From Diversifying Economic Quality: A Wiki for Instructors and Departments

Jump to: navigation, search

Teaching economics with nuance and sophistication

Even if your department decides not to offer separate courses in heterodox theories of economics or on Race, Ethnicity, and Gender in Economics, it is important (and maybe even preferable) to integrate alternative perspectives and experiences into the content of existing courses. Acknowledge that the world is more complex than our simple (or even advanced) models suggest. Show how economists have taken steps towards improving models and methods and how we still have work ahead.

Here are some examples:


On the Labor-Leisure Model: To analyze an individual's time allocation decision, use a model of utility model derived indirectly from market goods and nonmarket time. While a portion of time outside of paid employment is leisure, men and especially women spend significant amounts of nonmarket time producing goods and services for the household[1] and caring for children[2]. Francine D. Blau, Marianne A. Ferber, Anne E. Winkler offer a great presentation of this model in The Economics of Women, Men, and Work by
On discrimination: Explicitly acknowledge the narrow conditions under which competitive market forces penalize and eliminate discrimination. Teach alternative theories of discrimination, which explain the persistence of discrimination in markets.


On Shortcomings of GDP: Assign Who's Counting?: Marilyn Waring on Sex, Lies & Global Economics (online at, in which Marilyn Waring speaks about women's work and the importance of assigning value to it. Ask students to identify three policy decisions that may generate inefficiency if the policymakers do not adequately account for the value of nonmarket production. Ask students to identify and discuss three policy decisions that may generate inequity if policymakers do not adequately account for the value of nonmarket production.
On the Financial Crisis: Consider "the role of stratification along multiple trajectories – race, class, and gender – in contributing to economic crises and in shaping their distributional dynamics." See Fukuda-Parr, Sakiko, James Heintz, and Stephanie Seguino, "Critical Perspectives on Financial and Economic Crises: Heterodox Macroeconomics Meets Feminist Economics Feminist Economics," Volume 19, Issue 3, 2013.


Improving the teaching of econometrics, David F. Hendry & Grayham E. Mizon, Cogent Economics & Finance, Volume 4, Issue 1, 2016
We recommend a major shift in the Econometrics curriculum for both graduate and undergraduate teaching. It is essential to include a range of topics that are still rarely addressed in such teaching, but are now vital for understanding and conducting empirical macroeconomic research. We focus on a new approach to macro-econometrics teaching, since even undergraduate econometrics courses must include analytical methods for time series that exhibit both evolution from stochastic trends and abrupt changes from location shifts, and so confront the “non-stationarity revolution”. The complexity and size of the resulting equation specifications, formulated to include all theory-based variables, their lags and possibly non-linear functional forms, as well as potential breaks and rival candidate variables, places model selection for models of changing economic data at the centre of teaching. To illustrate our proposed new curriculum, we draw on a large UK macroeconomics database over 1860–2011. We discuss how we reached our present approach, and how the teaching of macro-econometrics, and econometrics in general, can be improved by nesting so-called “theory-driven” and “data-driven” approaches. In our methodology, the theory-model’s parameter estimates are unaffected by selection when the theory is complete and correct, so nothing is lost, whereas when the theory is incomplete or incorrect, improved empirical models can be discovered from the data. Recent software like Autometrics facilitates both the teaching and the implementation of econometrics, supported by simulation tools to examine operational performance, designed to be feasibly presented live in the classroom.

Additional suggestions for course content