Proposal Description:

On October 12, 1492, Christopher Columbus and their crew landed on the Caribbean island of Hispaniola, and the world would never be the same. During the centuries that followed, among other things, there was a massive flow of immigrants from Europe, mostly from Spain, to the American continent. Surprisingly, we know very little about this mass migration that lasted uninterrupted until the Napoleonic wars in Spain led to the independence of most of the American colonies.

The goal of this project is to gather data on all the individuals that migrated from Spain to the New World since 1492 until circa 1800. We would like to understand the patterns of migration. Did individuals migrated to places where their specific skills were in high demand (skills hypothesis), or did they just follow friends and relatives that have migrated there earlier (network hypothesis)? Were migrants positively or negatively selected from the sending populations? What was the level of human capital or skills of the migrant populations, and did it varies from receiving regions? Was this skill composition affected by the different political institutions in the receiving regions? What was the impact of the skill composition on future economic development and political institutions?

The Spanish case is particularly well-suited to study the questions above. The enormity of the empire in Latin America, includes many latitudes and climates. This heterogeneity is key to test for the specificity of skills. Moreover, since there were no Europeans living in America prior to 1492, and in many places of the continent until the 16th or 17th centuries, we know that the first migrants did not have relatives there, which would allow us to test the network hypothesis. The data includes information on the migrants, the sending town, the receiving town or region, but also information on their family and their occupation. This rich information is crucial to study the hypotheses above.

Requisite Skills and Qualifications:

The RA would use the preliminary data already collected and write code to clean the data and generate new variables. The RA would also create tables, graphs and maps with the dataset. Finally, the RA would use econometrics software such as R or STATA to run econometric analysis.