Incoming students may still have questions about which sections of Microeconomics and Statistics to select in the Core. Kusala Molligoda, MPP Class of 2022, covers some key differences between the two courses and provides an overview of the coding proficiency needed to maximize the Harris Core experience.


Microeconomics for Public Policy I provides students with little to no preliminary knowledge of economics a platform in which to develop foundational skills. Coursework in supply & demand equilibria, income vs. substitution effects, production functions, and profit maximization form the framework of the course. Although applications are discussed alongside course materials—for example, a discussion of minimum wage—the primary focus is on the derivation techniques themselves. Topics covered in Microeconomics I will be addressed in depth and application sections focus on implementing tools and techniques—e.g. capital markets, consumer and unemployment theory, or the model of self-selection.

Alternatively, Advanced Microeconomics for Public Policy I assumes the student already has a strong foundation in both microeconomics and calculus and focuses more on the applications of microeconomic theory. Disclaimer: the calculus covered in Math & Coding Camp is NOT sufficient for this course. For example, students should possess an understanding of how to manipulate integrals and derivatives or the underlying concept behind a Taylor series expansion. Since these topics all hinge around mathematical models, a student’s ability to understand and manipulate them is of paramount importance to their success in the class.


Much like its Microeconomics equivalent, Statistics for Data Analytics I assumes that students have no prior knowledge of statistics, apart from basic mathematical skills (commonly covered in Math & Coding Camp). This course introduces students to regression analysis and basic coding in R. Topics covered in coursework include probability theory, RV coefficients, hypothesis testing, and basic simulation.

Advanced Statistics for Data Analytics I covers a similar range of topics, but focuses more on the application of analysis methodologies—for example, using both Stata and R to code simulations that help to illustrate complex statistical problems or learning how and when to use the bootstrap to improve on asymptotic tests.

For both the regular and advanced courses, completion of Dataquest’s “Introduction to programming in R” and completing Math & Coding Camp are helpful in providing early practice in coding and access to coding resources. Students should utilize the help of teaching assistants (TAs) and learn from peers, external resources, as well as the R and Stata pages of the the student handbook, which will be shared with incoming students on August 10, 2021. They should also use supplementary assignments or resources offered on the course Canvas page itself.

If students are unsure which level is right for them, they can sit in both levels of Microeconomics or Statistics in the first week of the quarter to help determine which class is the best fit. Most students find value in discussing their choice with their academic advisor as well.

One of the purposes of the Core is to help transition students into taking elective courses, many of which require varying levels of microeconomic and statistical knowledge. For students to fully utilize the opportunities each course provides, selecting the appropriate courses in the Core is crucial.

For more information, read this previous blog post from Professor Tom Coleman on Taking Advanced Classes in the Core.