The impact of renewable energy consumption on export performance in Uzbekistan: A vector autoregression approach
Abstract
The paper deals with the growing importance of understanding energy consumption patterns and their relationship with export performance in developing economies. The study aims to analyze the bidirectional relationship between commodity exports and energy consumption in Uzbekistan from 1992 to 2023. A vector autoregression (VAR) model is employed as the primary methodology, incorporating four main variables: commodity exports, GDP per capita, renewable energy consumption, and renewable electricity generation. Unit root tests (ADF and PP) were conducted, revealing that all variables are stationary in their first differences, which necessitated cointegration analysis. The Johansen test results confirm the existence of a single long-run cointegration vector among the variables. Granger causality tests identify a bidirectional causal relationship between GDP per capita and exports, with changes in GDP per capita having a significant impact on exports (p < 0.001) and vice versa. The results demonstrate that renewable electricity has a positive effect on exports (coefficient = 0.055, p = 0.01), while GDP per capita shows a negative effect on exports (coefficient = –0.0002, p = 0.039). Additionally, VAR analysis reveals that past values of exports significantly influence current export levels, with a lagged coefficient of 0.883 (p < 0.05). These findings have practical implications for policymakers in Uzbekistan seeking to balance economic growth objectives with sustainable energy development strategies.