metadata: authors: 0: author: Bruhn,Miriam
1: author: Gallego,Francisco Antonio
count: World
docna: 0: docna: Good, bad, and ugly colonial activities :
            studying development across the Americas
docty: Policy Research Working Paper
subtopic: Primary Metals,Mining & Extractive Industry (Non-Energy),Inequality
teratopic: Health, Nutrition and Population,Macroeconomics and Economic Growth
abstracts: cdata!: Levels of economic development vary
            widely within countries in the Americas. This paper argues
            that part of this variation has its roots in the colonial
            era. Colonizers engaged in different economic activities in
            different regions of a country, depending on local
            conditions. Some activities were "bad" in the
            sense that they depended heavily on the exploitation of
            labor and created extractive institutions, while
            "good" activities created inclusive institutions.
            The authors show that areas with bad colonial activities
            have lower gross domestic product per capita today than
            areas with good colonial activities. Areas with high
            pre-colonial population density also do worse today. In
            particular, the positive effect of "good"
            activities goes away in areas with high pre-colonial
            population density. The analysis attributes this to the
            "ugly" fact that colonizers used the pre-colonial
            population as an exploitable resource. The intermediating
            factor between history and current development appears to be
            institutional differences across regions and not income
            inequality or the current ethnic composition of the population.
repnme: repnme: Good, bad, and ugly colonial activities :
            studying development across the Americas
display_title: Good, bad, and ugly colonial
            activities : studying development across the Americas
listing_relative_url: /research/2008/06/9496791/good-bad-ugly-colonial-activities-studying-development-across-americas
topicv3: Mining Services m1326410 1701,Poverty m1326687 695,Mining Sector m1327113 554,Population, Aging and Health m1327736 640,Gold m1503518 2936
publishtoextweb_dt: 2010-07-01T00:00:00Z
historic_topic: Health, Nutrition and Population,Macroeconomics and Economic Growth
no_of_pages: 58
author_keys: 0: author_key: 955274
1: author_key: 562458
model_extractions: WPS4641 Policy ReseaRch WoRking PaPeR 4641 Good, Bad, and Ugly Colonial Activities: Studying Development across the Americas _Miriam Bruhn Francisco A. Gallego_ The World Bank Development Research Group Finance and Private Sector Team June 2008
Policy ReseaRch WoRking PaPeR 4641

# **Abstract**

Levels of economic development vary widely within countries in the Americas. This paper argues that part of this variation has its roots in the colonial era. Colonizers engaged in different economic activities in different regions of a country, depending on local conditions. Some activities were "bad" in the sense that they depended heavily on the exploitation of labor and created extractive institutions, while "good" activities created inclusive institutions. The authors show that areas with bad colonial activities have lower gross domestic product per capita today than areas with good colonial activities. Areas with high pre-colonial population density also do worse today. In particular, the positive effect of "good" activities goes away in areas with high precolonial population density. The analysis attributes this to the "ugly" fact that colonizers used the pre-colonial population as an exploitable resource. The intermediating factor between history and current development appears to be institutional differences across regions and not income inequality or the current ethnic composition of the population.

This paper—a product of the Finance and Private Sector Team, Development Research Group—is part of a larger effort in the department to understand the role of history and institutions in the development process. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at mbruhn@worldbank. org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
<!-- Start of picture text --> Pontificia<br><!-- End of picture text --> <!-- Start of picture text --> Catélica<br><!-- End of picture text --> thank Lee Alston, Hoyt Bleakley, R6mulo Chumacero, Nicolas Depetris Chauvin, Esther Duflo, Jeffrey Woodruff, Ibanez Nicolas Sciences, Planning Ministry (MIDEPLAN), Republic of Chile, for financial support.
|countries is due to differences in institutions (See Pande and Udry, 2005, for an overview<br>differences<br>These institutions persisted over time and influence economic outcomes<br>effect<br>Colonizers engaged in different economic activities in<br>different|
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a�ect current economic outcomes<sup>3</sup> . Areas with bad colonial activities should thus have lower levels of economic development than areas with good colonial activities, which included many other economic activities that did not rely on coerced labor. Similarly, areas with high pre-colonial population density should have lower levels of economic development today.

