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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...
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Keywords:
Difference In Differences;
Staggered Difference-in-differences Designs;
Generalized Difference-in-differences;
Dynamic Treatment Effects;
Mathematical Methods
Baker, Andrew C., David F. Larcker, and Charles C.Y. Wang. "How Much Should We Trust Staggered Difference-In-Differences Estimates?" Journal of Financial Economics 144, no. 2 (May 2022): 370–395. (Editor's Choice, May 2022.)
- 2021
- Working Paper
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
Baker, Andrew C., David F. Larcker, and Charles C.Y. Wang. "How Much Should We Trust Staggered Difference-In-Differences Estimates?" European Corporate Governance Institute Finance Working Paper, No. 736/2021, February 2021. (Harvard Business School Working Paper, No. 21-112, April 2021.)
- 2021
- Working Paper
Crisis Interventions in Corporate Insolvency
By: Samuel Antill and Christopher Clayton
We model the optimal resolution of insolvent firms in general equilibrium. Absent externalities, the optimal corporate-insolvency system encourages lending by letting banks assign liquidations ex-post. We show that a social planner optimally intervenes in such a system...
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Keywords:
Insolvent Firms;
Government Intervention;
Liquidation;
Econometric Models;
Insolvency and Bankruptcy;
Governance;
Policy
Antill, Samuel, and Christopher Clayton. "Crisis Interventions in Corporate Insolvency." Working Paper, February 2021.
- 2021
- Working Paper
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed...
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Keywords:
Machine Learning;
Econometric Analysis;
Instrumental Variable;
Random Forest;
Causal Inference;
Analysis;
Theory;
Measurement and Metrics;
Performance Consistency
Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem." Working Paper, 2021. (3rd Round Revision.)
- January 2021
- Article
A Model of Relative Thinking
By: Benjamin Bushong, Matthew Rabin and Joshua Schwartzstein
Fixed differences loom smaller when compared to large differences. We propose a model of relative thinking where a person weighs a given change along a consumption dimension by less when it is compared to bigger changes along that dimension. In deterministic settings,...
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Bushong, Benjamin, Matthew Rabin, and Joshua Schwartzstein. "A Model of Relative Thinking." Review of Economic Studies 88, no. 1 (January 2021): 162–191.
- 2021
- Working Paper
Real Credit Cycles
By: Pedro Bordalo, Nicola Gennaioli, Andrei Shleifer and Stephen J. Terry
We incorporate diagnostic expectations, a psychologically founded model of overreaction to news, into a workhorse business cycle model with heterogeneous firms and risky debt. A realistic degree of diagnosticity, estimated from the forecast errors of managers of U.S....
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Bordalo, Pedro, Nicola Gennaioli, Andrei Shleifer, and Stephen J. Terry. "Real Credit Cycles." NBER Working Paper Series, No. 28416, January 2021.
- November 2020
- Article
Taxation in Matching Markets
By: Arnaud Dupuy, Alfred Galichon, Sonia Jaffe and Scott Duke Kominers
We analyze the effects of taxation in two-sided matching markets, i.e., markets in which all agents have heterogeneous preferences over potential partners. In matching markets, taxes can generate inefficiency on the allocative margin by changing who is matched to whom,...
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Dupuy, Arnaud, Alfred Galichon, Sonia Jaffe, and Scott Duke Kominers. "Taxation in Matching Markets." International Economic Review 61, no. 4 (November 2020): 1591–1634.
- Fall 2020
- Article
Business Credit Programs in the Pandemic Era
By: Samuel G. Hanson, Jeremy C. Stein, Adi Sunderam and Eric Zwick
We develop a pair of models that speak to the goals and design of the sort of business-lending and corporate-bond purchase programs that have been introduced by governments in response to the ongoing COVID-19 pandemic. An overarching theme is that, in contrast to the...
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Keywords:
COVID-19;
Business Lending;
Government Intervention;
Econometric Models;
Health Pandemics;
Credit;
Governance;
Policy
Hanson, Samuel G., Jeremy C. Stein, Adi Sunderam, and Eric Zwick. "Business Credit Programs in the Pandemic Era." Brookings Papers on Economic Activity (Fall 2020).
- August 2020 (Revised September 2020)
- Technical Note
Assessing Prediction Accuracy of Machine Learning Models
The note introduces a variety of methods to assess the accuracy of machine learning prediction models. The note begins by briefly introducing machine learning, overfitting, training versus test datasets, and cross validation. The following accuracy metrics and tools...
