Knowledge that Transforms

In this paper we examine whether the requirements that workers must satisfy to qualify for unemployment insurance (UI) benefits in any succeeding period of joblessness affect the duration of employment spells. This behavioral consequence of a UI system has been neglected in empirical research, which has instead focused on the effects of UI parameters on the actions of the unemployed. The effect is identified by a unique change in the eligibility requirements of the Canadian UI system in 1990, which increased the weeks of employment required to establish UI eligibility. We provide a variety of estimates of this behavioral effect. In our preferred set of results, we find a significant increase in the employment hazard in the week that an individual satisfies the eligibility requirement in many regions of the country. In the spirit of Feldstein's (1976) study of temporary layoffs, the results provide new evidence of the impact of UI system parameters on the actions of employers and workers.

We estimate a multivariate ARFIMA model to illustrate a cointegration testing methodology based on joint estimates of the fractional orders of integration of a cointegrating vector and its parent series. Previous cointegration tests relied on a two-step testing procedure and maintained the assumption in the second step that the parent series were known to have a unit root. In our empirical example of fractional cointegration, we illustrate how uncertainty regarding the order of integration of the parent series can be even more important than uncertainty regarding the order of integration of the cointegrating vector when testing for cointegration.

This study used a 1976–1992 panel data set to test whether farm machinery investors face finance constraints. Tests were based on fundamental q investment equations in which cash flow was added as an additional explanatory variable. Results indicated that (1) credit constraints were generally not a problem during the 1970s boom, (2) credit constraints became a problem during the 1980s and early 1990s because of tighter credit and/or more conservative financial managerial styles, (3) the investment-cash flow relationships of low-debt and older-operator farms were not significantly affected by farm business cycles, and (4) the investment-cash flow relationships of high-debt and young-operator farms were affected strongly by business cycles. Debt level was the strongest determinant of credit constraints; asset size and operator age were less important.

This paper considers the effects for offering a “would-not-vote” option in contingent valuation (CV) questions framed using the referendum format. This approach arises from a suggestion made by the National Oceanic and Atmospheric Administration's (NOAA) panel on contingent valuation. The NOAA panel was asked to evaluate the use of this method for estimating the economic value of nonmarketed environmental resources in the context of natural resource damage assessments. This test used the CV questionnaire developed for the study of the Exxon Valdez oil spill conducted by the State of Alaska with in-person interviews. The findings suggest that when those selecting the “would-not-vote” response are treated as having voted “against” the program (a conservative coding), offering this option does not alter (1) the distribution of “for” and “against” responses (2) the estimates of willingness to pay derived from these choices, or (3) the construct validity of the results.

This study tests for the presence of prejudicial or “noneconomic” discrimination on the part of mortgage lenders by evaluating the performance of home mortgage loans. The approach differs from that of previous studies of loan performance in that it is based on the proposition that noneconomic discrimination should be more pronounced in less competitive lending environments, while statistical discrimination should not. Using a rich set of FHA-insured loan records and measures of local market concentration to proxy the competitive environment, we test for the prediction of better loan performance by minority borrowers relative to white borrowers in more concentrated markets. We argue that this approach substantially reduces the potential for omitted-variable bias that has cast a shadow on previous studies of lending discrimination. Results fail to reject the null hypothesis of no noneconomic discrimination.

We assume that the instantaneous riskless rate reverts toward a central tendency which, in turn, is changing stochastically over time. As a result, current short-term rates are not sufficient to predict future short-term rate movements, as it would be the case if the central tendency were constant. However, since longer maturity bond prices incorporate information about the central tendency, longer maturity bond yields can be used to predict future short-term rate movements. We develop a two-factor model of the term structure which implies that a linear combination of any two rates can be used as a proxy for the central tendency. Based on this central-tendency proxy, we estimate a model of the one-month rate that performs better than models which assume the central tendency to be constant.

A feature of U.S. postwar business cycle experience that is by now widely documented is the tendency of the spread between the respective interest rates on commercial paper and Treasury bills to widen shortly before the onset of recessions. By contrast, the paper—bill spread did not anticipate the 1990–1991 recession. Empirical work presented in this paper supports two (not mutually exclusive) explanations for this departure from past experience. First, at least part of the paper—bill spread's predictive content with respect to business cycle fluctuations stems from its role as an indicator of monetary policy, but the 1990–1991 recession was unusual in postwar U.S. experience in not being immediately precipitated by tight monetary policy. Second, movements of the spread during the few years just prior to the 1990–1991 recession were strongly influenced by changes in the relative quantities of commercial paper, bank CDs, and Treasury bills that occurred for reasons unrelated to the business cycle. This latter finding in particular sheds light on the important role of imperfect substitutability of different short-term debt instruments in investors' portfolios, and highlights the burdens associated with using relative interest rate relationships as business cycle indicators.

This paper explores issues that arise in the evaluation of social programs using experimental data in the frequently encountered case where some of the experimental treatment group members drop out of the program prior to receiving treatment. We begin with the standard estimator for this case and the identifying assumption upon which it rests. We then examine the behavior of the estimator when the dropouts receive a partial “dose” of the program treatment prior to dropping out of the program. In the case of partial treatment, the identifying assumption is typically violated, thereby making the estimator inconsistent for the conventional parameter of interest: the impact of full treatment on the fully treated. We develop a test of the identifying assumption underlying the standard estimator and consider whether exclusion restrictions produce identification of the mean impact of the program when this assumption fails to hold. Finally, we discuss alternative parameters of interest in the presence of partial treatment among the dropouts and argue that the conventional parameter is not always the economically interesting one. We apply our methods to data from a recent experimental evaluation of the Job Training Partnership Act (JTPA) program.

This study uses data from the National Longitudinal Survey of Youth to distinguish empirically between mover—stayer, “search good,” and “experience good” models of job mobility. We estimate wage models in which the pattern of overall job mobility affects both the level and tenure slope of the log-wage path. After controlling for the correlation between mobility patterns and time-constant person- and job-specific unobservables, we find that workers who undergo persistent mobility have lower log-wage paths than less mobile workers. This finding is consistent with models in which job mobility is driven by time-varying unobservables, such as “experience good” models, where changes in perceived match quality cause turnover.

Asymmetric behavior has been documented in postwar quar-terly U.S. unemployment rates. This suggests that improvement over conventional linear forecasts may be possible through the use of nonlinear time-series models. In this note an out-of-sample forecasting competition is carried out for a set of leading nonlinear time-series models. It is shown that several nonlinear forecasts do indeed dominate the linear forecast. The results are sensitive, however, to whether a stationarity-inducing transfor-mation is applied to the nonstationary unemployment rate series.