This line of argument is not entirely new and is largely based on Engerman and Sokolo�(1997 and 2002) and Acemoglu et al. (2001, 2002, and 2005). The contribution of this paper is mainly two-fold:

1. We extend the previous arguments to explain within-country variation in levels of economic development. We present both anecdotal and empirical evidence supporting a within-country correlation between colonial activities and development today. In addition, we provide indirect evidence suggesting that institutions are the mechanism through which history a�ects current levels of economic development.

2. We argue, in contrast to Engerman and Sokolo�, that having good colonial activities did not always lead to a good development path. Instead, the technologies used in di�erent areas with good activities were endogenous to the availability of a local labor force. Areas suitable for good activities that had low pre-colonial population density followed the predictions of Engerman and Sokolo�in terms of creating a big middle class based on a disperse property structure. However, areas suitable for good activities that had high pre-colonial population density tended to feature exploitation of labor and have a high concentration of income. Some areas that had good activities thus also had ugly activities.

We collect data on economic activities performed in di�erent regions during the colonial period for 16 countries in the Americas.<sup>4</sup> Each region is assigned three dummy variables summarizing whether it had predominantly good, bad or no colonial activities. We also collect data on pre-colonial population density (mainly from Denevan, 1992 and the references therein). The paper then correlates these historical variables with two current measures of economics development for states or regions in the eight countries (PPP GDP per capita and poverty rates). The results show that, in 2000, pre-colonial population density is negatively and correlated with current GDP per capita. Going from the 25th percentile in pre-colonial population density (-0.97) to the 75th percentile

> 3For the purposes of this paper, we refer to institutions as bundle of variables that may a�ect long run development, including the availability of human capital.

> 4The sample includes data for Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Panama, Paraguay, Peru, United States, Uruguay, and Venezuela.

2
effects significant. significant effect effect pre-colonial population density confirms our hypothesis that good colonial activities were beneficial

|effect|
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|find|
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ethnic composition of the population, are an important mechanism to explain the effects

|affected<br>affects|
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Sokoloff (1997, affected classified Colonizers established extractive institutions in places where the net benefits of havbenefits benefits first Sokoloff, profitable inefficient inefficient
<!-- Start of picture text --> Sokoloff,<br>Sokoloff,<br>first<br>affected affected<br>influenced Sokoloff (1997<br>differences<br>“factor endowments” led to different degrees of initial concentration in wealth, in human<br>This initial inequality influenced the type of<br>different<br>Sokoloff consist<br>different<br>different Sokoloff identify<br>different<br>exemplified<br>Given the effi-<br><!-- End of picture text -->
labor. The consequent large-scale properties were to some degree based on pre-conquest social organizations in which the elites charged taxes. These large-scale structures, legitimated by the Spanish Crown (through the so-called encomiendas), survived even when the main production activities did not display economies of scale. The key aspect was that the rights to operate the tax systems were assigned to a small group of people. Hence, as in the previous group of countries, these economies featured highly concentrated political and economic power that translated into exclusive institutions preserving the power of the elite.

Finally, the third group of countries is composed of the colonies of the North American mainland (Canada and United States). These economies were neither endowed with crops that displayed economies of scale nor with an abundant native population. Therefore, their economies were organized into small units of production in a relatively competitive environment. The existence of abundant land and low capital requirements implied that most adult men operated as independent proprietors creating a relatively egalitarian society in economic and political terms.

Engerman and Sokolo�illustrate with a number of examples and summary statistics that the di�erences in productive processes across New World countries translated into very di�erent patterns of su�rage, public land, schooling policies, �nancial policies, and innovation policies among these countries. Easterly (2001) and Easterly and Levine (2002) provide econometric evidence linking factor endowments to institutional development. Both papers use a group of 11 dummy variables indicating whether a country produced any of a given set of leading commodities (crops and minerals). Easterly (2001) uses cross-country data to relate these measures, jointly the settler mortality variable from Acemoglu et al. (2001), to a variable measuring the \middle-class consensus" (i.e. the share of the three middle quantiles in total income). He shows that factor endowments and settler mortality are correlated with the middle class consensus. The middle class share subsequently a�ects the level of schooling, institutional quality, and openness of countries, and these variables a�ect per-capita income. In a related cross-country study, Easterly and Levine (2002) correlate factor endowments and settler mortality with the development of institutions. They �nd evidence that these variables a�ect income only through institutions.

