This paper describes a stochastic model of the process of competition via technological innovation as it might occur within a single industry. Individual firms undertake R&D projects in the hope of acquiring a decisive competitive advantage over their rivals. But such advantages and the economic rents arising from this are only temporary; they eventually disappear in the face of imitation, entry, and innovation by other firms. At the industry's long-run equilibrium, concentration and the pace of technological innovation are jointly determined by the conditions of entry and the extent of innovative opportunity. The model implies relationships among these variables that have in fact been detected in the empirical R&D literature

The authors find that a significant relationship exists between vertical integration and expenditures for basic and applied research for the US petroleum industry, 1954-1975. They advance several hypotheses consistent with this finding, and conclude that organizational structure influences expenditures on research in the modern business enterprise.

[Alternative measures of the rate of diffusion of a new innovation are discussed and applied to study the spread of hybrid corn in the United States, in the light of more recent data and improved estimating techniques. An assessment is made of the importance of "profitability" variables in accounting for variations in the rate of diffusion between states

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 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

This paper examines empirically the relationship between innovative activity, as measured by the rate of return to research-and-development expenditures, and firm size using a sample of firms from the chemicals and allied products industry (SIC 28). We find that size is a prerequisite for successful innovative activity. The estimated rate of return to research and development for the smaller firms is 30 percent, while for the larger size firms it is 78 percent. Statistical tests for structural stability were used to divide the sample into these two behavioral regimes

This paper examines empirically the relationship between innovative activity, as measured by the rate of return to research-and-development expenditures, and firm size using a sample of firms from the chemicals and allied products industry (SIC 28). We find that size is a prerequisite for successful innovative activity. The estimated rate of return to research and development for the smaller firms is 30 percent, while for the larger size firms it is 78 percent. Statistical tests for structural stability were used to divide the sample into these two behavioral regimes

[The fine structure of earnings is defined by a theoretically meaningful decomposition of the covariance matrix of earnings (or log earnings) time series. A three-element variance components model is proposed for analyzing earnings of young workers. These components are interpreted as the effects of differential on-the-job training (OJT) and differential economic ability. Several properties of these components and relationships between them are deduced from the OJT model. Background noise generated by a nonstationary first-order autoregressive process, with heteroscedastic innovations and time-varying AR parameters is also assumed present in observed earnings. ML estimates are obtained for all parameters of the model for a sample of Swedish males. The results are consistent with the view that the OJT mechanism is an empirically significant phenomenon in determining individual earnings profiles

Technological change and product life cycle concepts can be used to explain the concentration of cotton textile production in Southeastern New England during the industry's period of rapid innovation in machinery and machine tool design. Boston was the center for an agglomeration of high technology industries that were attracted by each other and the local resource pool of skilled mechanics and entrepreneurs. The movement of the textile industry to the Southeast, which took place after 1880, is linked to technological change in the product cycle that substituted unskilled labor for skilled labor and high technology inputs. The phrase "Yankee ingenuity " has be-come a part of the English language. If New England no longer holds all the good mechanics in the United States, there was a time when she came so near it that the term "New England mechanic " had a very definite meaning over the whole country [Roe, 1916, p. 109]. The nineteenth century industrialization process in the United States was quite unbalanced geographically. The major manufac-turing industries were highly concentrated in New England and the Middle Atlantic states, while the South lagged far behind. The textile industry is the example most often used to illustrate this imbalance. It was centered in New England during the nineteenth century but moved "belatedly " to the Southeast in the twentieth century. Most histories of the industry cite abundant water power and merchant capital as reasons for the original New England location, and the low wages and less restrictive labor laws in the South are said to explain the relocation. This paper argues that the textile industry became highly concentrated in Eastern Massachusetts and Rhode Island during the nineteenth century because of localization economies re-sulting from close proximity to the source of technological change in the industry. Textile firms, machinery builders, and entrepreneurs formed an agglomeration of skills and other resources which made firms more *I wish to thank Roger Bolton, John R. Meyer, and Christine Hekman for ideas and criticism, and a referee of this Journal for valuable suggestions. Work on this paper