by Edward L. Glaeser, Hyunjin Kim, and Michael Luca - Publications - Faculty & Research

April 2024
Article

Decision Authority and the Returns to Algorithms

By: Hyunjin Kim, Edward L. Glaeser, Andrew Hillis, Scott Duke Kominers and Michael Luca

We evaluate a pilot in an Inspections Department to explore the returns to a pair of algorithms that varied in their sophistication. We find that both algorithms provided substantial prediction gains, suggesting that even simple data may be helpful. However, these... View Details

Keywords: Algorithmic Aversion; Algorithmic Decision Making; Algorithms; Public Entrepreneurship; Govenment; Local Government; Crowdsourcing; Crowdsourcing Contests; Inspection; Principal-agent Theory; Government Administration; Decision Making; Public Administration Industry; United States

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Winter 2022
Article

Determinants of Small Business Reopening Decisions After COVID Restrictions Were Lifted

By: Dylan Balla-Elliott, Zoë B. Cullen, Edward L. Glaeser, Michael Luca and Christopher Stanton

The COVID-19 pandemic led to dramatic economic disruptions, including government-imposed restrictions that temporarily shuttered millions of American businesses. We use a nation-wide survey of thousands of small business owners to establish three main facts about... View Details

Keywords: COVID-19; Demand Forecasting; Reopening; Health Pandemics; Government Administration; Small Business

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2018
Working Paper

Measuring Gentrification: Using Yelp Data to Quantify Neighborhood Change

By: Edward L. Glaeser, Hyunjin Kim and Michael Luca

We demonstrate that data from digital platforms such as Yelp have the potential to improve our understanding of gentrification, both by providing data in close to real time (i.e., nowcasting and forecasting) and by providing additional context about how the local... View Details

Keywords: Geographic Location; Local Range; Transition; Analytics and Data Science; Measurement and Metrics; Forecasting and Prediction

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May 16, 2018
Other Article

How Companies Can Use the Data They Collect to Further the Public Good

By: Edward L. Glaeser, Hyunjin Kim and Michael Luca

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May 2018
Article

Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change

By: Edward L. Glaeser, Hyunjin Kim and Michael Luca

Data from digital platforms have the potential to improve our understanding of gentrification and enable new measures of how neighborhoods change in close to real time. Combining data on businesses from Yelp with data on gentrification from the Census, Federal Housing... View Details

Keywords: Forecasting Models; Simulation Methods; Regional Economic Activity: Growth, Development, Environmental Issues, And Changes; Geographic Location; Local Range; Transition; Analytics and Data Science; Measurement and Metrics; Economic Growth; Forecasting and Prediction

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January 17, 2018
Other Article

Using Traditional and Digital Data Sources Together in Economic Research

By: Edward L. Glaeser, Hyunjin Kim and Michael Luca

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2017
Working Paper

Nowcasting the Local Economy: Using Yelp Data to Measure Economic Activity

By: Edward L. Glaeser, Hyunjin Kim and Michael Luca

Can new data sources from online platforms help to measure local economic activity? Government datasets from agencies such as the U.S. Census Bureau provide the standard measures of economic activity at the local level. However, these statistics typically appear only... View Details

Keywords: Economy; Analytics and Data Science; Local Range; Social and Collaborative Networks

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Forthcoming
Article

The Rise of Remote Work: Evidence on Productivity and Preferences from Firm and Worker Surveys

By: Alexander Bartik, Zoë Cullen, Edward L. Glaeser, Michael Luca and Christopher Stanton

Drawing on surveys of small business owners and employees, we present three main findings about the evolution of remote work after the onset of COVID-19. First, uptake of remote work was abrupt and widespread in jobs suitable for telework according to the task-based... View Details

Keywords: COVID-19; Remote Work; Health Pandemics; Jobs and Positions; Demographics; Surveys