data science - Publications - Faculty & Research

06 Mar 2012
First Look

First Look: March 6

benefits from racial diversity but that diversity is a liability when society's negative stereotypes about racial minorities' competence inhibit such interactions. We analyze two years of data from 496 retail bank branches to investigate... View Details

Keywords: Sean Silverthorne

01 Feb 2002
News

It's academic. (Not!)

business administration (DBA) in accounting and control, marketing, policy and management, or technology and operations management. Another option is a joint program with Harvard University's Graduate School of Arts and Sciences that... View Details

Keywords: Colleges, Universities, and Professional Schools; Educational Services

21 Apr 2015
First Look

First Look: April 21

society as a whole. Publisher's link: http://www.wiley.com/WileyCDA/WileyTitle/productCd-1118646983.html April 2015 Management Science Private Equity and Industry Performance By: Bernstein, Shai, Josh Lerner, Morten Sorensen, and Per... View Details

Keywords: Carmen Nobel & Sean Silverthorne

Research Summary

Overview

The overarching goal of my research is to produce works that are influential and informative to both academics and practitioners in the field of operations management. To accomplish this, I collaborate with industry partners who provide knowledge about their field,... View Details

25 Aug 2022
News

Harnessing the Tools of the Digital Age

digitalization and data science and artificial intelligence are deployed as management and business tools,” Lakhani explains. And that means HBS needs to think differently, too. Enter the Digital, Data, and... View Details

Keywords: April White

01 Mar 2018
News

Realizing The Potential Of One Harvard

Administration at HBS. “This program will help established leaders work more effectively with data science teams and understand how to use new data capabilities to drive... View Details

2020
Working Paper

A General Theory of Identification

By: Iavor Bojinov and Guillaume Basse

What does it mean to say that a quantity is identifiable from the data? Statisticians seem to agree on a definition in the context of parametric statistical models — roughly, a parameter θ in a model P = {Pθ : θ ∈ Θ} is identifiable if the mapping θ 7→ Pθ is injective.... View Details

Keywords: Identification; Econometric Models; Analytics and Data Science; Theory

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July 2024
Technical Note

Introduction to SQL in Python

By: Michael Parzen and Jo Ellery

This note walks through the basics of SQL and how to use this language in Python via the SQLite package. View Details

Keywords: Analytics and Data Science

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01 Dec 2018
News

Adapting to Meet Changing Needs

Sciences (SEAS), and the Faculty of Arts and Sciences debuted the Harvard Business Analytics Program (HBAP), an online certificate offering for executives focused on quantitative analysis and View Details

09 Sep 2013
Lessons from the Classroom

Teaching Climate Change to Skeptics

probabilities below present values," adding that failing to do so could lead to losses upwards of $1 trillion annually. "Most skeptics I have come across are not skeptical of global warming or climate change itself, but argue that we don't have View Details

Keywords: by Carmen Nobel

November 1996
Article

Localized Autocorrelation Diagnostic Statistic for Sociological Models: Times-series, Network, and Spatial Datasets

By: C. I. Nass and Y. Moon

Keywords: Society; Analytics and Data Science; Information

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Workshops & Technical Talks - Research Computing Services

Introduction to Data Visualization with ggplot2 Cleaning Data in R Python Python workshop materials (e.g., Python Introduction; Python Web Scraping) from Harvard's Institute for Quantitative Social View Details

January–February 2025
Article

The Double-Edged Sword of Exemplar Similarity

By: Majid Majzoubi, Eric Zhao, Tiona Zuzul and Greg Fisher

We investigate how a firm’s positioning relative to category exemplars shapes security analysts’ evaluations. Using a two-stage model of evaluation (initial screening and subsequent assessment), we propose that exemplar similarity enhances a firm’s recognizability and... View Details

Keywords: Natural Language Processing; Analytics and Data Science; Performance Evaluation

2023
Article

On Minimizing the Impact of Dataset Shifts on Actionable Explanations

By: Anna P. Meyer, Dan Ley, Suraj Srinivas and Himabindu Lakkaraju

The Right to Explanation is an important regulatory principle that allows individuals to request actionable explanations for algorithmic decisions. However, several technical challenges arise when providing such actionable explanations in practice. For instance, models... View Details

Keywords: Mathematical Methods; Analytics and Data Science

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Supply Chain Management - Course Catalog

Data-driven, analytical decision-making is often critical in supply chain management, and thus SCM also builds on aspects of the first-year Data Science and AI for Leaders (RC DSAIL) course. However, whereas... View Details

23 Jul 2001
Research & Ideas

How Relationships are Building Biotech

context in which to study the missing link. Product development cycles are long, usually between seven and ten years. Millions of dollars are spent before a product ever gets to market. Uncertainty about the viability of a company's View Details

Keywords: by Martha Lagace & Mallory Stark

06 Dec 2021
News

HBS Curricula Explore the Complexities of Innovation

of data management and analytics also led HBS to introduce Data Science for Managers, a new Required Curriculum elective for first-year MBA students. Then in their second year,... View Details

Keywords: Jennifer Gillespie

2023
Working Paper

Corporate Website-based Measures of Firms' Value Drivers

By: Wei Cai, Dennis Campbell and Patrick Ferguson

We develop and validate new text-based measures of firms’ financial and non-financial value drivers. Using the Wayback Machine to access public US firms’ archived websites from 1995-2020, we scrape text from corporate homepages. We use Kaplan and Norton’s (1992)... View Details

Keywords: Value; Corporate Strategy; Accounting; Analytics and Data Science

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2023
Article

Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators

By: Benjamin Jakubowski, Siram Somanchi, Edward McFowland III and Daniel B. Neill

Regression discontinuity (RD) designs are widely used to estimate causal effects in the absence of a randomized experiment. However, standard approaches to RD analysis face two significant limitations. First, they require a priori knowledge of discontinuities in... View Details

Keywords: Regression Discontinuity Design; Analytics and Data Science; AI and Machine Learning

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