The economic consequences of the spanish Reconquest: The long-term effects of medieval conquest and colonization

1 The Economic Consequences of the Spanish Reconquest: The Long-term Effects of Medieval Conquest and Colonization DANIEL OTO-PERALÍAS AND DIEGO ROMERO-ÁVILA Pablo de Olavide University This version: December 2014 Abstract This paper shows that a historical process that ended more than five centuries ago, the Reconquest, is very important to explain Spanish regional economic development down to the present day. An indicator measuring the rate of Reconquest reveals a heavily negative effect on current income differences across the Spanish provinces. A main intervening factor in the impact the Reconquest has had is the concentration of economic and political power in a few hands, excluding large segments of the population from access to economic opportunities when Spain entered the industrialization phase. The timing of the effect is consistent with this argument. A general implication of our analysis is that large frontier expansions may favor a political equilibrium among the colonizing agents that is biased toward the elite, creating the conditions for an inegalitarian society, with negative consequences for long-term economic development. Keywords: Economic Development, Political Power, Economic inequality, Spanish Reconquest, History JEL Classification: C21, N2, O1 ----------------------------------------------------- Corresponding Author: Diego Romero-Ávila, Pablo de Olavide University, Department of Economics, Carretera de Utrera, Km. 1, Sevilla, Spain. E-mail: [email protected]. Tel. (+34) 954 348 381. Fax: (+34) 954 349 339. Daniel Oto-Peralías, Pablo de Olavide University, Department of Economics, Carretera de Utrera, Km. 1, Sevilla, Spain. E-mail: [email protected]. Acknowledgements: A previous version of this article was presented at the 2014 American Economic Association Meeting held in Philadelphia (January 2014) and at the EH Clio Lab UC Second Annual Conference held in Santiago de Chile (August 2014). We thank Marcella Alsan and James Fenske for detailed comments on an earlier version of this article. We also thank the participants at the 2014 AEA meeting, EH Clio Lab UC Second Annual Conference, and seminars at Pablo de Olavide University and Vienna University of Economics and Business for their valuable comments and suggestions. The authors are indebted to Joan R. Rosés, Julio Martínez-Galarraga and Daniel A. Tirado for sharing with us province-level data on GDP, and industrial and agricultural output in 1860 and 1930. Thanks also go to archival staff of the National Historic Archive and the Provincial Historic Archive of Seville for helping us with the access to some of the data employed in the article. The authors acknowledge financial support from the Spanish Ministry of Science and Technology (grant ECO2009-13357), the Spanish Ministry of Economics and Competitiveness (grant ECO2012-35430), and the Andalusian Council for Innovation and Science (Excellence Project SEJ-4546). 2 “The history of no other European people has been so decisively modified by a frontier as Castile, for century after century” –Claudio Sánchez-Albornoz, in Burns (1989, p. 325). I. Introduction This paper shows that the legacy of history is particularly pervasive in Spain. We provide evidence to show that a historical process that ended more than five centuries ago, the Reconquest, is very important to explain Spanish regional economic development. The socalled Reconquista is a milestone in Spanish history. For a period of almost eight hundred years that started in 711 with the invasion of the Iberian Peninsula by the Muslims, what is now mainland Spain experienced a process fairly akin to colonialism. Throughout this long period, and after an initial phase of mere resistance, the Christians located in the north gradually reconquered the Muslim lands and implemented measures to colonize the reclaimed territory. We argue that the rate or speed of the Reconquest, that is, whether the Christian frontier advanced rapidly or not, was a crucial factor affecting the type of colonization conducted in each territory and its corresponding initial political equilibrium. A fast rate of Reconquest is associated with imperfect colonization, characterized by an oligarchic political equilibrium, thus creating the conditions for an inegalitarian society with negative consequences for long-term economic development. This paper is framed within a new stream of literature dealing with the long-term effects of frontier expansions. In a recent contribution, García-Jimeno and Robinson (2011) have proposed the “conditional frontier hypothesis” to explain the starkly contrasting outcomes derived from the frontier experiences in North America (Turner, 1920) and Latin America (Hennessy, 1978). According to this hypothesis, the consequences of the frontier depend on the initial political equilibrium existing in society at the time of the territorial expansion. In North America, where the prevailing social climate was relatively democratic and egalitarian, the frontier brought about individualism, self-government and aversion to social stratification, whereas in the more oligarchic societies of South America, the presence of a 3 frontier reinforced economic and political inequality.1 Focusing on the historical border between Castile and the Nasrid Kingdom of Granada in southern Spain, Oto-Peralías and Romero-Ávila (2015) have suggested that military insecurity is a factor that favors a political equilibrium biased toward the military elite in frontier regions, generating persistent differences in inequality. This article argues that the political equilibrium among the colonizing agents may be endogenous to the scale of frontier expansion. This is because large territorial expansion allows the elite to play a dominant role in the process of colonizing the conquered lands. Applied to our case study, this became evident after the collapse of the Almohad Caliphate in 1212 following the Battle of Las Navas de Tolosa, which enabled the Christian armies to conquer vast swathes of territory in a short period of time. The outcome involved large frontier regions dominated by military orders and the nobility, with negative consequences for long-term development. In contrast, a slow frontier expansion was associated with a more balanced occupation of the territory and a more egalitarian social structure. This was so because smaller frontier regions favored the participation of individual settlers and the Crown in the repopulation, which would lead to better political institutions and a more equitable distribution of the land – as happened in the colonization of the Duero Valley, where settlers occupied land and obtained its ownership. As argued below, these initial differences in the patterns of distribution of economic and political power persisted over time, and led to divergent development paths across what are now the Spanish provinces. This paper also contributes in several ways to a growing body of research that considers economic development as a long-term process with deep historical roots (Spolaore and Wacziarg 2013; Nunn 2014).2 First, our case study is appealing in the sense that the 1 Their analysis of the frontiers on the American continent provides evidence of both higher long-term economic growth and levels of democracy, the greater the constraints on the executive in 1850 and the larger the frontier. 2 Examples of this vibrant literature are Engerman and Sokoloff (1997), Acemoglu et al. (2001, 2008), Bockstette, Chanda, and Putterman (2002), Banerjee and Iyer (2005), Angeles (2007), Gennaioli and Rainer (2007), Baten and van Zanden (2008), Feyrer and Sacerdote (2009), Angeles and Neanidis (2009), Iyer (2010), Dell (2010), Gallego (2010), Naritomi et al. (2012), Bruhn and Gallego (2012), Easterly and Levine (2003, 2014), Ashraf and Galor (2013), Alsan (2014), Cook (2014), and Fenske (2013, 2014). 4 historical process studied in this article is very remote in time. The Reconquest ended in 1492 with the fall of Granada yet, significantly, its effects remain visible today. Explaining the reasons for the effect of the Reconquest being so persistent, along with the channels through which it took place, are questions of general interest. Second, our work is also interesting because unlike most previous studies focusing on former colonies, it analyzes the experience of a developed economy that became a leading colonial power in the Mercantilist era of colonialism.3 Third, a particularity of the Spanish case is that over a long period of time its territory experienced a process very similar to colonialism. Thus, an analysis of the Spanish Reconquest is useful because it gives clues about the subsequent colonization of the New World. When Spain colonized Central and South America in the sixteenth century, it had all the experience gained in the Reconquest and through the policies implemented in the occupation of Muslim lands. Therefore, while the recent literature has emphasized that Spanish colonial policies were significantly influenced by the preexisting indigenous organization in conquered areas (Engerman and Sokoloff 2002; Frankema 2010), it should not be ignored that the granting of large tracts of land to the nobility, for example, had a clear precedent in the homeland.4 Interestingly, the Spanish Reconquest constitutes a historical process that resembles the long-term outcomes of the colonization of North and South America. As with the contrast between northern and southern Spain, in North America (the US and Canada) a type of colony based on smallholder farmers of European descent flourished, whereas in Central and South America landowners with large estates predominated, along with other institutions such as the encomienda that perpetuated a highly unequal society (Engerman and Sokoloff 1997, 2000). 3 See Acemoglu et al. (2011a, 2011b) for other studies on historical events taking place in non-colonies. 4 In the territories of the southern plateau and Andalusia, the Crown granted large estates (or encomiendas) to the military orders and the nobility (Brenan 1943). “An encomienda was an estate given by the King in señorío, or with full manorial rights, for one lifetime or for some determinate period only. The Comendador was the title of the temporary possessor, who enjoyed all or most of the rights of the King. After the twelfth century encomiendas died out except in the military orders, in which they were the recognized form of land tenure” (Brenan 1943, p. 113). 5 In the empirical part of the paper, we create an indicator measuring the “rate of Reconquest”, which captures whether the Christian military conquests progressed rapidly or slowly when each province was reclaimed. We show that there is a robustly negative relationship between the rate of Reconquest and current per capita income across today’s Spanish provinces. This relationship does not simply reflect the fact that regions in the South are poorer, since the results survive the inclusion of latitude. The effect remains statistically significant when the regression analysis is extended to the level of municipality, even after controlling for province fixed effects. The results are not driven by a selection problem informed by the possibility that –for instance– the Christian kingdoms chose to conquer faster economically less attractive territories. A number of falsification tests show that there is no link between the rate of Reconquest and several indicators of preReconquest economic development. We also analyze the channels through which the rate of Reconquest has affected current income. The results suggest that the concentrations of economic and political power played central roles as intervening variables. This is consistent with the hypothesis formulated by Engerman and Sokoloff (1997, 2000) and Acemoglu, Johnson, and Robinson (2002) whereby a high concentration of economic and political power in a few hands has impaired modern economic growth because it precludes large segments of the population from participating in economic activity when the opportunity to industrialize arrived. The timing of the effect of the Reconquest is consistent with this hypothesis, since its negative effect became apparent during the industrialization period (but not before). This interpretation is also congruent with the fact that although in 1860 (the onset of industrialization in Spain) the negative impact of the rate of Reconquest on per capita income was still absent, the effect was already present in some of the foundations of modern economic growth, such as human capital. A general conclusion of our analysis is that accelerated (and imperfect) colonization may create the conditions for an inegalitarian society, with negative consequences for long-term economic development. 