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    • All HBS Web  (155)
      • Faculty Publications  (40)

      Econometrics Remove Econometrics →

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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
      Keywords: Worker Relocation; Turnover; Firm-induced Migration; Smaller Towns; Employee Mobility; Geographic Mobility; Migration; Clusters; Employees; Geographic Location; Performance; Opportunities; Retention; Human Capital; Talent and Talent Management
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      Choudhury, Prithwiraj (Raj), Tarun Khanna, and Victoria Sevcenko. "Firm-Induced Migration Paths and Strategic Human-Capital Outcomes." Management Science 69, no. 1 (January 2023): 419–445.
      • 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
      Keywords: Machine Learning; Econometric Analysis; Instrumental Variable; Random Forest; Causal Inference; AI and Machine Learning; Forecasting and Prediction
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      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." INFORMS Journal on Data Science 1, no. 2 (October–December 2022): 138–155.
      • 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
      Keywords: Difference In Differences; Staggered Difference-in-differences Designs; Generalized Difference-in-differences; Dynamic Treatment Effects; Mathematical Methods
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      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.)
      • 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
      Keywords: Econometric Models; Mathematical Methods
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      Shapiro, Jesse M., and Liyang Sun. "A Linear Panel Model with Heterogeneous Coefficients and Variation in Exposure." NBER Working Paper Series, No. 29976, April 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
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      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...  View Details
      Keywords: Insolvent Firms; Government Intervention; Liquidation; Econometric Models; Insolvency and Bankruptcy; Governance; Policy
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      Antill, Samuel, and Christopher Clayton. "Crisis Interventions in Corporate Insolvency." Working Paper, February 2021.
      • 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
      Keywords: Relative Thinking; Econometric Models; Behavior; Cognition and Thinking
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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....  View Details
      Keywords: Econometric Models; Business Cycles; Credit
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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,...  View Details
      Keywords: Matching Markets; Labor Markets; Taxation; Labor; Markets
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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...  View Details
      Keywords: COVID-19; Business Lending; Government Intervention; Econometric Models; Health Pandemics; Credit; Governance; Policy
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      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

      By: Michael W. Toffel, Natalie Epstein, Kris Ferreira and Yael Grushka-Cockayne
      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
      Keywords: Machine Learning; Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Forecasting and Prediction; Analytics and Data Science; Analysis; Mathematical Methods
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      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

      By: Iavor I Bojinov, Chiara Farronato, Yael Grushka-Cockayne, Willy C. Shih and Michael W. Toffel
      This note describes sampling and t-tests, two fundamental statistical concepts.  View Details
      Keywords: Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Analytics and Data Science; Analysis; Surveys; Mathematical Methods
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      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.
      • 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
      Keywords: Assessment; Bias; Inspection; Scheduling; Econometric Analysis; Empirical Research; Regulation; Health; Food; Safety; Quality; Performance Consistency; Governing Rules, Regulations, and Reforms
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      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 injective....  View Details
      Keywords: Identification; Econometric Models; Analytics and Data Science; Theory
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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
      • 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
      Keywords: Investment Management; Anomalies; Portfolio Construction; Transaction Costs; Investment; Management; Asset Pricing; Market Transactions; Cost
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      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...  View Details
      Keywords: Assessment; Bias; Inspection; Scheduling; Econometric Analysis; Empirical Research; Regulation; Health; Food; Safety; Quality; Performance Consistency; Performance Evaluation; Food and Beverage Industry; Service Industry
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      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...  View Details
      Keywords: Empirical Operations Management; Flexibility; Pricing; Automotive Industry; Production; Price; Management; Analysis; Auto Industry; United States
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      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,...  View Details
      Keywords: Geographic Location; Selection and Staffing; Employment; Residency; Technology Industry; India
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      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...  View Details
      Keywords: Entrepreneurs; Business History; Entrepreneurship; History; Organizations
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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.
      • 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
      Keywords: Design Of Core; Graduate Economics; Higher Education; Economics; Curriculum and Courses
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      Pons, Vincent, Jose Miguel Abito, Katarina Borovickova, Hays Golden, Jacob Goldin, Matthew A. Masten, Miguel Morin, Alexander Poirier, Israel Romem, Tyler Williams, and Chamna Yoon. "How Should the Graduate Economics Core be Changed?" Journal of Economic Education 42, no. 4 (2011): 414–417.
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