مقاله سال ۲۰۱۶

 مجله امگا – Omega

Gordon [1] identifies three industrial revolutions comprising first, steam and railroads, second, electricity, indoor plumbing, communications, and the internal combustion engine, and third, computers, the internet, and mobile phones. However, economic growth has slowed since the middle of the twentieth century and Gordon predicts that the bottom 99% of the income distribution might experience growth of less than one half of 1% in the coming decades.

Although science and research and development of all forms have been responsible for a large proportion of past economic growth, recent federal spending on science and private spending on research and development as a percent of GDP has fallen from about 1.25% in 1976 to approximately 1% in 2009 (Economic Report of the President [2]). One beacon of light has been in the area of nanotechnology. Between 2001 and 2008 the number of inventions in nanotechnology and the number of nanotechnology workers grew at a 25% annual rate, with the worldwide nanotechnology product market reaching $254 billion in sales in 2009 (Roco et al. [3]). The National Science Foundation estimates that nanobiotechnology could become a trillion dollar industry employing more than 800,000 workers by 2015. In this paper we examine science spending for nanobiotechnology research and education at 30 US universities during the period 1990 to 2005.

Weber and Xia [4] estimated inefficiency and Morishima elasticities of output substitution for nanotechnology research publications, Ph.D. students, and patents using a stochastic directional distance function. We extend their research in an effort to shed light on two important questions. First, can a reallocation of resources between different universities enhance the university outputs of research, patents, and Ph.D. graduates? If some universities are consistently on the cutting edge of the research frontier then reallocation of resources away from non-frontier universities towards frontier universities could enhance productivity. On the other hand, scale diseconomies might limit the extent of the efficiency gains from reallocating resources. Second, can resources be reallocated across time to enhance productivity? Here, we want to investigate whether it is better for federal agencies to allocate research dollars early in the development stage of new technologies, later in the development stage, or more or less continuously throughout the period.