6 The remainder of the paper is organized as follows. Section 2 provides a brief historical overview of the Spanish Reconquest. Section 3 describes the indicator for the rate of Reconquest and the other variables used in the paper. Section 4 presents the analysis of the effect the Reconquest has had on current economic development, while Section 5 provides several sensitivity analyses. Section 6 analyzes the timing of the effect of the Reconquest, and Section 7 investigates the possible channels through which this effect occurs. Finally, Section 8 puts forward some implications, and concludes. II. Historical Background5 An interesting feature of Spanish history is that for a period of almost eight hundred years the Iberian Peninsula experienced a process somewhat akin to colonialism. In 711, what is now the Spanish mainland was invaded by the Muslims, who in a very short period of time occupied almost the whole of the Iberian Peninsula and created a Muslim domain that was known as al-Andalus. This western European Muslim territory achieved great economic and cultural development, and for most of the period under Moorish rule it was the most advanced country on the continent (Chejne 1999). With the passage of time, the Christian outposts located in northern Spain gradually conquered the Muslim territory in a process that lasted until 1492, with the fall of the Nasrid Kingdom of Granada. This long period of Christian conquest is known as the Reconquista. Military campaigns were followed by a process of colonization or repopulation of the new lands. The way in which the colonization was conducted had fundamental consequences for each region’s ensuing development.6 The crucial outcomes of the repopulation process were how land was distributed and who held political power. Other potential aspects of relevance were the resulting level of population density, the degree of integration of the Muslim population, and the extent to 5 This historical overview draws on Sánchez Albornoz (1932), Brenan (1943), Dominguez-Ortiz (1955), Herr (1958), Vicens Vives (1969), Malefakis (1970), Sobrequés (1972), Carrión (1975), Ruiz-Maya (1979), Glick (1979), Mestre-Campi and Sabaté (1998), Guichard (2002) and García-Ormaechea (2002). 6 Spanish historiography labels repopulation as the process of colonization of the reconquered lands by the Christian kingdoms. In this paper, we use the terms colonization and repopulation indistinctly to refer to this process. 7 which preexisting technologies were preserved. An important factor that decisively affected the outcome of the repopulation was the speed of the Christian conquests; that is, whether the Christian frontier advanced rapidly or slowly (Sobrequés 1972; Malefakis 1970). We call this factor “rate of Reconquest”. A slow process in this case is generally associated with a more complete and balanced repopulation. This is because a smaller area to be colonized favored the participation of individual settlers and the Crown in the repopulation, which led to better political institutions and a more egalitarian distribution of land. By contrast, a rapid process is associated with imperfect colonization (González Jiménez, 2006). In this case, a larger area to be repopulated implied fewer resources were available relative to the magnitude of the task; that is, an insufficient number of settlers, as well as administrative and military difficulties to govern and defend the territory. This favored the participation of the nobility and military orders in the organization and defense of the new lands. Figure 1 shows how the rate of Reconquest differs markedly across the different stages of this historical process. During the first three and half centuries of the Reconquest (from 711 to 1062) the Christian kingdoms conquered about 155,000 km2, while over the next two centuries (until 1266) the reconquered area almost doubled (about 287,000 km2). Thus, the rate of Reconquest (i.e., the area reconquered divided by the duration in years of that period) was much slower in the first period (approx. 441 km2/year) than in the second period (approx. 1407 km2/year). These differences had profound consequences for the type of colonization conducted in each case. [Insert Figure 1 about here] A slow rate of Reconquest implied that individual settlers with few economic resources could colonize the territory by themselves. This was the case of the repopulation of the Duero Valley, where the distinctive feature of this process was the predominance of private initiative; that is, a type of repopulation conducted by individuals who occupied land and acquired its property through the institution of presura or aprisio (i.e., apprehension of land). In general, this repopulation implied a more balanced occupation of the land, as 8 reflected in the presence of a large number of small settlements that appear evenly distributed across the repopulated territory. It also led to the creation of a society with a democratic structure of free peasants with access to land (Vicens Vives 1969).7 The Crown also found it easier to organize the repopulation when the area to be occupied was not large. Thus, in the lands comprised between the rivers Duero and Tagus the repopulation was to a large extent officially organized and conducted by the King through the creation of municipalities or councils (repoblación concejil), which delimited and distributed smallholdings among settlers (Ruiz-Maya 1979). When the repopulation was conducted by the Crown, the result was still beneficial to the peasantry, since land was relatively well distributed and cities remained under royal jurisdiction.8 In addition, a smaller area to be repopulated (consequence of a slow rate of Reconquest) favored the preservation of Muslim agricultural technologies and the integration of the Muslim population. Indeed, the repopulation in Aragon was different than in Castile, largely due to the smaller area this kingdom reconquered. In this case, the King was able to carefully organize the colonization, and the nobility played a smaller role (Sobrequés 1972). In contrast to Castile, the repopulation of Aragon had such particularities as a higher concern for maintaining irrigation structures, greater respect for the Muslim population, and less reward for the aristocracy for their participation in the conquest and defense of new territories (Casado-Alonso 2002; Vicens Vives 1969). The above contrasts with the situation in the stages of the Reconquest comprised between 1062 and 1266, particularly in Castile, where the Christian conquests progressed much more rapidly. The larger areas to be repopulated rendered it unfeasible to colonize through individual settlers. Likewise, it was also difficult for the King to be able to organize the repopulation on such a large scale. The intervention of the nobility and military orders was 7 The northern and mountainous territories that did not fall under Muslim control were characterized by the existence of few large estates, as well as by a social structure composed of a majority of free men and little class differentiation (Glick 1979). 8 Under royal jurisdiction, the peasantry faced a smaller tax burden than under noble jurisdiction, where seigneurial duties were added to state taxes (García-Ormaechea 2002). 9 therefore required in order to conduct an effective occupation and defense of the new lands.9 This situation was intensified after the Muslim defeat at the Battle of Las Navas de Tolosa in 1212. In a short period of time (between 1225 and 1250), most of the southern third of the peninsula suddenly fell into Christian hands (Malefakis 1970). By the midthirteenth century, the Reconquest was almost complete, with the exception being the Nasrid Kingdom of Granada. This gives an indication of the huge demographic effort that Castile would need to make in the thirteenth century in order to simultaneously repopulate Andalusia, La Mancha, Murcia and the majority of Extremadura (González Jiménez, 2006). The magnitude of the frontier expansion profoundly affected the subsequent social reorganization (Sobrequés 1972; Malefakis 1970). “[G]iven the weak resources of the period, the Castilians had to deploy enormous effort in order to cater for the administration, defense, and economic development of these southern lands [...] Inevitably, the disparity between the magnitude of the task and the precarious resources available produced problems. One of these was the birth of the great landed estates” (Cabrera Muñoz, 1989, p. 465); another was the concentration of political power in the hands of the nobility. In a context in which the rapid advance of the Christian frontier created clear problems of manpower and resources, the Crown found in the military orders and the nobility the most “effective means of defense in the border region” (Forey 1984, p. 214). The warrior-monks and warlords were clearly the best alternative for holding and defending extensive areas in the frontier regions. Since the Castilian kings by themselves were unable to administer and organize such a huge territory, they granted large estates and jurisdictional rights to the nobility and military orders. As a result, the concentration of landownership and the proportion of territory under the jurisdiction of nobles or military orders were the highest in 9 Following the example of the Holy Land crusaders, the Castilians created three great military orders that served as armies for the kingdom to conquer Muslim lands and defend the Christian frontier. The order of Calatrava was founded in 1158, the order of Santiago in 1170, and the order of Alcántara in 1176, all during the second half of the twelfth century, a period from which military orders grew in importance due to their key role in the defense of the frontier (González Jiménez 1989). 16 major trading partners and industrial centers in Europe– could also have been more important during the nineteenth century, when commercial relations across regions and countries intensified. In order to dispel doubts, we next control for variables that may be associated with both sets of geographic hypotheses. We begin with factors exhibiting geographic variation along a North-South gradient that mimics the direction of the Reconquest. The incorporation of latitude into column 11 (which enters insignificantly) does not affect the statistical significance or size of the coefficient on rate of Reconquest. Therefore, our results do not simply capture the fact that southern Spanish regions are poorer. Columns 12-14 control for such variables as temperature, rainfall and humidity, which may also affect soil quality and its suitability for crops that require large estates (and in turn induce the concentration of economic power in the hands of the landed elite). Higher aridity and less rainfall may also require a higher concentration of land on the grounds of economic efficiency and profitability (Brenan 1943). Hence, they may be factors that confuse the long-term effect of the Reconquest on development. It is worth stressing that none of these factors enters significantly or reduces the statistical significance of the effect of the Reconquest.19 The baseline result remains unaltered when column 15 introduces a direct measure of soil quality constructed on the basis of several dimensions (nutrient availability and retention capacity, rooting conditions, oxygen availability to roots, excess salts, toxicity and workability) from FAO/IIASA (2010) data, which enters with a highly significant and positive coefficient. Columns 16-18 exploit provincial variation in the suitability of land for such cash crops as sugar, cotton and tobacco in order to capture the possibility of a contrast in the suitability of land for large plantations in the South of Spain as opposed to the North (as in the US). It is worth noting that none of these three controls appears statistically significant or affects the main findings. The introduction in columns 19 and 20 of average altitude and terrain ruggedness does not alter the baseline results either. Only the former is marginally significant and with a negative coefficient. 19 Only humidity slightly reduces the size of the relevant coefficient from –0.018 to –0.015. 