Daniel McCarthy

Research

Substantive

Data privacy, customer management, customer-based corporate valuation

Methodological

Data fusion, limited data, computational methods, causal inference

Published or Forthcoming Papers:

  1. McCarthy, Daniel; Oblander, E. Shin (2020), "Scalable Data Fusion with Selection Correction: An Application to Customer Base Analysis," Marketing Science, 40(3), 459-480, Link (Download)
    Winner: 2019 Marketing Strategy Meets Wall Street Conference’s 2019 Best Paper Award

  1. Fader, Peter; Hardie, Bruce; McCarthy, Daniel; Vaidyanathan, Ramnath (2019), "Exploring the Equivalence of Two Common Mixture Models for Duration Data," The American Statistician, 73(3), 288-295, Link

  1. McCarthy, Daniel; Winer, Russell (2019), "The Pareto Rule in Marketing Revisited: Is it 80/20, or 70/20?," Marketing Letters, 30(2), 139-150, Link

  1. McCarthy, Daniel; Fader, Peter (2018), "Customer-Based Corporate Valuation for Publicly Traded Non-Contractual Firms," Journal of Marketing Research, 55(5), 617-635, Link (Download)

  1. McCarthy, Daniel; Zhang, Kai; Berk, Richard; Brown, Lawrence; Buja, Andreas; George, Edward; Zhao, Linda (2018), "Calibrated Percentile Double Bootstrap for Robust Linear Regression Inference," Statistica Sinica, 28, 2565-2589, Link (Download)

  1. McCarthy, Daniel; Fader, Peter; Hardie, Bruce (2017), "Valuing Subscription-Based Businesses Using Publicly Disclosed Customer Data," Journal of Marketing, 81(1), 17-35, Link (Download)

  1. McCarthy, Daniel; Jensen, Shane (2016), "Power Weighted Densities for Time Series Data," Annals of Applied Statistics, 10(1), 305-334, Link

  1. Brown, Lawrence; McCarthy, Daniel (2016), "Comments on the paper, "An Adaptive Resampling Test for Detecting the Presence of Significant Predictors," Journal of the American Statistical Association, Theory and Methods, 110, 1446-1449, Link

Other Publications

  • Damodaran, A.; McCarthy, Daniel; Cohen, M. (2022), "IPO Disclosures Are Ripe for Reform," Forthcoming at MIT Sloan Management Review

  • McCarthy, Daniel; Fader, Peter (2020), "How to Value a Company by Analyzing Its Customers," Harvard Business Review, 98 (1), 51-55, Link

Working Papers

  • Oblander, E. Shin; McCarthy, Daniel, "Persistence of Consumer Lifestyle Choices: Evidence from Restaurant Delivery During COVID-19," Under Review, Link

  • Kim, Kyeongbin; McCarthy, Daniel, "Wheels to Meals: Measuring the Economic Impact of Micromobility on Food Service Demand," Risky revision, revising for third round resubmission at Journal of Marketing Research Link

Selected Research In Progress

  • Kim, Kyeongbin; McCarthy, Daniel; Lee, Dokyun, "Deep Learning Methods for Customer Base Analysis: Evidence from 1000 Companies Over 6 Years"

  • McCarthy, Daniel; Oblander, E. Shin; Park, Young-Hoon, "The Impact of a Subscription Program Within and Across Categories: Evidence from Restaurant Delivery"

    • Winner, Stanley Sun Faculty Global Research Award ($10,000)

  • McCarthy, Daniel, "CBCV: Reshaping the Practice of Corporate Valuation Using a Customer-Driven Approach"

    • Winner, Gary Lilien ISMS-MSI-EMAC Practice Prize (video)