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Performance evaluation of the New Connecticut Leading Employment Index using lead profiles and BVAR models Author info | Abstract | Publisher info | Download info | Related research | Statistics 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)
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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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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:415-437Contact details of provider: Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966
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Sonali Das & Rangan Gupta & Alain Kabundi, 2008.
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