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    • All HBS Web  (157)
      • Faculty Publications  (35)

      Simulation Methods Remove Simulation Methods →

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      • November 2022
      • Article

      Measuring Inequality beyond the Gini Coefficient May Clarify Conflicting Findings

      By: Kristin Blesch, Oliver P. Hauser and Jon M. Jachimowicz
      Prior research has found mixed results on how economic inequality is related to various outcomes. These contradicting findings may in part stem from a predominant focus on the Gini coefficient, which only narrowly captures inequality. Here, we conceptualize the...  View Details
      Keywords: Economic Inequalty; Gini Coefficient; Income Inequality; Equality and Inequality; Social Issues; Health; Status and Position
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      Blesch, Kristin, Oliver P. Hauser, and Jon M. Jachimowicz. "Measuring Inequality beyond the Gini Coefficient May Clarify Conflicting Findings." Nature Human Behaviour 6, no. 11 (November 2022): 1525–1536.
      • 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
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      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.
      • 2022
      • Article

      Nonparametric Subset Scanning for Detection of Heteroscedasticity

      By: Charles R. Doss and Edward McFowland III
      We propose Heteroscedastic Subset Scan (HSS), a novel method for identifying covariates that are responsible for violations of the homoscedasticity assumption in regression settings. Viewing the problem as one of anomalous pattern detection, we use subset scanning...  View Details
      Keywords: Scan Statistics; Anomaly Detection; Regression; Model Diagnostics
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      Doss, Charles R., and Edward McFowland III. "Nonparametric Subset Scanning for Detection of Heteroscedasticity." Journal of Computational and Graphical Statistics 31, no. 3 (2022): 813–823.
      • Article

      Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)

      By: Eva Ascarza and Ayelet Israeli

      An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those “protected”...  View Details

      Keywords: Algorithm Bias; Personalization; Targeting; Generalized Random Forests (GRF); Discrimination; Customization and Personalization; Decision Making; Fairness; Mathematical Methods
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      Ascarza, Eva, and Ayelet Israeli. "Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)." e2115126119. Proceedings of the National Academy of Sciences 119, no. 11 (March 8, 2022).
      • March 2022
      • Article

      Estimating the Effectiveness of Permanent Price Reductions for Competing Products Using Multivariate Bayesian Structural Time Series Models

      By: Fiammetta Menchetti and Iavor Bojinov
      Researchers regularly use synthetic control methods for estimating causal effects when a sub-set of units receive a single persistent treatment, and the rest are unaffected by the change. In many applications, however, units not assigned to treatment are nevertheless...  View Details
      Keywords: Causal Inference; Partial Interference; Synthetic Controls; Bayesian Structural Time Series; Mathematical Methods
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      Menchetti, Fiammetta, and Iavor Bojinov. "Estimating the Effectiveness of Permanent Price Reductions for Competing Products Using Multivariate Bayesian Structural Time Series Models." Annals of Applied Statistics 16, no. 1 (March 2022): 414–435.
      • 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.)
      • November 2020
      • Article

      Taxation in Matching Markets

      By: Arnaud Dupuy, Alfred Galichon, Sonia Jaffe and Scott Duke Kominers
      We analyze the effects of taxation in two-sided matching markets, i.e., markets in which all agents have heterogeneous preferences over potential partners. In matching markets, taxes can generate inefficiency on the allocative margin by changing who is matched to whom,...  View Details
      Keywords: Matching Markets; Labor Markets; Taxation; Labor; Markets
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      Dupuy, Arnaud, Alfred Galichon, Sonia Jaffe, and Scott Duke Kominers. "Taxation in Matching Markets." International Economic Review 61, no. 4 (November 2020): 1591–1634.
      • 2019
      • Article

      Time Series Experiments and Causal Estimands: Exact Randomization Tests and Trading

      By: Iavor I Bojinov and Neil Shephard
      We define causal estimands for experiments on single time series, extending the potential outcome framework to dealing with temporal data. Our approach allows the estimation of a broad class of these estimands and exact randomization based p-values for testing causal...  View Details
      Keywords: Causality; Nonparametric; Potential Outcomes; Trading Costs; Mathematical Methods
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      Bojinov, Iavor I., and Neil Shephard. "Time Series Experiments and Causal Estimands: Exact Randomization Tests and Trading." Journal of the American Statistical Association 114, no. 528 (2019): 1665–1682.
      • 2019
      • Article

