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- 2024
- Working Paper
Empirical Guidance: Data Processing and Analysis with Applications in Stata, R, and Python
By: Melissa Ouellet and Michael W. Toffel
This paper describes a range of best practices to compile and analyze datasets, and includes some examples in Stata, R, and Python. It is meant to serve as a reference for those getting started in econometrics, and especially those seeking to conduct data analyses in... View Details
Keywords: Empirical Methods; Empirical Operations; Statistical Methods And Machine Learning; Statistical Interferences; Research Analysts; Analytics and Data Science; Mathematical Methods
Ouellet, Melissa, and Michael W. Toffel. "Empirical Guidance: Data Processing and Analysis with Applications in Stata, R, and Python." Harvard Business School Working Paper, No. 25-010, August 2024.
- 2024
- Working Paper
The New Digital Divide
By: Mayana Pereira, Shane Greenstein, Raffaella Sadun, Prasanna Tambe, Lucia Ronchi Darre, Tammy Glazer, Allen Kim, Rahul Dodhia and Juan Lavista Ferres
We build and analyze new metrics of digital usage that leverage telemetry data collected by Microsoft during operating system updates across forty million Windows devices in U.S. households. These measures of US household digital usage are much more comprehensive than... View Details
Keywords: Mathematical Methods; Measurement and Metrics; Geographic Location; Behavior; Technology Adoption; Demographics
Pereira, Mayana, Shane Greenstein, Raffaella Sadun, Prasanna Tambe, Lucia Ronchi Darre, Tammy Glazer, Allen Kim, Rahul Dodhia, and Juan Lavista Ferres. "The New Digital Divide." NBER Working Paper Series, No. 32932, September 2024.
- July–August 2024
- Article
Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals
By: Ta-Wei Huang and Eva Ascarza
Firms are increasingly interested in developing targeted interventions for customers with the best response,
which requires identifying differences in customer sensitivity, typically through the conditional average treatment
effect (CATE) estimation. In theory, to... View Details
Keywords: Long-run Targeting; Heterogeneous Treatment Effect; Statistical Surrogacy; Customer Churn; Field Experiments; Consumer Behavior; Customer Focus and Relationships; AI and Machine Learning; Marketing Strategy
Huang, Ta-Wei, and Eva Ascarza. "Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals." Marketing Science 43, no. 4 (July–August 2024): 863–884.
- 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
Akbarpour, Mohammad, Piotr Dworczak, and Scott Duke Kominers. "Redistributive Allocation Mechanisms." Journal of Political Economy 132, no. 6 (June 2024): 1831–1875. (Authors' names are in certified random order.)
- 2024
- Working Paper
Immigrant Entrepreneurship: New Estimates and a Research Agenda
By: Saheel Chodavadia, Sari Pekkala Kerr, William R. Kerr and Louis Maiden
Immigrants contribute disproportionately to entrepreneurship in many countries, accounting for a quarter of new employer businesses in the US. We review recent research on the measurement of immigrant entrepreneurship, the traits of immigrant founders, their economic... View Details
Keywords: Immigrant Employment; Immigration; Entrepreneurship; Demographics; Innovation and Invention
Chodavadia, Saheel, Sari Pekkala Kerr, William R. Kerr, and Louis Maiden. "Immigrant Entrepreneurship: New Estimates and a Research Agenda." Harvard Business School Working Paper, No. 24-068, April 2024.
- 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
Armona, Luis, Matthew Gentzkow, Emir Kamenica, and Jesse M. Shapiro. "What Is Newsworthy? Theory and Evidence." NBER Working Paper Series, No. 32512, May 2024.
- 2024
- Working Paper
The Effects of Medical Debt Relief: Evidence from Two Randomized Experiments
By: Raymond Kluender, Neale Mahoney, Francis Wong and Wesley Yin
Two in five Americans have medical debt, nearly half of whom owe at least $2,500. Concerned by this burden, governments and private donors have undertaken large, high-profile efforts to relieve medical debt. We partnered with RIP Medical Debt to conduct two randomized... View Details
Kluender, Raymond, Neale Mahoney, Francis Wong, and Wesley Yin. "The Effects of Medical Debt Relief: Evidence from Two Randomized Experiments." NBER Working Paper Series, No. 32315, April 2024.
- 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
Liang, Biyonka, and Iavor I. Bojinov. "An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits." Harvard Business School Working Paper, No. 24-057, March 2024.
- 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
Lindon, Michael, Dae Woong Ham, Martin Tingley, and Iavor I. Bojinov. "Anytime-Valid Inference in Linear Models and Regression-Adjusted Causal Inference." Harvard Business School Working Paper, No. 24-060, March 2024.
- 2023
- Working Paper
Design-Based Inference for Multi-arm Bandits
By: Dae Woong Ham, Iavor I. Bojinov, Michael Lindon and Martin Tingley
Multi-arm bandits are gaining popularity as they enable real-world sequential decision-making across application areas, including clinical trials, recommender systems, and online decision-making. Consequently, there is an increased desire to use the available... View Details
Ham, Dae Woong, Iavor I. Bojinov, Michael Lindon, and Martin Tingley. "Design-Based Inference for Multi-arm Bandits." Harvard Business School Working Paper, No. 24-056, March 2024.
- March 2024
- Article
Human Capital Affects Religious Identity: Causal Evidence from Kenya
By: Livia Alfonsi, Michal Bauer, Julie Chytilová and Edward Miguel
We study how human capital and economic conditions causally affect the choice of religious denomination. We utilize a longitudinal dataset monitoring the religious history of more than 5,000 Kenyans over 20 years, in tandem with a randomized experiment (deworming) that... View Details
Alfonsi, Livia, Michal Bauer, Julie Chytilová, and Edward Miguel. "Human Capital Affects Religious Identity: Causal Evidence from Kenya." Art. 103215. Journal of Development Economics 167 (March 2024).
