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Economies of Scale in Platforms and E-Commerce

Paper Session

Saturday, Jan. 7, 2023 2:30 PM - 4:30 PM (CST)

Hilton Riverside, Grand Salon D Sec 21 & 24
Hosted By: American Economic Association
  • Chair: Maisy Wong, University of Pennsylvania

The Impact of Distance and Taxes in Retail Markets

Jean-François Houde
,
University of Wisconsin-Madison
Peter Newberry
,
University of Georgia
Katja Seim
,
Yale University

Abstract

Over the past two decades, online retailers have invested heavily in their distribution networks.  While there are clear cost-side benefits to densifying distribution, being closer to consumers may also allow firms to decrease delivery times, increasing demand.  At the same time, due to ‘nexus laws’ in place during most of the sustained e-commerce growth period, retailers were only required to collect and remit sales tax on transactions originating from a state where they have a physical presence. Therefore, as retailers like Amazon open distribution facilities in new states, they increase their tax liabilities and, thus, decrease their demand.  We use transaction-level data for online and offline retailers to test for these two possible demand-side responses focusing on Amazon’s expansion of its distribution network. We find evidence that there is a significant tax response, but no response in demand as the distance between the consumer and the distribution network falls. This analysis suggests that Amazon trades off lower demand with cost-side benefits of distribution densification.

Scale Effects for Platforms in Housing Markets

Elsie Peng
,
University of Pennsylvania
Maisy Wong
,
University of Pennsylvania

Abstract

We contribute novel estimates of scale effects for platforms by studying the 2013 mergers of three Multiple Listings Service (MLS) in Florida, the primary platforms where properties are transacted. Our differences-in-differences estimates using listings data from 2009 to 2018 demonstrate that brokerage firms that experienced an expansion in platform scale also enjoyed more revenue gains, controlling for firm fixed effects and housing market conditions. Heterogeneity analyses suggest large brokerages benefit more. Platform scale expansion also translated into faster sales.

Field Experiments for Platform Regulation

Chiara Farronato
,
Harvard University
Andrey Fradkin
,
Boston University
Alexander MacKay
,
Harvard University

Abstract

There is increasing regulatory scrutiny of digital platforms. Regulators are focusing on the ways in which platforms collect and use consumer data as well as the competitive strategies that they adopt to achieve or maintain their dominant position. Despite the perceived urgency to rein in platforms, there is surprisingly little evidence on the welfare effects that their practices generate. For academics to collaborate with platform companies to answer these questions is understandably difficult, given the reputational risks facing platforms. In this paper we describe a new approach that the literature has recently adopted to estimate how platforms affect consumers: field experiments that make use of software to manipulate and track consumer experience on platforms. We describe the approach to document new facts about search purchasing behavior on a large e-commerce platform.

Matching and Network Effects in Ride Hailing

Juan Camilo Castillo
,
University of Pennsylvania

Abstract

In two-sided markets with matching, the form of the matching function determines the magnitude of network externalities and economies of scale, with important consequences for welfare and policy. Estimating the matching function, however, is typically challenging because of data limitations. In this article, I use detailed data from Uber to estimate the matching function in order to quantify network externalities and economies of density. I then present results about optimal taxes/subsidies and the effect of multi-homing in ride hailing platforms.
JEL Classifications
  • L1 - Market Structure, Firm Strategy, and Market Performance
  • L4 - Antitrust Issues and Policies