Reassessing the energy – finance – growth triangle in India: evidence from asymmetric and non-linear modelling

Purpose This study aims to examine the asymmetric and nonlinear relationships between energy consumption, financial development and economic growth in India, a developing economy characterised by structural and institutional complexities. It further investigates the Granger causal interlinkages among these key macroeconomic variables. Design/methodology/approach Using annual time series data from 1980 to 2020, the study applies the nonlinear autoregressive distributed lag (NARDL) model to capture potential asymmetries in the short and long run. In addition, the Toda–Yamamoto Granger causality test is used to ensure robustness in identifying directional causality among the variables. Findings The results confirm a long-run asymmetric cointegrating relationship among energy consumption, financial development, labour force, capital formation and economic growth. Negative shocks to energy consumption and financial development exhibit a more pronounced adverse effect on economic growth than positive shocks. Conversely, negative changes in labour force and capital formation have a stronger positive influence on growth than their positive counterparts, indicating possible structural or efficiency-based adjustments during downturns. Causality results support both the finance-led growth and conservation hypotheses. Research limitations/implications The study is confined to India and based on aggregate national data, which may mask regional disparities or sector-specific dynamics. Originality/value Despite growing interest in the energy–finance–growth nexus, limited empirical work has examined its asymmetric and nonlinear characteristics using advanced econometric techniques. Most studies continue to rely on linear models and single-indicator proxies for financial development, ignoring its complex and multidimensional nature. In the Indian context, there is a lack of studies that construct a comprehensive financial development index using principal component analysis and apply it within a nonlinear, asymmetric framework. Furthermore, the distinct effects of positive and negative shocks in energy use and financial development on economic growth remain largely unaddressed. This study bridges these critical gaps.