reports 585, Federal Reserve Bank of New York.
    23. Helmut Herwartz & Alexander Lange, 2024. "How certain are we about the role of uncertainty in the economy?," Economic Inquiry, Western Economic Association International, vol. 62(1), pages 126-149, January.
    24. Jonathan A. Attey & Casper G. de Vries, 2016. "Monetary Policy in the Presence of Random Wage Indexation," Tinbergen Institute Discussion Papers 16-086/VI, Tinbergen Institute.
    25. Dave, Chetan & Sorge, Marco M., 2020. "Sunspot-driven fat tails: A note," Economics Letters, Elsevier, vol. 193(C).
    26. Lindé, J. & Smets, F. & Wouters, R., 2016. "Challenges for Central Banks’ Macro Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 2185-2262, Elsevier.
    27. Liu, Xiaochun, 2019. "On tail fatness of macroeconomic dynamics," Journal of Macroeconomics, Elsevier, vol. 62(C).
    28. Mutschler, Willi, 2015. "Identification of DSGE models—The effect of higher-order approximation and pruning," Journal of Economic Dynamics and Control, Elsevier, vol. 56(C), pages 34-54.
    29. Michal Franta, 2015. "Rare Shocks vs. Non-linearities: What Drives Extreme Events in the Economy? Some Empirical Evidence," Working Papers 2015/04, Czech National Bank, Research and Statistics Department.
    30. Fidel Ernesto Castro Morales & Dimitris N. Politis & Jacek Leskow & Marina Silva Paez, 2022. "Student’s-t process with spatial deformation for spatio-temporal data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(5), pages 1099-1126, December.
    31. Siddhartha Chib & Minchul Shin & Fei Tan, 2023. "DSGE-SVt: An Econometric Toolkit for High-Dimensional DSGE Models with SV and t Errors," Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 69-111, January.
    32. Ching-Wai (Jeremy) Chiu & Haroon Mumtaz & Gabor Pinter, 2014. "Fat-tails in VAR Models," Working Papers 714, Queen Mary University of London, School of Economics and Finance.
    33. Fabian Goessling, 2019. "Exact Expectations: Efficient Calculation of DSGE Models," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 977-990, March.
    34. Dave, Chetan & Sorge, Marco M., 2021. "Equilibrium indeterminacy and sunspot tales," European Economic Review, Elsevier, vol. 140(C).
    35. Ferrentino, Rosa & Vota, Luca, 2024. "The development planning of the Italian Mezzogiorno: A statistical-mathematical analysis by a Real Business Cycle model," Socio-Economic Planning Sciences, Elsevier, vol. 96(C).
    36. Markku Lanne & Mika Meitz & Pentti Saikkonen, 2015. "Identification and estimation of non-Gaussian structural vector autoregressions," CREATES Research Papers 2015-16, Department of Economics and Business Economics, Aarhus University.
    37. Cross, Jamie & Poon, Aubrey, 2016. "Forecasting structural change and fat-tailed events in Australian macroeconomic variables," Economic Modelling, Elsevier, vol. 58(C), pages 34-51.
    38. Hartwig, Benny, 2022. "Bayesian VARs and prior calibration in times of COVID-19," Discussion Papers 52/2022, Deutsche Bundesbank.
    39. Xiao-Li Gong & Jin-Yan Lu & Xiong Xiong & Wei Zhang, 2022. "Higher-order dynamic effects of uncertainty risk under thick-tailed stochastic volatility," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-22, December.

  10. Siddhartha Chib & Kyu Ho Kang, 2013. "Change-Points in Affine Arbitrage-Free Term Structure Models," Journal of Financial Econometrics, Oxford University Press, vol. 11(2), pages 302-334, March.

    Cited by:

    1. Massimo Guidolin & Manuela Pedio, 2019. "Forecasting and Trading Monetary Policy Effects on the Riskless Yield Curve with Regime Switching Nelson†Siegel Models," Working Papers 639, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    2. Kim, Dongwhan & Kang, Kyu Ho, 2021. "Conditional value-at-risk forecasts of an optimal foreign currency portfolio," International Journal of Forecasting, Elsevier, vol. 37(2), pages 838-861.
    3. Malik, Sheheryar & Meldrum, Andrew, 2016. "Evaluating the robustness of UK term structure decompositions using linear regression methods," Journal of Banking & Finance, Elsevier, vol. 67(C), pages 85-102.
    4. Young Min Kim & Seojin Lee, 2017. "The Role of Unobservable Fundamentals in Korea Exchange Rate Fluctuations: Bayesian Approach," Economic Analysis (Quarterly), Economic Research Institute, Bank of Korea, vol. 23(3), pages 1-22, September.
    5. Azamat Abdymomunov & Kyu Ho Kang & Ki Jeong Kim, 2014. "Forecasting the Term Structure of Government Bond Yields Using Credit Spreads and Structural Breaks," Working Papers 2014-19, Economic Research Institute, Bank of Korea.
    6. Kim, Young Min & Kang, Kyu Ho & Ka, Kook, 2020. "Do bond markets find inflation targets credible? Evidence from five inflation-targeting countries," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 66-84.
    7. Eo, Yunjong & Kang, Kyu Ho, 2020. "The effects of conventional and unconventional monetary policy on forecasting the yield curve," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    8. Massimo Guidolin & Manuela Pedio, 2019. "Forecasting and Trading Monetary Policy Switching Nelson-Siegel Models," BAFFI CAREFIN Working Papers 19106, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    9. 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.
    10. Abdymomunov, Azamat & Kang, Kyu Ho & Kim, Ki Jeong, 2016. "Can credit spreads help predict a yield curve?," Journal of International Money and Finance, Elsevier, vol. 64(C), pages 39-61.
    11. Boot, Tom & Pick, Andreas, 2020. "Does modeling a structural break improve forecast accuracy?," Journal of Econometrics, Elsevier, vol. 215(1), pages 35-59.

  11. Chib, Siddhartha & Ramamurthy, Srikanth, 2010. "Tailored randomized block MCMC methods with application to DSGE models," Journal of Econometrics, Elsevier, vol. 155(1), pages 19-38, March.

    Cited by:

    1. Masuhr Andreas & Trede Mark, 2020. "Bayesian estimation of generalized partition of unity copulas," Dependence Modeling, De Gruyter, vol. 8(1), pages 119-131, January.
    2. Siddhartha Chib & Minchul Shin & Anna Simoni, 2021. "Bayesian Estimation and Comparison of Conditional Moment Models," Papers 2110.13531, arXiv.org.
    3. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.
    4. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    5. Rey, Clément & Rey, Serge & Viala, Jean-Renaud, 2014. "Detection of high and low states in stock market returns with MCMC method in a Markov switching model," Economic Modelling, Elsevier, vol. 41(C), pages 145-155.
    6. Li, Bing & Pei, Pei & Tan, Fei, 2021. "Financial distress and fiscal inflation," Journal of Macroeconomics, Elsevier, vol. 70(C).
    7. Edward P. Herbst & Frank Schorfheide, 2012. "Sequential Monte Carlo sampling for DSGE models," Working Papers 12-27, Federal Reserve Bank of Philadelphia.
    8. Lin, Yi Chun, 2021. "Business cycle fluctuations in Taiwan — A Bayesian DSGE analysis," Journal of Macroeconomics, Elsevier, vol. 70(C).
    9. Wichitaksorn, Nuttanan & Tsurumi, Hiroki, 2013. "Comparison of MCMC algorithms for the estimation of Tobit model with non-normal error: The case of asymmetric Laplace distribution," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 226-235.
    10. Chang, Yoosoon & Maih, Junior & Tan, Fei, 2021. "Origins of monetary policy shifts: A New approach to regime switching in DSGE models," Journal of Economic Dynamics and Control, Elsevier, vol. 133(C).
    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. Andreas Masuhr, 2019. "Big in Japan: Global Volatility Transmission between Assets and Trading Places," CQE Working Papers 8119, Center for Quantitative Economics (CQE), University of Muenster.
    13. 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.
    14. 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.
    15. Michael T. Belongia & Peter N. Ireland, 2019. "A Reconsideration of Money Growth Rules," Boston College Working Papers in Economics 976, Boston College Department of Economics.
    16. Ettmeier, Stephanie & Kriwoluzky, Alexander, 2019. "Active, or passive? Revisiting the role of fiscal policy in the Great Inflation," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203609, Verein für Socialpolitik / German Economic Association.
    17. Burda Martin & Maheu John M., 2013. "Bayesian adaptively updated Hamiltonian Monte Carlo with an application to high-dimensional BEKK GARCH models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(4), pages 345-372, September.
    18. Mariano Kulish & James Morley & Tim Robinson, 2016. "Estimating DSGE models with Zero Interest Rate Policy," Discussion Papers 2014-32B, School of Economics, The University of New South Wales.
    19. Stéphane Adjemian & Houtan Bastani & Michel Juillard & Frédéric Karamé & Ferhat Mihoubi & Willi Mutschler & Johannes Pfeifer & Marco Ratto & Sébastien Villemot & Normann Rion, 2023. "Dynare: Reference Manual Version 5," PSE Working Papers hal-04219920, HAL.
      • Stéphane Adjemian & Houtan Bastani & Michel Juillard & Frédéric Karamé & Ferhat Mihoubi & Willi Mutschler & Johannes Pfeifer & Marco Ratto & Sébastien Villemot & Normann Rion, 2023. "Dynare: Reference Manual Version 5," Working Papers hal-04219920, HAL.
      • Adjemian, Stéphane & Bastani, Houtan & Juillard, Michel & Karamé, Fréderic & Mihoubi, Ferhat & Mutschler, Willi & Pfeifer, Johannes & Ratto, Marco & Rion, Normann & Villemot, Sébastien, 2022. "Dynare: Reference Manual Version 5," Dynare Working Papers 72, CEPREMAP, revised Mar 2023.
    20. Stelios D. Bekiros & Alessia Paccagnini, 2014. "Bayesian forecasting with small and medium scale factor-augmented vector autoregressive DSGE models," Open Access publications 10197/7322, School of Economics, University College Dublin.
    21. Mariano Kulish & James Morley & Tim Robinson, 2014. "Estimating the Expected Duration of the Zero Lower Bound in DSGE Models with Forward Guidance," Melbourne Institute Working Paper Series wp2014n16, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    22. Chih‐Sheng Hsieh & Lung‐Fei Lee & Vincent Boucher, 2020. "Specification and estimation of network formation and network interaction models with the exponential probability distribution," Quantitative Economics, Econometric Society, vol. 11(4), pages 1349-1390, November.
    23. Vasco Curdia & Ricardo Reis, 2010. "Correlated disturbances and U.S. business cycles," Staff Reports 434, Federal Reserve Bank of New York.
    24. Stephanie Ettmeier & Alexander Kriwoluzky, 2020. "Active, or Passive? Revisiting the Role of Fiscal Policy in the Great Inflation," Discussion Papers of DIW Berlin 1872, DIW Berlin, German Institute for Economic Research.
    25. Kazuhiko Kakamu & Haruhisa Nishino, 2019. "Bayesian Estimation of Beta-type Distribution Parameters Based on Grouped Data," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 625-645, August.
    26. Panovska, Irina & Ramamurthy, Srikanth, 2022. "Decomposing the output gap with inflation learning," Journal of Economic Dynamics and Control, Elsevier, vol. 136(C).
    27. DUFAYS, Arnaud, 2012. "Infinite-state Markov-switching for dynamic volatility and correlation models," LIDAM Discussion Papers CORE 2012043, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    28. Adjemian, Stéphane & Juillard, Michel & Karamé, Fréderic & Mutschler, Willi & Pfeifer, Johannes & Ratto, Marco & Rion, Normann & Villemot, Sébastien, 2024. "Dynare: Reference Manual, Version 6," Dynare Working Papers 80, CEPREMAP, revised Nov 2025.
    29. Iiboshi, Hirokuni & Shintani, Mototsugu, 2016. "Zero interest rate policy and asymmetric price adjustment in Japan: an empirical analysis of a nonlinear DSGE model," MPRA Paper 93868, University Library of Munich, Germany.
    30. Girstmair, Stefan, 2024. "The effect of new housing supply in structural models: a forecasting performance evaluation," Working Paper Series 2895, European Central Bank.
    31. Siddhartha Chib & Srikanth Ramamurthy, 2014. "DSGE Models with Student- t Errors," Econometric Reviews, Taylor & Francis Journals, vol. 33(1-4), pages 152-171, June.
    32. Kim, Dongwhan & Kang, Kyu Ho, 2021. "Conditional value-at-risk forecasts of an optimal foreign currency portfolio," International Journal of Forecasting, Elsevier, vol. 37(2), pages 838-861.
    33. Born, Benjamin & Peifer, Johannes, 2011. "Policy Risk and the Business Cycle," Bonn Econ Discussion Papers 06/2011, University of Bonn, Bonn Graduate School of Economics (BGSE).
    34. Siddhartha Chib & Minchul Shin & Fei Tan, 2020. "High-Dimensional DSGE Models: Pointers on Prior, Estimation, Comparison, and Prediction∗," Working Papers 20-35, Federal Reserve Bank of Philadelphia.
    35. Jim Malley & Ulrich Woitek, 2011. "Productivity Shocks and Aggregate Fluctuations in an Estimated Endogenous Growth Model with Human Capital," CESifo Working Paper Series 3567, CESifo.
    36. Mark Bognanni & Edward P. Herbst, 2014. "Estimating (Markov-Switching) VAR Models without Gibbs Sampling: A Sequential Monte Carlo Approach," Working Papers (Old Series) 1427, Federal Reserve Bank of Cleveland.
    37. Johannes Huber, 2022. "An Augmented Steady-State Kalman Filter to Evaluate the Likelihood of Linear and Time-Invariant State-Space Models," Discussion Paper Series 343, Universitaet Augsburg, Institute for Economics.
    38. Xin Luo & Håkon Tjelmeland, 2019. "A multiple-try Metropolis–Hastings algorithm with tailored proposals," Computational Statistics, Springer, vol. 34(3), pages 1109-1133, September.
    39. Young Min Kim & Seojin Lee, 2017. "The Role of Unobservable Fundamentals in Korea Exchange Rate Fluctuations: Bayesian Approach," Economic Analysis (Quarterly), Economic Research Institute, Bank of Korea, vol. 23(3), pages 1-22, September.
    40. Böhl, Gregor, 2022. "Ensemble MCMC sampling for robust Bayesian inference," IMFS Working Paper Series 177, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    41. Peter Rosenkranz & Tobias Straumann & Ulrich Woitek, 2022. "The limits of internal devaluation: Switzerland during the great depression," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 158(1), pages 1-17, December.
    42. Masuhr Andreas & Trede Mark, 2023. "Mutual volatility transmission between assets and trading places," Dependence Modeling, De Gruyter, vol. 11(1), pages 1-15.
    43. Kazuhiko Kakamu & Haruhisa Nishino, 2016. "Bayesian Estimation Of Beta-Type Distribution Parameters Based On Grouped Data," Discussion Papers 2016-08, Kobe University, Graduate School of Business Administration.
    44. Kapetanios, George & Masolo, Riccardo M. & Petrova, Katerina & Waldron, Matthew, 2019. "A time-varying parameter structural model of the UK economy," Journal of Economic Dynamics and Control, Elsevier, vol. 106(C), pages 1-1.
    45. Daniel O. Beltran & David Draper, 2016. "Estimating Dynamic Macroeconomic Models : How Informative Are the Data?," International Finance Discussion Papers 1175, Board of Governors of the Federal Reserve System (U.S.).
    46. Chetan Dave & Marco Sorge, 2023. "Fat Tailed DSGE Models: A Survey and New Results," Working Papers 2023-03, University of Alberta, Department of Economics.
    47. Bauwens, Luc & De Backer, Bruno & Dufays, Arnaud, 2014. "A Bayesian method of change-point estimation with recurrent regimes: Application to GARCH models," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 207-229.
    48. Jean-François Carpantier, 2014. "Specific Markov-switching behaviour for ARMA parameters," DEM Discussion Paper Series 14-07, Department of Economics at the University of Luxembourg.
    49. Mariano Kulish & James Morley & Tim Robinson, 2014. "Estimating DSGE models with forward guidance," Discussion Papers 2014-32A, School of Economics, The University of New South Wales.
    50. 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.
    51. Dube, Arindrajit & Lester, T. William & Reich, Michael, 2011. "Do Frictions Matter in the Labor Market? Accessions, Separations and Minimum Wage Effects," IZA Discussion Papers 5811, IZA Network @ LISER.
    52. Zheng, Tingguo & Guo, Huiming, 2013. "Estimating a small open economy DSGE model with indeterminacy: Evidence from China," Economic Modelling, Elsevier, vol. 31(C), pages 642-652.
    53. Rachael McCririck & Daniel Rees, 2016. "The Slowdown in US Productivity Growth: Breaks and Beliefs," RBA Research Discussion Papers rdp2016-08, Reserve Bank of Australia.
    54. Born, Benjamin & Peter, Alexandra & Pfeifer, Johannes, 2013. "Fiscal news and macroeconomic volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2582-2601.
    55. Corbo, Vesna & Strid, Ingvar, 2020. "MAJA: A two-region DSGE model for Sweden and its main trading partners," Working Paper Series 391, Sveriges Riksbank (Central Bank of Sweden).
    56. Edward P. Herbst, 2012. "Using the \"Chandrasekhar Recursions\" for likelihood evaluation of DSGE models," Finance and Economics Discussion Series 2012-35, Board of Governors of the Federal Reserve System (U.S.).
    57. Brownstone, David & Li, Phillip, 2018. "A model for broad choice data," Journal of choice modelling, Elsevier, vol. 27(C), pages 19-36.
    58. Siddharta Chib & Minchul Shin & Anna Simoni, 2016. "Bayesian Empirical Likelihood Estimation and Comparison of Moment Condition Models," Working Papers 2016-21, Center for Research in Economics and Statistics.
    59. Markku Lanne & Jani Luoto, 2015. "Estimation of DSGE Models under Diffuse Priors and Data-Driven Identification Constraints," CREATES Research Papers 2015-37, Department of Economics and Business Economics, Aarhus University.
    60. Markku Lanne & Jani Luoto, 2014. "Noncausal Bayesian Vector Autoregression," CREATES Research Papers 2014-07, Department of Economics and Business Economics, Aarhus University.
    61. Peter Rosenkranz & Tobias Straumann & Ulrich Woitek, 2014. "A small open economy in the Great Depression: the case of Switzerland," ECON - Working Papers 164, Department of Economics - University of Zurich.
    62. Markku Lanne & Jani Luoto, 2018. "Data†Driven Identification Constraints for DSGE Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(2), pages 236-258, April.
    63. Dufays, A. & Rombouts, V., 2015. "Sparse Change-Point Time Series Models," LIDAM Discussion Papers CORE 2015032, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    64. Ming Lin & Eric A. Suess & Robert H. Shumway & Rong Chen, 2016. "Bayesian Deconvolution of Signals Observed on Arrays," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(6), pages 837-850, November.
    65. Li, Bing & Pei, Pei & Tan, Fei, 2018. "Credit Risk and Fiscal Inflation," MPRA Paper 90486, University Library of Munich, Germany.
    66. Siddhartha Chib & Minchul Shin & Fei Tan, 2023. "DSGE-SVt: An Econometric Toolkit for High-Dimensional DSGE Models with SV and t Errors," Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 69-111, January.
    67. Joshua Brault, 2024. "Parallel Tempering for DSGE Estimation," Staff Working Papers 24-13, Bank of Canada.
    68. Andreas Masuhr, 2018. "Bayesian Estimation of Generalized Partition of Unity Copulas," CQE Working Papers 7318, Center for Quantitative Economics (CQE), University of Muenster.
    69. Morris, Stephen D., 2017. "DSGE pileups," Journal of Economic Dynamics and Control, Elsevier, vol. 74(C), pages 56-86.
    70. Donggyu Lee, 2024. "Unconventional Monetary Policies and Inequality," Staff Reports 1108, Federal Reserve Bank of New York.
    71. Abdymomunov Azamat & Kang Kyu Ho, 2015. "The effects of monetary policy regime shifts on the term structure of interest rates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(2), pages 183-207, April.
    72. Stefano Grassi & Marco Lorusso & Francesco Ravazzolo, 2021. "Adaptive Importance Sampling for DSGE Models," BEMPS - Bozen Economics & Management Paper Series BEMPS84, Faculty of Economics and Management at the Free University of Bozen.
    73. Martin Burda & John Maheu, 2011. "Bayesian Adaptive Hamiltonian Monte Carlo with an Application to High-Dimensional BEKK GARCH Models," Working Papers tecipa-438, University of Toronto, Department of Economics.
    74. Jim Malley & Ulrich Woitek, 2019. "Estimated Human Capital Externalities in an Endogenous Growth Framework," Working Papers 2019_04, Business School - Economics, University of Glasgow.
    75. Stephanie Ettmeier & Alexander Kriwoluzky, 2024. "Active or Passive? Revisiting the Role of Fiscal Policy During High Inflation," CRC TR 224 Discussion Paper Series crctr224_2024_565, University of Bonn and University of Mannheim, Germany.
    76. Xiao-Li Gong & Jin-Yan Lu & Xiong Xiong & Wei Zhang, 2022. "Higher-order dynamic effects of uncertainty risk under thick-tailed stochastic volatility," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-22, December.

