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Ivan Jeliazkov

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

    Sorry, no citations of working papers recorded.

Articles

  1. 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.

    Cited by:

    1. Mohammad Arshad Rahman & Angela Vossmeyer, 2019. "Estimation and Applications of Quantile Regression for Binary Longitudinal Data," Papers 1909.05560, arXiv.org.
    2. 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.
    3. Bresson, Georges & Lacroix, Guy & Arshad Rahman, Mohammad, 2020. "Bayesian Panel Quantile Regression for Binary Outcomes with Correlated Random Effects: An Application on Crime Recidivism in Canada," IZA Discussion Papers 12928, Institute of Labor Economics (IZA).
    4. Sanjiv R. Das & Kris James Mitchener & Angela Vossmeyer, 2022. "Bank Regulation, Network Topology, and Systemic Risk: Evidence from the Great Depression," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(5), pages 1261-1312, August.
    5. Padma Sharma, 2022. "Assessing Regulatory Responses to Banking Crises," Research Working Paper RWP 22-04, Federal Reserve Bank of Kansas City.

  2. 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.

    Cited by:

    1. 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.
    2. Djonata Schiessl & Helison Bertoli Alves Dias & José Carlos Korelo, 2022. "Artificial intelligence in marketing: a network analysis and future agenda," Journal of Marketing Analytics, Palgrave Macmillan, vol. 10(3), pages 207-218, September.
    3. José Ramón Saura & Pedro Palos-Sánchez & Luis Manuel Cerdá Suárez, 2017. "Understanding the Digital Marketing Environment with KPIs and Web Analytics," Future Internet, MDPI, vol. 9(4), pages 1-13, November.
    4. Mitchener, Kris & Das, Sanjiv & Vossmeyer, Angela, 2018. "Bank Regulation, Network Topology, and Systemic Risk: Evidence from the Great Depression," CEPR Discussion Papers 13416, C.E.P.R. Discussion Papers.
    5. Sanjiv R. Das & Kris James Mitchener & Angela Vossmeyer, 2022. "Bank Regulation, Network Topology, and Systemic Risk: Evidence from the Great Depression," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(5), pages 1261-1312, August.

  3. 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.

    Cited by:

    1. Christian Schlereth & Fabian Schulz, 2014. "Schnelle und einfache Messung von Bedeutungsgewichten mit der Restricted-Click-Stream Analyse: Ein Vergleich mit etablierten Präferenzmessmethoden," Schmalenbach Journal of Business Research, Springer, vol. 66(8), pages 630-657, December.
    2. Jiangyuan Hou & Mingyue Du & Qingjie Zhou, 2023. "What People Talk About Multi-Channel Purchasing Behavior and What They Intend to do: Related Perspective From ESG Evaluation System," SAGE Open, , vol. 13(4), pages 21582440231, October.
    3. Yanju Zhou & Yi Yu & Xiaohong Chen & Xiongwei Zhou, 2020. "Guanxi or Justice? An Empirical Study of WeChat Voting," Journal of Business Ethics, Springer, vol. 164(1), pages 201-225, June.
    4. Ke Gong & Yi Peng & Yong Wang & Maozeng Xu, 2018. "Time series analysis for C2C conversion rate," Electronic Commerce Research, Springer, vol. 18(4), pages 763-789, December.
    5. Diehl, Kristin & van Herpen, Erica & Lamberton, Cait, 2015. "Organizing Products with Complements versus Substitutes: Effects on Store Preferences as a Function of Effort and Assortment Perceptions," Journal of Retailing, Elsevier, vol. 91(1), pages 1-18.
    6. Gilbride, Timothy J. & Currim, Imran S. & Mintz, Ofer & Siddarth, S., 2016. "A Model for Inferring Market Preferences from Online Retail Product Information Matrices," Journal of Retailing, Elsevier, vol. 92(4), pages 470-485.

  4. Ivan Jeliazkov & Rui Liu, 2010. "A model-based ranking of U.S. recessions," Economics Bulletin, AccessEcon, vol. 30(3), pages 2289-2296.

    Cited by:

    1. Joshua C. C. Chan & Eric Eisenstat, 2015. "Marginal Likelihood Estimation with the Cross-Entropy Method," Econometric Reviews, Taylor & Francis Journals, vol. 34(3), pages 256-285, March.
    2. Joshua C C Chan & Cody Y L Hsiao, 2013. "Estimation of Stochastic Volatility Models with Heavy Tails and Serial Dependence," CAMA Working Papers 2013-74, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. Paul Viefers, 2011. "Bayesian Inference for the Mixed-Frequency VAR Model," Discussion Papers of DIW Berlin 1172, DIW Berlin, German Institute for Economic Research.

  5. 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.

