Measurement with Minimal Theory
A central debate in applied macroeconomics is whether statistical tools that use minimal identifying assumptions are useful for isolating promising models within a broad class. In this paper, I extend the analysis of Chari, Kehoe, and McGrattan (2005) to compare four statistical methods---structural VARs, VARMAs, unrestricted state space methods, and restricted state space methods---all applied to data from the same business cycle model. The objective is to determine which, if any, of the methods can successfully uncover moments of the underlying economy. The methods differ in the amount of a priori theory that is imposed, with structural VARs imposing minimal assumptions and restricted state space methods imposing the maximal. The moments that I focus on are those typically reported in the business cycle literature. Preliminary results show that the identifying assumptions of structural VARs, VARMAs, and unrestricted state space methods are too minimal: they cannot robustly uncover many of the moments business cycle researchers are interested in measuring.
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- V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2002.
"Business cycle accounting,"
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.
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- V. V. Chari & Patrick Kehoe & Ellen McGrattan, 2004. "Business Cycle Accounting," Levine's Bibliography 122247000000000560, UCLA Department of Economics.
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101, Federal Reserve Bank of Minneapolis.
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- 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.
- 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, 2007. "Are structural VARs with long-run restrictions useful in developing business cycle theory?," Staff Report 364, Federal Reserve Bank of Minneapolis.
- 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.
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