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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

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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/cp/p06a/p0637.pdf
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File URL: http://cowles.econ.yale.edu/P/cd/d07a/d0743.pdf
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Publisher Info
Paper provided by Cowles Foundation, Yale University in its series Cowles Foundation Discussion Papers with number 743.

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

Note: CFP 637.
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Related research
Keywords: Rational expectations; non-stationary time series; detrending; small sample bias;

Cited by:
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  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. [Downloadable!]
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  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. [Downloadable!] (restricted)
    Other versions:
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