A prediction of how much a country will grow based on its current level of Economic Complexity, its Complexity Outlook or connectedness to new complex products in the Product Space, as compared to its current income level in GDP per capita and expected natural resource exports.
Economic complexity alone helps explain the lion’s share of variance in current income levels. But the value of economic complexity is in its predictive power on future growth, where a simple measure of current complexity and connectedness to new complex products, in relation to current income levels and expected natural resource exports, holds greater accuracy in predicting future growth than any other single economic indicator.
To calculate Economic Complexity Growth Projections, the authors consider four factors as explanatory variables: the Economic Complexity Index; the Complexity Outlook Index; the current level of income; and the expected growth in the value of natural resource exports per capita.
In effect, the growth projections show countries grow by expanding the know-how they have that allows them to produce more, and more complex products, depending on the connectedness of know-how and how many other products rely on similar capabilities, as well as the initial economic complexity the country held.
Growth projections are calculated through a process largely based on determining whether a country's economic complexity is higher or lower than expected given its level of income. The authors expect countries whose economic complexity is greater than the authors would expect for its level of income to grow faster than those that are "too rich" for their current level of complexity.
In this data, a country's growth projection value for a given year is for the decade beginning with that year. For example, a value in a 2017 row is the projection of annualized growth for 2017–2027.
Type of variable: Continuous
Downloaded by QoG on: 2023-11-24
Last updated by source: 2023-07-28
| Dataset | No. Countries |
|---|---|
| Standard cross-section: | 133 |
| Standard time-series: | 133 |
| OECD cross-section: | 36 |
| OECD time-series: | 36 |