Latent Variable Models - Publications - Faculty & Research - Harvard Business School

Filter Results: (339)

Filter Results: (339)

Show Results For

← Page 3 of 339 Results →

Article

Physician-Induced Demand for Medical Care

By: Jerry R. Green

This paper addresses the theoretical models designed to ascertain the existence of a variable level of physicians' activity in shifting the demand of their patients. Two basic approaches are followed: equilibrium models of the demand for health care, and disequilibrium... View Details

Keywords: Physicians; Economic Equilibrium; Monopolistic Competition; Economic Competition; Medical Care

Find at Harvard

March 2004
Article

Inflation, Inflation Variability, and Corruption

By: Miguel Braun and Rafael Di Tella

We present a model where agents can inflate the cost of goods needed to start an investment project and inflation variability increases monitoring costs. We show that inflation variability can lead to higher corruption and lower investment. We document a positive... View Details

Keywords: Inflation and Deflation; Crime and Corruption

Find at Harvard

Forthcoming
Article

Institutional Corporate Bond Pricing

By: Ishita Sen, Lorenzo Bretscher, Lukas Schmid and Varun Sharma

We propose an equilibrium corporate bond pricing model that accommodates the heterogeneity in institutional investors' preferences and mandates in an empirically tractable way. Our model, estimated on rich holdings data, quantifies investors' preferences and demand... View Details

Keywords: Corporate Bonds; Demand Systems; Insurance Companies; Mutual Funds; Liquidity; Bonds; Price; Investment Funds

2020
Working Paper

Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach

By: Eva Ascarza

The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to understand consumers' preferences and precisely capture how these preferences may differ across customers. Only by understanding customer heterogeneity, firms can... View Details

Keywords: Customer Management; Targeting; Deep Exponential Families; Probabilistic Machine Learning; Cold Start Problem; Customer Relationship Management; Customer Value and Value Chain; Consumer Behavior; Analytics and Data Science; Mathematical Methods; Retail Industry

Do Bonuses Enhance Sales Productivity? A Dynamic Structural Analysis of Bonus-Based Compensation Plans

We estimate a dynamic structural model of sales force response to a bonus based compensation plan. Substantively, the paper sheds insights on how different elements of the compensation plan enhance productivity. We find evidence that: (1) bonuses enhance productivity... View Details

January 2021
Article

Machine Learning for Pattern Discovery in Management Research

By: Prithwiraj Choudhury, Ryan Allen and Michael G. Endres

Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used for exploratory inductive or abductive research, or for post-hoc analysis of regression results to detect... View Details

Keywords: Machine Learning; Supervised Machine Learning; Induction; Abduction; Exploratory Data Analysis; Pattern Discovery; Decision Trees; Random Forests; Neural Networks; ROC Curve; Confusion Matrix; Partial Dependence Plots; AI and Machine Learning

Find at Harvard

Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem

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,... View Details

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

Keywords: AI and Machine Learning; Mathematical Methods

January 22, 2015
Other Article

Are Capital Controls Effective? Firm-level Evidence from Brazil

By: Laura Alfaro, Anusha Chari and Fabio Kanczuk

Capital controls are back in fashion. This column discusses new firm-level evidence from Brazil showing that capital controls segment international financial markets, reduce external financing, and lower firm-level investment. They disproportionately affect small,... View Details

March–April 2014
Article

Do Bonuses Enhance Sales Productivity? A Dynamic Structural Analysis of Bonus-Based Compensation Plans

By: Doug J. Chung, Thomas Steenburgh and K. Sudhir

We estimate a dynamic structural model of sales force response to a bonus based compensation plan. Substantively, the paper sheds insights on how different elements of the compensation plan enhance productivity. We find evidence that: (1) bonuses enhance productivity... View Details

Keywords: Performance Productivity; Salesforce Management; Compensation and Benefits

Find at Harvard

2010
Working Paper

Do Bonuses Enhance Sales Productivity? A Dynamic Structural Analysis of Bonus-Based Compensation Plans

