Comparative Analysis of Smallholder Maize Yield Responses to Climate Risks

Thesis Abstract

This study examines how climate risks influence maize yields among smallholder farmers in a comparative cross-sectional framework across three distinct agro-ecological zones, addressing the gap in regionally differentiated risk responses and adaptation effectiveness. The problem centers on increasing climate volatility—characterized by erratic rainfall, rising temperatures, and extreme events—that jeopardizes yield stability and food security for resource-constrained smallholders. The aim is to quantify yield responses to climate risks and to identify drivers of resilience and vulnerability to inform targeted adaptation policies. Specific objectives are (i) to characterize climate risk exposure and variability across zones; (ii) to estimate the elasticities of maize yield to key climate variables using panel-structured cross-sectional data; (iii) to evaluate the role of adaptation strategies (input diversification, soil and water management, and agro-meteorological information access) in moderating climate impacts; (iv) to compare risk-adjusted productivity and profitability implications among households with differing asset endowments; and (v) to generate policy-relevant recommendations for scalable adaptation interventions. The study adopts a cross-sectional survey design with a quasi-experimental comparative component. The population comprises smallholder maize-producing households in three agro-ecological zones within a selected country, with a target sample size of 1,200 households systematically sampled from village strata that reflect contrasting climate variability and soil fertility. Data collection combines structured household questionnaires, agronomic records, and secondary climate data from national meteorological services spanning the last fifteen growing seasons. Instruments are developed to capture yield outcomes, input use, management practices, asset ownership, access to credit and extension services, and exposure to climate risk indicators (seasonal rainfall deviation, temperature anomalies, and frequency of extreme events). Survey instruments undergo pre-testing and pilot validation; their reliability is assessed via Cronbach’s alpha for index constructs and test-retest measures for key scales. Analytical approaches integrate econometric and computational methods. Descriptive statistics summarize yield distributions and climate stressors by zone; multivariate regression models estimate maize yield responses to climate variables, with interaction terms to capture adaptation effects. A double-hounded approach—random-effects and fixed-effects models—accounts for unobserved heterogeneity across households and zones. A Heckman selection model addresses potential input usage bias due to non-random participation in adaptation practices. To quantify risk considerations, a stochastic frontier analysis with a two-stage approach separates technical efficiency from environmental stochasticity, while a Latent Class Analysis identifies distinct farmer typologies based on adaptation capacities and asset portfolios. The theoretical framework draws on the Climate Adaptation Theory and Relative Risk Aversion, with references to the Theory of Planned Behavior to interpret adoption determinants. Key expected findings include (i) climate variability exerts statistically significant negative effects on maize yields, with larger elasticities in the marginal rainfall periods and hotter growing seasons; (ii) adoption of diverse soil and water management practices, timely access to weather information, and diversified input use mitigate yield losses and enhance profitability, with heterogeneity across zones; (iii) asset-rich households exhibit higher resilience due to greater capital for risk management and faster uptake of adaptation options; (iv) optimal combinations of practices yield higher technical efficiency under climate stress, reducing the yield gap relative to less resilient peers. The study contributes to knowledge by providing robust cross-zone comparative estimates of climate yield responses, delineating the channels through which adaptation improves resilience, and offering a typology of farmer responses to climate risks. Policy and practical implications include prioritizing region-specific extension services, subsidized access to climate-resilient inputs, and the co-design of locally tailored early warning and information dissemination systems. Recommendations emphasize scaling up successful adaptation bundles—such as conservation agriculture, soil moisture conservation, and drought-tolerant maize varieties—coupled with financial instruments that lower liquidity barriers for smallholders. The study concludes that climate risk management for smallholder maize systems requires integrated, zone-sensitive strategies that align asset-based resilience with accessible risk information and supportive institutions to sustain yield stability under increasing climate variability.