PUBLICATIONS

Should We Expect Merger Synergies to Be Passed Through to Consumers?, with Andrew Sweeting and Xuezhen Tao, February 2022, CEPR discussion paper #17059. The Journal of Industrial Economics, Vol. 73(1) pp.1-30, March 2025. [WP version]

How Do Top Acquirers Compare in Technology Mergers? New Evidence from an S&P Taxonomy, with Ginger Zhe Jin and Liad Wagman, NBER working paper #29642, International Journal of Industrial Organization, Vol.89, 2023. [NBER WP version]. Finalist of the 2024 Antitrust Writing Award.

M&A and Innovation: A New Classification of Patents, with Zhaoqi Cheng, Ginger Zhe Jin, Dokyun Lee, and Liad Wagman, American Economic Association: Papers and Proceedings, Vol. 113, pp.288-293, May 2023. [WP version]

M&A and Technological Expansion, with Ginger Zhe Jin and Liad Wagman, NBER working paper #31126, Journal of Economics & Management Strategy, Vol. 3(2), pp. 338-359, 2024. [NBER WP version]

Taxing Ride-sharing: Which Neighborhoods Pay More?, January 2022, SSRN working paper #4021595. Journal of Regional Science, Vol. 64(4), pp. 1393-1413, 2024. [WP version]

WORKING PAPERS

Strategic Investment in Competitors: Theory and Evidence from Technology Startups, September 2024, SSRN working paper #4968068.

Washington Center for Equitable Growth grant.
Presented at: IIOC 2025, EAYE 2025, Harvard-Oxford Conference on Common Ownership, 2024 BSE Summer Forum, EARIE 2024, DRUID 2024, Boston University Questrom School of Business, University of Toronto Rotman School of Management, ESADE Business School, Universitat Pompeu Fabra, Universidad Carlos III de Madrid, Georgia Institute of Technology (Strategy & Innovation), WEFI Student Workshop, University of Maryland (Dept. of Economics), University of Maryland Smith School of Business (Finance, Strategy).

Abstract. I examine how venture capitalists’ (VCs') investments in competing startups impact their outcomes. Theoretically, I show that if VCs improve their screening practices by investing in a particular business area, they may favor the startup subsequently invested in that area, at the expense of that initially financed. Using Crunchbase data and S&P’s unique technology taxonomy, I find that these subsequent startups raise more venture capital and secure follow-on funding more often than those not sharing a VC with a competitor. This, however, hurts initial startups. The result is only partially explained by improved screening by VCs, indicating how investing in competing startups significantly affects their monitoring practices.

Dynamic Competition with Bargaining: Implications for Subsidy and Competition Policies, with Shanglyu Deng, Calvin Jia and Andrew Sweeting. April 2024, NBER working paper #32360. [NBER WP version]

Presented at: Yale, Berkeley, IIOC 2023, Annual Northwestern Conference on Antitrust and Competiton Policy, Bank of Canada, CEPR/JIE IO Conference 2023, Cornell University.

Abstract. Existing models of dynamic competition assume that buyers are price-takers, even though prices are negotiated in many industries motivating this literature. We ex- tend a well-known duopoly model to allow for Nash-in-Nash bargaining, with seller price-setting nested as a special case. We illustrate how market structure, dynamic incentives, welfare and the existence of multiple equilibria change with the allocation of bargaining power. We extend the model to allow for forward-looking buyers and more sellers, and to illustrate how the allocation affects optimal subsidy policies and the effects of horizontal mergers, exclusive contracts and policies designed to limit dominance.

Hiding a Flaw? Experimental Evidence on Multi-Dimensional Information Disclosure, with Agata Farina, April 2024, SSRN working paper #4785923.

Presented at: 2025 AES Annual Conference, Accounting and Economics Society Weekly Webinars, DISS 2025, University of Maryland, NYU, North America ESA 2022.

Abstract. Economic agents often have private verifiable information about multiple attributes characterizing their product or service. Since selectively disclosing only certain attributes can make information withholding more salient, we experimentally study how the dimensionality of the information space affects receivers’ skepticism about undisclosed information and hence senders’ disclosure incentives. We find that increasing the number of attributes from one to two leads to more disclosure of unfavorable information. By eliciting players’ beliefs, we show that this effect is driven by senders expecting more skepticism about undisclosed dimensions. Nonetheless, receivers do not exhibit any significant behavior change, making senders’ strategy sub-optimal.

The Effects of Targeted Platform Taxes: Evidence from the Ride-Sharing and Taxi Industry, April 2021, SSRN working paper #3824453.

