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- Research Summary
Hybrid organizing
By: Julie Battilana
While historically the commercial and social sectors have evolved on fairly separate tracks, over the last 30 years we have witnessed a blurring of the boundaries between these two sectors. In an effort to account for this transition, Professor Battilana’s second... View Details
- 2024
- Chapter
Inflation and Misallocation in New Keynesian Models
By: Alberto Cavallo, Francesco Lippi and Ken Miyahara
The New Keynesian framework implies that sluggish price adjustment results in a distorted allocation of resources. We use a simple model to quantify these unobservable distortions, using data that depict the price-setting behavior of firms, specifically the frequency... View Details
- Research Summary
Internalizing Global Value Chains: A Firm-Level Analysis
By: Laura Alfaro
In recent decades, advances in information and communication technology and falling trade barriers have led firms to retain within their boundaries and in their domestic economies only a subset of their production stages. A key decision facing firms worldwide is the... View Details
- Teaching Interest
Interpretability and Explainability in Machine Learning
As machine learning models are increasingly being employed to aid decision makers in high-stakes settings such as healthcare and criminal justice, it is important to ensure that the decision makers correctly understand and consequent trust the functionality of these... View Details
- Article
Learning by Thinking: The Role of Reflection in Individual Learning
By: Giada Di Stefano, Francesca Gino, Gary P. Pisano and Bradley R. Staats
It is common wisdom that practice makes perfect. And, in fact, we find evidence that when given a choice between practicing a task and reflecting on their previously accumulated practice, most people opt for the former. We argue in this paper that this preference is... View Details
- 2023
- Chapter
Marketing Through the Machine’s Eyes: Image Analytics and Interpretability
By: Shunyuan Zhang, Flora Feng and Kannan Srinivasan
he growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility—if only the... View Details
- Forthcoming
- Article
On the Representativeness of Voter Turnout
By: Louis Kaplow and Scott Duke Kominers
Prominent theory research on voting analyzes a variety of models in which expected pivotality drives voters' turnout decisions and hence determines voting outcomes. It is recognized, however, that such work is at odds with Downs's paradox: in practice, many... View Details
- Research Summary
Optimal Reserve Management and Sovereign Debt (with Fabio Kanczuk)
By: Laura Alfaro
Most models currently used to determine optimal foreign reserve holdings take the level of international debt as given. Some of the implications of this analysis, however, may not be generalized once one considers the joint decision to hold debt and reserves by a... View Details
- Teaching Interest
Overview
By: John F. Batter
As as Senior Lecturer I teach the EC course Law, Management and Entrepreneurship (cross-listed in the General Management and Entrepreneurial Management Units) in both the Fall and Spring semesters. While I have retired from my public and private company litigation... View Details
- Research Summary
Overview
By: Feng Zhu
Professor Zhu’s research focuses on the design of platform business models and its impact on platform performance. Platforms have become central to our economy. A platform is a product or service that enables two or more customer groups to interact. For example,... View Details
- Research Summary
Overview
My academic research centers on uncovering and closing gaps between the theory and reality of tax policy. My main contribution has been to identify and address a mismatch between the goals for taxation typically assumed in theory and the goals the public and... View Details
- Research Summary
Overview
By: Iavor I. Bojinov
Over the last decade, technology companies like Amazon, Google, and Netflix have pioneered data-driven research and development processes centered on massive experimentation. However, as companies increase the breadth and scale of their experiments to millions of... View Details
- Research Summary
Overview
By: Shunyuan Zhang
Professor Zhang uses machine learning to address marketing problems that have arisen within the nascent sharing economy. She conducts rigorous analyses of structured and unstructured data generated by new sharing economy platforms to address important issues emerging... View Details
- Research Summary
Overview
By: Jorge Tamayo
Professor Tamayo’s research focuses on theoretical modeling and structural estimation of firm decision-making and productivity.
Professor Tamayo studies dynamic competition for customer membership. Generally, firms that implement a membership model charge a... View Details
Professor Tamayo studies dynamic competition for customer membership. Generally, firms that implement a membership model charge a... View Details
- Research Summary
Overview
Engaged with field work in South Asia and East Africa, Professor Hussam places a focus on exploring questions with strong theoretical motivation in the economics literature as well as relevant downstream policy implications. Her research spans four broad interests.... View Details
- Research Summary
Overview
Professor Ferreira's research primarily focuses on how retailers can use algorithms to make better revenue management decisions, including pricing, product display, and assortment planning. In the retail industry, anticipating consumer demand is arguably one of the... View Details
- Forthcoming
- Article
Preference Externality Estimators: A Comparison of Border Approaches and IVs
By: Xi Ling, Wesley R. Hartmann and Tomomichi Amano
This paper compares two estimators—the Border Approach and an Instrumental Variable (IV) estimator—using a unified framework where identifying variation arises from “preference externalities,” following the intuition in Waldfogel (2003). We highlight two dimensions in... View Details
- Research Summary
Sovereign Debt as a Contingent Claim: A Quantitative Approach (joint with Fabio Kanczuk)
By: Laura Alfaro
We construct a dynamic equilibrium model with contingent service and adverse selection to quantitatively study sovereign debt. In the model, benefits of defaulting are tempered by higher future interest rates. For a wide parameter, the only equilibrium is one in which... View Details
- Forthcoming
- Article
Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments
By: Kosuke Imai and Michael Lingzhi Li
Researchers are increasingly turning to machine learning (ML) algorithms to investigate causal heterogeneity in randomized experiments. Despite their promise, ML algorithms may fail to accurately ascertain heterogeneous treatment effects under practical settings with... View Details
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