17 [Insert Table 1 about here] Columns 1-11 in Table 2 control for geographic attributes related to transportation costs that include access to the Mediterranean Sea, the Atlantic Ocean, and the Cantabrian Sea, a dummy indicator for being an island, a coast dummy, coast length over surface area, distance to the coast, border with Portugal, and distance from Madrid, London, and Paris. Of all these controls, only distance to the coast and border with Portugal are statistically significant and negatively associated with current development. Most importantly, the effect of the Reconquest remains fairly robust to these additions. Columns 12-16 control for indicators accounting for natural resource endowments that include the percentage of agricultural land in 1900, the percentage of arable land in 1962, log mining output in 1860, a coal dummy in 1860, and log coal output in 1860. Only provincial mining output is statistically significant and with a positive coefficient, whereas the baseline results remain unaltered. [Insert Table 2 about here] B. Baseline Specification and Robustness Checks Column 1 in Table 3 includes in the same specification all the controls that are individually significant. This is our paper’s baseline specification. Even in this case, the coefficient on the Reconquest measure is significant at the 1% level, and its size is not reduced. Besides, the dummies Crown of Aragon and Madrid, soil quality, and log mining output in 1860 continue to be statistically significant and positively associated with current development, while the coefficient on urban population density in 800 is negative and marginally significant. The strength of the effect of the rate of Reconquest on current development is illustrated in Figure 2 by a scatter plot of the two variables, after conditioning on the set of controls included in column 1. The partial R-square of the rate of Reconquest is 36% in this baseline specification. It is remarkable that an indicator measuring a historical event that occurred many centuries ago has such a large explanatory power on current income. 18 A typical concern of empirical analyses with a limited number of observations is the possibility that a few extreme cases drive the results. Columns 2-6 in Table 3 show that our findings are robust to removing outliers detected by the following procedures: leverage, standardized residuals, studentized residuals, Cook’s distance, DFITS, Welsch distance, and DF-Beta. Likewise, the effect of the Reconquest remains unchanged when the northern provinces forming the core of initial Christian outposts, for which the reconquered area was assumed to be zero, are excluded from the analysis (column 7). Another potential concern is the presence of spatial correlation, which may reduce the true precision of the effect. We have checked that the statistical significance of the coefficient on the rate of Reconquest is not reduced when using standard errors corrected for spatial dependence (i.e., Conley (1999) standard errors). Finally, the inclusion of the geographic coordinates (latitude and longitude) in the baseline specification does not eliminate the effect of the Reconquest. Notably, the effect remains statistically highly significant even when including a higherorder (cubic) latitude/longitude polynomial.20 [Insert Table 3 and Figure 2 about here] V. Sensitivity analysis A. Municipality-level Analysis Although the relationship between the rate of Reconquest and current GDP appears robust to the inclusion of many geographic and historical controls, as well as to the removal of outliers, a possible objection is that some unobservable province-level characteristics are driving this result. One way to address this concern is to conduct the analysis at a finer level, namely, using municipality data, and test whether the results hold even when conditional upon province-specific fixed effects. This test is quite strong, and allows us to exploit within-province variation in the conditions surrounding the Reconquest. The inclusion of such powerful fixed effects enables us to account for any systematic and structural particularities related to the history of each province, which cannot be controlled 20 These unreported results are available in the unpublished appendix. 19 explicitly in a province-level analysis. For this exercise, we create a dataset of more than 8,000 municipalities in Spain. We impute to each municipality the rate of Reconquest corresponding to the Reconquest phase to which the municipality belongs. As proxies for income at local level, we use current data for average socioeconomic conditions, average number of vehicles per household, and labor force activity rate, which appear clearly linked to economic development. This is corroborated by the existence of a high correlation with GDP per capita at provincial level (the correlation is 0.81 with average socioeconomic condition, 0.54 with average number of vehicles per household, and 0.73 with labor force activity rate). Table 4 presents the results with standard errors clustered at provincial level in order to consider spatial correlation, which can be substantial in this municipality-level analysis. All regressions include province dummies. Columns 1, 3 and 5 show that the rate of Reconquest appears negatively associated with the three proxies for local economic development, at least at the 5% significance level after incorporating the municipalities’ total population to control for differences in municipal size, latitude, and geographic factors related to transportation costs, such as distance to Madrid, distance to the coast, and distance to the nearest provincial capital (in linear and square form), together with a provincial capital dummy. In columns 2, 4 and 6, we extend the control set to incorporate additional variables for the municipalities’ climate, geography and topography. These include altitude, annual average temperature, annual rainfall, and seven dimensions measuring soil quality (nutrient availability and retention capacity, rooting capacity, oxygen availability to roots, excess salts, toxicity, and workability).21 It is worth noting that the baseline effect of the Reconquest remains statistically significant in all cases. This alleviates our concern that unobserved heterogeneity at provincial level might be the driving force behind the significant effect the Reconquest has had on current development in the province-level analysis. 21 The inclusion of all these controls together, along with the province-level fixed effects, is particularly important here. This is because with only 50 observations in the province-level analysis, we could not control for all the individual regressors together, since the degrees of freedom would dramatically fall. Instead, we opted for including in the same specification only those regressors that were found individually significant. 20 [Insert Table 4 about here] B. Alternative Indicators of the Reconquest Thus far, we have reported the existence of a strong and robust negative effect of the Reconquest on current income. However, a further concern about our previous results is that they hinge on a particular indicator of the Reconquest. To address this concern, in the first place, we check that our results are robust to the use of an alternative indicator of the rate of Reconquest, which divides this historical process in stages of the same duration. More specifically, provinces are classified according to the century in which they were reconquered. As in the construction of the baseline Reconquest indicator, the territory that was not occupied by the Muslims is assigned a reconquered area equal to zero. For each century, we compute the total land area reconquered in that period, differentiating between the areas conquered by Castile and Aragon. Then, the rate of Reconquest in a given province is estimated as the total land area that was reconquered in the century in which that province was reconquered. The results shown in Tables 1, 2 and 3 are highly robust to the use of this alternative indicator (the detailed results are provided in Tables A9-A11 of the unpublished appendices). In the second place, with the same underlying argument used in the calculation of the rate of Reconquest, we create an indicator consisting of a dummy variable indicating whether the province was reconquered after the collapse of the Almohad Caliphate in 1212 following the Battle of Las Navas de Tolosa. This military victory by the Christian armies enabled them to conquer a vast territory in a short period of time. The rapid advance of the Christian frontier made the task of repopulation difficult and demanding, giving rise to a type of colonization in which the nobility and military orders played a predominant role in the occupation and defense of the new territories, with negative consequences for long-term economic development. Table 5 replicates regressions in Table 3 using this alternative indicator of the Reconquest called post-1212 conquest. The coefficient on post-1212 conquest is negative and statistically highly significant in all the columns. The magnitude of the effect is also 21 economically important in this case. Column 1 indicates that, conditional upon the controls included in the regression, the provinces conquered after 1212 are 24% poorer (e-0.274 – 1 ≈ –0.24). Thus, according to this result, the large frontier expansion recorded after 1212 led to negative long-term outcomes across today’s Spanish provinces.22 [Insert Table 5 about here] C. Falsification Test This section conducts a falsification exercise to show that the rate of Reconquest is not negatively related to the level of economic development in the pre-Reconquest era. A main threat to the validity of our analysis is the possibility that areas conquered faster were initially poorer, which could have facilitated a rapid conquest. If those areas conquered faster were worse off even before the Reconquest, then the observed relationship between the rate of Reconquest and current income may be driven by the territories’ intrinsic characteristics, rather than by the type of colonization conducted by Christians. However, it is very unlikely that the rate of Reconquest hinged on the territories’ economic development, since the pace of the advance of the Christian frontier was arguably caused mainly by the relative military weakness of the Muslim territory in each period. Therefore, the rate of Reconquest was the consequence of an exogenous factor with respect to the territories’ economic potential. Our aim is to verify that our indicator of the Reconquest does not have a statistically significant negative association with economic development and other outcome variables before the Reconquest. We measure pre-Reconquest development primarily through city population and urban population density in 800, which is the earliest year for which urban population data are available. Given that the Reconquest had hardly begun at that time, it serves our purpose. We also consider additional outcome indicators related to preReconquest development. These include years since the transition to agriculture, ancient 22 We also replicated all the regressions in Tables 1 and 2, finding that the coefficient on post-1212 conquest was always negative and statistically significant. These unreported results are available in Tables A7-A8 of the unpublished appendix. 22 (pre-medieval) settlements over surface area, Roman road density (total roads and main roads), the ratio of the number of locations where imperial coinage was found to surface area, Roman villas over surface area, and density of bishoprics circa 600. To assess whether these variables can be used as plausible measures of early development, we look at their correlation with an indicator of land suitability for agriculture –the percentage of agricultural area in 1900–, since pre-industrial prosperity is commonly considered to be related to soil fertility and, more specifically, to agricultural land potential. Remarkably, all the indicators –except for years since the transition to agriculture– are positively correlated with the percentage of agricultural area. In the case of city population and the density of urban population in 800, Roman road density –total and main roads–, presence of imperial Roman coinage, and Roman villas, correlations are statistically significant.23 Very similar correlations follow when we employ the variable percentage of arable land in 1962 as a measure of land suitability for agriculture. These results indicate that most indicators of pre-Reconquest development reveal expected relationships with agricultural land potential, which makes us more confident about their reliability. Table 6 provides the results on the relationship between the rate of Reconquest and early development. It is worth noting that the rate of Reconquest is not negatively associated with any of the measures of early economic development.24 The above findings suggest that the effect of the Reconquest does not merely represent the perpetuation of differences in economic development that already existed before the Reconquest, or mean that provinces conquered more rapidly started off at a disadvantage or were intrinsically poorer. [Insert Table 6 about here] 23 For total Roman road density, the coefficient of correlation is significant at the 10.7% level. Detailed results are provided in the unpublished appendix. 