Climate Variability, Food Crops Supply and Family Farm Employment in the Sudano-Sahelian Zone of Nigeria

Abstract

This thesis is based on the premise that the impact of climate variability on crop production decisions can be either positive or negative depending on the crop, cropping system and the nature of the variation in weather pattern. These features of a crop production system approximate the actual/implied possibility famers’ adaptive responses through changing crop input and output mixes. The main objective is to estimate the impact of climate variability on the supply of three most extensively grown food crops (millet, sorghum and cowpea) in the Sudano-Sahelian zone of Nigeria and to deduce the implications of the estimated production relationship for family farm labour utilization. Crop production is characterized by a stochastic multi-output technology based on duality theory. The resulting system of multi-crops supply, variable inputs demand, variances and covariance equations were represented by a normalized quadratic (dual) indirect utility function, assuming linear mean-variance risk preferences or constant absolute risk aversion (CARA). The price of the least important crop (cowpea) is used as a numerie to normalize the other equations and the supply equation for cowpea was dropped. Relevant time series data from 1994 to 2009 on crop outputs, inputs, prices and monthly rainfall were collected from varied sources and pooled across sub-regional states level to yield a pooled time-series cross-sectional (TSCS) panel data structure. The variances and covariance equations were estimated with a non-linear least squares estimation technique and their predicted values were used as instruments in the expected crop supply equations. Thereafter, the two regional expected crop supply and variable input demand equations were estimated using linear seemingly unrelated regression (SUR) estimation technique. Estimation is done at two spatial resolutions (that is, sudano-sahelian and sudano-savannah zones) using both satellite (MERRA) and ground level (NIMET) monthly seasonal rainfall data. Among other important production relationships, results indicate that climate variability has largely impacted negatively on expected crops supply of millet and sorghum with largely negative implications for the utilization of family farm labour in the study region. It is recommended that investments in the infrastructure and technology that provides timely and quality weather forecast information to farmers be increased. There is also a need for the introduction of crop specific weather index-based insurance as a mechanism for managing climate related risk in a multiple cropping system.