Measuring Weather Impact on Crop Yield Using Aridity Index: Evidence from Odisha

Rainfall and temperature are the two important weather factors that affect crop yields due to their direct and indirect influences on agricultural practices. This study has negated the method of direct use of meteorological factors (either monthly or seasonal), in multiple regression analysis to measure weather impact on crop yield where rainfall and temperature are incorporated in the model as increasing monotonic functions of yield. With evidences from Odisha, where agriculture is rainfed and weather-dependent, the study has advocated the incorporation of ‘aridity index’ variable in the regression model. The use of composite aridity index variable in econometric model has made the analysis more easy and logical. More importantly, the use of aridity index saves the ‘degrees of freedom’ which is very crucial in econometric analysis. In addition, the ambiguity of using the linear trend to proxy for technological progress is taken care of adequately by using cubic function of time. The testing of hypothesis of changing rainfall dependency has established the fact that the dependence of agriculture on rainfall in Odisha has declined slightly possibly because of the developments in irrigation and other facilities.