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- Faculty Publications (1,362)
Show Results For
-
All HBS Web
(3,562)
- People (38)
- News (618)
- Research (1,845)
- Events (19)
- Multimedia (208)
- Faculty Publications (1,362)
- Article
Four Things No One Will Tell You About ESG Data
By: Sakis Kotsantonis and George Serafeim
As the ESG finance field and the use of ESG data in investment decision-making continue to grow, the authors seek to shed light on several important aspects of ESG measurement and data. This article is intended to provide a useful guide for the rapidly rising number of...
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Keywords:
ESG;
ESG (Environmental, Social, Governance) Performance;
ESG Reporting;
Data Analytics;
Sustainability;
Sustainability Reporting;
CSR;
Transparency;
Investment Management;
Socially Responsible Investing;
Sustainable Finance;
Sustainable Development;
Inclusion;
Inclusive Growth;
Corporate Social Responsibility and Impact;
Corporate Accountability;
Investment;
Management;
Climate Change;
Corporate Governance;
Diversity;
Integrated Corporate Reporting
Kotsantonis, Sakis, and George Serafeim. "Four Things No One Will Tell You About ESG Data." Journal of Applied Corporate Finance 31, no. 2 (Spring 2019): 50–58.
- 2015
- Working Paper
Public R&D Investments and Private-sector Patenting: Evidence from NIH Funding Rules
By: Pierre Azoulay, Joshua S. Graff Zivin, Danielle Li and Bhaven N. Sampat
We quantify the impact of scientific grant funding at the National Institutes of Health (NIH) on patenting by pharmaceutical and biotechnology firms. Our paper makes two contributions. First, we use newly constructed bibliometric data to develop a method for flexibly...
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Keywords:
Economics Of Science;
Patenting;
Academic Reserach;
NIH;
Knowledge Spillovers;
Patents;
Research;
Government and Politics
Azoulay, Pierre, Joshua S. Graff Zivin, Danielle Li, and Bhaven N. Sampat. "Public R&D Investments and Private-sector Patenting: Evidence from NIH Funding Rules." Harvard Business School Working Paper, No. 16-056, October 2015.
- 2014
- Working Paper
Search-Based Peer Firms: Aggregating Investor Perceptions Through Internet Co-Searches
By: Charles M.C. Lee, Paul Ma and Charles C.Y. Wang
Applying a "co-search" algorithm to Internet traffic at the SEC's EDGAR web-site, we develop a novel method for identifying economically-related peer firms and for measuring their relative importance. Our results show that firms appearing in chronologically adjacent...
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Keywords:
Peer Firm;
EDGAR Search Traffic;
Revealed Preference;
Co-search;
Industry Classification;
Analytics and Data Science;
Internet and the Web;
Mathematical Methods;
Corporate Finance
Lee, Charles M.C., Paul Ma, and Charles C.Y. Wang. "Search-Based Peer Firms: Aggregating Investor Perceptions Through Internet Co-Searches." Harvard Business School Working Paper, No. 13-048, November 2012. (Revised September 2013, March 2014, June 2014, July 2014.)
- 31 Jan 2017
- First Look
First Look at New Research: January 31, 2017
democracy as well as its resilience over time. The book adapts the case method to revitalize conversations about governance and democracy and show how the United States has often thrived on political conflict. Each of the book’s nineteen...
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Keywords:
Carmen Nobel
- Article
Reliable Post hoc Explanations: Modeling Uncertainty in Explainability
By: Dylan Slack, Sophie Hilgard, Sameer Singh and Himabindu Lakkaraju
As black box explanations are increasingly being employed to establish model credibility in high stakes settings, it is important to ensure that these explanations are accurate and reliable. However, prior work demonstrates that explanations generated by...
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Keywords:
Black Box Explanations;
Bayesian Modeling;
Decision Making;
Risk and Uncertainty;
Information Technology
Slack, Dylan, Sophie Hilgard, Sameer Singh, and Himabindu Lakkaraju. "Reliable Post hoc Explanations: Modeling Uncertainty in Explainability." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
- 10 Apr 2023
MBA Class Visit
The excitement, energy, and unexpected insights generated by case method make it a hallmark of the HBS distinctive learning environment. We invite you to experience our stimulating academic environment by observing an MBA class in...
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- Article
Financial Innovation and Endogenous Growth
By: Luc Laeven, Ross Levine and Stelios Michalopoulos
Is financial innovation necessary for sustaining economic growth? To address this question, we build a Schumpeterian model in which entrepreneurs earn profits by inventing better goods, and profit-maximizing financiers arise to screen entrepreneurs. The model has two...
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Laeven, Luc, Ross Levine, and Stelios Michalopoulos. "Financial Innovation and Endogenous Growth." Journal of Financial Intermediation 24, no. 1 (January 2015): 1–24.
