We use nonparametrie production function methods to decompose farm-level labor productiv- ity growth into components attributable to efficiency change, technical change, and factor in- tensity. The estimation is accomplished using balanced panel data drawn from the Kansas Farm Management Association for the period 1993 to 2007. We find that labor productivity growth is primarily driven by factor intensity and technical change. Efficiency change is de- clining with increasing productivity growth, and technical change is not Hicks-neutral and oc- curs at high levels of factor intensity, suggesting that innovation is embodied in factor intensity.
Key Words: labor productivity growth, efficiency change, technical change, factor intensity
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The rise in agricultural productivity has been chronicled as the single most important source of economic growth in the U.S. farm sector (Acs, Morck, and Yeung 1999, Ball and Norton 2002). The remarkable growth in productivity has been attributed to research and development (Huffman and Evenson 1993, Alston, Craig, and Pardey 1998, McCunn and Huffman 2000), development of human capital (Huffman and Evenson 1992, McCunn and Huffman 2000, Yee et al. 2002), production contracts (Key and McBride 2003), and increasing farm size (Weersink and Tauer 1991, Thirtle, Schimmelpfennig, and Townsend 2002). Several empirical studies have focused on understanding the sources of productivity growth by decomposing total factor productivity (TFP) into technical change and efficiency change, while others have focused on understanding factors that contribute to convergence or divergence of TFP (Ball et al. 2001, Ball, Hallhan, and Nehring 2004, Managi and Karemera 2004, Liu et al. 2011).
This paper contributes to the literature by fo- cusing on labor productivity as one of the main drivers of total factor productivity growth in pro- duction agriculture. Specifically, we contribute to the literature in three ways: (i) by decomposing labor productivity growth into efficiency change, technical change, and factor intensity, (ii) by fo- cusing our analyses at the farm rather than state or national level, and (iii) by relating labor pro- ductivity change to important farm policy devel- opments. The motivation for this decomposition is to identify the main sources of labor productiv- ity growth. From a policy perspective, accurate measures of the sources of productivity growth are important because they provide policymakers with information about which areas could be targeted for appropriate policy intervention to improve labor productivity.
The passage of the 1996 Federal Agricultural Improvement and Reform (FAIR) Act introduced substantial changes to the overall U.S. farm pol- icy environment. Price support measures and de- ficiency payments were reduced in favor of in- come support direct payments. As observed by Serra, Goodwin, and Featherstone (2005), the in- troduction of the fixed decoupled payments may have reduced the likelihood of off-farm labor par- ticipation in Kansas because of an increase in the income support system. However, the effects of the new policy environment on farm income vari- ability were attenuated by changes in crop insur- ance programs and by the increase in emergency assistance payments by the end of the 1990s. This motivated a higher participation in non-farm labor markets, thus reducing the net effects of the policy on off-farm labor participation. Serra et al. (2006) showed that use of inputs that are risk- increasing will have an impact on output variabil- ity. Serra, Zilberman, and Gil (2008) observed that an increase in the decoupling of government payments would likely decrease technical effi- ciency (technological diffusion) because higher production yields would not receive any premium because payments are not linked to yield. Mugera and Langemeier (2011) confirm this by finding that Kansas farms experienced declining technical efficiencies over the 1993 to 2007 period. …