<quote> Estimating Total Factor Productivity
Neoclassical growth theory can be viewed as either an organizing framework for thinking about growth or as a substantive theory. To the extent that it is a substantive theory, one of its most basic predictions must be that TFP growth is not associated with the principal dynamic variables-investment, depreciation, and population growth rates- about which neoclassical growth theory makes predictions. In this subsection, we test and reject the null hypothesis that TFP growth is uncorrelated with equipment investment.
It should come as no surprise that the very strong association of output per worker growth and equipment investment documented above is, in large part, also a strong association between equipment investment and total factor productivity growth. Given the limitations of our database, the calculation of total factor productivity estimates is not straightforward. We require estimates of the average share accruing to factors of production, and estimates not of gross, but of net investment rates. Thus total factor productivity estimates require estimates of initial capital stocks. Because such initial capital stock estimates are crude, they introduce a potential source of noise into TFP growth calculations.
We have estimated 1960-85 TFP growth rates for 31 of the economies in our high-productivity sample. For these 31 economies, we have year-by-year estimates of nominal investment in different types of assets and of price structures in the 1950s. Along with an assumption about pre1950 investment, we can construct 1960 estimates of capital stocks that can then be used to calculate total factor productivity growth from 1960 to 1985. The restriction of our total factor productivity growth estimates to 31 high-productivity economies limits us to a sample that does not show the growth-equipment nexus as strongly as some of our other samples. For equations such as those in table 1, the equipment investment coefficient over the 1960-85 period is 0.198 for this particular sample, toward the low end of the range found in our later regressions. </quote>
Doug