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- Forthcoming
- Article
Estimating Models of Supply and Demand: Instruments and Covariance Restrictions
By: Alexander MacKay and Nathan H. Miller
We consider the identification of empirical models of supply and demand with imperfect competition. We show that a restriction on the covariance between unobserved demand and cost shocks can resolve endogeneity and identify the price parameter. We demonstrate how to... View Details
Keywords: Demand Estimation; Identification; Endogeneity Bias; Covariance Restrictions; Ordinary Least Squares; Instrumental Variables; Price; Demand and Consumers; Competition
MacKay, Alexander, and Nathan H. Miller. "Estimating Models of Supply and Demand: Instruments and Covariance Restrictions." American Economic Journal: Microeconomics (forthcoming). (Direct download.)
- August 2010 (Revised December 2010)
- Case
Malcolm Life Enhances Its Variable Annuities
By: Robert C. Pozen and David J. Pearlman
The case involves an insurance CEO choosing between different designs for a variable annuity product in light of hedging, marketing, and pricing issues. The case provides students with background on the economics and regulation of life insurance and variable annuities.... View Details
Keywords: Annuities; Insurance; Investment Return; Governing Rules, Regulations, and Reforms; Product Design; Insurance Industry; United States
Pozen, Robert C., and David J. Pearlman. "Malcolm Life Enhances Its Variable Annuities." Harvard Business School Case 311-041, August 2010. (Revised December 2010.)
- 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
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.
- August 2010 (Revised August 2010)
- Teaching Note
Malcolm Life Enhances Its Variable Annuities (TN)
By: Robert C. Pozen and David J. Pearlman
Teaching Note for 311041. View Details
- 2014
- Working Paper
The Contaminating Effects of Building Instrumental Ties: How Networking Can Make Us Feel Dirty
By: Tiziana Casciaro, Francesca Gino and Maryam Kouchaki
To create social ties to support their professional or personal goals, people actively engage in instrumental networking. Drawing from moral psychology research, we posit that this intentional behavior has unintended consequences for an individual's morality. Unlike... View Details
Keywords: Networking; Morality; Dirtiness; Power; Networks; Moral Sensibility; Personal Development and Career; Power and Influence
Casciaro, Tiziana, Francesca Gino, and Maryam Kouchaki. "The Contaminating Effects of Building Instrumental Ties: How Networking Can Make Us Feel Dirty." Harvard Business School Working Paper, No. 14-108, April 2014.
- September–October 2020
- Article
The Air War Versus the Ground Game: An Analysis of Multi-Channel Marketing in U.S. Presidential Elections
By: Lingling Zhang and Doug J. Chung
This study jointly examines the effects of television advertising and field operations in U.S. presidential elections, with the former referred to as the “air war” and the latter as the “ground game.” Specifically, the study focuses on how different campaign... View Details
Keywords: Multi-channel Marketing; Ground Campaigning; Political Campaigns; Discrete-choice Model; Instrumental Variables; Political Elections; Marketing Channels; Advertising; United States
Zhang, Lingling, and Doug J. Chung. "The Air War Versus the Ground Game: An Analysis of Multi-Channel Marketing in U.S. Presidential Elections." Marketing Science 39, no. 5 (September–October 2020): 872–892.
- 2015
- Working Paper
Selling to a Moving Target: Dynamic Marketing Effects in US Presidential Elections
By: Doug J. Chung and Lingling Zhang
We examine the effects of various political campaign activities on voter preferences in the domain of US Presidential elections. We construct a comprehensive data set that covers the three most recent elections, with detailed records of voter preferences at the... View Details
Keywords: Multi-channel Marketing; Personal Selling; Advertising; Political Campaigns; Dynamic Panel Data; Instrumental Variables; Marketing Communications; Political Elections; Advertising Campaigns; United States
Chung, Doug J., and Lingling Zhang. "Selling to a Moving Target: Dynamic Marketing Effects in US Presidential Elections." Harvard Business School Working Paper, No. 15-095, June 2015. (Revised December 2015.)
- June 1986
- Article
Dividend Variability and Variance Bounds Tests for the Rationality of Stock Market Prices
By: Robert C. Merton and Terry A. Marsh
Merton, Robert C., and Terry A. Marsh. "Dividend Variability and Variance Bounds Tests for the Rationality of Stock Market Prices." American Economic Review 76, no. 3 (June 1986): 483–498.
- December 2014
- Article
The Contaminating Effects of Building Instrumental Ties: How Networking Can Make Us Feel Dirty
By: Tiziana Casciaro, Francesca Gino and Maryam Kouchaki
To create social ties to support their professional or personal goals, people actively engage in instrumental networking. Drawing from moral psychology research, we posit that this intentional behavior has unintended consequences for an individual's morality. Unlike... View Details
Keywords: Networking; Morality; Dirtiness; Power; Networks; Moral Sensibility; Identity; Power and Influence
Casciaro, Tiziana, Francesca Gino, and Maryam Kouchaki. "The Contaminating Effects of Building Instrumental Ties: How Networking Can Make Us Feel Dirty." Administrative Science Quarterly 59, no. 4 (December 2014): 705–735.
- February 2017
- Article
How Much Is a Win Worth? An Application to Intercollegiate Athletics
By: Doug J. Chung
Intercollegiate athletics in the United States have become a multibillion-dollar industry over the past several decades. In this study, we investigate the short- and long-term direct monetary effects of operating a winning athletics program for an academic institution... View Details
Keywords: Dynamic Panel Data; Heterogeneity; Instrumental Variables; Intercollegiate Athletics; Educational Finance; Entertainment Marketing; Higher Education; Marketing; Sports; Revenue; Education Industry; United States
Chung, Doug J. "How Much Is a Win Worth? An Application to Intercollegiate Athletics." Management Science 63, no. 2 (February 2017): 548–565.
