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Comparing Alternative Output-Gap Estimators: A Monte Carlo Approach

  • Andrew Rennison
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    The author evaluates the ability of a variety of output-gap estimators to accurately measure the output gap in a model economy. A small estimated model of the Canadian economy is used to generate artificial data. Using output and inflation data generated by this model, the author uses each output-gap estimation methodology to construct an estimate of the true output gap. He then evaluates the methodologies by comparing their respective estimates of the output gap with the true gap. The estimators are evaluated on the basis of correlations between the actual and estimated output gap, as well as the root-mean-squared estimation error. The author also varies the properties of potential output and the output gap in the data-generating process to test the robustness of his results. His findings indicate that an estimator that combines the Hodrick-Prescott filter with a Blanchard-Quah structural vector autoregression (SVAR) yields an estimate that is accurate compared with competing methods at the end-of-sample. He also finds that the performance of the SVAR relative to that of other methodologies is quite robust to violations in the identifying assumptions of the SVAR.

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    Paper provided by Bank of Canada in its series Working Papers with number 03-8.

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    Length: 33 pages
    Date of creation: 2003
    Date of revision:
    Handle: RePEc:bca:bocawp:03-8
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    1. Kuttner, Kenneth N, 1994. "Estimating Potential Output as a Latent Variable," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 361-68, July.
    2. St-Amant, P. & van Norden, S., 1997. "Measurement of the Output Gap: A Discussion of Recent Research at the Bank of Canada," Technical Reports 79, Bank of Canada.
    3. repec:cup:etheor:v:12:y:1996:i:1:p:61-87 is not listed on IDEAS
    4. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
    5. Jean-Philippe Cayen & Simon van Norden, 2002. "La fiabilité des estimations de l'écart de production au Canada," Working Papers 02-10, Bank of Canada.
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    8. Paul Conway & Ben Hunt, 1997. "Estimating potential output: a semi-structural approach," Reserve Bank of New Zealand Discussion Paper Series G97/9, Reserve Bank of New Zealand.
    9. Ehlgen, Jurgen, 1998. "Distortionary effects of the optimal Hodrick-Prescott filter," Economics Letters, Elsevier, vol. 61(3), pages 345-349, December.
    10. Guay, A & St-Amant, P, 1996. "Do Mechanical Filters Provide a Good Approximation of Business Cycles?," Technical Reports 78, Bank of Canada.
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    12. Athanasios Orphanides & Simon van Norden, 2002. "The Unreliability of Output-Gap Estimates in Real Time," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 569-583, November.
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    15. Cooley, Thomas F. & Dwyer, Mark, 1998. "Business cycle analysis without much theory A look at structural VARs," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 57-88.
    16. Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(3), pages 231-47, July-Sept.
    17. Kichian, Maral, 1999. "Measuring Potential Output within a State-Space Framework," Working Papers 99-9, Bank of Canada.
    18. Wecker, William E, 1979. "Predicting the Turning Points of a Time Series," The Journal of Business, University of Chicago Press, vol. 52(1), pages 35-50, January.
    19. Clark, Peter K, 1987. "The Cyclical Component of U.S. Economic Activity," The Quarterly Journal of Economics, MIT Press, vol. 102(4), pages 797-814, November.
    20. Stephen Murchison, . "NAOMI A New Quarterly Forecasting Model Part II: A Guide to Canadian NAOMI," Working Papers-Department of Finance Canada 2001-25, Department of Finance Canada.
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