Measurement and analysis of agricultural productivity in Colombia

Worldwide agricultural commodity prices boomed from 2006 to 2011, peaking up 65% in 2008 and 80% in 2011 (IMF, 2015). Consequently, agricultural gross production value expanded 25% worldwide in 2011 relative to its average in 2000-2005, and by 25%-45% in Latin America (FAO, 2015). However, in Colombia it only increased by 10%. Colombia’s agricultural value exhibited this limited expansion likely due to deep structural problems that led to low levels of productivity growth. Colombia is a small trading economy, making it is a price taker in international markets (Tovar, Jaramillo, Maldonado, Jimenez, & Plazas, 2007). There surely was transmission of these high commodity prices to Colombia’s domestic prices and so incentives to increase both productivity and input use. This study analyses the weak performance of Colombia’s agriculture, conducting a long-term prospective analysis that evaluates how this was determined by productivity growth versus input accumulation. Productivity is the increase in output attributable to technical change (Domar, 1961; Jorgenson & Griliches, 1967; Solow, 1957). Colombia’s agricultural productivity has rarely been analyzed in economics literature (Atkinson, 1970; Avila, Romano, & Garagorry, 2010; Ludena, 2010; Pfeiffer, 2003; USDA, 2015). Existing studies do not reach a consensus, and methods used to measure it are questionable. Accordingly, this study measures and analyzes Colombia’s agricultural productivity during the period 1975-2013. This study begins by analyzing Colombia’s agricultural context from 1975 to 2013, identifying six key periods between which economic conditions and policy regimes changed. Then it uses econometric techniques to measure aggregate and disaggregated crop and livestock productivity, an approach that has never been used before to measure Colombia’s agricultural productivity. This study finds that Colombia’s agricultural productivity grew on average between 0.8% and 1.3% per year from 1975 to 2013, which was mainly driven by livestock productivity. The three different approaches used – Cobb- Douglas and CES production functions and Dual cost function estimation -- yielded mostly similar results. Productivity exhibited different trends in each identified period, and output value was more sensitive to productivity trends influenced by policy regimes and economic circumstances than by input accumulation. Also, stagnant growth of Colombia’s agriculture in recent decades was due to low productivity growth. In addition, it exhibited biased technical change according to the methods that can identify bias. Colombia will be able to raise its agricultural productivity in the future if it steadily increases R&D; investment, human capital, and foreign competence in the domestic market. Success will depend on implementing a comprehensive policy regime that includes all three elements and is designed with a long-term perspective