The Price of Decentralization: Linguistic Polarization and the Provision of Schooling*

*** Preliminary version – please do not cite or circulate without the authors’ permission ***

Francesco Cinnirella† and Ruth Maria Schueler§

Abstract In this paper we argue that the decentralization of education policies in Prussia resulted in under- provision of public education in areas characterized by conflicting and divergent interests. Using rich county-level data on public schooling from the education census of 1886, we show that linguistic polarization in East Prussia had a negative effect on local school spending. We obtain this result while holding the municipal tax base, state expenditures, and the agricultural and industrial structure constant. Instrumental variable estimates using distance to the eastern border and the geography of Prussian annexations suggest that the negative relationship between linguistic polarization and public expenditure on education can be interpreted as causal. Our findings suggest that linguistic polarization has a negative effect on local school spending, which results in fewer teachers and school buildings as well as lower teacher wages.

Keywords: human capital, polarization, public goods, decentralization, Prussia. JEL classification: N130, N330, H410, I220

July 31, 2015

* We are grateful to Sascha O. Becker, Pawel Bukowski, Luigi Pascali, Rita Peto, Ralf Meisenzahl, Stelios Michalopoulos, Alfred Reckendrees, Justin Tumlinson, Nikolaus Wolf, Ludger Woessmann, and the participants of the Economic History Talk in Mannheim, at the European Historical Economics Society Summer School in Berlin, the First German Economic History Congress in Muenster, the Conference of the Association for Religion, Economics and Culture in Boston, and at two internal seminars at the Ifo Institute for their comments and suggestions. † Ifo Institute for Economic Research at the University of Munich, Poschingerstr. 5, 81679 Munich, Germany; [email protected]. § Ifo Institute for Economic Research at the University of Munich, Poschingerstr. 5, 81679 Munich, Germany; [email protected]. 0

1. Introduction

Nineteenth-century Prussia is well-known for its advanced educational system. For example, by 1816, the average enrollment rate in primary school was already about 65 percent. In 1871, the share of persons older than 10 years old able to read and write was about 70 percent. Protestantism is believed to be a crucial factor in this country’s high level of human capital (Becker and Woessmann 2009), a belief bolstered by the high levels of literacy in economically poor but highly Protestant Sweden in the 19th century. From a political economy perspective, Lindert (2004) convincingly argues that the success of the Prussian education system was mainly due to its high level of decentralization, which allowed it to respond more efficiently to a local demand for education. At an early stage of development, highly centralized systems, in contrast, would be unable to detect the local demand for education and therefore tend to under-provide public primary education (Hanushek et al. 2013). In this paper we argue that for a given demand for education related to the economic structure, a highly decentralized educational system may result in a comparatively lower spending on primary education in presence of a heterogeneous population. We argue that the comparatively low educational performance of the Prussian eastern provinces can, to a large extent, be ascribed to the linguistic heterogeneity of those areas. More specifically, we hypothesize that the divergent interests of different linguistic groups prevented reaching a consensus on local expenditure on primary education. The eastern part of Prussia had always been a melting pot of German and Slavic culture and the foundation of the German Reich in 1871 fueled national feelings on both sides. Becoming part of a German state increased the minority’s awareness of its own ethnic identity and exacerbated conflicts of interest. We use language as a salient measure for diversity as language policy played a major role in the Germanization policy of the Prussian state and because linguistic identity was the only ethnic identifier that Prussian statistical authorities provided (Heinrich 1992a). As school policy played a major role in the enforcement of Germanization policies, we look at the provision of public school funds as a means of investigating the effect of diverging interests. As decisions on school funding were taken at the municipal level, that is, by the local school boards, we expect there to be conflicts over the provision of public education in linguistically polarized counties. Using data from the first comprehensive education census of 1886, published by the Royal Statistical Office of Prussia, we show that the presence of two linguistic groups of similar size, that is, high polarization, led to lower expenditure on public primary education. Specifically, our

1 rich dataset allows us to look more deeply into the allocation of school funds and investigate the impact of linguistic polarization on school density, student-teacher ratios, and teacher wages. The educational census of 1886 provides a unique opportunity to study the impact of linguistic polarization on the local provision of public education as the state’s contribution to primary education was still very limited at that time. In fact, decisions on school funding were at the discretion of local authorities; no statewide law regulating school funds was passed until 1906 (Hühner 1998). We address the issue of causality using an instrumental variable approach. The arguably exogenous variation in polarization comes from the geography of the Kingdom of Prussia’s annexation policies. The successive annexations toward east, for example, the Partitions of Poland, increased the share of ethnic Polish in the population and thus the linguistic heterogeneity. Thus, each province’s distance to the eastern border is used to identify variation in linguistic polarization. Instrumental variable estimates confirm the negative effect of linguistic polarization on local expenditure on primary education. We find a substantial negative effect of polarization on primary education expenditure and one that affected several aspects of school-related spending, including school density, child-to- teacher and student-teacher ratios, and teacher salary. Therefore, we are able to shed light on why East Prussia underperformed in education and, consequently, in economic performance, as basic education played an important role in the Prussian industrial revolution (Becker et al. 2011). Our rich dataset allows us to rule out many possible confounding factors such as income, religious fractionalization, and urbanization. To measure income as accurately as possible, we collected new data on the municipal tax statistics of 1883/1884. We find that the negative impact of linguistic polarization on educational expenditure holds for a given level of economic prosperity as measured by municipal tax revenues. Accounting for the subsidiary role of the central state does not affect our main result either. Additional specifications illustrate the effect of linguistic polarization on other municipal obligations, chiefly infrastructure and poor relief. Consistent with the notion that linguistic polarization was detrimental only for education policies, we find no consistent effect of linguistic polarization on expenditure on infrastructure or on policies related to poor relief. The paper is structured as follows. Section 2 sets out the historical background of 19th- century Prussia. Section 3 surveys the literature. Section 4 describes the dataset. Section 5 presents OLS results. Section 6 presents the instrumental variable approach and its results. Section 7 establishes the falsification exercise. Section 8 examines distributional effects, and Section 9 concludes.

