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- All HBS Web (154)
- Faculty Publications (82)
Show Results For
- All HBS Web (154)
- Faculty Publications (82)
- 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. Collateral constrained
banks lend to (i) solvent firms to finance investments and (ii) distressed firms to
avoid liquidation. Liquidations create negative fire-sale externalities. Liquidations...
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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. (Accept with Revisions, Journal of Finance.)
- 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.
- 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.))
- 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...
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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...
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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.)
- 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.)
- Research Summary
Overview
By: Ayelet Israeli
Professor Israeli utilizes econometric methods and field experiments to study data driven decision making in marketing context. Her research focuses on data-driven marketing, with an emphasis on how businesses can leverage their own data, customer data, and market data...
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- 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.
- 06 Apr 2017
- News
Harvard Business School Professor Julio Rotemberg Dies at 63
- Teaching Interest
Overview
Paul has been a teaching assistant for two years in the 2nd-year graduate level econometrics course, working with Professors Guido Imbens and Alberto Abadie. Additionally, he has been a TA in the undergraduate course "Household Finance."
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- 25 Oct 2018
- HBS Seminar
Fanyin Zheng, Columbia University
- 19 Jun 2019
- Working Paper Summaries
Migrant Inventors and the Technological Advantage of Nations
- 01 Aug 2012
- News
ISO standards stamp approval
- 20 Jan 2012
- News
LRQA talks to world’s leading management systems expert
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
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,...
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- Research Summary
The Connection Between Volatility and Leverage
Professor Siriwardane has co-developed a new econometric model that captures the link between equity volatility and financial leverage, driven by the desire to incorporate the record levels of both leverage and volatility that characterized the 2008 financial crisis... View Details
- 28 Mar 2019
- HBS Seminar
Gabriel Weintraub, Stanford University
- Research Summary
Research overview
By: Michael Luca
The growth of consumer review websites over the past decade has revolutionized the way in which consumers learn about product quality. The centrality of information to consumer welfare has also been underscored in public policy debates, where quality disclosure has...
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- Research Summary
The Economics of Enterprise IT
Why do some organizations adopt new information systems while others do not? Why do some face high costs while others do not? Professor Greenstein has been pursuing this stream of research throughout his career, analyzing the factors shaping the costs of acquiring... View Details
- Research Summary
Evolution of Competitive Advantage
Anita M. McGahan is studying the evolution of competitive advantage among firms in a cross section of industries. She is particularly interested in the structural conditions that enable firms to develop an enduring competitive advantage in new markets. McGahan has...
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