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Simulation-based Inference in Econometrics

Citations

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Cited by:

  1. Christian Belzil & Arnaud Maurel & Modibo Sidibé, 2021. "Estimating the Value of Higher Education Financial Aid: Evidence from a Field Experiment," Journal of Labor Economics, University of Chicago Press, vol. 39(2), pages 361-395.
  2. Aguirregabiria, Victor & Mira, Pedro, 2010. "Dynamic discrete choice structural models: A survey," Journal of Econometrics, Elsevier, vol. 156(1), pages 38-67, May.
  3. Arvanitis Stelios & Demos Antonis, 2018. "On the Validity of Edgeworth Expansions and Moment Approximations for Three Indirect Inference Estimators," Journal of Econometric Methods, De Gruyter, vol. 7(1), pages 1-38, January.
  4. Nathalie Havet, 2006. "La valorisation salariale et professionnelle de la formation en entreprise diffère-t-elle selon le sexe ? L'exemple canadien," Économie et Prévision, Programme National Persée, vol. 175(4), pages 147-161.
  5. Pablo Mitnik & Sunyoung Baek, 2013. "The Kumaraswamy distribution: median-dispersion re-parameterizations for regression modeling and simulation-based estimation," Statistical Papers, Springer, vol. 54(1), pages 177-192, February.
  6. Matteo Richiardi, 2003. "The Promises and Perils of Agent-Based Computational Economics," LABORatorio R. Revelli Working Papers Series 29, LABORatorio R. Revelli, Centre for Employment Studies.
  7. Hurtado, Samuel, 2014. "DSGE models and the Lucas critique," Economic Modelling, Elsevier, vol. 44(S1), pages 12-19.
  8. Bhat, Chandra R., 2011. "The maximum approximate composite marginal likelihood (MACML) estimation of multinomial probit-based unordered response choice models," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 923-939, August.
  9. Kristensen, Dennis & Salanié, Bernard, 2017. "Higher-order properties of approximate estimators," Journal of Econometrics, Elsevier, vol. 198(2), pages 189-208.
  10. Andrew T. Ching & Matthew Osborne, 2020. "Identification and Estimation of Forward-Looking Behavior: The Case of Consumer Stockpiling," Marketing Science, INFORMS, vol. 39(4), pages 707-726, July.
  11. Avdis, Efstathios & Wachter, Jessica A., 2017. "Maximum likelihood estimation of the equity premium," Journal of Financial Economics, Elsevier, vol. 125(3), pages 589-609.
  12. Damien Rousselière & Samira Rousselière, 2010. "On the impact of trust on consumer willingness to purchase GM food:Evidence from a European survey," Review of Agricultural and Environmental Studies - Revue d'Etudes en Agriculture et Environnement, INRA Department of Economics, vol. 91(1), pages 5-26.
  13. Aiste Ruseckaite & Dennis Fok & Peter Goos, 2016. "Flexible Mixture-Amount Models for Business and Industry using Gaussian Processes," Tinbergen Institute Discussion Papers 16-075/III, Tinbergen Institute.
  14. Aguirregabiria, Victor & Magesan, Arvind, 2013. "Euler Equations for the Estimation of Dynamic Discrete Choice Structural," MPRA Paper 46056, University Library of Munich, Germany.
  15. Sumeetpal S. Singh & Nicolas Chopin & Nick Whiteley, 2010. "Bayesian Learning of Noisy Markov Decision Processes," Working Papers 2010-36, Center for Research in Economics and Statistics.
  16. Bauwens, Luc & Veredas, David, 2004. "The stochastic conditional duration model: a latent variable model for the analysis of financial durations," Journal of Econometrics, Elsevier, vol. 119(2), pages 381-412, April.
  17. Canova, Fabio & Ciccarelli, Matteo, 2013. "Panel vector autoregressive models: a survey," Working Paper Series 1507, European Central Bank.
  18. Gabriele Fiorentini & Enrique Sentana & Neil Shephard, 2004. "Likelihood-Based Estimation of Latent Generalized ARCH Structures," Econometrica, Econometric Society, vol. 72(5), pages 1481-1517, 09.
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