Livestock Supply and Price Formation across Market Conditions: Evidence from Quantile Regression

Abstract

This study models livestock market attendance and price data in the commune of Sidéradougou, Burkina Faso, over the period June 2021 to April 2022. It analyzes the impact of livestock supply (cattle, sheep, goats) on prices, taking into account seasonal variations and security disruptions. The dataset comprises 35 monthly market-day observations per species, drawn from CESAO field records. Using quantile regression models, the study highlights the heterogeneous effects of supply on prices at different points in the conditional distribution. The results show that prices and supply are strongly influenced by three key periods: the lean season, holidays, and security events. During the lean season, prices are generally low while supply increases, reflecting households’ economic difficulties. The periods leading up to holidays show high prices and reduced supply, due to herd retention in anticipation of celebrations. Security events disrupt trade flows and the mobility of herders, leading to significant fluctuations in prices and supply. Supply has a statistically significant negative effect on prices for sheep and goats across all quantiles, and for cattle specifically at the upper quantile (q0.75). These findings are consistent with a plausible demand-side interpretation, though the cross-sectional nature of the data precludes causal identification. These insights can guide the development of public policies aimed at stabilizing markets and strengthening the resilience of rural communities to economic and security crises.