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Performance evaluation of the New Connecticut Leading Employment Index using lead profiles and BVAR models

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  • Pami Dua

    (Delhi School of Economics, New Delhi, India)

  • Anirvan Banerji

    (Economic Cycle Research Institute, New York, USA)

  • Stephen M. Miller

    (University of Nevada, Las Vegas, Las Vegas, Nevada, USA)

Abstract

The leading and coincident employment indexes for the state of Connecticut developed following the recession of the early 1990s fell short of expectations. This paper performs two tasks. First, it describes the process of revising the Connecticut Coincident and Leading Employment Indexes. Second, it analyzes the statistical properties and performance of the new indexes by comparing the lead profiles of the new and old indexes as well as their out-of-sample forecasting performance, using the Bayesian Vector Autoregressive (BVAR) method. The new coincident index shows improved performance in dating employment cycle chronologies. The lead profile test demonstrates that superiority in a rigorous, non-parametric statistic fashion. The mixed evidence on the BVAR forecasting experiments illustrates that leading indexes properly predict cycle turning points and do not necessarily provide accurate forecasts except at turning points, a view that our results support.  Copyright © 2006 John Wiley & Sons, Ltd.

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Bibliographic Info

Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 25 (2006)
Issue (Month): 6 ()
Pages: 415-437

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Handle: RePEc:jof:jforec:v:25:y:2006:i:6:p:415-437

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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  1. Sims, Christopher A & Stock, James H & Watson, Mark W, 1990. "Inference in Linear Time Series Models with Some Unit Roots," Econometrica, Econometric Society, vol. 58(1), pages 113-44, January.
  2. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
  3. Cooley, Thomas F. & Leroy, Stephen F., 1985. "Atheoretical macroeconometrics: A critique," Journal of Monetary Economics, Elsevier, vol. 16(3), pages 283-308, November.
  4. Pami Dua & Stephen Miller, 1995. "Forecasting and Analyzing Economic Activity with Coincident and Leading Indexes: The Case of Connecticut," Working papers 1995-05, University of Connecticut, Department of Economics.
  5. Sims, Christopher A., 1988. "Bayesian skepticism on unit root econometrics," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 463-474.
  6. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1, October.
  7. Layton, Allan P & Moore, Geoffrey H, 1989. "Leading Indicators for the Service Sector," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(3), pages 379-86, July.
  8. Zellner, Arnold & Palm, Franz, 1974. "Time series analysis and simultaneous equation econometric models," Journal of Econometrics, Elsevier, vol. 2(1), pages 17-54, May.
  9. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1983. "Forecasting and Conditional Projection Using Realistic Prior Distributions," NBER Working Papers 1202, National Bureau of Economic Research, Inc.
  10. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
  11. Richard M. Todd, 1984. "Improving economic forecasting with Bayesian vector autoregression," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall.
  12. Robert B. Litterman, 1984. "Above-average national growth in 1985 and 1986," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall.
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Cited by:
  1. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2010. "Forecasting Nevada Gross Gaming Revenue and Taxable Sales Using Coincident and Leading Employment Indexes," Working Papers 201018, University of Pretoria, Department of Economics.
  2. Rangan Gupta & Sonali Das, 2008. "Predicting Downturns in the US Housing Market: A Bayesian Approach," Working Papers 200821, University of Pretoria, Department of Economics.
  3. Hong Chen, 2010. "Using Financial and Macroeconomic Indicators to Forecast Sales of Large Development and Construction Firms," The Journal of Real Estate Finance and Economics, Springer, vol. 40(3), pages 310-331, April.

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