Measurement with minimal theory
AbstractApplied 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Federal Reserve Bank of Minneapolis in its journal Quarterly Review.
Volume (Year): (2010)
Issue (Month): July ()
Other versions of this item:
- E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Harald Uhlig, 1998.
"A Toolkit for Analysing Nonlinear Dynamic Stochastic Models Easily,"
123, Quantitative Macroeconomics & Real Business Cycles.
- Harald Uhlig, 1995. "A toolkit for analyzing nonlinear dynamic stochastic models easily," Discussion Paper / Institute for Empirical Macroeconomics 101, Federal Reserve Bank of Minneapolis.
- Uhlig, H., 1995. "A toolkit for analyzing nonlinear dynamic stochastic models easily," Discussion Paper 1995-97, Tilburg University, Center for Economic Research.
- V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2007.
"Business Cycle Accounting,"
Econometric Society, vol. 75(3), pages 781-836, 05.
- V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2002. "Business cycle accounting," Working Papers 625, Federal Reserve Bank of Minneapolis.
- V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2006. "Business cycle accounting," Staff Report 328, Federal Reserve Bank of Minneapolis.
- V.V. Chari & Patrick J. Kehoe & Ellen McGrattan, 2004. "Business Cycle Accounting," NBER Working Papers 10351, National Bureau of Economic Research, Inc.
- V V Chari & Patrick J Kehoe & Ellen R. McGrattan, 2003. "Business Cycle Accounting," Levine's Bibliography 506439000000000421, UCLA Department of Economics.
- V. V. Chari & Patrick Kehoe & Ellen McGrattan, 2004. "Business Cycle Accounting," Levine's Bibliography 122247000000000560, UCLA Department of Economics.
- Chari, V.V. & Kehoe, Patrick J. & McGrattan, Ellen R., 2008.
"Are structural VARs with long-run restrictions useful in developing business cycle theory?,"
Journal of Monetary Economics,
Elsevier, vol. 55(8), pages 1337-1352, November.
- V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2008. "Are Structural VARs with Long-Run Restrictions Useful in Developing Business Cycle Theory?," NBER Working Papers 14430, National Bureau of Economic Research, Inc.
- V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2007. "Are structural VARs with long-run restrictions useful in developing business cycle theory?," Staff Report 364, Federal Reserve Bank of Minneapolis.
- Hannan, E J, 1976. "The Identification and Parameterization of ARMAX and State Space Forms," Econometrica, Econometric Society, vol. 44(4), pages 713-23, July.
- Burmeister, Edwin & Wall, Kent D & Hamilton, James D, 1986. "Estimation of Unobserved Expected Monthly Inflation Using Kalman Filtering," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(2), pages 147-60, April.
- Christian Kascha & Karel Mertens, 2008.
"Business cycle analysis and VARMA models,"
2008/05, Norges Bank.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Janelle Ruswick).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.