2 2. Historical Background

2.1 The Political Economy of Schooling in late 19th-Century Prussia

In 1886, Prussia’s school system was still locally organized. According to (Lindert 2004), this state of affairs was largely responsible for the school system’s success. Indeed, Prussia’s high school- enrollment and literacy rates made it a role model for other European countries (Clark 2007). At the same time, however, the Prussian administration was aware that the school system in the East, and especially in those regions with a high share of Polish speakers, lagged behind the rest of the country in terms of student-teacher ratios and enrollment rates (Königliches Statistisches Bureau in Berlin 1889), largely due to low school-related investment. We argue that this area’s lower investment in the educational system might have stemmed from high linguistic polarization in these parts of Prussia, a situation itself exacerbated by local organization of the schooling system. The historical literature supports such a relationship by pointing out that municipalities with a linguistically mixed population suffered especially when it came to the provision of school buildings and teachers, explicitly mentioning the coexistence of languages as a reason for this situation (cf. (Grzes 1992); (Heinrich 1992b). Local organization of schooling meant that the local municipality was responsible for levying and allocating school funds (cf. (Lindert 2004; Heinrich et al. 1992; Lamberti 1989). In many places, provincial or even district legislation regulated school financing, but in the absence of such regional regulations, the Allgemeines Landrecht, the Prussian subsidiary law, held. However, regardless of which law applied, the municipality was the decision-making authority when it came to school finance (Königliches Statistisches Bureau in Berlin 1889). In rural municipalities, local patronage, at least in some cases, was able to smooth ethno-linguistic tensions. In cities, however, the organizational reforms (Städteordnung) of 1808 and 1831 regulated school affairs as municipal duties, that is, citizens and, therefore, parents were given a voice in school matter. Moreover, schools were separated by denomination, leading to linguistic segregation in cases where denomination and language collided. Interconfessionally mixed schools (Simultanschulen) existed in municipalities that could not afford operating more than one school (Groeben 1992b). School funding came from various sources, including tuition fees, foundations, schooling societies, municipal taxes, and contributions from the nobility. Funding schemes varied across Prussia and are explored in detail in Section 4.1 of this paper. Decisions as to how to allocate local school funds were made by the school board (Schulvorstand), which consisted of the noble landlord in the estates or the mayor in urban and rural municipalities, the local clergyman, and two to four members of the school district (Schulgemeinde) whose election had to be confirmed by

3 the chief administrative officer of the county, the Landrat. In 1887, the likelihood that members of the Polish-speaking population would sit on these school boards decreased when a ministerial decree ruled that the county’s Landrat should confirm members of the school board only if would-be members were inclined to foster the German-language policy imposed by the Prussian authorities. The purpose of this decree was to assure that Polish and other minority languages were effectively eliminated from being taught (Glück 1979). According to (Grzes 1992), linguistic barriers and diverging interests led to particular problems in the organization of primary schools in linguistically mixed regions. A uniform minimum wage for teachers was not introduced until 1897 (Berger 1897) and a coherent framework for the maintenance of public elementary schools was not enacted into Prussian law until 1906 (Anderson 1970; Lamberti 1989). In addition to school funding, the municipality was also widely responsible for appointing teachers (Glück 1979) until 1886, at which time a law in regard to the appointment of school teachers in the provinces of Posen and West Prussia was enacted. This law shifted the authority to recruit and hire teachers from the local to the state level in these two provinces (Lamberti 1989), but before its enactment, in general, all decisions on hiring teachers, teacher pay, and facility upgrades were made by the municipalities. Thus, 1886, the year in which the reforms were instituted, is the last year in which it is possible to observe the effects of linguistic polarization on educational matters at the local level.

2.2 The Origins of Linguistic Polarization in East Prussia

Prussia’s core territory consisted of the Margraviate of Brandenburg and the Duchy of Prussia. The Margraviate of Brandenburg was primarily inhabited by Germans, with very small shares of non-German speakers. Berlin, the administrative center of the empire, was situated in this territory. As the Duchy of Prussia had been under the rule of the Teutonic Order, the majority of its population traced back to the German colonists. However, the 300 years under Polish sovereignty resulted in a substantial number of Polish- and Lithuanian-speaking Prussians in this territory. The immigration, over centuries, of Huguenots, Lutheran Austrians (Salzburger), Dutchmen, Scots, Lithuanians, Masurians, and Poles had turned the Duchy into a melting pot. The Prussian census of 1886 reports three language groups in this territory: Germans, Poles, and Lithuanians. The Polish-speaking individuals mainly identified as Masurians, who spoke a Polish dialect and were Protestants. They had arrived in the territory in 1460 as religious refugees. Even though the Masurians distinguished themselves from the Catholic Poles, the Prussian statistic does not indicate the Masurians as being a separate ethno-linguistic group. Over time and

4 especially after the war experience of 1871, the Masurians identified primarily as Prussians and increased their usage of German. The Lithuanians in the Duchy of Prussia considered the usage of their language essential to the practice of their beliefs, which put them in opposition to school reforms abolishing the use of minority languages during religious education classes. The archdiocese of Magdeburg fell to Brandenburg in 1541. Germans arrived in this area during the German eastward expansion and thus the originally Slavic territory had been Germanized and Christianized relatively early. After the Thirty Years’ War, Eastern Pomerania became part of Prussia in 1648. Western Pomerania was acquired 70 years later, that is, in 1720 after the Great Northern War. The Pomeranian population consisted of rural colonists stemming from several Germanic tribes that had mixed with local Slavs and who had Germanized in the past. The forest between Pomerania and the former Poland served as a natural border, inhibiting exchange between Poles and Germans at the time the territories fell to Prussia. In the very northeast of Pomerania were the Kashubians, a numerically negligible minority that, nonetheless, succeeded in protecting itself against German influences by being granted far-reaching minority rights. In a long acquisition process that stretched from 1740 to 1763 and involved the two Silesian Wars and the Seven Years’ War, Prussia finally acquired Silesia in 1763. As parts of the province had been devastated by the wars, Frederick the Great initiated a reestablishment plan that involved the settlement of foreigners in the province and reorganization of the province according to the Prussian model. This consolidation phase continued until the end of Frederick the Great’s reign in 1786. In 1886, three-quarters of the Silesian population indicated German as their principal language, whereas this province’s Poles and other Slavs chiefly resided in the district of Oppeln (Neubach 1992). In 1772, the First Partition of Poland resulted in the Netze District, Pomerelia, Chelmno Land, and Warmia becoming part of Prussia. Sixty percent of the population in these territories was German. As the new province connected the core lands of Prussia, that is, the Margraviate of Brandenburg and the Duchy of Prussia, the Prussian authorities were interested in imposing a structured organization on the new province, which was directly controlled by Berlin. Medium- level administration personnel were recruited from nonresidential officials. The German-speaking nobility and the bourgeoisie mixed through intermarriage; however, the Polish Catholic nobility was excluded from administrative positions. Its market access to both the Margraviate of Brandenburg and the Duchy of Prussia made the newly acquired territory of value which led to an expulsion of the land-holding Polish nobility. The Polish nobility had held 80 to 90 percent of the landholdings in 1772, but by 1806, this number had fallen to around 50 percent. This rollback

