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Show Results For
- All HBS Web
(3,434)
- People (1)
- News (917)
- Research (2,087)
- Events (7)
- Multimedia (37)
- Faculty Publications (1,062)
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- 26 Apr 2012
- Working Paper Summaries
What Makes a Critic Tick? Connected Authors and the Determinants of Book Reviews
- 20 Aug 2007
- Working Paper Summaries
Hedge Fund Investor Activism and Takeovers
- 2003
- Working Paper
Ensure Your Survival by Leading an Organization Wide Conversation That Matters
By: Michael Beer and Russell Eisenstat
- 15 Nov 2011
- Working Paper Summaries
Engaging Supply Chains in Climate Change
- 19 Aug 2011
- Working Paper Summaries
The Globalization of Corporate Environmental Disclosure: Accountability or Greenwashing?
- 26 Apr 2017
- Working Paper Summaries
Assessing the Quality of Quality Assessment: The Role of Scheduling
- 2021
- Working Paper
International Evidence on the Effects of a Local Presence by U.S. Credit Rating Agencies
By: Liran Eliner, Michael Machokoto and Anywhere Sikochi
Major U.S. credit rating agencies are criticized for failing to understand developments in other economies and thereby impeding capital access by assigning lower ratings. Consistent with this, we find that Moody's and S&P credit ratings are more favorable after the... View Details
Keywords: Credit Rating Agencies; Credit Ratings; Rating Adjustments; Rating Disagreement; Geographic Proximity; Soft Information; Credit; Geographic Location; Local Range
Eliner, Liran, Michael Machokoto, and Anywhere Sikochi. "International Evidence on the Effects of a Local Presence by U.S. Credit Rating Agencies." Harvard Business School Working Paper, No. 20-083, February 2020. (Revised August 2021.)
- 23 Mar 2021
- Book
Succeeding in the New Work-from-Anywhere World
the Author Michael Blanding is a writer based in the Boston area. [Image: Shutterstock/Min C. Chiu] What do you think it takes to succeed as a remote team? Share your insights in the comments below. Book Excerpt Remote Work Revolution:... View Details
Keywords: by Michael Blanding
- 18 Jul 2018
- Research & Ideas
No More General Tso's? A Threat to 'Knowledge Recombination'
In the current squabble over how many skilled immigrants to let into the United States on H1-B visas, academics have fiercely debated whether they create jobs by bringing new skills to companies or whether they take jobs away View Details
- 11 Nov 2020
- Research & Ideas
How Hackathons Help Decide Platform Winners and Losers
competitive challenges facing software companies. Their market success depends largely on persuading the above-mentioned developers to write for their platforms. A new research paper suggests that the two sides can serve their own best interests View Details
- 19 Aug 2013
- Research & Ideas
Studying How Income Inequality Shapes Behavior
Business Administration at Harvard Business School, where he teaches in the Business, Government and the International Economy unit. "It's striking how much work has gone into examining this question—including by many truly... View Details
Keywords: by Michael Blanding
- 2022
- Working Paper
Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments
By: Kosuke Imai and Michael Lingzhi Li
Researchers are increasingly turning to machine learning (ML) algorithms to investigate causal heterogeneity in randomized experiments. Despite their promise, ML algorithms may fail to accurately ascertain heterogeneous treatment effects under practical settings with... View Details
Imai, Kosuke, and Michael Lingzhi Li. "Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments." Working Paper, March 2022.
- 09 Dec 2015
- Working Paper Summaries
Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life
- 21 Sep 2012
- Working Paper Summaries
Public Procurement and the Private Supply of Green Buildings
Keywords: by Timothy Simcoe & Michael W. Toffel
- 13 Feb 2008
- Working Paper Summaries
Unconventional Insights for Managing Stakeholder Trust
Keywords: by Michael Pirson & Deepak Malhotra
- Forthcoming
- Article
Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments
By: Kosuke Imai and Michael Lingzhi Li
Researchers are increasingly turning to machine learning (ML) algorithms to investigate causal heterogeneity in randomized experiments. Despite their promise, ML algorithms may fail to accurately ascertain heterogeneous treatment effects under practical settings with... View Details
Imai, Kosuke, and Michael Lingzhi Li. "Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments." Journal of Business & Economic Statistics (forthcoming). (Pre-published online July 8, 2024.)
- 09 Aug 2011
- Working Paper Summaries
How Firms Respond to Mandatory Information Disclosure
- 20 Aug 2018
- Research & Ideas
Bargain Hunters Beware: A Store's 'Original Price' Might Not Be After All
marketing chicanery almost by accident. He was working on a related project involving a major US-based clothing and accessories brand (he can’t say which), when he noticed something odd happening at their outlet stores. “They never even... View Details
- 22 Oct 2012
- Research & Ideas
Not Your Father’s State-Run Capitalism
state-owned enterprises (SOEs) such as those in the Soviet Union and China, which were tightly controlled by government, packed with party apparatchiks, and stifled honest competition by introducing all... View Details
Keywords: by Michael Blanding