# **Per Capita GDP and Other Controls:**

We have GDP per capita every ten years for 1960-2010. The main variable used in our analysis is average log GDP per capita for each decade (constant 2005 international $). We use various sources to reconstruct a range of time-invariant or time-varying controls at the country-level. In the panel regressions, we include the time-varying controls (estimated in the same or previous decade). In the cross-sectional regressions, we also include the time-invariant controls (the time-varying controls are estimated for 1960-2010 instead of for the same or previous decade). First, we consider various rural push factors: (i) FAO (2013) reports the cereal yields (hg per ha) for each country-year observation. We then estimate the average yields for each decade; (ii) Rural density is defined as the ratio of rural population (1000s) to arable area (sq km). The arable area of each country is reported by FAO (2013); (iii) CRED (2013) reports the number of droughts experienced by each country every year. We use two variables: the number of droughts (per sq km) since 1960, and the number of droughts (per sq km) for each decade (e.g., 1960-1969 for the 1960s); and (iv) The Polity IV data series includes a measure of political violence for each country (1964-present). We create an indicator whose value is one if the country experienced an interstate or civil conflict in each decade (Polity IV 2013a). Second, we consider various urban pull factors: (i) The share of manufacturing and services in GDP (%) in 2010 is obtained from WB (2013). The data is missing for many country-year observations before the recent period; (ii) We use the data set of Gollin, Jedwab and Vollrath (2013) to obtain the average share of natural resource exports in GDP (%) for each decade; (iii) We use the Polity IV data series to calculate the average combined polity score for each country for each decade (Polity IV 2013b). We create an indicator whose value is one if the average polity score is lower than -5, the threshold for not being considered autocratic; and (iv) From WB (2013), we know the share of the largest city in the urban population, the primacy rate, for all years in 1960-2010. Third, we use the other following controls: (i) The 97 countries use four different types of urban definition in their most recent censuses: (a) “administrative cities” are administrative centers of territorial units (e.g., provinces, districts, etc.), (b) “threshold cities” are localities whose population is greater than a population threshold of X inhabitants (e.g.,5,000 or 2,500), (c) “administrative or threshold cities” are either administrative centers or localities whose population is greater than a population threshold, and (d) “threshold with condition cities” are localities whose population is greater than a population threshold and who have a large share of the labor force engaged in non-agricultural activities. We create dummies for each definition. For each country using a population threshold, we know the threshold and use it as a control in our regressions; and (ii) We create two dummies equal to one if the country is a small island or if the country is landlocked. We consider an island country small if its area is smaller than 50,000 sq km.

A. 7