- February 2024
- Article
Fifty Shades of QE: Robust Evidence
By: Brian Fabo, Marina Jančoková, Elisabeth Kempf and Ľuboš Pástor
Fabo et al. (2021) show that papers written by central bank researchers find quantitative easing (QE) to be more effective than papers written by academics. Weale and Wieladek (2022) show that a subset of these results lose statistical significance when OLS regressions... View Details
Keywords: Quantitative Easing; Research; Mathematical Methods; Perception; Banks and Banking; Body of Literature
Fabo, Brian, Marina Jančoková, Elisabeth Kempf, and Ľuboš Pástor. "Fifty Shades of QE: Robust Evidence." Art. 107065. Journal of Banking & Finance 159 (February 2024).
- January 2024
- Article
Subset Scanning for Multi-Trait Analysis Using GWAS Summary Statistics
By: Rui Cao, Evan Olawsky, Edward McFowland III, Erin Marcotte, Logan Spector and Tianzhong Yang
Multi-trait analysis has been shown to have greater statistical power than single-trait analysis. Most of the existing multi-trait analysis methods only work with a limited number of traits and usually prioritize high statistical power over identifying relevant traits,... View Details
Cao, Rui, Evan Olawsky, Edward McFowland III, Erin Marcotte, Logan Spector, and Tianzhong Yang. "Subset Scanning for Multi-Trait Analysis Using GWAS Summary Statistics." Bioinformatics 40, no. 1 (January 2024).
- 2023
- Article
MoPe: Model Perturbation-based Privacy Attacks on Language Models
By: Marvin Li, Jason Wang, Jeffrey Wang and Seth Neel
Recent work has shown that Large Language Models (LLMs) can unintentionally leak sensitive information present in their training data. In this paper, we present Model Perturbations (MoPe), a new method to identify with high confidence if a given text is in the training... View Details
Li, Marvin, Jason Wang, Jeffrey Wang, and Seth Neel. "MoPe: Model Perturbation-based Privacy Attacks on Language Models." Proceedings of the Conference on Empirical Methods in Natural Language Processing (2023): 13647–13660.
- 2023
- Working Paper
How People Use Statistics
By: Pedro Bordalo, John J. Conlon, Nicola Gennaioli, Spencer Yongwook Kwon and Andrei Shleifer
We document two new facts about the distributions of answers in famous statistical problems: they are i) multi-modal and ii) unstable with respect to irrelevant changes in the problem. We offer a model in which, when solving a problem, people represent each hypothesis... View Details
Bordalo, Pedro, John J. Conlon, Nicola Gennaioli, Spencer Yongwook Kwon, and Andrei Shleifer. "How People Use Statistics." NBER Working Paper Series, No. 31631, August 2023.
- June 2023
- Simulation
Artea Dashboard and Targeting Policy Evaluation
By: Ayelet Israeli and Eva Ascarza
Companies deploy A/B experiments to gain valuable insights about their customers in order to answer strategic business problems. In marketing, A/B tests are often used to evaluate marketing interventions intended to generate incremental outcomes for the firm. The Artea... View Details
Keywords: Algorithm Bias; Algorithmic Data; Race And Ethnicity; Experimentation; Promotion; Marketing And Society; Big Data; Privacy; Data-driven Management; Data Analysis; Data Analytics; E-Commerce Strategy; Discrimination; Targeted Advertising; Targeted Policies; Pricing Algorithms; A/B Testing; Ethical Decision Making; Customer Base Analysis; Customer Heterogeneity; Coupons; Marketing; Race; Gender; Diversity; Customer Relationship Management; Marketing Communications; Advertising; Decision Making; Ethics; E-commerce; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; United States
- 2023
- Working Paper
Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness
By: Neil Menghani, Edward McFowland III and Daniel B. Neill
In this paper, we develop a new criterion, "insufficiently justified disparate impact" (IJDI), for assessing whether recommendations (binarized predictions) made by an algorithmic decision support tool are fair. Our novel, utility-based IJDI criterion evaluates false... View Details
Menghani, Neil, Edward McFowland III, and Daniel B. Neill. "Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness." Working Paper, June 2023.
- 2023
- Working Paper
Design-Based Confidence Sequences: A General Approach to Risk Mitigation in Online Experimentation
By: Dae Woong Ham, Michael Lindon, Martin Tingley and Iavor Bojinov
Randomized experiments have become the standard method for companies to evaluate the performance of new products or services. In addition to augmenting managers’ decision-making, experimentation mitigates risk by limiting the proportion of customers exposed to... View Details
Keywords: Performance Evaluation; Research and Development; Analytics and Data Science; Consumer Behavior
Ham, Dae Woong, Michael Lindon, Martin Tingley, and Iavor Bojinov. "Design-Based Confidence Sequences: A General Approach to Risk Mitigation in Online Experimentation." Harvard Business School Working Paper, No. 23-070, May 2023.
- 2023
- Working Paper
PRIMO: Private Regression in Multiple Outcomes
By: Seth Neel
We introduce a new differentially private regression setting we call Private Regression in Multiple Outcomes (PRIMO), inspired the common situation where a data analyst wants to perform a set of l regressions while preserving privacy, where the covariates... View Details
Neel, Seth. "PRIMO: Private Regression in Multiple Outcomes." Working Paper, March 2023.
- 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
Yue, Daniel, Paul Hamilton, and Iavor Bojinov. "Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development." Harvard Business School Working Paper, No. 23-029, December 2022. (Revised April 2023.)