5 policy generated mistrust between the Polish- and the German-speaking populations, which became evident during county councils and other assemblies at the local level. Even though language itself did not create insurmountable barriers, different traditions in administration and different values resulted in irritation and conflict, leading to the establishment of stereotypes as well as to different understandings of governance (Bömelburg 2013). After the Second and Third Partitions of Poland in 1793 and 1795, Posen became part of Prussia. This meant that Posen, a province with a majority of Polish-speaking individuals, needed to be integrated into the Prussian Empire. Only one-third of the population in this province was of German descent. However, Germans and Poles cohabited relatively peacefully until initiation of Germanization policies in the 1830s (Struve 2013). Germanization peaked with the 1873 and 1876 laws on language usage, with the perhaps not unforeseen effect of fostering Polish nationalism. The laws were passed during the Kulturkampf, the struggle between the Catholic Church and the Prussian authorities between 1871 and 1879, which ultimately destroyed Polish- German relations in the province of Posen (Unruh 1992a). Although Napoleon reestablished a Polish state—the Duchy of Warsaw—between 1807 and 1815, Prussia was restored in its borders before Napoleon’s conquest during the Congress of Vienna in 1815. Moreover, Lower Lusatia and New Western Pomerania were bestowed on Prussia by the Congress of Vienna. Lower Lusatia was populated by the Wendish minority, a Slavic people that had converted to Protestantism during the Reformation (Unruh 1992b). In short, the coexistence of German and non-German speakers observed in Prussia at the end of the 19th century primarily dates back to the conquest of Pomerania and Silesia in the 17th and 18th centuries and to the three partitions of Poland at the end of the 18th century as well as to the so-called fourth partition of Poland during the Congress of Vienna in 1815 (Hansen & Wenning 2003). The partitions of Poland had the consequence that one-third of the Prussian population had formerly belonged to the Polish-Lithuanian Commonwealth (Alexander 2008). These Slavic regions had experienced an in-migration of German settlers since the early Middle- Ages, following the territorial expansion of both the Holy Roman Empire and the Teutonic Order in clear West-to-East lines. The end result was that Poles and Germans lived side by side, even before these regions became Prussian (Zernack 2008). After coming under Prussian rule, Prussia’s active settlement policy, which had as its objective the population of vacant or devastated land, increased the level of polarization. While settlers initially came from German- speaking regions such as the Palatinate or Franconia, periodic wars and epidemics led to a shortage of German colonizers. This is what ultimately led to Lutheran Austrians (Salzburger),

6 Masurian Poles, and Lithuanians, as well as the French Huguenots,1 being invited to settle in the southern and eastern regions of East Prussia. After the three partitions of Poland, the Prussian state authorities reengaged in their population-enhancing policies by inviting and sponsoring German colonizers to settle in the newly acquired Grand Duchy of Posen and, especially, in West Prussia (Zbroschzyk 2014). The West-to-East migration was only reversed after foundation of the German Reich in 1871 when people—of both Polish and German origin—began to move to the industrialized regions of the Rhineland (Wünsch 2008).

2.3 Prussian Language Policy throughout the 19th Century

Historians concur that it was the foundation of the German Empire in 1871 that ultimately initiated German-Polish antagonism (Alexander 2008). The German Empire was understood as a nation state, as opposed to the Prussian Empire, which was built on an abstract and fragmentary common identity of its subjects (Clark 2007). Until the foundation of the German Empire in 1871, the Prussian authorities considered the Polish- or Slavic-dominated regions as “colonies” with their own cultural identity and, as such, supported the use of Slavic languages and local dialects, especially through primary schooling (Clark 2007). The right to freely move across inner-Polish borders and to maintain one’s Polish identity had been legally protected as early as the Congress of Vienna in 1815 and such rights were strengthened by the edict of 1822, which recognized the importance of language and nationality to Polish-speaking citizens. These rights were also enforced in the primary school system. For example, a regulation of 1842 mandated that the language of school instruction was to be that of the majority of the pupils. (Lamberti 1989). After the foundation of the German Reich, Imperial Chancellor Bismarck began to promote Germanization policy. The primary school was to play a key role in this policy by socializing the Polish-speaking students in East Prussia. (Lamberti 1989). Several laws were passed in provinces with Slavic minority populations that gradually established German as the only language of instruction. More than half the curriculum was devoted to German and history lessons aiming at educating loyal Prussian citizens (Lundgreen 1976). Another measure deployed to achieve Germanization was the introduction of the Ostmarkenzulage, a bonus paid to teachers who acted in line accordance with the wishes of the Prussian state (Alexander 2008). However, the Germanization policy did not achieve its objective of a homogenous German-speaking Prussian nationhood. Instead, Poles began to establish their own parallel society by founding banks, organizing themselves in clubs, and passing on Polish-specific human

1 For the effect of the Huguenot immigration into Prussia on productivity, see (Hornung 2014).

7 capital in confirmation classes (Alexander 2008).2 Foundation of Polish cooperatives was a central aspect of the Polish national movement. Moreover, Poles disengaged from the public primary education system and sent their children to private schools (Groeben 1992b). This parallel structure meant that Germans and Poles rarely interacted voluntarily in everyday life, which inhibited the exchange between the two groups that could have resulted in mutual values and beliefs, and, consequently, better cooperation. The social conflict between Germans and Poles peaked with the Polish school strikes in Wreschen in 1901 and in Posen in 1906 (cf. (Lamberti 1989).

3. Literature Review

This paper contributes to two strands of the literature. First, it builds on the vast literature on ethnic fractionalization and the provision of public goods that was initiated by (Alesina et al. 1999) by framing a theoretical model that links the heterogeneity of preferences across ethnic groups to the amount and type of public goods provided. This paper furthermore explores the negative association between ethnic fractionalization and a range of public goods using data from U.S. cities, U.S. metropolitan areas, and U.S. urban counties. Building on neo-institutional economics, the authors argue that the main channel for this negative association is in-group bias, that is, people tending to favor their own kind. The literature provides evidence in support of this argument with its findings that public good provision, redistributive policies, and effective governance are less prevalent in ethnically diverse municipalities or countries (compare the survey by (Alesina & LaFerrara 2005). The early literature restricts itself to showing mere correlations. However, Dahlberg et al. (2012) and Gerdes (2011) exploit natural experiments that randomly placed refugees across Swedish or Danish municipalities, respectively. Dahlberg et al. (2012) find that previous estimates are positively biased and thereby underestimate the true negative effect of fractionalization (for an overview on the recent empirical literature with a focus on the experimental literature also, see the survey by Stichnoth & Van der Straeten 2013). Secondly, our paper contributes to the debate over whether decentralizing provision of public education is beneficial or detrimental. The provision of public education leads to a collective action problem as no party is willing to provide a good that can be used by the other group without exclusion. Overall, the literature examining the role of decentralization in the provision of public schooling is inconclusive (cf. Gallego 2010; Hanushek et al. 2013). For

2 (Alexander 2008) argues that the Prussian policy against linguistic minorities and especially against the Poles eventually led to the country’s decline.

