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- June 2024
- Article
Redistributive Allocation Mechanisms
By: Mohammad Akbarpour, Piotr Dworczak and Scott Duke Kominers
Many scarce public resources are allocated at below-market-clearing prices, and sometimes for free. Such "non-market" mechanisms sacrifice some surplus, yet they can potentially improve equity. We develop a model of mechanism design with redistributive concerns. Agents... View Details
- 2024
- Working Paper
What Is Newsworthy? Theory and Evidence
By: Luis Armona, Matthew Gentzkow, Emir Kamenica and Jesse M. Shapiro
We study newsworthiness in theory and practice. We focus on situations in which a news outlet observes the realization of a state of the world and must decide whether to report the realization to a consumer who pays an opportunity cost to consume the report. The... View Details
- 2023
- Working Paper
An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits
By: Biyonka Liang and Iavor I. Bojinov
Typically, multi-armed bandit (MAB) experiments are analyzed at the end of the study and thus require the analyst to specify a fixed sample size in advance. However, in many online learning applications, it is advantageous to continuously produce inference on the... View Details
- 2024
- Working Paper
Anytime-Valid Inference in Linear Models and Regression-Adjusted Causal Inference
By: Michael Lindon, Dae Woong Ham, Martin Tingley and Iavor I. Bojinov
Linear regression adjustment is commonly used to analyze randomized controlled experiments due to its efficiency and robustness against model misspecification. Current testing and interval estimation procedures leverage the asymptotic distribution of such estimators to... View Details
- 2023
- Working Paper
Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development
By: Daniel Yue, Paul Hamilton and Iavor Bojinov
Predictive model development is understudied despite its centrality in modern artificial
intelligence and machine learning business applications. Although prior discussions
highlight advances in methods (along the dimensions of data, computing power, and
algorithms)... View Details
Keywords: Analytics and Data Science
- 2022
- Working Paper
Stories, Statistics and Memory
By: Thomas Graeber, Christopher Roth and Florian Zimmermann
For most decisions, we rely on information encountered over the course of days,
months or years. We consume this information in various forms, including abstract
summaries of multiple data points – statistics – and contextualized anecdotes about
individual instances... View Details
- September 2022
- Article
Tone at the Bottom: Measuring Corporate Misconduct Risk from the Text of Employee Reviews
By: Dennis W. Campbell and Ruidi Shang
This paper examines whether information extracted via text-based statistical methods applied to employee reviews left on the website Glassdoor.com can be used to develop indicators of corporate misconduct risk. We argue that inside information on the incidence of... View Details
- 2022
- Article
Data Poisoning Attacks on Off-Policy Evaluation Methods
By: Elita Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin and Himabindu Lakkaraju
Off-policy Evaluation (OPE) methods are a crucial tool for evaluating policies in high-stakes domains such as healthcare, where exploration is often infeasible, unethical, or expensive. However, the extent to which such methods can be trusted under adversarial threats... View Details
- 2022
- Working Paper
Causal Inference During A Pandemic: Evidence on the Effectiveness of Nebulized Ibuprofen as an Unproven Treatment for COVID-19 in Argentina
By: Sebastian Calonico, Rafael Di Tella and Juan Cruz Lopez Del Valle
Many medical decisions during the pandemic were made without the support of causal evidence obtained in clinical trials. We study the case of nebulized ibuprofen (NaIHS), a drug that was extensively used on COVID-19 patients in Argentina amidst wild claims about its... View Details
- Article
Do the Right Firms Survive Bankruptcy?
