The Causes of the Wealth of Nations

Written by Ryan McGuine //

Sustained, long-term output per capita growth, often referred to simply as “economic growth” is the ultimate goal of most economic policy interventions, and there are a number of models — mathematic representations of the economy — designed to explain how adjusting certain variables affects output per capita. The Solow Model is one of the simplest models of economic growth, and this post is a non-mathy overview of its implications. Readers interested in a more technical explanation can check out Dietrich Vollrath’s March 2014 blog posts about it.

The first key takeaway from the Solow Model is that output per worker is a function of capital per worker. Capital refers to the anything used by workers to create goods, be that equipment, tools, etc. Thus, capital per worker is broadly “the amount of physical things available to each worker to make stuff,” and it makes sense that a worker can make more stuff with more things at their disposal. For example, a manufacturing employee with an electric drill and 15 interchangeable screw heads is more effective than one with an electric drill and only 1 screw head.

The second important takeaway is that there are decreasing marginal returns — with every additional unit of capital, the resulting increase in output is less than the previous one. Continuing with the manufacturing example, the benefit that the employee gains by having 16 instead of 15 interchangeable screw heads is a lot smaller than the benefit that he gains by having 2 instead of 1.

Thirdly, the rate of capital accumulation is positively affected by savings rate, and negatively affected by population growth rate and depreciation rate. The quality of our manufacturing employee’s electric drill improves with the amount of money spent on it, and declines with both the number of people sharing it and the harshness with which it is used.

Something to note is that the exact values of an economy’s savings rate, population growth rate, and depreciation rate are determined by a combination of prevailing economic conditions and societal norms. For a given population, they are mostly constant and difficult to manipulate by those in power. Further, according to the Solow Model, increasing the savings rate, or decreasing the population growth and depreciation rate, can only boost the long-term level of output per captita, not the rate of output per capita growth.

Given the sustained economic growth seen by much of the world since the Industrial Revolution which can only be described as extraordinary by historical standards, though, there must be some missing feature. Indeed, that missing feature is technological progress. Technology augments labor and makes it more productive — more goods and services can be produced with the same amount of inputs. In the manufacturing example, a robotic drill arm is able to do more work and make fewer mistakes than an employee with an electric drill, regardless of how many interchangeable screw heads he has. Productivity-enhancing technological advancement enables sustained, long-run economic growth, and is in fact the only variable that can change the rate of output per capita growth.

Factor (physical and human capital) accumulation and technological progress are referred to as “proximate causes of growth” — that is, they are easily measured and are thus chosen as variables for the model. However, they say nothing of why one country might have a faster rate of factor accumulation and technological progress than another. The reasons for cross-country differences in rates of variable change are referred to as “fundamental causes of growth.” Specifically, these are: luck, geography, institutions, and culture. Interested readers should see Chapter 4 of Professor Daron Acemoglu’s textbook on growth economics for more about the fundamental causes of growth.

The Solow Model is far from the only analytical model of economic growth. However, because it has so few moving parts and matches empirical observations well, it is a valuable initial litmus test when considering how a particular policy will affect growth.