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      • Faculty Publications  (530)

      Qualitative Research Methods Remove Qualitative Research Methods →

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      • December 2022
      • Article

      Shaping Nascent Industries: Innovation Strategy and Regulatory Uncertainty in Personal Genomics

      By: Cheng Gao and Rory McDonald
      In nascent industries—whose new technologies are often poorly understood by regulators—contending with regulatory uncertainty can be crucial to organizational survival and growth. Prior research on nonmarket strategy has largely focused on established firms in mature...  View Details
      Keywords: Technological Change; Innovation; Qualitative Methods; New Categories; Entrepreneurship; Technological Innovation; Governing Rules, Regulations, and Reforms; Risk and Uncertainty; Strategy
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      Gao, Cheng, and Rory McDonald. "Shaping Nascent Industries: Innovation Strategy and Regulatory Uncertainty in Personal Genomics." Administrative Science Quarterly 67, no. 4 (December 2022): 915–967.
      • November 2022
      • Article

      Measuring Inequality beyond the Gini Coefficient May Clarify Conflicting Findings

      By: Kristin Blesch, Oliver P. Hauser and Jon M. Jachimowicz
      Prior research has found mixed results on how economic inequality is related to various outcomes. These contradicting findings may in part stem from a predominant focus on the Gini coefficient, which only narrowly captures inequality. Here, we conceptualize the...  View Details
      Keywords: Economic Inequalty; Gini Coefficient; Income Inequality; Equality and Inequality; Social Issues; Health; Status and Position
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      Blesch, Kristin, Oliver P. Hauser, and Jon M. Jachimowicz. "Measuring Inequality beyond the Gini Coefficient May Clarify Conflicting Findings." Nature Human Behaviour 6, no. 11 (November 2022): 1525–1536.
      • August 2022
      • Article

      Contract Duration and the Costs of Market Transactions

      By: Alexander MacKay
      The optimal duration of a supply contract balances the costs of reselecting a supplier against the costs of being matched to an inefficient supplier when the contract lasts too long. I develop a structural model of contract duration that captures this tradeoff and...  View Details
      Keywords: Supply Contracts; Intermediate Goods; Switching Costs; Vertical Relationships; Transaction Costs; Contract Duration; Identification; Supply Chain; Cost; Contracts; Auctions; Mathematical Methods
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      MacKay, Alexander. "Contract Duration and the Costs of Market Transactions." American Economic Journal: Microeconomics 14, no. 3 (August 2022): 164–212.
      • June 2022
      • Article

      Conservatism Gets Funded? A Field Experiment on the Role of Negative Information in Novel Project Evaluation

      By: Jacqueline N. Lane, Misha Teplitskiy, Gary Gray, Hardeep Ranu, Michael Menietti, Eva C. Guinan and Karim R. Lakhani
      The evaluation and selection of novel projects lies at the heart of scientific and technological innovation, and yet there are persistent concerns about bias, such as conservatism. This paper investigates the role that the format of evaluation, specifically information...  View Details
      Keywords: Project Evaluation; Innovation; Knowledge Frontier; Information Sharing; Negativity Bias; Projects; Innovation and Invention; Information; Knowledge Sharing
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      Lane, Jacqueline N., Misha Teplitskiy, Gary Gray, Hardeep Ranu, Michael Menietti, Eva C. Guinan, and Karim R. Lakhani. "Conservatism Gets Funded? A Field Experiment on the Role of Negative Information in Novel Project Evaluation." Management Science 68, no. 6 (June 2022): 4478–4495.
      • June 2022
      • Article

      The Use and Misuse of Patent Data: Issues for Finance and Beyond

      By: Josh Lerner and Amit Seru
      Patents and citations are powerful tools for understanding innovation increasingly used in financial economics (and management research more broadly). Biases may result, however, from the interactions between the truncation of patents and citations and the changing...  View Details
      Keywords: Patents; Analytics and Data Science; Corporate Finance; Research
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      Lerner, Josh, and Amit Seru. "The Use and Misuse of Patent Data: Issues for Finance and Beyond." Review of Financial Studies 35, no. 6 (June 2022): 2667–2704.
      • 2022
      • Article

      Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis.

      By: Martin Pawelczyk, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay and Himabindu Lakkaraju
      As machine learning (ML) models become more widely deployed in high-stakes applications, counterfactual explanations have emerged as key tools for providing actionable model explanations in practice. Despite the growing popularity of counterfactual explanations, a...  View Details
      Keywords: Machine Learning Models; Counterfactual Explanations; Adversarial Examples; Mathematical Methods
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      Pawelczyk, Martin, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay, and Himabindu Lakkaraju. "Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 25th (2022).
      • Article

      How Much Should We Trust Staggered Difference-In-Differences Estimates?

      By: Andrew C. Baker, David F. Larcker and Charles C.Y. Wang
      Difference-in-differences analysis with staggered treatment timing is frequently used to assess the impact of policy changes on corporate outcomes in academic research. However, recent advances in econometric theory show that such designs are likely to be biased in the...  View Details
      Keywords: Difference In Differences; Staggered Difference-in-differences Designs; Generalized Difference-in-differences; Dynamic Treatment Effects; Mathematical Methods
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      Baker, Andrew C., David F. Larcker, and Charles C.Y. Wang. "How Much Should We Trust Staggered Difference-In-Differences Estimates?" Journal of Financial Economics 144, no. 2 (May 2022): 370–395. (Editor's Choice, May 2022.)
      • 2022
      • Article

      Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods.

      By: Chirag Agarwal, Marinka Zitnik and Himabindu Lakkaraju
      As Graph Neural Networks (GNNs) are increasingly employed in real-world applications, it becomes critical to ensure that the stakeholders understand the rationale behind their predictions. While several GNN explanation methods have been proposed recently, there has...  View Details
      Keywords: Graph Neural Networks; Explanation Methods; Mathematical Methods; Framework; Theory; Analysis
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      Agarwal, Chirag, Marinka Zitnik, and Himabindu Lakkaraju. "Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 25th (2022).
      • 2022
      • Working Paper

      A Linear Panel Model with Heterogeneous Coefficients and Variation in Exposure

      By: Jesse M. Shapiro and Liyang Sun
      Linear panel models featuring unit and time fixed effects appear in many areas of empirical economics. An active literature studies the interpretation of the ordinary least squares estimator of the model, commonly called the two-way fixed effects (TWFE) estimator, in...  View Details
      Keywords: Econometric Models; Mathematical Methods
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      Shapiro, Jesse M., and Liyang Sun. "A Linear Panel Model with Heterogeneous Coefficients and Variation in Exposure." NBER Working Paper Series, No. 29976, April 2022.
      • April 2022
      • Article

      Predictable Financial Crises

      By: Robin Greenwood, Samuel G. Hanson, Andrei Shleifer and Jakob Ahm Sørensen
      Using historical data on post-war financial crises around the world, we show that crises are substantially predictable. The combination of rapid credit and asset price growth over the prior three years, whether in the nonfinancial business or the household sector, is...  View Details
      Keywords: Financial Crisis; Global Range; Forecasting and Prediction; Mathematical Methods
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      Greenwood, Robin, Samuel G. Hanson, Andrei Shleifer, and Jakob Ahm Sørensen. "Predictable Financial Crises." Journal of Finance 77, no. 2 (April 2022): 863–921.
      • March 2022 (Revised July 2022)
      • Module Note

      Linear Regression

      By: Iavor I. Bojinov, Michael Parzen and Paul Hamilton
      This note provides an overview of linear regression for an introductory data science course. It begins with a discussion of correlation, and explains why correlation does not necessarily imply causation. The note then describes the method of least squares, and how to...  View Details
      Keywords: Data Science; Linear Regression; Mathematical Modeling; Mathematical Methods; Analytics and Data Science
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      Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Linear Regression." Harvard Business School Module Note 622-100, March 2022. (Revised July 2022.)
      • March 2022 (Revised July 2022)
      • Module Note

      Statistical Inference

      By: Iavor I. Bojinov, Michael Parzen and Paul Hamilton
      This note provides an overview of statistical inference for an introductory data science course. First, the note discusses samples and populations. Next the note describes how to calculate confidence intervals for means and proportions. Then it walks through the logic...  View Details
      Keywords: Data Science; Statistics; Mathematical Modeling; Mathematical Methods; Analytics and Data Science
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      Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Statistical Inference." Harvard Business School Module Note 622-099, March 2022. (Revised July 2022.)
      • Article

      Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)

      By: Eva Ascarza and Ayelet Israeli

      An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those “protected”...  View Details

      Keywords: Algorithm Bias; Personalization; Targeting; Generalized Random Forests (GRF); Discrimination; Customization and Personalization; Decision Making; Fairness; Mathematical Methods
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      Ascarza, Eva, and Ayelet Israeli. "Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)." e2115126119. Proceedings of the National Academy of Sciences 119, no. 11 (March 8, 2022).
      • March 2022
      • Article

      Estimating the Effectiveness of Permanent Price Reductions for Competing Products Using Multivariate Bayesian Structural Time Series Models

      By: Fiammetta Menchetti and Iavor Bojinov
      Researchers regularly use synthetic control methods for estimating causal effects when a sub-set of units receive a single persistent treatment, and the rest are unaffected by the change. In many applications, however, units not assigned to treatment are nevertheless...  View Details
      Keywords: Causal Inference; Partial Interference; Synthetic Controls; Bayesian Structural Time Series; Mathematical Methods
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      Menchetti, Fiammetta, and Iavor Bojinov. "Estimating the Effectiveness of Permanent Price Reductions for Competing Products Using Multivariate Bayesian Structural Time Series Models." Annals of Applied Statistics 16, no. 1 (March 2022): 414–435.
      • March 2022
      • Article

