THE DIFFUSION OF NUMERICALLY-CONTROLLED TOOLS

In order for productivity to improve, not only must new technologies be adopted, they must become widespread. Identifying the determinants of the conversion of capital stock to a new technology would aid the public discussion of how to improve efficiency in the manufacturing sector. This dissertation estimates the determinants of the conversion of turning tools to numerical-control by the U.S. metalworking sector, using two models of diffusion: an epidemic model and a probit model. The empirical evidence suggests that the probit model provides superior estimates of the determinants of conversion to numerically-controlled turning tools. Competitive market structure has often been chosen as a possible determinant of technological diffusion. However, prior studies have estimated its effect as negative, positive and insignificant. This study found competitive market structure to be positively correlated with diffusion. Furthermore, market structure accounted for 32% of the explained variation of estimated diffusion rates from their mean. This study examined the influence of the ability of a corporation to bear risk, by estimating the effect of the degree of labor stability. It was hypothesized that industries which provided stable employment to their workforce would receive greater labor cooperation upon the introduction of a new technology. This, in turn, would aid diffusion. The empirical evidence supports this hypothesis. Separation rates were found to be negatively correlated with diffusion rates. They made the largest contribution of any variable (42%) to the explained variation of estimated diffusion rates from their mean. These results, along with the finding that diffusion was faster in industries with low ratios of labor to capital, suggest that even though numerically-controlled tools are labor replacing, industries with more stable employment converted to numerical-control more quickly.