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- October 2024
- Article
Canary Categories
By: Eric Anderson, Chaoqun Chen, Ayelet Israeli and Duncan Simester
Past customer spending in a category is generally a positive signal of future customer spending. We show that there exist “canary categories” for which the reverse is true. Purchases in these categories are a signal that customers are less likely to return to that... View Details
Keywords: Churn; Churn Management; Churn/retention; Assortment Planning; Retail; Retailing; Retailing Industry; Preference Heterogeneity; Assortment Optimization; Customers; Retention; Consumer Behavior; Forecasting and Prediction; Retail Industry
Anderson, Eric, Chaoqun Chen, Ayelet Israeli, and Duncan Simester. "Canary Categories." Journal of Marketing Research (JMR) 61, no. 5 (October 2024): 872–890.
- 2023
- Article
Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness
By: Suraj Srinivas, Sebastian Bordt and Himabindu Lakkaraju
One of the remarkable properties of robust computer vision models is that their input-gradients are often aligned with human perception, referred to in the literature as perceptually-aligned gradients (PAGs). Despite only being trained for classification, PAGs cause... View Details
Srinivas, Suraj, Sebastian Bordt, and Himabindu Lakkaraju. "Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- 2023
- Working Paper
Targeting, Personalization, and Engagement in an Agricultural Advisory Service
By: Susan Athey, Shawn Cole, Shanjukta Nath and Jessica Zhu
ICT is increasingly used to deliver customized information in developing countries. We
examine whether individually targeting the timing of automated voice calls meaningfully
increases engagement in an agricultural advisory service. We define, estimate, and... View Details
Keywords: Developing Countries and Economies; Knowledge Dissemination; Customization and Personalization; Performance Effectiveness
Athey, Susan, Shawn Cole, Shanjukta Nath, and Jessica Zhu. "Targeting, Personalization, and Engagement in an Agricultural Advisory Service." Harvard Business School Working Paper, No. 24-006, August 2023.
- 2023
- Article
Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten
By: Himabindu Lakkaraju, Satyapriya Krishna and Jiaqi Ma
The Right to Explanation and the Right to be Forgotten are two important principles outlined to regulate algorithmic decision making and data usage in real-world applications. While the right to explanation allows individuals to request an actionable explanation for an... View Details
Keywords: Analytics and Data Science; AI and Machine Learning; Decision Making; Governing Rules, Regulations, and Reforms
Lakkaraju, Himabindu, Satyapriya Krishna, and Jiaqi Ma. "Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten." Proceedings of the International Conference on Machine Learning (ICML) 40th (2023): 17808–17826.
- July 2023
- Article
Design and Analysis of Switchback Experiments
By: Iavor I Bojinov, David Simchi-Levi and Jinglong Zhao
In switchback experiments, a firm sequentially exposes an experimental unit to a random treatment, measures its response, and repeats the procedure for several periods to determine which treatment leads to the best outcome. Although practitioners have widely adopted... View Details
Bojinov, Iavor I., David Simchi-Levi, and Jinglong Zhao. "Design and Analysis of Switchback Experiments." Management Science 69, no. 7 (July 2023): 3759–3777.
- 2023
- Article
Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse
By: Martin Pawelczyk, Teresa Datta, Johannes van-den-Heuvel, Gjergji Kasneci and Himabindu Lakkaraju
As machine learning models are increasingly being employed to make consequential decisions in real-world settings, it becomes critical to ensure that individuals who are adversely impacted (e.g., loan denied) by the predictions of these models are provided with a means... View Details
Pawelczyk, Martin, Teresa Datta, Johannes van-den-Heuvel, Gjergji Kasneci, and Himabindu Lakkaraju. "Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse." Proceedings of the International Conference on Learning Representations (ICLR) (2023).
- 2023
- Working Paper
Distributionally Robust Causal Inference with Observational Data
By: Dimitris Bertsimas, Kosuke Imai and Michael Lingzhi Li
We consider the estimation of average treatment effects in observational studies and propose a new framework of robust causal inference with unobserved confounders. Our approach is based on distributionally robust optimization and proceeds in two steps. We first... View Details
Bertsimas, Dimitris, Kosuke Imai, and Michael Lingzhi Li. "Distributionally Robust Causal Inference with Observational Data." Working Paper, February 2023.
