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Publications

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  • All HBS Web  (17)
    • Faculty Publications  (6)

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    • All HBS Web  (17)
      • Faculty Publications  (6)

      Bayesian Statistics Remove Bayesian Statistics →

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      • August 2021
      • Article

      Multiple Imputation Using Gaussian Copulas

      By: F.M. Hollenbach, I. Bojinov, S. Minhas, N.W. Metternich, M.D. Ward and A. Volfovsky
      Missing observations are pervasive throughout empirical research, especially in the social sciences. Despite multiple approaches to dealing adequately with missing data, many scholars still fail to address this vital issue. In this paper, we present a simple-to-use...  View Details
      Keywords: Missing Data; Bayesian Statistics; Imputation; Categorical Data; Estimation
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      Hollenbach, F.M., I. Bojinov, S. Minhas, N.W. Metternich, M.D. Ward, and A. Volfovsky. "Multiple Imputation Using Gaussian Copulas." Special Issue on New Quantitative Approaches to Studying Social Inequality. Sociological Methods & Research 50, no. 3 (August 2021): 1259–1283. (0049124118799381.)
      • December 2019
      • Technical Note

      Technical Note on Bayesian Statistics and Frequentist Power Calculations

      By: Amitabh Chandra and Ariel Dora Stern
      This Technical Note provides an introduction to Bayes’ Rule and the statistical intuition that stems from it. In this note, we review the concepts that underlie Bayesian statistics, and we offer several simple mathematical examples to illustrate applications of Bayes’...  View Details
      Keywords: Bayesian Statistics; Mathematical Methods
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      Chandra, Amitabh, and Ariel Dora Stern. "Technical Note on Bayesian Statistics and Frequentist Power Calculations." Harvard Business School Technical Note 620-032, December 2019.
      • Article

      Learning from Potentially Biased Statistics: Household Inflation Perceptions and Expectations in Argentina

      By: Alberto Cavallo, Guillermo Cruces and Ricardo Perez-Truglia
      When forming expectations, households may be influenced by perceived bias in the information they receive. In this paper, we study how individuals learn from potentially biased statistics using data from both a natural experiment and a survey experiment during a...  View Details
      Keywords: Inflation Expectations; Bayesian Estimation; Inflation and Deflation; Information; Household; Behavior; Argentina
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      Cavallo, Alberto, Guillermo Cruces, and Ricardo Perez-Truglia. "Learning from Potentially Biased Statistics: Household Inflation Perceptions and Expectations in Argentina." Brookings Papers on Economic Activity (Spring 2016): 59–108.
      • 2016
      • Article

      Does Volunteering Improve Well-being?

      By: A.V. Whillans, S.C. Seider, R. Dwyer, L. Chen, S. Novick, K.J. Graminga, B.A. Mitchell, V. Savalei, S.S. Dickerson and E.W. Dunn
      Does volunteering causally improve well-being? To empirically test this question, we examined one instantiation of volunteering that is common at post-secondary institutions across North America: community service learning (CSL). CSL is a form of experiential learning...  View Details
      Keywords: Prosocial Behavior; College Students; Bayesian Statistics; Education; Well-being
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      Whillans, A.V., S.C. Seider, R. Dwyer, L. Chen, S. Novick, K.J. Graminga, B.A. Mitchell, V. Savalei, S.S. Dickerson, and E.W. Dunn. "Does Volunteering Improve Well-being?" Comprehensive Results in Social Psychology 1, nos. 1-3 (2016): 35–50.
      • Article

      Fast Generalized Subset Scan for Anomalous Pattern Detection

      By: Edward McFowland III, Skyler Speakman and Daniel B. Neill
      We propose Fast Generalized Subset Scan (FGSS), a new method for detecting anomalous patterns in general categorical data sets. We frame the pattern detection problem as a search over subsets of data records and attributes, maximizing a nonparametric scan statistic...  View Details
      Keywords: Pattern Detection; Anomaly Detection; Knowledge Discovery; Bayesian Networks; Scan Statistics
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      McFowland III, Edward, Skyler Speakman, and Daniel B. Neill. "Fast Generalized Subset Scan for Anomalous Pattern Detection." Art. 12. Journal of Machine Learning Research 14 (2013): 1533–1561.
      • September 1990
      • Article

      Competition on Many Fronts: A Stackelberg Signaling Equilibrium

      By: Jerry R. Green and Jean-Jacques Laffont
      An economic agent, the incumbent, is operating in many environments at the same time. These may be locations, markets, or specific activities. He is informed of the particular conditions relevant to each situation. His action in each case is observable by another...  View Details
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      Green, Jerry R., and Jean-Jacques Laffont. "Competition on Many Fronts: A Stackelberg Signaling Equilibrium." Games and Economic Behavior 2, no. 3 (September 1990): 247–272.
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