Gary Cornwall

Gary is a PhD student in the Economic Department of the Carl H. Lindner College of Business.

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Teaching Interest
Econometrics, Microeconomics

Research Interest
Spatial Econometrics, Bayesian Econometric Methods, Income Distributions, Income Inequality, Savings and Retirement

Awards | Honors
Organization: Lindner College of Business
Name: Dean's List of Teaching Excellence
Year Received: 2015

Organization: TAFT Research Center
Name: Charles Phelps Taft Dissertation Fellowship
Year Received: 2015

Education
Institution: University of Cincinnati
Location: Cincinnati, Ohio
Major: Applied Economics
Completed: 2012
Degree: MA

Institution: University of Cincinnati
Location: Cincinnati, Ohio
Major: Economics
Completed: 2010
Degree: BA

Published Contributions
Gary Cornwall, Jeffrey Mills, Beau Sauley, Huibin Weng, (2019). Bayesian predictive inference for Granger Causality. Advances in Econometrics. 

Jeffrey Strawn, Jeffrey Mills, Gary Cornwall, Sarah Mossman, Sara Varney, Brooks Keeshin, Paul Croakin,  (2018). Buspirone in Children and Adolescents with Anxiety:  A Review and Bayesian Analysis of Abandoned Randomized Controlled Trials. . Journal of Child and Adolescent Psychopharmacology, 2-9.

Jeffrey Strawn, Eric Dobson, Jeffrey Mills, Gary Cornwall, Dara Salosky, Boris Birmaher, Scott Compton, John Piacentini,  (2017). Placebo Response in Pedriatic Anxiety Disorders:  Results from the Child/Adolescent Anxiety Multimodal Study. Journal Adolescent and Child Psychopharmacology, 501-508.

Gary Cornwall, Olivier Parent,  (2017). Embracing Heterogeneity:  The Spatial Autoregressive Mixture Model. Regional Science and Urban Economics, 148-161.

Research in progress
Title: Bayesian Predictive Inference for Granger Causality
Status: On-Going
Research Type: Scholarly

Title: Mixture Distributions with Spatial Dependency
Description: Methodological paper focused on incorporating measures of spatial dependency into Bayesian mixture modeling.
Status: Writing Results
Research Type: Scholarly

Title: Spatial Durbin Mixture Models
Description: This paper extends the finite mixture model structure to include Spatial Durbin and Spatial Durbin Error model specifications. The partial derivatives of this heterogeneous spatial model structure are shown to differ between border and interior agents; the designation of which is based on group assignment and first order neighbor designation. It is shown that, under conditions of heterogeneous spatial scalars, the own-partial and cross-partial derivatives have predictable but differing behaviors than their homogeneous model counterparts. As an illustration the model is employed to look at individual income based on a data set from the restricted Panel Study of Income Dynamics data files.
Status: Writing Results
Research Type: Scholarly

Title: The Econometrics of Learning-by-Doing.
Status: Writing Results
Research Type: Scholarly

Title: Where do I fit in? Examining Employee Membership Profiles
Description: Research examining working adults determines if there are distinct and interpretable employee membership profiles based on perceived organizational membership. Contrary to prior theorizing on employee membership typologies which suggests four different profiles, the current study suggests evidence of three. A method commonly used in economics research and quickly gaining popularity in organizational research—mixture modeling and latent profile analysis is used. We provide a description of each typology and explain why this information is crucial to organizations. Implications in practice include what may happen if employers do not understand differences between their employees when it comes to perceived organizational membership.
Status: On-Going
Research Type: Scholarly

Presentations
Title: Regression Discontinuity in Network Models: Non-linear Partial Effects and Spillovers
Location: University of Cincinnati
Year: 2018

Title: Regression Discontinuity in Network Models: Non-linear Partial Effects and Spillovers
Location: Washington, D.C.
Year: 2018

Title: Regression Discontinuity in Network Models: Non-linear Partial Effects and Spillovers
Location: Texas A&M
Year: 2017

Title: Where do I fit in? Examining employee membership profiles.
Organization: Society for Industrial and Organizational Psychology
Location: Orlando, FL
Year: 2017

Title: Bayesian predictive inference for Granger Causality
Organization: Midwest Economics Association
Location: Cincinnati, OH
Year: 2017

Title: Bayesian Predictive Inference for Granger Causality
Organization: Midwest Econometrics Group
Location: University of Illinois at Urbana-Champaign
Year: 2016

Title: Spatial Durbin Mixture Models
Organization: Midwest Econometrics Group
Location: University of Illinois at Urbana-Champaign
Year: 2016

Title: Mixture Distributions with Spatial Dependency
Organization: Southern Regional Science Association
Location: Washington DC
Year: 2016

Title: Mixture Distributions with Spatial Dependency
Organization: Midwest Econometrics Group
Location: St. Louis Federal Reserve Bank
Year: 2015

Title: The Econometrics of Learning by Doing
Organization: Midwest Economics Association
Location: Minneapolis, MN
Year: 2015

Title: The Econometrics of Learning by Doing
Organization: Midwest Econometrics Group
Location: University of Iowa
Year: 2014