Abstract:

This study contributes to understanding the relationship between climatic variables and
groundnut production in different farming systems in Uganda. Alternative production
function models are estimated using pooled cross-sectional time series data at the district
level. The models incorporate land area, indicators for farming systems, technological
change, and either rainfall or the El Niño–Southern Oscillation (ENSO) effect as
variables to account for climatic conditions. The data set includes 333 observations
corresponding to 37 districts for 9 consecutive years, from 1992 to 2000. Analyses were
performed using a Translog functional form and GARCH estimators. The results suggest
that the partial elasticity of production for land is positive, high and significant, which is
consistent with a priori expectations. Farming systems are also found to have a
significant impact on output variability. Climatic conditions, measured by rainfall, have a
non-significant effect; but, when the ENSO phenomenon is used instead a significant
negative effect is detected particularly for the warm phase. An important and alarming
finding is a marked negative rate of technological change revealing productivity losses over the time period studied.