Overall, the existing literature indicates that colonial factors can explain di�erences in economic development across countries. However, they are relatively silent about the e�ects of colonial factors on institutions and development at the sub-national level. In particular, if one takes the papers by Acemoglu et al. literally, colonial factors created 6
Sokoloff stress differences different Sokoloff to explain differences in economic development across regions within countries In fact, the three types of scenarios that Engerman and Sokoloff describe different differences Sokoloff briefly However, our aim is to explain existing current differences view institutions as social arrangements specific to a region that are largely invariant to migration (this effect different affect finds different significant effects discuss differences of development between the North and South of the US (e.g. Engerman and Sokoloff). Interestingly, the effects of historical factors on development seem to be relevant not only among former effect
Our argument differs from Engerman and Sokoloff in that we claim that having good different Sokoloff in tivities such as mining or sugar production were highly profitable and had less flexibility e Differences differences e specifically, Assuncgao different nature.

Assungao different
e benefitted finance, Sokoloff, different.

Laeven and Woodruff (2007) differ Mexico to show that average firm size is larger in states with more effective legal systems.

specific different different And, finally, we provide an example in which the initial development influence
performed by colonizers led to extractive institutions and to lower levels of development today. An example for this mechanism is the north-eastern region of Brazil which grew sugar during the colony. Nowadays this region corresponds to the states of Alagoas and Pernambuco. These states had very unequal societies during colonial times for two reasons. First, sugar plantations used slaves, leading to the importation and subjugation of many Africans. Second, since sugar areas were rich areas, they attracted more rich people from the European elites. The sugar regions developed societal norms (institutions) that bene�ted only the elites and that did not leave room for the natives or slaves. The following quote from Colonial Brazil describes society in the sugar regions \While the old planter families tended to intermarry, room was always found for sons-in-law who were merchants with access to capital or high-court judges and lawyers bringing prestige, family name, and political leverage. Obviously, the arranged marriage was a key element in the strategy of family success." (Bethell, 1987, p. 89) In contrast to this elite dominated society stood S~ao Paulo (formerly S~ao Vicente), a region that was not favorable to growing sugar. The region was poor during the early years of the colony and displayed a very di�erent societal structure. \Few Portuguese women were attracted to the area and the Portuguese households and farms were �lled with captive and semi-captive Indians. Illicit unions between Portuguese men and Indian women were common and a large number of mamelucos (the local term for mesti�cos<sup>11</sup> ) resulted. [. . . ] In the early period of S~ao Vicente's history, little discrimination was made between mamelucos and Portuguese so long as the former were willing to live according to what passed in the region for European norms." (Bethell, 1987, p.111-112) Colonial society in S~ao Paulo was thus comparatively inclusive. Societal norms (institutions) bene�tted a larger set of people than in the sugar regions.

Although Alagoas and Pernambuco were rich states during colonial times and S~ao Paulo was poor, their fortunes are now reversed. In 2000, PPP GDP per capita in Alagoas was US$ 2,809 and US$ 3,531 in Pernambuco. In S~ao Paulo, on the other hand, GDP per capita was US$ 11,718. Poverty rates show a similar pattern. In 2000, they stood at 46.5 percent in Alagoas (57.4 percent in Pernambuco) and 12.3 in S~ao Paulo.

Section 2 also argued that areas with high pre-colonial population density developed extractive institutions during the colony and are therefore less developed today. This pattern is well illustrated by comparing two Mexican states, Aguascalientes and Tlaxcala. These states have similar background characteristics, but they had di�erent pre-colonial population densities. Both states are landlocked and have similar average

> 11 Mesit�cos are people of mixed Indian and European decent.

