IJSSER

Title: UNDOING THE LOCKDOWN: DATA DRIVEN SOLUTIONS FOR THE POST-COVID INDIAN ECONOMY
Authors: Arjun Gupta
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Arjun Gupta Shri Ram School moulsari
MLA 8 Gupta, Arjun. "UNDOING THE LOCKDOWN: DATA DRIVEN SOLUTIONS FOR THE POST-COVID INDIAN ECONOMY." Int. j. of Social Science and Economic Research, vol. 7, no. 7, July 2022, pp. 1830-1837, doi.org/10.46609/IJSSER.2022.v07i07.006. Accessed July 2022. APA 6 Gupta, A. (2022, July). UNDOING THE LOCKDOWN: DATA DRIVEN SOLUTIONS FOR THE POST-COVID INDIAN ECONOMY. Int. j. of Social Science and Economic Research, 7(7), 1830-1837. Retrieved from https://doi.org/10.46609/IJSSER.2022.v07i07.006 Chicago Gupta, Arjun. "UNDOING THE LOCKDOWN: DATA DRIVEN SOLUTIONS FOR THE POST-COVID INDIAN ECONOMY." Int. j. of Social Science and Economic Research 7, no. 7 (July 2022), 1830-1837. Accessed July, 2022. https://doi.org/10.46609/IJSSER.2022.v07i07.006.
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ABSTRACT: With the Indian and global economy steadily improving and recovering after the initial slump caused by the Covid-19 pandemic, the usage of big data analysis to drive policy solutions for economic recovery has emerged as a key method for targeted intervention. Governments in India and globally have underscored the importance of data collection to create evidence-based measures to understand the trends emerging from the pandemic. The trends observed are economic growth, and a steep rise in internet adoption, digital transformation in multiple varied sectors, and automation of work as well as the rise in gig work. This has also consequently led to positive trends in relation to the rise in digital entrepreneurship and new business models, including social entrepreneurship. However, there are also significant avenues for improvement in relation to data collection for the most underserved and marginalised communities in India, and workers in the informal economy. This paper analyzes the available data on trends in relation to economic recovery and highlights the key issues and pitfalls of data driven approaches. This paper argues for the prioritisation of poor and informal workers who are often left behind in the narrative of digital transformation and provides policy recommendations for future research to address these key data gaps for a more sustainable economic recovery model.

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