Live and Let Live
Seller Reputation and Price Gouging: Evidence from the COVID‐19 Pandemic
Luís Cabral & Lei Xu
Economic Inquiry, forthcoming
From mid‐January to March 2020, 3M masks sold on Amazon by third party sellers were priced 2.4 times higher than Amazon's 2019 price. However, this price increase was not uniform across sellers. We estimate that when Amazon is stocked out (one of our measures of scarcity) new (entrant) sellers increase price by 178%, whereas the continuing sellers' increase is limited to 56.7%. This is consistent with the idea that seller reputation limits the extent of profitable price gouging. Similar results are obtained for Purell hand sanitizer and for other measures of scarcity. We also explore policy implications of our results.
The “Matthew Effect” and Market Concentration: Search Complementarities and Monopsony Power
Jesús Fernández-Villaverde et al.
NBER Working Paper, February 2021
This paper develops a dynamic general equilibrium model with heterogeneous firms that face search complementarities in the formation of vendor contracts. Search complementarities amplify small differences in productivity among firms. Market concentration fosters monopsony power in the labor market, magnifying profits and further enhancing high-productivity firms' output share. Firms want to get bigger and hire more workers, in stark contrast with the classic monopsony model, where a firm aims to reduce the amount of labor it hires. The combination of search complementarities and monopsony power induces a strong “Matthew effect” that endogenously generates superstar firms out of uniform idiosyncratic productivity distributions. Reductions in search costs increase market concentration, lower the labor income share, and increase wage inequality.
Does Restricting the Entry of Formula Businesses Help Mom-and-Pop Stores? The Case of Small American Towns With Unique Community Character
Minjee Kim & Tingyu Zhou
Economic Development Quarterly, May 2021, Pages 157-173
Communities worldwide are increasingly introducing regulatory measures to protect independent businesses from chain stores, but the efficacy of these attempts is largely debated. Moreover, effects are likely to vary by the characteristics of the local economy, a consideration overlooked by existing studies. Using a sample of U.S. cities with unique community characteristics, the authors examine Formula Business Restrictions (FBR), a type of an American land use regulation that restricts the entry of “formula businesses.” The authors find that the passage of FBR led to a higher number and percentage of employees working in mom-and-pop businesses, which was primarily achieved by protecting existing ones from downsizing. This positive effect occurred over time with increasing magnitude. The authors also find heterogeneous effects on different sectors: FBR had strong positive effects on the retail sector, but not on the service sector. Findings suggest that chain store entry barriers can be beneficial for mom-and-pop businesses when designed carefully.
Are dominant platforms good for consumers?
Chiu Yu Ko & Bo Shen
Economic Inquiry, forthcoming
We develop a two‐sided market model where both platforms and sellers charge buyers for access. When network effects are moderate, a dominant platform that attracts more sellers and buyers is more likely to arise. Compared to when platforms split the market equally, a dominant platform always leads to higher consumer surplus and total welfare. Moreover, both of these measures improve as network effects increase. Our results suggest that competition authorities should be cautious regarding complaints related to dominant platforms in two‐sided markets, as they may be good for consumers.
The Short-Run Effects of the General Data Protection Regulation on Technology Venture Investment
Jian Jia, Ginger Zhe Jin & Liad Wagman
Marketing Science, forthcoming
The General Data Protection Regulation (GDPR) was enacted in the European Union in April 2016 and went into effect in May 2018. We study its impact on investment in new and emerging technology firms. Our findings indicate negative post-GDPR effects after its 2018 rollout on European ventures relative to their counterparts in the United States and the rest of the world, and considerably lesser effects after its 2016 enactment and before implementation. The negative effects manifest in the number of and amounts raised in financing deals, and are particularly pronounced for newer, data-related, and business-to-consumer ventures.
What Happens When Airbnb Comes to the Neighborhood: The Impact of Home-sharing on Neighborhood Investment
Minhong Xu & Yilan Xu
Regional Science and Urban Economics, forthcoming
Home-sharing increases the potential economic returns to residential properties. We examine how the expansion of Airbnb has stimulated neighborhood investment. Our instrumental variable estimates show that a one-percent increase in Airbnb listings raised the number of residential renovation projects by 0.527 percent and the value of retail renovation investment by 3.691 percent in the following quarter. Meanwhile, the net growth of liquor, retail food, and entertainment business licenses increased by 2.067, 3.933, and 0.755, respectively. The investment effects were driven disproportionately by commercial hosts operating multiple listings and were more prominent in declining neighborhoods.
Externalities of the Sharing Economy: Evidence from Ridesharing and the Local Housing Market
Georgia State University Working Paper, December 2020
This study highlights the externalities of the sharing economy on local economies. Using the introduction of Uber X as a staggered shock, I assess how ridesharing influences the local housing market through the interaction with public transit. After ridesharing’s entry, housing prices and market rents increase at the zip code level. The effect is more pronounced in locations with greater access to public transit and lower driving probability, consistent with the notion that ridesharing complements public transit. Similarly, there is a larger increase in housing prices and rents in zip codes with larger populations, lower median ages and more minorities, consistent with Uber X users’ characteristics. Also, price appreciation is strongest for houses that are just beyond walking distance to public transit, suggesting that ridesharing helps solve the “last mile” problem and redistributes the public transit premium. Overall, this study highlights the externalities of the sharing economy and provides important policy implications.
