their bachelor’s degree, and are 35 years of age or younger at the time we observe their wages. These age restrictions ensure we compare individuals at a similar stage in their lifecycle profile and results in 389,749 observations.

Our sample is further restricted to exclude those with missing locations and all observations in 2008 because the geographic identifiers in that year were incorrectly recorded (resulting in _n_ = 310,581). Excluding workers with zero observed wages—either because they are self-employed, long-term unemployed, not in the labor force, or informally employed—we have _n_ = 252,788 individuals.<sup>5</sup> Our next restriction is to exclude workers in the health sector, who are subject to a mandatory rural service requirement for doctors and college graduates in these fields.<sup>6</sup> For ease of interpretation in our results below, we also leave out individuals who moved to a smaller city for college. Only 2.7% of the sample at this stage moves to a smaller city for college, whereas 17.7% of individuals moves to a bigger city. Nonetheless, the inclusion of those who move to a smaller city for college does not alter our results. Our final sample is comprised of _n_ = 212,023 individuals for whom we use their last recorded annual wage if they are observed in multiple years, and we deflate nominal annual wages using the Colombian cpi (Dec 2008 = 100).

# **_Definition of cities_**

For the purposes of the analyses that follow, we define a ‘city’ as the metropolitan area constructed from the aggregation of municipalities that are interconnected through commuting flows, as laid out in Duranton (2015). Duranton (2015) takes all pairs of origin and destination municipalities, and designs an algorithm that flags those pairs for which the share of commuters from the origin is above some chosen commuting threshold. Around each ‘urban core’ or central city, the algorithm then identifies the commuting shed as the set of areas whose commuter share is above the commuting threshold. Both the urban core and the commuting shed thus constitute the metropolitan area. Duranton (2015) also proposes a commuting threshold of 10%, which appears to be reasonable given that Colombian municipalities tend to be fairly large. From hereon out, when we discuss cities, we are referring to the metropolitan areas as defined by this algorithm.

Next we classify a city as big if it has a population of 2.5 million or more (this would include Bogota, Medellin, and Cali), medium if it has a population of 400,000 to 2.5 million, and small if it has less than 400,000 inhabitants. To define a migratory move across cities, we first create a matrix of road distances for all municipalities. We then define an individual in our data as having moved for college if her high school city is different from her college city _and_ the road distance between those two cities is greater than 50 kilometers. Moves after college for work are defined similarly.

# **_Descriptive statistics_**

Table 1 reports summary statistics for our sample of college graduates in the formal sector. Our sample are young workers (average age is 26.6), majority female (57%), 49% of whom are first-born

> 5Our data do not allow us to identify the work status of an individual outside formal employee or formal selfemployee. We observe some individuals over a few years so we can identify them when working, even if they start their careers in unemployment or out of the labor force.

> 6Thus, mobility after college for health care workers is not voluntary and their salaries are set at the national level.

5