Peer Review Report For: VALUE CHAIN PERFORMANCE IN KENYA'S AGRICULTURAL SECTORS: A MACRO-SECTORAL ANALYSIS OF PRODUCTIVITY, VALUE ADDITION, TRADE INTEGRATION, AND ECONOMIC OUTCOMES [version 1; peer review: 1 not approved]

Résumé

Value chain performance in the agriculture sector is a complex global challenge. The study constitutes a multi sectoral analysis from a comparative perspective of Maize, Tea, Horticulture, Coffee, and Dairy value chains starting 2010 to 2023. The main focus is productivity, value addition, trade integration, and economic outcomes. A mono approach was utilized and a quantitative analysis of secondary data from thirteen complementary datasets was undertaken. The analysis reveals substantial performance heterogeneity across value chains. Dairy recorded the highest average Value Chain Performance Index (VCPI) (0.75), followed by Tea (0.62), while Coffee ranked lowest (−0.83). Tea demonstrated the fastest improvement (β = 0.044, p = 0.002), whereas Maize and Coffee exhibited stagnation. Panel regression findings indicate that improvements in value chain performance were positively associated with agricultural value added per worker within sectors over time (β = 92.44, p < 0.05 in Fixed Effects models), but Total Factor Productivity, labour productivity, and trade openness consistently emerged as stronger predictors of economic outcomes. Notably, VCPI showed no statistically significant association with GDP, GDP per capita, or trade openness in preferred Random Effects models. Evidence-based case studies of Tea and Maize value chains revealed that sustained competitiveness depends on complementary factors including institutional coordination, value addition, market integration, and productivity enhancement. The findings suggest that agricultural transformation in Kenya requires integrated approaches combining productivity growth with value addition and supportive macroeconomic policies, rather than focusing on individual performance indicators in isolation.

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