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  • September 2022
  • Article

The Impact of Financial Assistance Programs on Health Care Utilization: Evidence from Kaiser Permanente
By: Alyce S. Adams, Raymond Kluender, Neale Mahoney, Jinglin Wang, Francis Wong and Wesley Yin
Most hospitals have financial assistance programs for low-income patients. We use administrative data from Kaiser Permanente to study the effects of financial assistance on health care utilization. Using a regression discontinuity design based on an income threshold...  View Details
Keywords: Healthcare; Utilization; Financial Assistance; Health Care and Treatment; Social Issues; Poverty; Health Industry
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  • 2022
  • Article

Nonparametric Subset Scanning for Detection of Heteroscedasticity
By: Charles R. Doss and Edward McFowland III
We propose Heteroscedastic Subset Scan (HSS), a novel method for identifying covariates that are responsible for violations of the homoscedasticity assumption in regression settings. Viewing the problem as one of anomalous pattern detection, we use subset scanning...  View Details
Keywords: Scan Statistics; Anomaly Detection; Regression; Model Diagnostics
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  • 2022
  • Working Paper

Innovation on Wings: Nonstop Flights and Firm Innovation in the Global Context
By: Dany Bahar, Prithwiraj Choudhury, Do Yoon Kim and Wesley W. Koo
We study whether, when, and how better connectivity through nonstop flights leads to positive innovation outcomes for firms in the global context. Using unique data of all flights emanating from 5,015 airports around the globe from 2005 to 2015 and exploiting a...  View Details
Keywords: Nonstop Flights; Collaborative Innovation and Invention; Patents; Research and Development; Air Transportation Industry
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  • 2022
  • Working Paper

Machine Learning Models for Prediction of Scope 3 Carbon Emissions
By: George Serafeim and Gladys Vélez Caicedo
For most organizations, the vast amount of carbon emissions occur in their supply chain and in the post-sale processing, usage, and end of life treatment of a product, collectively labelled scope 3 emissions. In this paper, we train machine learning algorithms on 15...  View Details
Keywords: Carbon Emissions; Climate Change; Environment; Carbon Accounting; Machine Learning; Artificial Intelligence; Digital; Data Science; Environmental Sustainability; Environmental Management; Environmental Accounting
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  • May 2022
  • Supplement

Regression Exercises
By: David E. Bell
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  • May 2022
  • Exercise

Regression Exercises
By: David E. Bell
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  • May 2022
  • Article

Complex Disclosure
By: Ginger Zhe Jin, Michael Luca and Daniel Martin
We present evidence that unnecessarily complex disclosure can result from strategic incentives to shroud information. In our lab experiment, senders are required to report their private information truthfully, but can choose how complex to make their reports. We find...  View Details
Keywords: Disclosure; Experiments; Naiveté; Overconfidence; Corporate Disclosure; Policy; Information; Complexity; Strategy; Consumer Behavior
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  • March 2022 (Revised July 2022)
  • Module Note

Linear Regression
By: Iavor I. Bojinov, Michael Parzen and Paul Hamilton
This note provides an overview of linear regression for an introductory data science course. It begins with a discussion of correlation, and explains why correlation does not necessarily imply causation. The note then describes the method of least squares, and how to...  View Details
Keywords: Data Science; Linear Regression; Mathematical Modeling; Mathematical Methods; Analytics and Data Science
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  • March 2022 (Revised July 2022)
  • Module Note

Prediction & Machine Learning
By: Iavor I. Bojinov, Michael Parzen and Paul Hamilton
This note provides an introduction to machine learning for an introductory data science course. The note begins with a description of supervised, unsupervised, and reinforcement learning. Then, the note provides a brief explanation of the difference between traditional...  View Details
Keywords: Machine Learning; Data Science; Learning; Analytics and Data Science; Performance Evaluation
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  • March 2022
  • Article

Assessing the Impact of the COVID-19 Pandemic on Clinician Ambulatory Electronic Health Record Use
By: A Jay Holmgren, Lance Downing, Mitchell Tang, Christopher Sharp, Christopher Longhurst and Robert S. Huckman
Objective: The COVID-19 pandemic changed clinician electronic health record (EHR) work in a multitude of ways. To evaluate how, we measure ambulatory clinician EHR use in the United States throughout the COVID-19 pandemic.