8 example, Oates (1972), Inman and Rubinfeld (1997), and Lindert (2003) stress the positive role of decentralization, whereas Willis et al. (1999), Bardhan (2002), and Kremer et al. (2003) argue that decentralization leads to inefficient provision of education. In a cross-country study, Hanushek et al. (2013) reconcile these opposing views by finding that decentralization is beneficial in developed countries, but has the opposite effect in the developing world. The authors use principal-agent theory to explain their findings, arguing that decentralization reduces the asymmetric information problem as local information is provided but, at the same time, is detrimental where diverging interests impede decisions. Hanushek et al. (2013) can only hypothesize that the downside of decentralization in lower-income countries stems from diverging interests, but the foundation of the German Empire in 1871 and the subsequent increased antagonism between Germans and Poles in East Prussia allows us to empirically test this hypothesis. As the primary school system was decentralized across the entire Prussian Empire, we are not able to look at the counterfactual. However, previous empirical literature on the negative association between ethnic fractionalization and the provision of public goods has focused on U.S. or cross-country evidence, and thus studying East Prussia, an economically underdeveloped region, provides a good laboratory for testing this channel. Along the same lines as this paper, Miguel and Gugerty (2005) investigate the impact of ethnic diversity on local school funding in Kenya by using historical settlement patterns as an instrument. They find that shifting from complete ethnic homogeneity to average school ethnic diversity decreases school funding by approximately 20 percent of the mean local school funding per pupil. They suggest that the inability of ethnically diverse school boards to enforce social sanctions within the municipality3 is crucial to the allocation of school funds. We are not able to examine the mechanisms behind lower provision of educational funding, but we do explore a unique setting where students are segregated along religious lines and consequently, in many cases, also by linguistic affiliation (Grzes 1992),4 and where funding decisions are taken at the municipal level (where different linguistic groups have to interact in order to agree on funding decisions). In the framework of our historical setting, Bukowski (2015) shows the long-term impact of Prussia’s educational policy in regard to its Polish minority in his investigation of the effect of the Polish Partitions on today’s Polish students, arguing that it was Prussia’s oppressive policy

3 These findings are backed up by the experimental literature in this field (cf. Habyarimana et al. 2007). 4 An exception being the interconfessional schools (Lamberti 1989).

9 toward Poles that has had a persistent and deleterious effect of educational outcomes in formerly Polish regions.

4. Data

The data originate from the first educational census of 1886, which was published by the Royal Statistical Office of Prussia (Königliches Statistisches Bureau in Berlin 1889).5 The census was conducted every five years until 1911 and again after World War I, both in 1921 and 1926. The census provides detailed and comprehensive information on enrollment rates, school facilities, teachers, class size, school organization, teacher income, and student background for Prussian counties, the smallest administrative unit. We restrict our analysis to East Prussia where linguistic polarization was most prevalent and more salient and thus exploit variation across 214 counties.6 We concentrate on the first education census of 1886 since—as discussed in Section 2.1— that was the last year in which the level of school expenditure at the local level was high and the central state played only a subsidiary role. This environment is illustrated in Figure 1, which shows the share of state subventions to primary school funding. Clearly, 1886 is the last year for which state subventions are modest, after which they reach over 40 percent of the total expenditure on public primary education.

[Insert Figure 1 about here]

The education census of 1886 provides data on the language spoken in the pupil’s home. The census distinguishes between German, Polish, Lithuanian, Masurian, Slavic, Danish, and other languages. The census also contains information on whether the reported language is the only one spoken at home or whether both German and the other language are spoken at home. When constructing the index of linguistic polarization we include the latter category of bilingual pupils in the group of non-German speakers. We assume that the interests of this bilingual group are more aligned with the interests of the non-German group. In any event, omitting this group when constructing the polarization index does not affect our main results.

5 For a detailed description of the source, see (Becker et al. 2014). 6 We decided not to include Schleswig-Holstein in the analysis as the instrumental variable approach is not expected to identify linguistic variation in that area. However, our baseline results hold when we include counties in Schleswig-Holstein.

10 We measure the antagonism between Germans and Poles or other Slavic populations by using the polarization index proposed by Esteban and Ray (1994),7 which is also employed by Fearon and Laitin (2003) and Collier and Hoeffler (2004), among others. The polarization index is traditionally used to explain (civil) conflicts. Even though the antagonism between the German-speaking Prussians and the Slavic minorities did not culminate in a violent conflict at the time, German-Slavic antagonism was a severe social conflict in that two groups strongly opposed each other in social interaction, culminating first in two parallel societies and finally in two separate states (Alexander 2008). As the Prussian case is characterized by the dualism between Germans and Slavs rather than by linguistic fractionalization, and as recent work by Esteban et al. (2012) shows that linguistic polarization is related to conflict over public goods, while fractionalization increases conflict over private goods, we use the polarization index as set out below to capture the antagonism between German- and Slavic-speaking populations:8

1 ∑ , (1)

where denotes the share of the linguistic group in county . The polarization index varies between 0 and 1 and captures how far the distribution of the groups is from a bipolar distribution, which represents the highest level of polarization. In our case, polarization equals 1 if 50 percent of the pupils speak German and the other 50 percent speak another language at home. Our outcome variables are also constructed from the education census of 1886. The educational census is very detailed and permits distinguishing between educational expenditures stemming from local and national sources. Local funds are comprised of tuition fees and money from foundations, schooling societies, municipalities, charitable institutions, or other sources. National funds are comprised of state funds and state grants that were mainly targeted to municipalities incapable of independently funding their schools (Lamberti 1989). We measure school spending by the amount of local expenditure per child of mandatory school age. Furthermore, our data report the allocation of educational investment, namely, whether public expenditure was used for teacher wages, new buildings, or maintenance. This enables us to investigate how different types of public expenditure on education were affected by linguistic

7 For a discussion on which polarization index to use, see (Duclos et al. 2004; Montalvo & Reynal-Querol 2005); for a more recent discussion, see (Esteban & Ray 2012). 8 In fact, the fractionalization index and the polarization index are almost perfectly collinear in the Prussian case as the counties east of the river Elbe were mainly dominated by only two linguistic groups, Germans and Poles.

