Search results

Central theme: The present chapter discusses the integration of data science methods in devising economic policies in different countries with special reference to India.

Purpose: It explains how the policy-making process in countries can be transformed from estimate-based policies to evidence-based policies with the help of techniques such as artificial intelligence (AI), big data, and data analytics. It answers the research question of whether the data science techniques can make the economic policy process efficient or not in developing countries like India.

Research methodology: Data are collected from secondary sources such as government websites, journals, corporate reports, and research databases to conduct this descriptive analysis. Research papers from Scopus/Web of Science (WoS) database are extracted, and exclusion/inclusion criteria are applied for extracting papers relevant to this research.

Findings: The chapter found out various opportunities which India can tap by gaining new insights on critical macroeconomic issues such as unemployment, labour markets, and water crises and would be able to resolve the problems with the help of predictive modelling. The findings exhibit the possibility of building models that could explain how to integrate data science techniques into the policy-making process. It also highlights the challenges that Indian economy is facing in incorporating these techniques in its policy-making process. It states the need to design different evaluation schemes based on information and communication technology (ICT) and data science for different policies, since one methodology does not suit all.