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 Dua-Miller 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 out-of-sample forecasting performance, using the Bayesian Vector Autoregressive (BVAR) method. The new indexes show 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 the truth in the 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.

The Congressional Budget Process and the Aggregate Level of Spending

This paper analyzes whether the Congressional budget process (instituted in 1974) leads to lower aggregate spending than does the piece-meal appropriations process that preceded it. Previous theoretical analysis, using spatial models of legislator preferences, is inconclusive. This paper uses a model of interest group lobbying, where a legislature determines spending on a national public good and on subsidies to subsets of the population that belong to nationwide sector-specific interest groups. In the appropriations process, the Appropriations Committee proposes a budget, maximizing the joint welfare of voters and the interest groups, that leads to overspending on subsidies. In the budget process, a Budget Committee proposes an aggregate level of spending (the budget resolution); the Appropriations Committee then proposes a budget. If the lobby groups are not subject to a binding resource constraint, the two institutional structures lead to identical outcomes. With such a constraint, however, there is a free rider problem among the groups in lobbying the Budget Committee, as each group only obtains a small fraction of the benefits from increasing the aggregate budget. If the number of groups is sufficiently large, each takes the budget resolution as given, and lobbies only the Appropriations Committee. The main results are that aggregate spending is lower, and social welfare higher, under the budget process; however, provision of the public good is suboptimal. The paper also presents two extensions: the first endogenizes the enforcement of the budget resolution by incorporating the relevant procedural rules into the model. The second analyzes statutory budget rules that limit spending levels, but can be revised by a simple majority vote. In each case,the free rider problem prevents the groups from securing the required changes to procedural and budget rules.

Student Performance in Traditional vs. Online Format: Evidence from an MBA Level Introductory Economics Class

All previous studies comparing online and face-to-face format for instruction of economics compared courses that were either online or face-to-face format and regressed exam scores on selected student characteristics. This approach is subject to the econometric problems of self-selection omitted unobserved variables. Our study uses two methods to deal with these problems. First we eliminate self-selection bias by using students from a course that uses both instruction formats. Second, we use the exam questions as the unit of observation, and eliminate omitted variable bias by using an indicator variable for each student to capture the effect of differences in unobserved student characteristics on learning outcomes. We report the finding that students had a significantly greater chance of answering a question correctly if it came from a chapter covered online.