Skip to Main Content
HBS Home
  • About
  • Academic Programs
  • Alumni
  • Faculty & Research
  • Baker Library
  • Giving
  • Harvard Business Review
  • Initiatives
  • News
  • Recruit
  • Map / Directions
Faculty & Research
  • Faculty
  • Research
  • Featured Topics
  • Academic Units
  • …→
  • Harvard Business School→
  • Faculty & Research→
  • Research
    • Research
    • Publications
    • Global Research Centers
    • Case Development
    • Initiatives & Projects
    • Research Services
    • Seminars & Conferences
    →
  • Publications→

Publications

Publications

Filter Results: (107) Arrow Down
Filter Results: (107) Arrow Down Arrow Up

Show Results For

  • All HBS Web  (290)
    • Faculty Publications  (107)

    Show Results For

    • All HBS Web  (290)
      • Faculty Publications  (107)

      by Alvin RothRemove by Alvin Roth →

      ← Page 2 of 107 Results →

      Are you looking for?

      →Search All HBS Web
      • June 2019
      • Article

      Debt Traps? Market Vendors and Moneylender Debt in India and the Philippines

      By: Dean Karlan, Sendhil Mullainathan and Benjamin Roth
      A debt trap occurs when someone takes on a high-interest rate loan and is barely able to pay back the interest, and thus perpetually finds themselves in debt (often by refinancing). Studying such practices is important for understanding financial decision-making of... View Details
      Keywords: Borrowing and Debt; Household; Personal Finance; Decision Making; Behavior; India; Philippines
      Citation
      SSRN
      Register to Read
      Related
      Karlan, Dean, Sendhil Mullainathan, and Benjamin Roth. "Debt Traps? Market Vendors and Moneylender Debt in India and the Philippines." American Economic Review: Insights 1, no. 1 (June 2019): 27–42.
      • May 2019 (Revised May 2020)
      • Case

      fidentiaX: The Tradable Insurance Marketplace on Blockchain

      By: Alexander Braun, Lauren H. Cohen and Jiahua Xu
      Three years ago, Alvin Ang and his partner founded fidentiaX in Singapore, with the ambition to create the world’s first marketplace for tradable insurance policies on blockchain. With a 26-page white paper, the start-up closed a successful fundraising round through an... View Details
      Keywords: Blockchain; Insurance; Corporate Entrepreneurship; Technology Adoption; Business Strategy; Insurance Industry; Technology Industry; Singapore
      Citation
      Educators
      Purchase
      Related
      Braun, Alexander, Lauren H. Cohen, and Jiahua Xu. "fidentiaX: The Tradable Insurance Marketplace on Blockchain." Harvard Business School Case 219-116, May 2019. (Revised May 2020.)
      • 2019
      • Article

      Fair Algorithms for Learning in Allocation Problems

      By: Hadi Elzayn, Shahin Jabbari, Christopher Jung, Michael J Kearns, Seth Neel, Aaron Leon Roth and Zachary Schutzman
      Settings such as lending and policing can be modeled by a centralized agent allocating a scarce resource (e.g. loans or police officers) amongst several groups, in order to maximize some objective (e.g. loans given that are repaid, or criminals that are apprehended).... View Details
      Keywords: Allocation Problems; Algorithms; Fairness; Learning
      Citation
      Register to Read
      Related
      Elzayn, Hadi, Shahin Jabbari, Christopher Jung, Michael J Kearns, Seth Neel, Aaron Leon Roth, and Zachary Schutzman. "Fair Algorithms for Learning in Allocation Problems." Proceedings of the Conference on Fairness, Accountability, and Transparency (2019): 170–179.
      • 2019
      • Article