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Keywords:
Machine Learning;
Statistics;
Econometric Analyses;
Experimental Methods;
Data Analysis;
Data Analytics;
Forecasting and Prediction;
Analytics and Data Science;
Analysis;
Mathematical Methods
Toffel, Michael W., Natalie Epstein, Kris Ferreira, and Yael Grushka-Cockayne. "Assessing Prediction Accuracy of Machine Learning Models." Harvard Business School Technical Note 621-045, August 2020. (Revised September 2020.)
- August 2020
- Technical Note
Comparing Two Groups: Sampling and t-Testing
This note describes sampling and t-tests, two fundamental statistical concepts.
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Keywords:
Statistics;
Econometric Analyses;
Experimental Methods;
Data Analysis;
Data Analytics;
Analytics and Data Science;
Analysis;
Surveys;
Mathematical Methods
Bojinov, Iavor I., Chiara Farronato, Yael Grushka-Cockayne, Willy C. Shih, and Michael W. Toffel. "Comparing Two Groups: Sampling and t-Testing." Harvard Business School Technical Note 621-044, August 2020.
- 2020
- Working Paper
Optimal Illiquidity
By: John Beshears, James J. Choi, Christopher Clayton, Christopher Harris, David Laibson and Brigitte C. Madrian
We calculate the socially optimal level of illiquidity in an economy populated by households with taste shocks and present bias (Amador, Werning, and Angeletos 2006). The government chooses mandatory contributions to respective spending/savings accounts, each with a...
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Beshears, John, James J. Choi, Christopher Clayton, Christopher Harris, David Laibson, and Brigitte C. Madrian. "Optimal Illiquidity." NBER Working Paper Series, No. 27459, July 2020.
- 2020
- Article
A Practical Approach to Sales Compensation: What Do We Know Now? What Should We Know in the Future?
By: Doug J. Chung, Byungyeon Kim and Niladri B. Syam
Personal selling represents one of the most important elements in the marketing mix, and appropriate management of the sales force is vital to achieving the organization’s objectives. Among the various instruments of sales management, compensation plays a pivotal role...
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Keywords:
Sales Compensation;
Sales Management;
Sales Strategy;
Principal-agent Theory;
Structural Econometrics;
Field Experiments;
Machine Learning;
Artificial Intelligence;
Salesforce Management;
Compensation and Benefits;
Motivation and Incentives;
AI and Machine Learning
Chung, Doug J., Byungyeon Kim, and Niladri B. Syam. "A Practical Approach to Sales Compensation: What Do We Know Now? What Should We Know in the Future?" Foundations and Trends® in Marketing 14, no. 1 (2020): 1–52.
- June 2020
- Article
How Scheduling Can Bias Quality Assessment: Evidence from Food Safety Inspections
By: Maria Ibanez and Michael W. Toffel
Accuracy and consistency are critical for inspections to be an effective, fair, and useful tool for assessing risks, quality, and suppliers—and for making decisions based on those assessments. We examine how inspector schedules could introduce bias that erodes...
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Keywords:
Assessment;
Bias;
Inspection;
Scheduling;
Econometric Analysis;
Empirical Research;
Regulation;
Health;
Food;
Safety;
Quality;
Performance Consistency;
Governing Rules, Regulations, and Reforms
Ibanez, Maria, and Michael W. Toffel. "How Scheduling Can Bias Quality Assessment: Evidence from Food Safety Inspections." Management Science 66, no. 6 (June 2020): 2396–2416. (Revised February 2019. Featured in Harvard Business Review, Forbes, Food Safety Magazine, Food Safety News, and KelloggInsight. (2020 MSOM Responsible Research Finalist.))
- 2020
- Working Paper
A General Theory of Identification
By: Iavor Bojinov and Guillaume Basse
What does it mean to say that a quantity is identifiable from the data? Statisticians seem to agree
on a definition in the context of parametric statistical models — roughly, a parameter θ in a model
P = {Pθ : θ ∈ Θ} is identifiable if the mapping θ 7→ Pθ is...
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Bojinov, Iavor, and Guillaume Basse. "A General Theory of Identification." Harvard Business School Working Paper, No. 20-086, February 2020.
- 2018
- Chapter
Competing Interests
By: Joel Goh
Book Abstract: The editors, aided by a team of internationally acclaimed experts, have curated this timely volume to help newcomers and seasoned researchers alike to rapidly comprehend a diverse set of thrusts and tools in this rapidly growing cross-disciplinary field....