11 polarization. In particular, we look at school density, measured by the number of schools per 1,000 children of mandatory school age, the provision of teachers, measured by the number of children of mandatory school age per teacher, and class size, measured by the number of students per teacher. Finally, we also look at average teacher wages, constructed as the sum of local teacher wages divided by the number of teachers (in logarithm). To control for initial differences in both the supply and demand for education, we use data from the population census of 1871 (Königliches Statistisches Bureau in Berlin 1875) and 1885 (Königliches Statistisches Bureau in Berlin 1888), the occupational census of 1882 (Königliches Statistisches Bureau in Berlin 1884b), municipal taxes in 1883/1884 (Königliches Statistisches Bureau in Berlin 1884a), and landownership concentration, as well as data from the Zentralblatt of 1886, a monthly publication of the Prussian Ministry of Education reporting the number of secular as opposed to clerical school inspectors. This last control variable is important as we want to separate the effect of local linguistic polarization on education expenditure from the impact of the Kulturkampf, which aimed at weakening the role of the Catholic Church in providing public education in the Catholic-Polish areas. We also include a control for religious fractionalization in 1871, which, especially in the context of East Prussia, is positively correlated with linguistic heterogeneity. We account for religious fractionalization using the standard measure related to the Herfindahl index:

1∑ (3)

where denotes the share of the religious group in county , based on five religious denominations: Catholic, Protestant, other Christian, Jewish, and other religion. The fractionalization index, which varies also between 0 and 1, measures the probability that two individuals randomly drawn from a population belong to a different denomination. The index increases monotonically with the number of groups in a county. For a given number of groups, the index increases as the share of religious groups is more equally distributed.

4.1 Sources of School Funding

Prussia did not pass a universal law on school funding until 1906 (cf. (Anderson 1970; Lamberti 1989)). Prior to the law’s passage provincial regulations or customary law at the regional level set out guidelines for school funding. This ultimately led to very different funding schemes across the six eastern provinces, as can be seen in Table 1.

12 [Insert Table 1 about here]

There were five principal sources of local school funding. As the Prussian schooling system had been historically strongly intertwined with the church, church foundations provided parts of the school funds.9 They contributed the largest share to school funding in the four counties of Saxony being situated East of the Elbe. Schooling societies were another contributor to school funds. Schooling societies were constituted of the heads of economically independent households in a school district that had to make contributions on basis of their property, no matter whether they had children of mandatory school age or not. They accounted for the highest fraction of school funds in Pomerania and Posen. Whether tuition fees were demanded or not differed from province to province. In counties with schooling societies, households that had already contributed to the primary schools through the schooling societies were exempted from tuition fees as well as households that were financially unable to pay tuition fees. The fees for those children were paid out of the church’s collection of alms during service or the (municipal) fund for poor relief. Tuition fees were legally abolished in 1888/89. In 1886, they still constituted more than a quarter of school spending in Saxony10 and almost 20 percent in Brandenburg. The Allgemeines Landrecht set out the level of tuition fees where no other regulations existed. (Königliches Statistisches Bureau in Berlin 1889). Ethnic polarization might have only led to lower funding by tuition fees if parents resisted paying fees despite sending their children to school. Furthermore, revenues from municipal taxes contributed to school funding.11 Each municipality could determine the share of their revenues, generated from local taxes such as the income, business and property tax (cf. (Grzes 1992; Hühner 1998) that would go to the elementary education sector. Taxes raised for primary schools were a substantial financial burden for many municipalities. In the province of Brandenburg, municipal tax contributions made up for the highest fraction of school funds. In the provinces of Prussia, Silesia and Pomerania, municipal taxes made up for the second highest share of school funding. Even though the noble landlords were relieved from their obligation to fund primary schools in 1888/89 along with the abolition of the tuition fees (Neugebauer 1992), patronage still accounted for the highest share of local school funds in the provinces of Silesia and Prussia in 1886.

9 For a detailed description of the functioning of church foundations in Brandenburg, see (Moderow 2007). 10 Note that we examine only four Saxon counties as the rest of the counties were situated west of the river Elbe. 11 Earlier publications of the Royal Statistical Office of Prussia in 1861, 1864, 1867, 1871, 1878 already reported local school spending for primary schooling. However, this only included municipal taxes why earlier estimations of the contributions at the local level report much lower figures (Königliches Statistisches Bureau in Berlin 1889).

13 State grants and funds supported financially weak municipalities. As can be seen the share of state support was highest in the relatively poor provinces of Posen, Pomerania and Prussia. Provinces in Table 1 are sorted by their average school spending per child of mandatory school age starting with the province with the lowest level of spending, Posen. It can be seen that the composition of school spending is not directly related to the level of spending. Overall, the funding schemes across the six eastern provinces varied substantially. At over 60 percent, school funds in Posen exclusively came from schooling societies, while school funds in the provinces of Prussia and Silesia mainly stemmed from patronage and municipal taxes. The funding scheme in Pomerania was very balanced. While schooling societies contributed the largest share, considerable shares were also raised by municipal taxes, tuition fees and patronage. In Saxony, foundations made up the largest share of school funds, followed very closely by tuition fees while in Brandenburg municipal taxes were the most important source of school funds followed by contributions by the noble landlords.

4.2 Descriptive Evidence on Local School Spending and Linguistic Polarization

Table 2 shows how local school spending per child of mandatory school age varied widely across Prussian counties.

[Insert Table 2 and Map 1 about here]

The main share of expenditures is allocated to teacher wages: on average, teacher wages constitute 63 percent of total local school spending, whereas expenditures for infrastructure (new and maintenance) account for 22 percent of total education expenditure. Germans and Poles were the two dominant linguistic groups at 75 and 22 percent, respectively. The polarization index, which ranges between 0 and 1, has an average value of 0.29. In East Prussia, 171 out of 214 counties experienced some level of polarization. There are 47 counties where non-Germans constitute the majority. Overall, linguistic polarization increases the closer a county is to the eastern border of Prussia.

5. Polarization and Local School Spending in the Cross-Section

To discover the association between linguistic polarization and school funding, we estimate the following baseline OLS model:

14 (2) where the dependent variable is the (log) local school spending per child of mandatory school age, that is, between 6 and 14 years old, in county . is the polarization index at the county level and is a vector of covariates. The covariates included in the equation reflect findings of previous literature on the determinants and consequences of provision of education in Prussia (Becker & Woessmann 2009; Becker et al. 2011; Cinnirella & Hornung 2013). Becker and Woessmann (2009) establish that Luther’s request that every Protestant should be able to read the Bible increased demand for education in mainly Protestant regions, leading to better provision of schooling and, consequently, higher literacy. Primary education played a major role in Prussia’s effort to catch up with early-industrializer Britain (Becker et al. 2011). Furthermore, Cinnirella and Hornung (2013) show that large landownership and the institution of serfdom slow the accumulation of education. Therefore, religion, industrialization, and the concentration of large landownership are control variables included in vector X.

