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This study examines the role of personal loans in supporting sustainable economic growth in India by analysing their short-term and long-term effects on Gross Domestic Product (GDP). Using quarterly macroeconomic data, the analysis employs the Autoregressive Distributed Lag (ARDL) model, followed by Bounds Testing and an Error Correction Model (ECM) to determine the speed at which the system returns to equilibrium. The findings show that personal loans have a positive and statistically significant impact on GDP in the short run, indicating that credit-driven consumption can stimulate economic activity. However, in the long run, this effect becomes negative, suggesting that excessive reliance on consumption-oriented borrowing may undermine sustained growth. In contrast, Gross Fixed Capital Formation (GFCF) maintains a consistently positive influence in both the short and long run, underscoring the importance of investment-focused lending. The robustness of the model is supported by diagnostic tests such as the Durbin–Watson statistic, Breusch–Pagan test, and CUSUM/CUSUMSQ stability assessments. Overall, the study suggests that while personal loans can provide a temporary boost to economic activity, long-term stability requires redirecting credit flows toward productive and investment-led sectors. Accordingly, the paper recommends a strategic shift from consumption-based lending to investment-driven credit policies to strengthen India’s long-term growth trajectory.
Keywords:
ARDL Model; Economic Growth; Error Correction Model (ECM); Personal Loans; Sustainable Development.
Cite Article:
"DO PERSONAL LOANS PROMOTE SUSTAINABLE GROWTH? EVIDENCE FROM ARDL ANALYSIS IN INDIA", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 11, page no.b503-b519, November-2025, Available :http://www.ijrti.org/papers/IJRTI2511158.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator