Performance Evaluation of the New Connecticut Leading Employment Index Using Lead Profiles and BVAR Models

Dua and Miller (1996) created leading and coincident employment indexes for the state of Connecticut, following Moore’s (1981) work at the national level. The performance of the DuaMiller indexes 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 outof-sample forecasting performance, using the Bayesian Vector Autoregressive (BVAR) method. The new indexes show improved performance in dating employment cycle chronologies. Mixed results emerge with the out-of-sample BVAR forecasting experiments. The new indexes outperform the old indexes during the late 1990s; the old indexes do better than the new indexes during the late 1980s. Naïve no-change forecasts win the forecasting race during the jobless recovery of the earlyand mid-1990s. Granger and Newbold (1986) caution 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.