This paper develops new indicators of accumulated academic science and tests their explanatory power on productivity data from manufacturing industries. Knowledge is found to be a major contributor to productivity growth. Furthermore, a lag in effect of roughly 20 years is found between the appearance of research in the academic community and its effect on productivity in the form of knowledge absorbed by an industry. Academic technology and academic science filtered through interindustry spillovers exhibit lags of roughly 10 and 30 years each. Thus implied search and gestation times far exceed developmental periods in studies of R & D. A clear implication is that basic research declines relative to development in the face of an exogenous rise in the real of interest.

A version of the overlapping-generations model suggests that an increase in the rate of innovation alters capital formation in favor of schooling and other human capital at the expense of physical capital, and tends to reduce total savings, defined as human investments plus financial savings. The theoretical explanation suggests that relative capital formation in human beings, but not necessarily absolute capital formation, is positively associated with the degree of innovation. Analysis of U.S. time-series data supports the hypotheses advanced in the paper.

A model of labor supply under uncertainty is developed, and comparative statics of current labor are carried out with respect to temporary and persistent wage change. This and a complementary analysis of measurement error suggest that individual wage growth leads to downward-biased estimates of intertemporal labor substitution. An alternative strategy, namely, the use of short-lived industry wage pulses in place of individual wage growth, is free of the above biases. Findings presented in the paper support this point of view. These results also suggest that intertemporal substitution has been undervalued as a source of cyclical changes in unemployment.

This paper tests for the existence of wage premiums based on geographic and industry unemployment differences. These differences are broken down into permanent and transitory components in equations controlling for variation in state generosity of unemployment insurance benefits. Findings indicate that wage premiums arise for long-run unemployment differences, but that negative short-run shocks to industries generate wage cuts, while positive shocks generate wage hikes. Therefore, labor contracts accommodate long-term anticipated unemployment, and entail sharing of short-term unemployment risks.

A theory of personal wealth transfers is developed which implies that components given to a recipient, such as education and bequests, are perfect substitutes. Therefore, components whose marginal cost rises more rapidly than average reveal wealth elasticities that are smaller than average. For related reasons, time series elasticities are expected to fall short of cross-sectional elasticities. An empirical investigation estimates cross-sectional wealth elasticities of gifts and bequests and time series wealth elasticities of bequest. The estimates are ranked in the order that is anticipated from the theory.

This paper explores the effect of research and development (R&D) and capital on factor intensity and skill bias in a sample of manufacturing plants. Firm and industry R&D as well as plant level capital increase the factor intensity of labor over materials. In contrast, skill bias originates in portions of capital and R&D. Equipment capital and firm R&D in the same product as a plant are consistently skill biased, while structures are biased against skill. Furthermore, general firm and industry R&D increase investment in equipment but not structures. This shows that the skill bias of R&D occurs through two distinct channels. First, firm R&D specific to the product increases the relative demand for skilled labor directly and in the short run through the cost function. Second, general firm and industry R&D exert an additional skill bias by favoring equipment over structures in the long run, demonstrating the broader compass of the skill bias of R&D over time.

The influence of academic science on industrial R&D seems to have increased in recent years compared with the pre-World War II period. This paper outlines an approach to tracing this influence using a panel of 14 R&D performing industries from 1961-1986. The results indicate an elasticity between real R&D and indicators of stocks of academic science of about 0.6. This elasticity is significant controlling for industry effects. However, the elasticity declines from its level during the 1961-1973 subperiod, when it was 2.2, to 0.5 during the 1974-1986 subperiod. Reasons for the decline include exogenous and endogenous exhaustion of invention potential, and declining incentives to do R&D stemming from a weakening of intellectual property rights. The growth of R&D since the mid-1980s suggests a restoration of R&D incentives in still more recent times.

This paper develops new indicators of accumulated academic science and tests their explanatory power on productivity data from manufacturing industries. Knowledge is found to be a major contributor to productivity growth. Furthermore, a lag in effect of roughly 20 years is found between the appearance of research in the academic community and its effect on productivity in the form of knowledge absorbed by an industry. Academic technology and academic science filtered through interindustry spillovers exhibit lags of roughly 10 and 30 years each. Thus implied search and gestation times far exceed developmental periods in studies of R & D. A clear implication is that basic research declines relative to development in the face of an exogenous rise in the real of interest.

A version of the overlapping-generations model suggests that an increase in the rate of innovation alters capital formation in favor of schooling and other human capital at the expense of physical capital, and tends to reduce total savings, defined as human investments plus financial savings. The theoretical explanation suggests that relative capital formation in human beings, but not necessarily absolute capital formation, is positively associated with the degree of innovation. Analysis of U.S. time-series data supports the hypotheses advanced in the paper.