- November 2019
- Article
How Do Sales Efforts Pay Off? Dynamic Panel Data Analysis in the Nerlove-Arrow Framework
By: Doug J. Chung, Byungyeon Kim and Byoung G. Park
This paper evaluates the short- and long-term value of sales representatives’ detailing visits to different types of physicians. By understanding the dynamic effect of sales calls across heterogeneous physicians, we provide guidance on the design of optimal call... View Details
Keywords: Nerlove-Arrow Framework; Stock-of-goodwill; Dynamic Panel Data; Serial Correlation; Instrumental Variables; Sales Effectiveness; Detailing; Analytics and Data Science; Sales; Analysis; Performance Effectiveness; Pharmaceutical Industry
Chung, Doug J., Byungyeon Kim, and Byoung G. Park. "How Do Sales Efforts Pay Off? Dynamic Panel Data Analysis in the Nerlove-Arrow Framework." Management Science 65, no. 11 (November 2019): 5197–5218.
- Article
The Importance of Being Causal
By: Iavor I Bojinov, Albert Chen and Min Liu
Causal inference is the study of how actions, interventions, or treatments affect outcomes of interest. The methods that have received the lion’s share of attention in the data science literature for establishing causation are variations of randomized experiments.... View Details
Keywords: Causal Inference; Observational Studies; Cross-sectional Studies; Panel Studies; Interrupted Time-series; Instrumental Variables
Bojinov, Iavor I., Albert Chen, and Min Liu. "The Importance of Being Causal." Harvard Data Science Review 2.3 (July 30, 2020).
- August 2018 (Revised August 2019)
- Technical Note
A Note on Compensation
By: Ethan Bernstein and Michael Norris
This note provides an overview of the important terms, concepts, and frameworks that a manager should know about compensation—whether it be their own or that of an employee. Because compensation in practice is fraught with pitfalls, this note presents an overview of... View Details
Keywords: Compensation Design; Benefits; Perks; Variable Compensation; Compensation and Benefits; Executive Compensation; Stock Options; Profit Sharing; Job Design and Levels; Labor Unions; Wages; United States
Bernstein, Ethan, and Michael Norris. "A Note on Compensation." Harvard Business School Technical Note 419-020, August 2018. (Revised August 2019.)
- Awards
INFORMS Workshop on Data Science Best Complete Paper in Artificial Intelligence Award
Winner of the Best Complete Paper Award at the 2022 INFORMS Workshop on Data Science for "Ensemble IV: Creating Instrumental Variables from Ensemble Learners for Robust Statistical Inference” with Gordon Burtch, Mochen Yang, and Gediminas Adomavicius. View Details
- 26 Nov 2018
- Working Paper Summaries
Demand Estimation in Models of Imperfect Competition
Keywords: by Alexander MacKay and Nathan H. Miller
- 2013
- Working Paper
From Green Users to Green Voters
By: Diego Comin and Johannes Rode
We estimate the effect of the diffusion of photovoltaic (PV) systems on the fraction of votes obtained by the German Green Party. The logistic diffusion of PV systems offers a new identification strategy. We take first differences and instrument adoption rates (i.e.... View Details
Keywords: Voting; Political Elections; Technology Adoption; Environmental Sustainability; Green Technology Industry; Public Administration Industry; Germany
Comin, Diego, and Johannes Rode. "From Green Users to Green Voters." NBER Working Paper Series, No. 19219, July 2013.
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
- 2009
- Working Paper
Endowments, Fiscal Federalism, and the Cost of Capital for States: Evidence from Brazil, 1891-1930
By: Andre C. Martinez Fritscher and Aldo Musacchio
There is a large amount of literature that aims to explain what determines country risk (defined as the difference between the yield of a sovereign's bonds and the risk-free rate). In this paper, we contribute to the discussion by arguing that an important explanatory... View Details
- August 2014
- Article
Religion, Politician Identity and Development Outcomes: Evidence from India
By: Sonia Bhalotra, Irma Clots-Figueras, Guilhem Cassan and Lakshmi Iyer
This paper investigates whether the religious identity of state legislators in India influences development outcomes, both for citizens of their religious group and for the population as a whole. Using an instrumental variables approach derived from a regression... View Details
Keywords: Politician Identity; Infant Mortality; Primary Education; India; Muslim; Fairness; Religion; Government and Politics; India
Bhalotra, Sonia, Irma Clots-Figueras, Guilhem Cassan, and Lakshmi Iyer. "Religion, Politician Identity and Development Outcomes: Evidence from India." Journal of Economic Behavior & Organization 104 (August 2014): 4–17.
- 2023
- Working Paper
Causal Interpretation of Structural IV Estimands
By: Isaiah Andrews, Nano Barahona, Matthew Gentzkow, Ashesh Rambachan and Jesse M. Shapiro
We study the causal interpretation of instrumental variables (IV) estimands of nonlinear, multivariate structural models with respect to rich forms of model misspecification. We focus on guaranteeing that the researcher's estimator is sharp zero consistent, meaning... View Details
Keywords: Mathematical Methods
Andrews, Isaiah, Nano Barahona, Matthew Gentzkow, Ashesh Rambachan, and Jesse M. Shapiro. "Causal Interpretation of Structural IV Estimands." NBER Working Paper Series, No. 31799, October 2023.