      An Empirical Study of Rich Subgroup Fairness for Machine Learning

      By: Michael J Kearns, Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu
      Kearns et al. [2018] recently proposed a notion of rich subgroup fairness intended to bridge the gap between statistical and individual notions of fairness. Rich subgroup fairness picks a statistical fairness constraint (say, equalizing false positive rates across... View Details
      Keywords: Machine Learning; Fairness; AI and Machine Learning
      Citation
      Read Now
      Related
      Kearns, Michael J., Seth Neel, Aaron Leon Roth, and Zhiwei Steven Wu. "An Empirical Study of Rich Subgroup Fairness for Machine Learning." Proceedings of the Conference on Fairness, Accountability, and Transparency (2019): 100–109.
      • October 2018 (Revised February 2018)
      • Case

      Masayoshi Son and the Vision Fund

      By: Tom Nicholas, Ramana Nanda and Benjamin N. Roth
      In October 2016, SoftBank Group Corp., the Japanese conglomerate giant caused a significant shock to the worldwide market for venture capital and private equity by announcing the Vision Fund, the largest tech investment fund in the world at close to $100 billion. The... View Details
      Keywords: Strategy; Venture Capital; Private Equity; Entrepreneurship; Competitive Strategy
      Citation
      Educators
      Purchase
      Related
      Nicholas, Tom, Ramana Nanda, and Benjamin N. Roth. "Masayoshi Son and the Vision Fund." Harvard Business School Case 819-041, October 2018. (Revised February 2018.)
      • July 2018
      • Article

      Marketplaces, Markets, and Market Design

      By: Alvin E. Roth
      Marketplaces are often small parts of large markets, and both markets and marketplaces come in many varieties. Market design seeks to understand what marketplaces must accomplish to enable different kinds of markets. Marketplaces can have varying degrees of success,... View Details
      Keywords: Labor Market; Pricing; Market Design; Markets; Economics
      Citation
      Find at Harvard
      Related
      Roth, Alvin E. "Marketplaces, Markets, and Market Design." American Economic Review 108, no. 7 (July 2018): 1609–1658.
      • Article

      Mitigating Bias in Adaptive Data Gathering via Differential Privacy

      By: Seth Neel and Aaron Leon Roth
      Data that is gathered adaptively—via bandit algorithms, for example—exhibits bias. This is true both when gathering simple numeric valued data—the empirical means kept track of by stochastic bandit algorithms are biased downwards—and when gathering more complicated... View Details
      Keywords: Bandit Algorithms; Bias; Analytics and Data Science; Mathematical Methods; Theory
      Citation
      Read Now
      Related
      Neel, Seth, and Aaron Leon Roth. "Mitigating Bias in Adaptive Data Gathering via Differential Privacy." Proceedings of the International Conference on Machine Learning (ICML) 35th (2018).
      • Article

      Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness

      By: Michael J Kearns, Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu
      The most prevalent notions of fairness in machine learning are statistical definitions: they fix a small collection of pre-defined groups, and then ask for parity of some statistic of the classifier (like classification rate or false positive rate) across these groups.... View Details
      Keywords: Machine Learning; Algorithms; Fairness; Mathematical Methods
      Citation
      Read Now
      Related
      Kearns, Michael J., Seth Neel, Aaron Leon Roth, and Zhiwei Steven Wu. "Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness." Proceedings of the International Conference on Machine Learning (ICML) 35th (2018).
      • 14 Aug 2017
      • Conference Presentation

      A Convex Framework for Fair Regression

      By: Richard Berk, Hoda Heidari, Shahin Jabbari, Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Seth Neel and Aaron Roth
      We introduce a flexible family of fairness regularizers for (linear and logistic) regression problems. These regularizers all enjoy convexity, permitting fast optimization, and they span the range from notions of group fairness to strong individual fairness. By varying... View Details
      Keywords: Regression Models; Machine Learning; Fairness; Framework; Mathematical Methods
      Citation
      Read Now
      Related
      Berk, Richard, Hoda Heidari, Shahin Jabbari, Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Seth Neel, and Aaron Roth. "A Convex Framework for Fair Regression." Paper presented at the 4th Workshop on Fairness, Accountability, and Transparency in Machine Learning, Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD), August 14, 2017.
      • Article