[Insert Table 3 about here]

The OLS estimates are presented in Table 3. The unconditional correlation between linguistic polarization and local school funding is negative and highly significant (Column 1). We stepwise include covariates that might confound the relationship between linguistic polarization and local school funding. We start with the share of Protestants to control for the higher demand for education among the Protestant population. The share of Protestants is, as expected, positively associated with local school spending. The coefficient for linguistic polarization decreases slightly but remains significant. The coefficient for religious fractionalization has a negative sign but is not statistically significant (Table 3, Column 3). We also test whether linguistic polarization has a differential impact at different levels of religious fractionalization. However, the interaction term in Column 4 is not significant. The under-provision of primary schooling is often ascribed to the Polish population’s lower demand for education. Thus it is important to test the extent to which the polarization index captures a high share of Polish population. In Column 5 of Table 3 we include the share of pupils who speak only Polish. And, indeed, the share of Polish pupils is negatively correlated with local

15 school spending. Although this variable captures part of the impact of linguistic polarization, the coefficient of the latter is highly significant both economically and statistically. Population density is significantly positively related to local spending on primary education, whereas the number of years under Prussian rule shows no correlation. It could be argued that counties characterized by high levels of linguistic polarization are also economically less prosperous and therefore could afford less education. If this was the case, our interpretation of the negative impact of polarization because of coordination failure and divergent interests would be incorrect. It is therefore crucial to account for systematic differences in economic prosperity. The best measure available at the county level for the period under consideration is municipal tax revenues for the years 1883/1884. Indeed, we find that municipal tax revenues are strongly positively associated with local spending on primary education (Table 3, Column 8). Since municipal tax rates are also measured in logarithm, we can interpret the coefficients as elasticity: an increase of municipal tax revenues by 1 percent is associated with an increase in school spending of 0.26 percent. Importantly, we find that for a given level of revenue, redistribution in favor of public primary education was systematically lower in counties with high levels of linguistic polarization. We show below that the same results hold if we account for the subsidiary role of the state. In Column 9 of Table 3 we account for the economic structure of the county, including controls for the share of people living in urban centers, the concentration of large landownership, the share of people employed in agriculture, and the share of people employed in manufacturing. Only the coefficient for urbanization shows a positive significant relationship with local spending on primary schools, whereas the coefficient for linguistic polarization remains highly significant. In Column 10 of Table 3 we include all the control variables simultaneously. The only coefficients that remain significant are those for the share of Protestants, population density, municipal tax revenues, and urbanization. The coefficient for linguistic polarization also continues to be highly significant, albeit smaller in size. Finally, in Column 11 of Table 3 we employ an even more restrictive specification by including province fixed effects. It is very plausible that provincial-level regulations might have affected school spending (Königliches Statistisches Bureau in Berlin 1889) and we know that funding schemes varied substantially across provinces. Yet, the negative impact of linguistic polarization remains highly significant even when we exploit only within-province variation.

16 6. Addressing Causality

The previous regression results indicate that the relationship between linguistic polarization and local public expenditure on education is not due to differences in tax revenue, agricultural or industrial structure, religious fractionalization, or the share of Polish in a county. However, omitted variables and reverse causality might bias our results. It is reasonable to assume that a persistently underfunded school system contributed to the maintenance of a high level of linguistic polarization. Furthermore, Prussian authorities’ effort to downplay the size of linguistic minorities might have caused measurement error in the explanatory variable. As this could have resulted in an underestimation of polarization in most of the cases, this measurement error might lead to an attenuation bias. Finally, we cannot account for different price levels as a price index at the county-level is not available for Prussia during our period of study. We partially account for different price levels by considering different income levels; however, income levels do not perfectly capture price levels. We therefore propose an instrumental variable (IV) approach designed for the Prussian context.

6.1 Identification Strategy—An Instrumental Variable Approach for Prussia

We develop an instrumental variable approach using distance to the eastern border and the “geography” of Prussian acquisitions in order to predict polarization. The level of polarization in Prussia mainly dates back to the expansion of Prussian territory in the 18th and 19th centuries. Annexed or conquered territories faced different policies of integration into the Prussian Empire, each of which had a different impact on the assimilation or cohabitation of various linguistic population groups. The different treatment of linguistic minority groups and the cohabitation of Germans and the minority groups is detailed in Section 2.2 of this paper. At the same time, Slavic populations at the eastern border of the Empire exerted an influence that allowed regions close to the eastern border to maintain their Slavic culture even in the face of Germanization efforts by the Prussian authorities. This identification strategy relies on the assumption that the distance to the eastern border and the different legacies of annexation have an impact on local school spending through linguistic polarization alone. As no universal school law was passed until 1906, being acquired by Prussia as one territory should not affect school spending directly. Distance to other Slavic populations should not affect the level of school spending either. This could hold only if Polish or other minorities had a lower demand for education that decreased educational spending, which is why we additionally control for the Polish share in the population.

17 We adapt the following IV approach to the Prussian setting in order to predict polarization:

∗ , (4)

where denotes the polarization index of county c in 1886. captures the distance to the eastern border and is a dummy variable for the different territories annexed by Prussia, the so-called “geography” of annexations. We distinguish between nine different territories, namely, (1) the Margraviate of Brandenburg, (2) the Duchy of Prussia, (3) Eastern Pomerania, (4) Western Pomerania, (5) Magdeburg, (6) Silesia, (7) the First Partition of Poland, (8) the Second and the Third Partitions of Poland, and (9) the territories acquired by Prussia after the Congress of Vienna. After estimating Equation (4), we use its predicted values to instrument for the actual values of linguistic polarization in the second stage. Map 1 reveals that linguistic polarization seems to diminish as we move further from the eastern border. As described in Section 2.2, Germans and Poles had cohabited in the newly acquired territories before these regions became parts of Prussia, dating back to the German eastward expansion, which followed clear West-to-East lines. As the border to the east was the border with Russia and therefore with other Slavic-speaking populations, we suspect that populations living close to the border were more successful in withstanding the ongoing Germanization attempts of the Prussian authorities, thus maintaining a high level of polarization. By including the different annexation territories, we account for the active Prussian settlement policy (Ansiedlungspolitik) and different historical patterns of cohabitation at the same time.

[Insert Map 2 about here]

6.2 Results

The first stage of the first-differences estimation as shown in Table 4, confirms the expected mechanism of the instrument. Linguistic polarization decreases the farther a county is situated from the eastern border and thereby the farther away it is from the influence of other Slavic people, such as contiguous Poles in Congress Poland. With every additional 100 km distance from the eastern border, linguistic polarization on average decreases by 9 percentage points. For the interaction terms between the distance to the eastern border and the respective nine geographic territories of annexation, there is a significant negative coefficient for the interactions

18 with Farther Pomerania, Western Pomerania, and Silesia. In these territories, the negative effect of the distance to the eastern border is amplified. For the territories that became Prussian through the First and Second Partitions of Poland, however, polarization increases with distance to the eastern border. This result is intuitive given that these formerly Polish counties bordering the East were mainly populated by Poles, consequently having only a small German minority, which is why we find that polarization increases with distance to the eastern border in formerly Polish territories.

