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Tech Economics

Paper Session

Friday, Jan. 3, 2020 2:30 PM - 4:30 PM (PDT)

Marriott Marquis, San Diego Ballroom A
Hosted By: National Association for Business Economics
  • Chair: Michael Luca, Harvard Business School

GDPR and the Localness of Venture Investment

Jian Jia
,
Illinois Institute of Technology
Ginger Jin
,
University of Maryland
Liad Wagman
,
Illinois Institute of Technology

Abstract

We examine how investors' tendency to invest locally interacts with Europe's General Data Protection Regulation (GDPR). Using five-year investment data, we demonstrate that GDPR differentially affects investors as a function of their proximity to ventures. We show that GDPR's rollout in May 2018 has negative effects on EU venture investment, and the effects are larger when ventures and lead investors are not in the same state or union. The relationship manifests in the number of deals and the amount invested per deal, and is pronounced for newer, data-related, and consumer-facing ventures, as well as for repeat investments. GDPR's earlier enactment in April 2016 exhibits similar effects for investors that invest out of their preferred industries.

New Goods, Productivity and the Measurement of Inflation: Using Machine Learning to Improve Quality Adjustments

Victor Chernozhukov
,
Massachusetts Institute of Technology
Patrick Bajari
,
Amazon

Abstract

New Goods, Productivity and the Measurement of Inflation: Using Machine Learning to Improve Quality Adjustments

Double Randomized Online Experiments

Guido Imbens
,
Stanford University
Patrick Bajari
,
Amazon

Abstract

Consider an online market place where a large number of buyers and sellers meet. Each
meeting of a buyer and seller takes place in a structured environment, where some infor-
mation is made available to potential buyers (and possibly to sellers), prior to a decision
being made by buyers and sellers to engage in an exchange. We are interested in evaluating
interventions that change the structure in which these meetings or interactions take place.
Traditionally we design experiments where either buyers or sellers are randomly assigned
to the intervention. The concern is that there may be spillovers both within buyers and
within sellers. The current paper addresses settings where both types of spillovers are
present. We introduce a new class of randomized experiments where we randomize both
buyers and sellers separately, and then expose pairs of buyers and sellers to the intervention
depending on the outcomes of their separate randomizations. We show how this includes
buyer and seller experiments as special cases. We also show how such experiments can
shed light on spillovers that cannot be uncovered by buyer or seller experiments. We also
develop analytic methods for such experiments.
JEL Classifications
  • L1 - Market Structure, Firm Strategy, and Market Performance