Presented at: Digital Business Institute at BU, ACM EC'22, IIOC 2021, 2021 MACCI Annual Conference, University of Maryland.
Peer-reviewed extended abstract published in the Proceedings of the 2022 ACM Conference on Economics and Computation.

Abstract. I study the effects of a tax imposed by the city of Chicago, which levied taxes on ride-sharing but not traditional taxi trips. I document a significant increase in ride-sharing prices, particularly for single rides starting or ending in downtown Chicago, which faced the largest tax increment. Tax pass-through rates were above 100% for single rides and even more pronounced for shared rides in the downtown area. This pattern can be explained by the fact that ride-sharing companies are multi-product peer-to-peer platforms and riders may substitute single with shared rides. The tax steered riders towards the shared service downtown, leading to a slight increase in traditional taxi usage. Conversely, areas outside downtown witnessed reduced ride-sharing use, with no rise in demand for taxis. This is consistent with a more intense competition between taxi and ride-sharing services downtown. Lastly, although the tax alleviated congestion, the magnitude of this benefit remains modest and constrained to the downtown area.

The Signaling Value of Technology Venture Acquisitions, with Ginger Zhe Jin and Liad Wagman. Revise and Resubmit.

Presented at: NBER Productivity Seminar, SEA 2024 Annual Meeting, Bank of Canada, USC Gould, University of Maryland Smith School of Business, CRESSE 2022.

Abstract. We study the effects of technology venture acquisitions on investment in the acquired firm’s business area. Using data on acquisitions and venture capital funding in the U.S. from Crunchbase, we consider the ventures acquired between 2014 and 2016 alongside a set of comparable control ventures that remained independent as of 2016. By modeling each venture as a point in the technology space, we leverage textual analysis to track investments in business areas similar to acquired or control ventures. Our difference-in-differences analysis shows that acquisitions stimulate venture capital investment, particularly in areas with fewer ventures and more intense past M&A or VC investment activity. Contrary to antitrust concerns, we find that acquisitions by big tech platforms and other large acquirers have a similar positive effect, whereas private equity buyouts lead to an even greater increase in venture capital activity.

How Does Privacy Regulation Affect Transatlantic Venture Investment? Evidence from GDPR, with Jian Jia, Ginger Zhe Jin and Liad Wagman, April 2025, NBER working paper #33909, SSRN working paper #3436535.

Media Coverage: NBER Digest [link]
Presented at: BSE Summer Forum 2025, DRUID 2025, USC Marshall.

Abstract. We analyze the impact of Europe's General Data Protection Regulation (GDPR) on venture investment flows between the European Union (EU) and US. Using data on investment rounds from 2014 to 2019, we find that GDPR's rollout in May 2018 led to a significant decline in US investor activity in the EU, evidenced by fewer deals and investment. The effects are pronounced for newer and data-related ventures, with investors shifting toward geographically closer ventures and increasing deal syndication. We find that investing in closer ventures is a key driver of the decline in investment inflows to Europe, while syndication mitigated some of the negative effects. The rise in syndication is primarily driven by US investors joining syndicates led by EU-based investors. Our findings highlight the critical role of digital policies in shaping investment strategies and influencing transatlantic capital flows.

Serial Acquisitions in Tech, with Ginger Zhe Jin, Liad Wagman, and Yunfei Wang, July 2025, NBER working paper #34178, SSRN working paper #5392628. [NBER WP version]

Presented at: 2025 Penn State-Cornell Conference on Econometrics and Industrial Organization, Boston University, EARIE 2025, CRESSE 2025, 2025 BYU/USC Winter Antitrust Conference.

Abstract. We examine serial acquisitions in the technology sector from 2010 to 2023. Defining serial acquisitions based on a granular S&P industry taxonomy, we find that they account for 24–37% of majority-control tech M&A, with over half completed by public firms. Follow-on targets in a series are generally larger and older than the initial acquisition, and among public acquirers, starting a series is associated with higher market value and greater innovation value, but not with significant changes in market competitiveness. Among deals with valid transaction values, over half of serial deals exceed the reporting threshold of the U.S. Hart–Scott–Rodino (HSR) Act. However, in below-threshold acquisitions, acquirers primarily target their core business category. Accounting for the cumulative value of a series would, in most cases, keep the timing of HSR review unchanged or modestly accelerate it, but when it does accelerate it, review could occur several deals or years earlier, potentially yielding important benefits in markets with long acquisition sequences. Finally, while Google/Alphabet, Amazon, Facebook/Meta, Apple and Microsoft (GAFAM) stand out from the rest of the sample for more frequent serial acquisitions, some other large acquirers display similar patterns.