[Insert Table 4 about here]

Table 5 sets out the results from estimating the IV approach. Column 1 shows estimates from the OLS model to serve as a benchmark.

[Insert Table 5 about here]

Results from two-stage least-squares models confirm the negative effect of linguistic polarization on local school spending. The coefficient of the instrument and the first-stage F-statistics at the bottom of Table 5 support the validity and the strength of the instrument. In terms of magnitude, the coefficient estimated in Column 2 of Table 5 suggests that moving from a county with zero polarization to a county with total polarization reduces average local school spending by about 32 percent. This effect is substantial. The IV coefficient is higher than the OLS coefficient, which might be due to the fact that the IV approach accounts for the measurement error in polarization. As the average annual local teacher unit cost was 720 Marks in East Prussia, the average school with 200 students in a fully polarized county could have employed one additional teacher if the “costs” of polarization were completely eliminated. This is only speculative, though. In Section 7 we shift our attention to the real effects of linguistic polarization on the allocation of the school funds. In Columns 2–7 of Table 5 we include a set of geographical covariates, including longitude, latitude, terrain slope, temperature, and precipitation, in order to control for the fact that there might have been underlying geographic characteristics that influenced location-specific human capital (see (Michalopoulos 2012). Distance to the eastern border might capture other geographic determinants, which is why we control for latitude and longitude and include a

19 dummy variable for whether the county is a border county (Column 3). The coefficient decreases slightly, whereas the F-statistics even increases. The results are robust to including terrain slope, temperature, and precipitation. If the state or the provinces had any influence on the level of school spending, this should be captured by the distance to the Prussian capital, Berlin, or the distances to the provincial capitals, as we assume that political enforcement is easier closer to the political centers that shape politics and control their implementation. Column 6 includes all geographical and political covariates; Column 7 additionally considers province fixed effects. The coefficient increases slightly when including province fixed effects. When including province fixed effects, the F-statistic decreases to 6.0, which is explained by the fact that the timing of the geographical annexations and the province fixed effects are strongly correlated.

6.3 Rural Versus Urban Parts of Each County

Finally, we estimate the effect of polarization on local school spending for a sample that distinguishes between the urban and rural parts of a county. As the education census of 1886 distinguishes between the urban and the rural parts of each county and the financial statistics of 1883/1884 report data for single urban and aggregated rural communities of a county, we can distinguish between urban and rural parts of each county and thereby increase the number of observations to 408. We also look at the effect of polarization in the urban and rural samples separately to investigate whether effects differ between cities and the countryside. As local school funding decisions were made at the municipal level, this sample allows us to more closely approach the actual level of decision making. As we can only distinguish between rural and urban parts in the education census and the financial statistics, we have to forego including the standard set of controls, thus decreasing the comparability of the results. We furthermore weight the observations in the pooled sample by the urbanization share of the respective county in order to consider that, otherwise, the observations for the urban parts of each county would be overstated as the urbanization fraction in 1886 was only 25.5 percent. The results for the sample at the finer level of observation are set out in Table 6.

[Insert Table 6 about here]

The coefficients for the original county-level sample and the pooled sample are similar in size in both the ordinary least squares model as well as in the instrumental variable approach. Any difference can be attributed to the fact that 10 counties are lost in the pooled sample due to the fact that some counties are only rural while others are city counties. Once we split the sample

20 into the urban parts of a county and the rural parts of the county (Table 6, Columns 3 and 4), we find that polarization affects the level of educational spending in the urban parts much more severely than in the rural parts. This discrepancy is amplified by employing the instrumental variable approach (Columns 7 and 8). It is in the cities that people of different linguistic heritage meet in the school boards and in the municipal council, while in the countryside, people with different linguistic backgrounds would continue to live in segregated villages, and thus there would be little, if any, interaction between the different linguistic groups. However, it must be kept in mind that the explanatory power for the urban sample is limited.

6.4 Robustness

When distance to the eastern border is used as an instrument for linguistic polarization, there could be other confounding factors correlated with distance to the eastern border. As discussed in Section 4.1, the state began to gain influence in primary school education by subsidizing fiscally-challenged municipalities (Neugebauer 1992). Relying on state grants or state funds might have decreased local contributions to schooling. The detailed information on the levy of the school funds allows us to separately account for the state’s contributions. Furthermore, the Prussian state also aimed at monitoring primary schools by replacing clerical school inspectors with secular ones who were required to report directly to the Prussian authorities in Berlin (Lamberti 1989). We expect that a higher share of secular school inspectors increased local school spending as secular school inspectors would report to the Prussian state authorities on deficiencies in both personnel and buildings, thereby putting pressure on the municipalities to invest in their school systems. Spending levels might also vary depending on the ratio between people paying taxes and people dependent on these people, that is, the elderly and the very young who are not yet in the labor market. This is why we include the average household size in our estimations (Column 2 of table 7). As argued in Section 6.1, a higher share of military personnel might have increased the share of German speakers as non-German speakers were assimilated through the military service required of every Prussian male citizen. As noted previously, it could be that non-German speakers simply had a lower demand for education, which is why we include a dummy variable for whether the county had a German minority. As non-German speakers constitute the majority in these counties, they could have overruled the German minority in decisions concerning the educational system.

21 It is well-established (cf. (Lamberti 1989) that schooling societies were especially inefficient in levying funds for primary schools. To rule out that institutional patterns might impact the level of educational expenditure, we control for the share of funds provided by schooling societies in Column 6 of table 7. Finally, we include all these additional covariates simultaneously in Column 7 of table 7.

[Insert Table 7 about here]

Table 7 shows estimates of the different robustness checks. The coefficient remains negative with a similar magnitude as in the baseline IV model and it furthermore remains significant throughout all specifications. State interventions, measured by state expenditure per child of mandatory school age (Table 7, Column 2) negatively affect local school spending, which is in line with the idea that state subventions substitute for local school spending. The average household size, the share of people in the military, the dummy variable indicating whether the county has a German minority, the share of secular school inspectors, and the share of funds contributed by schooling societies do not have an impact on their own. Column 4 of Table 7 includes a dummy for whether the German population is in the minority. The coefficient on German minority is positive though not significant, that is, the often-stated claim that Poles and other linguistic minorities had a lower demand for education cannot be confirmed by this empirical analysis. This reinforces our finding that it is polarization and not a different demand for education per se that decreases local school spending in linguistically polarized counties.

