Risk, Time and Land Management under Market Imperfections: Applications to Ethiopia

Abstract

This Ph.D. thesis addresses both theoretical and empirical issues pertaining to land management decisions of farm households in developing countries working under an imperfect market and institutional setting (with case studies from Ethiopia). Using techniques in experimental economics, efforts are also made to assign some quantitative measures to the most important parameters (such as risk and time preferences) in the same decision making process.

Paper I: A Dynamic Economic Model of Soil Conservation with Imperfect Markets and Institutions In this paper, we develop a dynamic soil conservation model that explicitly incorporates labor, capital and land market imperfections and their interactions to suit the problems of smallholders in many developing countries. We use the model to analyze the impact of these institutional and market imperfections on the optimal levels of labor allocations into cultivation and conservation efforts. Increased transaction cost in factor markets is found to have a direct impact on soil conservation effort by increasing its shadow prices and curtailing its demand. It also has an indirect impact on soil conservation by affecting the shadow price of the soil stock and hence enhancing or curtailing its demand depending on the initial factor endowments of farm households, the relative strength of conservation and cultivation inputs on the soil dynamics, the profit share of cultivation input, and the degree of interaction across the factor markets. The overall impact is thus inconclusive. Various possible scenarios are explored in the model.

Paper II: Risk Preferences of Farm Households in Ethiopia This study measures farmers’ attitudes towards risk using an experimental approach for a sample of 262 farm households in the Ethiopian highlands. We find more than 50 percent of the households in the severe to extreme risk aversion category, with a constant partial risk aversion coefficient of more than 2.00. With careful construction of the experiment, the natures of absolute and partial risk aversion are examined, and our data supports the presence of Decreasing Absolute Risk Aversion (DARA) and Increasing Partial Risk Aversion (IPRA) behavior. The validity of some of the expected utility theory predictions is tested, and the predictions of risk neutrality for smaller stakes and predictions of similar preferences for gains and losses, which stem from the major tents of the theory (concavity and asset integration), are not supported by our experiment.

Paper III: Time Preferences of Farm Households in Ethiopia This study measures farmers’ time preferences (subjective discount rates) using an experimental approach with monetary incentives for a sample of 262 farm households in the Ethiopian highlands. The median discount rates are found to be more than 43 percent, which are more than double the interest rate on the outstanding debt. Given imperfect credit markets, household wealth (physical asset) levels are found to be highly correlated to this attitude measure. Time frame and magnitude effects, and delay/speed up asymmetries are anomalies found in the experiment.

Paper IV: Market Imperfections and Farm Technology Adoption Decisions: An Empirical Analysis In this paper, we investigate the impacts of market and institutional imperfections on farm technology adoptions in a model that considers fertilizer and soil conservation adoptions as related decisions. Controlling for plot characteristics and other factors, we find that a household’s decision to adopt fertilizers does significantly and negatively depend on whether the same household adopts soil conservation. The reverse causality, however, is insignificant. We also find outcomes of market imperfections such as limited access to credit, plot size, risk considerations, and rates of time preference to be significant factors explaining variations in farm technology adoption decisions. Relieving the existing market imperfections will more likely increase the adoption rate of farm technologies.