      Sensitivity Analysis of Agent-based Models: A New Protocol

      By: Emanuele Borgonovo, Marco Pangallo, Jan Rivkin, Leonardo Rizzo and Nicolaj Siggelkow
      Agent-based models (ABMs) are increasingly used in the management sciences. Though useful, ABMs are often critiqued: it is hard to discern why they produce the results they do and whether other assumptions would yield similar results. To help researchers address such...  View Details
      Keywords: Agent-based Modeling; Sensitivity Analysis; Design Of Experiments; Total Order Sensitivity Indices; Organizations; Behavior; Decision Making; Mathematical Methods
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      Borgonovo, Emanuele, Marco Pangallo, Jan Rivkin, Leonardo Rizzo, and Nicolaj Siggelkow. "Sensitivity Analysis of Agent-based Models: A New Protocol." Computational and Mathematical Organization Theory 28, no. 1 (March 2022): 52–94.
      • March 2022
      • Article

      Targeting High Ability Entrepreneurs Using Community Information: Mechanism Design in the Field

      By: Reshmaan Hussam, Natalia Rigol and Benjamin N. Roth
      Identifying high-growth microentrepreneurs in low-income countries remains a challenge due to a scarcity of verifiable information. With a cash grant experiment in India we demonstrate that community knowledge can help target high-growth microentrepreneurs; while the...  View Details
      Keywords: Microentrepreneurs; Community Information; Field Experiment; Loans; Entrepreneurship; Developing Countries and Economies; Financing and Loans; Information; Mathematical Methods; India
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      Hussam, Reshmaan, Natalia Rigol, and Benjamin N. Roth. "Targeting High Ability Entrepreneurs Using Community Information: Mechanism Design in the Field." American Economic Review 112, no. 3 (March 2022): 861–898.
      • Article

      A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects

      By: Edward McFowland III, Sandeep Gangarapu, Ravi Bapna and Tianshu Sun
      We define a prescriptive analytics framework that addresses the needs of a constrained decision-maker facing, ex ante, unknown costs and benefits of multiple policy levers. The framework is general in nature and can be deployed in any utility maximizing context, public...  View Details
      Keywords: Prescriptive Analytics; Heterogeneous Treatment Effects; Optimization; Observed Rank Utility Condition (OUR); Between-treatment Heterogeneity; Machine Learning; Decision Making; Analysis; Mathematical Methods
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      McFowland III, Edward, Sandeep Gangarapu, Ravi Bapna, and Tianshu Sun. "A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects." MIS Quarterly 45, no. 4 (December 2021): 1807–1832.
      • November 2021
      • Article

      Panel Experiments and Dynamic Causal Effects: A Finite Population Perspective

      By: Iavor Bojinov, Ashesh Rambachan and Neil Shephard
      In panel experiments, we randomly assign units to different interventions, measuring their outcomes, and repeating the procedure in several periods. Using the potential outcomes framework, we define finite population dynamic causal effects that capture the relative...  View Details
      Keywords: Panel Data; Dynamic Causal Effects; Potential Outcomes; Finite Population; Nonparametric; Mathematical Methods
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      Bojinov, Iavor, Ashesh Rambachan, and Neil Shephard. "Panel Experiments and Dynamic Causal Effects: A Finite Population Perspective." Quantitative Economics 12, no. 4 (November 2021): 1171–1196.
      • October 2021
      • Article

      Directors' Perceptions of Board Effectiveness and Internal Operations

      By: J. Yo-Jud Cheng, Boris Groysberg, Paul M. Healy and Rajesh Vijayaraghavan
      We contribute to the growing literature on the effectiveness of corporate boards by examining the effect of two insights that have been largely unexplored in prior studies that use public data. First, since boards’ responsibilities are wide-ranging, more holistic...  View Details
      Keywords: Boards Of Directors; Corporate Governance; Governing and Advisory Boards; Performance Effectiveness; Perception
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      Cheng, J. Yo-Jud, Boris Groysberg, Paul M. Healy, and Rajesh Vijayaraghavan. "Directors' Perceptions of Board Effectiveness and Internal Operations." Management Science 67, no. 10 (October 2021): 6399–6420.
      • September–October 2021
      • Article

      Frontiers: Can an AI Algorithm Mitigate Racial Economic Inequality? An Analysis in the Context of Airbnb

      By: Shunyuan Zhang, Nitin Mehta, Param Singh and Kannan Srinivasan
      We study the effect of Airbnb’s smart-pricing algorithm on the racial disparity in the daily revenue earned by Airbnb hosts. Our empirical strategy exploits Airbnb’s introduction of the algorithm and its voluntary adoption by hosts as a quasi-natural experiment. Among...  View Details
      Keywords: Smart Pricing; Pricing Algorithm; Machine Bias; Discrimination; Racial Disparity; Social Inequality; Airbnb Revenue; Revenue; Race; Equality and Inequality; Prejudice and Bias; Price; Mathematical Methods; Accommodations Industry
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      Zhang, Shunyuan, Nitin Mehta, Param Singh, and Kannan Srinivasan. "Frontiers: Can an AI Algorithm Mitigate Racial Economic Inequality? An Analysis in the Context of Airbnb." Marketing Science 40, no. 5 (September–October 2021): 813–820.
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