Measuring Entrepreneurial Businesses: Current Knowledge and Challenges brings together and unprecedented group of economists, data providers, and data analysts to discuss research on the state of entrepreneurship and to address the challenges in understanding this dynamic part of the economy. Each chapter addresses the challenges of measuring entrepreneurship and how entrepreneurial firms contribute to economies and standards of living. The book also investigates heterogeneity in entrepreneurs, challenges experienced by entrepreneurs over time, and how much less we know than we think about entrepreneurship given data limitations. This volume will be a groundbreaking first serious look into entrepreneurship in the NBER's Income and Wealth series.

Introduction.Big data for twenty-first-century economic statistics: the future is now /Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro --Toward comprehensive use of big data in economic statistics.Reengineering key national economic indicators /Gabriel Ehrlich, John Haltiwanger, Ron S. Jarmin, David Johnson, and Matthew D. Shapiro ;Big data in the US consumer price index: experiences and plans /Crystal G. Konny, Brendan K. Williams, and David M. Friedman ;Improving retail trade data products using alternative data sources /Rebecca J. Hutchinson ;From transaction data to economic statistics: constructing real-time, high-frequency, geographic measures of consumer spending /Aditya Aladangady, Shifrah Aron-Dine, Wendy Dunn, Laura Feiveson, Paul Lengermann, and Claudia Sahm ;Improving the accuracy of economic measurement with multiple data sources: the case of payroll employment data /Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz --Uses of big data for classification.Transforming naturally occurring text data into economic statistics: the case of online job vacancy postings /Arthur Turrell, Bradley Speigner, Jyldyz Djumalieva, David Copple, and James Thurgood ;Automating response evaluation for franchising questions on the 2017 economic census /Joseph Staudt, Yifang Wei, Lisa Singh, Shawn Klimek, J. Bradford Jensen, and Andrew Baer ;Using public data to generate industrial classification codes /John Cuffe, Sudip Bhattacharjee, Ugochukwu Etudo, Justin C. Smith, Nevada Basdeo, Nathaniel Burbank, and Shawn R. Roberts --Uses of big data for sectoral measurement.Nowcasting the local economy: using Yelp data to measure economic activity /Edward L. Glaeser, Hyunjin Kim, and Michael Luca ;Unit values for import and export price indexes: a proof of concept /Don A. Fast and Susan E. Fleck ;Quantifying productivity growth in the delivery of important episodes of care within the Medicare program using insurance claims and administrative data /John A. Romley, Abe Dunn, Dana Goldman, and Neeraj Sood ;Valuing housing services in the era of big data: a user cost approach leveraging Zillow microdata /Marina Gindelsky, Jeremy G. Moulton, and Scott A. Wentland --Methodological challenges and advances.Off to the races: a comparison of machine learning and alternative data for predicting economic indicators /Jeffrey C. Chen, Abe Dunn, Kyle Hood, Alexander Driessen, and Andrea Batch ;A machine learning analysis of seasonal and cyclical sales in weekly scanner data /Rishab Guha and Serena Ng ;Estimating the benefits of new products /W. Erwin Diewert and Robert C. Feenstra.

Robust and reliable measures of consumer expenditures are essential for analyzing aggregate economic activity and for measuring differences in household circumstances. Many countries, including the United States, are embarking on ambitious projects to redesign surveys of consumer expenditures, with the goal of better capturing economic heterogeneity. This is an appropriate time to examine the way consumer expenditures are currently measured, and the challenges and opportunities that alternative approaches might present. Improving the Measurement of Consumer Expenditures begins with a comprehensive review of current methodologies for collecting consumer expenditure data. Subsequent chapters highlight the range of different objectives that expenditure surveys may satisfy, compare the data available from consumer expenditure surveys with that available from other sources, and describe how the United States’s current survey practices compare with those in other nations.

Seventeen in a series of annual reports comparing business regulation in 190 economies, Doing Business 2020 measures aspects of regulation affecting 10 areas of everyday business activity.

Includes a separate report for each state, the District of Columbia, Puerto Rico, and a U.S. summary.

The U.S. economy is highly dynamic: businesses open and close, workers switch jobs and start new enterprises, and innovative technologies redefine the workplace and enhance productivity. With globalization markets have also become more interconnected. Measuring business activity in this rapidly evolving environment increasingly requires tracking complex interactions among firms, establishments, employers, and employees. Understanding Business Dynamics presents strategies for improving the accuracy, timeliness, coverage, and integration of data that are used in constructing aggregate economic statistics, as well as in microlevel analyses of topics ranging from job creation and destruction and firm entry and exit to innovation and productivity. This book offers recommendations that could be enacted by federal statistical agencies to modernize the measurement of business dynamics, particularly the production of information on small and young firms that can have a disproportionately large impact in rapidly expanding economic sectors. It also outlines the need for effective coordination of existing survey and administrative data sources, which is essential to improving the depth and coverage of business data.