Materials and Methods: We use EHR...  View Details
Keywords: Health Care; Electronic Health Records; Productivity; COVID-19 Pandemic; Health Care and Treatment; Health Pandemics; Information Technology; Performance Productivity; United States
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  • Working Paper

Electoral Turnovers
By: Benjamin Marx, Vincent Pons and Vincent Rollet
In most national elections, voters face a key choice between continuity and change. Electoral turnovers occur when the incumbent candidate or party fails to win reelection. To understand how turnovers affect national outcomes, we study the universe of presidential and...  View Details
Keywords: Election Outcomes; Regression Discontinuity Design; Political Elections; Change; Global Range; Outcome or Result; Economy; Governance; Performance Improvement
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  • February 2022
  • Article

Sugar-sweetened Beverage Purchases and Intake at Event Arenas with and without a Portion Size Cap
By: Sheri Volger, James Scott Parrott, Brian Elbel, Leslie K. John, Jason P. Block, Pamela Rothpletz-Puglia and Christina A. Roberto
This is the first real-world study to examine the association between a voluntary 16-ounce (oz.) portion-size cap on sugar-sweetened beverages (SSB) at a sporting arena on volume of SSBs and food calories purchased and consumed during basketball games. Cross-sectional...  View Details
Keywords: Sugar-sweetened Beverages; Nutrition Policy; Obesity Prevention; Portion Sizes; Nutrition; Policy; Health; Behavior
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  • 2022
  • Working Paper

The Impact of Campaign Finance Rules on Candidate Selection and Electoral Outcomes: Evidence from France
By: Nikolaj Broberg, Vincent Pons and Clémence Tricaud
This paper investigates the effects of campaign finance rules on electoral outcomes. In French departmental and municipal elections, candidates competing in districts above 9,000 inhabitants face spending limits and are eligible for public reimbursement if they obtain...  View Details
Keywords: Political Elections; Finance; Governing Rules, Regulations, and Reforms; Outcome or Result; France
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  • January–February 2022
  • Article

Operational Disruptions, Firm Risk, and Control Systems
By: William Schmidt and Ananth Raman
Operational disruptions can impact a firm's risk, which manifests in a host of operational issues, including a higher holding cost for inventory, a higher financing cost for capacity expansion, and a higher perception of the firm's risk among its supply chain partners....  View Details
Keywords: Operational Risk; Operational Disruptions; Information Asymmetry; Control Systems; Operations; Disruption; Risk Management
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  • August 2021
  • Case

Precision Paint Co.
By: Iavor I. Bojinov, Chiara Farronato, Janice H. Hammond, Michael Parzen and Paul Hamilton
Describes a marketing director about to launch a new process for demand forecasting. Provides data that allow students to do a multivariable regression analysis. A rewritten version of an earlier case.  View Details
Keywords: Regression; Prediction; Forecasting; Data Science; Analysis; Forecasting and Prediction
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  • July 2021
  • Article

Multinationality and Capital Structure Dynamics: A Corporate Governance Explanation
By: Daniel Gyimah, Nana Abena Kwansa, Anthony K. Kyiu and Anywhere Sikochi
This paper examines the impact of corporate governance on capital structure dynamics. Using ordinary least squares regressions on 17,496 firm-year observations for 2,294 U.S. multinational companies (MNCs) over the period 1990–2018, we find that MNCs with strong...  View Details
Keywords: Multinationality; Speed Of Adjustment; Corporate Governance; Multinational Firms and Management; Capital Structure
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  • June 2021
  • Technical Note

Introduction to Linear Regression
By: Michael Parzen and Paul Hamilton
This technical note introduces (from an applied point of view) the theory and application of simple and multiple linear regression. The motivation for the model is introduced, as well as how to interpret the summary output with regard to prediction and statistical...  View Details
Keywords: Linear Regression; Regression; Analysis; Forecasting and Prediction; Risk and Uncertainty; Theory; Compensation and Benefits; Mathematical Methods; Analytics and Data Science
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  • May 2021
  • Article

Choice Architecture in Physician–patient Communication: A Mixed-methods Assessment of Physicians' Competency
By: J. Hart, K. Yadav, S. Szymanski, A. Summer, A. Tannenbaum, J. Zlatev, D. Daniels and S.D. Halpern
Background: Clinicians’ use of choice architecture, or how they present options, systematically influences the choices made by patients and their surrogate decision makers. However, clinicians may incompletely understand this influence....  View Details
Keywords: Choice Architecture; Health Care and Treatment; Interpersonal Communication; Decision Choices and Conditions; Competency and Skills
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  • 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
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  • Article

Resilience vs. Vulnerability: Psychological Safety and Reporting of Near Misses with Varying Proximity to Harm in Radiation Oncology
By: Palak Kundu, Olivia Jung, Amy C. Edmondson, Nzhde Agazaryan, John Hegde, Michael Steinberg and Ann Raldow
Background
Psychological safety, a shared belief that interpersonal risk taking is safe, is an important determinant of incident reporting. However, how psychological safety affects near-miss reporting is unclear, as near misses contain contrasting cues that...  View Details
Keywords: Psychological Safety; Near-miss Reporting; Health Care and Treatment; Safety
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