Found 11 article(s) for author 'Michael Luca'

How Amazon’s Higher Wages Could Increase Productivity

How Amazon’s Higher Wages Could Increase Productivity. Michael Luca, October 10, 2018, Paper, “Amazon recently made headlines by announcing that it would voluntarily increase its minimum hourly wage to $15. With a federal minimum wage of only $7.25, this pledge might seem like a curious decision — especially for a company as laser-focused on cost containment as Amazon. But thinking only about the costs involved in raising wages misses a key issue: pay hikes can also boost workplace productivity.Link

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Economists (and Economics) in Tech Companies

Economists (and Economics) in Tech Companies. Michael Luca, September 11, 2018, Paper, “As technology platforms have created new markets and new ways of acquiring information, economists have come to play an increasingly central role in tech companies – tackling problems such as platform design, strategy, pricing, and policy. Over the past five years, hundreds of PhD economists have accepted positions in the technology sector. In this paper, we explore the skills that PhD economists apply in tech companies, the companies that hire them, the types of problems that economists are currently working on, and the areas of academic research that have emerged in relation to these problems.Link

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

How Companies Can Use the Data They Collect to Further the Public Good. Edward Glaeser, Michael Luca, May 16, 2018, Paper, “By the end of 2017, Yelp had amassed more than 140 million reviews of local businesses. While the company’s mission focuses on helping people find local businesses more easily, this wealth of data has the potential to serve other purposes. For instance, Yelp data might help restaurants understand which markets they should consider entering, or whether to add a bar. It can help real estate investors understand where gentrification might occur. And it might help private equity firms with an interest in coffee decide whether to invest in Philz or Blue Bottle.Link

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

Nowcasting the Local Economy: Using Yelp Data to Measure Economic Activity at Scale. Edward Glaeser, Michael Luca, 2017, Paper, “Can new data sources from online platforms help to measure local economic activity at scale? Government datasets from agencies such as the U.S. Census Bureau have long been the gold standard for measuring economic activity at the local level. However, these statistics typically appear only after multi-year lags, and the public-facing versions are aggregated to the county or ZIP code level. In contrast, crowdsourced data from online platforms such as Yelp are often contemporaneous and geographically finer than official government statistics. In this paper, we present evidence that Yelp data can complement government surveys by measuring economic activity in close to real time, at a granular level.Link

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Survival of the Fittest: The Impact of the Minimum Wage on Firm Exit

Survival of the Fittest: The Impact of the Minimum Wage on Firm Exit. Michael Luca, April 11, 2017, Paper, “We study the impact of the minimum wage on firm exit in the restaurant industry, exploiting recent changes in the minimum wage at the city level. The evidence suggests that higher minimum wages increase overall exit rates for restaurants. However, lower quality restaurants, which are already closer to the margin of exit, are disproportionately impacted by increases to the minimum wage. Our point estimates suggest that a one dollar increase in the minimum wage leads to a 14 percent increase in the likelihood of exit for a 3.5-star restaurant (which is the median rating), but has no discernible impact for a 5-star restaurant (on a 1 to 5 star scale).Link

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Why We Don’t Value Flextime Enough

Why We Don’t Value Flextime Enough. Michael Luca, March 3, 2017, Opinion, “Earlier this month, the city council in Copenhagen voted unanimously to give all municipal workers greater control over their schedules. The city’s 10,000 employees will work the same number of hours as before but with greater freedom to decide when that…Link

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Fixing Discrimination in Online Marketplaces

Fixing Discrimination in Online Marketplaces. Michael Luca, December 2016, Paper, “In the late 1980s, law professors Ian Ayres and Peter Siegelman set out to learn whether blacks and women got the same deals as white men when buying a new car. They trained 38 people—some white and some black, some male and some female—to negotiate a purchase using a fixed script, and uncovered disturbing differences: Across 153 dealerships, black and female buyers paid more for the same cars than white men did, with black women paying the most—on average, nearly $900 more than white men. Although the findings weren’t a surprise to most people, least of all to blacks and women, they were a compelling demonstration of just how discriminatory markets can be.Link

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Productivity and Selection of Human Capital with Machine Learning

Productivity and Selection of Human Capital with Machine Learning. Michael Luca, Sendhil Mullainathan, 2016, Paper. “Economists have become increasingly interested in studying the nature of production functions in social policy applications, Y = f(L, K), with the goal of improving productivity. For example what is the effect on student learning from hiring an additional teacher, ∂Y/∂L, in theory (Lazear, 2001) or in practice (Krueger, 2003)? What is the effect of hiring one more police officer (Levitt, 1997)?Link

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Racial Discrimination in the Sharing Economy: Evidence from a Field Experiment

Racial Discrimination in the Sharing Economy: Evidence from a Field Experiment. Benjamin Edelman, Michael Luca, December 9, 2015, “Online marketplaces increasingly choose to reduce the anonymity of buyers and sellers in order to facilitate trust. We demonstrate that this common market design choice results in an important unintended consequence: racial discrimination. In a field experiment on Airbnb, we find that requests from guests with distinctively African-American names are roughly 16% less likely to be accepted than identical guests with distinctively White names. The difference persists…Link

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