Financial development and agricultural productivity: Evidence from a multi-country panel
Abstract
Purpose: This study examines whether aggregate financial depth is associated with agricultural labour productivity in a panel of 24 economies over the period 2000–2024.
Design/Methodology/Approach: Agricultural labour productivity is measured by agriculture, forestry, and fishing value added per worker, while financial depth is proxied by domestic credit to the private sector as a share of GDP. GDP per capita, gross capital formation, and rural population share are included as core controls. Using World Development Indicators data, the analysis employs descriptive statistics, correlation analysis, pooled OLS with country-clustered robust standard errors, fixed-effects panel regressions, extended specifications with agriculture-related controls, and lagged robustness checks.
Findings: Agricultural labour productivity is strongly and consistently positively associated with GDP per capita. By contrast, the effect of aggregate financial depth is weaker and sensitive to specification. It is not statistically significant in the core pooled model, becomes positive and marginal or significant in some fixed-effects specifications, and weakens again in lagged robustness models. These findings suggest that broad financial deepening does not automatically translate into productivity-enhancing finance for agriculture.
Originality/Value: The study reassesses the finance–agriculture relationship in a multi-country panel and evaluates whether a standard macro-finance indicator adequately captures the type of finance that matters for agricultural productivity. By combining core models, extended specifications, and lagged robustness checks, the findings highlight the limits of aggregate financial depth as a proxy for effective rural and agricultural finance.
Keywords
References
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Details
Primary Language
English
Subjects
Agricultural Economics (Other)
Journal Section
Research Article
Authors
Özkan İmamoğlu
*
0000-0002-1646-9781
Türkiye
Early Pub Date
June 23, 2026
Publication Date
June 26, 2026
Submission Date
December 9, 2025
Acceptance Date
June 9, 2026
Published in Issue
Year 2026 Volume: 32 Number: 1