Category: Recommended Reads

Private Precaution and Public Restrictions: What Drives Social Distancing and Industry Foot Traffic in the COVID-19 Era?

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This paper analyzes cell phone data from March through mid May, finding that private, self-regulating changes in behavior explained about 75% of the decline in foot traffic across most industries, while restrictive regulation (including school closures) had more influence on essential retail foot traffic and the fraction of cell phones that remained at home all day.

Christopher J. Cronin & William N. Evans, National Bureau of Economic Research Working Paper No. 27531

The U.S. Labor Market During the Beginning of the Pandemic Recession

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Using data from the nation’s largest payroll processor from February through May, this paper finds that employment losses were disproportionately concentrated among low-income workers while wage cuts were disproportionately concentrated among workers in the top two deciles of the wage distribution. The percent of workers receiving wage cuts was roughly twice that
reported during the Great Recession.

Tomaz Cajner et al., National Bureau of Economic Research Working Paper No. 27159

Quants Sound the Alarm as Everyone Chases Same Alternative Data

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This article explores how Wall Street is mining geolocational data, payments
information, social media posts, and various other sources of data in an effort to better understand emerging trends from the pandemic. While useful in various ways, it also cautions about the risk of unrepresentative data.

Justina Lee, Bloomberg

The Impact of COVID-19 on Small Business Owners Continued Losses and the Partial Rebound in May 2020

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This paper provides the first analysis of impacts of the pandemic on the number of active small businesses in the United States using nationally representative data from May 2020. The number of active business owners rebounded 7% since the low in April but remained 15% down from February. Drops in business activity from pre-pandemic levels are disproportionately concentrated among African-American (26%), Latino (19%), Asian (21%), and immigrant (25%) business owners.

Robert Fairlie, National Bureau of Economic Research Working Paper No. 27462

How Did COVID-19 and Stabilization Policies Affect Spending and Employment? A New Real-Time Economic Tracker Based on Private Sector Data

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Using real time anonymized data from private companies, this paper focuses on the ripple effects of a sharp decrease in spending by high-income households on both small businesses and low-income workers.

Raj Chetty et al., National Bureau of Economic Research Working Paper No. 27431

Heterogeneity in the Marginal Propensity to Consume: Evidence from Covid-19 Stimulus Payments

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This report tracks consumer spending patterns in the weeks after receiving federal stimulus payments using debit card data for more than 16,000 recipients. Consumers who live paycheck-to-paycheck spent 68% of the funds in the first two weeks, while higher-income consumers and those who generally save a significant portion of their income spent an average of 23% in the same time period.

Ezra Karger & Aastha Rajan, Federal Reserve Bank of Chicago Working Paper No. 2020-15

New Data Suggests COVID-19 is Widening Housing Disparities by Race and Income

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The blog analyzes survey results from the U.S. Census Bureau that provide the first real-time, national data on housing payments disaggregated by race and ethnicity, income, age, and other household characteristics. Among both renters and homeowners, African-Americans, Latinos, and low-income households were more likely to miss or defer housing payments in May than other groups.

Solomon Greene & Alanna McCargo, Urban Institute

Implementing Personalized Law

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This essay considers the potential to use information technology to generate personalized disclosures to consumers concerning privacy policies, financial services, and consumer products more generally, as well as potential limits of the notice-and-consent model for managing privacy choices.

Christoph Busch, 86 University of Chicago Law Review 309

Privacy and Synthetic Datasets

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This article analyzes the technical nuances and legal implications of using synthetic data, which uses machine learning techniques to modify raw data, as an alternative to anonymization or differential privacy to protect privacy interests while facilitating research.

Steven M. Bellovin, Preetam K. Dutta, & Nathan Reitinger, 22 Stanford Technological Law Review 1

The New Frontier of Consumer Protection: Financial Data Privacy and Security

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This paper surveys several existing federal laws bearing on management of financial data as well as recent state activity before analyzing potential elements for comprehensive federal legislation.

Marshall Lux & Matthew Shakelford, Harvard Mossavar-Rahmani Center for Business & Government Working Paper 135

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