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Hypothesis testing and finite sample properties of generalized method of moments estimators: a Monte Carlo study

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  • Ching-Sheng Mao

Abstract

Econometric methods based on the first-order conditions of intertemporal optimization models have gained increasing popularity in recent years. To a large extent, this development stems from the celebrated Lucas critique, which argued forcibly that traditional econometric models are not structural with respect to changes in the economic environment caused by policy regime shifts. The generalized method of moments (GMM) estimation procedure developed by Hansen (1982) is a leading example of a large research program in estimating parameters of taste and technology that are arguably invariant to shifts in policy rules. This estimation procedure has been used by many researchers to estimate nonlinear rational expectations models and has a major impact on the practice of macroeconomics.

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  • Ching-Sheng Mao, 1990. "Hypothesis testing and finite sample properties of generalized method of moments estimators: a Monte Carlo study," Working Paper 90-12, Federal Reserve Bank of Richmond.
  • Handle: RePEc:fip:fedrwp:90-12
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    References listed on IDEAS

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    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Singleton, Kenneth J., 1985. "Testing specifications of economic agents' intertemporal optimum problems in the presence of alternative models," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 391-413.
    3. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-1370, November.
    4. Martin S. Eichenbaum & Lars Peter Hansen & Kenneth J. Singleton, 1988. "A Time Series Analysis of Representative Agent Models of Consumption and Leisure Choice Under Uncertainty," The Quarterly Journal of Economics, Oxford University Press, vol. 103(1), pages 51-78.
    5. Hendry, David F., 1984. "Monte carlo experimentation in econometrics," Handbook of Econometrics,in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 16, pages 937-976 Elsevier.
    6. Wouter J. Den Haan & Albert Marcet, 1994. "Accuracy in Simulations," Review of Economic Studies, Oxford University Press, vol. 61(1), pages 3-17.
    7. Hall, Robert E, 1988. "Intertemporal Substitution in Consumption," Journal of Political Economy, University of Chicago Press, vol. 96(2), pages 339-357, April.
    8. Brock, William A. & Mirman, Leonard J., 1972. "Optimal economic growth and uncertainty: The discounted case," Journal of Economic Theory, Elsevier, vol. 4(3), pages 479-513, June.
    9. Ching-Sheng Mao, 1989. "Estimating intertemporal elasticity of substitution: the case of log- linear restrictions," Economic Review, Federal Reserve Bank of Richmond, issue Nov, pages 3-14.
    10. Tauchen, George, 1986. "Statistical Properties of Generalized Method-of-Moments Estimators of Structural Parameters Obtained from Financial Market Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(4), pages 397-416, October.
    11. King, Robert G. & Plosser, Charles I. & Rebelo, Sergio T., 1988. "Production, growth and business cycles : I. The basic neoclassical model," Journal of Monetary Economics, Elsevier, vol. 21(2-3), pages 195-232.
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    Cited by:

    1. Gomes, Fábio Augusto Reis & Ribeiro, Priscila Fernandes, 2015. "Estimating the elasticity of intertemporal substitution taking into account the precautionary savings motive," Journal of Macroeconomics, Elsevier, vol. 45(C), pages 108-123.
    2. Weber, Christian E., 2002. "Intertemporal non-separability and "rule of thumb" consumption," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 293-308, March.
    3. Isakova, Asel, 2010. "Currency substitution in the economies of Central Asia : how much does it cost?," BOFIT Discussion Papers 14/2010, Bank of Finland, Institute for Economies in Transition.
    4. Waqas Ahmed & Adnan Haider & Javed Iqbal, 2012. "Estimation of Discount Factor ß and Coefficient of Relative Risk Aversion ? in Selected Countries," Working Papers id:5087, eSocialSciences.
    5. Franke, Reiner & Westerhoff, Frank, 2012. "Structural stochastic volatility in asset pricing dynamics: Estimation and model contest," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1193-1211.
    6. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
    7. Franke, Reiner, 2009. "Applying the method of simulated moments to estimate a small agent-based asset pricing model," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 804-815, December.

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