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  • 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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  • 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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  • March 2022
  • Module Note

Linear Regression
By: Iavor I. Bojinov, Michael Parzen and Paul J. 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; Mathematical Methods; Data and Data Sets
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  • March 2022
  • Module Note

Statistical Inference
By: Iavor I. Bojinov, Michael Parzen and Paul J. 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 Methods; Data and Data Sets
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  • 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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  • 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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  • 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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  • 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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  • 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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  • 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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  • 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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  • 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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  • September 15, 2021
  • Article

Improving Deconvolution Methods in Biology Through Open Innovation Competitions: An Application to the Connectivity Map
By: Andrea Blasco, Ted Natoli, Michael G. Endres, Rinat A. Sergeev, Steven Randazzo, Jin Hyun Paik, N.J. Maximilian Macaluso, Rajiv Narayan, Xiaodong Lu, David Peck, Karim R. Lakhani and Aravind Subramanian
A recurring problem in biomedical research is how to isolate signals of distinct populations (cell types, tissues, and genes) from composite measures obtained by a single analyte or sensor. Existing computational deconvolution approaches work well in many specific...  View Details
Keywords: Deconvolution; Methods; Open Innovation Competition; Genomics; Research; Innovation and Invention
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  • September 2021
  • Article

Diagnostic Bubbles
By: Pedro Bordalo, Nicola Gennaioli, Spencer Yongwook Kwon and Andrei Shleifer
We introduce diagnostic expectations into a standard setting of price formation in which investors learn about the fundamental value of an asset and trade it. We study the interaction of diagnostic expectations with two well-known mechanisms: learning from prices and...  View Details
Keywords: Bubble; Speculation; Diagnostic Expectations; Price Bubble; Mathematical Methods
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  • September 2021
  • Article

Oh's 8-Universality Criterion Is Unique
By: Scott Duke Kominers
Using the methods developed for the proof that the 2-universality criterion is unique, we partially characterize criteria for the n-universality of positive-definite integer-matrix quadratic forms. We then obtain the uniqueness of Oh’s 8-universality criterion as an...  View Details
Keywords: N-universal Lattice; 8-universal Lattice; Universality Criteria; Quadratic Forms; Additively Indecomposable; Mathematical Methods
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  • Fall 2021
  • Article

When to Go and How to Go? Founder and Leader Transitions in Private Equity Firms
By: Josh Lerner and Diana Noble
Leadership transition in private equity firms is an understudied field, despite the important, albeit controversial, role such firms play in developed economies. We analyzed 260 firms in an empirical study, supplemented by qualitative interviews with a small sample of...  View Details
Keywords: Leadership Transition; Private Equity; Leadership; Management Succession; Analysis
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  • August 2021
  • Article

Crowdsourcing Memories: Mixed Methods Research by Cultural Insiders-Epistemological Outsiders
By: Tarun Khanna, Karim R. Lakhani, Shubhangi Bhadada, Nabil Khan, Saba Kohli Davé, Rasim Alam and Meena Hewett
This paper examines the role that the two lead authors’ personal connections played in the research methodology and data collection for the Partition Stories project—a mixed-methods approach to revisiting the much-studied historical trauma of the Partition of British...  View Details
Keywords: Crowdsourcing; Mixed Methods Research; Oral History; History; Research
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  • August 2021
  • Article

Crowdsourcing Memories: Mixed Methods Research by Cultural Insiders-Epistemological Outsiders
By: Tarun Khanna, Karim R. Lakhani, Shubhangi Bhadada, Nabil Khan, Saba Kohli Davé, Rasim Alam and Meena Hewett
This paper examines the role that the two lead authors’ personal connections played in the research methodology and data collection for the Partition Stories Project—a mixed-methods approach to revisiting the much-studied historical trauma of the Partition of British...  View Details
Keywords: Mixed Methods; Insider-outsiders; Myth Of Informed Objectivity; Hybrid Research; Oral Narratives; Research; Analysis; India
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  • August 2021
  • Article

Multiple Imputation Using Gaussian Copulas
By: F.M. Hollenbach, I. Bojinov, S. Minhas, N.W. Metternich, M.D. Ward and A. Volfovsky
Missing observations are pervasive throughout empirical research, especially in the social sciences. Despite multiple approaches to dealing adequately with missing data, many scholars still fail to address this vital issue. In this paper, we present a simple-to-use...  View Details
Keywords: Missing Data; Bayesian Statistics; Imputation; Categorical Data; Estimation
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  • August 2021
  • Article

The Undervalued Power of Self-relevant Research: The Case of Researching Retirement While Retiring
By: Teresa M. Amabile and Douglas T. (Tim) Hall
For decades, training in management research has emphasized objectivity, typically viewed as an arm’s length distance between the topic of the research and the interests of the researcher. This emphasis has led most scholars to avoid research topics of deep personal...  View Details
Keywords: Qualitative Research Methods; Case Research Methods; Organizational Behavior; Careers; Career Changes And Transitions; Self-relevant Research; Research; Personal Development and Career; Transition; Identity; Retirement
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