Associating ridesourcing with road safety outcomes: Insights from Austin, Texas
Eleftheria Kontou & Noreen McDonald
PLoS ONE, March 2021
Improving road safety and setting targets for reducing traffic-related crashes and deaths are highlighted as part of the United Nations sustainable development goals and worldwide vision zero efforts. The advent of transportation network companies and ridesourcing expands mobility options in cities and may impact road safety outcomes. We analyze the effects of ridesourcing use on road crashes, injuries, fatalities, and driving while intoxicated (DWI) offenses in Travis County, Texas. Our approach leverages real-time ridesourcing volume to explain variation in road safety outcomes. Spatial panel data models with fixed-effects are deployed to examine whether the use of ridesourcing is significantly associated with road crashes and other safety metrics. Our results suggest that for a 10% increase in ridesourcing trips, we expect a 0.12% decrease in road crashes, a 0.25% decrease in road injuries, and a 0.36% decrease in DWI offenses in Travis County. On the other hand, ridesourcing use is not significantly associated with road fatalities. This study augments existing work because it moves beyond binary indicators of ridesourcing availability and analyzes crash and ridesourcing trips patterns within an urbanized area rather than their metropolitan-level variation. Contributions include developing a data-rich approach for assessing the impacts of ridesourcing use on the transportation system’s safety, which may serve as a template for future analyses for other cities. Our findings provide feedback to policymakers by clarifying associations between ridesourcing use and traffic safety and uncover the potential to achieve safer mobility systems with transportation network companies.
Human biases limit cumulative innovation
Bill Thompson & Thomas Griffiths
Proceedings of the Royal Society B: Biological Sciences, 10 March 2021
Is technological advancement constrained by biases in human cognition? People in all societies build on discoveries inherited from previous generations, leading to cumulative innovation. However, biases in human learning and memory may influence the process of knowledge transmission, potentially limiting this process. Here, we show that cumulative innovation in a continuous optimization problem is systematically constrained by human biases. In a large (n = 1250) behavioural study using a transmission chain design, participants searched for virtual technologies in one of four environments after inheriting a solution from previous generations. Participants converged on worse solutions in environments misaligned with their biases. These results substantiate a mathematical model of cumulative innovation in Bayesian agents, highlighting formal relationships between cultural evolution and distributed stochastic optimization. Our findings provide experimental evidence that human biases can limit the advancement of knowledge in a controlled laboratory setting, reinforcing concerns about bias in creative, scientific and educational contexts.
The influence of hidden researcher decisions in applied microeconomics
Nick Huntington‐Klein et al.
Economic Inquiry, forthcoming
Researchers make hundreds of decisions about data collection, preparation, and analysis in their research. We use a many‐analysts approach to measure the extent and impact of these decisions. Two published causal empirical results are replicated by seven replicators each. We find large differences in data preparation and analysis decisions, many of which would not likely be reported in a publication. No two replicators reported the same sample size. Statistical significance varied across replications, and for one of the studies the effect's sign varied as well. The standard deviation of estimates across replications was 3–4 times the mean reported standard error.
Mergers and labor market outcomes in the US airline industry
Myongjin Kim, Qi Ge & Donggeun Kim
Contemporary Economic Policy, forthcoming
This article examines US airline mergers between 1993 and 2018 and studies their impact on the labor market. Our difference‐in‐differences estimates indicate a significant reduction in the merging airlines' long‐term wage and fringe benefits following the mergers. The effect is particularly salient among large‐scale mergers involving major airlines and low cost carriers. The results also suggest a negative short‐term employment impact of mergers that varies by occupation types. Our findings are consistent with the impact of merger‐induced monopsony power discussed in recent literature and offer important policy implications regarding how to account for employer monopsony power during mergers and acquisitions.
Be Cautious in the Last Month: The Sunk Cost Fallacy Held by Car Insurance Policyholders
International Economic Review, forthcoming
Investigating a unique large dataset, we find that automobile insurance policyholders are more likely to encounter accidents during the last month of the insurance policy term than during any other month. Our interpretation is that this effect is driven by the sunk cost fallacy held by policyholders, which exacerbates their moral hazard. The explanation is that in the last month, policyholders may become concerned that they may “waste” the premiums paid upfront if they have not encountered an accident before the policy expires; thus, they will reduce their accident‐prevention efforts, although the premiums are sunk costs and cannot be reversed.
What do residential lotteries show us about transportation choices?
Adam Millard-Ball et al.
Urban Studies, forthcoming
Credibly identifying how the built environment shapes behaviour is empirically challenging, because people select residential locations based on differing constraints and preferences for site amenities. Our study overcomes these research barriers by leveraging San Francisco’s affordable housing lotteries, which randomly allow specific households to move to specific residences. Using administrative data, we demonstrate that lottery-winning households’ baseline preferences are uncorrelated with their allotted residential features such as public transportation accessibility, parking availability and bicycle infrastructure – meaning that neighbourhood attributes and a building’s parking supply are effectively assigned at random. Surveying the households, we find that these attributes significantly affect transportation mode choices. Most notably, we show that essentially random variation in on-site parking availability greatly changes households’ car ownership decisions and driving frequency, with substitution away from public transport. In contrast, we find that parking availability does not affect employment or job mobility. Overall, the evidence from our study robustly supports that local features of the built environment are important determinants of transportation behaviour.