  12. 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.

    Cited by:

    1. Christos Merkatas & Simo Särkkä, 2023. "System identification using autoregressive Bayesian neural networks with nonparametric noise models," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(3), pages 319-330, May.
    2. Siddhartha Chib & Minchul Shin & Anna Simoni, 2021. "Bayesian Estimation and Comparison of Conditional Moment Models," Papers 2110.13531, arXiv.org.
    3. Mark J. Jensen & John M. Maheu, 2014. "Risk, Return and Volatility Feedback: A Bayesian Nonparametric Analysis," Working Paper series 31_14, Rimini Centre for Economic Analysis.
    4. Xin Jin & John M. Maheu, 2014. "Bayesian Semiparametric Modeling of Realized Covariance Matrices," Working Paper series 34_14, Rimini Centre for Economic Analysis.
    5. Pelenis, Justinas, 2014. "Bayesian regression with heteroscedastic error density and parametric mean function," Journal of Econometrics, Elsevier, vol. 178(P3), pages 624-638.
    6. Debdeep Pati & David Dunson, 2014. "Bayesian nonparametric regression with varying residual density," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(1), pages 1-31, February.
    7. Manuel Wiesenfarth & Carlos Matías Hisgen & Thomas Kneib & Carmen Cadarso-Suarez, 2014. "Bayesian Nonparametric Instrumental Variables Regression Based on Penalized Splines and Dirichlet Process Mixtures," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(3), pages 468-482, July.
    8. Siddhartha Chib & Minchul Shin & Anna Simoni, 2024. "Testing for Endogeneity: A Moment-Based Bayesian Approach," Working Papers 24-19, Federal Reserve Bank of Philadelphia.
    9. Huaiye Zhang & Inyoung Kim & Chun Gun Park, 2014. "Semiparametric Bayesian hierarchical models for heterogeneous population in nonlinear mixed effect model: application to gastric emptying studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(12), pages 2743-2760, December.
    10. Sun, Peng & Kim, Inyoung & Lee, Ki-Ahm, 2018. "Dual-semiparametric regression using weighted Dirichlet process mixture," Computational Statistics & Data Analysis, Elsevier, vol. 117(C), pages 162-181.
    11. 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.
    12. Eoghan O'Neill, 2022. "Type I Tobit Bayesian Additive Regression Trees for Censored Outcome Regression," Papers 2211.07506, arXiv.org, revised Feb 2024.
    13. Didier Nibbering & Coos van Buuren & Wei Wei, 2021. "Real Options Valuation of Wind Energy Based on the Empirical Production Uncertainty," Monash Econometrics and Business Statistics Working Papers 19/21, Monash University, Department of Econometrics and Business Statistics.

  13. Chib, Siddhartha & Ergashev, Bakhodir, 2009. "Analysis of Multifactor Affine Yield Curve Models," Journal of the American Statistical Association, American Statistical Association, vol. 104(488), pages 1324-1337.

    Cited by:

    1. Zhang, Guoxiong, 2012. "Bayesian estimation of exchange rate regime choice with spatial effect," Economics Letters, Elsevier, vol. 117(3), pages 604-607.
    2. Michael D. Bauer & Glenn D. Rudebusch, 2014. "The Signaling Channel for Federal Reserve Bond Purchases," International Journal of Central Banking, International Journal of Central Banking, vol. 10(3), pages 233-289, September.
    3. Dubiel-Teleszynski, Tomasz & Kalogeropoulos, Konstantinos & Karouzakis, Nikolaos, 2024. "Sequential learning and economic benefits from dynamic term structure models," LSE Research Online Documents on Economics 123659, London School of Economics and Political Science, LSE Library.
    4. Hlouskova, Jaroslava & Sögner, Leopold, 2015. "GMM Estimation of Affine Term Structure Models," Economics Series 315, Institute for Advanced Studies.
    5. Mirkov, Nikola, 2012. "International Financial Transmission of the US Monetary Policy: An Empirical Assessment," Working Papers on Finance 1201, University of St. Gallen, School of Finance.
    6. Loria, Francesca & Matthes, Christian & Wang, Mu-Chun, 2022. "Economic theories and macroeconomic reality," Journal of Monetary Economics, Elsevier, vol. 126(C), pages 105-117.
    7. Hong, Zhiwu & Niu, Linlin & Zhang, Chen, 2022. "Affine arbitrage-free yield net models with application to the euro debt crisis," Journal of Econometrics, Elsevier, vol. 230(1), pages 201-220.
    8. Iryna Kaminska & Dimitri Vayanos & Gabriele Zinna, 2011. "Preferred-habitat investors and the US term structure of real rates," Bank of England working papers 435, Bank of England.
    9. Michael D. Bauer, 2015. "Restrictions on Risk Prices in Dynamic Term Structure Models," CESifo Working Paper Series 5241, CESifo.
    10. Michael D. Bauer & Glenn D. Rudebusch, 2020. "Interest Rates under Falling Stars," American Economic Review, American Economic Association, vol. 110(5), pages 1316-1354, May.
    11. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "No-Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," Working Papers 20-27, Federal Reserve Bank of Cleveland.
    12. Siddhartha Chib & Srikanth Ramamurthy, 2014. "DSGE Models with Student- t Errors," Econometric Reviews, Taylor & Francis Journals, vol. 33(1-4), pages 152-171, June.
    13. Siddhartha Chib & Minchul Shin & Fei Tan, 2020. "High-Dimensional DSGE Models: Pointers on Prior, Estimation, Comparison, and Prediction∗," Working Papers 20-35, Federal Reserve Bank of Philadelphia.
    14. Dewachter, Hans & Iania, Leonardo, 2009. "An Extended Macro-Finance Model with Financial Factors," MPRA Paper 18840, University Library of Munich, Germany.
    15. Zongwu Cai & Jiazi Chen & Linlin Niu, 2021. "A Semiparametric Model for Bond Pricing with Life Cycle Fundamental," Working Papers 2021-01-06, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    16. Young Min Kim & Seojin Lee, 2017. "The Role of Unobservable Fundamentals in Korea Exchange Rate Fluctuations: Bayesian Approach," Economic Analysis (Quarterly), Economic Research Institute, Bank of Korea, vol. 23(3), pages 1-22, September.
    17. Abdymomunov, Azamat & Gerlach, Jeffrey, 2014. "Stress testing interest rate risk exposure," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 287-301.
    18. Carlos Lenz, 2010. "Discussion: Reaction of Swiss Term Premia to Monetary Policy Surprises," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 146(I), pages 405-408, March.
    19. Dewachter, Hans & Iania, Leonardo & Lyrio, Marco, 2011. "Information in the Yield Curve: A Macro-Finance Approach," Insper Working Papers wpe_230, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    20. Zongwu Cai & Jiazi Chen & Linlin Liu, 2021. "Estimating Impact of Age Distribution on Bond Pricing: A Semiparametric Functional Data Analysis Approach," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202102, University of Kansas, Department of Economics, revised Jan 2021.
    21. Azamat Abdymomunov & Kyu Ho Kang & Ki Jeong Kim, 2014. "Forecasting the Term Structure of Government Bond Yields Using Credit Spreads and Structural Breaks," Working Papers 2014-19, Economic Research Institute, Bank of Korea.
    22. Kim, Young Min & Kang, Kyu Ho & Ka, Kook, 2020. "Do bond markets find inflation targets credible? Evidence from five inflation-targeting countries," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 66-84.
    23. Eo, Yunjong & Kang, Kyu Ho, 2020. "The effects of conventional and unconventional monetary policy on forecasting the yield curve," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    24. Iryna Kaminska & Gabriele Zinna, 2014. "Official Demand for U.S. Debt: Implications for U.S. Real Interest Rates," IMF Working Papers 2014/066, International Monetary Fund.
    25. Tsuyoshi Kunihama & Yasuhiro Omori & Zhengjun Zhang, 2011. "Efficient estimation and particle filter for max-stable processes," CIRJE F-Series CIRJE-F-791, CIRJE, Faculty of Economics, University of Tokyo.
    26. Januj Amar Juneja, 2022. "A Computational Analysis of the Tradeoff in the Estimation of Different State Space Specifications of Continuous Time Affine Term Structure Models," Computational Economics, Springer;Society for Computational Economics, vol. 60(1), pages 173-220, June.
    27. Ming Lin & Eric A. Suess & Robert H. Shumway & Rong Chen, 2016. "Bayesian Deconvolution of Signals Observed on Arrays," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(6), pages 837-850, November.
    28. Caldeira, João F. & Laurini, Márcio P. & Portugal, Marcelo S., 2010. "Bayesian Inference Applied to Dynamic Nelson-Siegel Model with Stochastic Volatility," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 30(1), October.
    29. Siddhartha Chib & Minchul Shin & Fei Tan, 2023. "DSGE-SVt: An Econometric Toolkit for High-Dimensional DSGE Models with SV and t Errors," Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 69-111, January.
    30. Martin Andreasen & Andrew Meldrum, 2013. "Likelihood inference in non-linear term structure models: the importance of the lower bound," Bank of England working papers 481, Bank of England.
    31. Taeyoung Doh, 2008. "Long run risks in the term structure of interest rates: estimation," Research Working Paper RWP 08-11, Federal Reserve Bank of Kansas City.
    32. Abdymomunov Azamat & Kang Kyu Ho, 2015. "The effects of monetary policy regime shifts on the term structure of interest rates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(2), pages 183-207, April.
    33. Andrew Meldrum & Matt Roberts-Sklar, 2015. "Long-run priors for term structure models," Bank of England working papers 575, Bank of England.
    34. Yuta Kurose & Yasuhiro Omori & Akira Hibiki, 2014. "A Discrete/Continuous Choice Model on a Nonconvex Budget Set," CIRJE F-Series CIRJE-F-942, CIRJE, Faculty of Economics, University of Tokyo.
    35. Gabriele Zinna, 2014. "Price pressures in the UK index-linked market: an empirical investigation," Temi di discussione (Economic working papers) 968, Bank of Italy, Economic Research and International Relations Area.
    36. Dorota Toczydlowska & Gareth W. Peters, 2018. "Financial Big Data Solutions for State Space Panel Regression in Interest Rate Dynamics," Econometrics, MDPI, vol. 6(3), pages 1-45, July.
    37. Lam, Clifford & Yao, Qiwei, 2012. "Factor modeling for high-dimensional time series: inference for the number of factors," LSE Research Online Documents on Economics 45684, London School of Economics and Political Science, LSE Library.

  14. Baranchuk, Nina & Chib, Siddhartha, 2008. "Assessing the role of option grants to CEOs: How important is heterogeneity?," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 145-166, March.

    Cited by:

    1. Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2023. "Forecasting with a panel Tobit model," Quantitative Economics, Econometric Society, vol. 14(1), pages 117-159, January.
    2. Yacine Belghitar & Ephraim A. Clark, 2012. "The Effect of CEO Risk Appetite on Firm Volatility: An Empirical Analysis of Financial Firms☆," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 19(2), pages 195-211, July.
    3. Voulgaris, Georgios & Stathopoulos, Konstantinos & Walker, Martin, 2014. "IFRS and the Use of Accounting-Based Performance Measures in Executive Pay," The International Journal of Accounting, Elsevier, vol. 49(4), pages 479-514.
    4. F. Louzada & P. H. Ferreira, 2016. "Modified inference function for margins for the bivariate clayton copula-based SUN Tobit Model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(16), pages 2956-2976, December.

  15. Chib, Siddhartha & Jacobi, Liana, 2008. "Analysis of treatment response data from eligibility designs," Journal of Econometrics, Elsevier, vol. 144(2), pages 465-478, June.

    Cited by:

    1. Liana Jacobi & Helga Wagner & Sylvia Frühwirth-Schnatter, 2014. "Bayesian Treatment Effects Models with Variable Selection for Panel Outcomes with an Application to Earnings Effects of Maternity Leave," NRN working papers 2014-12, The Austrian Center for Labor Economics and the Analysis of the Welfare State, Johannes Kepler University Linz, Austria.
    2. Martijn van Hasselt & Timothy Ferland & Jeremy Bray & Arnie Aldridge, 2017. "Bayesian Estimation of the Complier Average Casual Effect," UNCG Economics Working Papers 17-14, University of North Carolina at Greensboro, Department of Economics.
    3. Jacobi, Liana & Wagner, Helga & Frühwirth-Schnatter, Sylvia, 2016. "Bayesian treatment effects models with variable selection for panel outcomes with an application to earnings effects of maternity leave," Journal of Econometrics, Elsevier, vol. 193(1), pages 234-250.

  16. Chib, Siddhartha, 2007. "Analysis of treatment response data without the joint distribution of potential outcomes," Journal of Econometrics, Elsevier, vol. 140(2), pages 401-412, October.

    Cited by:

    1. Becher, Michael & Stegmueller, Daniel, 2019. "Cognitive Ability, Union Membership, and Voter Turnout," IAST Working Papers 19-97, Institute for Advanced Study in Toulouse (IAST).
    2. W. Blake Marsh & Padma Sharma, 2021. "Government Loan Guarantees during a Crisis: The Effect of the PPP on Bank Lending and Profitability," Research Working Paper RWP 21-03, Federal Reserve Bank of Kansas City.
    3. Angela Vossmeyer, 2014. "Treatment Effects and Informative Missingness with an Application to Bank Recapitalization Programs," American Economic Review, American Economic Association, vol. 104(5), pages 212-217, May.
    4. Hosoe, Nobuhiro & Takagi, Shingo, 2012. "Retail power market competition with endogenous entry decision—An auction data analysis," Journal of the Japanese and International Economies, Elsevier, vol. 26(3), pages 351-368.
    5. Li, Mingliang & Tobias, Justin L., 2011. "Bayesian inference in a correlated random coefficients model: Modeling causal effect heterogeneity with an application to heterogeneous returns to schooling," Journal of Econometrics, Elsevier, vol. 162(2), pages 345-361, June.
    6. Omori, Yasuhiro, 2007. "Efficient Gibbs sampler for Bayesian analysis of a sample selection model," Statistics & Probability Letters, Elsevier, vol. 77(12), pages 1300-1311, July.
    7. Watanabe, Hajime & Maruyama, Takuya, 2024. "A Bayesian sample selection model with a binary outcome for handling residential self-selection in individual car ownership," Journal of choice modelling, Elsevier, vol. 51(C).
    8. Vijay Ganesh Hariharan & Ram Bezawada & Debabrata Talukdar, 2015. "Aggregate Impact of Different Brand Development Strategies," Management Science, INFORMS, vol. 61(5), pages 1164-1182, May.
    9. Ishdorj, Ariun & Crepinsek, Mary Kay & Jensen, Helen H., "undated". "Children’s Consumption of Fruits and Vegetables: Do School Environment and Policies Affect Choice in School Meals?," 2012 AAEA/EAAE Food Environment Symposium 123534, Agricultural and Applied Economics Association.
    10. Ryo Kato & Takahiro Hoshino, 2018. "Semiparametric Bayes Instrumental Variable Estimation with Many Weak Instruments," Discussion Paper Series DP2018-14, Research Institute for Economics & Business Administration, Kobe University.
    11. Angela Vossmeyer, 2019. "Analysis of Stigma and Bank Credit Provision," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(1), pages 163-194, February.
    12. Ishdorj, Ariun & Crepinsek, Mary Kay & Jensen, Helen H., 2013. "Children's Consumption of Fruits and Vegetables: Do School Environment and Policies Affect Choice At School and Away from School?," Staff General Research Papers Archive 36020, Iowa State University, Department of Economics.
    13. Horvath, Akos & Lang, Peter, 2021. "Do loan subsidies boost the real activity of small firms?," Journal of Banking & Finance, Elsevier, vol. 122(C).
    14. Liana Jacobi & Helga Wagner & Sylvia Frühwirth-Schnatter, 2014. "Bayesian Treatment Effects Models with Variable Selection for Panel Outcomes with an Application to Earnings Effects of Maternity Leave," NRN working papers 2014-12, The Austrian Center for Labor Economics and the Analysis of the Welfare State, Johannes Kepler University Linz, Austria.
    15. Martijn van Hasselt & Timothy Ferland & Jeremy Bray & Arnie Aldridge, 2017. "Bayesian Estimation of the Complier Average Casual Effect," UNCG Economics Working Papers 17-14, University of North Carolina at Greensboro, Department of Economics.
    16. Ryo Kato & Takahiro Hoshino, 2020. "Semiparametric Bayesian multiple imputation for regression models with missing mixed continuous–discrete covariates," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(3), pages 803-825, June.
    17. Gilenko, Evgenii & Chernova, Aleksandra, 2021. "Saving behavior and financial literacy of Russian high school students: An application of a copula-based bivariate probit-regression approach," Children and Youth Services Review, Elsevier, vol. 127(C).
    18. Boyuan Zhang, 2022. "Incorporating Prior Knowledge of Latent Group Structure in Panel Data Models," Papers 2211.16714, arXiv.org, revised Oct 2023.
    19. Bretteville-Jensen, Anne Line & Jacobi, Liana, 2008. "Climbing the Drug Staircase: A Bayesian Analysis of the Initiation of Hard Drug Use," IZA Discussion Papers 3879, IZA Network @ LISER.
    20. Kris J. Mitchener & Angela Vossmeyer & Kris James Mitchener, 2023. "How Do Financial Crises Redistribute Risk?," CESifo Working Paper Series 10597, CESifo.
    21. Ishdorj, Ariun & Jensen, Helen H. & Crepinsek, Mary Kay, 2012. "Children’s Consumption of Fruits and Vegetables: Do School Environment and Policies Affect Choice At School and Away from School?," Hebrew University of Jerusalem Archive 133051, Hebrew University of Jerusalem.
    22. Ryo Kato & Takahiro Hoshino, 2018. "Semiparametric Bayes Multiple Imputation for Regression Models with Missing Mixed Continuous-Discrete Covariates," Discussion Paper Series DP2018-15, Research Institute for Economics & Business Administration, Kobe University.
    23. Li, Phillip, 2011. "Estimation of sample selection models with two selection mechanisms," Computational Statistics & Data Analysis, Elsevier, vol. 55(2), pages 1099-1108, February.
    24. Chib, Siddhartha & Jacobi, Liana, 2011. "Returns to Compulsory Schooling in Britain: Evidence from a Bayesian Fuzzy Regression Discontinuity Analysis," IZA Discussion Papers 5564, IZA Network @ LISER.
    25. Murat K. Munkin, 2022. "Count Roy model with finite mixtures," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1160-1181, September.
    26. Gregory Gilpin, 2009. "Reevaluating the Effect of Non-Teaching Wages on Teacher Attrition," CAEPR Working Papers 2009-022, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    27. Alexander Jordan & Alex Lenkoski, 2012. "Tobit Bayesian Model Averaging and the Determinants of Foreign Direct Investment," Papers 1205.2501, arXiv.org.
    28. Chib, Siddhartha & Jacobi, Liana, 2008. "Analysis of treatment response data from eligibility designs," Journal of Econometrics, Elsevier, vol. 144(2), pages 465-478, June.
    29. Dandan Xu & Michael J. Daniels & Almut G. Winterstein, 2018. "A Bayesian nonparametric approach to causal inference on quantiles," Biometrics, The International Biometric Society, vol. 74(3), pages 986-996, September.
    30. Jacobi, Liana & Wagner, Helga & Frühwirth-Schnatter, Sylvia, 2016. "Bayesian treatment effects models with variable selection for panel outcomes with an application to earnings effects of maternity leave," Journal of Econometrics, Elsevier, vol. 193(1), pages 234-250.

