Monte carlo experimentation in econometrics

Citations

Cited by:

1. Jorge Pérez-Rodríguez & Julián Andrada-Félix, 2013. "Estimating critical values for testing the i.i.d. in standardized residuals from GARCH models in finite samples," Computational Statistics, Springer, vol. 28(2), pages 701-734, April.
2. Neil R. Ericsson & Jaime R. Marquez, 1990. "Evaluating the predictive performance of trade-account models," International Finance Discussion Papers 377, Board of Governors of the Federal Reserve System (U.S.).
3. Liesenfeld, Roman & Breitung, Jörg, 1998. "Simulation based methods of moments in empirical finance," Tübinger Diskussionsbeiträge 136, University of Tübingen, School of Business and Economics.
   • Liesenfeld, Roman & Breitung, Jörg, 1998. "Simulation based methods of moments in empirical finance," SFB 373 Discussion Papers 1998,59, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
4. Jan F. Kiviet, 2005. "Judging Contending Estimators by Simulation: Tournaments in Dynamic Panel Data Models," Tinbergen Institute Discussion Papers 05-112/4, Tinbergen Institute.
5. Hajivassiliou, Vassilis A. & Ruud, Paul A., 1986. "Classical estimation methods for LDV models using simulation," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 40, pages 2383-2441, Elsevier.
   • Hajivassiliou, Vassilis A & Ruud, Paul A., 1993. "Classical Estimation Methods for LDV Models Using Simulation," Department of Economics, Working Paper Series qt3cg196fr, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
   • Vassilis A. Hajivassiliou and Paul A. Ruud., 1993. "Classical Estimation Methods for LDV Models Using Simulation," Economics Working Papers 93-219, University of California at Berkeley.
   • Vassilis A. Hajivassiliou & Paul A. Ruud, 1993. "Classical Estimation Methods for LDV Models Using Simulation," Cowles Foundation Discussion Papers 1051, Cowles Foundation for Research in Economics, Yale University.
   • V.A. Hajivassiliou & P. A. Ruud, 1993. "Classical Estimation Methods for LDV Models Using Simulation," Econometrics 9311002, University Library of Munich, Germany.
6. Steel, Mark F. J., 1991. "A Bayesian analysis of simultaneous equation models by combining recursive analytical and numerical approaches," Journal of Econometrics, Elsevier, vol. 48(1-2), pages 83-117.
   • Steel, M.F.J., 1989. "A Bayesian analysis of simultaneous equation models by combining recursive analytical and numerical approaches," Discussion Paper 1989-8, Tilburg University, Center for Economic Research.
   • Steel, M.F.J., 1989. "A Bayesian Analysis Of Simultaneous Equation Models By Combining Recursive Analytical And Numerical Approaches," Papers 8908, Tilburg - Center for Economic Research.
   • Steel, M.F.J., 1991. "A Bayesian analysis of simultaneous equation models by combining recursive analytical and numerical approaches," Other publications TiSEM 029ee64f-b5a0-4787-9f5e-0, Tilburg University, School of Economics and Management.
   • Steel, M.F.J., 1989. "A Bayesian analysis of simultaneous equation models by combining recursive analytical and numerical approaches," Other publications TiSEM b3f4c27f-4dab-46b3-9587-6, Tilburg University, School of Economics and Management.
7. Bertocco Giancarlo, 2006. "Are banks special? A note on Tobin’s theory of financial intermediaries," Economics and Quantitative Methods qf0605, Department of Economics, University of Insubria.
8. David N. DeJong & Roman Liesenfeld & Jean-Francois Richard, 2006. "Timing structural change: a conditional probabilistic approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(2), pages 175-190.
   • David N. DeJong & Roman Liesenfeld & Jean‐Francois Richard, 2006. "Timing structural change: a conditional probabilistic approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(2), pages 175-190, March.
9. Bianchi, Carlo & Calzolari, Giorgio & Brillet, Jean-Louis, 1987. "Measuring forecast uncertainty : A review with evaluation based on a macro model of the French economy," International Journal of Forecasting, Elsevier, vol. 3(2), pages 211-227.
