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Do We Reject Too Often? Small Sample Bias in Tests of Rational Expectations

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Author Info

  • N. Gregory Mankiw

    (Harvard University)

  • Matthew D. Shapiro

Abstract

We examine the small sample properties of tests of rational expectations models. We show using Monte Carlo experiments that these tests can be extremely biased toward rejection for sample sizes typical in applied research. These biases are important when the time series examined are highly autoregressive. We also show that these tests are even more biased with detrended data. We present correct small sample critical values for our canonical problem.

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File URL: http://cowles.econ.yale.edu/P/cd/d07a/d0743.pdf
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Bibliographic Info

Paper provided by Cowles Foundation for Research in Economics, Yale University in its series Cowles Foundation Discussion Papers with number 743.

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Length: 20 pages
Date of creation: Apr 1985
Date of revision:
Publication status: Published in Economics Letters (1986), 20: 139-145
Handle: RePEc:cwl:cwldpp:743

Note: CFP 637.
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Postal: Yale University, Box 208281, New Haven, CT 06520-8281 USA
Phone: (203) 432-3702
Fax: (203) 432-6167
Web page: http://cowles.econ.yale.edu/
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Postal: Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA

Related research

Keywords: Rational expectations; non-stationary time series; detrending; small sample bias;

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Cited by:
  1. Leonardo Bartolini & Gordon M. Bodnar, 1996. "Are exchange rates excessively volatile? And what does "excessively volatile" mean, anyway?," Research Paper 9601, Federal Reserve Bank of New York.
  2. N. Gregory Mankiw & David H. Romer & Matthew D. Shapiro, 1989. "Stock Market Forecastability and Volatility: A Statistical Appraisal," NBER Working Papers 3154, National Bureau of Economic Research, Inc.

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