24 This analysis omits those control variables that are meaningless when the dependent variable is a measure of pre-Reconquest development, namely, Crown of Aragon, Madrid, and border with Portugal. Nevertheless, we have confirmed that the findings are the same when they are included. For obvious reasons, urban population density in 800 was also excluded from the set of controls. We also confirmed that the indicator of post-1212 conquest is not related to pre-Reconquest economic development either. These unreported results are available in Tables A14-A15 of the unpublished appendix. 23 VI. The Timing of the Effect of the Reconquest The above results confirm the strong and robust negative effect that the Reconquest has had on current per capita income. A question that requires further study is when this effect actually took place. This is a key issue because it provides clues about the nature and causes of the effect. On the one hand, if our findings were due to –for example– some geographic confounding factor, the effect of the Reconquest would probably be visible at all times.25 On the other hand, the analysis of the timing of the effect is useful for considering the mechanisms at work. For example, if the main implications of the rapid advance of the Christian frontier were related to the destruction of Muslim technologies or to a lack of agglomeration economies due to low population density, the negative effect should have become apparent soon after the Reconquest. Table 7 presents estimates of the effect of the Reconquest at different moments in time: 1860, 1930, 1971 and 2005. We select 1860 as our first point in time because there are no data on GDP for Spain’s provinces before that date.26 The regression results shown in Panel A are appealing because they do not reveal a simple direct effect of the Reconquest on economic development. As shown in column 1, the coefficient on rate of Reconquest is insignificant in 1860, around the time when Spain entered the industrialization phase (Pascual and Sudriá 2002; Rosés 2006).27 This contrasts with the negative and highly significant coefficient found since then (columns 2-4). We find similar results when log GDP per capita is replaced by log industrial production per capita, which may be more closely related to industrialization (columns 5-8). Panel B provides the standardized effect of rate of Reconquest (i.e., the coefficient multiplied by the standard deviation of rate of 25 In this regard, the evidence presented so far dismisses such a possibility, since the effect is quite robust to many geographic controls, and the rate of Reconquest is not related to indicators of early development. 26 There is also the possibility of using urbanization rate as a proxy for economic development for previous periods. However, we prefer not to use this variable since it does not accurately measure the level of economic development at the subnational level for the case of Spain. This is because there are many densely populated agro-towns distributed across the southern part of Spain that accumulate a large number of landless peasants, but have very few features consistent with high levels of economic development (Reher 1990). 27 The fact that Spain began its industrialization around 1860 is well reflected in the evolution of the railway network, which grew from less than 400 kilometers in 1855 to 5,076 kilometers in 1866 (Pascual and Sudriá 2002). 24 Reconquest and divided by the standard deviation of the dependent variable). Focusing on GDP per capita, we observe that the negative effect of the Reconquest does not diminish over time, which reflects a high degree of persistence.28 [Insert Table 7 about here] Table 7 shows the effect of the Reconquest is clearly linked to industrialization. We pursue this question further by taking into account that the exact timing of industrialization in Spain may be endogenous. Thus, we complement the previous analysis with some panel regressions that use industrialization in the UK and the US (Mitchell 2007a, b) as a measure of the opportunity to industrialize, following the insights from Acemoglu, Johnson, and Robinson (2002, pp. 1274-1275). The panel data specification is as follows: yit= αi + θt + δ · Reconquesti x Industrializationt + νit (2) where yit is either provincial GDP per capita or industrial output per capita expressed in relative terms with respect to the national average at date t (1860, 1930, 1971, and 2005). αi is a set of province-level dummies and θt stands for a set of time dummies. Reconquesti represents the rate of Reconquest in province i and Industrializationt denotes either UK industrial output or US industrial output at date t. The coefficient of interest is δ on the interaction between rate of Reconquest and industrialization, which should be negative and statistically significant. Table 8 presents the panel regressions for the cases in which the dependent variable is relative GDP per capita and relative industrial output per capita. It is worth stressing that the interaction term δ appears negative and statistically significant at the 1% level in all cases, which is consistent with the results reported in Table 7. The magnitude of the coefficient of interest is found to be substantially larger (in absolute terms) in the specifications that use industrial output per capita as the dependent variable. This can be explained to the extent that industrial output is more closely related to industrialization than GDP. In sum, these results indicate that the effect of the Reconquest 28 Table A16 of the unpublished appendix shows a very similar pattern in the timing of the effect when post1212 conquest is used as an alternative indicator of the Reconquest. 25 on income occurred during industrialization, and has persisted since then. The remainder of the paper sets out to explain these findings. [Insert Table 8 about here] VII. Mechanisms at work In Section 2, we argued that the rate of Reconquest was a crucial factor affecting the outcome of the repopulation process. A rapid rate is generally associated with imperfect colonization, with negative consequences for each region’s subsequent development. The rapid advance of the Christian frontier made the task of repopulation more difficult and demanding, which originated several problems, such as scarcity of settlers and resources, defense requirements for vast territories, and the governance of a large conquered Muslim population. What follows describes the potential channels that may help explain the effect of the Reconquest on current development, as well as the way they can be measured. We also discuss the consistency of each alternative explanation with the observed timing of the effect. A. Economic and Political Power Concentration Spanish historiography suggests that two key outcomes of the repopulation process were how land was distributed and who held political power. This constitutes our main hypothesis, and the argument deserves to be further developed. The rate of Reconquest affected the possibility that either individual settlers or the nobility and military orders gained control over the newly conquered territories. As historically documented, a greater area to be repopulated increased the likelihood that nobles and military orders were called upon to participate in the repopulation and defense of such vast territories. Consequently, a rapid frontier expansion favored an initial political equilibrium biased toward the nobility, which led to the concentration of political power –in the form of jurisdictional rights– and economic power –in the form of land– in the hands of this social group. The consequences of a high concentration of power by the nobility were pervasive. Jurisdictional rights provided the landowning nobility with the legal and political apparatus 32 jurisdiction is somewhat lower. According to these results, both factors seem to be relevant mechanisms explaining the long-term consequences of the Reconquest. Regarding population density, the coefficient on rate of Reconquest is insignificant in the regression without controls, while it becomes statistically highly significant when control variables are included. The coefficient has an expected negative sign, and the effect is economically important (columns 7–8). Population density can thus be considered a potential channel for the effect of the Reconquest. However, an empirical problem here is that we cannot distinguish which part of the effect of population density works through economic and political power concentration, or through other mechanisms such as agglomeration economies. This evidence does not therefore allow us to know whether population density affects economic development beyond its effect on economic and political inequality. Columns 9–12 show that the coefficient on rate of Reconquest is statistically insignificant when the dependent variable is either Moorish ancestry or road density. With the evidence at hand, this suggests that the degree of integration of the Muslim population and market fragmentation are not relevant mechanisms explaining the long-term economic consequences of the Reconquest. As regards the two indicators related to the role of the Church and religion (columns 13-16), the coefficient on rate of Reconquest is only statistically significant in the case of villages under Church jurisdiction. However, when the set of control variables is included the statistical significance is greatly reduced, and most importantly, the sign is contrary to predictions. This is because a rapid rate of Reconquest is expected to lead to more Church jurisdictions, which would bring about lower GDP per capita (implying a positive coefficient on rate of Reconquest). [Insert Table 9 about here] D. Outcome Indicators at the Onset of Industrialization The evidence presented in this section largely supports the view that the concentration of economic and political power plays a central role in explaining the Reconquest’s effect and 33 why it became apparent during the era of industrialization. Table 10 provides additional evidence consistent with this hypothesis by focusing on the decisive moment in which Spain began industrializing. It shows that although the Reconquest’s impact on income was not yet apparent in 1860, some of the fundamentals of modern economic growth were already undermined at the onset of the industrialization period. Our dependent variables are a number of factors that are relevant for economic growth, all measured in the 1860s. They are two indicators related to education (literacy rate and school enrollment), two related to health (infant mortality and life expectancy), two associated with political participation (percentage of electors and voters), and two indicators related to social conflict (criminality and convicts). According to our view, we expect the rate of Reconquest –working through economic and political inequality– to lead to lower human capital (negatively affecting education and health), lower political participation, and higher social conflict.37 This is precisely what we observe in columns 1–8 in Table 10. [Insert Table 10 about here] The last two columns perform a falsification test by analyzing the relationship between, on the one hand, the rate of Reconquest and, on the other, agricultural productivity and agriculture’s share of GDP (both measured in 1860). If the coefficient on rate of Reconquest is negative and statistically significant, particularly in the case of agricultural productivity, it may suggest that provinces corresponding to areas that were conquered faster have poorer land or a less favorable climate, which would cast doubts on our conclusions. By contrast, if the coefficient is positive and significant in both cases, it will imply that those same provinces have a competitive advantage in agriculture and are specialized in this sector, which would also add confusion to our hypothesis about economic and political inequality as one of the main channels explaining the effect of the Reconquest. The results shown in columns 9 and 10 are again consistent with a genuine effect of the Reconquest, as well as with the empirical validity of the power concentration 37 Regarding political participation, it is important to note that at that time a limited suffrage system based on capacity and fiscal criteria was in place. 