About

I am a doctoral candidate in Finance at Columbia Business School. I will be available for interviews at the 2020 ASSA meeting in San Diego. 

  • Curriculum Vitae: CV

  • Email: dmei19[at]gsb.columbia.edu

  • Research Fields: Empirical Corporate Finance, Innovation, Merger and Acquisition 

Reference

Wei Jiang (Chair)

Arthur F. Burns Professor of Free and Competitive Enterprise

Columbia Business School

Finance & Economics Division

(212) 854 9002
wj2006@columbia.edu

Kairong Xiao

Assistant Professor

Columbia Business School
kairong.xiao@gsb.columbia.edu

Daniel Wolfenzon

Stefan H. Robock Professor of Finance and Economics
Columbia Business School

Finance & Economics Division
(212) 851 1803
dw2382@gsb.columbia.edu

Olivier M. Darmouni

Assistant Professor

Columbia Business School
omd2109@columbia.edu

 

Research

Technology Development and Corporate Mergers (Job Market Paper)

Presented at USC Marshall Ph.D. Conference in Finance; Empirics and Methods in Economics Conference; Meeting of Minds@HKU Forum; Western Finance Association 2020

 

Cubist Systematic Strategies Ph.D. Candidate Award for Outstanding Research, WFA

Abstract: I examine the motives as well as consequences of merger-and-acquisition (M&A) transactions between companies with varying degrees of technological overlap. High-overlap deals, with more collaboration between inventors from the merging companies, produce more patents and go deeper in the existing fields. In contrast, low-overlap deals, with a higher percentage of new inventors, experience larger technology shifts and develop patents in unexplored areas with higher commercial value. Importantly, M&A completion facilitates technology transformation to a greater degree than the two companies, especially pairs with low overlap, could have accomplished on their own. Overall, the direction of innovation is an important motive for technology-driven acquisitions.

 

Published Papers

- Activist Arbitrage in M&A Acquirers, Finance Research Letters, 2019, with Wei Jiang and Tao Li.

- Influencing Control: Jawboning in Risk Arbitrage, Journal of Finance, 2018, with Wei Jiang and Tao Li.​

 

- Appraisal: Shareholder Remedy or Litigation Arbitrage?, Journal of Law and Economics, 2016, with Wei Jiang, Tao Li, and Randall S. Thomas.

Work in Progress

- U.S.-China Technology Race, with Pengfei Han and Wei Jiang. 

- Technology, Information, and Firm Boundary, with Miao Liu. 

- Innovation, Management, and Compensation

- Debt Collection Technology, with Guangyu Cao and Daheng Yang.

Data

Matching USPTO Patent Assignees to Compustat Public Firms and SDC Private Firms

This data project is a systematic effort to match assignee names on USPTO patent records, sometimes abbreviated or misspelled, to all public and private firms that have been involved in alliances and M&A in Compustat and SDC Platinum databases. The current coverage runs from 1976 to 2017 for all public firms in Compustat and from 1985 to 2017 for all private firms in SDC Platinum.

The algorithm leverages the Bing web search engine and significantly improves upon fuzzy name matching, a common practice in the literature. This document presents a step-by-step guide to the searching and matching algorithm. All codes are publicly available on the GitHub page: 

https://github.com/danielm-github/patentsmatch_bingsearchapproach

This data is used in my job market paper "Technology Development and Corporate Mergers" and other projects including "Technology, Information, and Firm Boundary" (with Miao Liu). It will be made publicly available after the paper is published. I acknowledge the research grant from the Finance Division and the Deming Center at Columbia Business School.

 
 

Teaching

  • MBA. Advanced Corporate Finance, instructed by Neng Wang, Spring 2018

  • Executive Education. The Debevoise Business Education Program, Fall 2016

  • Ph.D. Financial Econometrics II Panel Data, instructed by Wei Jiang, Spring 2015

 

© 2019 by Danqing Mei.