Technical progress effects on productivity and growth in the Commonwealth of Nations (1993-2009)

The productivity generated by capital goods is not uniform along the time. When there exist conventional physical capital goods the productivity obtained is minor that the one generated by quality capital goods. To obtain a correct measure of growth in presence of this embodied technical progress there exist three schools: first, the traditional growth accounting school appears due to limitations existing in the measures in efficiency units of the quality of the real investment, because of the investment is not really comparable along the time. The analysis is based in to adjust the quality or productivity of the investment goods constructing hedonic prices indices. This school is represented among others by Hulten (1992), Jovanovic and Nyarko (1996), Bartelsman and Dhrymes (1998), and Gordon (1999). The second school analyzes the productivity using longitudinal micro-level data sets. The most important contributions of this school are Griliches and Ringstad (1971), Olley and Pakes (1996), Caves (1998), McGuckin and Stiroh (1999), and Tybout (2000). The third school is the equilibrium growth accounting school, which measures the balance growth by means of vintage capital models, being represented by Greenwood, Hercowitz and Krusell (1997), Campbell (1998), Hobijn (2000), and Comin (2002). The main aim of this paper is to analyze which are the effects of the two form of technical progress, neutral and directly embodied while capital is accumulated, on the economic growth and the labour productivity. The application has been made to compare the responsibility of the embodied technical progress on the economic growth and productivity during the period (1993-2009) in the most representative economies of the Commonwealth of Nations. The vintage capital model has been made taking quarterly and annual data to each country, coming from the OECD Statistics. We use multivariate time series and cointegration techniques, in special autoregressive integrated moving average and vector autoregressive models (VAR), and autoregressive distributed lags models (ARDL).