Productivity growth in Indian agriculture: is there evidence of convergence across states?

Abstract

This paper explores the question of convergence in total factor productivity (TFP) in agriculture across fourteen mdjor agricultural states of India. Using a Tornqvist-Theil index for TFP growth for the period 1973-1993, we find no evidence to support convergence to a single TFP level (a-convergence). After grouping the various states on the basis of their productivity performance, we find that the high-performing states show a gradual movement towards the trend, whereas the low-performing states generally show more volatility. Testing for long-run convergence in levels of agricultural productivity, we find evidence of conditional beta-convergence after controlling for state-specific factors and idiosyncratic year-specific volatility. The results are robust to alternative specifications of tests of unit root in panel data developed recently. (A.N. Mukherjee).shocks such as inflation is still large in the determination of wages and income in the rural areas. There is also enough empirical evidence in the literature to suggest that poverty and inequality are still persistent in rural India in spite of substantial gains in land and labour productivity in agriculture.The overall growth in productivity at the national level can mask significant differences between those states that have progressed rapidly, such as Punjab and Haryana, and those that have lagged behind. Das and Barua (1996) show that there were substantial inequalities in income among the states of India from the beginning of the Green Revolution period until the first half of the 1990s. They use a maximum entropy method to investigate the determinants of the persistence of regional inequality, and find that differences in agriculture and infrastructure are the 0169-5150/03/$ -see front matter 0

Agricultural Productivity Growth and the Role of Capital in South Asia (1980–2013)

“…Lynam and Herdt [37] argued for TFP analysis as an appropriate measure to determine sustainability, since in a sustainable production system, TFP should have a non-negative trend. Moreover, TFP indices capture the effect of technological improvements emanating from research and development activities and through investments made to develop infrastructures (e.g., irrigation, roads and electricity) [38]. Higher TFP ensures higher output from the use of modern technology and effective utilization of resources, thereby leading to poverty reduction, mainly in rural areas [39], which is one of the major policy objectives of the South Asian countries.…”

Agricultural productivity and convergence: Europe and the United States

“…When the two sub-periods are considered, i.e 1973-1982 and 1983-1993, the convergence results indicate the presence of weak β-convergence and and convergence between 1992 and 2000. While the study by Mukherjee and Kuroda (2003) found no evidence for σ-convergence between Indian states but strong evidence for stochastic convergence.…”

“…Such studies are the paper by Paci (1997) for European Union regions; the papers by , Gutierrez (2000), and Rezitis (2005) for the United States and the European Union; the paper by Suhariyanto and Thirtle (2001) for Asian countries; the paper by Mukherjee and Kuroda (2003) for Indian states; the paper by McErlean and Wu (2003) for Chinese regions; and the paper by Thirtle et al (2003) for Botswana regions. The present paper differs from the previous studies in terms of the empirical approach used in measuring agricultural productivity and testing convergence.…”

“…The present paper differs from the previous studies in terms of the empirical approach used in measuring agricultural productivity and testing convergence. In particular, the papers by Suhariyanto and Thirtle (2001) and Thirtle et al (2003) calculate Malmquist index with respect to the sequential frontier, which is formed without any statistical basis; the papers of and Mukherjee and Kuroda (2003) use Divisia indices to measure TFP, which in the words of Grosskopf (1993) ignores efficiency; the papers by Paci (1997), Gutierrez (2000) and McErlean and Wu (2003) use labor productivity for examining convergence. With regard to the approach used for testing convergence only four of the previous studies, i.e.…”

“…With regard to the approach used for testing convergence only four of the previous studies, i.e. Suhariyanto and Thirtle (2001), Thirtle et al (2003), Mukherjee and Kuroda (2003) and Rezitis (2005) use time series techniques while the rest of them use cross-section. It should be noted, however, that the present paper uses a wider spectrum of panel unit root tests than previous papers with the exception of the paper by Rezitis (2005) which uses the same unit root tests.…”