Performance evaluation of the New Connecticut Leading Employment Index using lead profiles and BVAR models
AbstractThe 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 Â© 2006 John Wiley & Sons, Ltd.
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Bibliographic InfoArticle provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.
Volume (Year): 25 (2006)
Issue (Month): 6 ()
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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966
Other versions of this item:
- Anirvan Banerji & Pami Dua & Stephen M. Miller, 2003. "Performance Evaluation of the New Connecticut Leading Employment Index Using Lead Profiles and BVAR Models," Working papers 114, Centre for Development Economics, Delhi School of Economics.
- Anirvan Banerji & Pami Dua & Stephen M. Miller, 2002. "Performance Evaluation of the New Connecticut Leading Employment Index Using Lead Profiles and BVAR Models," Working papers 2002-34, University of Connecticut, Department of Economics, revised Jun 2005.
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
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