  17. Omori, Yasuhiro & Chib, Siddhartha & Shephard, Neil & Nakajima, Jouchi, 2007. "Stochastic volatility with leverage: Fast and efficient likelihood inference," Journal of Econometrics, Elsevier, vol. 140(2), pages 425-449, October.

    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. Antonio A. F. Santos, 2021. "Bayesian Estimation for High-Frequency Volatility Models in a Time Deformed Framework," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 455-479, February.
    3. Martin Iseringhausen & Hauke Vierke, 2018. "What Drives Output Volatility? The Role of Demographics and Government Size Revisited," European Economy - Discussion Papers 075, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    4. 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.
    5. Mark J. Jensen & John M. Maheu, 2008. "Bayesian semiparametric stochastic volatility modeling," FRB Atlanta Working Paper 2008-15, Federal Reserve Bank of Atlanta.
    6. Bermudez, P. de Zea & Marín, J. Miguel & Rue, Håvard & Veiga, Helena, 2024. "Integrated nested Laplace approximations for threshold stochastic volatility models," Econometrics and Statistics, Elsevier, vol. 30(C), pages 15-35.
    7. Khorunzhina, Natalia & Richard, Jean-Francois, 2016. "Finite Gaussian Mixture Approximations to Analytically Intractable Density Kernels," MPRA Paper 72326, University Library of Munich, Germany.
    8. Kenichiro McAlinn & Asahi Ushio & Teruo Nakatsuma, 2020. "Volatility forecasts using stochastic volatility models with nonlinear leverage effects," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 143-154, March.
    9. Hernández, Juan R., 2025. "Covered interest parity: A forecasting approach to estimate the neutral band," Economic Modelling, Elsevier, vol. 148(C).
    10. 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.
    11. Jin‐Yu Chen & Xue‐Hong Zhu & Mei‐Rui Zhong, 2021. "Time‐varying effects and structural change of oil price shocks on industrial output: Evidence from China's oil industrial chain," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3460-3472, July.
    12. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023. "Bayesian Modeling of Time-Varying Parameters Using Regression Trees," Working Papers 23-05, Federal Reserve Bank of Cleveland.
    13. Yuta Kurose, 2021. "Stochastic volatility model with range-based correction and leverage," Papers 2110.00039, arXiv.org, revised Oct 2021.
    14. Makoto Takahashi & Toshiaki Watanabe & Yasuhiro Omori, 2014. "Volatility and Quantile Forecasts by Realized Stochastic Volatility Models with Generalized Hyperbolic Distribution," CIRJE F-Series CIRJE-F-949, CIRJE, Faculty of Economics, University of Tokyo.
    15. Gerdie Everaert & Martin Iseringhausen, 2017. "Measuring The International Dimension Of Output Volatility," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 17/928, Ghent University, Faculty of Economics and Business Administration.
    16. Pedro Clavijo-Cortes, 2023. "Is unemployment hysteretic or structural? A Bayesian model selection approach," Empirical Economics, Springer, vol. 65(6), pages 2837-2866, December.
    17. Tsyplakov, Alexander, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models," MPRA Paper 25511, University Library of Munich, Germany.
    18. Xi, Yanhui & Peng, Hui & Qin, Yemei & Xie, Wenbiao & Chen, Xiaohong, 2015. "Bayesian analysis of heavy-tailed market microstructure model and its application in stock markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 117(C), pages 141-153.
    19. Jonas D. M. Fisher, Jonas D. & Melosi, Leonardo & Sebastian Rast, Sebastian, 2025. "Long-Run Inflation Expectations," The Warwick Economics Research Paper Series (TWERPS) 1551, University of Warwick, Department of Economics.
    20. Jonas D. M. Fisher & Leonardo Melosi & Sebastian Rast, 2025. "Long-Run Inflation Expectations," Working Paper Series WP 2025-03, Federal Reserve Bank of Chicago.
    21. Tino Berger & Gerdie Everaert & Hauke Vierke, 2015. "Testing for time variation in an unobserved components model for the U.S. economy," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 15/903, Ghent University, Faculty of Economics and Business Administration.
    22. Creal, Drew D. & Tsay, Ruey S., 2015. "High dimensional dynamic stochastic copula models," Journal of Econometrics, Elsevier, vol. 189(2), pages 335-345.
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    24. Guglielmo Maria Caporale & Luis Alberiko Gil‐Alana & Tommaso Trani, 2022. "On the persistence of UK inflation: A long‐range dependence approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 439-454, January.
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  18. Chib, Siddhartha & Jacobi, Liana, 2007. "Modeling and calculating the effect of treatment at baseline from panel outcomes," Journal of Econometrics, Elsevier, vol. 140(2), pages 781-801, October.

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    1. Yijun Li & Cheuk Hang Leung & Xiangqian Sun & Chaoqun Wang & Yiyan Huang & Xing Yan & Qi Wu & Dongdong Wang & Zhixiang Huang, 2023. "The Causal Impact of Credit Lines on Spending Distributions," Papers 2312.10388, arXiv.org.
    2. Liana Jacobi & Helga Wagner & Sylvia Frühwirth-Schnatter, 2014. "Bayesian Treatment Effects Models with Variable Selection for Panel Outcomes with an Application to Earnings Effects of Maternity Leave," NRN working papers 2014-12, The Austrian Center for Labor Economics and the Analysis of the Welfare State, Johannes Kepler University Linz, Austria.
    3. Li, Mingliang & Mumford, Kevin J. & Tobias, Justin L., 2012. "A Bayesian analysis of payday loans and their regulation," Journal of Econometrics, Elsevier, vol. 171(2), pages 205-216.
    4. Boyuan Zhang, 2022. "Incorporating Prior Knowledge of Latent Group Structure in Panel Data Models," Papers 2211.16714, arXiv.org, revised Oct 2023.
    5. Bretteville-Jensen, Anne Line & Jacobi, Liana, 2008. "Climbing the Drug Staircase: A Bayesian Analysis of the Initiation of Hard Drug Use," IZA Discussion Papers 3879, IZA Network @ LISER.
    6. Wagner, Helga & Frühwirth-Schnatter, Sylvia & Jacobi, Liana, 2023. "Factor-augmented Bayesian treatment effects models for panel outcomes," Econometrics and Statistics, Elsevier, vol. 28(C), pages 63-80.
    7. Moreno, Elías & Girón, F.J. & Vázquez-Polo, F.J. & Negrín, M.A., 2012. "Optimal healthcare decisions: The importance of the covariates in cost–effectiveness analysis," European Journal of Operational Research, Elsevier, vol. 218(2), pages 512-522.
    8. Chib, Siddhartha & Jacobi, Liana, 2008. "Analysis of treatment response data from eligibility designs," Journal of Econometrics, Elsevier, vol. 144(2), pages 465-478, June.
    9. Jacobi, Liana & Wagner, Helga & Frühwirth-Schnatter, Sylvia, 2016. "Bayesian treatment effects models with variable selection for panel outcomes with an application to earnings effects of maternity leave," Journal of Econometrics, Elsevier, vol. 193(1), pages 234-250.

  19. Chib, Siddhartha & Jeliazkov, Ivan, 2006. "Inference in Semiparametric Dynamic Models for Binary Longitudinal Data," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 685-700, June.

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    1. Hosoe, Nobuhiro & Takagi, Shingo, 2012. "Retail power market competition with endogenous entry decision—An auction data analysis," Journal of the Japanese and International Economies, Elsevier, vol. 26(3), pages 351-368.
    2. Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2023. "Forecasting with a panel Tobit model," Quantitative Economics, Econometric Society, vol. 14(1), pages 117-159, January.
    3. Brajendra C. Sutradhar, 2022. "Fixed versus Mixed Effects Based Marginal Models for Clustered Correlated Binary Data: an Overview on Advances and Challenges," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(1), pages 259-302, May.
    4. Mohammad Arshad Rahman & Angela Vossmeyer, 2019. "Estimation and Applications of Quantile Regression for Binary Longitudinal Data," Papers 1909.05560, arXiv.org.
    5. Ivan Jeliazkov & Angela Vossmeyer, 2018. "The impact of estimation uncertainty on covariate effects in nonlinear models," Statistical Papers, Springer, vol. 59(3), pages 1031-1042, September.
    6. Kaeding, Matthias, 2015. "Flexible Modeling of Binary Data Using the Log-Burr Link," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113043, Verein für Socialpolitik / German Economic Association.
    7. Bacolod, Marigee P. & Tobias, Justin L., 2006. "Schools, school quality and achievement growth: Evidence from the Philippines," Economics of Education Review, Elsevier, vol. 25(6), pages 619-632, December.
    8. Manini Ojha & Mohammad Arshad Rahman, 2020. "Do Online Courses Provide an Equal Educational Value Compared to In-Person Classroom Teaching? Evidence from US Survey Data using Quantile Regression," Papers 2007.06994, arXiv.org.
    9. Justin L. Tobias, 2025. "Adaptive Bayesian Nonparametric Regression via Stationary Smoothness Priors," Mathematics, MDPI, vol. 13(7), pages 1-19, March.
    10. Georges Bresson & Guy Lacroix & Mohammad Arshad Rahman, 2021. "Bayesian panel quantile regression for binary outcomes with correlated random effects: an application on crime recidivism in Canada," Empirical Economics, Springer, vol. 60(1), pages 227-259, January.
    11. Artur J. Lemonte & Jorge L. Bazán, 2018. "New links for binary regression: an application to coca cultivation in Peru," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(3), pages 597-617, September.
    12. Todd E. Clark & Gergely Ganics & Elmar Mertens, 2022. "Constructing Fan Charts from the Ragged Edge of SPF Forecasts," Working Papers 22-36, Federal Reserve Bank of Cleveland.
    13. Chan, Joshua C.C. & Poon, Aubrey & Zhu, Dan, 2023. "High-dimensional conditionally Gaussian state space models with missing data," Journal of Econometrics, Elsevier, vol. 236(1).
    14. Dimitrakopoulos, Stefanos, 2018. "Accounting for persistence in panel count data models. An application to the number of patents awarded," Economics Letters, Elsevier, vol. 171(C), pages 245-248.
    15. Genya Kobayashi & Hideo Kozumi, 2012. "Bayesian analysis of quantile regression for censored dynamic panel data," Computational Statistics, Springer, vol. 27(2), pages 359-380, June.
    16. Ofer Mintz & Imran S. Currim & Ivan Jeliazkov, 2013. "Information Processing Pattern and Propensity to Buy: An Investigation of Online Point-of-Purchase Behavior," Marketing Science, INFORMS, vol. 32(5), pages 716-732, September.
    17. Wu, Frank C.Z., 2024. "A high-dimensional additive nonparametric model," Journal of Economic Dynamics and Control, Elsevier, vol. 166(C).
    18. Choudhary, Vidyanand & Currim, Imran & Dewan, Sanjeev & Jeliazkov, Ivan & Mintz, Ofer & Turner, John, 2017. "Evaluation Set Size and Purchase: Evidence from a Product Search Engine," Journal of Interactive Marketing, Elsevier, vol. 37(C), pages 16-31.
    19. Mertens, Elmar, 2023. "Precision-based sampling for state space models that have no measurement error," Journal of Economic Dynamics and Control, Elsevier, vol. 154(C).
    20. Zhao, Kaifeng & Lian, Heng, 2014. "Variational inferences for partially linear additive models with variable selection," Computational Statistics & Data Analysis, Elsevier, vol. 80(C), pages 223-239.
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    22. Tong Li & Xiaoyong Zheng, 2008. "Semiparametric Bayesian inference for dynamic Tobit panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(6), pages 699-728.
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    127. Lopes, Hedibert F. & McCulloch, Robert E. & Tsay, Ruey S., 2022. "Parsimony inducing priors for large scale state–space models," Journal of Econometrics, Elsevier, vol. 230(1), pages 39-61.
    128. Karmous, Aida & Boubaker, Heni & Belkacem, Lotfi, 2019. "A dynamic factor model with stylized facts to forecast volatility for an optimal portfolio," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    129. Roberto Casarin & Domenico Sartore & Marco Tronzano, 2018. "A Bayesian Markov-Switching Correlation Model for Contagion Analysis on Exchange Rate Markets," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 101-114, January.
    130. Xiaodong Du & Fengxia Dong, 2016. "Responses to market information and the impact on price volatility and trading volume: the case of Class III milk futures," Empirical Economics, Springer, vol. 50(2), pages 661-678, March.
    131. Zhou, Xiaocong & Nakajima, Jouchi & West, Mike, 2014. "Bayesian forecasting and portfolio decisions using dynamic dependent sparse factor models," International Journal of Forecasting, Elsevier, vol. 30(4), pages 963-980.
    132. Ghaemi Asl, Mahdi & Raheem, Ibrahim D. & Rashidi, Muhammad Mahdi, 2023. "Do stochastic risks flow between industrial and precious metals, Islamic stocks, green bonds, green stocks, clean investments, major foreign exchange rates, and Bitcoin?," Resources Policy, Elsevier, vol. 86(PA).
    133. McCausland, William & Miller, Shirley & Pelletier, Denis, 2021. "Multivariate stochastic volatility using the HESSIAN method," Econometrics and Statistics, Elsevier, vol. 17(C), pages 76-94.
    134. Gribisch, Bastian & Hartkopf, Jan Patrick & Liesenfeld, Roman, 2020. "Factor state–space models for high-dimensional realized covariance matrices of asset returns," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 1-20.
    135. Malefaki, Valia, 2015. "On Flexible Linear Factor Stochastic Volatility Models," MPRA Paper 62216, University Library of Munich, Germany.
    136. Roberto Casarin & Domenico sartore, 2008. "Matrix-State Particle Filter for Wishart Stochastic Volatility Processes," Working Papers 0816, University of Brescia, Department of Economics.
    137. Zhongxian Men & Adam W. Kolkiewicz & Tony S. Wirjanto, 2013. "Bayesian Inference of Asymmetric Stochastic Conditional Duration Models," Working Paper series 28_13, Rimini Centre for Economic Analysis.
    138. Xu, Yingying & Lien, Donald, 2020. "Dynamic exchange rate dependences: The effect of the U.S.-China trade war," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 68(C).
    139. Andrew Gordon Wilson & David A. Knowles & Zoubin Ghahramani, 2011. "Gaussian Process Regression Networks," Papers 1110.4411, arXiv.org.
    140. Yingying Xu & Donald Lien, 2020. "Optimal futures hedging for energy commodities: An application of the GAS model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1090-1108, July.
    141. Tao Sun, 2024. "Bundle Choice Model with Endogenous Regressors: An Application to Soda Tax," Papers 2412.05794, arXiv.org.

  21. P. Seetharaman & Siddhartha Chib & Andrew Ainslie & Peter Boatwright & Tat Chan & Sachin Gupta & Nitin Mehta & Vithala Rao & Andrei Strijnev, 2005. "Models of Multi-Category Choice Behavior," Marketing Letters, Springer, vol. 16(3), pages 239-254, December.

