What is the best way to auction an asset? How should a group of people organize themselves to ensure the best provision of public goods? How should exchanges be organized? In An Introduction to the Theory of Mechanism Design, Tilman Börgers addresses these questions and more through an exploration of the economic theory of mechanism design. Mechanism design is reverse game theory. Whereas game theory takes the rules of the game as a given and makes predictions about the behavior of strategic players, the theory of mechanism design goes a step further and selects the optimal rules of the game. A relatively new economic theory, mechanism design studies the instrument itself as well as the results of the instrument. An Introduction to the Theory of Mechanism Design provides rigorous but accessible explanations of classic results in the theory of mechanism design, such as Myerson's theorem on expected revenue maximizing auctions, Myerson and Satterthwaite's theorem on the impossibility of ex post efficient bilateral trade with asymmetric information, and Gibbard and Satterthwaite's theorem on the non-existence of dominant strategy voting mechanisms. Börgers also provides an examination of the frontiers of current research in the area with an original and unified perspective that will appeal to advanced students of economics.

A witty and thoughtful romp through the profession and practice of economics

In this issue Letter from the Editor Ying Zhu Hong Kong and Social Movements Hong Kong Unraveled: Social Media and the 2019 Protest Movement Anonymous Unleashing the Sounds of Silence: Hong Kong's Story in Troubled Times Andrea Riemenschnitter Tragedy of Errors at Warp Speed Sam Ho Imagining a City-Based Democracy: Review of The Appearing Demos: Hong Kong During and After the Umbrella Movement by Laikwan Pang, University of Michigan Press, 2020 Enoch Tam Building and Documenting National and Transnational Cinema China and the Film Festival Richard Peña Nationalism from Below: State Failures, Nollywood, and Nigerian Pidgin Jonathan Haynes Collective Memory and the Rhetorical Power of the Historical Fiction Film Carl Plantinga From Nations to Worlds: Chris Marker's Si j'avais quatre dromadaires Michael Walsh Sino-US Relations American Factory and the Difficulties of Documenting Neoliberalism Peter Hitchcock R.I.P. Soft Power: China's Story Meets the Reset Button: Review of Soft Power with Chinese Characteristics: China's Campaign for Hearts and Minds edited by Kingsley Edney, Stanley Rosen, and Ying Zhu, Routledge, 2019 Robert A. Kapp The Narrative of Virus Review: On Epidemics, Epidemiology, and Global Storytelling Carlos Rojas

When we think about history, we often think about people, events, ideas, and revolutions, but what about the numbers? What do the data tell us about what was, what is, and how things changed over time? Economist Robert E. Gallman (1926–98) gathered extensive data on US capital stock and created a legacy that has, until now, been difficult for researchers to access and appraise in its entirety. Gallman measured American capital stock from a range of perspectives, viewing it as the accumulation of income saved and invested, and as an input into the production process. He used the level and change in the capital stock as proxy measures for long-run economic performance. Analyzing data in this way from the end of the US colonial period to the turn of the twentieth century, Gallman placed our knowledge of the long nineteenth century—the period during which the United States began to experience per capita income growth and became a global economic leader—on a strong empirical foundation. Gallman’s research was painstaking and his analysis meticulous, but he did not publish the material backing to his findings in his lifetime. Here Paul W. Rhode completes this project, giving permanence to a great economist’s insights and craftsmanship. Gallman’s data speak to the role of capital in the economy, which lies at the heart of many of the most pressing issues today.

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.

Sixty percent of infectious human diseases are shared with other vertebrates. Alan Olmstead and Paul Rhode tell how innovations to combat livestock infections—border control, food inspection, drug regulation, federal research labs—turned the U.S. into a world leader in combatting communicable diseases, and remain central to public health policy.