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 : (155) Arrow Down
Filter Results : (155) Arrow Down Arrow Up

Show Results For

  • All HBS Web  (429)
    • Faculty Publications  (155)

    Show Results For

    • All HBS Web  (429)
      • Faculty Publications  (155)

      Causality Remove Causality →

      Page 1 of 155 Results →

      Are you looking for?

      → Search All HBS Web
      • 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
      Citation
      Read Now
      Related
      Jakubowski, Benjamin, Siram Somanchi, Edward McFowland III, and Daniel B. Neill. "Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators." Journal of Machine Learning Research 24, no. 133 (2023): 1–57.
      • 2023
      • Article

      Estimating Causal Peer Influence in Homophilous Social Networks by Inferring Latent Locations.

      By: Edward McFowland III and Cosma Rohilla Shalizi
      Social influence cannot be identified from purely observational data on social networks, because such influence is generically confounded with latent homophily, that is, with a node’s network partners being informative about the node’s attributes and therefore its...  View Details
      Keywords: Causal Inference; Homophily; Social Networks; Peer Influence; Social and Collaborative Networks; Power and Influence; Mathematical Methods
      Citation
      Find at Harvard
      Purchase
      Related
      McFowland III, Edward, and Cosma Rohilla Shalizi. "Estimating Causal Peer Influence in Homophilous Social Networks by Inferring Latent Locations." Journal of the American Statistical Association 118, no. 541 (2023): 707–718.
      • 2023
      • Working Paper

      Crowding in Private Quality: The Equilibrium Effects of Public Spending in Education

      By: Tahir Andrabi, Natalie Bau, Jishnu Das, Asim Ijaz Khwaja and Naureen Karachiwalla
      We estimate the equilibrium effects of a public-school grant program administered through school councils in Pakistani villages with multiple public and private schools and clearly defined catchment boundaries. The program was randomized at the village-level, allowing...  View Details
      Keywords: Product Differentiation; Public Sector; Private Sector; Spending; Education; Competition
      Citation
      Find at Harvard
      Register to Read
      Related
      Andrabi, Tahir, Natalie Bau, Jishnu Das, Asim Ijaz Khwaja, and Naureen Karachiwalla. "Crowding in Private Quality: The Equilibrium Effects of Public Spending in Education." NBER Working Paper Series, No. 30929, February 2023.
      • 2023
      • Article

      Experimental Evaluation of Individualized Treatment Rules

      By: Kosuke Imai and Michael Lingzhi Li
      The increasing availability of individual-level data has led to numerous applications of individualized (or personalized) treatment rules (ITRs). Policy makers often wish to empirically evaluate ITRs and compare their relative performance before implementing them in a...  View Details
      Keywords: Causal Inference; Heterogeneous Treatment Effects; Precision Medicine; Uplift Modeling; Analytics and Data Science; AI and Machine Learning
      Citation
      Find at Harvard
      Read Now
      Related
      Imai, Kosuke, and Michael Lingzhi Li. "Experimental Evaluation of Individualized Treatment Rules." Journal of the American Statistical Association 118, no. 541 (2023): 242–256.
      • January 2023
      • Article

      Racial Diversity and Racial Policy Preferences: The Great Migration and Civil Rights

      By: Alvaro Calderon, Vasiliki Fouka and Marco Tabellini
      Between 1940 and 1970, more than 4 million African Americans moved from the South to the North of the United States, during the Second Great Migration. This same period witnessed the struggle and eventual success of the civil rights movement in ending institutionalized...  View Details
      Keywords: Civil Rights; Great Migration; History; Race; Rights; Prejudice and Bias; Government Legislation
      Citation
      Find at Harvard
      Purchase
      Related
      Calderon, Alvaro, Vasiliki Fouka, and Marco Tabellini. "Racial Diversity and Racial Policy Preferences: The Great Migration and Civil Rights." Review of Economic Studies 90, no. 1 (January 2023): 165–200. (Available also from VOX, Broadstreet, and VOX EU.)
      • December 2022
      • Article

