Indirect Likelihood Inference
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- Michael Creel & Dennis Kristensen, 2011. "Indirect likelihood inference," UFAE and IAE Working Papers 874.11, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
- Michael Creel & Dennis Kristensen, "undated". "Indirect Likelihood Inference," Working Papers 558, Barcelona School of Economics.
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Citations
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Cited by:
- Kristensen, Dennis & Shin, Yongseok, 2012.
"Estimation of dynamic models with nonparametric simulated maximum likelihood,"
Journal of Econometrics, Elsevier, vol. 167(1), pages 76-94.
- Dennis Kristensen & Yongseok Shin, 2008. "Estimation of Dynamic Models with Nonparametric Simulated Maximum Likelihood," CREATES Research Papers 2008-58, Department of Economics and Business Economics, Aarhus University.
- Creel, Michael, 2017.
"Neural nets for indirect inference,"
Econometrics and Statistics, Elsevier, vol. 2(C), pages 36-49.
- Michael Creel, 2016. "Neural Nets for Indirect Inference," Working Papers 942, Barcelona School of Economics.
- Bertl Johanna & Ewing Gregory & Kosiol Carolin & Futschik Andreas, 2017. "Approximate maximum likelihood estimation for population genetic inference," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 16(5-6), pages 291-312, December.
- Valerio Scalone, 2018. "Estimating Non-Linear DSGEs with the Approximate Bayesian Computation: an application to the Zero Lower Bound," Working papers 688, Banque de France.
- Creel, Michael & Kristensen, Dennis, 2015.
"ABC of SV: Limited information likelihood inference in stochastic volatility jump-diffusion models,"
Journal of Empirical Finance, Elsevier, vol. 31(C), pages 85-108.
- Michael Creel & Dennis Kristensen, 2014. "ABC of SV: Limited Information Likelihood Inference in Stochastic Volatility Jump-Diffusion Models," CREATES Research Papers 2014-30, Department of Economics and Business Economics, Aarhus University.
- Forneron, Jean-Jacques & Ng, Serena, 2018.
"The ABC of simulation estimation with auxiliary statistics,"
Journal of Econometrics, Elsevier, vol. 205(1), pages 112-139.
- Jean-Jacques Forneron & Serena Ng, 2015. "The ABC of Simulation Estimation with Auxiliary Statistics," Papers 1501.01265, arXiv.org, revised Oct 2017.
- Michael Creel & Dennis Kristensen, 2013. "Indirect Likelihood Inference (revised)," UFAE and IAE Working Papers 931.13, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
- Michael Creel, 2016. "Neural Nets for Indirect Inference," UFAE and IAE Working Papers 960.16, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC), revised 18 Jul 2016.
- Creel, Michael & Kristensen, Dennis, 2016.
"On selection of statistics for approximate Bayesian computing (or the method of simulated moments),"
Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 99-114.
- Michael Creel & Dennis Kristensen, 2015. "On Selection of Statistics for Approximate Bayesian Computing or the Method of Simulated Moments," UFAE and IAE Working Papers 950.15, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC), revised 27 Feb 2015.
- Michael Creel & Jiti Gao & Han Hong & Dennis Kristensen, 2016. "Bayesian Indirect Inference and the ABC of GMM," Monash Econometrics and Business Statistics Working Papers 1/16, Monash University, Department of Econometrics and Business Statistics.
- Michael Creel, 2016. "A Note on Julia and MPI, with Code Examples," Computational Economics, Springer;Society for Computational Economics, vol. 48(3), pages 535-546, October.
- Jiti Gao & Han Hong, 2014. "A Computational Implementation of GMM," Monash Econometrics and Business Statistics Working Papers 24/14, Monash University, Department of Econometrics and Business Statistics.
- Valerio Scalone, 2015. "Estimating Non-Linear DSGEs with the Approximate Bayesian Computation: an application to the Zero Lower Bound," Working Papers 6/15, Sapienza University of Rome, DISS.
- Aldrich, EM, 2014. "GPU Computing in Economics," Santa Cruz Department of Economics, Working Paper Series qt8p12748g, Department of Economics, UC Santa Cruz.
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More about this item
Keywords
indirect inference; maximum-likelihood; simulation-based methods; bias correction; Bayesian estimation;All these keywords.
JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
Statistics
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