   • Bianchi, Carlo & Brillet, Jean-Louis & Calzolari, Giorgio & Panattoni, Lorenzo, 1987. "Forecast variance in simultaneous equation models: analytic and Monte Carlo methods," MPRA Paper 24541, University Library of Munich, Germany.
10. Giorgio Calzolari & Francesca Di Iorio & Gabriele Fiorentini, 1998. "Control variates for variance reduction in indirect inference: Interest rate models in continuous time," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages 100-112.
    • Calzolari, Giorgio & Di Iorio, Francesca & Fiorentini, Gabriele, 1996. "Control variates for variance reduction in indirect inference: interest rate models in continuous time," MPRA Paper 23160, University Library of Munich, Germany, revised Nov 1996.
    • Gabriele Fiorentini & Francesca Di Iorio & Giorgio Calzolari, 1998. "- Control Variates For Variance Reduction In Indirect Inference: Interest Rate Models In Continuous Time," Working Papers. Serie AD 1998-09, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
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12. Hamilton, James D., 1996. "Specification testing in Markov-switching time-series models," Journal of Econometrics, Elsevier, vol. 70(1), pages 127-157, January.
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14. Diebold, Francis X. & Chen, Celia, 1996. "Testing structural stability with endogenous breakpoint A size comparison of analytic and bootstrap procedures," Journal of Econometrics, Elsevier, vol. 70(1), pages 221-241, January.
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15. Ericsson, Neil R., 2017. "How biased are U.S. government forecasts of the federal debt?," International Journal of Forecasting, Elsevier, vol. 33(2), pages 543-559.
    • Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," Working Papers 2017-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    • Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," International Finance Discussion Papers 1189, Board of Governors of the Federal Reserve System (U.S.).
16. Krüger, Jens J., 2012. "A Monte Carlo study of old and new frontier methods for efficiency measurement," European Journal of Operational Research, Elsevier, vol. 222(1), pages 137-148.
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17. Krolzig, Hans-Martin & Hendry, David F., 2001. "Computer automation of general-to-specific model selection procedures," Journal of Economic Dynamics and Control, Elsevier, vol. 25(6-7), pages 831-866, June.
    • Hans-Martin Krolzig & David Hendry, 1999. "Computer Automation of General-to-Specific Model Selection Procedures," Computing in Economics and Finance 1999 314, Society for Computational Economics.
    • Hans-Martin Krolzig, 2000. "Computer Automation of General-to-Specific Model Selection Procedures," Econometric Society World Congress 2000 Contributed Papers 0411, Econometric Society.
    • David Hendry & Hans-Martin Krolzig, 2000. "Computer Automation of General-to-Specific Model Selection Procedures," Economics Series Working Papers 3, University of Oxford, Department of Economics.
18. Neil R. Ericsson & Esfandiar Maasoumi & Grayham E. Mizon, 2001. "A retrospective on J. Denis Sargan and his contributions to econometrics," International Finance Discussion Papers 700, Board of Governors of the Federal Reserve System (U.S.).
19. Davidson, Russell & MacKinnon, James G., 1992. "Regression-based methods for using control variates in Monte Carlo experiments," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 203-222.
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20. Mauro Costantini & Claudio Lupi, 2013. "A Simple Panel-CADF Test for Unit Roots," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(2), pages 276-296, April.
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21. Richard H. Clarida & Mark P. Taylor, 2003. "Nonlinear Permanent - Temporary Decompositions in Macroeconomics and Finance," Economic Journal, Royal Economic Society, vol. 113(486), pages 125-139, March.
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22. van Dijk, H. K., 1987. "Some Advances In Bayesian Estimation Methods Using Monte Carlo Integration," Econometric Institute Archives 272361, Erasmus University Rotterdam.