34 hypothesis. All in all, the evidence provided in Table 10 indicates that although in 1860 there was not yet a statistically significant relationship between rate of Reconquest and income, the conditions were already created for the subsequent failure to industrialize. VIII. Conclusions The legacy of history appears particularly pervasive in the case of Spain. This paper shows the Reconquest in the Middle Ages to have been a major historical process shaping the distribution of regional income. The rate of Reconquest, which captures the magnitude of the colonization effort required in the period when each one of what are now today’s provinces was conquered by the Christians, has a robust and strong negative effect on current income. Our results are robust to controlling for historical controls and a wide array of climatic, geographic and natural resource endowments that account for simple and sophisticated versions of the geography hypothesis. Of particular interest is the lack of a significant effect due to differences in land suitability for plantation crops featuring economies of scale in production. Moreover, the effect of the rate of Reconquest survive the inclusion of latitude, indicating that we are not simply capturing the fact that regions in the South are poorer. The results also remain unaltered when employing an alternative indicator of the Reconquest, measuring whether the province was conquered after 1212. A municipality-level analysis that includes province-level fixed effects also provides evidence supporting the existence of a negative effect of the rate of Reconquest on economic development. In addition, a number of falsification tests indicate that the rate of Reconquest is not associated with indicators of pre-Reconquest economic development. We argue that a rapid rate of Reconquest led to imperfect colonization, mainly characterized by a high concentration of power in a few hands. The evidence supports the view that a fast frontier expansion favored a political equilibrium biased toward the military elite (i.e., the nobility), which generated a high concentration of economic and political power, thus creating the conditions that led to the exclusion of large segments of the population from participating in the economic opportunities that opened up with the arrival of industrialization. The result was that provinces featuring an unequal distribution of 35 economic and political power fell behind during the industrialization period. Thus, the Reconquest set in motion processes that generated persistent inequality, constituting a severe impediment to the requirements for modern economic growth, which is based on entrepreneurship, innovation, and the participation in economic activity of broad segments of the population. Our results contribute to the novel literature on the political-economic effects of frontier expansions in that the existence of a large frontier that needs to be occupied and defended from the enemy may lead to a shift in the balance of power toward dominant groups, which may create the conditions for an inegalitarian society, with negative consequences for longterm development. This study of the Spanish Reconquest is also appealing from the point of view of the literature on colonialism, because it gives clues about the colonization of the New World. When Spain colonized Central and South America in the sixteenth century, it had the long experience gained in the Reconquest. The policy of distributing economic power in the form of large estates, as well as of political power in the form of feudal rights, as applied in Spain since the mid-eleventh century (becoming widespread as of the thirteenth century) is a foretaste of what would later be implemented in the New World. Finally, a question that deserves further research is why the effect of the Reconquest resulting from the pattern of colonization of the conquered lands is so persistent, even though today some sources of this problem are no longer present. The early obstruction of industrialization may have long-lasting consequences. Historical, economic, and political inequality may have affected the initial paths of industrialization and development and, once launched, different economic forces (e.g., increasing returns) reproduce the initial divergence. 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Madrid: Tipografía de Archivos. 48 Dependent variable: City population in 800 Density of urban population in 800 Years since transition to agriculture Ancient settlements over surface area Roman roads density Roman roads density: Main roads Coinage of imperial Roman coins over surface area Roman villas over surface area Number of bishoprics circa 600 over surface area (1) (2) (3) (4) (5) (6) (7) (8) (9) 1.411 0.104 -1.348 0.03 0.483 0.141 0.002 0.007 0.001 (0.925) (0.067) (1.197) (0.031) (0.318) (0.198) (0.002) (0.011) (0.003) Distance to the coast 4.871 0.281 -13.78** -0.266 0.644 2.516** -0.012 0.011 -0.016 (3.553) (0.256) (5.887) (0.166) (2.124) (0.984) (0.013) (0.043) (0.018) Altitude (average) -0.013 -0.001 0.054*** 0.000 0.001 -0.01** 0.000 0.000 0.000 (0.01) (0.001) (0.019) (0.001) (0.008) (0.004) (0.000) (0.000) (0.000) Soil quality 2.585 0.176 -4.669 0.768 -4.147 7.445* 0.088* 0.072 -0.012 (3.378) (0.237) (16.322) (0.744) (12.417) (3.971) (0.05) (0.14) (0.075) Mining output in 1860 0.335 0.02 0.196 0.03 0.271 0.15 0.000 0.000 0.001 (0.359) (0.025) (0.722) (0.029) (0.358) (0.123) (0.002) (0.007) (0.002) R 2 0.18 0.17 0.21 0.19 0.06 0.19 0.10 0.06 0.03 Number of observations 50 50 50 50 50 50 50 50 50 Notes : Variables descriptions are provided in Table A1. The estimations include a constant term, which is omitted for space considerations. Robust standard errors are in parentheses. *, ** and *** denote significance at the 10, 5 and 1% level, respectively. TABLE 6 - FALSIFICATION TEST: THE EFFECT OF THE RECONQUEST ON PRE-RECONQUEST DEVELOPMENT Rate of Reconquest 49 (1) (2) (3) (4) -0.011*** -0.026*** (0.003) (0.005) -0.002*** -0.004*** (0.000) (0.001) Time dummies Yes Yes Yes Yes Province dummies Yes Yes Yes Yes R20.65 0.63 0.66 0.63 Number of observations 200 200 200 200 TABLE 8 - THE TIMING OF THE EFFECT OF THE RECONQUEST: PANEL RESULTS Notes : Variables descriptions are provided in Table A1. The dependent variables GDP and industrial output per capita are expressed in relative terms with respect to the national average in each period. The panel consists of four data points: 1860, 1930, 1971 and 2005. The estimations include a constant term, which is omitted for space considerations. Robust standard errors are in parentheses. *, ** and *** denote significance at the 10, 5 and 1% level, respectively. Rate of Reconquest * UK industrial output Rate of Reconquest * US industrial output Dependent variable is relative GDP per capita (average=100) Dependent variable is relative industrial output per capita (average=100) Reduced-form results Reduced-form results 1860 1930 1971 2005 1860 1930 1970 2005 (1) (2) (3) (4) (5) (6) (7) (8) Panel A: Regression Results 0.010 -0.015* -0.023*** -0.019*** 0.034*** -0.041*** -0.056*** -0.040*** (0.006) (0.008) (0.005) (0.004) (0.01) (0.014) (0.013) (0.014) 0.001 -0.007 -0.007 -0.016* 0.005 0.012 -0.009 -0.028 (0.021) (0.011) (0.009) (0.008) (0.017) (0.024) (0.022) (0.027) Crown of Aragon 0.142 0.184* 0.131** 0.093** 0.248 0.2 0.196 0.201 (0.099) (0.098) (0.053) (0.041) (0.201) (0.169) (0.145) (0.198) Madrid 0.595*** 0.909*** 0.638*** 0.412*** 0.711*** 0.978*** 0.432** -0.136 (0.12) (0.139) (0.082) (0.061) (0.171) (0.281) (0.181) (0.176) Distance to the coast 0.032 0.001 -0.016 -0.027 0.086 -0.033 0.066 0.1 (0.066) (0.068) (0.038) (0.032) (0.084) (0.155) (0.1) (0.117) Border with Portugal -0.15 -0.118 -0.046 -0.034 -0.334* -0.238 -0.007 -0.181 (0.149) (0.098) (0.071) (0.046) (0.187) (0.219) (0.2) (0.224) Altitude (average) 0.000 -0.001*** -0.0004*** -0.0001 -0.0005** -0.001*** -0.001*** -0.0003 (0.0002) (0.0002) (0.0001) (0.0001) (0.0002) (0.0004) (0.0003) (0.0004) Soil quality 0.781** 0.369** 0.426*** 0.319*** 0.554 0.962** 0.693* 0.177 (0.34) (0.171) (0.119) (0.083) (0.411) (0.422) (0.348) (0.346) Mining output in 1860 0.003 0.009 0.004 0.006* 0.021 0.016 0.029** 0.03** (0.008) (0.006) (0.003) (0.003) (0.013) (0.011) (0.011) (0.012) R 2 0.48 0.63 0.71 0.68 0.46 0.60 0.56 0.33 Number of observations 50 50 50 50 50 50 50 50 Panel B: Standardized Effects Rate of Reconquest 0.171 -0.278 -0.512 -0.554 0.363 -0.354 -0.564 -0.411 TABLE 7 - THE TIMING OF THE EFFECT OF THE RECONQUEST Notes : Variables descriptions are provided in Table A1. GDP and industrial output variables are all expressed in pesetas. The estimations include a constant term, which is omitted for space considerations. Robust standard errors are in parentheses. *, ** and *** denote significance at the 10, 5 and 1% level, respectively. Rate of Reconquest Dependent variable: Log GDP per capita in: Log industrial output per capita in: Urban population density in 800 50 (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) Panel A: Regression Results -0.018***-0.019*** 2.484*** 2.374*** 0.013*** 0.014*** -0.233 -0.528*** 0.173 0.304 -0.0003 -0.0005 -0.008*** -0.004* 0.0001 -0.0001 (0.004) (0.004) (0.375) (0.452) (0.004) (0.005) (0.139) (0.186) (0.182) (0.203) (0.0003) (0.0004) (0.002) (0.002) (0.0001) (0.0001) -0.016* 0.723 0.001 0.289 -0.429 -0.001 0.001 0.001*** (0.008) (0.642) (0.005) (0.275) (0.275) (0.001) (0.003) (0.000) Crown of Aragon 0.093** 9.995* 0.058 -8.842*** -0.587 0.000 0.104*** 0.002* (0.041) (5.374) (0.065) (2.78) (2.04) (0.006) (0.037) (0.001) Madrid 0.412*** 13.938** 0.173*** 12.891*** -4.156 0.012** -0.002 0.006*** (0.061) (5.56) (0.046) (2.877) (2.856) (0.006) (0.038) (0.002) Distance to the coast -0.027 1.11 0.071** -0.092 -0.594 0.005* -0.009 0.001 (0.032) (3.013) (0.027) (1.446) (1.385) (0.003) (0.02) (0.001) Border with Portugal -0.034 -6.043 -0.014 3.532 7.787** -0.007 0.05 0.003* (0.046) (5.642) (0.057) (2.141) (3.152) (0.005) (0.044) (0.002) Altitude (average) -0.0001 0.003 0.0002 -0.006 0.001 0.000 0.0000 0.0000 (0.0001) (0.01) (0.0001) (0.004) (0.004) (0.000) (0.0001) (0.000) Soil quality 0.319*** 27.025*** 0.109 3.147 -15.099** 0.023* -0.297*** 0.008*** (0.083) (8.587) (0.124) (4.978) (5.757) (0.012) (0.095) (0.002) Mining output in 1860 0.006* -0.211 -0.006** -0.132 -0.352* 0.000 -0.002 0.000 (0.003) (0.291) (0.003) (0.134) (0.192) (0.000) (0.002) (0.000) R 2 0.3 0.68 0.48 0.66 0.15 0.53 0.05 0.42 0.02 0.55 0.01 0.29 0.15 0.57 0.03 0.48 Number of observations 50 50 50 50 50 50 47 47 48 48 50 50 50 50 50 50 Panel B: Standardized Effects Rate of Reconquest -0.548 -0.554 0.693 0.662 0.389 0.407 -0.208 -0.470 0.128 0.225 -0.120 -0.201 -0.393 -0.192 0.134 -0.134 TABLE 9 - MECHANISMS AT WORK Dependent variable: Religiosity (Clerical population in 1797) Rate of Reconquest Urban population density in 800 Notes : Variables descriptions are provided in Table A1. GDP and industrial output variables are all expressed in pesetas. The estimations include a constant term, which is omitted for space considerations. Robust standard errors are in parentheses. *, ** and *** denote significance at the 10, 5 and 1% level, respectively. Log GPD per capita 2005 Percentage of landless workers 1797 Percentage of villages and cities under seigneurial jurisdiction in 1797 Population density in 1594 Moorish ancestry Market fragmentation (Road density in 1760) Percentage of villages and cities under Church jurisdiction in 1797 51 Literacy rate School enrollment Infant mortality Life expectancy Percentage of electors Percentage of voters Crimes Convicts Agricultural productivity Agriculture ’s share (1)(2)(3)(4) (5) (6) (7)(8) (9) (10) -0.827*** -0.006*** 4.764*** -0.367*** -0.002** -0.002** 0.065*** 0.048*** 3.864 0.031 (0.249) (0.002) (1.122) (0.093) (0.001) (0.001) (0.02) (0.012) (5.518) (0.268) -0.224 0.000 -3.768** 0.109 -0.001 0.001* -0.014 -0.041* 12.294 0.681 (0.364) (0.002) (1.634) (0.135) (0.001) (0.001) (0.031) (0.021) (26.358) (0.498) Crown of Aragon -9.23*** -0.028 10.927 -1.096 0.01 -0.023** 0.566** 0.348 63.47 6.159 (2.981) (0.024) (14.295) (1.368) (0.01) (0.009) (0.263) (0.238) (74.535) (4.494) Madrid 15.818*** -0.085*** 61.499*** -4.525*** -0.002 -0.029*** 2.154*** 1.163*** -259.729*** -36.457*** (4.251) (0.03) (12.568) (1.463) (0.01) (0.008) (0.286) (0.221) (85.2) (4.25) Distance