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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November–December 2018
Article

Slack Time and Innovation

By: Ajay Agrawal, Christian Catalini, Avi Goldfarb and Hong Luo

Traditional innovation models assume that new ideas are developed up to the point where the benefit of the marginal project is just equal to the cost. Because labor is a key input to innovation when the opportunity cost of time is lower, such as during school breaks or... View Details

Keywords: Crowdfunding; Slack Time; Innovation and Invention; Labor; Projects; Complexity; Value

05 Jul 2006
Working Paper Summaries

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

Keywords: by Robin Greenwood; Financial Services

07 Jan 2019
Research & Ideas

The Better Way to Forecast the Future

different fields,” says Grushka-Cockayne, whose research is on data science, forecasting, project management, and behavioral decision-making. “Our work is focused on using crowds for prediction and for forecasting something that is... View Details

Keywords: by Roberta Holland; Air Transportation; Transportation

2023
Working Paper

How People Use Statistics

By: Pedro Bordalo, John J. Conlon, Nicola Gennaioli, Spencer Yongwook Kwon and Andrei Shleifer

We document two new facts about the distributions of answers in famous statistical problems: they are i) multi-modal and ii) unstable with respect to irrelevant changes in the problem. We offer a model in which, when solving a problem, people represent each hypothesis... View Details

Keywords: Decision Choices and Conditions; Microeconomics; Mathematical Methods; Behavioral Finance

2010
Working Paper

Agglomerative Forces and Cluster Shapes

By: William R. Kerr and Scott Duke Kominers

We model spatial clusters of similar firms. Our model highlights how agglomerative forces lead to localized, individual connections among firms, while interaction costs generate a defined distance over which attraction forces operate. Overlapping firm interactions... View Details

Keywords: Entrepreneurship; Geographic Location; Patents; Labor; Industry Clusters; Industry Structures; Relationships; Competitive Advantage; Technology Industry; California

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

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

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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2019
Working Paper

Soul and Machine (Learning)

By: Davide Proserpio, John R. Hauser, Xiao Liu, Tomomichi Amano, Alex Burnap, Tong Guo, Dokyun Lee, Randall Lewis, Kanishka Misra, Eric Schwarz, Artem Timoshenko, Lilei Xu and Hema Yoganarasimhan

Machine learning is bringing us self-driving cars, improved medical diagnostics, and machine translation, but can it improve marketing decisions? It can. Machine learning models predict extremely well, are scalable to “big data,” and are a natural fit to rich media... View Details

Keywords: Machine Learning; Technological Innovation; Marketing; AI and Machine Learning

SSRN

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

May 2025
Article

Imagining the Future: Memory, Simulation and Beliefs

By: Pedro Bordalo, Giovanni Burro, Katherine B. Coffman, Nicola Gennaioli and Andrei Shleifer

How do people form beliefs about novel risks, with which they have little or no experience? Motivated by survey data on beliefs about Covid we collected in 2020, we build a model based on the psychology of selective memory. When a person thinks about an event,... View Details

Keywords: Expectations; Memory; COVID-19 Pandemic; Risk and Uncertainty; Cognition and Thinking

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

July 2016
Article

Taxation, Corruption, and Growth

By: Philippe Aghion, Ufuk Akcigit, Julia Cagé and William R. Kerr

We build an endogenous growth model to analyze the relationships between taxation, corruption, and economic growth. Entrepreneurs lie at the center of the model and face disincentive effects from taxation but acquire positive benefits from public infrastructure.... View Details

Keywords: Endogenous Growth; Public Goods; Corruption; Crime and Corruption; Entrepreneurship; Taxation; Economic Growth

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

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
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

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

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