- 2022
- Working Paper
Slowly Varying Regression under Sparsity
By: Dimitris Bertsimas, Vassilis Digalakis Jr, Michael Lingzhi Li and Omar Skali Lami
We consider the problem of parameter estimation in slowly varying regression models with sparsity constraints. We formulate the problem as a mixed integer optimization problem and demonstrate that it can be reformulated exactly as a binary convex optimization problem... View Details
Keywords: Mathematical Methods
Bertsimas, Dimitris, Vassilis Digalakis Jr, Michael Lingzhi Li, and Omar Skali Lami. "Slowly Varying Regression under Sparsity." Working Paper, September 2022.
- March 2022
- Article
Where to Locate COVID-19 Mass Vaccination Facilities?
By: Dimitris Bertsimas, Vassilis Digalakis Jr, Alexander Jacquillat, Michael Lingzhi Li and Alessandro Previero
The outbreak of COVID-19 led to a record-breaking race to develop a vaccine. However, the limited vaccine capacity creates another massive challenge: how to distribute vaccines to mitigate the near-end impact of the pandemic? In the United States in particular, the new... View Details
Keywords: Vaccines; COVID-19; Health Care and Treatment; Health Pandemics; Performance Effectiveness; Analytics and Data Science; Mathematical Methods
Bertsimas, Dimitris, Vassilis Digalakis Jr, Alexander Jacquillat, Michael Lingzhi Li, and Alessandro Previero. "Where to Locate COVID-19 Mass Vaccination Facilities?" Naval Research Logistics Quarterly 69, no. 2 (March 2022): 179–200.
- 2021
- Article
Designing, Not Checking, for Policy Robustness: An Example with Optimal Taxation
By: Benjamin B. Lockwood, Afras Sial and Matthew C. Weinzierl
Economists typically check the robustness of their results by comparing them across plausible ranges of parameter values and model structures. A preferable approach to robustness—for the purposes of policymaking and evaluation—is to design policy that takes these... View Details
Lockwood, Benjamin B., Afras Sial, and Matthew C. Weinzierl. "Designing, Not Checking, for Policy Robustness: An Example with Optimal Taxation." Tax Policy and the Economy 35 (2021).
- January 2021
- Article
Turbulence, Firm Decentralization and Growth in Bad Times
By: Philippe Aghion, Nicholas Bloom, Brian Lucking, Raffaella Sadun and John Van Reenen
What is the optimal form of firm organization during “bad times”? We present a model of delegation within the firm to show that the effect is ambiguous. The greater turbulence following macro shocks may benefit decentralized firms because the value of local information... View Details
Keywords: Decentralization; Growth; Turbulence; Great Recession; Organizational Design; System Shocks; Economic Growth; Performance
Aghion, Philippe, Nicholas Bloom, Brian Lucking, Raffaella Sadun, and John Van Reenen. "Turbulence, Firm Decentralization and Growth in Bad Times." American Economic Journal: Applied Economics 13, no. 1 (January 2021): 133–169.
- Article
Robust and Stable Black Box Explanations
By: Himabindu Lakkaraju, Nino Arsov and Osbert Bastani
As machine learning black boxes are increasingly being deployed in real-world applications, there
has been a growing interest in developing post hoc explanations that summarize the behaviors
of these black boxes. However, existing algorithms for generating such... View Details
Lakkaraju, Himabindu, Nino Arsov, and Osbert Bastani. "Robust and Stable Black Box Explanations." Proceedings of the International Conference on Machine Learning (ICML) 37th (2020): 5628–5638. (Published in PMLR, Vol. 119.)
- 2020
- Working Paper
Designing, Not Checking, for Policy Robustness: An Example with Optimal Taxation
By: Benjami Lockwood, Afras Y. Sial and Matthew C. Weinzierl
Economists typically check the robustness of their results by comparing them across plausible ranges of parameter values and model structures. A preferable approach to robustness—for the purposes of policymaking and evaluation—is to design policy that takes these... View Details
Lockwood, Benjami, Afras Y. Sial, and Matthew C. Weinzierl. "Designing, Not Checking, for Policy Robustness: An Example with Optimal Taxation." NBER Working Paper Series, No. 28098, November 2020.
- 2020
- Working Paper
Design and Analysis of Switchback Experiments
By: Iavor I Bojinov, David Simchi-Levi and Jinglong Zhao
In switchback experiments, a firm sequentially exposes an experimental unit to a random treatment, measures its response, and repeats the procedure for several periods to determine which treatment leads to the best outcome. Although practitioners have widely adopted... View Details
Bojinov, Iavor I., David Simchi-Levi, and Jinglong Zhao. "Design and Analysis of Switchback Experiments." Harvard Business School Working Paper, No. 21-034, September 2020.
