Big Data for Twenty-First-Century Economic Statistics

This book explores how Big Data can revolutionize economic statistics, offering solutions to traditional data collection challenges and enhancing measurement accuracy.

This volume delves into the transformative impact of Big Data on economic measurement, illustrating its potential to address both longstanding and emerging challenges. Big Data for Twenty-First-Century Economic Statistics emphasizes the limitations of traditional data collection methods, which often rely on sample surveys and periodic censuses. As obtaining survey responses becomes increasingly difficult, the need for innovative data sources has never been more pressing. The book highlights how various new data streams, including scanner data, credit card transactions, and online pricing information, can enhance the accuracy and timeliness of economic statistics.

The text provides a comprehensive overview of the current landscape of economic data collection, discussing the transition from conventional methods to the integration of Big Data. By documenting the progress made in utilizing these new data sources, Big Data for Twenty-First-Century Economic Statistics offers insights into how statistical agencies can harness this information to better serve policymakers and other stakeholders. The authors explore the challenges that remain, emphasizing the importance of overcoming these hurdles to fully realize the potential of Big Data in economic measurement.

Targeted at statistical agency staff, academic researchers, and serious users of economic statistics, this volume serves as a critical resource for understanding the evolving nature of data in the twenty-first century. It presents a forward-looking perspective on how Big Data can reshape the field of economic statistics, ensuring that data remains relevant and effective in informing decision-making processes.