      Fostering Perceptions of Authenticity via Sensitive Self-Disclosure

      By: Li Jiang, Leslie K. John, Reihane Boghrati and Maryam Kouchaki
      Leaders’ perceived authenticity—the sense that leaders are acting in accordance with their “true self”—is associated with positive outcomes for both employees and organizations alike. How might leaders foster this impression? We show that sensitive self-disclosure, in...  View Details
      Keywords: Authenticity; Weaknesses; Self-disclosure; Leaders; Impression Management; Leadership Style; Motivation and Incentives
      Citation
      Find at Harvard
      Read Now
      Purchase
      Related
      Jiang, Li, Leslie K. John, Reihane Boghrati, and Maryam Kouchaki. "Fostering Perceptions of Authenticity via Sensitive Self-Disclosure." Journal of Experimental Psychology: Applied 28, no. 4 (December 2022): 898–915.
      • December 2022
      • Article

      The Emotional Rewards of Prosocial Spending Are Robust and Replicable in Large Samples

      By: Lara B. Aknin, Elizabeth W. Dunn and Ashley V. Whillans
      Past studies show that spending money on other people—prosocial spending—increases a person’s happiness. However, foundational research on this topic was conducted prior to psychology’s credibility revolution (or “replication crisis”), so it is essential to ask...  View Details
      Keywords: Happiness; Money
      Citation
      Find at Harvard
      Read Now
      Related
      Aknin, Lara B., Elizabeth W. Dunn, and Ashley V. Whillans. "The Emotional Rewards of Prosocial Spending Are Robust and Replicable in Large Samples." Current Directions in Psychological Science 31, no. 6 (December 2022): 536–545. (Pre-published online, November 9, 2022.)
      • November 2022
      • Article

      My Boss' Passion Matters as Much as My Own: The Interpersonal Dynamics of Passion Are a Critical Driver of Performance Evaluations

      By: Jon M. Jachimowicz, Andreas Wihler and Adam D. Galinsky
      Companies often celebrate employees who successfully pursue their passion. Academic research suggests that these positive evaluations occur because of the passion percolating inside the employee. We propose that supervisors are also a key piece of this puzzle:...  View Details
      Keywords: Passion; Job Performance; Motivation; Emotions; Performance Evaluation; Interpersonal Communication
      Citation
      Find at Harvard
      Purchase
      Related
      Jachimowicz, Jon M., Andreas Wihler, and Adam D. Galinsky. "My Boss' Passion Matters as Much as My Own: The Interpersonal Dynamics of Passion Are a Critical Driver of Performance Evaluations." Special Issue on Work Passion Research: Taming Breadth and Promoting Depth. Journal of Organizational Behavior 43, no. 9 (November 2022): 1496–1515.
      • November 2022
      • Article

      The Psychosocial Value of Employment: Evidence from a Refugee Camp

      By: Reshmaan Hussam, Erin M. Kelley, Gregory Lane and Fatima Zahra
      Employment may be important to wellbeing for reasons beyond its role as an income source. This paper presents a causal estimate of the psychosocial value of employment in refugee camps in Bangladesh. We involve 745 individuals in a field experiment with three arms: a...  View Details
      Keywords: Psychosocial Wellbeing; Employment; Refugees; Well-being
      Citation
      Find at Harvard
      Read Now
      Purchase
      Related
      Hussam, Reshmaan, Erin M. Kelley, Gregory Lane, and Fatima Zahra. "The Psychosocial Value of Employment: Evidence from a Refugee Camp." American Economic Review 112, no. 11 (November 2022): 3694–3724.
      • 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...  View Details
      Keywords: Machine Learning; Econometric Analysis; Instrumental Variable; Random Forest; Causal Inference; AI and Machine Learning; Forecasting and Prediction
      Citation
      Find at Harvard
      Register to Read
      Related
      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.
      • September 16, 2022
      • Article

