Abstract
I study a settlement policy implemented by the Chilean government between 1882 and 1904 to analyze the relationship between European immigration and the human capital of natives. Using historical censuses, I show that this policy was successful in recruiting skilled Europeans, who located in different parts of the country. Using a panel data of provinces observed between 1860 and 1920, I find a strong, positive, and robust correlation between recruited Europeans and the human capital of natives. This finding is not driven by changes in the provision of public goods or regional shocks. However, the arrival of Europeans is associated with an increase local economic output 50 years after the policy was terminated. These changes in the local economy, together with narrative historical evidence, suggest that a modernization of economic activities is a potential explanation for the increase in the human capital of natives.
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Notes
The consequences of this Columbian Exchange has been an active area of research in the last decade, estimating the impact it had in the Americas (e.g., Engerman and Sokoloff 2000; Acemoglu et al. 2001; Dell 2010; and Bruhn and Gallego 2012; among others, see Nunn 2009 for a review) and in Europe (e.g., Nunn and Qian 2011; see Nunn and Qian 2010 for a review).
Interestingly, the authors assume the existence of human capital spillovers from skilled Europeans to relatively unskilled natives, argue that human capital is persistent, and then estimate growth regressions at the regional level, finding large and positive effects.
There were some attempts to attract foreigners before the 1880s, but they were largely unsuccessful until the immigration policy I study was implemented in 1882 (Borgono 1913).
Some of the benefits for migrants were: free shipping of their tools and machinery (with a limit of 2 tons), free tickets across Chilean railroads upon arrival, and a significant reduction in travel tickets within Europe—from cities to main ports of departure—and from Europe to Chile.
As European governments wanted to prevent an exodus, only these immigration houses were able to recruit migrants. According to a letter from the agency to the Ministry of Foreign Affairs in February 1884, the agency partnered with the following immigration houses: A Ch. Colson in France and Spain; Casa de Ph. Rommel y Cia. in Switzerland, Baden, Würtemberg, Baviera, Tiral and Alsacia; and the former consul Carlos Ochsenius for the rest of Germany.
Unfortunately, the 1885 Census does not present information about the number of Europeans by province, so I had to drop it from the analysis.
More about school construction and education during this period can be found in Serrano et al. (2012). The development of the “Primary Instruction Law” summarizes the government’s intentions: all children between the ages of six and sixteen had to be at least 4 years at school. This law was enacted in 1920 but public spending on education began in the 1860s (Bowman and Wallerstein 1982; Ponce de León 2010). These changes were experienced at the country level and I can account for their impact using year fixed effects and regional trends. Figure 5 presents time series for real GDP per capita and its growth (Díaz et al. 2016). More about data construction in “Appendix″.
The official numbers are: 7457 from France, 1826 from England, 1567 from Germany, 7068 from Italy, and 9717 from Spain. These numbers exclude, as in the subsequent empirical analysis, the annexed territories in the north after the War of the Pacific (1879–1883). Robustness exercises speak directly to a potential confound from this war. Results, however, suggest this is not a concern.
As education was mostly public during this period, I interpret the cost of education as (i) an opportunity cost related to foregone labor income, and (ii) a transportation cost to go to school.
This can be derived more formally by solving the firm’s profit maximization problem. In particular, the firm will choose L to maximize Eq. (1). Then, \(P_\ell (\tilde{M})\) will simply be \(P_\ell (\tilde{M})=\sum _{i=1}^{\tilde{M}} (L_m/\bar{L})\), where \(\bar{L}\) is total labor force in the local economy and \(m=1,\ldots ,\tilde{M}\) indexes the number of European entrepreneurs in the local economy.
In particular, \(\varOmega (s,E,\tilde{M})\equiv \min \left\{ \sum _{m=1}^{\tilde{M}} \phi ,1\right\} \times P_\ell (\tilde{M})\), where \(\phi (s)\) represents the increase in the probability of starting a firm with a native’s additional unit of education for a European with skill s.
A region is a cluster of provinces. I consider three regions: north, center, and south.
Ponce de León (2010) documents that the government’s school construction policy was to follow urban population. This implies that by including the logarithm of total and urban population I also indirectly control for government spending in education.
In particular, if Europeans decided to settle in places with a growing economy, estimates are biased upwards. This is because, presumably, rich provinces can afford higher literacy rates. Estimates are biased downwards if they settled in relatively less developed provinces. Historical evidence suggest the latter is most likely to be the case (Agencia de Colonización 2010).
The port constructed in 1888 could be endogenous if, for example, its construction reflects future economic enterprises. If this is the case, expected economic prosperity could affect investments in human capital for reasons not related to Europeans’ presence.
A graphical representation of the cross-sectional variation in distances to the main ports of arrival can be found in Fig. 3. Red dots in the map represent the two main active ports, while yellow dots represent ports that opened after the agency.
It is perhaps important to emphasize that railroad construction was underway during this time period. However, railroads between the south of the country and the rest of the country were connected only after the settlement agency stopped operating. See Forero et al. (2019).
