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  • 2022
  • Working Paper

Measuring the Tolerance of the State: Theory and Application to Protest
By: Veli Andirin, Yusuf Neggers, Mehdi Shadmehr and Jesse M. Shapiro
We develop a measure of a regime's tolerance for an action by its citizens. We ground our measure in an economic model and apply it to the setting of political protest. In the model, a regime anticipating a protest can take a costly action to repress it. We define the...  View Details
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  • 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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  • Article

Act Like a Scientist: Great Leaders Challenge Assumptions, Run Experiments, and Follow the Evidence
By: Stefan Thomke and Gary W. Loveman
Though they’ve been warned for decades about the dangers of overrelying on gut instinct and personal experience, managers keep failing to critically examine—much less challenge—the ideas their decisions are based on. To correct this problem they need to think and act...  View Details
Keywords: Innovation and Management; Decision Making; Science; Leadership Style
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  • 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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  • 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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  • 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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  • 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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  • 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 (Revised 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; Analytics and Data Science
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  • March 2022 (Revised 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; Analytics and Data Science
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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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  • January 2022
  • Technical Note

Ethical Analysis: Deception
By: Nien-hê Hsieh and Christopher Diak
Information asymmetry is pervasive in business and can often confer great advantage. This note distinguishes forms of deceptive behavior in the face of information asymmetry and aims to help students analyze their impermissibility. The note also introduces students to...  View Details
Keywords: Ethics; Analysis; Balance and Stability
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  • 2022
  • Article

Improving Efficiency and Reducing Costs of MRI-Guided Prostate Brachytherapy Using Time-Driven Activity-Based Costing
By: Nikhil G. Thaker, Rajat J. Kudchadker, James R. Incalcaterra, Tharakeswara K. Bathala, Robert S. Kaplan, Ankit Agarwal, Deborah A. Kuban, Benjamin D. Frank, Prajnan Das, Thomas W. Feeley and Steven J. Frank
Integrated quality improvement (QI) and cost reduction strategies can help increase value in cancer care. We applied standard QI and TDABC methods to improve workflow efficiency and reduce costs for MRI-guided prostate brachytherapy. We constructed process maps,...  View Details
Keywords: Brachytherapy; Quality Improvement; Prostate; Time-Driven Activity-Based Costing; Cost Accounting; Health Care and Treatment; Performance Efficiency; Health Industry
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  • Article

Pattern Detection in the Activation Space for Identifying Synthesized Content
By: Celia Cintas, Skyler Speakman, Girmaw Abebe Tadesse, Victor Akinwande, Edward McFowland III and Komminist Weldemariam
Generative Adversarial Networks (GANs) have recently achieved unprecedented success in photo-realistic image synthesis from low-dimensional random noise. The ability to synthesize high-quality content at a large scale brings potential risks as the generated samples may...  View Details
Keywords: Subset Scanning; Generative Models; Synthetic Content Detection
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  • 2022
  • Working Paper

Understanding Rural Households' Time Use in a Developing Setting: Validating a Low-Cost Time Use Module
By: Erica M Field, Rohini Pande, Natalia Rigol, Simone G. Schaner, Elena M. Stacy and Charity M. Troyer Moore
Time use data facilitate deeper understanding of individual labor supply choices, especially for women, who are more likely to engage in unpaid care and home production. However, traditional time use data collection methods are time-consuming, expensive and susceptible...  View Details
Keywords: Time Use; Household; Rural Scope; Developing Countries and Economies; Time Management; Analytics and Data Science; Surveys
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  • 2021
  • Working Paper

Caccia Selvaggia: Myth, Rites, and the Right in Carlo Ginzburg's Storia notturna
By: Robert Fredona and Sophus A. Reinert
Carlo Ginzburg (b. 1939) is widely considered one of Europe’s leading historians. His masterpiece Storia notturna (Turin: Einaudi, 1989), widely praised for its extraordinary erudition and creativity, is now over three decades old but it continues to inspire...  View Details
Keywords: Mythology; Culture; Political Doctrine; History; Government and Politics; Society
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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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