Technological diffusion and productivity convergence: a study for manufacturing in the OECD

Southern Economic Journal, Oct, 2004 by Dirk Frantzen

1. Introduction

A large empirical literature by now exists on the issue of per capita income or labor productivity convergence between countries. Most of this work makes use of regression analysis and bases itself on the transitional dynamics of the standard neoclassical model of economic growth with exogenous technical progress. As is well-known, this dynamics is characterized by conditional convergence, due to the property of decreasing returns to capital inputs in the production function. Equations are estimated that relate the rate of growth of per capita income or labor productivity to the log of their initial level and to the rates of accumulation of the considered types of capital, as well as to other variables that condition the steady state. When estimated on large cross-sections of countries over an entire period of time, the results would appear to confirm the predictions of the neoclassical model, provided that this includes human capital as a factor input. In the case of the OECD, the results would even seem to suggest the occurrence of unconditional convergence (for a survey, see Sala-i-Martin 1996).

More recent studies that perform estimation on panel data of similar equations allowing for country-specific fixed effects have challenged this view, however. These fixed effects are found to be highly statistically significant, and their inclusion vastly reduces the measured impact of the other conditioning variables. Even in the case of the OECD countries, the fixed effects remain highly significant, suggesting that also here the convergence is conditional in nature. Moreover, and most important, the estimated convergence speed is now found to be much higher than implied by the cross-section results. In fact, it is found to be far higher than explainable by the operation of the mechanism of decreasing returns to capital (see especially Canova and Marcet 1995; Islam 1995: Caselli, Esquivel, and Lefort 1996; De La Fuente 2000).

Although these panel data estimates are, themselves, not without problems, this would appear to suggest that other convergence mechanisms are at work besides the neoclassical one. We think here in the first place at the process of technological diffusion between countries. Open economy versions of new innovation-driven theoretical growth models have emphasized its importance in helping to explain the catching-up by laggards with respect to countries at the technological frontier, because imitation is easier than innovation. They have, thereby, stressed the conditional nature of this process, which is highly dependent on factors that stimulate physical and human capital accumulation and, more generally, allow for an appropriate institutional setting that fosters the operation of market forces (Grossman and Helpman 1991; Segerstorm 1991; Barro and Sala-i-Martin 1995; Aghion and Howitt 1998).

The empirical work on convergence through technological diffusion is still limited, however. Most reliable are probably a set of regression studies on OECD regional and country panel data. allowing for regional- and country-specific fixed effects, by De La Fuente (1996) and De La Fuente and Domenech (2001). They estimate equations that relate the rate of growth of total factor productivity (TFP) to the initial level of technology gap between the technological frontier and the non-frontier country under consideration. Their results provide evidence of significant conditional convergence at a relatively high speed. A drawback of these studies is, however, their aggregate nature. This prevents identification of the sectors responsible for convergence. And, it cannot let us know whether technological convergence occurs, especially, in internationally tradable goods sectors, such as manufacturing, as implied by most open economy innovation-driven growth models.

Earlier cross-section estimates of comparable TFP growth equations by Bernard and Jones (1996a) on large subaggregates, such as manufacturing as a whole, agriculture, mining, services, utilities, and construction across OECD countries, find, surprisingly, no evidence of convergence in the case of manufacturing during the 1970s and 1980s. In another study, Bernard and Jones (1996b) readdress the issue by also analyzing the time series properties of the technology gap variable, by testing for its nonstationary nature by applying a unit root test for panel data on a sample of yearly observations during the same period. The results suggest the presence of a unit root and provide, according to the authors. further evidence of TFP divergence in manufacturing in the OECD. They argue that this may be due to the fact that international trade tends to lead to specialization between countries.

One has to be careful with the interpretation of these results, however. If it is indeed the case that they are caused by differences in product composition of the manufacturing aggregates, this calls for further disaggregation. The regression estimates on cross-sections may, moreover, vastly underestimate the convergence speed. More appropriate estimates on disaggregate panel data may, possibly, find evidence of transitional dynamics characterized by significant convergence. If so, the evidence provided by time series tests on the same period of time may be misleading, as it may mainly reflect the evolution of the difference between transitory movements of the concerned TFP series to their equilibrium growth paths, rather than the evolution of the difference between these paths itself.