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

• Author: Frantzen, Dirk
• Position: Organisation for Economic Co-operation and Development

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.

   A common drawback to the regression estimation approach to convergence analysis is that it only allows capturing of the dynamics of the "average" or "representative" economy in the sample. Most authors have, therefore, complemented it by a study of the evolution of the standard deviation of the considered measure of income or productivity. Although useful, this still does not provide insight into the actual underlying intradistribution dynamics across countries. In order to do so, some attempts have been made to approximate the evolving cross-country distribution by a stochastic process and to identify its law of motion and implied long-ran limit distribution. But this work has, to our knowledge, until now only been performed at an aggregate level and with respect to relative levels of per capita income (see Quah 1993a, b, 1996, 1997).

   In this study, we attempt a more systematic investigation of the issue of OECD manufacturing productivity convergence on disaggregate panel data with respect to 22 manufacturing sectors in 14 OECD countries from 1970 to 1995. We start by estimating different TFP growth equations that include the initial level of technology gap as a variable, both on a global panel of sector-country data collected every 5 years and on 22 subsamples, sector by sector. We compare average TFP growth performances of the frontier and non-frontier countries during the period of investigation. We pursue by considering the evolution of the standard deviation of the log of TFP and then study the cross-country distribution dynamics of relative TFP by means of a Markov-chain transition probability matrix approach. Finally, we perform a panel data unit root test on corresponding samples of yearly observations of our measures of technology gap variable.

   The article is organized as follows. Section 2 presents the empirical growth equations and section 3 the considered alternate measures of convergence. Section 4 exposes the econometric methods. The estimates are reported in section 5, and section 6 summarizes and concludes. The data sources and measurement issues are mentioned in a separate Appendix.

2. Empirical Growth Equations

   The purpose of this section is to present empirical growth equations that allow for total factor productivity convergence through international technological diffusion. In view of the observed relative constancy of the income shares of capital and labor across countries, we follow common practice and assume that the production of output occurs with a technology of the Cobb-Douglas type, with constant returns to scale and augmented by a variable reflecting the level of total factor productivity (TFP). This can be represented as:

   (1) [Y.sub.ijt] = [A.sub.ijt][K.sup.[alpha].sub.ijt] [L.sup.1-[alpha].sub.ijt],

   where [Y.sub.ijt], is the product or income in country i in sector j at time t, measured by value added at factor costs; [K.sub.ijt], is the corresponding physical capital stock; [L.sub.ijt], is the labor input; and [A.sub.ijt], is the level of Hicks-neutral TFP.

   In the standard neoclassical model, the rate of growth of [A.sub.ijt] is determined by the rate of exogenous technical progress. To the extent that it is equally accessible, this is assumed to be the same for all countries in each sector under consideration. Once one does, however, allow for technological diffusion between countries, one has to allow for the fact that countries with a less advanced technology can, moreover, benefit from the possibility of imitation from countries that are technologically more advanced. Other things equal, one should expect that the further a country's technology is behind the technological frontier, the greater are its possibilities of technical advance through imitation, and, therefore, the stronger will be its TFP growth.

   Consider a specific sector. Leaving out the sector subscript, the rate of growth of TFP of country i can be presented as follows:

   (2) [DELTA][a.sub.it] = [gamma] + [lambda]([a.sub.ft-1] - [a.sub.it-1]),

   where small letter variable a stands for the (natural) log of the level of TFP, A; [DELTA] stands for its first difference between t and t - 1; and the subscript f stands for the frontier country. The intercept,

   [gamma], captures the long-run rate of growth of TFP. This is supposed to be the same for all countries in the sector under consideration and determined by the sector-specific rate of exogenous technical progress. The...