Some recent time-series applications use probit models to measure the forecasting power of a set of variables. Correct inferences about the significance of the variables requires a consistent estimator of the covariance matrix of the estimated model coefficients. A potential source of...

The econometrics literature contains a variety of two-sided tests for unknown breakpoints in time-series models with one or more parameters. This paper derives an analogous one-sided test that takes into account the direction of the change for a single parameter. In particular, we propose a sup...

Empirical research over the last decade has uncovered predictive relationships between the slope of the yield curve and subsequent real activity and inflation. Some of these relationships are highly significant, but their theoretical motivations suggest that they may not be stable over time. We...

This paper examines how workers use 401(k) plans by examining their participation, contribution, and withdrawal decisions. Sixty-five percent of eligible workers participate in 401(k) plans. Employee participation rises with income, age, job tenure, and education. While participation also rises...

Eleven of fourteen monetary tightening cycles since 1955 were followed by increases in unemployment; three were not. The term spread at the end of these cycles discriminates almost perfectly between subsequent outcomes, but levels of nominal or real interest rates, as well as other interest rate...

One of the most robust stylized facts in macroeconomics is the forecasting power of the term spread for future real activity. The economic rationale for this forecasting power usually appeals to expectations of future interest rates, which affect the slope of the term structure. In this paper,...

Various methods are available to extract the "business cycle component" of a given time series variable. These methods may be derived as solutions to frequency extraction or signal extraction problems and differ in both their handling of trends and noise and their assumptions about the ideal...

This paper introduces a generalized approach to canonical regression, in which a set of jointly dependent variables enters the left-hand side of the equation as a linear combination, formally like the linear combination of regressors in the right-hand side of the equation. Natural applications...