      Ridesharing with Driver Location Preferences

      By: Duncan Rheingans-Yoo, Scott Duke Kominers, Hongyao Ma and David C. Parkes
      We study revenue-optimal pricing and driver compensation in ridesharing platforms when drivers have heterogeneous preferences over locations. If a platform ignores drivers' location preferences, it may make inefficient trip dispatches; moreover, drivers may strategize...  View Details
      Keywords: Ridesharing; Pricing; Compensation and Benefits; Geographic Location; Market Design; Mathematical Methods
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      Rheingans-Yoo, Duncan, Scott Duke Kominers, Hongyao Ma, and David C. Parkes. "Ridesharing with Driver Location Preferences." Proceedings of the International Joint Conference on Artificial Intelligence (2019): 557–564.
      • May 2018
      • Article

      Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change

      By: Edward L. Glaeser, Hyunjin Kim and Michael Luca
      Data from digital platforms have the potential to improve our understanding of gentrification and enable new measures of how neighborhoods change in close to real time. Combining data on businesses from Yelp with data on gentrification from the Census, Federal Housing...  View Details
      Keywords: Forecasting Models; Simulation Methods; Regional Economic Activity: Growth, Development, Environmental Issues, And Changes; Geographic Location; Local Range; Transition; Analytics and Data Science; Measurement and Metrics; Economic Growth; Forecasting and Prediction
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      Glaeser, Edward L., Hyunjin Kim, and Michael Luca. "Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change." AEA Papers and Proceedings 108 (May 2018): 77–82.
      • November 2021
      • Article

      Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data

      By: William Herlands, Edward McFowland III, Andrew Gordon Wilson and Daniel B. Neill
      Identifying anomalous patterns in real-world data is essential for understanding where, when, and how systems deviate from their expected dynamics. Yet methods that separately consider the anomalousness of each individual data point have low detection power for subtle,...  View Details
      Keywords: Pattern Detection; Subset Scanning; Gaussian Processes; Mathematical Methods
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      Herlands, William, Edward McFowland III, Andrew Gordon Wilson, and Daniel B. Neill. "Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data." Proceedings of Machine Learning Research (PMLR) 84 (2018): 425–434. (Also presented at the 21st International Conference on Artificial Intelligence and Statistics (AISTATS), 2018.)
      • 2018
      • Working Paper

      Efficient Discovery of Heterogeneous Treatment Effects in Randomized Experiments via Anomalous Pattern Detection

      By: Edward McFowland III, Sriram Somanchi and Daniel B. Neill
      In the recent literature on estimating heterogeneous treatment effects, each proposed method makes its own set of restrictive assumptions about the intervention’s effects and which subpopulations to explicitly estimate. Moreover, the majority of the literature provides...  View Details
      Keywords: Causal Inference; Program Evaluation; Algorithms; Distributional Average Treatment Effect; Treatment Effect Subset Scan; Heterogeneous Treatment Effects
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      McFowland III, Edward, Sriram Somanchi, and Daniel B. Neill. "Efficient Discovery of Heterogeneous Treatment Effects in Randomized Experiments via Anomalous Pattern Detection." Working Paper, 2018. (2nd Round Revision.)
      • May 2017
      • Article

      Agent-based Modeling: A Guide for Social Psychologists

      By: Joshua Conrad Jackson, David Rand, Kevin Lewis, Michael I. Norton and Kurt Gray
      Agent-based modeling is a longstanding but underused method that allows researchers to simulate artificial worlds for hypothesis testing and theory building. Agent-based models (ABMs) offer unprecedented control and statistical power by allowing researchers to...  View Details
      Keywords: Social Psychology; Marketing; Mathematical Methods
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      Jackson, Joshua Conrad, David Rand, Kevin Lewis, Michael I. Norton, and Kurt Gray. "Agent-based Modeling: A Guide for Social Psychologists." Social Psychological & Personality Science 8, no. 4 (May 2017): 387–395.
      • 2016
      • Article

      Penalized Fast Subset Scanning

      By: Skyler Speakman, Sriram Somanchi, Edward McFowland III and Daniel B. Neill
      We present the penalized fast subset scan (PFSS), a new and general framework for scalable and accurate pattern detection. PFSS enables exact and efficient identification of the most anomalous subsets of the data, as measured by a likelihood ratio scan statistic....  View Details
      Keywords: Disease Surveillance; Likelihood Ratio Statistic; Pattern Detection; Scan Statistic; Mathematical Methods
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      Speakman, Skyler, Sriram Somanchi, Edward McFowland III, and Daniel B. Neill. "Penalized Fast Subset Scanning." Journal of Computational and Graphical Statistics 25, no. 2 (2016): 382–404. (Selected for “Best of JCGS” invited session by the journal’s editor in chief.)
      • Article