10
five different (Gomez-Galvarriato, experience of Spanish masters and artisans” (G6mez-Galvarriato, 2006, p.

different different influenced GomezAccordingly to Gémez-Galvarriate, obrajes were widely present in Latin America since the mid XVI Michoacan México, Pert, Cérdoba
Pacific Chocé region had significant gold mining activities during the early colonial period. Chocé region to sugar plantations in the neighboring Valle del Cauca and Cauca regions. affected definitions specific definitions briefly
define definition we include country fixed effects. effects) significantly effect Iyer (2005) also shows that the effect of colonialism in India was stronger at the time of independence
Pert, Villamarin Villamarin (1981) for Pert.

Pert, difference first Sokoloff.

fishery, classification, first one indicates whether a region had good colonial activities.
have been affected by colonial activities and that may be the link between those activities first different differences differences a Bn
<!-- Start of picture text --> n fixed effect,<br>coefficient ay<br>coefficient<br>coefficient<br>The reason for the zero effect of good activities is that<br>effect,<br>effect.<br>the coefficient on good activities<br>coefficients<br>significantly<br>coefficients<br>significantly<br>coefficient<br><!-- End of picture text -->
significantly different coefficient coefficient As predicted, the coefficient on the good significant. significance.

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Sala-i-Martin (1999) find for U.S. states from 1880 to1980, namely 1.74 percent per year, the coefficient find, coefficient.

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This finding suggests that, conditional on being colonized, areas with significant.

significant different coefficient significant.

figures figures identified In order to further examine the robustness of the results, Table 6 displays 16 different with a different country excluded from the sample. coefficients. coefficient The coefficients on good and bad activities are never significant, finding identification significant
figure plots conditional averages of log GDP per capita, where the averages are calculated based on the coefficients from a regression that includes a good colonial activities dummy, difference significant difference significant.

first altitude in order to control for the potential effects of malaria on economic development following run regressions in which we find that good and bad activities are not statistically correlated with
<!-- Start of picture text --> coefficients<br>finding<br>find<br>significant effect<br>specification)<br>difference<br>significant,<br>off than<br>off even<br>something else other than colonization patters that explains these differences.<br>fixed effects falsification<br>different different<br>differences<br>Table 8 shows the results of the falsification exercise.<br>effects significant<br><!-- End of picture text -->
difference significant.

findings effect specific What is the channel through which colonial activities influence current levels of economic difficult different The first possible channel is that extractive colonial activities led to higher inequality Sokoloff who ay B80 fixed effect, 0 could explain the effects of colonial factors on development by a Q x ~~—~~ ~~—~~ effect Sokoloff argue
a — a specification, difference significant benefitted differ tions explain the effect of colonial activities on development, then local colonial activities effect differently, finds influence finds significantly
different a 7 Bon coefficients a coefficients = effects, effects The coefficient on the interaction term is positive and significant, findings difference coeffieffect effect effect find
significant specification coefficients This estimated effect probably captures the fact that the colonizers exploited An additional implication of this hypothesis is that we should observe a negative effect of institutions differences differences significant
# The coefficients on pre-colonial population density and on coefficients Overall, the results in this section suggest that institutions seem to explain the effect effects different

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## findings

effects of the effects. Sokoloff’s findings show that it is not only the identity (nationality) of the colonizers that matters
tutions in that region. Institutions in turn in�uence current levels of economic development. While we show that colonial activities are correlated with current economic development, it remains to investigate the channel connecting them in more detail. For the lack of measures of institutions at the region level, we use interactions with country level data on institutions to investigate the link. The results suggest that institutions are the channel. However, for future research we plan to construct region-level measures of institutions and elite dominance. This will allow us to study the link between colonial activities and current levels of development more extensively.

# 8 Appendix A: Variable Definitions

- PPP GDP per capita: Gross state product for each state divided by the contemporaneous population of that state and converted to PPP values using the 2000 value from the World Development Indicators. Due to data limitations, the data for Venezuela corresponds to household income.

- Poverty rate: Percentage of the population living below the poverty line, according to each country's de�nition of the poverty line.

- Gini index: Gini measure of income inequality for households.

