Knowledge that Transforms

Plant shutdowns shape industry productivity, the dynamics of employment, and industrial restructuring. Plant closures account for more than half of gross job destruction in U.S. manufacturing. This paper examines the effects of firm structure on U.S. manufacturing plant closures. Plants belonging to multiplant firms and those owned by U.S. multinationals are less likely to exit. However, the superior survival chances are due to the characteristics of the plants rather than the nature of the firms. Controlling for plant and industry attributes, we find that plants owned by multiunit firms and U.S. multinationals are much more likely to close.

In this paper we develop and estimate a model to explain variations in immigration to the United States by source country since the early 1970s. The explanatory variables include ratios to the United States of source country income and education as well as relative inequality. In addition, we incorporate the stock of previous immigrants and a variety of variables representing different dimensions of the immigration quotas set by policy. We use the results to shed light on the impact of policy by simulating the effects of the key changes in immigration policy since the late 1970s. We also examine the factors that influenced the composition of U.S. immigration by source region over the entire period.

This paper examines the relationship between workforce demographics and aggregate productivity. Changes in the age structure of the workforce are found to be significantly correlated with changes in aggregate productivity. Different demographic structures may be related to almost one-quarter of the persistent productivity gap between the OECD and low-income nations as well as part of the productivity divergence between 1960 and 1990.

In this paper, we describe the results of a study assessing the relationship between the certification of teachers by the National Board for Professional Teaching Standards (NBPTS) and elementary-level student achievement. We examine whether NBPTS assesses the most effective applicants, whether certification by NBPTS serves as a signal of teacher quality, and whether completing the NBPTS assessment process serves as a catalyst for increasing teacher effectiveness. We find consistent evidence that NBPTS is identifying the more effective teacher applicants and that National Board Certified Teachers are generally more effective than teachers who never applied to the program. The statistical significance and magnitude of the “NBPTS effect,” however, differs significantly by grade level and student type. We do not find evidence that the NBPTS certification process itself does anything to increase teacher effectiveness.

This paper presents theory and evidence on the relationship between inequality and institutional quality. We exhibit a model in which the two may dynamically reinforce each other and set to test this relationship with a broad array of institutional measures. The double causality between institutional strength and a more equal distribution of income is empirically established using dynamic panel and linear feedback analysis.

This paper evaluates the effects of patent protection on pharmaceutical innovations for 26 countries that established pharmaceutical patent laws during 1978–2002. Controlling for country characteristics through matched sampling techniques to establish two proper comparison sets among 92 sampled countries and through country-pair fixed-effects regressions, this study yields robust results. National patent protection alone does not stimulate domestic innovation, as estimated by changes in citation-weighted U.S. patent awards, domestic R&D, and pharmaceutical industry exports. However, domestic innovation accelerates in countries with higher levels of economic development, educational attainment, and economic freedom. Additionally, there appears to be an optimal level of intellectual property rights regulation above which further enhancement reduces innovative activities.

Beginning in the late 1980s, American corporations began increasingly linking the compensation of central research personnel to the economic objectives of the corporation. This paper examines the impact of the shifting compensation of the heads of corporate research and development. Among firms with centralized R&D organizations, a clear relationship emerges: more long-term incentives (such as stock options and restricted stock) are associated with more heavily cited patents. These incentives also appear to be associated with more patent awards and patents of greater originality. Short-term incentives appear to be unrelated to measures of innovation.

Are there productivity spillovers from FDI to domestic firms, and, if so, how much should host countries be willing to pay to attract FDI? To examine these questions, we use a plant-level panel covering U.K. manufacturing from 1973 through 1992. Consistent with spillovers, we estimate a robust and significantly positive correlation between a domestic plant's TFP and the foreign-affiliate share of activity in that plant's industry. Typical estimates suggest that a 10-percentage-point increase in foreign presence in a U.K. industry raises the TFP of that industry's domestic plants by about 0.5%. We also use these estimates to calculate the per-job value of these spillovers at about £2,400 in 2000 prices ($4,300). These calculated values appear to be less than per-job incentives governments have granted in recent high-profile cases, in some cases several times less.

We examine inference in panel data when the number of groups is small, as is typically the case for difference-in-differences estimation and when some variables are fixed within groups. In this case, standard asymptotics based on the number of groups going to infinity provide a poor approximation to the finite sample distribution. We show that in some cases the t-statistic is distributed as t and propose simple two-step estimators for these cases. We apply our analysis to two well-known papers. We confirm our theoretical analysis with Monte Carlo simulations.

A growing literature documents important gains in asset return volatility forecasting via use of realized variation measures constructed from high-frequency returns. We progress by using newly developed bipower variation measures and corresponding nonparametric tests for jumps. Our empirical analyses of exchange rates, equity index returns, and bond yields suggest that the volatility jump component is both highly important and distinctly less persistent than the continuous component, and that separating the rough jump moves from the smooth continuous moves results in significant out-of-sample volatility forecast improvements. Moreover, many of the significant jumps are associated with specific macroeconomic news announcements.