      Transition to Clean Technology

      By: Daron Acemoglu, Ufuk Akcigit, Douglas Hanley and William R. Kerr
      We develop a microeconomic model of endogenous growth where clean and dirty technologies compete in production and innovation, in the sense that research can be directed to either clean or dirty technologies. If dirty technologies are more advanced to start with, the...  View Details
      Keywords: Technological Innovation; Entrepreneurship; Environmental Sustainability; Green Technology Industry
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      Acemoglu, Daron, Ufuk Akcigit, Douglas Hanley, and William R. Kerr. "Transition to Clean Technology." Special Issue on Climate Change and the Economy. Journal of Political Economy 124, no. 2 (February 2016): 52–104.
      • 2015
      • Article

      Scalable Detection of Anomalous Patterns With Connectivity Constraints

      By: Skyler Speakman, Edward McFowland III and Daniel B. Neill
      We present GraphScan, a novel method for detecting arbitrarily shaped connected clusters in graph or network data. Given a graph structure, data observed at each node, and a score function defining the anomalousness of a set of nodes, GraphScan can efficiently and...  View Details
      Keywords: Biosurveillance; Event Detection; Graph Mining; Scan Statistics; Spatial Scan Statistic
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      Speakman, Skyler, Edward McFowland III, and Daniel B. Neill. "Scalable Detection of Anomalous Patterns With Connectivity Constraints." Journal of Computational and Graphical Statistics 24, no. 4 (2015): 1014–1033.
      • April 2014
      • Tutorial

      Conjoint Analysis: Online Tutorial

      By: Elie Ofek and Olivier Toubia
      The Conjoint Analysis: Online Tutorial is an interactive pedagogical vehicle intended to facilitate understanding of one of the most popular market research methods in academia and practice, namely conjoint analysis. The aim is to provide students or executives going...  View Details
      Keywords: Market Research; Conjoint Analysis; Market Segmentation; Pricing; Marketing Strategy
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      Ofek, Elie, and Olivier Toubia. Conjoint Analysis: Online Tutorial. Harvard Business School Tutorial 514-712, April 2014.
      • June 2013 (Revised November 2022)
      • Exercise

      Competition Simulator Exercise

      By: Eric J. Van den Steen
      In the Competition Simulator Exercise, students explore through trial and error some important economic foundations of competitive strategy and managerial economics. In particular, the nine simulator exercises let students explore horizontal differentiation with and...  View Details
      Keywords: Competition; Economics; Game Theory; Competitive Strategy; Learning; Mathematical Methods; Analysis
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      Van den Steen, Eric J. "Competition Simulator Exercise." Harvard Business School Exercise 713-804, June 2013. (Revised November 2022.)
      • 2011
      • Article

      Scalable Detection of Anomalous Patterns With Connectivity Constraints

      By: Skyler Speakman, Edward McFowland III and Daniel B. Neill
      We present GraphScan, a novel method for detecting arbitrarily shaped connected clusters in graph or network data. Given a graph structure, data observed at each node, and a score function defining the anomalousness of a set of nodes, GraphScan can efficiently and...  View Details
      Keywords: Biosurveillance; Event Detection; Graph Mining; Scan Statistics; Spatial Scan Statistic
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      Speakman, Skyler, Edward McFowland III, and Daniel B. Neill. "Scalable Detection of Anomalous Patterns With Connectivity Constraints." Emerging Health Threats Journal 4 (2011): 11121.
      • February 2010
      • Supplement

      Real Property Negotiation Game (CW): Excel Model

      By: Arthur I. Segel, John Vogel and Justin Seth Ginsburgh
      This Excel model is used to analyze the deals made in The Real Property Negotiation Game, which simulates the experience negotiating the sale, purchase, or financing of a property.  View Details
      Keywords: Property; Negotiation Deal; Sales; Financing and Loans; Mathematical Methods; Real Estate Industry
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      Segel, Arthur I., John Vogel, and Justin Seth Ginsburgh. "Real Property Negotiation Game (CW): Excel Model." Harvard Business School Spreadsheet Supplement 210-703, February 2010.
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