Research

Research Interests: Applied Econometrics, Simulation-Based Inference, Methodology Evaluation, Validation, and Selection, Forecasting and Time Series Methods, Machine Learning Applications, Meta-Regression Methodology

*My five-year research agenda includes 6 projects not listed here, details are in my job market package and available upon request

Publications

Revise & Resubmit

1) Crawley, A., Daigneault, A. & Gendron, J. (2025) Where the Trees Fall: Macroeconomic Forecasts for Forest-Reliant States. Forest Policy & Economics (Paper Link, Github Link)

• • • • Summary: Builds a macroeconomic forecasting model to forecast macroeconomic variables for the forest sector at the industry/state level (including key states) by using a Vector Error Correction (VEC) Model

      • Contributions: 

        • We provide a framework for policy analysis by integrating our previous identification of industry-dependent states within the forestry sector

        • We provide a framework for forecasting in other natural-resource reliant industries (such as mining, agriculture, and energy production)

Under Review

2) Job Market Paper: Gendron, J. & Habibnia, A. (2025) Evaluating Meta-Regression Techniques: A Simulation Study on Heterogeneity in Location and Time (Paper Link, Github Link, Flash Talk Link)

• • • • Summary: Uses simulations to test which meta-regression method performs optimally in the face of joint heterogeneity in the location and time that each study was conducted in

      • Contributions: The following are new to the literature

        • Providing a practitioner's guide to model selection

        • Testing performance of relevant methods with various degrees of location and time heterogeneity

        • Testing the efficacy of two new methods in the experimental economics and meta-analysis simulation literature

Preprint Available (arXiv Link)

3) Crawley, A., Daigneault, A., & Gendron, J. (2019) Maine’s Forestry and Logging Industry: Building a Model for Forecasting (Paper Link, Flash Talk Link)

• • • • Summary: Forecasts macroeconomic variables for the forestry and logging industry of Maine and analyzes industry shocks by using a Vector Error Correction (VEC) Model and Impulse Responses

      • Contributions:

        • We provide a framework for forecasting in the forestry and logging industry (NAICS 113)

        • We provide a framework for identifying key industry-dependent states within the forestry and logging industry (NAICS 113)

Working Papers

4) Gendron, J., Habibnia, A., & Jaimes Sandoval A. Automated Diagnostics for Meta-Regressions: A Machine Learning Framework

• • • Summary: Uses machine learning to formally detect whether heterogeneity arises at the study, location, time, or joint location-time level for meta-regression data sets

5) Gendron, J. & Habibnia, A., & Jaimes Sandoval A. Permutation Tests Improve Upon Model-Free Dependence Measures 

• • • Summary: This uses simulations to showcase the poor performance of standard model-free dependence measures compared to more advanced permutation testing and moving-block bootstrapping

6) Gendron, J. & Habibnia, A. Efficacy of Location-level Fixed Effects in Experimental Economics: A Simulation Study on Heterogeneity in Location

• • • Summary: This chapter of my dissertation uses simulations to test which meta-regression method performs optimally when there is heterogeneity in only the location each study was conducted in

7) Dickinson, S. & Gendron, J. Cost Saving with Misspecification Testing - Assuring Optimal Experimental Design

• • • Summary: Constructs a framework for experimental economists to assess design robustness pre-experiment

8) Gendron, J. From Normality to Reality: Improving Experimental Economic Analysis with Distributions

• • • Summary: Analyzes distribution details of experimental economic behavioral data, like trust and reciprocity (i.e. trustworthiness)

Invited Talks:

• Economics Department Seminar – Towson University

September 19, 2025

Conference Presentations:

• (Upcoming) Southern Economics Association – Tampa, Florida

November 22-24, 2025

• DC-MD-VA Econometrics Workshop – Washington, D.C.

September 20, 2025

• International Association of Applied Econometrics – Turin, Italy

June 25-27, 2025

• Camp Econometrics – Bolton Landing, New York

April 25-27, 2025

• Graduate Research Symposium – Virginia Tech

March 26, 2025

• Graduate Research Symposium – Virginia Tech

March 27, 2024

• PPE Research Fellow Panel – Virginia Tech

April 19, 2023

• Maine Economics Conference – Bates College

April 27, 2019

• University of Maine Student Symposium

April 10, 2019 

• Forest Resources Association – Bangor, Maine

April 4, 2019

• Three Minute Thesis Competition – University of Maine

March 25, 2019