Shripad Ramchandra Marathe

The transition to a sustainable energy economy requires substantial public investment, with government spending playing a crucial role in driving the adoption of renewable energy and achieving environmental outcomes. This study investigates the impact of India’s budgetary allocations on renewable energy consumption, carbon emissions, and economic growth. The analysis covers annual data from 1990 to 2024. It employs the autoregressive distributed lag (ARDL) bounds testing approach and the Granger causality test to examine long-term equilibrium relationships and directional causality among the variables. The results indicate a statistically significant long-run relationship between government expenditure, renewable energy usage, and carbon emissions. Specifically, a 1% increase in renewable energy consumption (REC) results in a 1.14% decrease in carbon emissions, demonstrating the environmental benefits of clean energy deployment. The ARDL model also shows that past government disbursements significantly contribute to emissions reduction, with coefficients of –2147.41 (p < 0.001) and –997.36 (p < 0.05) at lags one and two, respectively. Granger causality results confirm an unidirectional causal relationship between renewable energy expenditures (REE) and carbon emissions, as well as between government spending and gross domestic product (GDP), highlighting the dual impact of such investment on environmental sustainability and economic growth. The findings underscore the effectiveness of public financial support in accelerating the transition to renewable energy while advancing macroeconomic goals. Strengthening and sustaining government investment in renewable energy is essential for achieving India’s long-term development targets, reducing carbon intensity, and promoting green economic growth.

Type of the article: Research Article

Abstract
This study examines the impact of crude oil price shocks on stock market efficiency and volatility spillovers across BRICS countries (Brazil, Russia, India, China, and South Africa) using 6,275 daily observations from April 1999 to March 2024. The results from unit root and Lo-Mackinlay variance ratio tests show that only Russia and India exhibit weak-form efficiency, while Brazil, China, and South Africa display inefficiencies, indicating scope for abnormal returns. Granger causality analysis confirms strong short-term interlinkages, with Brazil emerging as a leading market for Russia, India, and South Africa. Johansen’s cointegration test reveals long-term relationships among BRICS markets and with crude oil prices, suggesting limited diversification opportunities. ARCH-GARCH models and impulse response functions show significant volatility spillovers triggered by oil price shocks, lasting 2-6 trading days. Crude oil volatility affects all markets except South Africa, reflecting varying energy dependencies. These findings underscore the interconnectedness and systemic risk exposure of BRICS financial systems, with critical implications for international investors and policymakers in managing portfolio strategies and stabilizing markets.