Jonathan Old

Ph.D. candidate in economics at UC Berkeley, on the job market in 2026–27. Political economy and development economics.

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Teaching materials

Here you can find teaching slides, code, and course evaluations for courses I am teaching.

A few examples of the visualizations I use to teach undergraduate applied econometrics:

This animation shows the consequences of measurement error in the independent variable in an OLS regression. As the random measurement error increases, the estimated slope becomes flatter - this is called attenuation bias.

Measurement error

The figure visualizes how omitted variable bias works in a simple wage-education-ability framework. Just looking at the correlation between education and wages, we could conclude that higher education leads to higher wages. However, in this case, the association purely comes from the fact that higher ability is correlated with both more education and higher wages. Seen in three dimensions makes this clear.

Omitted variable bias visualized

This images shows the Central Limit Theorem in action. We throw a number of dice and record the mean opf all these dice 100,000 times. As we increase the number of dice thrown in a single time from 1 to 50, the distribution of the overall means becomes more and more similar to a normal distribution.

Central Limit Theorem in Action

 

 

Fall 2023: Undergraduate Applied Econometrics (Econ 140), at UC Berkeley

Official evaluations (section 1), official evaluations (section 2).

Spring 2023: Undergraduate Applied Econometrics (Econ 140), at UC Berkeley

Official evaluations (section 1), official evaluations (section 2).

Fall 2022: Undergraduate Applied Econometrics (Econ 140), at UC Berkeley

Summary of student evaluations, official evaluations (section 1), official evaluations (section 2).