Knowledge that Transforms

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.

The ability of yield spreads to predict changes in long-term interest rates implied by the expectations hypothesis is usually rejected. It is suggested that this rejection is often caused by high persistence in the spread when standard inference is employed. Instead, the asymptotically valid method of Cavanagh et al. (1995) is applied to monthly U.S. data from 1952:1-1991:2. The persistence of the spreads seems to have varied over time, and in subsample analysis, the expectations hypothesis cannot be rejected at the long end of the maturity spectrum.

This paper examines the sources of productivity growth for the, U.S. telecommunications industry from 1935 to 1987. These years encompass both the pre-and post-AT&T divestiture periods. We formulate a structural model that accounts for both changes in the cost and the demand side of the industry. We measure the contributions of aggregate demand, information intensity of the economy, price-cost margins, relative factor prices, direct and indirect effects of technological progress, and R&D investment on total-factor productivity (TFP) growth rate. We show that TFP growth rate as conventionally measured is a seriously biased measure of rate of technical change in this industry.

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.

One current educational reform seeks to reward the “value added” by teachers and schools based on the average change in pupil test scores over time. In this paper, we outline the conditions under which the average change in scores is sufficient to rank schools in terms of value added. A key condition is that socioeconomic outcomes be a linear function of test scores. Absent this condition, one can still derive the optimal value-added policy if one knows the relationship between test scores and socioeconomic outcomes, and the distribution of test scores both before and after the intervention.Using the National Longitudinal Survey of Youth, we find a nonlinear relationship between test scores and one important outcome: log wages. We find no consistent pattern in the curvature of log wage returns to test scores (whether percentiles, scaled, or raw scores). This implies that, used alone, the average gain in test scores is an inadequate measure of school performance and current value-added methodology may misdirect school resources.

In many practical applications, one is interested in obtaining confidence intervals for nonlinear functions of the parameters. This paper considers the following different methods: Fieller's method, Taylor's series expansion, and bootstrap methods. Compared to some of the earlier results in the empirical studies that are against the application of bootstrap, our results suggest a different conclusion in favor of the bootstrap methods.

Auctions of government securities typically permit bidders to enter multiple price-quantity bids. Despite the widespread adoption of this institutional feature and its use by bidders, the motivations behind its use and its effects on auction outcomes are not well understood theoretically and have been little explored empirically. This paper proposes that bidders use multiple bids to adjust for winner's curse: By spreading her bids, a bidder aligns her outcome more closely to the aggregate outcome of the auction. This hypothesis is tested using bidding data from treasury bill auctions in Portugal. I find that, ceteris paribus, a bidder submits a greater number of bids and disperses prices on these bids more widely when there is a greater potential for winner's curse. In particular, both these measures of bid-spreading increase with the volatility of market interest rates and the expected number of participating well-informed bidders.

This paper empirically investigates high-yield bond default and call behavior using a competing risks hazard model that simultaneously estimates the impact of bond age, issue-specific characteristics and business conditions on both events. Results reveal nonmonotonic aging effects: default rates increase and then drop while call rates first increase and then level off. Rating and coupon size affect default risk, while maturity and issue size impact only call rates. Defaults are more likely when economic conditions have worsened and no improvement is anticipated. Calls are more likely when interest rates have decreased but are expected to rise.

In this paper, we estimate a transition model that allows for measurement errors in the data. The measurement errors arise because the survey design is partly retrospective, so that individuals sometimes forget or misclassify their past labor market transitions. The observed data are adjusted for errors via a measurement-error mechanism. The parameters of the distribution of the true data, and those of the measurement-error mechanism are estimated by a two-stage method. The results, based on the 1990-1992 French labor force survey, show that neglecting measurement errors leads to an underestimation of the average durations spent in labor market states. The estimates of some important transition probabilities between states are also biased by the measurement errors.