Productivity growth and convergence in US agriculture: new cointegration panel data results

Abstract

Dynamic effects of health and inter-state and inter-industry knowledge spillovers, Total Factor Productivity (TFP) growth and convergence in US agriculture are examined using recently developed procedures for panel data and a growth accounting model. Strong evidence is found to support the hypothesis that TFP converges to a steady state. Health care supply in rural areas and research spillovers from other states and from nonagricultural sectors are found to have significant impacts on the productivity growth rate in both the short and the long run. These results suggest a richer set of opportunities for policy makers to enhance productivity growth than previously considered.

Productivity and Convergence in European Agriculture

“…Following Sala‐i‐Martin () and Liu et al . (), we estimate:where is across‐country variance of the logarithm of TFP in period t , α are parameters and ε is a zero‐mean random disturbance term. A significantly negative coefficient associated with the time variable t , i.e.…”

“…As Liu et al . () point out: two primary concepts of cross‐sectional convergence have been used to measure convergence of productivity across countries or regions. The first notion, σ ‐convergence, considers whether the dispersion of TFP among countries or regions diminishes over time.…”

“…In order to test for convergence, researchers usually apply either a cross-sectional or a time series framework (Sonderman, 2012). As Liu et al (2011) point out: two primary concepts of cross-sectional convergence have been used to measure convergence of productivity across countries or regions. The first notion, r-convergence, considers whether the dispersion of TFP among countries or regions diminishes over time.…”

“…The first notion, r-convergence, considers whether the dispersion of TFP among countries or regions diminishes over time. The Ó 2016 The Agricultural Economics Society second, b-convergence, considers whether the correlation between a state's initial TFP level and its subsequent growth in TFP is negative (Liu et al, 2011). However, as Hern andez-Salmar on and Romero-Avila (2015) highlight: cross-section tests of bconvergence are problematic since they (i) tend to over-reject the null of no convergence when countries are characterised by different steady states (Bernard and Durlauf, 1996); (ii) may render evidence of conditional convergence even when crosscountry income distributions remain unaltered over time (Quah, 1993); and (iii) require identical first-order autoregressive dynamic structures across countries as well as control for all factors causing cross-country steady-state income differentials (Evans and Karras, 1996).…”

Agricultural Productivity Growth in Latin America and the Caribbean and Other World Regions: An Analysis of Climatic Effects, Convergence and Catch-up

“…However, applying classical time series methods might lead to the wrong conclusion of the non-stationary of a series because the analysis is not based on structural equations and does not account for the cross-sectional dependence of the data (Westerlund, 2007). Instead, we apply panel data unit root tests, which have been used in just a few productivity studies (e.g., Ball et al, 2004;Suhariyanto and Thirtle, 2001;Ludena, 2010;Liu et al, 2011). In addition, we consider panel data co-integration tests to explore the existence of a long-run uniform trend among CATFP estimates across LAC countries.…”