A model of endogenous growth is developed in which growth is driven by vertical innovations that involve creative destruction. Equilibrium is determined by a forward-looking difference equation, according to which the amount of research in any period depends negatively upon the amount expected next period. The paper analyzes positive and normative properties of stationary equilibria, and shows conditions for the existence of cyclical equilibria and no-growth traps. The growth rate may be more or less than optimal because a business-stealing effect counteracts the usual spillover and appropriability effects. In addition, innovations tend to be too small.
The factors that affect the supply of entrepreneurs are important but poorly understood. We study a sample of individuals who choose either to be employees or to run their own businesses. Four conclusions emerge. First, consistent with the existence of borrowing constraints on potential entrepreneurs, we find that the probability of self-employment depends markedly upon whether the individual ever received an inheritance or gift. Second, when directly questioned in interview surveys, potential entrepreneurs say that raising capital is their principal problem. Third, consistent with our theoretical framework's predictions, the self-employed have higher levels of job and life satisfaction than employees. Fourth, childhood personality measurements and psychological test scores are of almost no help in predicting who runs their own business later in life. It is access to start-up capital that matters.
R&D spillovers are, potentially, a major source of endogenous growth in various recent "New Growth Theory" models. This paper reviews the basic model of R&D spillovers and then focuses on the empirical evidence for their existence and magnitude. It reviews the older empirical literature with special attention to the econometric difficulties of actually coming up with convincing evidence on this topic. Taken individually, many of the studies are flawed and subject to a variety of reservations, but the overall impression remains that R&D spillovers are both prevalent and important.
The papers in this issue and the subsequent two issues of EINT were selected from those presented at an international conference on the effects of technology and innovation on firm performance and employment held in Washington, DC, in May 1995, at the National Academy of Sciences. Although the studies are drawn from many different countries, they are united by a common theme and the use of similar methodology and data. Taking advantage of the large micro datasets on firms and their workers that are now available in many countries, they report a series of findings about the consequences of technical change for enterprises and their employees during the recent past.
This paper argues that the "scale effects" prediction of many recent R&D-based models of growth is inconsistent with the times-series evidence from industrialized economies. A modified version of the Romer model that is consistent with this evidence is proposed, but the extended model alters a key implication usually found in endogenous growth theory. Although growth in the extended model is generated endogenously through R&D, the long-run growth rate depends only on parameters that are usually taken to be exogenous, including the rate of population growth.
Is there too much or too little private research and development (R&D)? A large empirical literature reports estimates of the rate of return to R&D ranging from 30% to over 100%, supporting the notion that there is too little private investment in research. However, this conclusion is challenged by the new growth theory, which emphasizes a richer description of the connection between R&D and productivity. In this paper we bridge the gap between the theoretical and empirical literatures. Using the framework of an R&D-based growth model, we derive analytically the relationship between the social rate of return to R&D and the coefficient estimates of the empirical literature. Somewhat surprisingly, we show that these estimates represent a lower bound on the true social rate of return. Furthermore, our analytic framework provides a direct mapping from the rate of return to the degree of underinvestment in research. Using a conservative estimate of the rate of return to R&D of about 30%, optimal R&D investment is at least four times larger than actual investment.
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