22 pages, Raising agricultural productivity in developing countries is often said to reduce poverty more than comparable growth arising from other sectors. This claim has frequently been based on casual theorising, rather than empirical evidence. Productivity growth generates additional income and must benefit someone, though not necessarily the poor. It is conceivable that most, or even all of the benefits might go to others. Using region-level data from Thailand, we study the relationship between agricultural productivity growth and rural poverty incidence. The dependent variable for our regression analysis is the annual rate of change in rural poverty incidence at the regional level between the years for which poverty data are available. Agricultural productivity is measured as the annual rate of change in regional total agricultural productivity, covering the same time intervals as the poverty observations, but lagged one calendar year. Other control variables include regional non-agricultural incomes and the real price of food. The estimated coefficient on the change in agricultural productivity is negative and highly significant, implying that agricultural productivity growth does reduce rural poverty, holding other variables constant, though not more so than non-agricultural sources of income growth. The poverty-reducing contribution of recent agricultural productivity growth has been small. The poverty-reducing effects of long-term drivers of agricultural productivity growth are also analysed, using simulations based on the estimated model.
18 pages, Recent studies cast doubt on the ability of abstract experiments to predict decision-making in the field. Thus, scholars have argued for more ‘realism’ by introducing context to field experiments. Yet, such realism may work against the induced values of monetary incentives in economic experiments. It is an open question whether contextual framing works best with or without inducing values, through methods such as the use of monetary incentives. Using a sample of 146 German farmers, we compare experimentally the predictive power of a framed lottery in an agricultural context vs. using an abstract version. For one half of the sample, lotteries are incentivised; for the other half, they are hypothetical. Although risk preferences differ between treatments, all four lottery tasks correlate poorly with farmers’ real-world use of risk management instruments such as harvest or hail insurance. Subjects who start with an agricultural framing are willing to take significantly greater risks in the lotteries. More generally, our findings cast doubt on the ability of lottery tasks to predict risk-taking in the field.
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: KerryByrnes4 Document Number: D01666
Notes:
Kerry J. Byrnes Collection, Thesis submitted to the faculty of the University Graduate School in partial fulfillment of the requirements for the degree Master of Arts in the School of Philanthropic Studies, Indiana University, 79 pages.
