In these turbulent and uncertain times, it is easy to focus only on the violent economic fluctuations within the business cycle. But there is also a bigger picture - the longer-run increase in economic output across history. Measuring growth is important, because it defines the standard of living available to humanity.
Once one starts to think about [questions of growth], it is hard to think about anything else.
- Robert Lucas (1988)
What is the history of economic growth?
Clark 2007 gives a three part account of the history of economic growth.
Firstly, a Malthusian trap persisted till 1800. That is, income per person varied across societies and epochs without an upward trend. Short-term gains in income from technological advances were lost to population growth. In fact, material living standards declined from the Stone Age to the 1800s, because life expectancy stayed static at 30 to 35 years, while society became less egalitarian.
Secondly, the Industrial Revolution changed the possibilities for material consumption. There was a large increase in output per person for a select group of countries, with the richest modern economies being ten to twenty times wealthier than in 1800.
Thirdly, prosperity has not arrived to all societies. Some countries have since converged to those modern economies, while others remain well below pre-industrial norms. This is most pronounced in sub-Saharan Africa. This Great Divergence is so massive that the gap in incomes between countries is on the order of 50 to 1.
What did the Malthusian trap persist for so long? Why did the Industrial Revolution allow an escape? Why was there a Great Divergence?
Answering these questions
In Part I, we will look at some basic theoretical models that describe economic growth.
We will go on to examine the “big history” reasons for why countries are able to grow their factors of production and improve their productivity in Part II - that is, the fundamental rather than proximate explanation for growth.
Finally, we will return to these big questions in Part III, applying the theoretical framework we will have established to explain real world datasets, with a splash of R-aided econometrics.