Agricultural Exports and Economic Growth: An Econometric Modeling Framework

Abstract

Background: Economic growth is one of the core goals of a developed and developing economy. Agricultural sector and more specifically agricultural exports are vital in providing foreign exchange, domestic production stimulation, as well as technological development. Nevertheless, the empirical correlation between agricultural exports and economic growth is controversial and incoherent in the results of different countries and at different periods of time. Objective: The paper will create a complex econometric modeling structure to investigate the effects of agricultural exports on economic growth, focusing on a short-run and long-run level. Method: The analysis also utilizes quantitative econometric analysis, such as time-series analysis, cointegration tests (Augmented Dickey-Fuller), Error Correction Models (ECM), and Autoregressive Distributed Lag (ARDL) models. The theoretical basis is based on the export-led growth theory, neoclassical growth models and endogenous growth theory. Results: The proposed framework confirms that agricultural exports have various effects on economic growth: foreign exchange revenues, productivity, job creation and sectoral interdependence. The model uses the following control variables: investment, labor force, trade openness, inflation and exchange rates. Conclusion: The paper presents a solid econometric approach to the assessment of the nexus of agricultural exports and economic growth. The new methodology fills the gaps in the literature by considering dynamic impacts, adjusting to macroeconomic variables, and allowing an analysis appropriate to the context. The framework has a practical implication to policy makers in the developing economies especially in Central Asia.

Keywords: Agricultural exports, economic growth, econometric modeling, ARDL, export-led growth, time-series analysis.