Conclusions and Implications for Policy.
This paper explores the impact of climate on crop revenue in Kenya. The paper uses
primary household level data enriched with secondary climate, hydrological and soil data.
We concentrate on a seasonal Ricardian model to assess the impact of climate on net crop
revenue per acre. First we assess the impact of climate on agriculture by estimating
models with climate factors only, then test the impact of hydrological, soil and household
variables.
Our results suggest that climate affects agricultural productivity. Increased winter
temperatures increase net crop revenue, while high summer temperatures have a negative
impact on crop revenue. Increased precipitation has the impact of increasing net crop
revenue. The results further show that there is a non-linear relationship between
temperature and crop revenue on one hand and between precipitation and crop revenue
on the other. This finding is consistent with studies on the impact of global warming on
agriculture (Mendelsohn et al. 1994, 2003; Kurukulasuriya et al., 2004). Another key
result is an inverted U-shaped relationship between mean flow and net crop revenue.
Further, we also find that andosols, irrigation and household size are positively correlated
with crop revenue, while livestock ownership, farm size and wage rates are inversely
correlated with revenue.
Estimated marginal impacts further show that crop revenue is elastic with respect to
climate change, but is less elastic with respect to temperature than to precipitation. The
temperature elasticities suggest that global warming is harmful for agricultural
productivity. Though precipitation elasticities are much higher than temperature
elasticities, the marginal impacts suggest that the temperature component of global
warming may have more serious repercussions than rainfall.