- Health index: The health index measures the quality-adjusted-life-years (QALY) based on the health status attributed to skeletal remains, which display chronic health conditions and infections. The health index is adjusted for the age distribution of the population and is a simple average of seven health indicators: stature, hypoplasias, anemia, dental health (teeth and abscesses), infections, degenerative joint disease, and trauma.

- Pre-colonial population density: The ratio of the estimated pre-colonial population to the area of modern states.

- Colonial activities: Predominant economic activity performed during the colony in the region that matches the current day state.

- Average temperature: Average yearly temperature (<sup>�</sup> C)

- Total rainfall: Total yearly rainfall (mm)

- Altitude: Elevation of capital city of the state (kms)

26
- Landlocked dummy: This dummy is equal to one if the state does not have a sea coast.

- Percent indigenous: Percentage of the population that is indigenous for all the countries with the exception of (i) Mexico: the percentage of the population speaking an indigenous language and (ii) Peru: the percentage of indigenous or black (not only indigenous) since they are not reported separately.

- Percent black: Percentage of the population that is black (exists only for Brazil, Colombia, Ecuador, Uruguay, and the US)

- Percent indigenous or black: The sum of the pervious two variables

# 9 Appendix B: Pre-Colonial Population Density

This appendix describes in detail how we construct the pre-colonial population density variable. We use data from several sources to estimate pre-colonial population density at the state level. The main sources of information are region-speci�c chapters in Denevan (1992) and references cited in that book. This section presents the main sources for each country and explains the assumptions we used to impute population estimates for the di�erent regions of each country. In each case we adjust the estimated size of the native population in each country to match the numbers presented in Denevan (1992, Table 00.1). Appendix Table 2 lists our pre-colonial population estimates for each region.

## 9.1 Argentina

The only source of information we use corresponds to Pyle (1992), a chapter in Denevan (1992). This paper includes several estimates of the native population for di�erent regions of Argentina. We take the average of the number of natives in each region as our estimate of the denominator. In addition, using maps from the same paper, we allocate di�erent tribes or groups to the di�erent modern states. As some of the Argentinean regions identi�ed in Pyle (1992) correspond to clusters of more than one modern Argentinean states, we estimated population density for the regions presented in Pyle (1992) and we impute the same population density for all the states in the same region. In particular, the regions that include more than one state are: (i) Buenos Aires and Capital Federal, (ii) Chubut, La Pampa, Neuqu�en, R��o Negro, Santa Cruz, and Tierra del Fuego.

27
# 9.2 Bolivia

The information for Bolivia comes from Denevan (1992) for the East of the country. We also use estimates for the South Sierra derived from Cook (1981), implying a population density of 17.3 people per square kilometer for the South Sierra. In addition, Denevan (1992, p. 228) presents his preferred estimated population �gures for di�erent regions of Northeastern Bolivia: Floodplain (14.6 people per square kilometer), Lowland Savanna, mainly Mojos (2.0), Santa Cruz area (1.8), Upland Forest (1.2), Lowland Forest (0.2), and Superhumid Upland Forest (0.1). Using estimates for the area of each state belonging to each region, we estimate population density in each state.

# 9.3 Brazil

The main source of information is Denevan (1992, p. 226 and 231). Denevan presents estimated population density at time of contact for di�erent habitats in Greater Amazonia, which includes most of the Brazilian states except for portions of the coastal states in the South (Paran�a, Rio Grande do Sul, Santa Catarina, and Sao Paulo). The habitats (estimated population density at contact time) considered by Denevan are: Central coast (9.5 people per square kilometer), Floodplain (14.6), Lowland{Amazon Basin (0.2), Mangrove coasts (4.75)<sup>26</sup> , Upland and Central savannas (0.5). Using these estimates we classify each Brazilian state in each habitat and we estimate population density for the states. In the cases that a state has more than one habitat we use a weighted average considering the di�erent habitats. In order to identify the habitats of the di�erent regions we use information from the Natural Vegetation Map from the Perry-Casta~neda Library Map Collection of the University of Texas.

For the Southern states we also use information from Denevan (1992, Table 00.1) on the total population for Southern Coastal Brazil combined (which implies a population density of 4 people per square kilometer) with the previous information on the density for the di�erent habitats of the Greater Amazonia. Finally, we impute the population density of the state of Goias to the Federal District (Brasilia).

