Blogging to resume again!

It has been far too long since my last post.  Life (becoming a father), travel (summer research trip to SFI), teaching (am teaching a course on Computational Economics), and research (also trying to finish my PhD!) have a way of getting in the way of my blogging.  As a mechanism to slowly move back into the blog world, I have decided to start a 'Graphic of the Day' series.  Each day I will create a new economic graphic using my favorite Python libraries (mostly Pandas, matplotlib, NumPy/Scipy).

The inaugural  'Graph of the Day' is Figure 1-1 from Mankiw's intermediate undergraduate textbook Macroeconomics.

Real GDP measures the total income of everyone in the economy, and real GDP per person measures the income of the average person in the economy.  The figure shows that real GDP per person tends to grow over time and that this normal growth is sometimes interrupted by period of declining income (i.e., the grey NBER bars!), called recessions or depressions.

Note that Real GDP per person is plotted on a logarithmic scale.  On such a scale equal distances on the vertical axis represent equal percentage changes. This is why the distance between \$8,000 and \$16,000 (a 100% increase) is the same as the distance between \$32,000 and \$64,000 (also a 100% increase).

The Python code is available on GitHub for download (I used pandas.io.data.get_data_fred() to grab the data).  The graphic is a bit boring.  I was a bit depressed to find that the longest time series for U.S. per capita real GDP only goes back to 1960! This seems a bit scandalous...but perhaps I was just using the wrong data tags!