    Cited by:

    1. Rakesh Niraj & V. Padmanabhan & P. B. Seetharaman, 2008. "Research Note—A Cross-Category Model of Households' Incidence and Quantity Decisions," Marketing Science, INFORMS, vol. 27(2), pages 225-235, 03-04.
    2. Harald Hruschka, 2017. "Analyzing the dependences of multi-category purchases on interactions of marketing variables," Journal of Business Economics, Springer, vol. 87(3), pages 295-313, April.
    3. Nitin Mehta, 2007. "Investigating Consumers' Purchase Incidence and Brand Choice Decisions Across Multiple Product Categories: A Theoretical and Empirical Analysis," Marketing Science, INFORMS, vol. 26(2), pages 196-217, 03-04.
    4. Philipp Noormann & Sebastian Tillmanns, 2017. "Drivers of private-label purchase behavior across quality tiers and product categories," Journal of Business Economics, Springer, vol. 87(3), pages 359-395, April.
    5. Taha Hossein Rashidi & Matthew J. Roorda, 2018. "A business establishment fleet ownership and composition model," Transportation, Springer, vol. 45(3), pages 971-987, May.
    6. Vinit Kumar Mishra & Karthik Natarajan & Dhanesh Padmanabhan & Chung-Piaw Teo & Xiaobo Li, 2014. "On Theoretical and Empirical Aspects of Marginal Distribution Choice Models," Management Science, INFORMS, vol. 60(6), pages 1511-1531, June.
    7. Park, Sangwon & Nicolau, Juan L., 2015. "Differentiated effect of advertising: Joint vs. separate consumption," Tourism Management, Elsevier, vol. 47(C), pages 107-114.
    8. Gal Oestreicher-Singer & Arun Sundararajan, 2012. "The Visible Hand? Demand Effects of Recommendation Networks in Electronic Markets," Management Science, INFORMS, vol. 58(11), pages 1963-1981, November.
    9. Raluca M. Ursu & Daria Dzyabura, 2020. "Retailers’ product location problem with consumer search," Quantitative Marketing and Economics (QME), Springer, vol. 18(2), pages 125-154, June.
    10. Sutthipong Meeyai, 2015. "Modeling Store Patronage: A Systematic Review," International Conference on Marketing and Business Development Journal, The Bucharest University of Economic Studies, vol. 1(1), pages 40-48, July.
    11. Harald Hruschka, 2021. "Comparing unsupervised probabilistic machine learning methods for market basket analysis," Review of Managerial Science, Springer, vol. 15(2), pages 497-527, February.
    12. S. Sriram & Pradeep K. Chintagunta & Manoj K. Agarwal, 2010. "Investigating Consumer Purchase Behavior in Related Technology Product Categories," Marketing Science, INFORMS, vol. 29(2), pages 291-314, 03-04.
    13. Klabjan, Diego & Pei, Jinxiang, 2011. "In-store one-to-one marketing," Journal of Retailing and Consumer Services, Elsevier, vol. 18(1), pages 64-73.
    14. Theja Tulabandhula & Deeksha Sinha & Saketh Reddy Karra & Prasoon Patidar, 2020. "Multi-Purchase Behavior: Modeling, Estimation and Optimization," Papers 2006.08055, arXiv.org, revised Aug 2023.
    15. Prasad, Ashutosh & Strijnev, Andrei & Zhang, Qin, 2008. "What can grocery basket data tell us about health consciousness?," International Journal of Research in Marketing, Elsevier, vol. 25(4), pages 301-309.
    16. George, Morris & Kumar, V. & Grewal, Dhruv, 2013. "Maximizing Profits for a Multi-Category Catalog Retailer," Journal of Retailing, Elsevier, vol. 89(4), pages 374-396.
    17. Hongju Liu & Qiang Liu & Pradeep K. Chintagunta, 2017. "Promotion Spillovers: Drug Detailing in Combination Therapy," Marketing Science, INFORMS, vol. 36(3), pages 382-401, May.
    18. Wei, Yuansheng & Huang, Pei, 2019. "A model of product compatibility introduction with consumer recognition," International Journal of Research in Marketing, Elsevier, vol. 36(4), pages 613-629.
    19. Minha Hwang & Sungho Park, 2016. "The Impact of Walmart Supercenter Conversion on Consumer Shopping Behavior," Management Science, INFORMS, vol. 62(3), pages 817-828, March.
    20. Lin, Chen & Bowman, Douglas, 2022. "The impact of introducing a customer loyalty program on category sales and profitability," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    21. Harald Hruschka, 2017. "Multi-category purchase incidences with marketing cross effects," Review of Managerial Science, Springer, vol. 11(2), pages 443-469, March.
    22. Gielens, Katrijn & Gijsbrechts, Els & Dekimpe, Marnik G., 2014. "Gains and losses of exclusivity in grocery retailing," International Journal of Research in Marketing, Elsevier, vol. 31(3), pages 239-252.
    23. Dahana, Wirawan Dony & Miwa, Yukihiro & Morisada, Makoto, 2019. "Linking lifestyle to customer lifetime value: An exploratory study in an online fashion retail market," Journal of Business Research, Elsevier, vol. 99(C), pages 319-331.
    24. Ma, Yu & Seetharaman, P.B. & Narasimhan, Chakravarthi, 2012. "Modeling Dependencies in Brand Choice Outcomes Across Complementary Categories," Journal of Retailing, Elsevier, vol. 88(1), pages 47-62.
    25. Zhang, Qin & Gangwar, Manish & Seetharaman, P.B., 2017. "Polygamous Store Loyalties: An Empirical Investigation," Journal of Retailing, Elsevier, vol. 93(4), pages 477-492.
    26. Youngsoo Kim & Rahul Telang & William B. Vogt & Ramayya Krishnan, 2010. "An Empirical Analysis of Mobile Voice Service and SMS: A Structural Model," Management Science, INFORMS, vol. 56(2), pages 234-252, February.
    27. Nguyen Tien Thong & Hans Stubbe Solgaard & Wolfgang Haider & Eva Roth & Lars Ravn†Jonsen, 2018. "Using labeled choice experiments to analyze demand structure and market position among seafood products," Agribusiness, John Wiley & Sons, Ltd., vol. 34(2), pages 163-189, March.
    28. Peter J. Danaher & Michael S. Smith, 2011. "Rejoinder--Estimation Issues for Copulas Applied to Marketing Data," Marketing Science, INFORMS, vol. 30(1), pages 25-28, 01-02.
    29. Pascucci, Federica & Nardi, Lorenzo & Marinelli, Luca & Paolanti, Marina & Frontoni, Emanuele & Gregori, Gian Luca, 2022. "Combining sell-out data with shopper behaviour data for category performance measurement: The role of category conversion power," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    30. Pramono, Ari & Oppewal, Harmen, 2021. "Where to refuel: Modeling on-the-way choice of convenience outlet," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
    31. Bryan Bollinger & Naim R. Darghouth & Kenneth T. Gillingham & Andres Gonzalez-Lira & Kenneth Gillingham, 2023. "Valuing Technology Complementarities: Rooftop Solar and Energy Storage," CESifo Working Paper Series 10871, CESifo.
    32. Pancras, Joseph & Gauri, Dinesh K. & Talukdar, Debabrata, 2013. "Loss leaders and cross-category retailer pass-through: A Bayesian multilevel analysis," Journal of Retailing, Elsevier, vol. 89(2), pages 140-157.
    33. Boztug, Yasemin & Reutterer, Thomas, 2008. "A combined approach for segment-specific market basket analysis," European Journal of Operational Research, Elsevier, vol. 187(1), pages 294-312, May.
    34. Feihong Xia & Rabikar Chatterjee & Jerrold H. May, 2019. "Using Conditional Restricted Boltzmann Machines to Model Complex Consumer Shopping Patterns," Marketing Science, INFORMS, vol. 38(4), pages 711-727, July.
    35. Jindal, Rupinder P. & Gauri, Dinesh K. & Li, Wanyu & Ma, Yu, 2021. "Omnichannel battle between Amazon and Walmart: Is the focus on delivery the best strategy?," Journal of Business Research, Elsevier, vol. 122(C), pages 270-280.
    36. Hongju Liu & Pradeep K. Chintagunta & Ting Zhu, 2010. "Complementarities and the Demand for Home Broadband Internet Services," Marketing Science, INFORMS, vol. 29(4), pages 701-720, 07-08.
    37. Wagner Kamakura, 2012. "Sequential market basket analysis," Marketing Letters, Springer, vol. 23(3), pages 505-516, September.
    38. Vithala R. Rao & Gary J. Russell & Hemant Bhargava & Alan Cooke & Tim Derdenger & Hwang Kim & Nanda Kumar & Irwin Levin & Yu Ma & Nitin Mehta & John Pracejus & R. Venkatesh, 2018. "Emerging Trends in Product Bundling: Investigating Consumer Choice and Firm Behavior," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 5(1), pages 107-120, March.
    39. Xiaojing Dong & Pradeep Chintagunta & Puneet Manchanda, 2011. "A new multivariate count data model to study multi-category physician prescription behavior," Quantitative Marketing and Economics (QME), Springer, vol. 9(3), pages 301-337, September.
    40. Hruschka, Harald, 2016. "Hidden Variable Models for Market Basket Data. Statistical Performance and Managerial Implications," University of Regensburg Working Papers in Business, Economics and Management Information Systems 489, University of Regensburg, Department of Economics.
    41. A. Ye(scedilla)im Orhun, 2009. "Optimal Product Line Design When Consumers Exhibit Choice Set-Dependent Preferences," Marketing Science, INFORMS, vol. 28(5), pages 868-886, 09-10.

  22. Siddhartha Chib & Ivan Jeliazkov, 2005. "Accept–reject Metropolis–Hastings sampling and marginal likelihood estimation," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 59(1), pages 30-44, February.

    Cited by:

    1. 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.
    2. Hosoe, Nobuhiro & Takagi, Shingo, 2012. "Retail power market competition with endogenous entry decision—An auction data analysis," Journal of the Japanese and International Economies, Elsevier, vol. 26(3), pages 351-368.
    3. Nakajima, Jouchi & Omori, Yasuhiro, 2009. "Leverage, heavy-tails and correlated jumps in stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2335-2353, April.
    4. Hedibert Freitas Lopes, 2014. "A Tutorial on the Computation of Bayes Factors," Business and Economics Working Papers 200, Unidade de Negocios e Economia, Insper.
    5. Jouchi Nakajima & Yasuhiro Omori, 2007. "Leverage, Heavy-Tails and Correlated Jumps in Stochastic Volatility Models (Revised in January 2008; Published in "Computational Statistics and Data Analysis", 53-6, 2335-2353. April 2009. )," CARF F-Series CARF-F-107, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    6. Angela Vossmeyer, 2019. "Analysis of Stigma and Bank Credit Provision," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(1), pages 163-194, February.
    7. Ivan Jeliazkov & Angela Vossmeyer, 2018. "The impact of estimation uncertainty on covariate effects in nonlinear models," Statistical Papers, Springer, vol. 59(3), pages 1031-1042, September.
    8. Asai, Manabu, 2009. "Bayesian analysis of stochastic volatility models with mixture-of-normal distributions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2579-2596.
    9. Jouchi Nakajima, 2008. "EGARCH and Stochastic Volatility: Modeling Jumps and Heavy-tails for Stock Returns," IMES Discussion Paper Series 08-E-23, Institute for Monetary and Economic Studies, Bank of Japan.
    10. Rufo, M.J. & Martín, J. & Pérez, C.J., 2010. "New approaches to compute Bayes factor in finite mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3324-3335, December.
    11. Michael L. Polemis & Mike G. Tsionas, 2023. "The environmental consequences of blockchain technology: A Bayesian quantile cointegration analysis for Bitcoin," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1602-1621, April.
    12. Arnab Kumar Maity & Sanjib Basu & Santu Ghosh, 2021. "Bayesian criterion‐based variable selection," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 835-857, August.
    13. Choudhary, Vidyanand & Currim, Imran & Dewan, Sanjeev & Jeliazkov, Ivan & Mintz, Ofer & Turner, John, 2017. "Evaluation Set Size and Purchase: Evidence from a Product Search Engine," Journal of Interactive Marketing, Elsevier, vol. 37(C), pages 16-31.
    14. Frederico M. Almeida & Vinícius D. Mayrink & Enrico A. Colosimo, 2023. "Bayesian solution to the monotone likelihood in the standard mixture cure model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 77(3), pages 365-390, August.
    15. Ehlers, Ricardo S., 2012. "Computational tools for comparing asymmetric GARCH models via Bayes factors," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(5), pages 858-867.
    16. Michael J. Daniels & Arkendu S. Chatterjee & Chenguang Wang, 2012. "Bayesian Model Selection for Incomplete Data Using the Posterior Predictive Distribution," Biometrics, The International Biometric Society, vol. 68(4), pages 1055-1063, December.
    17. Yuta Kurose & Yasuhiro Omori & Akira Hibiki, 2014. "A Discrete/Continuous Choice Model on a Nonconvex Budget Set," CIRJE F-Series CIRJE-F-942, CIRJE, Faculty of Economics, University of Tokyo.
    18. 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.

  23. Ram C. Tiwari & Kathleen A. Cronin & William Davis & Eric J. Feuer & Binbing Yu & Siddhartha Chib, 2005. "Bayesian model selection for join point regression with application to age‐adjusted cancer rates," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(5), pages 919-939, November.

    Cited by:

    1. Chen, Cathy W.S. & Chan, Jennifer S.K. & So, Mike K.P. & Lee, Kevin K.M., 2011. "Classification in segmented regression problems," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2276-2287, July.
    2. Ghosh, Pulak & Huang, Lan & Yu, Binbing & Tiwari, Ram C., 2009. "Semiparametric Bayesian approaches to joinpoint regression for population-based cancer survival data," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4073-4082, October.
    3. Yu, Binbing & Barrett, Michael J. & Kim, Hyune-Ju & Feuer, Eric J., 2007. "Estimating joinpoints in continuous time scale for multiple change-point models," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2420-2427, February.
    4. Yi Li & Ram C. Tiwari, 2008. "Comparing Trends in Cancer Rates Across Overlapping Regions," Biometrics, The International Biometric Society, vol. 64(4), pages 1280-1286, December.
    5. Binbing Yu & Lan Huang & Ram C. Tiwari & Eric J. Feuer & Karen A. Johnson, 2009. "Modelling population‐based cancer survival trends by using join point models for grouped survival data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(2), pages 405-425, April.
    6. Irene O L Wong & Benjamin J Cowling & Gabriel M Leung & C Mary Schooling, 2013. "Age-Period-Cohort Projections of Ischaemic Heart Disease Mortality by Socio-Economic Position in a Rapidly Transitioning Chinese Population," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-8, April.
    7. Chan, J.S.K. & Lam, C.P.Y. & Yu, P.L.H. & Choy, S.T.B. & Chen, C.W.S., 2012. "A Bayesian conditional autoregressive geometric process model for range data," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3006-3019.
    8. Erjia Ge & Yee Leung, 2013. "Detection of crossover time scales in multifractal detrended fluctuation analysis," Journal of Geographical Systems, Springer, vol. 15(2), pages 115-147, April.

  24. Basu S. & Chib S., 2003. "Marginal Likelihood and Bayes Factors for Dirichlet Process Mixture Models," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 224-235, January.

    Cited by:

    1. Rafael Carvalho Ceregatti & Rafael Izbicki & Luis Ernesto Bueno Salasar, 2021. "WIKS: a general Bayesian nonparametric index for quantifying differences between two populations," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 274-291, March.
    2. Argiento, Raffaele & Guglielmi, Alessandra & Pievatolo, Antonio, 2010. "Bayesian density estimation and model selection using nonparametric hierarchical mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 816-832, April.
    3. Ausín, M. Concepción & Galeano, Pedro & Ghosh, Pulak, 2014. "A semiparametric Bayesian approach to the analysis of financial time series with applications to value at risk estimation," European Journal of Operational Research, Elsevier, vol. 232(2), pages 350-358.
    4. Griffin, J. E. & Steel, M. F. J., 2004. "Semiparametric Bayesian inference for stochastic frontier models," Journal of Econometrics, Elsevier, vol. 123(1), pages 121-152, November.
    5. Alain Pirotte & Jean-Loup Madre, 2011. "Determinants of Urban Sprawl in France," Urban Studies, Urban Studies Journal Limited, vol. 48(13), pages 2865-2886, October.
    6. Georges Bresson & Cheng Hsiao & Alain Pirotte, 2011. "Assessing the contribution of R&D to total factor productivity—a Bayesian approach to account for heterogeneity and heteroskedasticity," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(4), pages 435-452, December.
    7. Ramírez–Hassan, Andrés & López-Vera, Alejandro, 2024. "Welfare implications of a tax on electricity: A semi-parametric specification of the incomplete EASI demand system," Energy Economics, Elsevier, vol. 131(C).
    8. Mark J Jensen & John M Maheu, 2012. "Estimating a Semiparametric Asymmetric Stochastic Volatility Model with a Dirichlet Process Mixture," Working Papers tecipa-453, University of Toronto, Department of Economics.
    9. Andr'es Ram'irez-Hassan & Alejandro L'opez-Vera, 2021. "Semi-parametric estimation of the EASI model: Welfare implications of taxes identifying clusters due to unobserved preference heterogeneity," Papers 2109.07646, arXiv.org.
    10. J. Griffin, 2011. "Bayesian clustering of distributions in stochastic frontier analysis," Journal of Productivity Analysis, Springer, vol. 36(3), pages 275-283, December.
    11. Jara, Alejandro & Jose Garcia-Zattera, Maria & Lesaffre, Emmanuel, 2007. "A Dirichlet process mixture model for the analysis of correlated binary responses," Computational Statistics & Data Analysis, Elsevier, vol. 51(11), pages 5402-5415, July.
    12. Tchumtchoua, Sylvie & Dey, Dipak, 2007. "Semiparametric Bayesian Estimation of Random Coefficients Discrete Choice Models," Research Reports 149208, University of Connecticut, Food Marketing Policy Center.
    13. Surya T. Tokdar & Ryan Martin, 2021. "Bayesian Test of Normality Versus a Dirichlet Process Mixture Alternative," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 66-96, May.
    14. Barrientos, Andrés F. & Canale, Antonio, 2021. "A Bayesian goodness-of-fit test for regression," Computational Statistics & Data Analysis, Elsevier, vol. 155(C).
    15. Laura Liu, 2018. "Density Forecasts in Panel Data Models : A Semiparametric Bayesian Perspective," Finance and Economics Discussion Series 2018-036, Board of Governors of the Federal Reserve System (U.S.).
    16. Jason A. Duan & Leigh McAlister & Shameek Sinha, 2011. "Commentary--Reexamining Bayesian Model-Comparison Evidence of Cross-Brand Pass-Through," Marketing Science, INFORMS, vol. 30(3), pages 550-561, 05-06.
    17. Ho, Man-Wai, 2011. "Usage of a pair of -paths in Bayesian estimation of a unimodal density," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1581-1595, April.
    18. Artur J. Lemonte & Jorge L. Bazán, 2018. "New links for binary regression: an application to coca cultivation in Peru," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(3), pages 597-617, September.
    19. 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.
    20. Laura Liu, 2017. "Density Forecasts in Panel Models: A semiparametric Bayesian Perspective," PIER Working Paper Archive 17-006, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 28 Apr 2017.
    21. 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).
    22. Kelter, Riko, 2022. "Power analysis and type I and type II error rates of Bayesian nonparametric two-sample tests for location-shifts based on the Bayes factor under Cauchy priors," Computational Statistics & Data Analysis, Elsevier, vol. 165(C).
    23. Im, Yunju & Tan, Aixin, 2021. "Bayesian subgroup analysis in regression using mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 162(C).
    24. Guohua Feng & Chuan Wang & Xibin Zhang, 2019. "Estimation of inefficiency in stochastic frontier models: a Bayesian kernel approach," Journal of Productivity Analysis, Springer, vol. 51(1), pages 1-19, February.
    25. Georges Bresson & Cheng Hsiao, 2011. "A functional connectivity approach for modeling cross-sectional dependence with an application to the estimation of hedonic housing prices in Paris," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(4), pages 501-529, December.
    26. Bhattacharya, Abhishek & Dunson, David, 2012. "Nonparametric Bayes classification and hypothesis testing on manifolds," Journal of Multivariate Analysis, Elsevier, vol. 111(C), pages 1-19.
    27. Sun, Peng & Kim, Inyoung & Lee, Ki-Ahm, 2018. "Dual-semiparametric regression using weighted Dirichlet process mixture," Computational Statistics & Data Analysis, Elsevier, vol. 117(C), pages 162-181.

  25. Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2002. "Markov chain Monte Carlo methods for stochastic volatility models," Journal of Econometrics, Elsevier, vol. 108(2), pages 281-316, June.

