The role of big data and CEIC data in supporting economic policy formulation and evaluation: opportunities, challenges, and implications

Abstract

This research comprehensively examines the transformative role of Big Data, with particular emphasis on data provided by the Central Economic Information Center (CEIC), in supporting the formulation and evaluation of economic policies. By analyzing the characteristics of Big Data (Volume, Velocity, Variety, Veracity, Value, etc.) and the CEIC's capabilities as a global macro- and microeconomic data provider, this article identifies how Big Data enables more granular, timely, and predictive economic analysis. The discussion explores concrete applications of Big Data in the policy cycle, from problem identification to impact evaluation, as well as its integration with econometric and machine learning methods. While offering great potential for evidence-based policymaking, the utilization of Big Data also faces significant challenges such as data quality, privacy, algorithmic bias, and regulatory gaps. This article presents solutions and recommendations to address these challenges, including the importance of strong data governance, cross-sector collaboration, and the development of data literacy, to maximize the benefits of Big Data in driving sustainable and inclusive economic growth. This data, which often has a non-standard structure, has the potential to provide much richer and deeper economic insights than conventional data sources. Effective economic policy formulation and evaluation require a deep understanding of market dynamics, the behavior of economic agents (consumers, firms), and the causal impact of government interventions. Big Data offers the potential for more granular, comprehensive, and timely analysis, which can complement and enrich traditional statistical data.