Poverty and altered planning horizons brought on by the HIV/AIDS epidemic can change individual discount rates, altering incentives to conserve natural resources. Using longitudinal household survey data from western Kenya, we estimate the effects of health status on investments in soil quality, as indicated by households' agricultural land fallowing decisions. We first show that this effect is theoretically ambiguous: while health improvements lower discount rates and thus increase incentives to conserve natural resources, they also increase labor productivity and make it more likely that households can engage in labor-intensive resource extraction activities. We find that household size and composition are predictors of whether the effect of health improvements on discount rates dominates the productivity effect, or vice-versa. Since households with more and younger members are better able to reallocate labor to cope with productivity shocks, the discount rate effect dominates for these households and health improvements lead to greater levels of conservation. In smaller families with less substitutable labor, the productivity effect dominates and health improvements lead to greater environmental degradation 1 This project would not have been possible without the support of the USAID-Academic Model Providing Access to Healthcare (USAID-AMPATH). Markus Goldstein and Mabel Nangami were key collaborators on the survey implementation. We are grateful to Markus Goldstein for helpful comments at early stages of this paper, as well as seminar participants at the Brookings Institution, Columbia University, RAND, Duke University, University of Toronto. We also acknowledge research assistance from Sam Masters. Financial support for this project was received from the Economic and Social Research Council (UK), The World Bank, the Eunice Kennedy Shriver National Institute for Child Health and Human Development (Thirumurthy, K01HD061605), the Social Science Research Council, the Swedish Research Council Formas, and the Calderone Program at Columbia University. All errors and opinions are our own. 19 Since ART households have 6.8 acres on average, the effect of ART on fallowing, as one would expect, is nearly identical in the two specifications. 20 We also estimated additional regressions to determine whether the number of distinct plots a household owned modified the effect of ART. We did this by including an interaction term between ART and the number of plots of land owned by a household. The interaction term was not statistically significant. We also note that land sales and acquisitions over the 3 year period of our study are extremely low. Only 4% of households in the sample sold land between 2004 and 2006; and 5.5% of households purchased land; changes in quantity of land owned did not affect the results.
JEL Classification Codes: I15, Q15, O1