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    1. Antonio A. F. Santos, 2021. "Bayesian Estimation for High-Frequency Volatility Models in a Time Deformed Framework," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 455-479, February.
    2. Hautsch, Nikolaus & Yang, Fuyu, 2010. "Bayesian inference in a stochastic volatility Nelson-Siegel Model," SFB 649 Discussion Papers 2010-004, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    3. Mark J. Jensen & John M. Maheu, 2008. "Bayesian semiparametric stochastic volatility modeling," FRB Atlanta Working Paper 2008-15, Federal Reserve Bank of Atlanta.
    4. J. Beirlant & G. Claeskens & C. Croux & H. Degryse & H. Dewachter & G. Dhaene & J. Dhaene & I. Gijbels & M. Goovaerts & M. Hubert & F. Roodhooft & W. Schouten & M. Willekens, 2005. "Managing Uncertainty: Financial, Actuarial and Statistical Modeling," Review of Business and Economic Literature, KU Leuven, Faculty of Economics and Business (FEB), Review of Business and Economic Literature, vol. 0(1), pages 23-48.
    5. Kenichiro McAlinn & Asahi Ushio & Teruo Nakatsuma, 2020. "Volatility forecasts using stochastic volatility models with nonlinear leverage effects," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 143-154, March.
    6. Arnaud Dufays, 2014. "On the conjugacy of off-line and on-line Sequential Monte Carlo Samplers," Working Paper Research 263, National Bank of Belgium.
    7. Faruk Selcuk, 2005. "Asymmetric stochastic volatility in emerging stock markets," Applied Financial Economics, Taylor & Francis Journals, vol. 15(12), pages 867-874.
    8. Yong Li & Jun Yu, 2011. "Bayesian Hypothesis Testing in Latent Variable Models," Working Papers 11-2011, Singapore Management University, School of Economics.
    9. Robert J. Barro & Tao Jin, 2016. "Rare Events and Long-Run Risks," NBER Working Papers 21871, National Bureau of Economic Research, Inc.
    10. Joshua C.C. Chan & Angelia L. Grant, 2014. "Issues in Comparing Stochastic Volatility Models Using the Deviance Information Criterion," CAMA Working Papers 2014-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    11. Lombardi, Marco J. & Calzolari, Giorgio, 2009. "Indirect estimation of [alpha]-stable stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2298-2308, April.
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  26. Chib, Siddhartha & Shephard, Neil, 2002. "Numerical Techniques for Maximum Likelihood Estimation of Continuous-Time Diffusion Processes: Comment," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 325-327, July.

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    1. Osnat Stramer & Jun Yan, 2007. "Asymptotics of an Efficient Monte Carlo Estimation for the Transition Density of Diffusion Processes," Methodology and Computing in Applied Probability, Springer, vol. 9(4), pages 483-496, December.
    2. Siddhartha Chib & Michael K Pitt & Neil Shephard, 2004. "Likelihood based inference for diffusion driven models," Economics Papers 2004-W20, Economics Group, Nuffield College, University of Oxford.

  27. Chib, Siddhartha & Hamilton, Barton H., 2002. "Semiparametric Bayes analysis of longitudinal data treatment models," Journal of Econometrics, Elsevier, vol. 110(1), pages 67-89, September.

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    1. Mark J. Jensen & John M. Maheu, 2008. "Bayesian semiparametric stochastic volatility modeling," FRB Atlanta Working Paper 2008-15, Federal Reserve Bank of Atlanta.
    2. Carneiro, Pedro & Hansen, Karsten T. & Heckman, James J., 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College Choice," IZA Discussion Papers 767, IZA Network @ LISER.
    3. Moshe Buchinsky & Denis Fougère & Francis Kramarz & Rusty Tchernis, 2008. "Interfirm Mobility, Wages, and the Returns to Seniority and Experience in the U.S," CAEPR Working Papers 2008-006, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    4. Markus Jochmann & Roberto Leon-Gonzalez, 2003. "Estimating the Demand for Health Care with Panel Data: A Semiparametric Bayesian Approach," Working Papers 2003005, The University of Sheffield, Department of Economics, revised Oct 2003.
    5. Tong Li & Xiaoyong Zheng, 2006. "Entry and competition effects in first-price auctions: theory and evidence from procurement auctions," CeMMAP working papers CWP13/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Burda, Martin & Harding, Matthew, 2014. "Environmental Justice: Evidence from Superfund cleanup durations," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PA), pages 380-401.
    7. Griffin, J.E. & Steel, M.F.J., 2011. "Stick-breaking autoregressive processes," Journal of Econometrics, Elsevier, vol. 162(2), pages 383-396, June.
    8. Fisher, Mark & Jensen, Mark J., 2022. "Bayesian nonparametric learning of how skill is distributed across the mutual fund industry," Journal of Econometrics, Elsevier, vol. 230(1), pages 131-153.
    9. 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.
    10. Flossmann Anton L. & Pohlmeier Winfried, 2006. "Causal Returns to Education: A Survey on Empirical Evidence for Germany," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 226(1), pages 6-23, February.
    11. Chib, Siddhartha & Jacobi, Liana, 2007. "Modeling and calculating the effect of treatment at baseline from panel outcomes," Journal of Econometrics, Elsevier, vol. 140(2), pages 781-801, October.
    12. Jaeun Choi & A. James O'Malley, 2017. "Estimating the causal effect of treatment in observational studies with survival time end points and unmeasured confounding," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(1), pages 159-185, January.
    13. Li, Mingliang & Tobias, Justin L., 2011. "Bayesian inference in a correlated random coefficients model: Modeling causal effect heterogeneity with an application to heterogeneous returns to schooling," Journal of Econometrics, Elsevier, vol. 162(2), pages 345-361, June.
    14. Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2023. "Forecasting with a panel Tobit model," Quantitative Economics, Econometric Society, vol. 14(1), pages 117-159, January.
    15. Ishdorj, Ariun & Crepinsek, Mary Kay & Jensen, Helen H., "undated". "Children’s Consumption of Fruits and Vegetables: Do School Environment and Policies Affect Choice in School Meals?," 2012 AAEA/EAAE Food Environment Symposium 123534, Agricultural and Applied Economics Association.
    16. Martin Burda & Matthew C. Harding & Jerry Hausman, 2008. "A Bayesian mixed logit-probit model for multinomial choice," CeMMAP working papers CWP23/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    17. Griffin, J. E. & Steel, M. F. J., 2004. "Semiparametric Bayesian inference for stochastic frontier models," Journal of Econometrics, Elsevier, vol. 123(1), pages 121-152, November.
    18. Mingliang Li & Dale J. Poirier & Justin L. Tobias, 2004. "Do dropouts suffer from dropping out? Estimation and prediction of outcome gains in generalized selection models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(2), pages 203-225.
    19. Roberto Casarin & Federico Bassetti & Francesco Ravazzolo, 2015. "Bayesian Nonparametric Calibration and Combination of Predictive Distributions," Working Papers 2015:04, Department of Economics, University of Venice "Ca' Foscari".
    20. Zarepour, Mahmoud & Labadi, Luai Al, 2012. "On a rapid simulation of the Dirichlet process," Statistics & Probability Letters, Elsevier, vol. 82(5), pages 916-924.
    21. 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.
    22. Ishdorj, Ariun & Crepinsek, Mary Kay & Jensen, Helen H., 2013. "Children's Consumption of Fruits and Vegetables: Do School Environment and Policies Affect Choice At School and Away from School?," Staff General Research Papers Archive 36020, Iowa State University, Department of Economics.
    23. Asim Ansari & Raghuram Iyengar, 2006. "Semiparametric Thurstonian Models for Recurrent Choices: A Bayesian Analysis," Psychometrika, Springer;The Psychometric Society, vol. 71(4), pages 631-657, December.
    24. Joshua C.C. Chan & Justin L. Tobias, 2012. "Priors and Posterior Computation in Linear Endogenous Variable Models with Imperfect Instruments," ANU Working Papers in Economics and Econometrics 2012-580, Australian National University, College of Business and Economics, School of Economics.
    25. Federico Bassetti & Roberto Casarin & Marco Del Negro, 2022. "A Bayesian Approach to Inference on Probabilistic Surveys," Staff Reports 1025, Federal Reserve Bank of New York.
    26. 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.
    27. Abel Rodriguez & Enrique ter Horst, 2008. "Measuring expectations in options markets: An application to the SP500 index," Papers 0901.0033, arXiv.org.
    28. Murat K. Munkin & Partha Deb & Pravin K. Trivedi, 2006. "Bayesian analysis of the two-part model with endogeneity: application to health care expenditure," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(7), pages 1081-1099.
    29. Ishdorj, Ariun & Jensen, Helen H. & Tobias, Justin, 2007. "Intra-Household Allocation and Consumption of WIC-Approved Foods: A Bayesian Approach," Staff General Research Papers Archive 12833, Iowa State University, Department of Economics.
    30. Didier Nibbering, 2019. "A High-dimensional Multinomial Choice Model," Monash Econometrics and Business Statistics Working Papers 19/19, Monash University, Department of Econometrics and Business Statistics.
    31. Pedro Carneiro & Karsten T. Hansen & James J. Heckman, 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College," NBER Working Papers 9546, National Bureau of Economic Research, Inc.
    32. Marie Albertine Djuikom, 2018. "Incentives to labour migration and agricultural productivity: The Bayesian perspective," WIDER Working Paper Series wp-2018-45, World Institute for Development Economic Research (UNU-WIDER).
    33. Maksym Obrizan, 2011. "A Bayesian Model of Sample Selection with a Discrete Outcome Variable: Detecting Depression in Older Adults," Discussion Papers 41, Kyiv School of Economics.
    34. Chib, Siddhartha, 2007. "Analysis of treatment response data without the joint distribution of potential outcomes," Journal of Econometrics, Elsevier, vol. 140(2), pages 401-412, October.
    35. Abel Rodr�guez & Enrique ter Horst, 2011. "Measuring expectations in options markets: an application to the S&P500 index," Quantitative Finance, Taylor & Francis Journals, vol. 11(9), pages 1393-1405, July.
    36. Mark J. Jensen, 2004. "Semiparametric Bayesian Inference of Long‐Memory Stochastic Volatility Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(6), pages 895-922, November.
    37. 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.
    38. Mark J. Jensen & John M. Maheu, 2018. "Risk, Return and Volatility Feedback: A Bayesian Nonparametric Analysis," JRFM, MDPI, vol. 11(3), pages 1-29, September.
    39. Monica Billio & Roberto Casarin & Luca Rossini, 2016. "Bayesian nonparametric sparse seemingly unrelated regression model (SUR)," Working Papers 2016:20, Department of Economics, University of Venice "Ca' Foscari".
    40. Justin Tobias, 2006. "Estimation, Learning and Parameters of Interest in a Multiple Outcome Selection Model," Econometric Reviews, Taylor & Francis Journals, vol. 25(1), pages 1-40.
    41. Monica Billio & Roberto Casarin & Luca Rossini, 2016. "Bayesian nonparametric sparse VAR models," Papers 1608.02740, arXiv.org, revised Oct 2018.
    42. Martin Burda & Artem Prokhorov, 2012. "Copula Based Factorization in Bayesian Multivariate Infinite Mixture Models," Working Papers 12012, Concordia University, Department of Economics.
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    3. Paolo Girardello & Orietta Nicolis & Giovanni Tondini, 2003. "Comparing Conditional Variance Models: Theory and Empirical Evidence," Multinational Finance Journal, Multinational Finance Journal, vol. 7(3-4), pages 177-206, September.
    4. Markus Jochmann & Roberto Leon-Gonzalez, 2003. "Estimating the Demand for Health Care with Panel Data: A Semiparametric Bayesian Approach," Working Papers 2003005, The University of Sheffield, Department of Economics, revised Oct 2003.
    5. Azam, Kazim & Pitt, Michael, "undated". "Bayesian Inference for a Semi-Parametric Copula-based Markov Chain," Economic Research Papers 270232, University of Warwick - Department of Economics.
    6. Bermúdez, Lluís & Karlis, Dimitris, 2012. "A finite mixture of bivariate Poisson regression models with an application to insurance ratemaking," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 3988-3999.
    7. Hilger, James & Englin, Jeffrey, 2009. "Utility theoretic semi-logarithmic incomplete demand systems in a natural experiment: Forest fire impacts on recreational values and use," Resource and Energy Economics, Elsevier, vol. 31(4), pages 287-298, November.
    8. B.P.M. McCabe & G.M. Martin, 2003. "Coherent Predictions of Low Count Time Series," Monash Econometrics and Business Statistics Working Papers 8/03, Monash University, Department of Econometrics and Business Statistics.
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    10. De Oliveira, Victor, 2013. "Hierarchical Poisson models for spatial count data," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 393-408.
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    22. Azam, Kazim & Pitt, Michael, 2014. "Bayesian Inference for a Semi-Parametric Copula-based Markov Chain," The Warwick Economics Research Paper Series (TWERPS) 1051, University of Warwick, Department of Economics.
    23. Tzougas, George & di Cerchiara, Alice Pignatelli, 2021. "Bivariate mixed Poisson regression models with varying dispersion," LSE Research Online Documents on Economics 114327, London School of Economics and Political Science, LSE Library.
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    32. Shirota, Shinichiro & Omori, Yasuhiro & F. Lopes, Hedibert. & Piao, Haixiang, 2017. "Cholesky realized stochastic volatility model," Econometrics and Statistics, Elsevier, vol. 3(C), pages 34-59.
    33. Cabras, Stefano & Sunhe, Flor, 2021. "A Bayesian Spatio-temporal model for predicting passengers' occupancy at Beijing Metro," DES - Working Papers. Statistics and Econometrics. WS 33787, Universidad Carlos III de Madrid. Departamento de Estadística.
    34. Marco Alfò & Giovanni Trovato, 2004. "Semiparametric Mixture Models for Multivariate Count Data, with Application," CEIS Research Paper 51, Tor Vergata University, CEIS.
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    36. Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro, 2016. "Volatility and quantile forecasts by realized stochastic volatility models with generalized hyperbolic distribution," International Journal of Forecasting, Elsevier, vol. 32(2), pages 437-457.
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    38. Rico Krueger & Taha H. Rashidi & Akshay Vij, 2020. "X vs. Y: an analysis of intergenerational differences in transport mode use among young adults," Transportation, Springer, vol. 47(5), pages 2203-2231, October.
    39. Minjung Kyung & Jeff Gill & George Casella, 2011. "Sampling schemes for generalized linear Dirichlet process random effects models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(3), pages 259-290, August.
    40. Yuta Kurose, 2022. "Bayesian GARCH modeling for return and range," Economics Bulletin, AccessEcon, vol. 42(3), pages 1717-1727.
    41. Arnar Buason & Dadi Kristofersson & Kyrre Rickertsen, 2021. "Habits in frequency of purchase models: the case of fish in France," Applied Economics, Taylor & Francis Journals, vol. 53(31), pages 3577-3589, July.
    42. Wedel, Michel & Böckenholt, Ulf & Kamakura, Wagner A., 2003. "Factor models for multivariate count data," Journal of Multivariate Analysis, Elsevier, vol. 87(2), pages 356-369, November.
    43. Bermúdez, Lluís & Karlis, Dimitris, 2011. "Bayesian multivariate Poisson models for insurance ratemaking," Insurance: Mathematics and Economics, Elsevier, vol. 48(2), pages 226-236, March.
    44. P. Girardello & Orietta Nicolis & Giovanni Tondini, 2002. "Comparing conditional variance models: Theory and empirical evidence," Departmental Working Papers 2002-08, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    45. Woojung Kim & Xiaokun (Cara) Wang, 2022. "Double parking in New York city: a comparison between commercial vehicles and passenger vehicles," Transportation, Springer, vol. 49(5), pages 1315-1337, October.
    46. Hellström, Jörgen & Nordström, Jonas, 2012. "Demand and welfare effects in recreational travel models: Accounting for substitution between number of trips and days to stay," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(3), pages 446-456.
    47. Sofia Anyfantaki & Antonis Demos, 2016. "Estimation and Properties of a Time-Varying EGARCH(1,1) in Mean Model," Econometric Reviews, Taylor & Francis Journals, vol. 35(2), pages 293-310, February.
    48. Nadarajah Saralees, 2007. "A Truncated Bivariate t Distribution," Stochastics and Quality Control, De Gruyter, vol. 22(2), pages 303-313, January.
    49. Gianluca Baio & Marta Blangiardo, 2010. "Bayesian hierarchical model for the prediction of football results," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(2), pages 253-264.
    50. Herriges, Joseph A. & Phaneuf, Daniel J. & Tobias, Justin L., 2008. "Estimating demand systems when outcomes are correlated counts," Journal of Econometrics, Elsevier, vol. 147(2), pages 282-298, December.
    51. Hellström, Jörgen & Nordström, Jonas, 2005. "Demand and Welfare Effects in Recreational Travel Models: A Bivariate Count Data Approach," Umeå Economic Studies 648, Umeå University, Department of Economics.
    52. George Tzougas & Despoina Makariou, 2022. "The multivariate Poisson‐Generalized Inverse Gaussian claim count regression model with varying dispersion and shape parameters," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 25(4), pages 401-417, December.
    53. Jung, Robert C. & Kukuk, Martin & Liesenfeld, Roman, 2006. "Time series of count data: modeling, estimation and diagnostics," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2350-2364, December.
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    55. Gaurav Sabnis & Rajdeep Grewal, 2015. "Cable News Wars on the Internet: Competition and User-Generated Content," Information Systems Research, INFORMS, vol. 26(2), pages 301-319, June.
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    60. Patricia Lengua Lafosse & Cristian Bayes & Gabriel Rodríguez, 2015. "A Stochastic Volatility Model with GH Skew Student’s t-Distribution: Application to Latin-American Stock Returns," Documentos de Trabajo / Working Papers 2015-405, Departamento de Economía - Pontificia Universidad Católica del Perú.
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    1. Nafisa Lohawala & Mohammad Arshad Rahman, 2025. "Do Determinants of EV Purchase Intent vary across the Spectrum? Evidence from Bayesian Analysis of US Survey Data," Papers 2504.09854, arXiv.org, revised Jan 2026.
    2. Patrick Waelbroeck, 2005. "Computational Issues in the Sequential Probit Model: A Monte Carlo Study," Computational Economics, Springer;Society for Computational Economics, vol. 26(2), pages 141-161, October.
    3. David B. Dunson & Zhen Chen & Jean Harry, 2003. "A Bayesian Approach for Joint Modeling of Cluster Size and Subunit-Specific Outcomes," Biometrics, The International Biometric Society, vol. 59(3), pages 521-530, September.
    4. Alhamzawi, Rahim, 2016. "Bayesian model selection in ordinal quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 103(C), pages 68-78.
    5. Andrew S. Fullerton, 2009. "A Conceptual Framework for Ordered Logistic Regression Models," Sociological Methods & Research, , vol. 38(2), pages 306-347, November.
    6. D. B. Dunson & C. Holloman & C. Calder & L. H. Gunn, 2004. "Bayesian Modeling of Multiple Lesion Onset and Growth from Interval-Censored Data," Biometrics, The International Biometric Society, vol. 60(3), pages 676-683, September.
    7. Wang, Jianqiang C. & Holan, Scott H., 2012. "Bayesian multi-regime smooth transition regression with ordered categorical variables," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4165-4179.
    8. B. Nebiyou Bekele & Yu Shen, 2005. "A Bayesian Approach to Jointly Modeling Toxicity and Biomarker Expression in a Phase I/II Dose-Finding Trial," Biometrics, The International Biometric Society, vol. 61(2), pages 343-354, June.
    9. Satkartar K. Kinney & David B. Dunson, 2007. "Fixed and Random Effects Selection in Linear and Logistic Models," Biometrics, The International Biometric Society, vol. 63(3), pages 690-698, September.
    10. Munkin, Murat K., 2011. "The Endogenous Sequential Probit model: An application to the demand for hospital utilization," Economics Letters, Elsevier, vol. 112(2), pages 182-185, August.
    11. 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.
    12. Li, Phillip, 2010. "Estimation of Sample Selection Models With Two Selection Mechanisms," University of California Transportation Center, Working Papers qt0h97w9x2, University of California Transportation Center.
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    21. Lei Shi, 2020. "Bayesian analysis of multivariate ordered probit model with individual heterogeneity," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(4), pages 649-665, December.
    22. Shimeles Abebe & Andinet Woldemichael, 2015. "Working Paper 225 - Measuring the Impact of Micro-Health Insurance on Healthcare Utilization: A Bayesian Potential Outcomes Approach," Working Paper Series 2166, African Development Bank.
    23. Gerhard Tutz, 2003. "Generalized Semiparametrically Structured Ordinal Models," Biometrics, The International Biometric Society, vol. 59(2), pages 263-273, June.

