Total factor productivity in the G7 countries: a short note

The analysis of the composition of economic growth in the G7 countries has been motivated by the desire to identify regularities that contribute to explaining economic success. Such analysis must be carried out with a long term perspective, and the relevant production function should reflect existing world technology and not just domestic conditions. Moreover, in order to assess the relative performance of each country, economic growth should be broken down such that total factor productivity (TFP) is not determined as a mere residual. The seminal papers in modern economic growth literature are those of Solow (1956), Romer (1986, 1990) and Lucas (1988). The empirical research literature in this area consists of two different strands. One strand decomposes economic growth in a given economy on the basis of factor accumulation and total factor productivity. The other uses cross-country regressions, with a multitude of explanatory variables. In the last few years, progress in computation methods has facilitated the use of Bayesian statistical methods in economic research. Nevertheless, the utilisation of Bayesian inference techniques in growth accounting is still very limited. The exceptions are the initial contributions of Koop, Osiewalski and Steel (1999, 2000), on which we rely heavily throughout this paper. In this paper we use Bayesian stochastic production frontiers in a growth accounting exercise for the period 1960/2005, assuming a dynamic translog production function and using data on 21 OECD economies. The results provide information on the contribution of inputs to GDP growth, on capital and labour elasticities and on TFP contribution. Furthermore, TFP is broken down into technological change (TC) and degree of efficiency. Intuitively, these components represent two different aspects. TC corresponds in general to more efficient production techniques. Improvements in efficiency correspond to better institutional and organisational arrangements, ie the more efficient use of the current level of inputs and technology. However, in practice it is often difficult to establish a clear distinction as TC and efficiency interact. Thus, not surprisingly, although the statistical method used provided contributions for both components, the degree of precision is smaller than the one associated with the computation of total TFP. In addition, it should be noted that, although it uses less conventional methods, this paper is still a growth accounting exercise. Thus, it does not reveal economic causation channels.