      A Causal Test of the Strength of Weak Ties

      By: Karthik Rajkumar, Guillaume Saint-Jacques, Iavor I. Bojinov, Erik Brynjolfsson and Sinan Aral
      The authors analyzed data from multiple large-scale randomized experiments on LinkedIn’s People You May Know algorithm, which recommends new connections to LinkedIn members, to test the extent to which weak ties increased job mobility in the world’s largest...  View Details
      Keywords: Job Mobility; Social Networks; Social Ties; Networks; Personal Development and Career
      Citation
      Register to Read
      Related
      Rajkumar, Karthik, Guillaume Saint-Jacques, Iavor I. Bojinov, Erik Brynjolfsson, and Sinan Aral. "A Causal Test of the Strength of Weak Ties." Science 377, no. 6612 (September 16, 2022).
      • 2022
      • Working Paper

      Human Capital and the Managerial Revolution in the United States

      By: Tom Nicholas
      This paper estimates the returns to human capital accumulation during the first era of megafirms in the United States by linking employees at General Electric—a canonical enterprise associated with the “visible hand” of managerial hierarchies—to data from the 1940...  View Details
      Keywords: Returns To Education; Management Practices; Hierarchies; Human Capital; Management; Training; Higher Education; Government and Politics; United States
      Citation
      Read Now
      Related
      Nicholas, Tom. "Human Capital and the Managerial Revolution in the United States." Harvard Business School Working Paper, No. 23-015, September 2022.
      • 2022
      • Working Paper

      Product2Vec: Leveraging Representation Learning to Model Consumer Product Choice in Large Assortments

      By: Fanglin Chen, Xiao Liu, Davide Proserpio and Isamar Troncoso
      We propose a method, Product2Vec, based on representation learning, that can automatically learn latent product attributes that drive consumer choices, to study product-level competition when the number of products is large. We demonstrate Product2Vec’s...  View Details
      Keywords: Consumer Choice; Consumer Behavior; Competition; Product Marketing
      Citation
      SSRN
      Read Now
      Related
      Chen, Fanglin, Xiao Liu, Davide Proserpio, and Isamar Troncoso. "Product2Vec: Leveraging Representation Learning to Model Consumer Product Choice in Large Assortments." NYU Stern School of Business Research Paper Series, July 2022.
      • June 2022 (Revised July 2022)
      • Module Note

      Causal Inference

      By: Iavor I Bojinov, Michael Parzen and Paul Hamilton
      This note provides an overview of causal inference for an introductory data science course. First, the note discusses observational studies and confounding variables. Next the note describes how randomized experiments can be used to account for the effect of...  View Details
      Keywords: Causal Inference; Causality; Experiment; Experimental Design; Data Science; Analytics and Data Science
      Citation
      Purchase
      Related
      Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Causal Inference." Harvard Business School Module Note 622-111, June 2022. (Revised July 2022.)
      • June 2022
      • Article

      Conservatism Gets Funded? A Field Experiment on the Role of Negative Information in Novel Project Evaluation

      By: Jacqueline N. Lane, Misha Teplitskiy, Gary Gray, Hardeep Ranu, Michael Menietti, Eva C. Guinan and Karim R. Lakhani
      The evaluation and selection of novel projects lies at the heart of scientific and technological innovation, and yet there are persistent concerns about bias, such as conservatism. This paper investigates the role that the format of evaluation, specifically information...  View Details
      Keywords: Project Evaluation; Innovation; Knowledge Frontier; Information Sharing; Negativity Bias; Projects; Innovation and Invention; Information; Knowledge Sharing
      Citation
      Find at Harvard
      Read Now
      Related
      Lane, Jacqueline N., Misha Teplitskiy, Gary Gray, Hardeep Ranu, Michael Menietti, Eva C. Guinan, and Karim R. Lakhani. "Conservatism Gets Funded? A Field Experiment on the Role of Negative Information in Novel Project Evaluation." Management Science 68, no. 6 (June 2022): 4478–4495.
      • May 2022
      • Article

      Can Gambling Increase Savings? Empirical Evidence on Prize-Linked Savings Accounts

