Journal Article
Measurement with minimal theory
Abstract: Applied macroeconomists interested in identifying the sources of business cycle fluctuations typically have no more than 40 or 50 years of data at a quarterly frequency. With sample sizes that small, identifi cation may not be possible even with correctly specifi ed representations of the data. In this article, I investigate whether small samples are indeed a problem for some commonly used statistical representations. I compare three?a vector autoregressive moving average (VARMA), an unrestricted state space, and a restricted state space?that are all consistent with the same prototype business cycle model. The statistical representations that I consider differ in the amount of a priori theory that is imposed, but all are correctly specifi ed. I fi nd that the identifying assumptions of VARMAs and unrestricted state space representations are too minimal: the range of estimates for statistics of interest for business cycle researchers is so large as to be uninformative.
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Bibliographic Information
Provider: Federal Reserve Bank of Minneapolis
Part of Series: Quarterly Review
Publication Date: 2010
Issue: July
Pages: 2-13
Order Number: v. 33, No. 1