Publications

SSRN

2022
Article

A Human-Centric Take on Model Monitoring

By: Murtuza Shergadwala, Himabindu Lakkaraju and Krishnaram Kenthapadi

Predictive models are increasingly used to make various consequential decisions in high-stakes domains such as healthcare, finance, and policy. It becomes critical to ensure that these models make accurate predictions, are robust to shifts in the data, do not rely on... View Details

Keywords: AI and Machine Learning; Research and Development; Demand and Consumers

June 2023
Article

When Does Uncertainty Matter? Understanding the Impact of Predictive Uncertainty in ML Assisted Decision Making

By: Sean McGrath, Parth Mehta, Alexandra Zytek, Isaac Lage and Himabindu Lakkaraju

As machine learning (ML) models are increasingly being employed to assist human decision makers, it becomes critical to provide these decision makers with relevant inputs which can help them decide if and how to incorporate model predictions into their decision... View Details

Keywords: AI and Machine Learning; Decision Making

2013
Working Paper

Return Predictability in the Treasury Market: Real Rates, Inflation, and Liquidity

By: Carolin E. Pflueger and Luis M. Viceira

Estimating the liquidity differential between inflation-indexed and nominal bond yields, we separately test for time-varying real rate risk premia, inflation risk premia, and liquidity premia in U.S. and U.K. bond markets. We find strong, model independent evidence... View Details

Keywords: Expectations Hypothesis; Term Structure; Real Interest Rate Risk; Inflation Risk; Inflation-Indexed Bonds; Financial Crisis; Inflation and Deflation; Financial Liquidity; Bonds; Investment Return; Risk and Uncertainty; United Kingdom; United States

SSRN

February 2007 (Revised January 2008)
Supplement

Multifactor Models (CW)

By: Malcolm P. Baker

Keywords: Asset Pricing; Cost of Capital; Forecasting and Prediction; Investment Funds; Investment Return; Mathematical Methods; Performance Evaluation

Purchase

2011
Article

A Choice Prediction Competition for Social Preferences in Simple Extensive Form Games: An Introduction

By: Eyal Ert, Ido Erev and Alvin E. Roth

Two independent, but related, choice prediction competitions are organized that focus on behavior in simple two-person extensive form games: one focuses on predicting the choices of the first mover and the other on predicting the choices of the second mover. The... View Details

Keywords: Forecasting and Prediction; Behavior; Decision Choices and Conditions; Competition; Motivation and Incentives; Game Theory; Fairness

Research Summary

Models of optimal experience (flow)

Flow is a state of profound task-absorption, involvement, and intrinsic enjoyment that makes the person feel one with the activity. Csikszentmihalyi's Flow Theory states that flow is more likely to occur in situations in which the person feels that the activity is very... View Details

April 2024
Article

A Machine Learning Algorithm Predicting Risk of Dilating VUR among Infants with Hydronephrosis Using UTD Classification

By: Hsin-Hsiao Scott Wang, Michael Lingzhi Li, Dylan Cahill, John Panagides, Tanya Logvinenko, Jeanne Chow and Caleb Nelson

Backgrounds: Urinary Tract Dilation (UTD) classification has been designed to be a more objective grading system to evaluate antenatal and post-natal UTD. Due to unclear association between UTD classifications to specific anomalies such as vesico-ureteral reflux (VUR),... View Details

Keywords: Health Disorders; Health Testing and Trials; AI and Machine Learning; Health Industry

In this paper, we propose a neurocomputational model of altruistic choice and test it using behavioral and fMRI data from a task in which subjects make choices between real monetary prizes for themselves and another. Our model captures key patterns of choice,... View Details

07 Oct 2024
Research & Ideas

Election 2024: Why Demographics Won't Predict the Next President

years—the more dubious the predictions become. Studying almost 70 years of voting records and results The team analyzed voting from the American National Election Study and demographic information from government sources going back to... View Details

Keywords: by Jay Fitzgerald

2009
Article

Modeling Expert Opinions on Food Healthfulness: A Nutrition Metric

By: Jolie M. Martin, John Beshears, Katherine L. Milkman, Max H. Bazerman and Lisa Sutherland