- March 2015
- Article
Business Model Evaluation: Quantifying Walmart's Sources of Advantage
By: Humberto Brea-Solís, Ramon Casadesus-Masanell and Emili Grifell-Tatjé
We develop an analytical framework on the basis of the economics of business performance to provide quantitative insight into the link between a firm's business model choices and its profit consequences. The method is applied to Walmart by building a qualitative...
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Keywords:
Business Models;
Quantitative Analysis;
Walmart;
Production Theory;
Business Model;
Competitive Advantage;
Profit
Brea-Solís, Humberto, Ramon Casadesus-Masanell, and Emili Grifell-Tatjé. "Business Model Evaluation: Quantifying Walmart's Sources of Advantage." Strategic Entrepreneurship Journal 9, no. 1 (March 2015): 12–33.
- 2010
- Working Paper
Valuation When Cash Flow Forecasts Are Biased
This paper focuses adaptations to the discount cash flow (DCF) method when valuing forecasted cash flows that are biased measures of expected cash flows. I imagine a simple setting where the expected cash flows equal the forecasted cash flows plus an omitted downside....
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Keywords:
Forecasting and Prediction;
Cash Flow;
Cost of Capital;
Performance Expectations;
Prejudice and Bias;
Valuation
Ruback, Richard S. "Valuation When Cash Flow Forecasts Are Biased." Harvard Business School Working Paper, No. 11-036, October 2010.
- August 1988 (Revised December 2000)
- Case
Dunkin' Donuts (E): 1988 Distribution Strategies
Dunkin' Donuts is exploring various methods of increasing distribution. Possibilities involving new outlets include area development contracts, subfranchising, regional rollout strategies, and an increase in company owned stores. Possibilities focusing on existing...
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Keywords:
Expansion;
Franchise Ownership;
Distribution Channels;
Retail Industry;
Food and Beverage Industry;
United States
Kaufmann, Patrick J. "Dunkin' Donuts (E): 1988 Distribution Strategies." Harvard Business School Case 589-017, August 1988. (Revised December 2000.)
- 24 Oct 2018
- News
America’s Need for Skilled Immigrants Isn’t Going Away
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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- Web
Strategy Execution Online Course | HBS Online
"What I found most valuable were the methods and tools, which were useful and practical. I’ve already applied some of my learning at my job." Atanas AtanasovStrategy Execution Participant Design new structures and systems to manage the...
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- 30 Oct 2006
- First Look
First Look: October 31, 2006
Working PapersHow Does Foreign Direct Investment Promote Economic Growth? Exploring the Effects of Financial Markets on Linkages Authors:Laura Alfaro, Areendam Chanda, Sebnem Kalemli-Ozcan, and Selin Sayek Abstract The empirical literature finds mixed evidence on the...
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Keywords:
Sean Silverthorne
- January 2004 (Revised February 2005)
- Background Note
A Note on Methodological Fit in Management Field Research
By: Amy C. Edmondson and Stacy McManus
To use in doctoral-level management courses on the design of field research methods. Advocates the importance of fit, or internal consistency, among the different elements of a field research project. Although the scientific method provides an essential framework for...
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Edmondson, Amy C., and Stacy McManus. "A Note on Methodological Fit in Management Field Research." Harvard Business School Background Note 604-072, January 2004. (Revised February 2005.)
- Research Summary
Valuation Theory and Practice
Timothy A. Luehrman's primary research interest is in the application of valuation methods to companies, businesses, and individual assets. Some of his work involves applications of tools originally developed for valuing derivative securities to the valuation of other...
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- Research Summary
Choice, Rationality and Welfare Measurement
By: Jerry R. Green
For the past century, economists have used the hypothesis that individual choice is based on rationality in their calculations of individual and collective welfare. The central ideas are that actual market choice reveal underlying preferences, and with a good set of...
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- June 2006 (Revised April 2007)
- Case
BioScale
By: H. Kent Bowen and Bradley R. Staats
In 2004, Mark Lundstrom must decide on a funding method and strategic approach for BioScale, a biotechnology company that he founded. BioScale has developed a microchip-based bioanalytical platform that can be used to detect very small concentrations of cells, viruses,...
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Keywords:
Entrepreneurship;
Science-Based Business;
Capital;
Financing and Loans;
Partners and Partnerships;
Biotechnology Industry
Bowen, H. Kent, and Bradley R. Staats. "BioScale." Harvard Business School Case 606-100, June 2006. (Revised April 2007.)
- 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...
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Keywords:
Machine Learning;
Econometric Analysis;
Instrumental Variable;
Random Forest;
Causal Inference;
AI and Machine Learning;
Forecasting and Prediction
Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem." INFORMS Journal on Data Science 1, no. 2 (October–December 2022): 138–155.