Publications

May 2023
Article

Equilibrium Effects of Pay Transparency

By: Zoë B. Cullen and Bobak Pakzad-Hurson

The public discourse around pay transparency has focused on the direct effect: how workers seek to rectify newly-disclosed pay inequities through renegotiations. The question of how wage-setting and hiring practices of the firm respond in equilibrium has received... View Details

Keywords: Pay Transparency; Online Labor Market; Privacy; Wage Gap; Corporate Disclosure; Wages; Negotiation

February 2020
Article

Being 'Good' or 'Good Enough': Prosocial Risk and the Structure of Moral Self-regard

By: Julian Zlatev, Daniella M. Kupor, Kristin Laurin and Dale T. Miller

The motivation to feel moral powerfully guides people’s prosocial behavior. We propose that people’s efforts to preserve their moral self-regard conform to a moral threshold model. This model predicts that people are primarily concerned with whether their... View Details

Keywords: Prosocial Behavior; Moral Sensibility; Decision Making; Risk and Uncertainty; Behavior; Perception

2022
Working Paper

Values as Luxury Goods and Political Polarization

By: Benjamin Enke, Mattias Polborn and Alex A Wu

Motivated by novel survey evidence, this paper develops a theory of political behavior in which values are a luxury good: the relative weight voters place on values rather than material considerations increases in income. The model predicts (i) voters who are... View Details

Keywords: Political Polarization; Government and Politics; Moral Sensibility; Luxury; Values and Beliefs; Voting

2012
Working Paper

Prominent Job Advertisements, Group Learning and Wage Dispersion

By: Julio J. Rotemberg

A model is presented in which people base their labor search strategy on the average wage and the average unemployment duration of people who belong to their peer group. It is shown that, if the distribution of wage offers is not stationary so lower wage offers tend to... View Details

Keywords: Wages; Job Offer; Job Search; Advertising

27 Feb 2019
HBS Seminar

David Robinson, Fuqua School of Business at Duke University

05 Jul 2006
Working Paper Summaries

A Cross-Sectional Analysis of the Excess Comovement of Stock Returns

Keywords: by Robin Greenwood; Financial Services

2022
Article

Efficiently Training Low-Curvature Neural Networks

By: Suraj Srinivas, Kyle Matoba, Himabindu Lakkaraju and Francois Fleuret

Standard deep neural networks often have excess non-linearity, making them susceptible to issues such as low adversarial robustness and gradient instability. Common methods to address these downstream issues, such as adversarial training, are expensive and often... View Details

Keywords: AI and Machine Learning

Article

Thinking About Technology: Applying a Cognitive Lens to Technical Change

We apply a cognitive lens to understanding technology trajectories across the life cycle by developing a co-evolutionary model of technological frames and technology. Applying that model to each stage of the technology life cycle, we identify conditions under which a... View Details

Keywords: Technology; Transformation; Outcome or Result; Economics; Cognition and Thinking; Business Model; Forecasting and Prediction

23 Aug 2013
Working Paper Summaries

Waves in Ship Prices and Investment

Keywords: by Robin Greenwood & Samuel Hanson

Siyu Zhang

Siyu Zhang is a second-year doctoral student at HBS. Zhang joined Harvard Business School in 2020 as a Research Associate and has been working on macroeconomic forecasting projects. Prior to joining HBS, he was a Data Scientist at John Hancock, where he utilized... View Details

October 2009 (Revised April 2010)
Case

Societe Generale (A): The Jerome Kerviel Affair

By: Francois Brochet

This case illustrates the tension/balance that firms with complex and risky business models must consider in designing their internal controls. It describes the environment in which a derivatives trader engaged in massive directional positions on major European stocks... View Details

Keywords: Risk Management; Problems and Challenges; Complexity; Cost Management; Balance and Stability; Business Model; Design; Stocks; Crisis Management; Financial Markets; Consulting Industry; Europe

Educators

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

2024
Working Paper

How Inflation Expectations De-Anchor: The Role of Selective Memory Cues

By: Nicola Gennaioli, Marta Leva, Raphael Schoenle and Andrei Shleifer

In a model of memory and selective recall, household inflation expectations remain rigid when inflation is anchored but exhibit sharp instability during inflation surges, as similarity prompts retrieval of forgotten high-inflation experiences. Using data from the New... View Details

Keywords: Cognition and Thinking; Inflation and Deflation; Personal Finance

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2024
Article

Learning Under Random Distributional Shifts

By: Kirk Bansak, Elisabeth Paulson and Dominik Rothenhäusler

Algorithmic assignment of refugees and asylum seekers to locations within host countries has gained attention in recent years, with implementations in the U.S. and Switzerland. These approaches use data on past arrivals to generate machine learning models that can... View Details

Keywords: AI and Machine Learning; Refugees; Employment

Article

Beacon and Warning: Sherman Kent, Scientific Hubris, and the CIA's Office of National Estimates

By: J. Peter Scoblic

Would-be forecasters have increasingly extolled the predictive potential of Big Data and artificial intelligence. This essay reviews the career of Sherman Kent, the Yale historian who directed the CIA’s Office of National Estimates from 1952 to 1967, with an eye toward... View Details

Keywords: National Security; Analytics and Data Science; Analysis; Forecasting and Prediction; History

June, 2021
Article

Learning from Deregulation: The Asymmetric Impact of Lockdown and Reopening on Risky Behavior During COVID-19

By: Edward L. Glaeser, Ginger Zhe Jin, Benjamin T. Leyden and Michael Luca

During the COVID-19 pandemic, states issued and then rescinded stay-at-home orders that restricted mobility. We develop a model of learning by deregulation, which predicts that lifting stay-at-home orders can signal that going out has become safer. Using restaurant... View Details

Keywords: COVID-19; Lockdown; Reopening; Impact; Coronavirus; Public Health Measures; Mobility; Health Pandemics; Governing Rules, Regulations, and Reforms; Consumer Behavior

Forthcoming
Article

An AI Method to Score Celebrity Visual Potential from Human Faces

By: Flora Feng, Shunyuan Zhang, Xiao Liu, Kannan Srinivasan and Cait Lamberton

It has long been a mantra of marketing practice that, particularly in low-involvement situations, spokespeople should be physically attractive. This paper suggests there is a higher probability of gaining fame and influence (i.e., celebrity potential) than is captured... View Details

Keywords: Personal Characteristics; AI and Machine Learning; Forecasting and Prediction; Marketing

2024
Working Paper

Pitfalls of Demographic Forecasts of U.S. Elections

By: Richard Calvo, Vincent Pons and Jesse M. Shapiro

Many observers have forecast large partisan shifts in the US electorate based on demographic trends. Such forecasts are appealing because demographic trends are often predictable even over long horizons. We backtest demographic forecasts using data on US elections... View Details

Keywords: Mathematical Methods; Voting; Political Elections; Trends; Forecasting and Prediction; Demographics