Estimating the causal effect of improved fallows on farmer welfare using robust identification strategies in Chongwe, Zambia

The purpose of this study was to estimate the impact of improved fallows on farmer welfare. The researchers used used farm-level data collected in 2011 from a random cross-section sample of 324 small-scale farmers in Zambia to estimate the impact of improved fallows. Since the improved fallow is mainly used to promote maize production, the staple food in most parts of Southern Africa, welfare indicators used in this study included household total maize yield, per capita maize yield, maize productivity and per capita income emanating from the maize crop. In addition, we included income from all crops grown on the farm to assess the technology's impact on this broad variable. The econometric methods' estimates confirmed the positive impact of improved fallows on the chosen welfare parameters. However, conflicting evidence was obtained on whether the technology positively affects per capita crop income. The findings showed that without randomization there is a tendency to over estimate the impact of improved fallows on farmer welfare variables. Estimations from both the matching strategies (nearest neighbour and kernel) and endogenous switching regression model indicated that the technology has a positive and significant impact on the welfare variables.