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Small sample properties of GMM for business cycle analysis

  • Lawrence J. Christiano
  • Wouter den Haan

The authors investigate, by Monte Carlo methods, the finite sample properties of generalized method of moments procedures for conducting inference about statistics that are of interest in the business cycle literature. These statistics include the second moments of data filtered using the first difference and Hodrick-Prescott filters, and they include statistics for evaluating model fit. The authors' results indicate that, for the procedures considered, the existing asymptotic theory is not a good guide in a sample the size of quarterly postwar U.S. data.

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Paper provided by Federal Reserve Bank of Chicago in its series Working Paper Series, Macroeconomic Issues with number 95-3.

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Date of creation: 1995
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Handle: RePEc:fip:fedhma:95-3
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  1. David K. Backus & Patrick J. Kehoe, 1991. "International evidence on the historical properties of business cycles," Staff Report 145, Federal Reserve Bank of Minneapolis.
  2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
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  7. Kenneth D. West & David W. Wilcox, 1993. "Some Evidence on Finite Sample Behavior of an Instrumental Variables Estimator of the Linear Quadtratic Inventory Model," NBER Technical Working Papers 0139, National Bureau of Economic Research, Inc.
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  9. R. Anton Braun & Charles L. Evans, 1994. "Seasonality and equilibrium business cycle theories," Staff Report 168, Federal Reserve Bank of Minneapolis.
  10. Fuhrer, Jeffrey C. & Moore, George R. & Schuh, Scott D., 1995. "Estimating the linear-quadratic inventory model Maximum likelihood versus generalized method of moments," Journal of Monetary Economics, Elsevier, vol. 35(1), pages 115-157, February.
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  12. Christiano, Lawrence J., 1988. "Why does inventory investment fluctuate so much?," Journal of Monetary Economics, Elsevier, vol. 21(2-3), pages 247-280.
  13. R. Anton Braun & Charles L. Evans, 1996. "Seasonal Solow residuals and Christmas: a case for labor hoarding and increasing returns," Working Papers 575, Federal Reserve Bank of Minneapolis.
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  19. Lawrence J. Christiano, 1988. "Searching For a Break in GNP," NBER Working Papers 2695, National Bureau of Economic Research, Inc.
  20. Marianne Baxter & Robert G. King, 1999. "Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 575-593, November.
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  22. Stephen G. Cecchetti & Pok-sang Lam & Nelson C. Clark, 1991. "The Equity Premium and the Risk Free Rate: Matching the Moments," NBER Working Papers 3752, National Bureau of Economic Research, Inc.
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  25. Edward C. Prescott, 1986. "Theory ahead of business cycle measurement," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall, pages 9-22.
  26. Ericsson, Neil R, 1991. "Monte Carlo Methodology and the Finite Sample Properties of Instrumental Variables Statistics for Testing Nested and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 59(5), pages 1249-77, September.
  27. Hansen, Lars Peter & Hodrick, Robert J, 1980. "Forward Exchange Rates as Optimal Predictors of Future Spot Rates: An Econometric Analysis," Journal of Political Economy, University of Chicago Press, vol. 88(5), pages 829-53, October.
  28. Burnside, Craig & Eichenbaum, Martin & Rebelo, Sergio, 1993. "Labor Hoarding and the Business Cycle," Journal of Political Economy, University of Chicago Press, vol. 101(2), pages 245-73, April.
  29. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-70, November.
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  31. den Haan, Wouter J., 1995. "The term structure of interest rates in real and monetary economies," Journal of Economic Dynamics and Control, Elsevier, vol. 19(5-7), pages 909-940.
  32. Donald W.K. Andrews & Christopher J. Monahan, 1990. "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator," Cowles Foundation Discussion Papers 942, Cowles Foundation for Research in Economics, Yale University.
  33. King, Robert G. & Rebelo, Sergio T., 1993. "Low frequency filtering and real business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 17(1-2), pages 207-231.
  34. 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.
  35. Timothy Cogley & James M. Nason, 1993. "Effects of the Hodrick-Prescott filter on trend and difference stationary time series: implications for business cycle research," Working Papers in Applied Economic Theory 93-01, Federal Reserve Bank of San Francisco.
  36. Fisher, Jonas D. M., 1997. "Relative prices, complementarities and comovement among components of aggregate expenditures," Journal of Monetary Economics, Elsevier, vol. 39(3), pages 449-474, August.
  37. Singleton, Kenneth J., 1988. "Econometric issues in the analysis of equilibrium business cycle models," Journal of Monetary Economics, Elsevier, vol. 21(2-3), pages 361-386.
  38. Anton Braun, R., 1994. "Tax disturbances and real economic activity in the postwar United States," Journal of Monetary Economics, Elsevier, vol. 33(3), pages 441-462, June.
  39. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119, July.
  40. Long, John B, Jr & Plosser, Charles I, 1983. "Real Business Cycles," Journal of Political Economy, University of Chicago Press, vol. 91(1), pages 39-69, February.
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