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Why Is It So Hard to Measure the Current Output Gap?

  • Simon van Norden

    ((Bank of Canada))

In order for time series estimates of the output gap to be useful to policy makers, this paper argues that two factors will be critical. First, they must be able to produce an estimate of the current output gap based only on past information. Put another way, to evaluate the performance of such estimators, we should focus on their properties as _filters_ rather than _smoothers_. Second, the decomposition of actual output into potential output and the output gap must not be based on arbitrary assumptions about the time-series behaviour of these variables. In general, this leads to a multiplicity of possible solutions that may differ greatly in their policy implications. The arbitrary selection of one of these creates arbitrary policy advice. A trivial but flexible estimator of the output gap (dubbed TOFU) can be constructed which satisfies both of the above criteria. It estimates the output gap as part of a larger economic relationship. A discussion of its properties shows that except under very strict circumstances, such time series estimates will produce better estimates of the output gap ex post than they will ex ante. Furthermore, under certain conditions, contemporary and historical data will be of no use in estimating the output gap whatsoever. This in turn places limits on the extent to which time series methods can hope to improve upon structural estimates of the output gap.

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Paper provided by EconWPA in its series Macroeconomics with number 9506001.

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Length: 22 pages
Date of creation: 07 Jun 1995
Date of revision:
Handle: RePEc:wpa:wuwpma:9506001
Note: 22 pages of text & 3 pages graphs. Text and Graphs in separate Postscript files. Files compressed in a single Info-zip archive, then uuencoded.
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  1. Evans, George W. & Reichlin, Lucrezia, 1993. "Information, Forecasts and Measurement of the Business Cycle," CEPR Discussion Papers 756, C.E.P.R. Discussion Papers.
  2. Lucas, Robert Jr, 1976. "Econometric policy evaluation: A critique," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 1(1), pages 19-46, January.
  3. Lippi, Marco & Reichlin, Lucrezia, 1994. "VAR analysis, nonfundamental representations, blaschke matrices," Journal of Econometrics, Elsevier, vol. 63(1), pages 307-325, July.
  4. Setterfield, M. A. & Gordon, D. V. & Osberg, L., 1992. "Searching for a will o' the wisp : An empirical study of the NAIRU in Canada," European Economic Review, Elsevier, vol. 36(1), pages 119-136, January.
  5. Claude Giorno & Pete Richardson & Deborah Roseveare & Paul van den Noord, 1995. "Estimating Potential Output, Output Gaps and Structural Budget Balances," OECD Economics Department Working Papers 152, OECD Publishing.
  6. Christopher A. Sims, 1986. "Are forecasting models usable for policy analysis?," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 2-16.
  7. Lippi, Marco & Reichlin, Lucrezia, 1993. "The Dynamic Effects of Aggregate Demand and Supply Disturbances: Comment," American Economic Review, American Economic Association, vol. 83(3), pages 644-52, June.
  8. Alain DeSerres, & Alain Guay & Pierre St-Amant, . "Estimating and Projecting Potential Output Using Structural VAR Methodology: The Case of the Mexican Economy," Staff Working Papers 95-2, Bank of Canada.
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