By: Samuel Antill
In U.S. Chapter 11 bankruptcy cases, firms are either reorganized, acquired, or liquidated. I show that decisions to liquidate often reduce creditor recovery, costing creditors billions of dollars every year. I exploit the within-district random assignment of... View Details
- Article
Decreases In Readmissions Credited to Medicare's Program to Reduce Hospital Readmissions Have Been Overstated
By: Christopher Ody, Lucy Msall, Leemore S. Dafny, David Grabowski and David Cutler
Medicare’s Hospital Readmissions Reduction Program (HRRP) has been credited with lowering risk-adjusted readmission rates for targeted conditions at general acute care hospitals. However, these reductions appear to be illusory or overstated. This is because a... View Details
- January 2019
- Article
Increasing the Electoral Participation of Immigrants: Experimental Evidence from France
By: Vincent Pons and Guillaume Liegey
Improving the political participation of immigrants could advance their interests and foster their integration into receiving countries. In this study, 23,800 citizens were randomly assigned to receive visits from political activists during the lead-up to the 2010... View Details
- 2018
- Working Paper
Corporate Tax Cuts Increase Income Inequality
By: Suresh Nallareddy, Ethan Rouen and Juan Carlos Suárez Serrato
This paper studies the effects of corporate tax changes on income inequality. Using state corporate tax rate changes as a setting, we show that cutting state corporate tax rates leads to increases in income inequality. This result is robust to using regression and... View Details
- September 2017
- Article
The Real Effects of Capital Controls: Firm-Level Evidence from a Policy Experiment
By: Laura Alfaro, Anusha Chari and Fabio Kanczuk
Emerging-market governments adopted capital control taxes to manage the massive surge in foreign capital inflows in the aftermath of the global financial crisis. Theory suggests that the imposition of capital controls can drive up the cost of capital and curb... View Details
- July 31, 2017
- Article
A Commitment Contract to Achieve Virologic Suppression in Poorly Adherent Patients with HIV/AIDS
By: Marcella Alsan, John Beshears, Wendy S. Armstrong, James J. Choi, Brigitte C. Madrian, Minh Ly T. Nguyen, Carlos Del Rio, David Laibson and Vincent C. Marconi
Objective: Assess whether a commitment contract informed by behavioral economics leads to persistent virologic suppression among HIV-positive patients with poor antiretroviral therapy (ART) adherence.
Design: Single-center pilot randomized clinical trial and a... View Details
- May 2017
- Article
Agent-based Modeling: A Guide for Social Psychologists
By: Joshua Conrad Jackson, David Rand, Kevin Lewis, Michael I. Norton and Kurt Gray
Agent-based modeling is a longstanding but underused method that allows researchers to simulate artificial worlds for hypothesis testing and theory building. Agent-based models (ABMs) offer unprecedented control and statistical power by allowing researchers to... View Details
- Fall 2016
- Article
The Impact of Supplier Inventory Service Level on Retailer Demand
By: Nathan Craig, Nicole DeHoratius and Ananth Raman
To set inventory service levels, suppliers must understand how changes in inventory service level affect demand. We build on prior research, which uses analytical models and laboratory experiments to study the impact of a supplier’s service level on demand from... View Details
- August 2016
- Article
Independent Directors' Dissent on Boards: Evidence from Listed Companies in China
By: Juan Ma and Tarun Khanna
In this paper, we examine the circumstances under which so-called "independent" directors voice their independent views on public boards in a sample of Chinese firms. First, we ask why independent directors dissent, i.e. how they justify such dissent to public... View Details
- 2015
- Chapter
Optimal Process Control of Symbolic Transfer Functions
By: Christopher Griffin and Elisabeth Paulson
Transfer function modeling is a standard technique in classical Linear Time Invariant and Statistical Process Control. The work of Box and Jenkins was seminal in developing methods for identifying parameters associated with classical (r, s, k) transfer functions.... View Details
- June 28, 2011
- Article
Using Implementation Intentions Prompts to Enhance Influenza Vaccination Rates
By: Katherine L Milkman, John Beshears, James J. Choi, David Laibson and Brigitte C. Madrian
We evaluate the results of a field experiment designed to measure the effect of prompts to form implementation intentions on realized behavioral outcomes. The outcome of interest is influenza vaccination receipt at free on-site clinics offered by a large firm to its... View Details