to the coast 1.939 0.022 16.951** -1.917** 0.009 -0.002 0.378** 0.256** -59.492 -1.188 (2.295) (0.015) (7.295) (0.794) (0.006) (0.004) (0.154) (0.118) (69.618) (2.31) Border with Portugal 0.485 0.044* -29.764* 3.486** -0.003 0.009 -0.144 -0.186 -19.138 9.444* (3.188) (0.024) (17.64) (1.465) (0.009) (0.009) (0.23) (0.158) (96.896) (4.886) Altitude (average) 0.003 0.0001* 0.027 -0.006** 0.000 0.000 0.001 0.001** 0.35 0.026*** (0.007) (0.0000) (0.022) (0.002) (0.000) (0.000) (0.000) (0.000) (0.236) (0.007) Soil quality 4.599 0.055 56.551** -3.882 0.047** 0.032* 0.629 0.399 309.43* -12.351* (6.752) (0.062) (23.139) (2.595) (0.023) (0.016) (0.431) (0.373) (178.396) (6.464) Mining output in 1860 0.228 0.002 -1.595** -0.012 0.001 0.001 -0.007 0.007 -2.342 -0.144 (0.247) (0.002) (0.734) (0.09) (0.001) (0.000) (0.016) (0.013) (6.13) (0.235) R 2 0.44 0.45 0.62 0.64 0.45 0.43 0.65 0.59 0.23 0.50 Number of observations 50 50 50 50 50 50 50 50 50 50 Notes : Variables descriptions are provided in Table A1. GDP and industrial output variables are all expressed in pesetas. The estimations include a constant term, which is omitted for space considerations. Robust standard errors are in parentheses. *, ** and *** denote significance at the 10, 5 and 1% level, respectively. Rate of Reconquest Urban population density in 800 TABLE 10 - OUTCOMES INDICATORS IN THE 1860s Dependent variable: 52 Figure 1. The Spanish Reconquest (711-1492) 0,000000 - 2,826830 2,826831 - 4,047660 4,047661 - 7,074030 7,074031 - 8,762120 8,762121 - 22,52520 0 Crown of Castile Crown of Aragon 711 (initial resistance) Frontier in 800 Frontier in 900 Frontier in 1062 Frontier in 1150 Frontier in 1220 Frontier in 1238 Frontier in 1266 Frontier in 1450 Rate of Reconquest : (in 100km 2 /year) 0.0000 - 2.8268 2.8269 - 4.0477 4.0478 - 7.0740 7.0741 - 8.7621 8.7622 - 22.5252 Figure 2. Conditional relationship between current GDP per capita and rate of Reconquest Vizcaya Guipúzcoa Salamanca Álava Navarra Zamora Cantabria Toledo Pontevedra Córdoba Valladolid Huesca Palmas (Las) Tarragona Asturias Zaragoza Barcelona Segovia Santa Cruz de Tenerife Girona Málaga Burgos Ciudad Real Soria Alicante Palencia Orense Rioja (La) Lleida Granada Madrid Coruña (A) Teruel Lugo León Ávila Almería Guadalajara Cáceres Castellón de la Plana Balears (Illes) Valencia Jaén Badajoz Cádiz Cuenca Huelva Albacete Sevilla Murcia -.4 -.2 0.2 .4 e(Log GDP per capita 2005 | X ) -10 -5 0 5 10 15 e(Rate of Reconquest | X ) coef = -.01858997, (robust) se = .00351305, t = -5.29 1  (NOT FOR PUBLICATION) Unpublished appendix to “The Economic Consequences of the Spanish Reconquest: The Long-term Effects of Medieval Conquest and Colonization” Daniel Oto-Peralías and Diego Romero-Ávila December 2014 This appendix includes: Table A1. Description of variables. Table A2. Descriptive statistics. Table A3. Replication of Table 1 using Conley standard errors. Table A4. Replication of Table 2 using Conley standard errors. Table A5. Replication of Table 3 using Conley standard errors. Table A6. Including geographic coordinates and a cubic polynomial in longitude and latitude. Table A7. Replication of Table 1 using the Post-1212 conquest indicator. Table A8. Replication of Table 2 using the Post-1212 conquest indicator. Table A9. Replication of Table 1 using an alternative indicator of rate of Reconquest. Table A10. Replication of Table 2 using an alternative indicator of rate of Reconquest. Table A11. Replication of Table 3 using an alternative indicator of rate of Reconquest. Table A12. Replication of Table 6 using the complete set of controls. Table A13. Correlations between indicators of pre-Reconquest development and suitability for agriculture. Table A14. Replication of Table 6 using the Post-1212 conquest indicator. Table A15. Replication of Table 6 using the Post-1212 conquest indicator and the complete set of controls. Table A16. Replication of Table 7 using the Post-1212 conquest indicator. Table A17. The effect of rate of Reconquest on the average size of municipalities. Figure A1. Current income distribution in the Spanish provinces. 2   Variable Description Source Main dependent variables Log GDP per capita Lof of GDP per capita in 1860, 1930, 1971 and 2005. Rosés et al (2010) for 1860 and 1930; Carreras et al. (2005) for 1971; Spanish Regional Accounts. Base 2000 (INE) for 2005. Log industrial output per capita Log of industrial output per capita in 1860, 1930, 1970 and 2005. Rosés et al. (2010) for 1860; Carreras (2005) for 1930 and 1970; Spanish Regional Accounts. Base 2000 (INE) for 2005. Reconquest indicators Rate of Reconquest This variable is created (using ArcGIS) as follows. We overlap the Reconquest map from Mestre-Campi and Sabaté (1998) with a geo-referenced map of the Spanish provinces. We also overlap a map of the initial resistance area (http://explorethemed.com/Reconquista.asp) with the map of Spanish provinces. We then draw the lines of each stage of the Reconquest as well as a line separating Castile and Aragon. We calculate the surface area corresponding to each stage of the Reconquest for Castile and Aragon. Next, we divide the reconquered area in each stage by the duration in years that each stage lasted for, thus obtaining a measure of the rate of Reconquest. Since the area of a province can partially cover more than one stage of the Reconquest, we calculate its area within each of the respective stages. We then compute the weighted average o f the rate of Reconquest of each province, where the weights are given by the percentage of the province area conquered in each stage. The variable is expressed in 100 km 2 /year. Authors’ elaboration using information from Mestre-Campi and Sabaté (1998). Post-1212 conquest Dummy variable indicating whether the province was reconquered after the collapse of the Almohad Empire in 1212 in the battle of Las Navas de Tolosa. Authors’ elaboration using information from Mestre-Campi and Sabaté (1998) and Guichard (2002), among others. Rate of Reconquest (alternative) This indicator is calculated as follows: (i) Provinces are classified according to the century in which they were reconquered. In this way, the Reconquest is divided in stages of the same duration. The five Cantabrian provinces not occupied by the Muslim are considered separately, with a value equal to 0. (ii) For each century, we compute the total land area reconquered in that period, differentiating between the areas conquered by Castile and Aragon. (iii) Then, the rate of Reconquest in a given province is the total land area that was reconquered in the century in which that province was reconquered, expressed in 100 km 2 /year. Authors’ elaboration using information from Mestre-Campi and Sabaté (1998). Controls Agricultural land in 1900 (%) Percentage of agricultural area over provincial surface area in 1900. Barciela et al. (2005). Arable land in 1962 (%) Percentage of arable land over total surface area. 1962 agricultural census (INE) (www.ine.es). Average altitude Average altitude of the province (simple average of the municipalities of the province) Geographic Nomenclature of Municipalities and Local Population (Instituto Geográfico Nacional -IGN2012). Average urban population density at conquest in the Christian kingdom Average density of urban population (inhabitants in cities greater than or equal to 5000 inhabitants over provincial surface area in km 2 ) in Castile or Aragon just before the conquest of the province. Authors’ elaboration using information from Bairoch (1988). Border with Portugal Dummy variable indicating whether the province is in the border with Portugal. Authors’ elaboration. Centuries under Muslim domination Number of centuries that the province was under Muslim domination. It is calculated as the closest integer to the difference between the year of the Reconquest of the capital city of the province and the date of the Muslim invasion (711). Authors’ elaboration using information from Mestre-Campi and Sabaté (1998) and Guichard (2002), among others. Coal dummy in 1860 Dummy variable indicating whether the province had some coal mine in 1860. 1860-1861 Statistical Yearbook o f Spain (Junta General de Estadística -JGE1863). Coal output in 1860 Logarithm of the value created by coal mining in 1860. 1860-1861 Statistical Yearbook o f Spain (JGE 1863a). TABLE A1 - DESCRIPTION OF VARIABLES  3  Variable Description Source Controls (continued) Coast dummy Dummy variable indicating whether the province has coast. Authors’ elaboration. Coast length/ surface area Length of coast over surface area. Physical variables. Territory (INE) (www.ine.es). Crown of Aragon Dummy variable capturing whether the province belonged to the Crown o f Aragon. Authors’ elaboration. Distance from London and from Paris Linear distance between the centroid of the province and London or Paris (in 100 km), using ArcGIS. Authors’ elaboration. Distance from Madrid Linear distance between the centroid of the province and Madrid (in 100 km), using ArcGIS. Authors’ elaboration. Distance to the coast Linear distance between the centroid of the province and the nearest point of the coast (in 100 km), using ArcGIS. For the three provinces that are islands, this variable takes the value of 0. Authors’ elaboration. Humidity, Temperature and Rainfall Annual average temperature, rainfall and relative humidity. Standard Climate Values (Agencia Estatal de Meteorología 2012). Island Dummy variable indicating whether the province is an island. Authors’ elaboration. Latitude Latitude of the centroid of the province, using ArcGIS. Authors’ elaboration. Land suitability for cotton Provincial average of the crop suitability index for low input level rain-fed cotton. Authors’ elaboration using data from FAO/IIASA (2010). Land suitability for sugar Provincial average of the crop suitability index for low input level rain-fed sugarcane. Authors’ elaboration using data from FAO/IIASA (2010). Land suitability for tobacco Provincial average of the crop suitability index for low input level rain-fed tobacco. Authors’ elaboration using data from FAO/IIASA (2010). Madrid Dummy variable indicating the capital city of Spain. Authors’ elaboration. Mediterranean Sea, Atlantic Ocean, Cantabrian Sea Dummy variables indicating whether the province has access to the Mediterranean Sea, the Atlantic Ocean or the Cantabrian Sea. Authors’ elaboration. Mining output in 1860 Logarithm of the value created by the mining industry in 1860. 1860-1861 Statistical Yearbook o f Spain (JGE 1863a). Roman roads density Length of Roman roads (in meters) over provincial surface area (in km 2 ). Authors’ elaboration using ArcGIS and data from García de Cortázar (2007). Ruggedness Coefficient of variation of the altitude of the municipalities of the province. Geographic Nomenclature of Municipalities and Local Population (Instituto Geográfico Nacional -IGN2012). Soil quality Average of seven key soil dimensions important for crop production: nutrient availability, nutrient retention capacity, rooting conditions, oxygen availability to roots, excess salts, toxicities, and workability. For each component, we calculate the provincial average value. Authors’ elaboration using data from Fischer et al. (2008). Urban population density in 800 Density of urban population (inhabitants in cities greater than or equal to 5000 inhabitants over provincial surface area in km 2 ) in 800. Bairoch (1988). Urban population density at conquest Density of urban population (inhabitants in cities greater than or equal to 5000 inhabitants over provincial surface area in km 2 ) in the latest available date previous to the conquest of the province by the Christians. Authors’ elaboration using information from Bairoch (1988). Wooded steppe (% area) Percentage of province area that was subject to wooded steppe 10,000 years ago. Authors’ elaboration using ArcGIS and information from Olsson and Paik (2013). Years since transition to agriculture This variable is constructed for each province using the following equation: Y(S 0 )=Σλ i Y(S i ), where Y(S 0 ) is the predicted date of adoption of agriculture for the centroid of each respective province (denoted by S 0 ). Σmeans a sum from site 1 to N, where N is the number of measured sample points surrounding S 0 . We restrict the measured sample points to those located in the Iberian Peninsula that make a total of 13 Neolithic sites. Y(S i ) is the observed value o f the predicted date of early adoption of agriculture in Neolithic site S i .