Caitlin Knowles Myers joined the Economics faculty in the fall of 2005. She teaches Regression Analysis, Empirical Economic Research, Data Science Across Disciplines, and supervises senior research workshops.

Professor Myers’ research examines issues related to gender, race, and the economy, with particular focus on the effects of reproductive policies.  Her work been published in journals including the Journal of Political Economy, Journal of Labor EconomicsJournal of Human Resources, and Journal of Public Economics. It also has been featured by media outlets such as The New York TimesThe New YorkerSalonVice, and Vox.

Professor Myers also serves as the co-host of Middlebury’s Faculty at Home webinar series and as the co-director of the Middlebury Initiative for Data and Digital Methods (midd.data).

Courses Taught

Course Description

Introduction to Regression Analysis
In this course regression analysis is introduced. The major focus is on quantifying relationships between economic variables. Multiple regression identifies the effect of several exogenous variables on an endogenous variable. After exploring the classical regression model, fundamental assumptions underlying this model will be relaxed, and further new techniques will be introduced. Methods for testing hypotheses about the regression coefficients are developed throughout the course. Both theoretical principles and practical applications will be emphasized. The course goal is for each student to employ regression analysis as a research tool and to justify and defend the techniques used. (MATH 0121; and ECON 0111, (formerly ECON 0210) ECON 0150 or ECON 0155) 3 hrs. lect., 1 hr. lab

Terms Taught

Fall 2021

Requirements

DED

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Course Description

Empirical Research Methods in Economics
In this course we will provide students with the tools to conceptualize, design, and carry out a research project in economics. Topics will include survey design, sampling and power, experimental design (in and out of the lab), natural experiments, and other approaches to identifying causal relationships. Drawing from several sub-disciplines in economics, students will examine, replicate, and critique various studies. Emphasis will be placed on the formulation of valid, feasible research questions, and on the description and interpretation of results. (ECON 0211) 3 hrs. lect.

Terms Taught

Fall 2020, Fall 2023

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Course Description

Causal Inference
“Correlation is not causation” is a frequent refrain from people investigating relationships in data. But what does this mean? In this course we will focus on empirical tools that economists use to identify causal relationships. Students will explore the concept of causality and estimation of counterfactuals using randomized and natural experiments to study economic and social phenomena. Students will learn to apply the main research designs used by economists including randomized control trials (RCTs), difference-in-differences estimation, event studies, instrumental variables, and regression discontinuity. The ethics of conducting empirical research will also be emphasized throughout the course. (ECON 0211) (Formerly ECON 212) 3 hrs. lect.

Terms Taught

Fall 2024

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Course Description

Individual Special Project
If you choose to pursue an area that we do not offer or go in depth in an area already covered, we recommend the Individual Special Project option. These ECON 0500 proposals MUST be passed by the entire department and are to be submitted to the chair by the first Friday of fall and spring semester, respectively. The proposals should contain a specific description of the course contents, its goals, and the mechanisms by which goals are to be realized. It should also include a bibliography. According to the College Handbook, ECON 0500 projects are a privilege open to those students with advanced preparation and superior records in their fields. A student needs to have a 3.5 or higher G.P.A. in Economics courses taken at Middlebury in order to pursue an Individual Special Project. ECON 0500 does not count towards the major or minor requirements.

Terms Taught

Fall 2020, Winter 2021, Fall 2021, Winter 2022, Spring 2022, Winter 2023, Fall 2023, Winter 2024, Spring 2024, Fall 2024, Winter 2025, Spring 2025

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Course Description

Senior Research Workshop I
In this first semester, students will design and begin their projects. Emphasis will be on designing a novel research question (while making the case for its importance) and an appropriate strategy for answering it. This requires immersion in the academic literature on the topic. General research principles and tools will be taught in class, as a group, while those specific to individual projects will be covered in one-on-one meetings. By the end of the term, students will outline their plan for completing the project, including demonstrating that it is a feasible research question for which the necessary information (e.g., data or source materials) is available or can be generated by the student (e.g., lab or other experiment). (Approval required)

Terms Taught

Fall 2020, Winter 2022, Winter 2024, Winter 2025

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Course Description

Senior Research Workshop II
In this second semester of the senior research workshop sequence, the focus is on the execution of the research plan developed in ECON 0701. Most instruction is now one-on-one but the workshop will still meet as a group to discuss and practice the presentation of results in various formats (seminars, poster sessions, et cetera) to the rest of the workshop and others in the college and broader communities. Feedback and critiques from such presentations will be incorporated into the project, which will culminate in a research paper in the style of an economics journal article. (ECON 0701; Approval required)

Terms Taught

Spring 2021, Spring 2022, Spring 2024, Spring 2025

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Course Description

Data Science Across Disciplines
In this course we will gain exposure to the entire data science pipeline—obtaining and cleaning large and messy data sets, exploring these data and creating meaningful visualizations, and communicating insights from the data in a meaningful manner. During morning sessions, students will attend a combined lecture where they will learn the tools and techniques required to explore new and exciting data sets. During afternoon sessions, students will break out into smaller groups to apply these tools to domain-specific research projects in Art History, Biology, Economics, or Japanese and Linguistics.
Students enrolled in Professor Abe’s (Japanese) afternoon section will use the tools of data science to create visualizations of social and emotive meanings that surface through Japanese language/culture materials. Participants will use these visualizations to engage in various theoretical and pedagogical topics pertaining to (educational) linguistics.
Students enrolled in Professor Allen’s (Biology) afternoon section will use the tools of data science to investigate the drivers of tick abundance and tick-borne disease risk. To do this students will draw from a nation-wide ecological database.
Students enrolled in Professor Anderson’s (History of Art and Architecture) afternoon section will use the tools of data science to create interactive visualizations of the Dutch textile trade in the early eighteenth century. These visualizations will enable users to make connections between global trade patterns and representations of textiles in paintings, prints, and drawings.
Students enrolled in Professor Myers’ (Economics) afternoon section will use the tools of data science to create an interactive visualization of the landscape of abortion policy and access in the United States. This visualization will allow users to explore how abortion access varies across the country and how this variation in turn correlated with demographic, health, and economic outcomes.
This course will utilize the R programming language. No prior experience in statistics, data science, programming, art history, biology, economics, or Japanese is necessary

Terms Taught

Winter 2021

Requirements

DED, SOC, WTR

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Course Description

Terms Taught

Fall 2021, Winter 2022, Fall 2022, Winter 2023, Fall 2023, Winter 2024, Fall 2024, Winter 2025

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Course Description

Senior Thesis
(Approval Required)

Terms Taught

Fall 2020, Winter 2021, Fall 2021, Winter 2022, Fall 2022, Winter 2023, Fall 2023, Winter 2024, Fall 2024, Winter 2025

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