Information-theoretic estimation of preference parameters: macroeconomic applications and simulation evidence
Abstract
This paper investigates the behaviour of estimators based on the Kullback-Leibler information criterion (KLIC), as an alternative to the generalized method of moments (GMM). We first study the estimators in a Monte Carlo simulation model of consumption growth with power utility. Then we compare KLIC and GMM estimators in macroeconomic applications, in which preference parameters are estimated with aggregate data. KLIC probability measures serve as useful diagnostics. In dependent data, tests of overidentifying restrictions in the KLIC framework have size properties comparable to those of the J-test in iterated GMM, but superior size-adjusted power.(This abstract was borrowed from another version of this item.)
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Bibliographic Info
Article provided by Elsevier in its journal Journal of Econometrics.
Volume (Year): 107 (2002)
Issue (Month): 1-2 (March)
Pages: 213-233
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Web page: http://www.elsevier.com/locate/jeconom
Related research
Keywords:Other versions of this item:
- Allan W. Gregory & Jean-Francois Lamarche & Gregor W. Smith, 2001. "Information-Theoretic Estimation of Preference Parameters: Macroeconomic Applications and Simulation Evidence," Working Papers 1249, Queen's University, Department of Economics.
- 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
- E21 - Macroeconomics and Monetary Economics - - Macroeconomics: Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
References
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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Noor, Jawwad, 2009. "Hyperbolic discounting and the standard model: Eliciting discount functions," Journal of Economic Theory, Elsevier, vol. 144(5), pages 2077-2083, September.
- Jason Allen & Allan W. Gregory & Katsumi Shimotsu, 2008.
"Empirical Likelihood Block Bootstrapping,"
Working Papers
08-18, Bank of Canada.
- Allen, Jason & Gregory, Allan W. & Shimotsu, Katsumi, 2011. "Empirical likelihood block bootstrapping," Journal of Econometrics, Elsevier, vol. 161(2), pages 110-121, April.
- Jason Allen & Allan W. Gregory & Katsumi Shimotsu, 2008. "Empirical Likelihood Block Bootstrapping," Working Papers 1156, Queen's University, Department of Economics.
- Allen, Jason & Gregory, Allan W. & Shimotsu, Katsumi, 2010. "Empirical Likelihood Block Bootstrapping," Discussion Papers 2010-01, Graduate School of Economics, Hitotsubashi University.
- Sowell, Fallaw, 2009. "The empirical saddlepoint likelihood estimator applied to two-step GMM," MPRA Paper 15494, University Library of Munich, Germany, revised May 2009.
- Yasutomo Murasawa, 2009. "Do coincident indicators have one-factor structure?," Empirical Economics, Springer, vol. 36(2), pages 339-365, May.
- Manuel Dominguez & Ignacio Lobato, 2010. "Consistent Inference in Models Defined by COnditional Moment Restrictions: an Alternative to GMM," Working Papers 1005, Centro de Investigacion Economica, ITAM.
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