λ i are weights calculated as λ i =(D/d i )/Σ(D/d i ), where Σλ i =1andd i is the distance between S 0 and each Neolithic site S i .D=Σd i is the total sum of the 13 d i for the centroid of each respective province (S 0 ). Note that (D/d i ) implies that we assign greater weights to those sites located closer to the centroid of each province. Authors’ elaboration using ArcGIS and data from Pinhasi, Fort and Ammerman (2005). TABLE A1 - DESCRIPTION OF VARIABLES (Continued)  4  Variable Description Source Variables of pre-Reconquest development Ancient settlements over surface area Number of ancient (pre-medieval) settlements over provincial surface area (in 1,000 km 2 ). Authors’ elaboration using ArcGIS and data from Pleiades (2014). City population in 800 Inhabitants (in thousands) in cities greater than or equal to 5000 inhabitants in 800. Bairoch (1988). Coinage of imperial Roman coins over surface area Number of points of coinage of imperial Roman coins over provincial surface area (in 1,000 km 2 ). Authors’ elaboration using data from García de Cortázar (2007). Number of bishoprics circa 600 over surface area Number of bishoprics circa 600 over provincial surface area (in 1,000 km 2 ). Authors’ elaboration using data from Digital Atlas of Roman and Medieval Civilizations. Roman roads density: Main roads Length of the main Roman roads (in meters) over provincial surface area (in km 2 ). Authors’ elaboration using ArcGIS and data from García de Cortázar (2007). Roman villas over surface area Number of Roman villas over provincial surface area (in 1,000 km 2 ). Authors’ elaboration using ArcGIS and data from Pleiades (2014). UK and US industrial output Total UK industrial output Total industrial output of the United Kingdom in 1860, 1930, 1971 and 2005. Base year is 1913. Mitchell (2007a) and IMF (2013). Total US industrial output Total industrial output of the United States in 1860, 1930, 1971 and 2005. Base year is 1899. Mitchell (2007b) and IMF (2013). Variables used as mechanisms Religiosity (Clerical population in 1797) Percentage of population that is member of the clergy (both secular and regular) in 1797. We impute data from historical regions to current provinces by estimating (with ArcGIS) the percentage of area in each province that corresponds to each historical region. Authors’ elaboration using data from Morales (1998) and 1797 population census (INE, 1992). Moorish ancestry Proportion of Moorish ancestry in the current population of each province. Adams et al. (2008). Percentage of landless workers in 1797 Percentage of landless workers over the agricultural active population in 1797. We impute data from historical regions to current provinces by estimating (with ArcGIS) the percentage of area in each province that corresponds to each historical region. Authors’ elaboration using data from Morales (1998) and 1797 population census (INE, 1992). Percentage of villages and cities under Church jurisdiction in 1797 Variable measuring the percentage of villages and cities (“villas” and “ciudades”) under ecclesiastical jurisdiction in 1797. We impute data from historical regions to current provinces by estimating (with ArcGIS) the percentage of area in each province that corresponds to each historical region. Authors’ elaboration using data from Morales (1998) and 1797 population census (INE, 1992). Percentage of villages and cities under seigneurial jurisdiction in 1797 Variable measuring the percentage of villages and cities (“villas” and “ciudades”) under either noble or military order jurisdiction in 1797. We impute data from historical regions to current provinces by estimating (with ArcGIS) the percentage of area in each province that corresponds to each historical region. Authors’ elaboration using data from Morales (1998) and 1797 population census (INE, 1992). Population density in 1594 Number of inhabitants per square kilometer in 1594. We impute data from historical regions to current provinces by estimating (with ArcGIS) the percentage of area in each province that corresponds to each historical region. Authors’ elaboration using data from 1858 Statistical Yearbook of Spain (JGE 1860) and INE (1982). Market fragmentation (Road density in 1760) Kilometers of roads in 1760 (“caminos de ruedas”) over provincial surface area (in km 2 ). Authors’ elaboration using ArcGIS and data from IGN (2008). TABLE A1 - DESCRIPTION OF VARIABLES (Continued)  5  Variable Description Source Outcomes variables in the 1860s Agricultural productivity Agricultural output in 1860 divided by the number of male agricultural workers. Authors’ elaboration from Rosés et al. (2010), Erdozáin and Mikelarena (1999), and the 1860 population census (JGE 1863b). Agriculture’s share Agricultural output in 1860 divided by total provincial output. Rosés et al. (2010). Convicts and Crimes Total crimes committed over total population in 1860 (in thousands). Total convicts over total population in 1860 (in thousands). 1860-1861 Statistical Yearbook o f Spain (JGE 1863a); 1860 population census (JGE 1863b). Infant mortality Infant mortality rates. Probability of dying (per thousand) of individuals under one year in 1860. Regional and provincial mortality tables. Spain 1860 (ProyectoNisal, 2014). Life expectancy Life expectancy at birth in 1860. Regional and provincial mortality tables. Spain 1860 (ProyectoNisal, 2014). Literacy rate Total literacy rates for the adult population in 1860. Núñez (1992). Percentage of electors and voters Electors (or voters) in the parliamentary election of 1865 as a percentage of the male population aged 25 or older. Authors’ elaboration from the 1862-1865 Statistical Yearbook o f Spain (JGE 1865) and the 1860 population census (JGE 1863b). School enrollment Total children enrolled over the population under 15 years. Authors’ elaboration from the 1860 population census (JGE 1863b). Variables at the municipal level Altitude Altitude corresponding to the municipality centroid. Geographic Nomenclature of Municipalities and Local Population (IGN 2012). Annual average temperature Annual average temperature corresponding to the municipality centroid (in centigrade degrees multiplied by 10). Authors’ elaboration using ArcGIS and data from WorldClim (Hijmans et al., 2005). Annual rainfall Annual precipitation corresponding to the municipality centroid (in millimeters). Authors’ elaboration using ArcGIS and data from WorldClim (Hijmans et al., 2005). Average number of vehicles per household Number of vehicles (cars and vans) for personal transport owned by households, divided by the number of households. The year of measurement is 2001. INE. Censos de Población y Viviendas 2001 (www.ine.es). Average socioeconomic condition Average of class marks of socioeconomic conditions of individuals (multiplied by 100). Socioeconomic condition is obtained by combining information from the variables occupation, activity and professional situation. To illustrate the construction of this variable, a (maximum) class mark equal to 3 is given to nonagricultural entrepreneurs with employees, and a (minimun) class mark of 0 to those unemployed who have not worked previously. The year of measurement is 2001. INE. Censos de Población y Viviendas 2001 (www.ine.es). Distance to Madrid Linear distance between the centroid of the municipality and Madrid (in km), using ArcGIS. Authors’ elaboration. Distance to the coast Linear distance between the centroid of the municipality and the nearest point o f the coast (in km), using ArcGIS. Authors’ elaboration. Distance to the nearest capital Linear distance between the centroid of the municipality and the nearest provincial capital (in km), using ArcGIS. Authors’ elaboration. Excess salts This variable assesses the following soil characteristics: “Soil salinity, soil sodicity and soil phases influencing salt conditions”. We calculate the average value of the municipality. Authors’ elaboration using ArcGIS and data from Fischer et al. (2008). Labor force activity rate Labor force activity rate of the population between 20 and 59 years old. The year of measurement is 2001. INE. Censos de Población y Viviendas 2001 (www.ine.es). TABLE A1 - DESCRIPTION OF VARIABLES (Continued)  12   Mediterranean Sea Atlantic Ocean Cantabrian Sea Island Coast Dummy Coast length/ surface area Distance to the coast Border with Portugal (1) (2) (3) (4) (5) (6) (7) (8) -0.019*** -0.018*** -0.019*** -0.019*** -0.018*** -0.018*** -0.018*** -0.016*** (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.003) (0.004) Additional control 0.079 -0.026 -0.02 0.08 0.038 0.329 -0.047* -0.164*** (0.054) (0.061) (0.082) (0.065) (0.045) (0.303) (0.028) (0.053) R 2 0.33 0.30 0.30 0.31 0.31 0.31 0.35 0.38 Number of observations 50 50 50 50 50 50 50 50 Distance from Madrid Distance from London Distance from Paris Agric. land 1900 (%) Arable land 1962 (%) Mining output in 1860 Coal dummy in 1860 Coal output in 1860 (9) (10) (11) (12) (13) (14) (15) (16) -0.018*** -0.016*** -0.015*** -0.02*** -0.018*** -0.019*** -0.018*** -0.018*** (0.004) (0.004) (0.004) (0.005) (0.004) (0.004) (0.004) (0.004) Additional control 0.002 -0.007 -0.01 0.156 -0.069 0.007** 0.061 0.003 (0.004) (0.005) (0.007) (0.187) (0.152) (0.003) (0.054) (0.005) R 2 0.30 0.32 0.33 0.31 0.30 0.35 0.31 0.3 Number of observations 50 50 50 48 50 50 50 50 Rate of Reconquest Notes: Variables descriptions are provided in Table A1. The estimations include a constant term, which is omitted for space considerations. Conley standard errors are in parentheses. *, ** and *** denote significance at the 10, 5 and 1% level, respectively. TABLE A4. REPLICATION OF TABLE 2 USING CONLEY STANDARD ERRORS Dependent variable is log GDP per capita in 2005 Geographic controls related to transportation costs Rate of Reconquest Geographic controls related to transportation costs (continued) Natural resources endowments 13  Baseline specification Leverage Standard. residuals/ Student. residuals Cook’s distance/ Dfits Welsch distance DF-Beta Initial resistance provinces remove d (1) (2) (3) (4) (5) (6) (7) -0.019*** -0.017*** -0.016*** -0.019*** -0.017*** -0.02*** -0.015*** (0.003) (0.004) (0.002) (0.004) (0.004) (0.003) (0.004) -0.016** -0.047 -0.015*** 0.006 -0.047 -0.061** -0.017** (0.007) (0.032) (0.003) (0.028) (0.032) (0.027) (0.006) Crown of Aragon 0.093** 0.094** 0.12*** 0.087** 0.094** 0.105*** 0.127*** (0.04) (0.04) (0.03) (0.04) (0.04) (0.036) (0.043) Madrid 0.412*** n.a. 0.409*** 0.435*** 0.397*** 0.389*** 0.417*** (0.056) n.a. (0.048) (0.058) (0.057) (0.047) (0.052) Distance to the coast -0.027 -0.022 -0.04 -0.051* -0.022 -0.012 -0.023 (0.029) (0.027) (0.025) (0.027) (0.027) (0.023) (0.025) Border with Portugal -0.034 -0.043 -0.041 -0.019 -0.043 -0.062 -0.052 (0.041) (0.041) (0.033) (0.043) (0.041) (0.038) (0.039) Altitude (average) -0.0001 -0.0001 0.0000 0.0000 -0.0001 -0.0001 0.0000 (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) Soil quality 0.319*** 0.32*** 0.307*** 0.32*** 0.32*** 0.29*** 0.223*** (0.079) (0.08) (0.069) (0.08) (0.08) (0.07) (0.076) Mining output in 1860 0.006** 0.005** 0.006*** 0.006** 0.005** 0.004* 0.004 (0.003) (0.003) (0.002) (0.003) (0.003) (0.002) (0.003) R 2 0.68 0.65 0.8 0.68 0.67 0.75 0.67 Number of observations 50 48 46 48 49 44 45 TABLE A5. REPLICATION OF TABLE 3 USING CONLEY STANDARD ERRORS Dependent variable is log GDP per capita in 2005 Rate of Reconquest Urban population density in 800 Notes: Variables descriptions are provided in Table A1. The estimations include a constant term, which is omitted for space considerations. Conley standard errors are in parentheses. *, ** and *** denote significance at the 10, 5 and 1% level, respectively. Outliers are the following: Column 2, Madrid and Córdoba; Column 3, Alicante, Granada, Jaén and Álava; Column 4, Granada and Córdoba. Column 5, Córdoba. Column 6, Córdoba, Huelva, Jaén, Murcia, Sevilla and Álava. Initial resistance provinces in column 7 are Asturias, Cantabria, Guipúzcoa, Vizcaya and Álava.  14  Including geographic coordinates (latitude & longitude) Including a cubic polynomial in longitude and latitude (1) (2) -0.01*** -0.01** (0.003) (0.003) -0.02** -0.01*** (0.007) (0.005) Crown of Aragon 0.06 -0.036 (0.053) (0.051) Madrid 0.52*** 0.45*** (0.048) (0.028) Distance to the coast -0.08*** -0.09*** (0.022) (0.025) Border with Portugal -0.04 -0.29*** (0.041) (0.056) Altitude (average) 0.00 0.00 (0.000) (0.000) Soil quality 0.60*** 0.29** (0.092) (0.114) Mining output in 1860 0.00 0.00 (0.003) (0.002) R 2 0.81 0.93 Number of observations 50 50 TABLE A6. INCLUDING GEOGRAPHIC COORDINATES AND A CUBIC POLYNOMIAL IN LONGITUDE AND LATITUDE Dependent variable is log GDP per capita in 2005 Rate of Reconquest Urban population density in 800 Notes: Variables descriptions are provided in Table A1. The estimations include a constant term, which is omitted for space considerations. Robust standard errors are in parentheses. *, ** and *** denote significance at the 10, 5 and 1% level, respectively.  