The most important firm in this industry was the brewery of Carlos Anwandter, a pharmaceutical chemist immigrant from Luckenwalde. At the beginning of the 20th century his firm produced more than 12 million liters and exported its product to several countries in South America. The Anwandter family hired plenty of workers at the breweries (Sociedad de Fomento Fabril 1914). Importantly, the wages paid to skilled workers were higher in these breweries. According to Pérez Canto (1894), the wages for skilled workers reached the 200 Chilean pesos, while in an alternative job the same worker could obtain a maximum of 130 Chilean pesos.
The first tannery of Valdivia was founded by the german Hermann Schulke (Sociedad de Fomento Fabril 1884). Then, with the help of the german Eduard Prochelle, the firm grew to become the Industrial Company of Valdivia. By the 1890s, the firm had more than fifty workers and used steam engines.
Examples of these are the clockmaking factory Del Gatto, the Lucchetti and Carozzi food factories (which still exist today), and the Rossi millinery, among many others. Some important families were the Ferretti family that sold wines, and the Fortunato and Bosini family who owned a sausage factory.
An example of these firms was the tanneries owned by Eugene Saint-Macary and his brother Victor in the 1890s. They had a big factory in Valparaiso, a shoe factory in Santiago, and a 8000 square feet tannery in Concepcion.
One of the most important Spaniard firms was “Presa Hermanos,” which operated as a distribution company for a wide range of different products (e.g., hardware, fruits, woods, and shoes). This firm also worked as wool exporter, agent of the West Indian and the Ford Motor Company, and sold tractors and other machinery for agricultural activities Estrada (2005).
To the best of my knowledge similar data for the industrial sector in the 1950s does not exist and the period after that is likely to have been affected by an agrarian reform policy in the 1960s, the trade liberalization in the 1970s, and the policies of the dictatorship (1973–1990) more generally.
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Acknowledgements
I would like to thank Jorge Cariola and Cristián Larroulet for their work in early stages of this project. I also thank José Díaz, Barry Eichengreen, Francisco Gallego, Jeanne Lafortune, Ted Miguel, Tomás Monarrez, Pablo Muñoz, Cristóbal Otero, Santiago Pérez, David Schoenholzer, José Tessada, Danae Valenzuela, Gert Wagner and seminar participants at the Annual Meeting of the Chilean Economic Society, PUC-Chile, Universidad Carlos III, and UC Berkeley for comments and suggestions that improved the paper.
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Appendix: data construction
Appendix: data construction
Censuses can be found in the website of the National Statistics Bureau of Chile. Censuses before 1865 do not present information about immigrants by province. The analysis excludes the territory annexed after the War of the Pacific (1879–1883) and the Magallanes province because it was unpopulated in the 1860s—then populated mainly by foreigners—and it is geographically disconnected by thousand of kilometers from the rest of the country. Results are similar if I include it.
Variables used in the empirical analysis were constructed in the following way:
- Provinces:
-
I construct 44 units that are geographically equivalent during the period 1865–1920. Through the paper I call these units “provinces.” Table 9 presents these units and the provinces. The majority of units are provinces (26), and only three units include more than four provinces (Ancud, Arauco, and Santiago). All results are robust to exclude units with more than one province.
- Europeans:
-
I define a European as a person born in one of the following European countries: Austria, Belgium, Czech Republic, Germany, Denmark, Scotland, Spain, France, Great Britain, Ireland, Italy, Netherlands, Norway, Portugal, Sweden, or Switzerland. I label all other immigrants as non-Europeans. Children of Europeans are classified as natives in the census and country statistics. Results are robust to include people from the USA, Canada, and Australia into a category of “high skilled immigrants.”
- Natives’ literacy:
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National censuses present information on the average literacy rate in each province. Let \(\ell _{it}\) be the literacy rate and \(P_{it}\) the total population of province i in census year t. To construct natives’ literacy rate I assume all Europeans are literate, although results are robust to other assumptions. Therefore, if \(E_{it}\) the number of Europeans in the province i at time t, the natives’ literacy rate is \(y_{it}=\frac{\ell _{it}\times P_{it} - E_{it}}{P_{it}-E_{it}}\).
- Public schools:
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National censuses of 1865 and 1875 present information on the number of public schools in each province i at census year t. To construct public schools per 1000 inhabitants I take the average number of public schools between 1865 and 1875, and divide it by the average population between 1865 and 1875, and then multiply this number by 1000.
- Distances:
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To calculate the distance between each province and the two ports of interest I first take information on the latitude and longitude for each province’s centroid from Google Maps. Then, I obtain the latitude and longitude for each port using the same procedure. Finally, I use the Stata command vincenty to calculate the distance between provinces and ports. This command uses an accurate ellipsoidal model of the Earth to account for the surface’s curvature (see Figs. 5, 6 and Tables 9, 10, 11).
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González, F. Immigration and human capital: consequences of a nineteenth century settlement policy. Cliometrica 14, 443–477 (2020). https://doi.org/10.1007/s11698-019-00194-x
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DOI: https://doi.org/10.1007/s11698-019-00194-x