- November 2018 (Revised May 2019)
- Case
California Closets: Organizing the Customer Experience
By: Boris Groysberg and Annelena Lobb
California Closets had used robust net promoter score (NPS) data, surveyed across its locations, to create a more consistent and satisfying customer experience. CEO Bill Barton wanted to further optimize the customer experience around best practices. He also wanted to... View Details
Keywords: Net Promoter Score; Customer Relationship Management; Customer Satisfaction; Customers; Acquisition; Demographics; Strategy
Groysberg, Boris, and Annelena Lobb. "California Closets: Organizing the Customer Experience." Harvard Business School Case 419-004, November 2018. (Revised May 2019.)
- 2018
- Working Paper
Opportunistic Returns and Dynamic Pricing: Empirical Evidence from Online Retailing in Emerging Markets
By: Chaithanya Bandi, Antonio Moreno, Donald Ngwe and Zhiji Xu
We investigate how dynamic pricing can lead to more product returns in the online retail industry. Using detailed sales data of more than two million transactions from the Indian online retail market, where price promotions are very common, we document two types of... View Details
Keywords: Cash On Delivery; Dynamic Pricing; Online Retail; Payment Methods; Strategic Customer Behavior; Opportunistic Returns; Price; Policy; Consumer Behavior; Emerging Markets; Retail Industry
Bandi, Chaithanya, Antonio Moreno, Donald Ngwe, and Zhiji Xu. "Opportunistic Returns and Dynamic Pricing: Empirical Evidence from Online Retailing in Emerging Markets." Harvard Business School Working Paper, No. 19-030, September 2018.
- Article
Popular Acceptance of Inequality Due to Innate Brute Luck and Support for Classical Benefit-based Taxation
U.S. survey respondents' views on distributive justice differ in two specific, related ways from what is conventionally assumed in modern optimal tax research. When expressing their preferences over allocations in stylized, hypothetical scenarios meant to isolate key... View Details
Keywords: Optimal Taxation; Welfarism; Luck; Benefit-based Taxation; Taxation; Equality and Inequality; Attitudes
Weinzierl, Matthew C. "Popular Acceptance of Inequality Due to Innate Brute Luck and Support for Classical Benefit-based Taxation." Journal of Public Economics 155 (November 2017): 54–63. (Also Harvard Business School Working Paper, No. 16-104, March 2016; revised July 2016, and NBER Working Paper Series, No. 22462, July 2016. See Notes on Fortune article.)
- May 2017
- Article
Experimental Evidence of Pooling Outcomes Under Information Asymmetry
By: William Schmidt and Ryan W. Buell
Operational decisions under information asymmetry can signal a firm's prospects to less-informed parties, such as investors, customers, competitors, and regulators. Consequently, managers in these settings often face a tradeoff between making an optimal decision and... View Details
Keywords: Behavioral Decision Research; Information Asymmetry; Signaling; Decision Choices and Conditions; Alignment
Schmidt, William, and Ryan W. Buell. "Experimental Evidence of Pooling Outcomes Under Information Asymmetry." Management Science 63, no. 5 (May 2017): 1586–1605.
- October 2011
- Article
The Surprising Power of Age-Dependent Taxes
This article provides a new, empirically driven application of the dynamic Mirrleesian framework by studying a feasible and potentially powerful tax reform: age-dependent labor income taxation. I show analytically how age dependence improves policy on both the... View Details
Weinzierl, Matthew C. "The Surprising Power of Age-Dependent Taxes." Review of Economic Studies 78, no. 4 (October 2011): 1490–1518. (Also Harvard Business School Working Paper, No. 11-114, May 2011.)
- February 2009
- Article
Optimal Reserve Management and Sovereign Debt
By: Laura Alfaro and Fabio Kanczuk
Most models currently used to determine optimal foreign reserve holdings take the level of international debt as given. However, given the sovereign's willingness-to-pay incentive problems, reserve accumulation may reduce sustainable debt levels. In addition, assuming... View Details
Keywords: Borrowing and Debt; Motivation and Incentives; Decisions; Emerging Markets; Balance and Stability; Earnings Management; Policy; Interest Rates; International Finance; Cost
Alfaro, Laura, and Fabio Kanczuk. "Optimal Reserve Management and Sovereign Debt." Journal of International Economics 77, no. 1 (February 2009): 23–36. (Also Harvard Business School Working Paper, No. 07-010, 2006 and NBER Working Paper No. 13216.)