    Cited by:

    1. Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2019. "Forecasting with a Panel Tobit Model," CAEPR Working Papers 2019-005, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    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. 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. Bresson, Georges & Lacroix, Guy & Arshad Rahman, Mohammad, 2020. "Bayesian Panel Quantile Regression for Binary Outcomes with Correlated Random Effects: An Application on Crime Recidivism in Canada," IZA Discussion Papers 12928, Institute of Labor Economics (IZA).
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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).
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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).
    18. 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.
    19. Ivan Jeliazkov & Shubham Karnawat & Mohammad Arshad Rahman & Angela Vossmeyer, 2023. "Flexible Bayesian Quantile Analysis of Residential Rental Rates," Papers 2305.13687, arXiv.org, revised Sep 2023.
    20. 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.
    21. Finn Lindgren & Håvard Rue, 2008. "On the Second‐Order Random Walk Model for Irregular Locations," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 35(4), pages 691-700, December.
    22. Panagiotelis, Anastasios & Smith, Michael, 2008. "Bayesian identification, selection and estimation of semiparametric functions in high-dimensional additive models," Journal of Econometrics, Elsevier, vol. 143(2), pages 291-316, April.
    23. D. Rummel & T. Augustin & H. Küchenhoff, 2010. "Correction for Covariate Measurement Error in Nonparametric Longitudinal Regression," Biometrics, The International Biometric Society, vol. 66(4), pages 1209-1219, December.
    24. Ali Aghamohammadi, 2018. "Bayesian analysis of dynamic panel data by penalized quantile regression," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(1), pages 91-108, March.

  6. 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. Koji Miyawaki & Yasuhiro Omori & Akira Hibiki, 2018. "A discrete/continuous choice model on a nonconvex budget set," Econometric Reviews, Taylor & Francis Journals, vol. 37(2), pages 89-113, February.
    2. 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.
    3. 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.
    4. 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.
    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. Joshua Chan & Rodney Strachan, 2012. "Estimation in Non-Linear Non-Gaussian State Space Models with Precision-Based Methods," CAMA Working Papers 2012-13, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.

  7. Garfinkel, Michelle R. & Jeliazkov, Ivan, 2004. "Comment on "The macroeconomic consequences of terrorism"," Journal of Monetary Economics, Elsevier, vol. 51(5), pages 1033-1037, July.

    Cited by:

    1. Stergios Skaperdas, 2011. "The costs of organized violence: a review of the evidence," Economics of Governance, Springer, vol. 12(1), pages 1-23, March.

  8. Bianco, William T. & Jeliazkov, Ivan & Sened, Itai, 2004. "The Uncovered Set and the Limits of Legislative Action," Political Analysis, Cambridge University Press, vol. 12(3), pages 256-276, July.

    Cited by:

    1. Tasos Kalandrakis, 2022. "Generalized medians and a political center," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 58(2), pages 301-319, February.
    2. Michel Le Breton & Karine Van Der Straeten, 2017. "Alliances Électorales et Gouvernementales : La Contribution de la Théorie des Jeux Coopératifs à la Science Politique," Revue d'économie politique, Dalloz, vol. 127(4), pages 637-736.
    3. Anthony J. McGann & Sebastian Dellepiane‐Avellaneda & John Bartle, 2023. "Dynamics of public opinion and policy response under proportional and plurality elections," Economics and Politics, Wiley Blackwell, vol. 35(1), pages 333-355, March.
    4. Elizabeth Penn, 2006. "Alternate Definitions of the Uncovered Set and Their Implications," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 27(1), pages 83-87, August.
    5. Gyung-Ho Jeong, 2017. "The supermajority core of the US Senate and the failure to join the League of Nations," Public Choice, Springer, vol. 173(3), pages 325-343, December.
    6. Tovey, Craig A., 2010. "A finite exact algorithm for epsilon-core membership in two dimensions," Mathematical Social Sciences, Elsevier, vol. 60(3), pages 178-180, November.
    7. John Duggan, 2011. "Uncovered Sets," Wallis Working Papers WP63, University of Rochester - Wallis Institute of Political Economy.
    8. John Duggan, 2013. "Uncovered sets," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 41(3), pages 489-535, September.
    9. Nicholas R. Miller, 2015. "The spatial model of social choice and voting," Chapters, in: Jac C. Heckelman & Nicholas R. Miller (ed.), Handbook of Social Choice and Voting, chapter 10, pages 163-181, Edward Elgar Publishing.

  9. Chib S. & Jeliazkov I., 2001. "Marginal Likelihood From the Metropolis-Hastings Output," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 270-281, March.

