# The Economic Complexity of US Metropolitan Areas

## TL;DR

This paper measures economic complexity across US metropolitan areas from 2007 to 2015, revealing its correlation with income, resilience to crises, and regional development patterns.

## Contribution

It adapts the economic complexity concept from countries to regions, incorporating local and traded industries for metropolitan analysis.

## Key findings

- Higher complexity regions have higher income per capita.
- Traded industries are generally more complex than local industries.
- Economic complexity predicts income and population changes.

## Abstract

We calculate measures of economic complexity for US metropolitan areas for the years 2007-2015 based on industry employment data. We show that the concept of economic complexity translates well from the cross-country to the regional setting, and is able to incorporate local as well as traded industries. The largest cities and the Northeast of the US have the highest average complexity, while traded industries are more complex than local-serving ones on average, but with some exceptions. On average, regions with higher complexity have a higher income per capita, but those regions also were more affected by the financial crisis. Finally, economic complexity is a significant predictor of within-decreases in income per capita and population. Our findings highlight the importance of subnational regions, and particularly metropolitan areas, as units of economic geography.