    • VAN DIJK, Herman K., 1987. "Some advances in Bayesian estimations methods using Monte Carlo Integration," LIDAM Reprints CORE 783, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
23. Gajda, Jan B. & Markowski, Aleksander, 1998. "Model Evaluation Using Stochastic Simulations: The Case of the Econometric Model KOSMOS," Working Papers 61, National Institute of Economic Research.
24. Anna M. Caristo, 2015. "Incentivos al trabajo y cobertura de riesgos de los programas de pensiones: el caso de Uruguay," Económica, Departamento de Economía, Facultad de Ciencias Económicas, Universidad Nacional de La Plata, vol. 61, pages 81-126, January-D.
25. Lawford, Steve & Stamatogiannis, Michalis P., 2009. "The finite-sample effects of VAR dimensions on OLS bias, OLS variance, and minimum MSE estimators," Journal of Econometrics, Elsevier, vol. 148(2), pages 124-130, February.
    • Steve Lawford & Michalis P. Stamatogiannis, 2008. "The Finite-Sample E ects of VAR Dimensions on OLS Bias, OLS Variance, and Minimum MSE Estimators," Working Paper series 13_08, Rimini Centre for Economic Analysis.
    • Steve Lawford & Michalis P. Stamatogiannis, 2009. "The finite-sample effects of VAR dimensions on OLS bias, OLS variance, and minimum MSE estimators," Post-Print hal-00563603, HAL.
26. Sarno, Lucio & Taylor, Mark P. & Chowdhury, Ibrahim, 2004. "Nonlinear dynamics in deviations from the law of one price: a broad-based empirical study," Journal of International Money and Finance, Elsevier, vol. 23(1), pages 1-25, February.
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27. Jurgen A. Doornik & Rocco Mosconi & Paolo Paruolo, 2017. "Formula I(1) and I(2): Race Tracks for Likelihood Maximization Algorithms of I(1) and I(2) Cointegrated VAR Models," Econometrics, MDPI, vol. 5(4), pages 1-30, November.
28. Bianchi, Carlo & Calzolari, Giorgio & Sterbenz, Frederic P., 1991. "Simulation of interest rate options using ARCH," MPRA Paper 24844, University Library of Munich, Germany.
29. Rybinski, Krzysztof, 1997. "Testing Integration of Macroeconomic Time Series in Transitional Socialist Economies. A Modification of Perron Test," Economic Change and Restructuring, Springer, vol. 30(2-3), pages 127-179.
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30. Giorgio Valente & Lucio Sarno, 2004. "Comparing the accuracy of density forecasts from competing models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(8), pages 541-557.
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32. Giorgio Calzolari & F. Di Iorio & G. Fiorentini, 1999. "Indirect Estimation of Just-Identified Models with Control Variates," Econometrics Working Papers Archive quaderno46, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
33. Calzolari, Giorgio, 1987. "La varianza delle previsioni nei modelli econometrici [Forecast variance in econometric models]," MPRA Paper 23866, University Library of Munich, Germany.
34. Neil R. Ericsson & James G. MacKinnon, 2002. "Distributions of error correction tests for cointegration," Econometrics Journal, Royal Economic Society, vol. 5(2), pages 285-318, June.
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39. Kesavan, Thulasiram, 1988. "Monte Carlo experiments of market demand theory," ISU General Staff Papers 198801010800009854, Iowa State University, Department of Economics.
40. Mr. Alessandro Rebucci, 2003. "On the Heterogeneity Bias of Pooled Estimators in Stationary VAR Specifications," IMF Working Papers 2003/073, International Monetary Fund.
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42. Takamitsu Kurita, 2019. "A Recursive Monte Carlo Study of Structural-Break Sensitivity of Adjustment Coefficients in Cointegrated VAR Systems," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(2), pages 251-270, June.
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51. Jean-François Richard, 2019. "Bidder Collusion: Accounting for All Feasible Bidders," Working Paper 6759, Department of Economics, University of Pittsburgh.
52. Taşpınar Süleyman & Doğan Osman, 2017. "Teaching Size and Power Properties of Hypothesis Tests Through Simulations," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-15, January.
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