15   Wooded steppe (% area) Years since transition to agriculture Roman roads density Urban population density in 800 Urban population density at conquest Av. urban pop.dens. at conquest in the Christian kingdom Centuries under Muslim domination Crown of Aragon Madrid (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) -0.182*** -0.196*** -0.173*** -0.181*** -0.156*** -0.167*** -0.273*** -0.139* -0.182*** -0.172*** (0.051) (0.056) (0.053) (0.051) (0.051) (0.057) (0.064) (0.079) (0.043) (0.051) Additional control -0.047 0.001 -0.001 -0.026*** -0.007 0.126* -0.012 0.195*** 0.293*** (0.064) (0.001) (0.002) (0.008) (0.014) (0.067) (0.016) (0.04) (0.034) R 2 0.20 0.21 0.20 0.2 0.24 0.2 0.23 0.20 0.36 0.24 Number of observations 50 50 50 50 50 50 50 50 50 50 Latitude Temperature Rainfall Humidity Soil quality Land suitability for sugar Land suitability for cotton Land suitability for tobacco Average altitude Ruggedness (11) (12) (13) (14) (15) (16) (17) (18) (19) (20) -0.161* -0.271*** -0.182*** -0.137** -0.254*** -0.189*** -0.142** -0.158*** -0.221*** -0.213*** (0.081) (0.086) (0.055) (0.056) (0.058) (0.059) (0.064) (0.051) (0.053) (0.05) Additional control 0.004 0.02 0.000 0.011 0.405*** 0.001 0.000 0.000 -0.0002** 0.166** (0.011) (0.013) (0.000) (0.007) (0.089) (0.002) (0.000) (0.000) (0.000) (0.069) R 2 0.20 0.22 0.20 0.27 0.37 0.20 0.21 0.23 0.27 0.27 Number of observations 50 50 50 50 50 50 50 50 50 50 Climatic, geographic and topographic factors Post-1212 conquest Notes: Variables descriptions are provided in Table A1. The estimations include a constant term, which is omitted for space considerations. Robust standard errors are in parentheses. *, ** and *** denote significance at the 10, 5 and 1% level, respectively. Post-1212 conquest TABLE A7. REPLICATION OF TABLE 1 USING THE POST-1212 CONQUEST INDICATOR Dependent variable is log GDP per capita in 2005 Basic relationship Neolithic controls Historical controls 16        Mediterranean Sea Atlantic Ocean Cantabrian Sea Island Coast Dummy Coast length/ surface area Distance to the coast Border with Portugal (1) (2) (3) (4) (5) (6) (7) (8) -0.247*** -0.177*** -0.175*** -0.215*** -0.226*** -0.214*** -0.232*** -0.173*** (0.043) (0.054) (0.053) (0.051) (0.048) (0.05) (0.045) (0.047) Additional control 0.185*** -0.028 0.04 0.202*** 0.125** 0.931*** -0.089*** -0.214*** (0.044) (0.059) (0.093) (0.072) (0.051) (0.321) (0.029) (0.045) R 2 0.32 0.20 0.20 0.25 0.28 0.27 0.36 0.34 Number of observations 50 50 50 50 50 50 50 50 Distance from Madrid Distance from London Distance from Paris Agric. land 1900 (%) Arable land 1962 (%) Mining output in 1860 Coal dummy in 1860 Coal output in 1860 (9) (10) (11) (12) (13) (14) (15) (16) -0.21*** -0.146* -0.126* -0.2*** -0.164*** -0.178*** -0.178*** -0.181*** (0.054) (0.074) (0.071) (0.056) (0.049) (0.052) (0.053) (0.053) Additional control 0.012** -0.007 -0.011 0.054 -0.207 0.005 0.03 0.001 (0.006) (0.01) (0.011) (0.163) (0.15) (0.004) (0.057) (0.005) R 2 0.23 0.20 0.23 0.21 0.22 0.22 0.20 0.2 Number of observations 50 50 50 48 50 50 50 50 Post-1212 conquest Notes: Variables descriptions are provided in Table A1. The estimations include a constant term, which is omitted for space considerations. Robust standard errors are in parentheses. *, ** and *** denote significance at the 10, 5 and 1% level, respectively. TABLE A8. REPLICATION OF TABLE 2 USING THE POST-1212 CONQUEST INDICATOR Dependent variable is log GDP per capita in 2005 Geographic controls related to transportation costs Post-1212 conquest Geographic controls related to transportation costs (continued) Natural resources endowments 17   Wooded steppe (% area) Years since transition to agriculture Roman roads density Urban population density in 800 Urban population density at conquest Av. urban pop.dens. at conquest in the Christian kingdom Centuries under Muslim domination Crown of Aragon Madrid (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) -0.025*** -0.025*** -0.024*** -0.026*** -0.023*** -0.023*** -0.024*** -0.022*** -0.022*** -0.025*** (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) Additional control -0.035 0.0000 0.001 -0.015* -0.017 -0.029 -0.014 0.122** 0.352*** (0.051) (0.001) (0.002) (0.008) (0.013) (0.052) (0.01) (0.049) (0.022) R 2 0.36 0.37 0.36 0.37 0.38 0.39 0.37 0.39 0.42 0.43 Number of observations 50 50 50 50 50 50 50 50 50 50 Latitude Temperature Rainfall Humidity Soil quality Land suitability for sugar Land suitability for cotton Land suitability for tobacco Average altitude Ruggedness (11) (12) (13) (14) (15) (16) (17) (18) (19) (20) -0.022*** -0.024*** -0.025*** -0.022*** -0.027*** -0.025*** -0.028*** -0.026*** -0.025*** -0.024*** (0.004) (0.004) (0.004) (0.005) (0.003) (0.004) (0.006) (0.005) (0.004) (0.004) Additional control 0.011* -0.003 0.000 0.004 0.292*** -0.001 0.000 0.000 0.000 0.041 (0.005) (0.006) (0.000) (0.007) (0.08) (0.002) (0.000) (0.000) (0.000) (0.059) R 2 0.39 0.37 0.36 0.37 0.47 0.36 0.37 0.36 0.37 0.37 Number of observations 50 50 50 50 50 50 50 50 50 50 Climatic, geographic and topographic factors Rate of Reconquest (alternative) Notes: Variables descriptions are provided in Table A1. The estimations include a constant term, which is omitted for space considerations. Robust standard errors are in parentheses. *, ** and *** denote significance at the 10, 5 and 1% level, respectively. TABLE A9. REPLICATION OF TABLE 1 USING AN ALTERNATIVE INDICATOR OF RATE OF RECONQUEST Dependent variable is log GDP per capita in 2005 Basic relationship Neolithic controls Historical controls Rate of Reconquest (alternative) 18     Mediterranean Sea Atlantic Ocean Cantabrian Sea Island Coast Dummy Coast length/ surface area Distance to the coast Border with Portugal (1) (2) (3) (4) (5) (6) (7) (8) -0.025*** -0.024*** -0.026*** -0.025*** -0.025*** -0.025*** -0.024*** -0.022*** (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) Additional control 0.013 -0.039 -0.037 -0.007 -0.021 -0.031 -0.021 -0.141*** (0.06) (0.047) (0.086) (0.063) (0.05) (0.313) (0.027) (0.045) R 2 0.36 0.37 0.37 0.36 0.37 0.36 0.37 0.42 Number of observations 50 50 50 50 50 50 50 50 Distance from Madrid Distance from London Distance from Paris Agric. land 1900 (%) Arable land 1962 (%) Mining output in 1860 Coal dummy in 1860 Coal output in 1860 (9) (10) (11) (12) (13) (14) (15) (16) -0.025*** -0.022*** -0.022*** -0.027*** -0.025*** -0.025*** -0.025*** -0.025*** (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) Additional control -0.004 -0.011** -0.013** 0.185 -0.007 0.007** 0.069 0.004 (0.004) (0.005) (0.006) (0.165) (0.145) (0.003) (0.05) (0.005) R 2 0.37 0.40 0.42 0.38 0.36 0.4 0.38 0.37 Number of observations 50 50 50 48 50 50 50 50 Rate of Reconquest (alternative) Notes: Variables descriptions are provided in Table A1. The estimations include a constant term, which is omitted for space considerations. Robust standard errors are in parentheses. *, ** and *** denote significance at the 10, 5 and 1% level, respectively. TABLE A10. REPLICATION OF TABLE 2 USING AN ALTERNATIVE INDICATOR OF RATE OF RECONQUEST Dependent variable is log GDP per capita in 2005 Geographic controls related to transportation costs Rate of Reconquest (alternative) Geographic controls related to transportation costs (continued) Natural resources endowments 19  Baseline specification Leverage Standard. residuals/ Student. residuals Cook’s distance/ Dfits Welsch distance DF-Beta Initial resistance provinces removed (1) (2) (3) (4) (5) (6) (7) -0.02*** -0.019*** -0.02*** -0.023*** -0.021*** -0.017*** -0.015** (0.005) (0.005) (0.004) (0.005) (0.005) (0.004) (0.006) -0.021** -0.074** -0.015*** -0.008 -0.063 -0.026*** -0.021** (0.011) (0.036) (0.005) (0.027) (0.038) (0.009) (0.01) Crown of Aragon 0.103** 0.101** 0.13*** 0.09* 0.097** 0.112** 0.145*** (0.045) (0.046) (0.039) (0.045) (0.045) (0.043) (0.048) Madrid 0.35*** n.a. 0.379*** 0.307*** 0.285*** 0.281*** 0.376*** (0.063) n.a. (0.054) (0.059) (0.061) (0.06) (0.056) Distance to the coast -0.001 0.006 -0.023 0.008 0.03 0.033 -0.007 (0.037) (0.028) (0.028) (0.029) (0.031) (0.035) (0.03) Border with Portugal -0.055 -0.064 -0.042 -0.052 -0.073 -0.095** -0.069 (0.045) (0.044) (0.041) (0.051) (0.049) (0.046) (0.043) Altitude (average) 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) Soil quality 0.242*** 0.259*** 0.242*** 0.268*** 0.272*** 0.223*** 0.15* (0.081) (0.082) (0.077) (0.082) (0.082) (0.075) (0.074) Mining output in 1860 0.006* 0.006* 0.006* 0.007** 0.007* 0.007** 0.004 (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) R 2 0.65 0.64 0.73 0.68 0.67 0.68 0.65 Number of observations 50 48 47 47 48 47 45 TABLE A11. REPLICATION OF TABLE 3 USING AN ALTERNATIVE INDICATOR OF RATE OF RECONQUEST Dependent variable is log GDP per capita in 2005 Rate of Reconquest (alternative) Urban population density in 800 Notes: Variables descriptions are provided in Table A1. The estimations include a constant term, which is omitted for space considerations. Robust standard errors are in parentheses. *, ** and *** denote significance at the 10, 5 and 1% level, respectively. Outliers are the following: Column 2, Madrid and Córdoba; Column 3, Alicante, Granada, and Álava; Column 4, Toledo, Granada, and Córdoba. Column 5, Toledo and Córdoba. Column 6, Toledo, Jaén, and Álava. Initial resistance provinces in column 7 are Asturias, Cantabria, Guipúzcoa, Vizcaya and Álava.  20   Dependent variable: City population in 800 Density of urban population in 800 Years since transition to agriculture Ancient settlements over surface area Roman roads density Roman roads density: Main roads Coinage of imperial Roman coins over surface area Roman villas over surface area Number of bishoprics circa 600 over surface area (1) (2) (3) (4) (5) (6) (7) (8) (9) 1.661 0.123 -0.607 0.026 0.48 0.356* 0.004 0.009 0.003 (1.071) (0.078) (1.18) (0.041) (0.376) (0.176) (0.002) (0.014) (0.003) - - -0.252 0.087** -0.171 -0.189 (0.000) 0.022 0.005 - - (2.142) (0.042) (0.47) (0.345) (0.004) (0.017) (0.007) Crown of Aragon 0.423 -0.045 5.721 0.247 8.076 9.929*** 0.031 0.068 0.086 (3.575) (0.242) (13.284) (0.431) (7.052) (2.793) (0.037) (0.1) (0.054) Madrid -21.26* -1.42 5.191 -0.398 5.434 -0.699 -0.046 -0.143 0.041 (12.077) (0.872) (11.566) (0.423) (6.391) (1.615) (0.038) (0.135) (0.035) Distance to the coast 7.89 0.504 -10.381* -0.247 -0.333 3.134*** -0.003 0.034 -0.01 (4.992) (0.361) (6.071) (0.215) (3.061) (1.095) (0.016) (0.062) (0.023) Border with Portugal -14.944 -1.238 -31.413* -0.013 11.059* 0.971 -0.037 -0.145 -0.041 (12.649) (0.916) (17.121) (0.374) (5.825) (3.025) (0.025) (0.152) (0.04) Altitude (average) -0.019 -0.001 0.047** 0.0000 0.006 -0.007 0.0000 0.0000 0.0000 (0.014) (0.001) (0.018) (0.001) (0.01) (0.004) (0.000) (0.000) (0.000) Soil quality -6.535 -0.558 -26.485 0.663 -0.177 4.543 0.055 -0.044 -0.07 (8.966) (0.657) (19.622) (0.935) (11.745) (3.054) (0.051) (0.179) (0.066) Mining output in 1860 0.295 0.014 -0.067 0.032 0.424 0.252** 0.0000 0.0000 0.001 (0.324) (0.023) (0.736) (0.033) (0.362) (0.092) (0.002) (0.007) (0.002) R 2 0.22 0.22 0.29 0.21 0.15 0.48 0.14 0.12 0.15 Number of observations 50 50 50 50 50 50 50 50 50 TABLE A12. REPLICATION OF TABLE 6 USING THE COMPLETE SET OF CONTROLS Rate of Reconquest Notes: Variables descriptions are provided in Table A1. The estimations include a constant term, which is omitted for space considerations. Robust standard errors are in parentheses. *, ** and *** denote significance at the 10, 5 and 1% level, respectively. Urban population density in 800 21  Agricultural land 1900 (%) Arable land 1962 (%) City population in 800 0.2642* 0.2749* 0.0696 0.0533 Density of urban population in 800 0.2817* 0.2707* 0.0524 0.0573 Years since transition to agriculture -0.0129 -0.1147 0.9308 0.4275 Ancient settlements over surface area 0.1488 0.0628 0.3127 0.6646 Roman roads density: Main roads 0.2941** 0.3915*** 0.0425 0.0049 Roman roads density 0.2356 + 0.3676*** 0.107 0.0086 Coinage of imperial Roman coins over surface area 0.2478* 0.2091 0.0895 0.145 Roman villas over surface area 0.3869*** 0.3010** 0.0066 0.0337 Number of bishoprics circa 600 over surface area 0.1589 0.1763 0.2808 0.2206 TABLE A13. CORRELATIONS BETWEEN INDICATORS OF PRE-RECONQUEST DEVELOPMENT AND SUITABILITY FOR AGRICULTURE Notes: Variables descriptions are provided in Table A1. For each entry we provide the correlation coefficient (above) and the p-value (below). + , *, ** and *** denote significance at the 11, 10, 5 and 1% level, respectively. 