Evidence of the importance of agglomeration economies in productivity is reported by a number of studies in regional economics. We extend the literature by looking into agglomeration and congestion in innovation and technological change using an endogenous innovation approach. It turns out that the geographic specificity of knowledge spillovers is also a central concern. Using data from U.S. states, evidence is found that knowledge spillovers are geographically concentrated but agglomeration economies far outweigh congestion effects. These results have important implications for new growth theory as well as regional economics because growth theorists have abandoned the scale implications of their models.

This paper employs a hazard model to analyse the impact of education and two types of prison employment programmes on recidivism over a ten-year period for 4515 prisoners released from Ohio prisons in 1992. Estimations with a Weibull mixture model and propensity score approach provide two means for investigating self-selection bias. Selection bias is detected for participation in the most common prison job programme but has little effect on estimated marginal savings impacts of prison industry and education programmes. Estimates of the cost savings from postponing return to prison due to programme participation are provided. The potential for cost savings through decreasing or delaying return to prison is an important finding given the substantial and increasing cost of incarceration. Copyright (c) The London School of Economics and Political Science 2008.

No abstract

Evidence of the importance of urban agglomeration and the offsetting effects of congestion are provided in a number of studies of productivity and wages. Little attention has been paid to this evidence in the economic growth literature, where the recent focus is on technological change. We extend the idea of agglomeration and congestion effects to the area of innovation by empirically looking for a nonlinear link between population density and patent activity. A panel data set consisting of observations on 302 USA metropolitan statistical areas (MSAs) over a 10-year period from 1990 to 1999 is utilized. Following the patent and R&D literature, models that account for the discreet nature of the dependent variable are employed. Strong evidence is found that agglomeration and congestion are important in explaining the vast differences in patent rates across US cities. The most important reason cities continue to exist, given the dramatic drop in transportation costs for physical goods over the last century, is probably related to the forces of agglomeration as they apply to knowledge spillovers. Therefore, the empirical investigation proposed here is an important part of understanding the viability of urban areas in the future.

No abstract

Evidence suggests that race‐ and gender‐based discrimination are prevalent. If discrimination misallocates resources then it is likely to generate social costs. This paper provides a general equilibrium model of the impacts of discrimination. We analyze effects of labor market discrimination in a model where agents make human capital decisions based on comparing the marginal benefits and marginal costs of additional human capital accumulation. Life expectancy is a consideration in making human capital decisions, and is allowed to be endogenous. We find that the impact of discrimination on equilibrium depends on the nature of any skills bias in discrimination.

This paper explores the dynamics of semiendogenous versus fully endogenous growth models in “lab equipment” specifications of the models with expanding sectors. Capital is allowed to accumulate and is used, together with other inputs, to produce new knowledge. The stability of the steady state path is found to be determined by the inequality and/or knife-edge restrictions needed to produce steady state growth. This paper takes the ratio of the shadow price of capital to knowledge and the level of consumption as jump variables. Semiendogenous growth models lead to a 4 × 4 dynamic system where the sign of the coefficient matrix of the log linearized dynamic system is indefinite, leading to a potential for both stable and unstable equilibria. The knife-edge restrictions needed to generate policy influences on growth are shown to be restrictions that reduce the system to 3 × 3 with a positive definite coefficient matrix, thereby guaranteeing a globally stable equilibrium. Implications for empirical testing are addressed.

This article finds evidence that ideas and innovation are a key force explaining postwar growth in the U.S. economy. Utilizing data on patents issued since 1851, I construct a measure of the growth rate of knowledge. Capital stock estimates, human capital estimates, and real gross domestic product per worker growth rates are combined with the knowledge growth series to construct a time series test of endogenous innovation growth models. The results support the endogenous innovation approach but suggest that the accumulation of the per worker capital stock and changes in average human capital per worker are at least as important. (JEL 030, C32)