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In this paper we examine the impacts of toxic chemical releases on labor productivity. The hypothesis is that exposure to releases results in chronic or acute illnesses, which increases number of work days lost. To test the hypothesis we combine data from the National Health Interview Survey with data from US Environmental Protection Agency’s Toxic Release Inventory, using an instrumental variable approach to control for endogeneity of subjective binary health status. We find that the survey respondents are significantly more likely to have increased work days lost as their exposure to toxic releases increases and that work days lost increase at an increasing rate with diminished health status. [ABSTRACT FROM AUTHOR]

Rennison (Comparing alternative output gap estimations: a Monte Carlo approach, 2003) has provided simulation-based evidence showing that the joint use of extended multivariate filters and structural vector autoregression models is optimal for estimating potential output. We use this approach to estimate the two components of potential GDP: the full-employment labour input and trend labour productivity. This decomposition is useful for identifying sources of fluctuations in potential output. It reveals, for example, that the vigorous growth rate of U.S. potential GDP recorded during the second half of the 1990s is attributable to a fall in the structural rate of unemployment and a marked upswing in trend productivity growth. [ABSTRACT FROM AUTHOR]

The article discusses methods with which universities in the United States can effectively serve the social and economic ends demanded by the institution while simultaneously adhering to classical academic norms that encourage the free and open exchange of research and ideas. To effectively achieve this end, universities must be measured not against the traditional yardstick of productivity, since they have never produced tangible objects besides people, and instead should focus on the production of students and research.

This study uses state-level variation in labor productivity levels at twenty-year intervals between 1880 and 1980 to examine the relative importance of institutional and geographical influences in explaining observed and persistent differences in standards of living over time and across regions. Focusing on fundamental rather than proximate influences, we find that both institutional characteristics and some physical geography characteristics account for a high proportion of the differences in state productivity levels: states with navigable waterways, a large minerals endowment, and no slaves in 1860, on average, had higher labor productivity levels throughout the sample period. However, we find little support for two other influences that have previously received attention—climate and latitude. [ABSTRACT FROM AUTHOR]

Following Brown and Medoff (1978), a number of studies have investigated the effect of unionization on labor productivity using a log-linear, Cobb-Douglas model of technology. To derive this model, a first-order Taylor-series approximation to the intrinsically nonlinear unionization variable is made; the resulting linear equation is estimated with generalized least-squares (GLS) techniques. We demonstrate that this approximation introduces a bias that necessarily results in an overstatement of the absolute value of the exact union productivity effect. We illustrate the magnitude of this bias by comparing GLS estimates of the linear Brown-Medoff model with GLS estimates of the exact, nonlinear relationship, using aggregate time-series data from the private domestic sector of the U.S. economy. [ABSTRACT FROM AUTHOR]