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- January 2023
- Article
Firm-Induced Migration Paths and Strategic Human-Capital Outcomes
By: Prithwiraj (Raj) Choudhury, Tarun Khanna and Victoria Sevcenko
Firm-induced migration typically entails firms relocating workers to fill value-creating positions at destination locations. But such relocated workers are often exposed to external employment opportunities at their destinations, possibly triggering turnover. We... View Details
- October–December 2022
- Article
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... View Details
- Article
How Much Should We Trust Staggered Difference-In-Differences Estimates?
By: Andrew C. Baker, David F. Larcker and Charles C.Y. Wang
We explain when and how staggered difference-in-differences regression estimators, commonly applied to assess the impact of policy changes, are biased. These biases are likely to be relevant for a large portion of research settings in finance, accounting, and law that... View Details
- 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
- 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
- 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,... View Details
- 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.... View Details
- 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,... View Details
- 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... View Details
- 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... View Details
- August 2020
- Technical Note
Comparing Two Groups: Sampling and t-Testing
This note describes sampling and t-tests, two fundamental statistical concepts. View Details
- 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... View Details
- 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 injective.... View Details
- 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... View Details
- 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... View Details
- 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... View Details
- 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,... View Details
- 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... View Details
- 2011
- Article
How Should the Graduate Economics Core be Changed?
By: Vincent Pons, Jose Miguel Abito, Katarina Borovickova, Hays Golden, Jacob Goldin, Matthew A. Masten, Miguel Morin, Alexander Poirier, Israel Romem, Tyler Williams and Chamna Yoon
The authors present suggestions by graduate students from a range of economics departments for improving the first-year core sequence in economics. The students identified a number of elements that should be added to the core: more training in building microeconomic... View Details
- 2008
- Chapter
Allocating Marketing Resources
By: Sunil Gupta and Thomas J. Steenburgh
Companies spend billions of dollars on marketing every year because it is essential to organic growth. Given these large investments, marketing managers have the responsibility to optimally allocate resources and to demonstrate that their investments generate... View Details