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.

This statistical volume contains data usually unavailable in other statistical publications. It gives statistics for two groups of countries in their 2007 borders. First, since year 1950 (for 1950, 1960, 1970, 1980, 1990, 2000, and 2007), it provides statistical data for all countries of the world (232 countries). Second, since year 1 AD (for 0001, 1000, 1500, 1600, 1700, 1820, 1870, 1880, 1890, 1900, 1913, 1920, 1929, and 1938), it provides data for a smaller group of countries (133 countries). This book is based on the groundbreaking works of Angus Maddison but it differs from his books in that it gives data up to the most recent year available and calculates GDP (gross and per capita) in the prices of that most recent year. For the recent years, the World Bank, CIA, and Encyclopedia Britannica were principal sources. But, despite the author's great debt to these sources, the preponderance of data in the book is not direct citations from them but rather the result of calculations. Among other computational techniques he uses a new logarithmic interpolation which takes care of cross-country statistical distortions when calculating in the prices of the most recent year. For every line of data (for every country, each year), he provides a note on the technique used in obtaining his estimate (i. e., proxy, exponential interpolation, direct estimate with source citation, etc.). Dr. Avakov's annual title Quality of Life, Balance of Powers, and Nuclear Weapons gives a current snapshot of world statistics. This new work, Two Thousand Years of Economic Statistics, gives the population and current price GDP data in a historical perspective.

Business Statistics of the United States is a comprehensive and practical collection of data from as early as 1913 that reflects the nation's economic performance. It provides several years of annual, quarterly, and monthly data in industrial and demographic detail including key indicators such as: gross domestic product, personal income, spending, saving, employment, unemployment, the capital stock, and more. Business Statistics of the United States is the best place to find historical perspectives on the U.S. economy. Of equal importance to the data are the introductory highlights, extensive notes, and figures for each chapter that help users to understand the data, use them appropriately, and, if desired, seek additional information from the source agencies. The 2021 edition examines the dramatic effect that COVID-19 had on the U.S. and world economies. For the first time, it examines many issues related to the pandemic including the impact it has had on income and spending, the sharp increase in e-commerce, the decline in trade, and its effect on energy prices. Business Statistics of the United States provides a rich and deep picture of the American economy and contains approximately 3,500 time series in all. The data are predominately from federal government sources including: Board of Governors of the Federal Reserve System Bureau of Economic Analysis Bureau of Labor Statistics Census Bureau Employment and Training Administration Energy Information Administration Federal Housing Finance Agency U.S. Department of the Treasury

This work examines theoretical issues, as well as practical developments in statistical inference related to econometric models and analysis. This work offers discussions on such areas as the function of statistics in aggregation, income inequality, poverty, health, spatial econometrics, panel and survey data, bootstrapping and time series.

Examining 35 series of economic statistics, this volume covers a variety of topics, including: using and abusing statistics; total output, production and growth; investment and capital expenditures; employment, earnings and profits; and labour statistics.