      By: Shawn A. Cole, Benjamin Iverson and Peter Tufano
      This paper studies the adoption and impact of prize-linked savings (PLS) accounts, which offer lottery-like payouts to individual account holders in lieu of interest. Using microlevel data from a bank in South Africa, we show that PLS is attractive to a broad group of...  View Details
      Keywords: Household Finance; Banking; Savings; Prize-linked Savings; Lottery; Household; Personal Finance; Saving; Banks and Banking
      Citation
      Find at Harvard
      Purchase
      Related
      Cole, Shawn A., Benjamin Iverson, and Peter Tufano. "Can Gambling Increase Savings? Empirical Evidence on Prize-Linked Savings Accounts." Management Science 68, no. 5 (May 2022): 3282–3308.
      • 2022
      • Working Paper

      Causal Inference During A Pandemic: Evidence on the Effectiveness of Nebulized Ibuprofen as an Unproven Treatment for COVID-19 in Argentina

      By: Sebastian Calonico, Rafael Di Tella and Juan Cruz Lopez Del Valle
      Many medical decisions during the pandemic were made without the support of causal evidence obtained in clinical trials. We study the case of nebulized ibuprofen (NaIHS), a drug that was extensively used on COVID-19 patients in Argentina amidst wild claims about its...  View Details
      Keywords: COVID-19; Drug Treatment; Health Pandemics; Health Care and Treatment; Decision Making; Outcome or Result; Argentina
      Citation
      Find at Harvard
      Read Now
      Related
      Calonico, Sebastian, Rafael Di Tella, and Juan Cruz Lopez Del Valle. "Causal Inference During A Pandemic: Evidence on the Effectiveness of Nebulized Ibuprofen as an Unproven Treatment for COVID-19 in Argentina." NBER Working Paper Series, No. 30084, May 2022.
      • Article

      How Much Should We Trust Staggered Difference-In-Differences Estimates?

      By: Andrew C. Baker, David F. Larcker and Charles C.Y. Wang
      We explain when and how staggered difference-in-differences regression estimators, commonly applied to assess the impact of policy changes, are biased. These biases are likely to be relevant for a large portion of research settings in finance, accounting, and law that...  View Details
      Keywords: Difference In Differences; Staggered Difference-in-differences Designs; Generalized Difference-in-differences; Dynamic Treatment Effects; Mathematical Methods
      Citation
      SSRN
      Find at Harvard
      Read Now
      Related
      Baker, Andrew C., David F. Larcker, and Charles C.Y. Wang. "How Much Should We Trust Staggered Difference-In-Differences Estimates?" Journal of Financial Economics 144, no. 2 (May 2022): 370–395. (Editor's Choice, May 2022.)
      • April–June 2022
      • Other Article

      Commentary on 'Causal Decision Making and Causal Effect Estimation Are Not the Same... and Why It Matters'

      By: Edward McFowland III
      There has been a substantial discussion in various methodological and applied literatures around causal inference; especially in the use of machine learning and statistical models to understand heterogeneity in treatment effects and to make optimal decision...  View Details
      Keywords: Causal Inference; Treatment Effect Estimation; Treatment Assignment Policy; Human-in-the-loop; Decision Making; Fairness
      Citation
      Find at Harvard
      Purchase
      Related
      McFowland III, Edward. "Commentary on 'Causal Decision Making and Causal Effect Estimation Are Not the Same... and Why It Matters'." INFORMS Journal on Data Science 1, no. 1 (April–June 2022): 21–22.
      • 2022
      • Working Paper

      Is Hybrid Work the Best of Both Worlds? Evidence from a Field Experiment

      By: Prithwiraj Choudhury, Tarun Khanna, Christos A. Makridis and Kyle Schirmann
      Hybrid work is emerging as a novel form of organizing work globally. This paper reports causal evidence on how the extent of hybrid work—the number of days worked from home relative to days worked from the office—affects work outcomes. Collaborating with an...  View Details
      Keywords: Hybrid Work; Remote Work; Work-from-home; Field Experiment; Employees; Geographic Location; Performance; Work-Life Balance
      Citation
      SSRN
      Read Now
      Related
      Choudhury, Prithwiraj, Tarun Khanna, Christos A. Makridis, and Kyle Schirmann. "Is Hybrid Work the Best of Both Worlds? Evidence from a Field Experiment." Harvard Business School Working Paper, No. 22-063, March 2022.
      • 1
      • 2
      • …
      • 7
      • 8
      • →

      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