Publications

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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2010
Working Paper

The Unbundling of Advertising Agency Services: An Economic Analysis

By: Mohammad Arzaghi, Ernst R. Berndt, James C. Davis and Alvin J. Silk

We address a longstanding puzzle surrounding the unbundling of services occurring over several decades in the U.S. advertising agency industry: What accounts for the shift from bundling to unbundling of services and the slow pace of change? Using Evans and Salinger's... View Details

Keywords: Advertising; Change; Forecasting and Prediction; Cost; Price; Analytics and Data Science; Surveys; Marketing Strategy; Media; Service Operations; Agency Theory; Mathematical Methods; Advertising Industry; United States

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

Research Summary

Overview

Professor Israeli utilizes econometric methods and field experiments to study pricing and channel management. Her current research examines how the prevalence of the online channel affects both the interactions between manufacturers and their downstream channel... View Details

Keywords: Pricing; Pricing Policies; Channel Management; Online Marketing; Online Retail; Field Experiment; Analytics; Econometric Analysis

Research Summary

Overview

Professor Israeli utilizes econometric methods and field experiments to study pricing and channel management. Her current research examines how the prevalence of the online channel affects both the interactions between manufacturers and their downstream channel... View Details

Keywords: Pricing; Pricing Policies; Channel Management; Online Marketing; Online Retail; Field Experiment; Analytics; Econometric Analysis

Teaching

Overview

By: Charles C.Y. Wang

Charles C.Y. Wang is the Tandon Family Professor of Business Administration at Harvard Business School in the Accounting and Management Unit and is currently course head of Financial Reporting and Control in the MBA core curriculum; he is also a coordinator of the... View Details

Research Summary

Overview

Downstream businesses that utilize global suppliers frequently use auditing programs to monitor their suppliers’ working conditions and are often deployed to address reputational concerns associated with procuring from unregulated suppliers. Despite their widespread... View Details

Keywords: Audit Quality; Remote Work; Outsourcing; Econometric Analysis; Switching Costs; Service Operations; Performance Effectiveness; Retail Industry; Service Industry

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

Purchase

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

Educators

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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

SSRN

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

Educators

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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,... View Details

Charles C.Y. Wang

Charles C.Y. Wang is the Tandon Family Professor of Business Administration at Harvard Business School. He is a research member of the European Corporate Governance Institute (ECGI) and an associate editor of Management Science and Journal of Accounting Research,... View Details

2025
Working Paper

Methane Abatement Costs in the Oil and Gas Industry: Survey and Synthesis

By: Joseph E. Aldy, Forest Reinhardt and Robert N. Stavins

There is growing recognition of the relative importance of anthropogenic emissions of methane as a contributor to global climate change. An important source of such emissions in some countries, including the United States, is the oil and gas (O&G) sector. This points... View Details

Keywords: Emission Reduction; Environmental Sustainability; Climate Change; Pollutants; Energy Industry

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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

SSRN

2017
Working Paper

The Need for Speed: Effects of Uncertainty Reduction in Patenting

By: Mike Horia Teodorescu

Patents are essential in commerce to establish property rights for ideas and to give equal protection to firms that develop new technologies. Young firms especially depend on the protection of intellectual property to bring a product from concept to market. However,... View Details

Keywords: Startups; Natural Language Processing; Machine Learning; Patents; Business Startups; Risk and Uncertainty; Outcome or Result; Green Technology Industry

2011
Working Paper

The First Deal: The Division of Founder Equity in New Ventures

By: Thomas F. Hellmann and Noam Wasserman

This paper examines the division of founder shares in entrepreneurial ventures, focusing on the decision of whether or not to divide the shares equally among all founders. To motivate the empirical analysis we develop a simple theory of costly bargaining, where... View Details

Keywords: Business Startups; Decision Choices and Conditions; Entrepreneurship; Fairness; Equity; Managerial Roles; Negotiation Deal; Ownership Stake; Value

2008
Working Paper

Economic Factors Underlying the Unbundling of Advertising Agency Services

By: Mohammad Arzaghi, Ernst R. Berndt, James C. Davis and Alvin J. Silk

This paper addresses a longstanding puzzle involving the unbundling of services that has occurredover more than two decades in the U.S. advertising agency industry: How can the shift from the bundling to the unbundling of services be explained and what accounts for the... View Details

Keywords: Transformation; Framework; Service Operations; Decisions; Relationships; Price; Diversification; Geography; Cost; Advertising Industry; United States

1980
Working Paper

Components of Manufacturing Inventories: A Structural Model of the Production Process

By: Alan J. Auerbach and Jerry R. Green

This paper presents a structural model of production and inventory accumulation based on the hypothesis of cost minimization. It differs from previous attempts in several respects. First, it integrates the analysis of input inventories with output inventories, treating... View Details