Analyzing the Macroeconomic Transmission of Climate Shocks in Kenya Using a Production-Weighted SPEI: A Bayesian Vector Autoregressive Approach

Abstract

This study uses a Bayesian Vector Autoregressive model with exogenous variables (BVARX) to analyze the macroeconomic transmission of climate shocks in Kenya. Given the country’s heavy reliance on rain-fed agriculture, the Kenyan economy is particularly vulnerable to climatic extremes. This paper examines how droughts in Kenya, which have become increasingly frequent and severe, affect agricultural production, GDP, inflation, and interest rates from 1973 to 2023. As a proxy for drought shocks, a novel production-weighted Standardized Precipitation Evapotranspiration Index (SPEI) is constructed, accounting for heterogeneity in agricultural production across Kenya’s 47 counties. The BVARX model is estimated across seasonal specifications to separately identify the effects of rainy-season, dry-season, and annual drought conditions. The results show that increased rainy-season drought severity is associated with contemporaneous and statistically significant declines in agricultural production and GDP. In contrast, annual drought severity yields weaker and less consistent effects, and dry-season droughts do not produce statistically significant macroeconomic responses. These findings underscore the importance of seasonal disaggregation in the economic analysis of climate shocks. Moreover, the production-weighted SPEI yields stronger, more statistically significant effects than a simple nationwide average, suggesting that existing literature relying on unweighted climate measures may underestimate the economic consequences of climate shocks. These results carry important implications for both academic research and Kenyan public policy, particularly in irrigation investment and drought monitoring.