By: Doug J. Chung, Thomas J. Steenburgh and K. Sudhir

We estimate a dynamic structural model of sales force response to a bonus based compensation plan. The paper has two main methodological innovations: First, we implement empirically the method proposed by Arcidiacono and Miller (2010) to accommodate unobserved latent... View Details

Keywords: Compensation and Benefits; Performance Productivity; Mathematical Methods; Salesforce Management; Motivation and Incentives

winter 2003
Article

Massively Categorical Variables: Revealing the Information in Zip Codes

We introduce the idea of a massively categorical variable, a variable such as zip code that takes on too many values to be treated in the standard manner, and show how to use it directly as explanatory variables in an econometric model. In an application of this... View Details

Keywords: Strategy; Analytics and Data Science; Behavior; Marketing; Standards; Finance

Find at Harvard

October 1, 2021
Article

An Evaluation of Cross-efficiency Methods: With an Application to Warehouse Performance.

By: B.M. Balk, M.R. De Koster, Christian Kaps and J.L. Zofio

Cross-efficiency measurement is an extension of Data Envelopment Analysis that allows for tie-breaking ranking of the Decision Making Units (DMUs) using all the peer evaluations. In this article we examine the theory of cross-efficiency measurement by comparing a... View Details

Keywords: Efficiency Analysis; Performance Benchmarking; Warehousing; Analytics and Data Science; Performance Evaluation; Measurement and Metrics; Mathematical Methods

February 2018 (Revised December 2020)
Case

People Analytics at Teach For America (A)

By: Jeffrey T. Polzer and Julia Kelley

As of mid-2016, national nonprofit Teach For America (TFA) had struggled with three consecutive years of declining application totals, and senior management was re-examining the organization's strategy, including recruitment and selection. A few months earlier, former... View Details

Keywords: Recruitment; Selection and Staffing; Analysis; Forecasting and Prediction

2001
Working Paper

Strategies to Fight Ad-sponsored Rivals

By: Ramon Casadesus-Masanell and Feng Zhu

We analyze the optimal strategy of a high-quality incumbent that faces a low-quality ad-sponsored competitor. In addition to competing through adjustments of tactical variables such as price or the number of ads a product carries, we allow the incumbent to consider... View Details

Keywords: Advertising; Business Model; Competition; Competitive Strategy

13 Mar 2025
HBS Seminar

Sonny Tambe, Wharton

February 2005 (Revised November 2016)
Background Note

Forecasting the Adoption of a New Product

Provides tools and methodologies that allow forecasting demand for innovative new products. Highlights the Bass model—the theory behind it and ways to determine its parameters. Provides a detailed example of how to use the Bass model to forecast demand for satellite... View Details

Keywords: Forecasting and Prediction; Innovation and Invention; Marketing; Demand and Consumers; Mathematical Methods; Competition

Strategies to Fight Ad-sponsored Rivals

We analyze the optimal strategy of a high-quality incumbent that faces a low-quality ad-sponsored competitor. In addition to competing through adjustments of tactical variables such as price or the number of ads a product carries, we allow the incumbent to... View Details

January 2020
Article

Using Time-Driven Activity-Based Costing to Demonstrate Value in Perioperative Care: Recommendations and Review from the Society for Perioperative Assessment and Quality Improvement

By: O. Allin, R. D. Urman, A. F. Edwards, J. D. Blitz, K. J. Pfeifer, T. W. Feeley and A. M. Bader

A shift in health care payment models from volume toward value-based incentives will require deliberate input into systems development from both perioperative clinicians and administrators to ensure appropriate recognition of the value of all services... View Details

Keywords: Value-based Health Care; Outcomes; Time-Driven Activity-Based Costing; Health Care and Treatment; Cost Management; Value; Activity Based Costing and Management

Find at Harvard

28 Nov 2011
Research & Ideas

Rethinking the Fairness of Organ Transplants

simulations, the model suggests that life-year expectancies for the program can be increased by up to 8 percent, depending on variables plugged into the process. As with the "Moneyball" metrics... View Details

Keywords: by Dennis Fisher; Health

←
3
4
…
16
17
→