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Discusses what causation is and what one can (and cannot) learn about causation from observational (nonexperimental) data.
This paper examines the approaches accounting researchers use to draw causal inferences using observational (or non-experimental) data. The vast...
- 2021
- Working Paper
Population Interference in Panel Experiments
By: Iavor I Bojinov, Kevin Wu Han and Guillaume Basse
The phenomenon of population interference, where a treatment assigned to one experimental unit affects another experimental unit's outcome, has received considerable attention in standard randomized experiments. The complications produced by population interference in...
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- 2020
- Working Paper
Estimating Causal Effects in the Presence of Partial Interference 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...
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- 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....
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- 2020
- Working Paper
Panel Experiments and Dynamic Causal Effects: A Finite Population Perspective
By: Iavor Bojinov, Ashesh Rambachan and Neil Shephard
In panel experiments, we randomly expose multiple units to different treatments and measure their subsequent outcomes, sequentially repeating the procedure numerous times. Using the potential outcomes framework, we define finite population dynamic causal effects that...
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- April 2020
- Article
Regulatory Oversight, Causal Inference, and Safe and Effective Health Care Machine Learning
By: Ariel Dora Stern and W. Nicholson Price, II
In recent years, the applications of Machine Learning (ML) in the health care delivery setting have grown to become both abundant and compelling. Regulators have taken notice of these developments and the U.S. Food and Drug Administration (FDA) has been engaging...
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- May 2019
- Supplement
Kjell and Company: Motivating Salespeople with Incentive Compensation (C)
By: Doug J. Chung
Kjell & Company was a Swedish retail electronics chain. The company’s products consisted of home electronics and accessories. The company was noted for its excellent customer service and a fair “one-for-all” HR policy. Historically, the salespeople had been compensated...
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- May 2019
- Supplement
Kjell and Company: Motivating Salespeople with Incentive Compensation (D)
By: Doug J. Chung
Kjell & Company was a Swedish retail electronics chain. The company’s products consisted of home electronics and accessories. The company was noted for its excellent customer service and a fair “one-for-all” HR policy. Historically, the salespeople had been compensated...
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- 2018
- Article
Your Visual System Provides All the Information You Need to Make Moral Judgments about Generic Visual Events
By: Julian De Freitas and George A. Alvarez
To what extent are people's moral judgments susceptible to subtle factors of which they are unaware? Here we
show that we can change people’s moral judgments outside of their awareness by subtly biasing perceived
causality. Specifically, we used subtle visual...
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- December 2017
- Article
Discordant vs. Harmonious Selves: The Effects of Identity Conflict and Enhancement on Sales Performance in Employee-Customer Interactions
By: Lakshmi Ramarajan, Nancy Rothbard and Steffanie Wilk
Across multiple studies, we examine how identity conflict and enhancement within people affect performance in tasks that involve interactions between people through two mechanisms: role-immersion, operationalized as intrinsic motivation, and role-taking,...
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- June 2017 (Revised May 2019)
- Supplement
Kjell and Company: Motivating Salespeople with Incentive Compensation (B)
By: Doug J. Chung
Kjell & Company was a Swedish retail electronics chain founded in 1988 by brothers Marcus, Mikael and Fredrik Dahnelius. The company operated 84 stores, all company-owned, located mainly in the metropolitan areas of Sweden’s most popular cities: Stockholm, Gothemburg...
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- January 2017 (Revised May 2019)
- Case
Kjell and Company: Motivating Salespeople with Incentive Compensation (A)
By: Doug J. Chung
Kjell & Company was a Swedish retail electronics chain. The company’s products consisted of home electronics and accessories. The company was noted for its excellent customer service and a fair “one-for-all” HR policy. Historically, the salespeople had been compensated...
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- March 2016
- Teaching Note
Evive Health and Workplace Influenza Vaccinations
By: John Beshears
Evive Health is a company that manages communication campaigns on behalf of health insurance plans and large employers. Using big data techniques and insights from behavioral economics, Evive deploys targeted and effective messages that improve individuals' health...
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Keywords:
Vaccination;
Influenza;
Flu Shot;
Preventive Care;
Health Care;
Behavioral Economics;
Choice Architecture;
Nudge;
Experimental Design;
Randomized Controlled Trial;
RCT;
Causal Inference;
Insurance;
Consumer Behavior;
Health Care and Treatment;
Health Testing and Trials;
Communication Strategy;
Insurance Industry;
Health Industry
- March 2016
- Case
Evive Health and Workplace Influenza Vaccinations
By: John Beshears
Evive Health is a company that manages communication campaigns on behalf of health insurance plans and large employers. Using big data techniques and insights from behavioral economics, Evive deploys targeted and effective messages that improve individuals' health...
View Details
Keywords:
Vaccination;
Influenza;
Flu Shot;
Preventive Care;
Health Care;
Behavioral Economics;
Choice Architecture;
Nudge;
Experimental Design;
Randomized Controlled Trial;
RCT;
Causal Inference;
Consumer Behavior;
Health Care and Treatment;
Health Testing and Trials;
Communication Strategy;
Health Industry
- June 2012
- Article
Consequence-Cause Matching: Looking to the Consequences of Events to Infer Their Causes
By: Robyn A. LeBoeuf and Michael I. Norton
We show that people non-normatively infer event causes from event consequences. For example, people inferred that a product failure (computer crash) had a large cause (widespread computer virus) if it had a large consequence (job loss), but that the identical failure...
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- February 1994
- Background Note
Causal Inference
Discusses what causation is and what one can (and cannot) learn about causation from observational (nonexperimental) data.
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- Research Summary
Overview
By: Eva Ascarza
Professor Ascarza’s research primarily focuses on providing researchers and marketers a better understanding of how to manage customer retention so as to reduce churn and increase firm’s profitability. She addresses these issues by building empirical models of customer...
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