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    1. Zhang, Guoxiong, 2012. "Bayesian estimation of exchange rate regime choice with spatial effect," Economics Letters, Elsevier, vol. 117(3), pages 604-607.
    2. Antonio Pacifico, 2018. "Panel Bayesian VAR Modeling for Policy and Forecasting when dealing with confounding and latent effects," EERI Research Paper Series EERI RP 2018/15, Economics and Econometrics Research Institute (EERI), Brussels.
    3. Arnaud Dufays, 2014. "On the conjugacy of off-line and on-line Sequential Monte Carlo Samplers," Working Paper Research 263, National Bank of Belgium.
    4. Philippe J. Deschamps, 2008. "Comparing smooth transition and Markov switching autoregressive models of US unemployment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(4), pages 435-462.
    5. Yong Li & Jun Yu, 2011. "Bayesian Hypothesis Testing in Latent Variable Models," Working Papers 11-2011, Singapore Management University, School of Economics.
    6. Yong Li & Zhongxin Ni & Jie Zhang, 2011. "An Efficient Stochastic Simulation Algorithm for Bayesian Unit Root Testing in Stochastic Volatility Models," Computational Economics, Springer;Society for Computational Economics, vol. 37(3), pages 237-248, March.
    7. Makoto Takahashi & Toshiaki Watanabe & Yasuhiro Omori, 2014. "Volatility and Quantile Forecasts by Realized Stochastic Volatility Models with Generalized Hyperbolic Distribution," CIRJE F-Series CIRJE-F-949, CIRJE, Faculty of Economics, University of Tokyo.
    8. Luc Bauwens & Arnaud Dufays & Jeroen V.K. Rombouts, 2011. "Marginal Likelihood for Markov-Switching and Change-Point GARCH Models," Cahiers de recherche 1138, CIRPEE.
    9. Chan, Jennifer S.K. & Leung, Doris Y.P. & Boris Choy, S.T. & Wan, Wai Y., 2009. "Nonignorable dropout models for longitudinal binary data with random effects: An application of Monte Carlo approximation through the Gibbs output," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4530-4545, October.
    10. Lulu Cheng & Inyoung Kim & Herbert Pang, 2016. "Bayesian Semiparametric Model for Pathway-Based Analysis with Zero-Inflated Clinical Outcomes," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(4), pages 641-662, December.
    11. Neville Francis & Michael T. Owyang & Özge Savascin, 2012. "An endogenously clustered factor approach to international business cycles," Working Papers 2012-014, Federal Reserve Bank of St. Louis.
    12. Li, Bing & Pei, Pei & Tan, Fei, 2021. "Financial distress and fiscal inflation," Journal of Macroeconomics, Elsevier, vol. 70(C).
    13. Franta, Michal, 2021. "The Likelihood Of Effective Lower Bound Events," Macroeconomic Dynamics, Cambridge University Press, vol. 25(8), pages 2058-2079, December.
    14. Kakamu, Kazuhiko & Yunoue, Hideo & Kuramoto, Takashi, 2014. "Spatial patterns of flypaper effects for local expenditure by policy objective in Japan: A Bayesian approach," Economic Modelling, Elsevier, vol. 37(C), pages 500-506.
    15. Hubin, Aliaksandr & Storvik, Geir, 2018. "Mode jumping MCMC for Bayesian variable selection in GLMM," Computational Statistics & Data Analysis, Elsevier, vol. 127(C), pages 281-297.
    16. Wichitaksorn, Nuttanan & Tsurumi, Hiroki, 2013. "Comparison of MCMC algorithms for the estimation of Tobit model with non-normal error: The case of asymmetric Laplace distribution," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 226-235.
    17. Parent, Olivier & LeSage, James P., 2011. "A space-time filter for panel data models containing random effects," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 475-490, January.
    18. Chib, Siddhartha & Jacobi, Liana, 2007. "Modeling and calculating the effect of treatment at baseline from panel outcomes," Journal of Econometrics, Elsevier, vol. 140(2), pages 781-801, October.
    19. Das, Priyam & Ghosal, Subhashis, 2017. "Bayesian quantile regression using random B-spline series prior," Computational Statistics & Data Analysis, Elsevier, vol. 109(C), pages 121-143.
    20. Lee, Sik-Yum & Song, Xin-Yuan, 2008. "On Bayesian estimation and model comparison of an integrated structural equation model," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4814-4827, June.
    21. Sanjiv R. Das & Kris James Mitchener & Angela Vossmeyer, 2018. "Bank Regulation, Network Topology, and Systemic Risk: Evidence from the Great Depression," NBER Working Papers 25405, National Bureau of Economic Research, Inc.
    22. Ralf van der Lans & Bram Van den Bergh & Evelien Dieleman, 2014. "Partner Selection in Brand Alliances: An Empirical Investigation of the Drivers of Brand Fit," Marketing Science, INFORMS, vol. 33(4), pages 551-566, July.
    23. Reichl Johannes, 2020. "Estimating marginal likelihoods from the posterior draws through a geometric identity," Monte Carlo Methods and Applications, De Gruyter, vol. 26(3), pages 205-221, September.
    24. 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.
    25. Davide Ravagli & Georgi N. Boshnakov, 2022. "Bayesian analysis of mixture autoregressive models covering the complete parameter space," Computational Statistics, Springer, vol. 37(3), pages 1399-1433, July.
    26. Chen, Cathy W.S. & Chan, Jennifer S.K. & So, Mike K.P. & Lee, Kevin K.M., 2011. "Classification in segmented regression problems," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2276-2287, July.
    27. WATANABE, Toshiaki, 2025. "Bayesian Analysis of Business Cycles in Japan by Extending the Markov Switching Model," Discussion paper series HIAS-E-148, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
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    2. Jan Willem Nijenhuis, 2021. "Estimation of ordered probit model with endogenous switching between two latent regimes," 2021 Stata Conference 22, Stata Users Group.
    3. Flossmann Anton L. & Pohlmeier Winfried, 2006. "Causal Returns to Education: A Survey on Empirical Evidence for Germany," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 226(1), pages 6-23, February.
    4. Munkin, Murat K. & Trivedi, Pravin K., 2008. "Bayesian analysis of the ordered probit model with endogenous selection," Journal of Econometrics, Elsevier, vol. 143(2), pages 334-348, April.
    5. Jaeun Choi & A. James O'Malley, 2017. "Estimating the causal effect of treatment in observational studies with survival time end points and unmeasured confounding," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(1), pages 159-185, January.
    6. Li, Mingliang & Tobias, Justin L., 2011. "Bayesian inference in a correlated random coefficients model: Modeling causal effect heterogeneity with an application to heterogeneous returns to schooling," Journal of Econometrics, Elsevier, vol. 162(2), pages 345-361, June.
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    8. Ishdorj, Ariun & Crepinsek, Mary Kay & Jensen, Helen H., "undated". "Children’s Consumption of Fruits and Vegetables: Do School Environment and Policies Affect Choice in School Meals?," 2012 AAEA/EAAE Food Environment Symposium 123534, Agricultural and Applied Economics Association.
    9. Mingliang Li & Dale J. Poirier & Justin L. Tobias, 2004. "Do dropouts suffer from dropping out? Estimation and prediction of outcome gains in generalized selection models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(2), pages 203-225.
    10. Dominic Coey, 2013. "Physician Incentives and Treatment Choices in Heart Attack Management," Discussion Papers 12-027, Stanford Institute for Economic Policy Research.
    11. Barton H. Hamilton, 2001. "Estimating treatment effects in randomized clinical trials with non‐compliance: the impact of maternal smoking on birthweight," Health Economics, John Wiley & Sons, Ltd., vol. 10(5), pages 399-410, July.
    12. Ishdorj, Ariun & Crepinsek, Mary Kay & Jensen, Helen H., 2013. "Children's Consumption of Fruits and Vegetables: Do School Environment and Policies Affect Choice At School and Away from School?," Staff General Research Papers Archive 36020, Iowa State University, Department of Economics.
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    15. BAUWENS, Luc & ROMBOUTS, Jeroen, 2003. "Bayesian clustering of many GARCH models," LIDAM Discussion Papers CORE 2003087, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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    19. Ishdorj, Ariun & Jensen, Helen H. & Tobias, Justin, 2007. "Intra-Household Allocation and Consumption of WIC-Approved Foods: A Bayesian Approach," Staff General Research Papers Archive 12833, Iowa State University, Department of Economics.
    20. Pedro Carneiro & Karsten T. Hansen & James J. Heckman, 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College," NBER Working Papers 9546, National Bureau of Economic Research, Inc.
    21. Du Juan, 2012. "Formal and Informal Care: An Empirical Bayesian Analysis Using the Two-part Model," Forum for Health Economics & Policy, De Gruyter, vol. 15(1), pages 1-42, November.
    22. Boyuan Zhang, 2022. "Incorporating Prior Knowledge of Latent Group Structure in Panel Data Models," Papers 2211.16714, arXiv.org, revised Oct 2023.
    23. Andrei A. Sirchenko, 2017. "An endogenous regime-switching model of ordered choice with an application to federal funds rate target," 2017 Papers psi424, Job Market Papers.
    24. Maksym Obrizan, 2011. "A Bayesian Model of Sample Selection with a Discrete Outcome Variable: Detecting Depression in Older Adults," Discussion Papers 41, Kyiv School of Economics.
    25. Chib, Siddhartha, 2007. "Analysis of treatment response data without the joint distribution of potential outcomes," Journal of Econometrics, Elsevier, vol. 140(2), pages 401-412, October.
    26. Ishdorj, Ariun & Jensen, Helen H. & Crepinsek, Mary Kay, 2012. "Children’s Consumption of Fruits and Vegetables: Do School Environment and Policies Affect Choice At School and Away from School?," Hebrew University of Jerusalem Archive 133051, Hebrew University of Jerusalem.
    27. L.G. Leon-Novelo & X. Zhou & B. Nebiyou Bekele & P. Müller, 2010. "Assessing Toxicities in a Clinical Trial: Bayesian Inference for Ordinal Data Nested within Categories," Biometrics, The International Biometric Society, vol. 66(3), pages 966-974, September.
    28. Browne, William J., 2006. "MCMC algorithms for constrained variance matrices," Computational Statistics & Data Analysis, Elsevier, vol. 50(7), pages 1655-1677, April.
    29. Justin Tobias, 2006. "Estimation, Learning and Parameters of Interest in a Multiple Outcome Selection Model," Econometric Reviews, Taylor & Francis Journals, vol. 25(1), pages 1-40.
    30. Ishdorj, Ariun & Jensen, Helen H. & Tobias, Justin, 2007. "Intra-Household Allocation and Consumption of WIC-Approved Foods: A Bayesian Approach," Hebrew University of Jerusalem Archive 9239, Hebrew University of Jerusalem.
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    34. Chib, Siddhartha & Jacobi, Liana, 2008. "Analysis of treatment response data from eligibility designs," Journal of Econometrics, Elsevier, vol. 144(2), pages 465-478, June.
    35. Roberto Leon Gonzalez, "undated". "A Panel Data Simultaneous Equation Model with a Dependent Categorical Variable and Selectivity," Discussion Papers 01/04, Department of Economics, University of York.
    36. Yulia V. Marchenko & Marc G. Genton, 2012. "A Heckman Selection- t Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(497), pages 304-317, March.
    37. Jacobi, Liana & Wagner, Helga & Frühwirth-Schnatter, Sylvia, 2016. "Bayesian treatment effects models with variable selection for panel outcomes with an application to earnings effects of maternity leave," Journal of Econometrics, Elsevier, vol. 193(1), pages 234-250.
    38. Maria Ana Odejar & Kostas Mavromaras & Mandy Ryan, 2004. "Messy Data Modelling in Health Care Contingent Valuation Studies," Econometric Society 2004 North American Summer Meetings 406, Econometric Society.
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    1. Mueller, Milton L. & Park, Yuri & Lee, Jongsu & Kim, Tai-Yoo, 2006. "Digital identity: How users value the attributes of online identifiers," Information Economics and Policy, Elsevier, vol. 18(4), pages 405-422, November.
    2. Zhu, Siying & Cai, Yutong & Wang, Mengtong & Wang, Hua & Meng, Qiang, 2023. "How will China–Singapore International Land–Sea Trade Corridor affect route choice behaviour? A discrete choice model," Transport Policy, Elsevier, vol. 144(C), pages 11-22.
    3. Christian Helmers & Pramila Krishnan & Manasa Patnam, 2015. "Attention and Saliency on the Internet: Evidence from an Online Recommendation System," Cambridge Working Papers in Economics 1563, Faculty of Economics, University of Cambridge.
    4. Roger Haefen, 2008. "Latent Consideration Sets and Continuous Demand Systems," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 41(3), pages 363-379, November.
    5. Pilli, Luis & Swait, Joffre & Mazzon, José Afonso, 2022. "Jeopardizing brand profitability by misattributing process heterogeneity to preference heterogeneity," Journal of choice modelling, Elsevier, vol. 43(C).
    6. Zhenghui Sha & Yun Huang & Jiawei Sophia Fu & Mingxian Wang & Yan Fu & Noshir Contractor & Wei Chen, 2018. "A Network-Based Approach to Modeling and Predicting Product Coconsideration Relations," Complexity, Hindawi, vol. 2018, pages 1-14, January.
    7. Maria Ana Vitorino & Ali Hortacsu & Elisabeth Honka, 2014. "Advertising, Consumer Awareness and Choice: Evidence from the U.S. Banking Industry," 2014 Meeting Papers 574, Society for Economic Dynamics.
    8. Kim, Yeonbae, 2005. "Estimation of consumer preferences on new telecommunications services: IMT-2000 service in Korea," Information Economics and Policy, Elsevier, vol. 17(1), pages 73-84, January.
    9. Han Qiu, 2018. "An Inattention Model for Traveler Behavior with e-Coupons," Papers 1901.05070, arXiv.org.
    10. Hicks, Robert L. & Schnier, Kurt E., 2010. "Spatial regulations and endogenous consideration sets in fisheries," Resource and Energy Economics, Elsevier, vol. 32(2), pages 117-134, April.
    11. Siddhartha Chib & Kenichi Shimizu, 2023. "Scalable Estimation of Multinomial Response Models with Random Consideration Sets," Papers 2308.12470, arXiv.org, revised Sep 2025.
    12. Gallego, Guillermo & Li, Anran & Truong, Van-Anh & Wang, Xinshang, 2020. "Approximation algorithms for product framing and pricing," LSE Research Online Documents on Economics 101983, London School of Economics and Political Science, LSE Library.
    13. Griffith, Rachel & Crawford, Gregory & Iaria, Alessandro, 2016. "Preference Estimation with Unobserved Choice Set Heterogeneity using Sufficient Sets," CEPR Discussion Papers 11675, C.E.P.R. Discussion Papers.
    14. Joseph Pancras, 2010. "A Framework to Determine the Value of Consumer Consideration Set Information for Firm Pricing Strategies," Computational Economics, Springer;Society for Computational Economics, vol. 35(3), pages 269-300, March.
    15. Vroomen, Bjorn & Hans Franses, Philip & van Nierop, Erjen, 2004. "Modeling consideration sets and brand choice using artificial neural networks," European Journal of Operational Research, Elsevier, vol. 154(1), pages 206-217, April.
    16. Michelle Sovinsky Goeree, 2005. "Advertising in the US Personal Computer Industry," Industrial Organization 0503002, University Library of Munich, Germany.
    17. Cascetta, Ennio & Papola, Andrea, 2009. "Dominance among alternatives in random utility models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(2), pages 170-179, February.
    18. Crawford, Gregory S. & Griffith, Rachel & Iaria, Alessandro, 2021. "A survey of preference estimation with unobserved choice set heterogeneity," Journal of Econometrics, Elsevier, vol. 222(1), pages 4-43.
    19. Alicia Barroso & Gerard Llobet, 2011. "Advertising and Consumer Awareness of New, Differentiated Products," Working Papers wp2011_1104, CEMFI.
    20. Yusufcan Masatlioglu & Daisuke Nakajima & Erkut Y. Ozbay, 2012. "Revealed Attention," American Economic Review, American Economic Association, vol. 102(5), pages 2183-2205, August.
    21. Erik Brynjolfsson & Astrid Dick & Michael Smith, 2010. "A nearly perfect market?," Quantitative Marketing and Economics (QME), Springer, vol. 8(1), pages 1-33, March.
    22. Michael Cohen & Rui Huang & Chen Zhu, 2012. "The Use of Voluntary Marketing Initiatives to Improve the Nutritional Profile of Kids Cereals," Working Papers 11, University of Connecticut, Department of Agricultural and Resource Economics, Charles J. Zwick Center for Food and Resource Policy.
    23. Anocha Aribarg & Thomas Otter & Daniel Zantedeschi & Greg M. Allenby & Taylor Bentley & David J. Curry & Marc Dotson & Ty Henderson & Elisabeth Honka & Rajeev Kohli & Kamel Jedidi & Stephan Seiler & X, 2018. "Advancing Non-compensatory Choice Models in Marketing," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 5(1), pages 82-92, March.
    24. Steffen Jahn & Daniel Guhl & Ainslee Erhard, 2024. "Substitution Patterns and Price Response for Plant-Based Meat Alternatives," Rationality and Competition Discussion Paper Series 509, CRC TRR 190 Rationality and Competition.
    25. Lee, Jongsu & Kim, Yeonbae & Lee, Jeong-Dong & Park, Yuri, 2006. "Estimating the extent of potential competition in the Korean mobile telecommunications market: Switching costs and number portability," International Journal of Industrial Organization, Elsevier, vol. 24(1), pages 107-124, January.
    26. Roy Allen, 2024. "Exogenous Consideration and Extended Random Utility," Papers 2405.13945, arXiv.org.
    27. Allen, Roy & Rehbeck, John, 2024. "Latent utility and permutation invariance: A revealed preference approach," Journal of Econometrics, Elsevier, vol. 244(1).
    28. Arana, Jorge E. & Leon, Carmelo J., 2005. "Flexible mixture distribution modeling of dichotomous choice contingent valuation with heterogenity," Journal of Environmental Economics and Management, Elsevier, vol. 50(1), pages 170-188, July.
    29. Marco A. Palma, 2017. "Improving the prediction of ranking data," Empirical Economics, Springer, vol. 53(4), pages 1681-1710, December.
    30. Vardit Landsman & Moshe Givon, 2010. "The diffusion of a new service: Combining service consideration and brand choice," Quantitative Marketing and Economics (QME), Springer, vol. 8(1), pages 91-121, March.
    31. Assele, Samson Yaekob & Meulders, Michel & Vandebroek, Martina, 2022. "The value of consideration data in a discrete choice experiment," Journal of choice modelling, Elsevier, vol. 45(C).
    32. Lee, Younghwan, 2019. "Fast computation algorithm for the random consideration set model," Economics Letters, Elsevier, vol. 179(C), pages 38-41.
    33. Bleile, Jörg, 2016. "Limited Attention in Case-Based Belief Formation," Center for Mathematical Economics Working Papers 518, Center for Mathematical Economics, Bielefeld University.
    34. Yeonbae Kim & Jeong-Dong Lee & Daeyoung Koh, 2005. "Effects of consumer preferences on the convergence of mobile telecommunications devices," Applied Economics, Taylor & Francis Journals, vol. 37(7), pages 817-826.
    35. Ahn, Jiwoon & Jeong, Gicheol & Kim, Yeonbae, 2008. "A forecast of household ownership and use of alternative fuel vehicles: A multiple discrete-continuous choice approach," Energy Economics, Elsevier, vol. 30(5), pages 2091-2104, September.
    36. J. DeShazo & Trudy Cameron & Manrique Saenz, 2009. "The Effect of Consumers’ Real-World Choice Sets on Inferences from Stated Preference Surveys," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 42(3), pages 319-343, March.
    37. Guillermo Gallego & Anran Li & Van-Anh Truong & Xinshang Wang, 2020. "Approximation Algorithms for Product Framing and Pricing," Operations Research, INFORMS, vol. 68(1), pages 134-160, January.
    38. Araña, Jorge E. & León, Carmelo J. & Hanemann, Michael W., 2008. "Emotions and decision rules in discrete choice experiments for valuing health care programmes for the elderly," Journal of Health Economics, Elsevier, vol. 27(3), pages 753-769, May.

