Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Relationship of Payment Statistics and Sector-Wise GrossValue Added in the Indian Economy: A Regression Analysis Approach

Version 1 : Received: 23 July 2023 / Approved: 25 July 2023 / Online: 26 July 2023 (05:30:52 CEST)
Version 2 : Received: 16 October 2023 / Approved: 16 October 2023 / Online: 16 October 2023 (09:56:09 CEST)

A peer-reviewed article of this Preprint also exists.

Kiran, B. V., Satyanarayana, K. T. S. S., Kumar, T. Y., Surya, K. J., Kalesha, K., & Rao, A. N. (2023). Relationship of Payment Statistics and Sector-Wise Gross Value Added in the Indian Economy: A Regression Analysis Approach. Journal of Law and Sustainable Development, 11(11), e1895. https://doi.org/10.55908/sdgs.v11i11.1895 Kiran, B. V., Satyanarayana, K. T. S. S., Kumar, T. Y., Surya, K. J., Kalesha, K., & Rao, A. N. (2023). Relationship of Payment Statistics and Sector-Wise Gross Value Added in the Indian Economy: A Regression Analysis Approach. Journal of Law and Sustainable Development, 11(11), e1895. https://doi.org/10.55908/sdgs.v11i11.1895

Abstract

This study explores the correlation between payment statistics and sector-wise gross value added (GVA) in the Indian economy from 2011 to January 2023, shedding light on the importance of payment and settlement systems. Through regression analysis, the impact of payment statistics on GVA across diverse sectors is assessed. The results indicate that, during the specified period, payment statistics do not exhibit a significant influence on sector-wise GVA. These findings emphasize the need for further investigation into alternative factors driving sector-wise GVA, while underscoring the pivotal role of payment and settlement systems in the Indian financial landscape.

Keywords

Indian economy; gross value added; payment and settlement systems; payment statistics; regression analysis

Subject

Business, Economics and Management, Finance

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