Research over the last several decades indicates the failure of existing nutritional labels to substantially improve the healthiness of consumers' food and beverage choices. The difficulty for policy-makers is to encapsulate a wide body of scientific knowledge in a... View Details

Keywords: Judgments; Food; Nutrition; Labels; Knowledge Use and Leverage; Demand and Consumers; Measurement and Metrics; Mathematical Methods

30 May 2023
Research & Ideas

Can AI Predict Whether Shoppers Would Pick Crest or Colgate?

but large language models like generative pre-trained transformers (GPTs) may allow companies to rely on AI to uncover consumers’ tastes, according to new research from Harvard Business School and Microsoft. Ayelet Israeli, an associate... View Details

Keywords: by Kristen Senz

January 1986 (Revised April 1987)
Background Note

Models for Updating Demand Forecasts

By: Arthur Schleifer Jr.

Keywords: Forecasting and Prediction

July 2023
Article

Takahashi-Alexander Revisited: Modeling Private Equity Portfolio Outcomes Using Historical Simulations

By: Dawson Beutler, Alex Billias, Sam Holt, Josh Lerner and TzuHwan Seet

In 2001, Dean Takahashi and Seth Alexander of the Yale University Investments Office developed a deterministic model for estimating future cash flows and valuations for the Yale endowment’s private equity portfolio. Their model, which is simple and intuitive, is still... View Details

Keywords: Forecasting and Prediction; Investment Portfolio; Analytics and Data Science

Purchase

August 2023
Article

Explaining Machine Learning Models with Interactive Natural Language Conversations Using TalkToModel

By: Dylan Slack, Satyapriya Krishna, Himabindu Lakkaraju and Sameer Singh

Practitioners increasingly use machine learning (ML) models, yet models have become more complex and harder to understand. To understand complex models, researchers have proposed techniques to explain model predictions. However, practitioners struggle to use... View Details

Keywords: AI and Machine Learning; Technological Innovation; Technology Adoption

18 Jun 2024
Research & Ideas

Central Banks Missed Inflation Red Flags. This Pricing Model Could Help.

doctoral student at the University of Chicago. The ‘state’ of the price gap matters Economists generally use two main data models to detect inflation and predict the pace at which retailers raise prices:... View Details

Keywords: by Rachel Layne; Financial Services; Banking

1994
Article

Three-dimensional Finite Element Modeling of a Cervical Vertebra: An Investigation of Burst Fracture Mechanism

By: Kevin J. Bozic, J H Keyak, H B Skinner, H U Bueff and David Bradford

Finite element modeling was used to study the mechanical behavior of a cervical vertebra under axial compressive loading. A three-dimensional (3-D) finite element (FE) model of a mid-cervical vertebra using inhomogeneous material properties was generated from... View Details

Keywords: Performance Expectations; Strength and Weakness; Health; Mathematical Methods; Health Industry

15 Aug 2016
Research & Ideas

Black Swans and Big Trends Can Ruin Anyone's Internet Prediction

investments are once again declining. Reasoning that today’s tech entrepreneurs and investors might value a history lesson, I’ve published Speed Trap as an ebook, which is downloadable for free in PDF format, and available in the iBooks Store for free and in the Kindle... View Details

Keywords: by Thomas R. Eisenmann; Technology

07 Jul 2003
Research & Ideas

The Organizational Model for Open Source

three projects: Debian, a complete non-commercial distribution of Linux; the GNU Object Model Environment (GNOME), which is a graphical user interface for Linux-based operating systems; and Apache, a public domain open source Web server.... View Details

Keywords: by Mallory Stark

Article

Stereotype Content Model across Cultures: Universal Similarities and Some Differences

By: A.J.C. Cuddy, S.T. Fiske, V.S.Y. Kwan, P. Glick, S. Demoulin, J. Ph. Leyens and M.H. Bond

The stereotype content model (SCM; Fiske, Cuddy, Glick, & Xu, 2002) proposes potentially universal principles of societal stereotypes and their relation to social structure. Here, the SCM reveals theoretically grounded, cross-cultural, cross-groups' similarities and... View Details

Keywords: Cross-Cultural and Cross-Border Issues; Management Analysis, Tools, and Techniques; Relationships; Groups and Teams; Prejudice and Bias; Culture; Societal Protocols; East Asia; Europe