Bitcoin and economy: unravelling drivers of industrial production in India

Monika, Sunil Kumar and Mona Sharma

International Journal of Trade and Global Markets, 2026, vol. 22, issue 2, 111-131

Abstract: This study investigates the dynamic impact of Bitcoin prices and key macroeconomic variables, consumer price index (CPI), exchange rate, and crude oil prices, on industrial output in India, proxied by the index of industrial production (IIP). The Toda-Yamamoto causality analysis reveals that CPI and oil prices Granger-cause IIP, whereas Bitcoin and exchange rate do not exhibit causal influence. Utilising the auto-regressive distributed lag (ARDL) bounds testing framework for robustness, the study captures both short- and long-run relationships. Impulse response functions (IRFs) and the error correction model (ECM) confirm these findings, showing significant responsiveness of IIP to CPI and oil shocks. Stability tests (CUSUM and CUSUMSQ) validate model reliability, while robust standard errors address heteroscedasticity concerns. Diagnostic tests indicate no autocorrelation or autoregressive conditional heteroscedasticity (ARCH) effects, though non-normality and mild heteroscedasticity are observed. The findings highlight that conventional macroeconomic variables continue to dominate industrial performance, with Bitcoin exerting a negligible real-sector impact.

Keywords: digital assets; digital currency; cryptocurrency; GDP; gross domestic product; economy; inflation; econometrics; ARDL; auto-regressive distributed lag. (search for similar items in EconPapers)
Date: 2026
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