Neither the issue of how local and aggregate labor markets interact over time-nor the issue of how heterogeneity by education, race, and other factors interacts with these spatial dynamics-has previously been explored in the literature on the cyclicality of real wages. This study investigates how real wages respond to local and aggregate unemployment rates over time, and explores possible heterogeneities in the responses. Results, based upon data from the Panel Study of Income Dynamics, indicate that real wages move procyclically with both aggregate and local markets, but that the response to local changes occurs with a lag; that rates of return to education are procyclical overall for aggregate labor markets, but tend to be countercyclical for blacks; and that wages of union, manufacturing, blue-collar, and black workers tend to be less procyclical, even countercyclical for black college graduates. Overall, we find substantial spatial dynamics and heterogeneity in the cyclicality of real wages.

An important factor driving energy policy over the past two decades has been the “energy paradox,” the perception that consumers apply unreasonably high hurdle rates to energy-saving investments. We explore one possible explanation for this apparent puzzle: that realized returns fall short of the returns promised by engineers and product manufacturers. Using a unique data set, we find that the realized return to attic insulation is statistically significant, but the median estimate (9.7%) is almost identical to a discount rate for this investment implied by a CAPM analysis. We conclude that the case for the energy paradox is weaker than has previously been believed.

We demonstrate that the conventional practice of running firm investment regressions on beginning-of-period average Q cannot recover structural parameters related to adjustment costs. We propose two new methods of estimating these structural parameters by using financial market information (average Q's). We find that the sensitivity of investment to Q is more than ten times higher than estimated in conventional Q regressions. Furthermore, a firm's investment rate is more responsive to expected future Q the higher the level of this Q; i.e., investment is a convex function of fundamentals. The cost of installing new capital is estimated to be approximately 10% to 13% of the total investment cost (including purchase) at usual rates of investment.

Using data from professional baseball, basketball, and hockey, we estimate the parameters of a sequential game model of best-of-n championship series controlling for measured and unmeasured differences in team strength and bootstrapping the maximum-likelihood estimates to improve their small sample properties. We find negligible strategic effects in all three sports: teams play as well as possible in each game regardless of the game's importance in the series. We also estimate negligible unobserved heterogeneity after controlling for regular season records and past appearance in the championship series: Teams are estimated to be exactly as strong as they appear on paper.

Random utility models (RUMs) are used in the literature to model consumer choices from among a discrete set of alternatives, and they typically impose a constant marginal utility of income on individual preferences. This assumption is driven partially by the difficulty of constructing welfare estimates in models with nonlinear income effects. Recently, McFadden (1995) developed an algorithm for computing these welfare impacts using a Monte Carlo Markov chain simulator for generalized extreme-value variates. This paper investigates the empirical consequences of nonlinear RUMs in the case of sportfishing modal choice, while refining and contrasting the available methods for welfare estimation.

Previous property tax capitalization studies assume that families itemize, that they save in taxable assets, and that real interest income is taxed. However, many families do not itemize, many families invest in tax-deferred assets, and nominal interest income is taxed. As a consequence, prior studies likely misspecify the property tax capitalization equation for roughly ninety percent of their samples. Taking federal tax provisions into account increases the precision of our estimated capitalization rate. In addition, our results suggest that biases in prior studies likely contribute to the variety of capitalization estimates in the literature.

Acommon model for security price dynamics is the continuous-time stochastic volatility model. For this model, Hull and White (1987) show that the price of a derivative claim is the conditional expectation of the Black-Scholes price with the forward integrated variance replacing the Black-Scholes variance. Implementing the Hull and White characterization requires both estimates of the price dynamics and the conditional distribution of the forward integrated variance given observed variables. Using daily data on close-to-close price movement and the daily range, we find that standard models do not fit the data very well and that a more general three-factor model does better, as it mimics the long-memory feature of financial volatility. We develop techniques for estimating the conditional distribution of the forward integrated variance given observed variables.