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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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  • 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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  • 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; Data and Data Sets; 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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  • Article

Counterfactual Explanations Can Be Manipulated
By: Dylan Slack, Sophie Hilgard, Himabindu Lakkaraju and Sameer Singh
Counterfactual explanations are useful for both generating recourse and auditing fairness between groups. We seek to understand whether adversaries can manipulate counterfactual explanations in an algorithmic recourse setting: if counterfactual explanations indicate...  View Details
Keywords: Machine Learning Models; Counterfactual Explanations
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  • Article

Reliable Post hoc Explanations: Modeling Uncertainty in Explainability
By: Dylan Slack, Sophie Hilgard, Sameer Singh and Himabindu Lakkaraju
As black box explanations are increasingly being employed to establish model credibility in high stakes settings, it is important to ensure that these explanations are accurate and reliable. However, prior work demonstrates that explanations generated by...  View Details
Keywords: Black Box Explanations; Bayesian Modeling; Decision Making; Risk and Uncertainty; Information Technology
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  • Article

Accounting for Climate Change
By: Robert S. Kaplan and Karthik Ramanna
Corporations are facing growing pressure—from investors, advocacy groups, politicians, and even business leaders themselves—to reduce greenhouse gas (GHG) emissions from their operations and their supply and distribution chains. About 90% of the companies in the S&P...  View Details
Keywords: Greenhouse Gas Mitigation; Social Accounting; E-liabilities; Business And The Environment; Climate Change; Corporate Social Responsibility and Impact; Environmental Sustainability
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  • 2021
  • Working Paper

Friends and Family Money: P2P Transfers and Financially Fragile Consumers
By: Tetyana Balyuk and Emily Williams
We assess the impact that real time money transfer technology has on consumer outcomes, particularly during periods of financial fragility. We do this by developing a new data set that documents use of Zelle—the most widely used P2P money transfer technology in the...  View Details
Keywords: P2P Money Transfers; Real Time Payments; Fintech; Finance; Technology; Personal Finance; Financial Condition
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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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