    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. Richard Kleijn & Herman K. van Dijk, 2006. "Bayes model averaging of cyclical decompositions in economic time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(2), pages 191-212, March.
    3. Koji Miyawaki & Yasuhiro Omori & Akira Hibiki, 2018. "A discrete/continuous choice model on a nonconvex budget set," Econometric Reviews, Taylor & Francis Journals, vol. 37(2), pages 89-113, February.
    4. 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.
    5. Arnaud Dufays, 2014. "On the conjugacy of off-line and on-line Sequential Monte Carlo Samplers," Working Paper Research 263, National Bank of Belgium.
    6. Akihisa Shibata & Mototsugu Shintani & Takayuki Tsuruga, 2018. "Current account dynamics under information rigidity and imperfect capital mobility," CAMA Working Papers 2018-56, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    7. 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.
    8. Yong Li & Jun Yu, 2011. "Bayesian Hypothesis Testing in Latent Variable Models," Working Papers 11-2011, Singapore Management University, School of Economics.
    9. Siddhartha Chib & Minchul Shin & Anna Simoni, 2021. "Bayesian Estimation and Comparison of Conditional Moment Models," Papers 2110.13531, arXiv.org.
    10. 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.
    11. 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.
    12. Luc Bauwens & Arnaud Dufays & Jeroen V.K. Rombouts, 2011. "Marginal Likelihood for Markov-Switching and Change-Point GARCH Models," Cahiers de recherche 1138, CIRPEE.
    13. 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.
    14. 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.
    15. 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.
    16. Li, Bing & Pei, Pei & Tan, Fei, 2021. "Financial distress and fiscal inflation," Journal of Macroeconomics, Elsevier, vol. 70(C).
    17. Gholamreza Hajargasht & D.S. Prasada Rao, 2019. "Multilateral Index Number Systems for International Price Comparisons: Properties, Existence and Uniqueness," CEPA Working Papers Series WP032019, School of Economics, University of Queensland, Australia.
    18. 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.
    19. 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.
    20. 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.
    21. Makoto Takahashi & Yasuhiro Omori & Toshiaki Watanabe, 2007. "Estimating Stochastic Volatility Models Using Daily Returns and Realized Volatility Simultaneously," CIRJE F-Series CIRJE-F-515, CIRJE, Faculty of Economics, University of Tokyo.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. 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.
    32. 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.
    33. 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.
    34. Lacombe, Donald J. & Michieka, Nyakundi M. & Gebremedhin, Tesfa, 2012. "A Bayesian Spatial Econometric Analysis of SNAP Participation Rates in Appalachia," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 42(3), pages 1-12.
    35. Joshua C. C. Chan & Eric Eisenstat, 2015. "Marginal Likelihood Estimation with the Cross-Entropy Method," Econometric Reviews, Taylor & Francis Journals, vol. 34(3), pages 256-285, March.
    36. Dimitris Korobilis & Kenichi Shimizu, 2021. "Bayesian Approaches to Shrinkage and Sparse Estimation," Working Papers 2021_19, Business School - Economics, University of Glasgow.
    37. Shinya Sugawara & Yasuhiro Omori, 2010. "Duopoly in the Japanese Airline Market: Bayesian Estimation for the Entry Game," CIRJE F-Series CIRJE-F-763, CIRJE, Faculty of Economics, University of Tokyo.
    38. Ho-chuan Huang, 2004. "Estimation of Technical Inefficiencies with Heterogeneous Technologies," Journal of Productivity Analysis, Springer, vol. 21(3), pages 277-296, May.
    39. Marco Grzegorczyk & Andrej Aderhold & Dirk Husmeier, 2017. "Targeting Bayes factors with direct-path non-equilibrium thermodynamic integration," Computational Statistics, Springer, vol. 32(2), pages 717-761, June.
    40. Arefiev, Nikolay & Khabibullin, Ramis, 2018. "Bayesian identification of structural vector autoregression models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 49, pages 115-142.
    41. Keisuke Kondo, 2015. "Spatial Dependence in Regional Business Cycles: Evidence from Mexican States," Discussion Paper Series DP2015-27, Research Institute for Economics & Business Administration, Kobe University, revised Jun 2021.
    42. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    43. Bernardi, Mauro & Della Corte, Giuseppe & Proietti, Tommaso, 2008. "Extracting the Cyclical Component in Hours Worked: a Bayesian Approach," MPRA Paper 8967, University Library of Munich, Germany.
    44. 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.
    45. Timothy Cogley & Argia M. Sbordone, 2006. "Trend inflation and inflation persistence in the New Keynesian Phillips curve," Staff Reports 270, Federal Reserve Bank of New York.
    46. Liu, Xiaochun, 2017. "Measuring systemic risk with regime switching in tails," Economic Modelling, Elsevier, vol. 67(C), pages 55-72.
    47. Yoosoon Chang & Junior Maih & Fei Tan, 2018. "State Space Models with Endogenous Regime Switching," Working Papers No 9/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    48. Deschamps, Philippe J., 2011. "Bayesian estimation of an extended local scale stochastic volatility model," Journal of Econometrics, Elsevier, vol. 162(2), pages 369-382, June.
    49. BAUWENS, Luc & DUFAYS, Arnaud & DE BACKER, Bruno, 2011. "Estimating and forecasting structural breaks in financial time series," LIDAM Discussion Papers CORE 2011055, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    50. Zhenyu Zhao & Thomas A. Severini, 2017. "Integrated likelihood computation methods," Computational Statistics, Springer, vol. 32(1), pages 281-313, March.
    51. Gary Bolton & Duncan Fong & Paul Mosquin, 2003. "Bayes Factors with an Application to Experimental Economics," Experimental Economics, Springer;Economic Science Association, vol. 6(3), pages 311-325, November.
    52. So, Mike K.P. & Chan, Raymond K.S., 2014. "Bayesian analysis of tail asymmetry based on a threshold extreme value model," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 568-587.
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