      Does Front-Loading Taxation Increase Savings?: Evidence from Roth 401(k) Introductions

      By: John Beshears, James J. Choi, David Laibson and Brigitte C. Madrian
      Can governments increase private savings by taxing savings up front instead of in retirement? Roth 401(k) contributions are not tax-deductible in the contribution year, but withdrawals in retirement are untaxed. The more common before-tax 401(k) contribution is... View Details
      Keywords: Saving; Retirement; Taxation
      Citation
      Read Now
      Related
      Beshears, John, James J. Choi, David Laibson, and Brigitte C. Madrian. "Does Front-Loading Taxation Increase Savings? Evidence from Roth 401(k) Introductions." Journal of Public Economics 151 (July 2017): 84–95.
      • 2017
      • Working Paper

      Minimizing Justified Envy in School Choice: The Design of New Orleans' OneApp

      By: Atila Abdulkadiroglu, Yeon-Koo Che, Parag A. Pathak, Alvin E. Roth and Oliver Tercieux
      In 2012, New Orleans Recovery School District (RSD) became the first U.S. district to unify charter and traditional public school admissions in a single-offer assignment mechanism known as OneApp. The RSD also became the first district to use a mechanism based on Top... View Details
      Keywords: Education; Decision Choices and Conditions; Marketplace Matching; Mathematical Methods; Design
      Citation
      Read Now
      Related
      Abdulkadiroglu, Atila, Yeon-Koo Che, Parag A. Pathak, Alvin E. Roth, and Oliver Tercieux. "Minimizing Justified Envy in School Choice: The Design of New Orleans' OneApp." NBER Working Paper Series, No. 23265, March 2017.
      • 18 Nov 2016
      • Conference Presentation

      Rawlsian Fairness for Machine Learning

      By: Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Seth Neel and Aaron Leon Roth
      Motivated by concerns that automated decision-making procedures can unintentionally lead to discriminatory behavior, we study a technical definition of fairness modeled after John Rawls' notion of "fair equality of opportunity". In the context of a simple model of... View Details
      Keywords: Machine Learning; Algorithms; Fairness; Decision Making; Mathematical Methods
      Citation
      Related
      Joseph, Matthew, Michael J. Kearns, Jamie Morgenstern, Seth Neel, and Aaron Leon Roth. "Rawlsian Fairness for Machine Learning." Paper presented at the 3rd Workshop on Fairness, Accountability, and Transparency in Machine Learning, Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD), November 18, 2016.
      • 2015
      • Chapter

      Is Experimental Economics Living Up to Its Promise?

      By: Alvin E. Roth
      The question that is the title of this essay already suggests that experimental economics has at least reached a sufficient state of maturity that we can try to take stock of its progress and consider how that progress matches the anticipations we may have had for the... View Details
      Keywords: Economics; History; Science
      Citation
      Find at Harvard
      Related
      Roth, Alvin E. "Is Experimental Economics Living Up to Its Promise?" Chap. 1 in Handbook of Experimental Economic Methodology, edited by Guillaume R. Frechette and Andrew Schotter, 13–42. Oxford University Press, 2015.
      • 2014
      • Working Paper

      College Admissions as Non-Price Competition: The Case of South Korea

      By: Christopher Avery, Alvin E. Roth and Soohyung Lee
      This paper examines non-price competition among colleges to attract highly qualified students, exploiting the South Korean setting where the national government sets rules governing applications. We identify some basic facts about the behavior of colleges before and... View Details
      Keywords: Competition; Higher Education; Policy; Government and Politics; Education Industry; South Korea
      Citation
      Read Now
      Related
      Avery, Christopher, Alvin E. Roth, and Soohyung Lee. "College Admissions as Non-Price Competition: The Case of South Korea." NBER Working Paper Series, No. 20774, December 2014.
      • 2014
      • Working Paper

      Don't Take 'No' for an Answer: An Experiment with Actual Organ Donor Registrations

