Some Platypus Economics videos come with a companion worksheet, built in partnership with Stata. Watch the video for the intuition, then open Stata and work through the data yourself — each worksheet pulls real numbers, runs a handful of commands, and lets the pattern emerge in your own hands. Free to use in your classroom or on your own.
New to this? You'll need Stata and a free FRED API key — grab one at fredaccount.stlouisfed.org/apikeys. Each worksheet's first step shows you how to set it up (importing FRED data needs Stata 15.1 or later).
Does higher inflation mean more volatile inflation?
Pull decades of inflation data from FRED and measure it two ways — the average rate and how much it bounces around. See for yourself whether the two move together, and what that means for planning a life around prices you can't fully predict.
The building blocks of descriptive statistics — the mean as a measure of the average and the standard deviation as a measure of dispersion — plus computing growth rates as percentage changes and comparing the spread of a variable across groups.
Paired with the video “You Can't Stop Inflation, But Here's How to Minimize the Pain”
Does gas rise like a rocket and fall like a feather?
Line up weekly gas and oil prices from FRED, then run one regression to test a famous asymmetry: the price at the pump shoots up like a rocket when oil rises, but drifts down like a feather when oil falls. Measure the pass-through on impact and eight weeks out.
Regression as the workhorse of econometrics — here a distributed-lag model with several lags of one regressor, dummy and interaction terms that let an effect differ by direction, log changes as approximate percentage changes, and summing coefficients into a cumulative effect.
Paired with the video “You're Not Imagining It: Gas Prices Really Do Fall Slower Than They Rise”
Did tariffs on China reduce imports, or change their source?
Pull monthly import data from FRED for China and all eleven ASEAN members, then smooth it into rolling 12-month totals and watch a 25-year relationship flip sign. Before the 2025 tariffs, America bought more from ASEAN whenever it bought more from China; since then, every dollar lost from China shows up somewhere in Southeast Asia. Run one regression per era and measure the flip yourself.
Working with time series — building a monthly date, computing rolling 12-month totals that strip out seasonality, and aggregating series across countries — plus splitting a sample at a structural break, reading scatterplots with fitted lines, and interpreting a regression slope that flips from complements to substitutes.
Paired with the video “The Muddled Thinking Behind Trump's Tariffs”
Pull quarterly data from FRED on what corporations pay their workers and what they earn, then compute labor's share of income two ways — out of every dollar earned, and out of every dollar left after depreciation. Both measures have sunk to all-time lows. Run the numbers yourself and decide: depreciation changes the number, but does it change the story?
National income accounting made concrete — gross versus net value added, and why depreciation isn't income to anyone — plus building shares from raw dollar series, checking how a conclusion holds up when you change the denominator, and using summary statistics to judge whether today's value is an all-time low.
Paired with the video “The Great Shift from Workers to Owners”
Paired video coming soon
Worksheet 05
What a $20 Burrito Can Teach Us About Affordability
Pull sixty years of wages and consumer prices for twelve major economies straight from the OECD, then line them up country by country. From the 1970s inflation spike to the 2020s, wage growth and inflation rise and fall together almost everywhere. But "together" isn't the same as "one-for-one" — run the regression yourself and test whether a percentage point of inflation buys workers a full percentage point of wage growth.
Working with panel data — importing from a web API, merging two sources on country and year, and using tsset so lags respect country boundaries — plus building growth rates from index levels, reading small-multiples charts to spot a pattern across countries, and testing a specific hypothesis about a regression coefficient (b = 1) rather than just whether it differs from zero.
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