# 9.4 Chile

In the case of Chile there are no detailed estimates of population by state. Instead, there is some information on the location of several native groups, except for the Mapuche people. In this case, Cooper (1946) quoted in Denevan (1992) estimates a pre-contact

> 26For Mangrove coasts, Denevan states "probably considerably less than 9.5 per square kilometer". We use 50% of 9.5.

28
<!-- Start of picture text --> fifth<br>first<br>So we use half of the estimate we have for the Tacna region in Pert,<br><!-- End of picture text --> tion from Ocampo (1997) and Villamarin and Villamarin (1999), we estimate population Andrés,
<!-- Start of picture text --> is the average for similar regions in Colombia and Pert),<br><!-- End of picture text --> <!-- Start of picture text --> Pert).<br><!-- End of picture text --> <!-- Start of picture text --> Petén<br><!-- End of picture text --> <!-- Start of picture text --> Pacific<br>Panama”.<br>different<br>Ahuachapan<br><!-- End of picture text -->

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# 9.9 Honduras

As for El Salvador and Guatemala, we take advantage of the estimate of the total population from Denevan (1992, p. 291), which is 750,000 for both Honduras and Belize. We assume a similar population density in both areas and therefore, we get a total estimated population of 622,843 people for Honduras. To distribute this population across the states we proceed as follows. First, we consider the coastal states of Choluteca and Valle and parts of the state of El Para��so. For these areas, we apply a population density of 17.70, which corresponds to the simple average of the coastal states of La Uni�on and Moraz�an in El Salvador. This leaves us with a total estimated population of about 220,000 people. The remaining population corresponds to the eastern regiones of the country, which were populated by several peoples, such as the Lencas. Thus, we apply an estimate of 8.19 people per square kilometer to these areas, to get the total population estimated in Denevan.

# 9.10 Mexico

Estimates for Central Mexico come from Sanders (1992), in particular for Mexico, DF, Hidalgo, Puebla, Tlaxcala, Tamaulipas, and Morelos. In addition, Denevan (1992) presents population estimates for the following regions: (i) Baja California Norte and Sur; (ii) Campeche, Quintana Roo, and Yucat�an; (iii) Chiapas; (iv) Chihuahua, Durango, Sinaloa, and Sonora; (v) Coahuila de Zaragoza and Nuevo Le�on; (vi) Colima, (vii) and Tabasco. In the cases in which a region includes more than one state, we impute the same population density for each region. As in all the other cases, we adjust the population estimates so to match the total estimate for Mexico from Denevan (1992, Table 00.1).

# 9.11 Panam�a

As for all other Central American countries, we take advantage of the information that coastal areas were more densely populated. In this case, we use a population density of 0.01 people per square kilometer in the mountain areas. For the coastal regions we apply a population density of 30.88 people per square kilometer, so that we generate the total population of 1,000,000 estimated by Denevan (1992, p. 291). Using estimates for the area of each state belonging to each region, we estimate population density in each state.

31
<!-- Start of picture text --> different<br>Parana Caaguazu,<br>Parana<br>Asuncion,<br>average of the the estimates for Alto Parana and<br>for Alto Parana,<br>Itapuia<br> estimates for Formosa and Chaco in Argentina.<br>for Misiones (Paraguay) and Central.<br>finally,<br>Canindeyt.<br>Denevan ‘s<br><!-- End of picture text --> Boquerén For Caazapaé and Guaira we use the simple average of the the estimates for Alto Parana and Canindeyti for Alto Parana, Concepcion, Itapuia Neembuct, we use a weighted average of estimates for Formosa and Chaco in Argentina. For Paraguari, we use the average of estimates for Misiones (Paraguay) and Central.

PERU The information for Peri comes from Cook (1981) for most of the regions in the country 96) presents his preferred estimated population figures for six different Peruvian regions:
densities for specific states because some tribes lived in more than one state so we present

|José<br>Chana,|
|---|

Chana, Paysandt, Rio Negro were more heavily settled by peoples such as the Yaros, Chana, and Charruas, Rios first