Connor Lennon is an Economist and Data Scientist specializing in causal inference and spatial techniques in machine learning and Environmental Economics.
What I believe: Economics as a discipline has been slow to adopt machine learning in causal estimation - much of this is due to the field’s justifiable concern regarding the validity of estimates that emerge from ‘black boxes.’ To that end, I am interested in bridging the gap between machine-learning theorists and econometric practitioners. The research I’ve performed during my doctorate has focused on providing for the traditional econometrician a path to understanding the limitations and possibilities that machine learning can bring to observational studies. Much of my applied research is on a particularly challenging environment for causal identification—estimating how property value affects wildfire suppression costs in the United States.
Resources for the Future
Summer 2020, Doctoral Economic Research Intern
Acted as research assistant alongside RFF research fellow Matthew Wibbenmeyer for a a project funded by AFRI to determine what extent individuals sort over wildfire risk in the wildland urban interface (WUI).
Created a postgresql database that links ztrax assessment and transaction data to mortgage lending HMDA
data in California to create an extensive geo-located database of property characteristics and buyer de-
mographics from 2004 to 2019.
Perform initial exploratory analysis of wildfire hazard (wfh) capitalization into sale prices in San Diego
Catalogued possible policy tools that may be useful as an instrument for wildfire hazard that are orthogonal to property amenities - one of which, California’s remapping of FHSZ, will be used in final publication
Responsible for communicating research difficulties and hurdles
to responsible parties, along with adjusted timelines for requested projects.
Invited to continue working on project as a formal co-author after internship completion
University of Oregon
2017-2022, Graduate Educator and Ph.D Candidate
Independently plan and teach undergraduate economics courses, including Econometrics and Introductory Microeconometrics, with enrollments ranging from 80 to 300 students.
Supervise up to 3 graduate students to coordinate lab sections and create material to assist undergraduate understanding of economic concepts.
Create instructional materials and provide instruction for labs built for a variety of audiences, from undergraduate level understanding to first year Ph.D students
Instructor of Record
2020-2022
Lab Instructor
2017-2022
Econ 421 Introduction to Econometrics (II) Spring 2021
– Built and organized a course github
– developed new notes to instruct undergraduates on use of Judea Pearl’s structural causal model and logic
over formal DAGs
– Developed new homework assignments to fit modified curriculum
Econ 201 Introduction to Microeconomic Analysis Spring 2022, Spring 2020, Fall 2020
– Designed a course curriculum from scratch to help undergraduates understand where and how economic
models inform current events and how human behavior and the messiness of the ’real world’ can change
those models
– Developed custom homework assignments to work best in a newly-remote learning environment
- Econ 607 PhD Core Econometrics Fall 2021
- Econ 421 Introduction to Econometrics (II) Winter, Fall 2021 Developed lab notes and a basic github site for teaching students how to use R for econometrics that are still in use today by lab section leaders
- Econ 524 Prediction and Econometrics Winter 2020
Ran labs for newly designed, master’s level machine learning and prediction course
Assist masters students with code - wrote notes to teach students to use the ‘tidymodels’ framework in R
Prepared and taught the end of course lecture on neural networks and how to code a real-world example of an LSTM to predict home-level electricity usage from electricity meter data in keras. Returned to teach this lecture to following class in Winter of 2021.
- Econ 201 Introduction to Microeconomic Analysis Fall 2017,2018
- Econ 202 Introduction to Macroeconomic Analysis Fall’17,Spring 17, 18
- Econ 101 Introduction to Economic Analysis Spring 2019
If you’re interested in learning more about me, please reach out!