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A necessary exploration into the mechanics of data privacy protections within empirical social science research.

The explosion of computational power and data availability has revolutionized empirical social science research, but it has also created unprecedented challenges for protecting the privacy of individuals and businesses. As computational tools make it increasingly possible to breach data anonymity in government surveys by combining the survey data with additional information from external sources, statistical agencies face mounting pressure to develop new privacy protection methods while maintaining data quality essential for research and policymaking. This volume explores how innovations in data privacy protection, including differential privacy and synthetic data methods, affect the conduct of empirical analysis in economics, computer science, and statistics. Contributors explore critical questions about the trade-offs between privacy and data usability: How do new protection methods impact statistical inference and parameter estimation? What standards should data providers adopt? The chapters examine frameworks for characterizing privacy protection, disclosure limitation challenges for survey data, methodological innovations for privacy-preserving statistical analysis, regulatory considerations in modern data governance, and strategies for balancing confidentiality with research access.

This volume provides researchers, statistical agencies, and policymakers with essential guidance for navigating the complex landscape where data protection meets scientific inquiry.

A landmark practical guide from the twenty-first-century pioneer in economics.

Experimental economics—generating and interpreting data to understand human decisions, motivations, and outcomes—is today all but synonymous with economics as a discipline. The advantages of the experimental method for understanding causal effects make it the gold standard for an increasingly empirical field. But until now the discipline has lacked comprehensive and definitive guidance for how to optimally design and conduct economic experiments.

For more than 30 years, John A. List has been at the forefront of using experiments to advance economic knowledge, expanding the domain of economic experiments from the lab to the real-world. Experimental Economics is his A-to-Z compendium for students and researchers on the ground floor of designing, conducting, analyzing, and interpreting data that they generate. List seeks not only to guide readers on how to develop and implement their experimental projects—everything from design to administrative and ethical considerations—but to help them avoid all the mistakes he’s made in his career, too. Experimental Economics codifies its author’s refined approach to the design, execution, and analysis of laboratory and field experiments. It is a milestone work poised to become the definitive reference for the next century of economics (and economists).

A comprehensive survey of the evolution of market design over the past three decades.

In the mid-1990s, the first Federal Communications Commission spectrum auction and the redesign of the National Residency Matching Program collectively helped to jumpstart the field of market design. Since then, extensive research has improved auction design and broken new conceptual ground in addressing multi-agent matching problems. This volume summarizes key discoveries and advances in market design over the past three decades and explores contemporary challenges—from climate policy and electricity markets to AI-mediated exchanges and hospital resource allocation.

Contributors examine how to design efficient, incentive-compatible mechanisms that are robust to shifting conditions and increasing complexity. They consider a wide variety of applications that could benefit from the market design viewpoint, such as environmental markets, school choice, and organ exchange. Together, the chapters illustrate the important interactions between economic theory, computational tools, and institutional insight.

Categorizing race and ethnicity for twenty-first-century statistics and economics.

The increasing racial and ethnic diversity of the US population raises the question of whether the race and ethnicity categories and definitions used by federal statistical agencies to create demographic statistics on which government officials, business decision-makers, and private citizens rely fully reflect the changing population. Official definitions of existing race and ethnic groups do not always command wide agreement, and over time, some definitions that were once widely accepted may become less so based on political, legal, and social factors. Comparable measures of race and ethnicity over time are needed to accurately track historical changes in economic and social outcomes, as well as racial and ethnic segregation.

This volume explores the production of economic statistics that accurately depict the complex racial and ethnic diversity of the US population in the twenty-first century. The chapters examine the consequences for economic analyses of different measurement choices concerning race and ethnicity, assess the likely implications of the 2024 changes in federal race and ethnicity measurement standards, introduce new data sets with richer demographic information, and compare measures of race and ethnicity in administrative versus survey data. They also apply existing data in creative ways to develop alternative characterizations of the changing US workforce and to illuminate important policy questions related to criminal justice, immigration, labor market discrimination, the social safety net, health care, and child welfare.

The Solutions Manual to Elements of Econometrics, Second Edition provides chapter solutions to the exercises in the college textbook: Elements of Econometrics, Second Edition by Jan Kmenta.

Innovative new approaches for improving GDP measurement to better gauge economic productivity.

Official measures of gross domestic product (GDP) indicate that productivity growth has declined in the United States over the last two decades. This has led to calls for policy changes from pro-business tax reform to stronger antitrust measures. But are our twentieth-century economic methods actually measuring our twenty-first-century productivity?

The Measure of Economies offers a synthesis of the state of knowledge in productivity measurement at a time when many question the accuracy and scope of GDP. With chapters authored by leading economic experts on topics such as the digital economy, health care, and the environment, it highlights the inadequacies of current practices and discusses cutting-edge alternatives.

Pragmatic and forward-facing, The Measure of Economies is an essential resource not only for social scientists, but also for policymakers and business leaders seeking to understand the complexities of economic growth in a time of rapidly evolving technology.