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Goh, Joel. "Competing Interests." Chap. 4 in Handbook of Healthcare Analytics: Theoretical Minimum for Conducting 21st Century Research on Healthcare Operations, edited by Tinglong Dai and Sridhar Tayur, 51–78. John Wiley & Sons, 2018.
- 2018
- Working Paper
Detecting Anomalies: The Relevance and Power of Standard Asset Pricing Tests
By: Malcolm Baker, Patrick Luo and Ryan Taliaferro
The two standard approaches for identifying capital market anomalies are cross-sectional coefficient tests, in the spirit of Fama and MacBeth (1973), and time-series intercept tests, in the spirit of Jensen (1968). A new signal can pass the first test, which we label a...
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Keywords:
Investment Management;
Anomalies;
Portfolio Construction;
Transaction Costs;
Investment;
Management;
Asset Pricing;
Market Transactions;
Cost
Baker, Malcolm, Patrick Luo, and Ryan Taliaferro. "Detecting Anomalies: The Relevance and Power of Standard Asset Pricing Tests." Working Paper, July 2018.
- 2018
- Working Paper
How Scheduling Can Bias Quality Assessment: Evidence from Food Safety Inspections
By: Maria Ibanez and Michael W. Toffel
Many production processes are subject to inspection to ensure they meet quality, safety, and environmental standards imposed by companies and regulators. Inspection accuracy is critical to inspections being a useful input to assessing risks, allocating quality...
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Keywords:
Assessment;
Bias;
Inspection;
Scheduling;
Econometric Analysis;
Empirical Research;
Regulation;
Health;
Food;
Safety;
Quality;
Performance Consistency;
Performance Evaluation;
Food and Beverage Industry;
Service Industry
Ibanez, Maria, and Michael W. Toffel. "How Scheduling Can Bias Quality Assessment: Evidence from Food Safety Inspections." Harvard Business School Working Paper, No. 17-090, April 2017. (Revised October 2018. Formerly titled "Assessing the Quality of Quality Assessment: The Role of Scheduling". Featured in Forbes, Food Safety Magazine, and Food Safety News.)
- Article
Pricing and Production Flexibility: An Empirical Analysis of the U.S. Automotive Industry
By: Antonio Moreno and Christian Terwiesch
We use a detailed data set from the U.S. auto industry spanning from 2002 to 2009 and a variety of econometric methods to characterize the relationship between the availability of production mix flexibility and firms’ use of responsive pricing. We find that production...
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Keywords:
Empirical Operations Management;
Flexibility;
Pricing;
Automotive Industry;
Production;
Price;
Management;
Analysis;
Auto Industry;
United States
Moreno, Antonio, and Christian Terwiesch. "Pricing and Production Flexibility: An Empirical Analysis of the U.S. Automotive Industry." Manufacturing & Service Operations Management 17, no. 4 (Fall 2015): 428–444.
- 2020
- Working Paper
Should Firms Move Talent from the Geographic Periphery to Hubs? A Strategic Human Capital Perspective
By: Prithwiraj Choudhury, Victoria Sevcenko and Tarun Khanna
A longstanding literature holds that firms should hire and move talent from the geographic periphery to hubs as a means to create value from human capital. They do so, however, at the risk of losing the worker to rivals located in the same geographic hub,...
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Keywords:
Geographic Location;
Selection and Staffing;
Employment;
Residency;
Technology Industry;
India
Choudhury, Prithwiraj, Victoria Sevcenko, and Tarun Khanna. "Should Firms Move Talent from the Geographic Periphery to Hubs? A Strategic Human Capital Perspective." Harvard Business School Working Paper, No. 14-080, February 2014. (Revised August 2020.)
- 2014
- Chapter
Schumpeter's Plea: Historical Reasoning in Entrepreneurial Theory and Research
By: G. Jones and R. Daniel Wadhwani
This chapter draws on theories of entrepreneurship and history to explore the ways in which historical processes play an integral role in entrepreneurship. It builds off the plea by Joseph Schumpeter for an active exchange between historical approaches and theories of...
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Jones, G., and R. Daniel Wadhwani. "Schumpeter's Plea: Historical Reasoning in Entrepreneurial Theory and Research." Chap. 8 in Organizations in Time: History, Theory, Methods, edited by Marcelo Bucheli and R. Daniel Wadhwani, 192–216. New York: Oxford University Press, 2014.