      By: Judd B. Kessler and Alvin E. Roth
      Over 10,000 people in the U.S. die each year while waiting for an organ. Attempts to increase organ transplantation have focused on changing the registration question from an opt-in frame to an active choice frame. We analyze this change in California and show it... View Details
      Keywords: Decision Choices and Conditions; Health Care and Treatment; Philanthropy and Charitable Giving; Health Industry
      Citation
      Read Now
      Related
      Kessler, Judd B., and Alvin E. Roth. "Don't Take 'No' for an Answer: An Experiment with Actual Organ Donor Registrations." NBER Working Paper Series, No. 20378, August 2014.
      • May 2014
      • Article

      Incorporating Field Data into Archival Research

      By: Eugene F. Soltes
      I explore the use of field data in conjunction with archival evidence by examining Iliev, Miller, and Roth's (2014) analysis of an amendment to the Securities Exchange Act of 1934. This regulatory amendment allowed depositary banks to cross-list firms without the... View Details
      Keywords: Analytics and Data Science; Research; Financial Reporting
      Citation
      SSRN
      Find at Harvard
      Related
      Soltes, Eugene F. "Incorporating Field Data into Archival Research." Journal of Accounting Research 52, no. 2 (May 2014): 521–540.
      • 2013
      • Book

      The Handbook of Market Design

      By: Nir Vulkan, Alvin E. Roth and Zvika Neeman
      Citation
      Related
      Vulkan, Nir, Alvin E. Roth and Zvika Neeman, eds. The Handbook of Market Design. Oxford University Press, 2013.
      • 2013
      • Article

      Matching with Couples: Stability and Incentives in Large Markets

      By: Fuhito Kojima, Parag A. Pathak and Alvin E. Roth
      Accommodating couples has been a long-standing issue in the design of centralized labor market clearinghouses for doctors and psychologists, because couples view pairs of jobs as complements. A stable matching may not exist when couples are present. This article's main... View Details
      Keywords: Market Design; Marketplace Matching; Balance and Stability; Jobs and Positions; Family and Family Relationships; Health Care and Treatment; Employment Industry; Health Industry
      Citation
      Purchase
      Related
      Kojima, Fuhito, Parag A. Pathak, and Alvin E. Roth. "Matching with Couples: Stability and Incentives in Large Markets." Quarterly Journal of Economics 128, no. 4 (November 2013): 1585–1632.
      • Article

      Unraveling Results from Comparable Demand and Supply: An Experimental Investigation

      By: Muriel Niederle, Alvin E. Roth and M. Utku Ünver
      Markets sometimes unravel, with offers becoming inefficiently early. Often this is attributed to competition arising from an imbalance of demand and supply, typically excess demand for workers. However this presents a puzzle, since unraveling can only occur when firms... View Details
      Keywords: Two-side Matching; Unraveling; Experiments; Market Design
      Citation
      Read Now
      Related
      Niederle, Muriel, Alvin E. Roth, and M. Utku Ünver. "Unraveling Results from Comparable Demand and Supply: An Experimental Investigation." Games 4, no. 2 (June 2013): 243–282. (Special Issue on Games and Matching Markets.)
      • 2013
      • Chapter

      In 100 Years

      By: Alvin E. Roth
      Citation
      Find at Harvard
      Related
      Roth, Alvin E. "In 100 Years." Chap. 7 in In 100 Years: Leading Economists Predict the Future, edited by Ignacio Palacios-Huerta, 109–119. MIT Press, 2013.
      • ←
      • 2
      • 3
      • 4
      • 5
      • 6
      • →

      Are you looking for?

      →Search All HBS Web
      ǁ
      Campus Map
      Harvard Business School
      Soldiers Field
      Boston, MA 02163
      →Map & Directions
      →More Contact Information
      • Make a Gift
      • Site Map
      • Jobs
      • Harvard University
      • Trademarks
      • Policies
      • Accessibility
      • Digital Accessibility
      Copyright © President & Fellows of Harvard College.