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    1. Bauwens, Luc & Rombouts, Jeroen V.K., 2012. "On marginal likelihood computation in change-point models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3415-3429.
    2. Sylvia Kaufmann, 2001. "Is there an asymmetric effect on monetary policy over time? A bayesian analysis using Austrian data," Working Papers 45, Oesterreichische Nationalbank (Austrian Central Bank).
    3. Francesco Bianchi & Cosmin Ilut, 2014. "Monetary/Fiscal Policy Mix and Agents' Beliefs," NBER Working Papers 20194, National Bureau of Economic Research, Inc.
    4. Paap, R. & Segers, R. & van Dijk, D.J.C., 2007. "Do leading indicators lead peaks more than troughs?," Econometric Institute Research Papers EI 2007-08, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Antonio Pacifico, 2018. "Panel Bayesian VAR Modeling for Policy and Forecasting when dealing with confounding and latent effects," EERI Research Paper Series EERI RP 2018/15, Economics and Econometrics Research Institute (EERI), Brussels.
    6. Wilkinson, Darren J & KH Yeung, Stephen, 2004. "A sparse matrix approach to Bayesian computation in large linear models," Computational Statistics & Data Analysis, Elsevier, vol. 44(3), pages 493-516, January.
    7. S. Bordignon & D. Raggi, 2010. "Long memory and nonlinearities in realized volatility: a Markov switching approach," Working Papers 694, Dipartimento Scienze Economiche, Universita' di Bologna.
    8. Du, Kai & Huddart, Steven & Xue, Lingzhou & Zhang, Yifan, 2020. "Using a hidden Markov model to measure earnings quality," Journal of Accounting and Economics, Elsevier, vol. 69(2).
    9. Philippe J. Deschamps, 2008. "Comparing smooth transition and Markov switching autoregressive models of US unemployment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(4), pages 435-462.
    10. Sylvia Frühwirth‐Schnatter & Sylvia Kaufmann, 2006. "How do changes in monetary policy affect bank lending? An analysis of Austrian bank data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 275-305, April.
    11. Jia Liu & John M. Maheu & Yong Song, 2024. "Identification and forecasting of bull and bear markets using multivariate returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 723-745, August.
    12. Sylvia Kaufmann, 2014. "K-state switching models with time-varying transition distributions – Does credit growth signal stronger effects of variables on inflation?," Working Papers 14.04, Swiss National Bank, Study Center Gerzensee.
    13. Monica Billio & Roberto Casarin & Anthony Osuntuyi, 2012. "Efficient Gibbs Sampling for Markov Switching GARCH Models," Working Papers 2012:35, Department of Economics, University of Venice "Ca' Foscari".
    14. Luc Bauwens & Arnaud Dufays & Jeroen V.K. Rombouts, 2011. "Marginal Likelihood for Markov-Switching and Change-Point GARCH Models," Cahiers de recherche 1138, CIRPEE.
    15. Rosychuk, Rhonda J. & Shofiqul Islam, 2009. "Parameter estimation in a model for misclassified Markov data -- a Bayesian approach," Computational Statistics & Data Analysis, Elsevier, vol. 53(11), pages 3805-3816, September.
    16. Lütkepohl, Helmut & Woźniak, Tomasz, 2020. "Bayesian inference for structural vector autoregressions identified by Markov-switching heteroskedasticity," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    17. Beutler, Toni & Gubler, Matthias & Hauri, Simona & Kaufmann, Sylvia, 2021. "Bank lending in Switzerland: Driven by business models and exposed to uncertainty," International Review of Financial Analysis, Elsevier, vol. 78(C).
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    30. Sarferaz, Samad & Uebele, Martin, 2009. "Tracking down the business cycle: A dynamic factor model for Germany 1820-1913," Explorations in Economic History, Elsevier, vol. 46(3), pages 368-387, July.
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    33. Michael T. Owyang & Garey Ramey, 2003. "Regime switching and monetary policy measurement," Working Papers 2001-002, Federal Reserve Bank of St. Louis.
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    45. Lynn Kuo & Jun Ying & Gim S. Seow, 2005. "Forecasting stock prices using a hierarchical Bayesian approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(1), pages 39-59.
    46. Fong, Pak Wing & Li, Wai Keung, 2003. "On time series with randomized unit root and randomized seasonal unit root," Computational Statistics & Data Analysis, Elsevier, vol. 43(3), pages 369-395, July.
    47. Tsai-Hung Fan & Yi-Fu Wang & Yi-Chen Zhang, 2014. "Bayesian model selection in linear mixed effects models with autoregressive(p) errors using mixture priors," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(8), pages 1814-1829, August.
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    1. Dufrénot, Gilles & Malik, Sheheryar, 2012. "The changing role of house price dynamics over the business cycle," Economic Modelling, Elsevier, vol. 29(5), pages 1960-1967.
    2. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2013. "Interactions between Eurozone and US Booms and Busts: A Bayesian Panel Markov-switching VAR Model," Tinbergen Institute Discussion Papers 13-142/III, Tinbergen Institute, revised 01 Nov 2014.
    3. Sylvia Kaufmann, 2001. "Is there an asymmetric effect on monetary policy over time? A bayesian analysis using Austrian data," Working Papers 45, Oesterreichische Nationalbank (Austrian Central Bank).
    4. Daniel Aromi & Marcos Dal Bianco, 2014. "Un analisis de los desequilibrios del tipo de cambio real argentino bajo cambios de regimen," Working Papers 1431, BBVA Bank, Economic Research Department.
    5. Marcelle Chauvet & Elcyon C. R. Lima & Brisne Vasquez, 2015. "Forecasting Brazilian Output in Real Time in the Presence of breaks: a Comparison Of Linear and Nonlinear Models," Discussion Papers 0118, Instituto de Pesquisa Econômica Aplicada - IPEA.
    6. Owyang, Michael T. & Piger, Jeremy M. & Wall, Howard J. & Wheeler, Christopher H., 2008. "The economic performance of cities: A Markov-switching approach," Journal of Urban Economics, Elsevier, vol. 64(3), pages 538-550, November.
    7. Paap, R. & Segers, R. & van Dijk, D.J.C., 2007. "Do leading indicators lead peaks more than troughs?," Econometric Institute Research Papers EI 2007-08, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Battulga Gankhuu, 2021. "Options Pricing under Bayesian MS-VAR Process," Papers 2109.05998, arXiv.org, revised Sep 2024.
    9. Marcelle Chauvet, 2001. "The Brazilian Economic Fluctuations," Anais do XXIX Encontro Nacional de Economia [Proceedings of the 29th Brazilian Economics Meeting] 033, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    10. S. Bordignon & D. Raggi, 2010. "Long memory and nonlinearities in realized volatility: a Markov switching approach," Working Papers 694, Dipartimento Scienze Economiche, Universita' di Bologna.
    11. Philippe J. Deschamps, 2008. "Comparing smooth transition and Markov switching autoregressive models of US unemployment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(4), pages 435-462.
    12. Sylvia Frühwirth‐Schnatter & Sylvia Kaufmann, 2006. "How do changes in monetary policy affect bank lending? An analysis of Austrian bank data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 275-305, April.
    13. Christos Merkatas & Simo Särkkä, 2023. "System identification using autoregressive Bayesian neural networks with nonparametric noise models," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(3), pages 319-330, May.
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    15. Andrew Ang & Allan Timmermann, 2011. "Regime Changes and Financial Markets," NBER Working Papers 17182, National Bureau of Economic Research, Inc.
    16. Silvestro Di Sanzo, 2007. "Forecasting Time Series with Long Memory and Level Shifts, A Bayesian Approach," Working Papers 2007_03, Department of Economics, University of Venice "Ca' Foscari".
    17. Basturk, N. & Paap, R. & van Dijk, D.J.C., 2010. "Financial Development and Convergence Clubs," Econometric Institute Research Papers EI 2010-52, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    18. Favero, Carlo A. & Giglio, Stefano, 2006. "Fiscal Policy and the Term Structure: Evidence from the Case of Italy in the EMS and the EMU Periods," CEPR Discussion Papers 5793, C.E.P.R. Discussion Papers.
    19. John M. Maheu & Qiao Yang, 2015. "An Infinite Hidden Markov Model for Short-term Interest Rates," Working Paper series 15-05, Rimini Centre for Economic Analysis.
    20. Liu, Wen-Hsien & Chyi, Yih-Luan, 2006. "A Markov regime-switching model for the semiconductor industry cycles," Economic Modelling, Elsevier, vol. 23(4), pages 569-578, July.
    21. 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.
    22. Çakmaklı, Cem & Paap, Richard & van Dijk, Dick, 2013. "Measuring and predicting heterogeneous recessions," Journal of Economic Dynamics and Control, Elsevier, vol. 37(11), pages 2195-2216.
    23. Marcelle Chauvet & James D. Hamilton, 2005. "Dating Business Cycle Turning Points," NBER Working Papers 11422, National Bureau of Economic Research, Inc.
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    96. Ofer Mintz & Imran S. Currim & Ivan Jeliazkov, 2013. "Information Processing Pattern and Propensity to Buy: An Investigation of Online Point-of-Purchase Behavior," Marketing Science, INFORMS, vol. 32(5), pages 716-732, September.
    97. Ishdorj, Ariun & Jensen, Helen H. & Tobias, Justin, 2007. "Intra-Household Allocation and Consumption of WIC-Approved Foods: A Bayesian Approach," Hebrew University of Jerusalem Archive 9239, Hebrew University of Jerusalem.
    98. Lapar, M. L. & Holloway, G. & Ehui, S., 2003. "Policy options promoting market participation among smallholder livestock producers: a case study from the Phillipines," Food Policy, Elsevier, vol. 28(3), pages 187-211, June.
    99. Delgado, Christopher L. & Ehui, Simeon K. & Holloway, Garth & Nicholson, Charles F. & Staal, Steven, 1999. "Agroindustrialization through institutional innovation: transactions costs, cooperatives and milk-market development in the Ethiopian highlands," MTID discussion papers 35, International Food Policy Research Institute (IFPRI).
    100. Arana, Jorge E. & Leon, Carmelo J., 2005. "Flexible mixture distribution modeling of dichotomous choice contingent valuation with heterogenity," Journal of Environmental Economics and Management, Elsevier, vol. 50(1), pages 170-188, July.
    101. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2025. "Forecasting with shadow rate VARs," Quantitative Economics, Econometric Society, vol. 16(3), pages 795-822, July.
    102. Garth Holloway & Simeon Ehui & Amare Teklu, 2008. "Bayes estimates of distance-to-market: transactions costs, cooperatives and milk-market development in the Ethiopian highlands," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(5), pages 683-696.
    103. Lee, Lung-fei, 1999. "Estimation of dynamic and ARCH Tobit models," Journal of Econometrics, Elsevier, vol. 92(2), pages 355-390, October.
    104. Lapar, Ma. Lucila A. & Holloway, Garth J. & Ehui, Simeon K., 2003. "How Big Is Your Neighborhood? Spatial Implications Of Market Participation By Smallholder Livestock Producers," 2003 Annual Meeting, August 16-22, 2003, Durban, South Africa 25860, International Association of Agricultural Economists.
    105. Yuta Kurose & Yasuhiro Omori & Akira Hibiki, 2014. "A Discrete/Continuous Choice Model on a Nonconvex Budget Set," CIRJE F-Series CIRJE-F-942, CIRJE, Faculty of Economics, University of Tokyo.
    106. Jensen, Uwe & Gartner, Hermann & Rässler, Susanne, 2006. "Measuring overeducation with earnings frontiers and multiply imputed censored income data," IAB-Discussion Paper 200611, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    107. Han Liu & Heng Liu & Leihua Geng, 2024. "Analysis of Industrial Water Use Efficiency Based on SFA–Tobit Panel Model in China," Sustainability, MDPI, vol. 16(19), pages 1-12, October.
    108. Barton H. Hamilton, 1999. "HMO selection and Medicare costs: Bayesian MCMC estimation of a robust panel data tobit model with survival," Health Economics, John Wiley & Sons, Ltd., vol. 8(5), pages 403-414, August.
    109. Araña, Jorge E. & León, Carmelo J., 2008. "Do emotions matter? Coherent preferences under anchoring and emotional effects," Ecological Economics, Elsevier, vol. 66(4), pages 700-711, July.

  44. Tiwari, R C & Jammalamadaka, S R & Chib, Siddhartha, 1988. "Bayes Prediction Density and Regression Estimation--A Semiparametric Approach," Empirical Economics, Springer, vol. 13(3/4), pages 209-222.

    Cited by:

    1. Mark J. Jensen & John M. Maheu, 2008. "Bayesian semiparametric stochastic volatility modeling," FRB Atlanta Working Paper 2008-15, Federal Reserve Bank of Atlanta.
    2. Chib, Siddhartha & Hamilton, Barton H., 2002. "Semiparametric Bayes analysis of longitudinal data treatment models," Journal of Econometrics, Elsevier, vol. 110(1), pages 67-89, September.
    3. Mark J. Jensen, 2004. "Semiparametric Bayesian Inference of Long‐Memory Stochastic Volatility Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(6), pages 895-922, November.
    4. 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. Fisher, Mark & Jensen, Mark J., 2019. "Bayesian inference and prediction of a multiple-change-point panel model with nonparametric priors," Journal of Econometrics, Elsevier, vol. 210(1), pages 187-202.
    6. Han, Yufeng, 2012. "State uncertainty in stock markets: How big is the impact on the cost of equity?," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2575-2592.

  45. Chib, Siddhartha & Tiwari, Ram C. & Jammalamadaka, S. Rao, 1988. "Bayes prediction in regressions with elliptical errors," Journal of Econometrics, Elsevier, vol. 38(3), pages 349-360, July.

    Cited by:

    1. Saverio Ranciati & Giuliano Galimberti & Gabriele Soffritti, 2019. "Bayesian variable selection in linear regression models with non-normal errors," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(2), pages 323-358, June.
    2. Kibria, B. M. Golam & Haq, M. Safiul, 1999. "Predictive Inference for the Elliptical Linear Model," Journal of Multivariate Analysis, Elsevier, vol. 68(2), pages 235-249, February.
    3. Osiewalski, Jacek & Steel, Mark F.J., 1992. "Posterior moments of scale parameters in elliptical regression models," UC3M Working papers. Economics 10879, Universidad Carlos III de Madrid. Departamento de Economía.
    4. Peter C.B. Phillips, 1987. "Conditional and Unconditional Statistical Independence," Cowles Foundation Discussion Papers 824R, Cowles Foundation for Research in Economics, Yale University, revised Dec 1987.
    5. Siddhartha Chib & Srikanth Ramamurthy, 2014. "DSGE Models with Student- t Errors," Econometric Reviews, Taylor & Francis Journals, vol. 33(1-4), pages 152-171, June.
    6. Osiewalski, J. & Steel, M.F.J., 1989. "A Bayesian analysis of exogeneity in models pooling time-series and cross-section data," Discussion Paper 1989-14, Tilburg University, Center for Economic Research.
    7. Ng, Vee Ming, 2002. "Robust Bayesian Inference for Seemingly Unrelated Regressions with Elliptical Errors," Journal of Multivariate Analysis, Elsevier, vol. 83(2), pages 409-414, November.
    8. Kibria, B.M. Golam, 2006. "The matrix-t distribution and its applications in predictive inference," Journal of Multivariate Analysis, Elsevier, vol. 97(3), pages 785-795, March.
    9. Osiewalski, J. & Steel, M.F.J., 1991. "Bayesian marginal equivalence of elliptical regression models," Other publications TiSEM 9ecaf734-de5e-42e4-9017-8, Tilburg University, School of Economics and Management.
    10. Kim, Hyoung-Moon & Mallick, Bani K., 2003. "A note on Bayesian spatial prediction using the elliptical distribution," Statistics & Probability Letters, Elsevier, vol. 64(3), pages 271-276, September.
    11. Zellner, Arnold & Ando, Tomohiro, 2010. "Bayesian and non-Bayesian analysis of the seemingly unrelated regression model with Student-t errors, and its application for forecasting," International Journal of Forecasting, Elsevier, vol. 26(2), pages 413-434, April.
    12. Liu, Jin Shan & Ip, Wai Cheung & Wong, Heung, 2009. "Predictive inference for singular multivariate elliptically contoured distributions," Journal of Multivariate Analysis, Elsevier, vol. 100(7), pages 1440-1446, August.
    13. Jiang, Jie & Wang, Lichun, 2024. "Bayes minimax estimator of the mean vector in an elliptically contoured distribution," Statistics & Probability Letters, Elsevier, vol. 213(C).

  46. Jammalamadaka, S. Rao & Tiwari, Ram C. & Chib, Siddhartha, 1987. "Bayes prediction in the linear model with spherically symmetric errors," Economics Letters, Elsevier, vol. 24(1), pages 39-44.

    Cited by:

    1. Osiewalski, Jacek & Steel, Mark F.J., 1992. "Posterior moments of scale parameters in elliptical regression models," UC3M Working papers. Economics 10879, Universidad Carlos III de Madrid. Departamento de Economía.
    2. Díaz-García, José A. & Gutiérrez-Jáimez, Ramón, 2011. "Distributions of the compound and scale mixture of vector and spherical matrix variate elliptical distributions," Journal of Multivariate Analysis, Elsevier, vol. 102(1), pages 143-152, January.
    3. Osiewalski, J. & Steel, M.F.J., 1991. "Bayesian marginal equivalence of elliptical regression models," Other publications TiSEM 9ecaf734-de5e-42e4-9017-8, Tilburg University, School of Economics and Management.

  47. Basu, Parantap & Chib, Siddhartha, 1985. "Equity premium in a production economy : A parametric example," Economics Letters, Elsevier, vol. 18(1), pages 53-58.

