Why are some countries rich and others poor? This question has troubled economists for a long time. Probably the most well-known economic model to study this question is the Solow growth model, which predicts that income per capita of countries that share similar savings rates, capital depreciation, and population growth (among other characteristics) should converge over time to similar values. This convergence hypothesis means that, holding all else equal, countries with low income per capita should grow fast and eventually catch up with countries with high income per capita. FRED data can help us evaluate whether this convergence hypothesis holds over time.
We take the U.S. as our “benchmark” high-income country and analyze whether other countries are catching up with it. The graph above shows real GDP per capita in low- and middle-income countries as a ratio to real GDP per capita in the U.S. For example, if Brazil’s ratio moves closer to 1, that means Brazil’s GDP per capita is converging to U.S. GDP per capita. We see some clear evidence of convergence in three countries: South Korea (solid blue line), China (solid red line), and India (solid green line). GDP per capita in Brazil (dotted blue line) moved toward convergence until 1980, then started decreasing and leveled out. The dashed lines at the bottom, representing Mozambique and Kenya, do not seem to converge at all.
The graph below shows GDP per capita in high-income countries as a ratio with GDP per capita in the U.S.: Japan (dashed purple line) and France (solid blue line) show some stronger signs of convergence, moving from about 20% and 55% of U.S. GDP per capita, respectively, to about 75% of U.S. GDP per capita between 1950 and 2010. The United Kingdom (red line) also shows some signs of convergence to the U.S., while Germany (dotted blue line) and Canada (green line) are mostly flat over the sample period.
Overall, the evidence on Solow convergence is mixed. Some assumptions important for the theory may not hold, and the lack of convergence could be related to differences in savings rates, depreciation, and population growth across some of the countries we analyze here.
How this graph was created: In the FRED search bar, search for “purchasing power parity converted GDP per capita (Chain Series) for China.” Add this series to a graph and search for the same series for other desired countries within the “Add Data Series” tab underneath the graph. After adding all the low- and middle-income countries, go back to the “Add Data Series” tab and modify the existing series by adding GDP per capita for the U.S. Next, for each series, under the “Create your own data transformation” option, type “a/b” in the formula box to create the ratio. You can turn off the title and axis titles on the “Graph Settings” tab to keep the graph clean. Individual series color and line styles can be changed on the “Edit Data Series.”
Suggested by Maximiliano Dvorkin and Hannah Shell.
