Factor productivity in EU agriculture: A microeconometric perspective - Mathias Kloss (Leibniz Institute of Agricultural Development in Transition Economies (IAMO), 2017)
Measuring factor productivity has been important in economics since its early days as a scientific discipline for a number of reasons. The first is the availability of systematically collected agricultural data after World War I, which allowed researchers to motivate and test newly developed methods. This data was collected to fulfill the societal need to learn more about the farming sector, which was stuck in a deep economic crisis at that time. In addition, economists stressed that agricultural technologies approximate the key assumptions of production theory particularly well. To measure agricultural productivity the analyst must deal with tangible (land, labour, and capital) as well as intangible (e.g., management abilities or unexpected weather shocks) production factors. Separating these two types of inputs and appropriately accounting for the latter is at the core of understanding agricultural production. Recent developments such as rising food prices and the decline in global productivity growth indicate that there is a societal need to understand and raise agricultural productivity again. Interestingly, these trends are accompanied by a new debate among econometricians about basic methodological issues in measuring firm level productivity. [...] Following my analyses, a number of policy implications unfold. As it turned out, materials is the most important input in European field crop farming. Hence, improving the availability of working capital is the most promising way to increase agricultural productivity. This finding is also underlined by the shadow price analysis, which indicated that in a number of countries the estimated return on working capital is much above observed market interest rates. Therefore, policy reforms should aim to ease access to short-term credit. With regards to agricultural labour markets the results indicate for France, West Germany and Italy that hired workers perform the highly specialised tasks leading to an increase in agricultural productivity. Consequently, policy makers should focus on creating incentives for farms to hire such specialised labour. For instance, programs to qualify and hire specialised labour could improve their inflow into agricultural labour markets.
urn:nbn:de:gbv:3:2-86101
Keywords: 330; Agricultural factor productivity; Labour productivity; Production function estimation; Outlier detection; Farm Accountancy Data Network; European Union