    Cited by:

    1. Kogan, Leonid, 2004. "Asset prices and real investment," Journal of Financial Economics, Elsevier, vol. 73(3), pages 411-431, September.

Chapters

  1. Siddhartha Chib & Yasuhiro Omori & Manabu Asai, 2009. "Multivariate Stochastic Volatility," Springer Books, in: Thomas Mikosch & Jens-Peter Kreiß & Richard A. Davis & Torben Gustav Andersen (ed.), Handbook of Financial Time Series, chapter 16, pages 365-400, Springer.
    See citations under working paper version above.
  2. Chib, Siddhartha, 2001. "Markov chain Monte Carlo methods: computation and inference," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 57, pages 3569-3649, Elsevier.

    Cited by:

    1. Congressional Budget Office, 2022. "Quantifying the Uncertainty of Long-Term Economic Projections: Working Paper 2022-07," Working Papers 57711, Congressional Budget Office.
    2. Song, Zefang & Song, Xinyuan & Li, Yuan, 2023. "Bayesian Analysis of ARCH-M model with a dynamic latent variable," Econometrics and Statistics, Elsevier, vol. 28(C), pages 47-62.
    3. Yuko Onishi & Yasuhiro Omori, 2016. "Bayesian Estimation of Entry Games with Multiple Players and Multiple Equilibria," The Japanese Economic Review, Springer, vol. 67(4), pages 418-440, December.
    4. Sofia Anyfantaki & Antonis Demos, 2012. "Estimation and Properties of a Time-Varying EGARCH(1,1) in Mean Model," DEOS Working Papers 1228, Athens University of Economics and Business.
    5. Sylvia Frühwirth‐Schnatter & Sylvia Kaufmann, 2006. "How do changes in monetary policy affect bank lending? An analysis of Austrian bank data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 275-305, April.
    6. Paolo Girardello & Orietta Nicolis & Giovanni Tondini, 2003. "Comparing Conditional Variance Models: Theory and Empirical Evidence," Multinational Finance Journal, Multinational Finance Journal, vol. 7(3-4), pages 177-206, September.
    7. Moshe Buchinsky & Denis Fougère & Francis Kramarz & Rusty Tchernis, 2008. "Interfirm Mobility, Wages, and the Returns to Seniority and Experience in the U.S," CAEPR Working Papers 2008-006, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    8. Yuta Kurose, 2021. "Stochastic volatility model with range-based correction and leverage," Papers 2110.00039, arXiv.org, revised Oct 2021.
    9. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.
    10. Coşkun Akdeniz, 2021. "Construction of the Monetary Conditions Index with TVP-VAR Model: Empirical Evidence for Turkish Economy," Springer Books, in: Burcu Adıgüzel Mercangöz (ed.), Handbook of Research on Emerging Theories, Models, and Applications of Financial Econometrics, edition 1, pages 215-228, Springer.
    11. Christoph Berninger & Almond Stöcker & David Rügamer, 2022. "A Bayesian time‐varying autoregressive model for improved short‐term and long‐term prediction," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 181-200, January.
    12. John M. Maheu & Stephen Gordon, 2004. "Learning, Forecasting and Structural Breaks," Cahiers de recherche 0422, CIRPEE.
    13. Koji Miyawaki & Yasuhiro Omori & Akira Hibiki, 2009. "Bayesian Estimation of Demand Functions under Block Rate Pricing," CIRJE F-Series CIRJE-F-631, CIRJE, Faculty of Economics, University of Tokyo.
    14. Marcelle Chauvet & Simon Potter, 2005. "Forecasting recessions using the yield curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(2), pages 77-103.
    15. Chib, Siddhartha & Jacobi, Liana, 2007. "Modeling and calculating the effect of treatment at baseline from panel outcomes," Journal of Econometrics, Elsevier, vol. 140(2), pages 781-801, October.
    16. Omori, Yasuhiro & Watanabe, Toshiaki, 2008. "Block sampler and posterior mode estimation for asymmetric stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2892-2910, February.
    17. Czado, Claudia & Delwarde, Antoine & Denuit, Michel, 2005. "Bayesian Poisson log-bilinear mortality projections," Insurance: Mathematics and Economics, Elsevier, vol. 36(3), pages 260-284, June.
    18. Vasco Cúrdia & Ricardo Reis, 2010. "Correlated Disturbances and U.S. Business Cycles," NBER Working Papers 15774, National Bureau of Economic Research, Inc.
    19. Nakajima, Jouchi & Omori, Yasuhiro, 2009. "Leverage, heavy-tails and correlated jumps in stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2335-2353, April.
    20. Jouchi Nakajima, 2011. "Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 29, pages 107-142, November.
    21. Anatoliy Belaygorod & Michael J. Dueker, 2007. "The price puzzle and indeterminacy in an estimated DSGE model," Working Papers 2006-025, Federal Reserve Bank of St. Louis.
    22. Nakajima, Jouchi & Kasuya, Munehisa & Watanabe, Toshiaki, 2011. "Bayesian analysis of time-varying parameter vector autoregressive model for the Japanese economy and monetary policy," Journal of the Japanese and International Economies, Elsevier, vol. 25(3), pages 225-245, September.
    23. Omori, Yasuhiro, 2007. "Efficient Gibbs sampler for Bayesian analysis of a sample selection model," Statistics & Probability Letters, Elsevier, vol. 77(12), pages 1300-1311, July.
    24. Nima Nonejad, 2013. "Time-Consistency Problem and the Behavior of US Inflation from 1970 to 2008," CREATES Research Papers 2013-25, Department of Economics and Business Economics, Aarhus University.
    25. Lucciano Villacorta, 2016. "Estimating Country Heterogeneity in Capital - Labor Substitution Using Panel Data," Working Papers Central Bank of Chile 788, Central Bank of Chile.
    26. Keisuke Kondo, 2022. "Spatial dependence in regional business cycles: evidence from Mexican states," Journal of Spatial Econometrics, Springer, vol. 3(1), pages 1-46, December.
    27. Michael Koenig & Claudio Tessone & Yves Zenou, 2012. "Nestedness in Networks: A Theoretical Model and Some Applications," Discussion Papers 11-003, Stanford Institute for Economic Policy Research.
    28. Andrea Brasili & Loredana Federico, 2008. "Recent Developments in Productivity and the Role of Entrepreneurship in Italy: An Industry View," Rivista di Politica Economica, SIPI Spa, vol. 98(2), pages 179-214, March-Apr.
    29. Makoto Nakakita & Teruo Nakatsuma, 2021. "Bayesian Analysis of Intraday Stochastic Volatility Models of High-Frequency Stock Returns with Skew Heavy-Tailed Errors," JRFM, MDPI, vol. 14(4), pages 1-29, March.
    30. Nimark, Kristoffer P, 2013. "Man-bites-dog Business Cycles," CEPR Discussion Papers 9517, C.E.P.R. Discussion Papers.
    31. Gianni Amisano & Maria Letizia Giorgetti, 2005. "Entry in Pharmaceutical submarkets: A Bayesian Panel Probit Approach," Working Papers ubs0511, University of Brescia, Department of Economics.
    32. Tsunehiro Ishihara & Yasuhiro Omori, 2009. "Efficient Bayesian estimation of a multivariate stochastic volatility model with cross leverage and heavy-tailed errors," CARF F-Series CARF-F-198, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    33. Li, Yipeng & Hu, Xiangyue & Jin, Xing & Zhang, Huizhen & Yang, Jiajia & Wang, Zhen, 2025. "Environmental information perception enhances cooperation in stochastic public goods games via Q-learning," Applied Mathematics and Computation, Elsevier, vol. 504(C).
    34. Shinichiro Shirota & Yasuhiro Omori & Hedibert. F. Lopes & Haixiang Piao, 2016. "Cholesky Realized Stochastic Volatility Model," CIRJE F-Series CIRJE-F-1019, CIRJE, Faculty of Economics, University of Tokyo.
    35. Michael T. Belongia & Peter N. Ireland, 2016. "The Evolution of U.S. Monetary Policy: 2000 - 2007," NBER Working Papers 22693, National Bureau of Economic Research, Inc.
    36. Jouchi Nakajima & Yasuhiro Omori, 2007. "Leverage, Heavy-Tails and Correlated Jumps in Stochastic Volatility Models (Revised in January 2008; Published in "Computational Statistics and Data Analysis", 53-6, 2335-2353. April 2009. )," CARF F-Series CARF-F-107, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    37. George Monokroussos, 2006. "Dynamic Limited Dependent Variable Modeling and U.S. Monetary Policy," Discussion Papers 06-02, University at Albany, SUNY, Department of Economics.
    38. Sarno, Lucio & Valente, Giorgio, 2006. "Deviations from purchasing power parity under different exchange rate regimes: Do they revert and, if so, how?," Journal of Banking & Finance, Elsevier, vol. 30(11), pages 3147-3169, November.
    39. Anatoliy Belaygorod & Michael J. Dueker, 2005. "Discrete monetary policy changes and changing inflation targets in estimated dynamic stochastic general equilibrium models," Review, Federal Reserve Bank of St. Louis, vol. 87(Nov), pages 719-734.
    40. Khanal, Aditya R. & Mishra, Ashok K. & Lambert, Dayton M. & Paudel, Krishna P., 2013. "A Bayesian Analysis of GPS Guidance System in Precision Agriculture: The Role of Expectations," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150421, Agricultural and Applied Economics Association.
    41. Xu, Ke-Li, 2020. "Inference of local regression in the presence of nuisance parameters," Journal of Econometrics, Elsevier, vol. 218(2), pages 532-560.
    42. Alain Pirotte & Jean-Loup Madre, 2011. "Determinants of Urban Sprawl in France," Urban Studies, Urban Studies Journal Limited, vol. 48(13), pages 2865-2886, October.
    43. Munehisa Kasuya, 2003. "Investment with Uncertainty: Detection of Decomposed Uncertainty Factors Affecting Investment," Bank of Japan Working Paper Series 03-E-1, Bank of Japan.
    44. IIBOSHI Hirokuni & MATSUMAE Tatsuyoshi & NISHIYAMA Shin-Ichi, 2014. "Sources of the Great Recession：A Bayesian Approach of a Data-Rich DSGE model with Time-Varying Volatility Shocks," ESRI Discussion paper series 313, Economic and Social Research Institute (ESRI).
    45. Omori, Yasuhiro & Chib, Siddhartha & Shephard, Neil & Nakajima, Jouchi, 2007. "Stochastic volatility with leverage: Fast and efficient likelihood inference," Journal of Econometrics, Elsevier, vol. 140(2), pages 425-449, October.
    46. Huang, Shirley J. & Yu, Jun, 2010. "Bayesian analysis of structural credit risk models with microstructure noises," Journal of Economic Dynamics and Control, Elsevier, vol. 34(11), pages 2259-2272, November.
    47. Tristani, Oreste & Amisano, Gianni, 2007. "Euro area inflation persistence in an estimated nonlinear DSGE model," Working Paper Series 754, European Central Bank.
    48. Moeltner Klaus & Rosenberger Randall S, 2008. "Predicting Resource Policy Outcomes via Meta-Regression: Data Space, Model Space, and the Quest for 'Optimal Scope'," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 8(1), pages 1-31, August.
    49. Cem Çakmakli & Selva Demi̇ralp & Gökhan Şahi̇n Güneş, 2024. "Do Financial Markets Respond to Populist Rhetoric?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(3), pages 541-567, June.
    50. Nakajima Jouchi, 2011. "Monetary Policy Transmission under Zero Interest Rates: An Extended Time-Varying Parameter Vector Autoregression Approach," The B.E. Journal of Macroeconomics, De Gruyter, vol. 11(1), pages 1-24, October.
    51. Ouysse, Rachida & Kohn, Robert, 2010. "Bayesian variable selection and model averaging in the arbitrage pricing theory model," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3249-3268, December.
    52. Hariharan, Vijay Ganesh & Landsman, Vardit & Stremersch, Stefan, 2024. "Branded response to generic entry: Detailing beyond the patent cliff," International Journal of Research in Marketing, Elsevier, vol. 41(3), pages 567-588.
    53. Tatjana Petrov & Matej Hajnal & Julia Klein & David Šafránek & Morgane Nouvian, 2022. "Extracting individual characteristics from population data reveals a negative social effect during honeybee defence," PLOS Computational Biology, Public Library of Science, vol. 18(9), pages 1-20, September.
    54. Marcelle Chauvet & Chinhui Juhn & Simon M. Potter, 2001. "Markov switching in disaggregate unemployment rates," Staff Reports 132, Federal Reserve Bank of New York.
    55. Gavin A. Whitaker & Ricardo Silva & Daniel Edwards & Ioannis Kosmidis, 2021. "A Bayesian approach for determining player abilities in football," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(1), pages 174-201, January.
    56. Koji Miyawaki & Yasuhiro Omori & Akira Hibiki, 2010. "Discrete/Continuous Choice Model of the Residential Gas Demand on the Nonconvex Budget Set," CIRJE F-Series CIRJE-F-770, CIRJE, Faculty of Economics, University of Tokyo.
    57. Dimitrakopoulos, Stefanos, 2017. "Semiparametric Bayesian inference for time-varying parameter regression models with stochastic volatility," Economics Letters, Elsevier, vol. 150(C), pages 10-14.
    58. Demirel, Ufuk Devrim & Otterson, James, 2023. "Quantifying the uncertainty of long-term macroeconomic projections," Journal of Macroeconomics, Elsevier, vol. 75(C).
    59. Jouchi Nakajima & Yasuhiro Omori, 2010. "Stochastic Volatility Model with Leverage and Asymmetrically Heavy-Tailed Error Using GH Skew Student's t-Distribution Models," CIRJE F-Series CIRJE-F-738, CIRJE, Faculty of Economics, University of Tokyo.
    60. Grassi, S. & Proietti, T., 2014. "Characterising economic trends by Bayesian stochastic model specification search," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 359-374.
    61. Yasuhiro Omori & Toshiaki Watanabe, 2007. "Block Sampler and Posterior Mode Estimation for A Nonlinear and Non-Gaussian State-Space Model with Correlated Errors," CARF F-Series CARF-F-104, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    62. Abanto-Valle, Carlos A. & Rodríguez, Gabriel & Garrafa-Aragón, Hernán B., 2021. "Stochastic Volatility in Mean: Empirical evidence from Latin-American stock markets using Hamiltonian Monte Carlo and Riemann Manifold HMC methods," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 272-286.
    63. Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro, 2021. "Forecasting Daily Volatility of Stock Price Index Using Daily Returns and Realized Volatility," Discussion paper series HIAS-E-104, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    64. Agnieszka Rabiej & Dominika Sikora & Andrzej Torój, 2023. "How regional business cycles diffuse across space and time: evidence from a Bayesian Markov switching panel of GDP and unemployment in Poland," KAE Working Papers 2023-082, Warsaw School of Economics, Collegium of Economic Analysis.
    65. Koji Miyawaki & Yasuhiro Omori & Akira Hibiki, 2016. "Exact Estimation of Demand Functions under Block-Rate Pricing," Econometric Reviews, Taylor & Francis Journals, vol. 35(3), pages 311-343, March.
    66. Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," "Marco Fanno" Working Papers 0288, Dipartimento di Scienze Economiche "Marco Fanno".
    67. Anna Mikusheva, 2014. "Estimation of dynamic stochastic general equilibrium models (in Russian)," Quantile, Quantile, issue 12, pages 1-21, February.
    68. Hideo Kozumi & Genya Kobayashi, 2009. "Gibbs Sampling Methods for Bayesian Quantile Regression," Discussion Papers 2009-02, Kobe University, Graduate School of Business Administration.
    69. Yasuhiro Omori & Koji Miyawaki, 2008. "Tobit Model with Covariate Dependent Thresholds," CIRJE F-Series CIRJE-F-594, CIRJE, Faculty of Economics, University of Tokyo.
    70. Pavithra Hariharan & P. G. Sankaran, 2024. "Semiparametric regression modelling of current status competing risks data: a Bayesian approach," Computational Statistics, Springer, vol. 39(4), pages 2083-2108, June.
    71. Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2006. "Analysis of high dimensional multivariate stochastic volatility models," Journal of Econometrics, Elsevier, vol. 134(2), pages 341-371, October.
    72. Fiorentini, Gabriele & Sentana, Enrique & Shephard, Neil, 2003. "Likelihood-based estimation of latent generalised ARCH structures," LSE Research Online Documents on Economics 24852, London School of Economics and Political Science, LSE Library.
    73. Shinya Sugawara, 2013. "An Interval Regression Analysis for Tenures of Japanese Elder Care Workers Using Matched Employer-Employee Data," CIRJE F-Series CIRJE-F-887, CIRJE, Faculty of Economics, University of Tokyo.
    74. Yasuhiro Omori & Siddhartha Chib & Neil Shephard & Jouchi Nakajima, 2004. "Stochastic Volatility with Leverage: Fast Likelihood Inference," CIRJE F-Series CIRJE-F-297, CIRJE, Faculty of Economics, University of Tokyo.
    75. Takashi Kano, 2026. "Distribution-Matching Posterior Inference for Incomplete Structural Models," Papers 2601.01077, arXiv.org.
    76. Dorn, Sabrina & Egger, Peter, 2015. "On the distribution of exchange rate regime treatment effects on international trade," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 75-94.
    77. Hugh Christensen & Simon Godsill & Richard E Turner, 2020. "Hidden Markov Models Applied To Intraday Momentum Trading With Side Information," Papers 2006.08307, arXiv.org.
    78. George Monokroussos, 2006. "A Dynamic Tobit Model for the Open Market Desk's Daily Reaction Function," Computing in Economics and Finance 2006 390, Society for Computational Economics.
    79. Chib, Siddhartha & Hamilton, Barton H., 2002. "Semiparametric Bayes analysis of longitudinal data treatment models," Journal of Econometrics, Elsevier, vol. 110(1), pages 67-89, September.
    80. Nakajima, Jouchi & Omori, Yasuhiro, 2012. "Stochastic volatility model with leverage and asymmetrically heavy-tailed error using GH skew Student’s t-distribution," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3690-3704.
    81. Azam, Kazim & Pitt, Michael, 2014. "Bayesian Inference for a Semi-Parametric Copula-based Markov Chain," The Warwick Economics Research Paper Series (TWERPS) 1051, University of Warwick, Department of Economics.
    82. Uchenna Emmanuel Edeh & Tek Tjing Lie & Md Apel Mahmud, 2025. "Assessment of Transmission Reliability Margin: Existing Methods and Challenges and Future Prospects," Energies, MDPI, vol. 18(9), pages 1-20, April.
    83. Tsunehiro Ishihara & Yasuhiro Omori & Manabu Asai, 2014. "Matrix Exponential Stochastic Volatility with Cross Leverage," CIRJE F-Series CIRJE-F-932, CIRJE, Faculty of Economics, University of Tokyo.
    84. Chernozhukov, Victor & Hong, Han, 2003. "An MCMC approach to classical estimation," Journal of Econometrics, Elsevier, vol. 115(2), pages 293-346, August.
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    86. Shinichiro Shirota & Takayuki Hizu & Yasuhiro Omori, 2013. "Realized Stochastic Volatility with Leverage and Long Memory," CIRJE F-Series CIRJE-F-880, CIRJE, Faculty of Economics, University of Tokyo.
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