7. Alternative Public Goods

In Section 2.3, we stated that the polarization between Germans and those of Slavic descent chiefly manifested in the matter of primary schools and finally cumulated in the Polish school strikes of 1901 and 1906. We therefore believe that the negative effect of polarization should first be found in matters related to the primary school system. The dataset on municipal taxes from 1883/1884 also provides information on investments in infrastructure and in poor relief, two alternative public goods. Poor relief was regulated through the Allgemeines Landrecht, meaning that the municipality was responsible for the poor within its boundaries. Syndicates comprised of (groups of) municipalities or land estates were responsible for the local poor and set the level of support. Poor relief encompassed preventive and direct support. Preventive support included the allocation of labor, the education

22 of disadvantaged children, and free primary healthcare. Direct support included the provision of working houses and orphanages as well as monetary and nonmonetary contributions (Hühner 1998). Expenditures for poor relief are measured per person living in an institution, capturing the population in need. The construction and maintenance of streets, canals, bridges, harbors, and railways, street cleaning, surveying and mapping, gardening, and other traffic-related tasks all fell within the ambit of the municipal administration (Hühner 1998). As it is hard to observe who is benefitting from the infrastructure provision, we expect that linguistic polarization should not affect public investments in this sphere.

[Insert Table 8 about here]

Although there is at first a negative and significant coefficient on infrastructure expenditures in the parsimonious model (Table 8, Column 1), the negative and significant coefficient turns insignificant and diminishes substantially as soon as extensive covariates are considered and also remains insignificant in the IV setting even though the coefficient increases tremendously. This is due to the fact that the instrumental variable approach is not appropriate in this case. The Prussians fostered the expansion of roads, channels, and other infrastructure early on in newly acquired provinces, which violates the exclusion restriction as the geography of annexations had a direct impact on infrastructure investments. For poor relief, we find a positive coefficient in the parsimonious model. The coefficient is insignificant both in the parsimonious model as well as when we include extensive controls. Once we apply the identification strategy that we consider appropriate in this setting, as poor relief - like education policy - was clearly a local affair, we find a significant positive effect of linguistic polarization on poor relief.

8. Distributional Effects

We now shift our attention to the distributional effects. As the education census of 1886 distinguishes between investments made in teachers and in school facilities, we can discover which sectors of the schooling system suffered most from underinvestment in education. To this end, we look at school density, measured as the number of schools per 1,000 children of mandatory school age, and the number of both children of mandatory school age and students per teacher, as well as unit teacher wages. We apply the IV model and include the standard covariates as in the general IV approach.

23 The results in Table 9 show that all subcategories of local school spending are negatively affected by a higher level of polarization. The magnitudes of these four coefficients show a very substantial impact of polarization.

[Insert Table 9 about here]

Increasing polarization from 0 to 1 implies a reduction of two schools per 1,000 children of mandatory school age. As the average school density is 6.65 schools per 1,000 children of mandatory school age, this is a one-third reduction in school supply. Of course, smaller schools were not automatically better schools. Large urban schools in particular benefited from school standardization in ensuring a certain quality, school-based diversification and economies of scale (Kahlert 1978). However, if we exclude nine city counties from our regression, the negative effect decreases to 1.86 schools, showing that the negative effect was even more severe in urban regions. The student-teacher ratio increases by 15 students when polarization is increased from 0 to 1 and the number of children of mandatory school age, accounting for the school enrollment at the same time, increased by 27 children per teacher. These are very substantial effects. Teacher unit costs decrease by 31 percentage points.

9. Conclusion

Prussia’s primary school system rightly had an excellent reputation. Average enrollment rates were much higher relative to the rest of Europe during the entirety of the 19th century and the average high level of basic education played a major role in the second phase of its industrialization (Becker et al. 2011). A recent revisionist view argues that the accumulation of human capital in Prussia was a bottom-up process in which the high level of political decentralization played a major role in the country’s success (Lindert 2004). The decentralization of education policies is said to have allowed local municipalities to satisfy the demand for human capital in the early stages of the country’s development. In this paper we argue that decentralization of education policies resulted in an under- provision of public education in those areas of the country characterized by conflicting and divergent interests, underlining the recent finding by (Hanushek et al. 2013) that decentralization is detrimental in economically less developed counties for this precise reason. In particular, we demonstrate that in the context of 19th-century Prussia, a high level of linguistic polarization

24 resulted in significantly lower local expenditure on education. We show that this effect is not due to lower tax revenues, agricultural or industrial structure, or religious denominations. Instrumental variable estimates using distance to the eastern border and the geography of Prussian annexations suggest that the estimated effect is causal. We also show that the state’s subsidizing role does not neutralize the negative effect of linguistic polarization. In fact, the negative effect of linguistic polarization on local school spending manifests itself in lower school density, fewer teachers per students and also per children of mandatory school age, and lower teacher unit costs, despite additional resources supplied by the state. Centralized decision making on school spending might have increased the level of spending, but would have very likely neglected Polish interests at a time when these interests were already under attack by the Prussian authorities’ Germanization policy.

25 References

Alesina, A., Baqir, R. & Easterly, W., 1999. Public Goods and Ethnic Divisions. The Quarterly Journal of Economics, 114(November), pp.1243–1284. Alesina, A. & LaFerrara, E., 2005. Ethnic Diversity and Economic Performance. Journal of Economic Literature, 43(September), pp.762–800. Alexander, M., 2008. Kleine Geschichte Polens, Stuttgart: Reclam. Anderson, E.N., 1970. The Prussian Volksschule in the Nineteenth Century. In G. A. Ritter, ed. In Entstehung und Wandel der modernen Gesellschaft. Festschrift für Hans Ro-senberg zum 65. Geburststag. Berlin: Walter de Gruyter, pp. 261–279. Bardhan, P., 2002. Decentralization of Governance and Development. Journal of Economic Perspectives, 16(4), pp.185–205. Becker, S.O. et al., 2014. The ifo Prussian Economic History Database. Historical Methods: A Journal of Quantitative and Interdisciplinary History, 47(2), pp.57–66. Becker, S.O., Hornung, E. & Woessmann, L., 2011. Education and catch-up in the industrial revolution. American Economic Journal: Macroeconomics, 3(3), pp.92–126. Becker, S.O. & Woessmann, L., 2009. Was Weber wrong? A Human Capital Theory of Protestant Economic History. The Quarterly Journal of Economics, 124(2), pp.531–596. Berger, P., 1897. Das preussische Lehrerbesoldungsgesetz vom 3. März 1897. Finanzarchiv, 14(2). Bömelburg, H.-J., 2013. Inklusion und Exklusion nach der ersten Teilung Polen-Litauens. In H.- J. Bömelburg, A. Gestrich, & H. Schnabel-Schüle, eds. Die Teilungen Polen-Litauens. Inklusions- und Exklusionsmechanismen – Traditionsbildung – Vergleichsebenen. Osnabrück: fibre Verlag, pp. 171–200. Cinnirella, F. & Hornung, E., 2011. Landownership Concentration and the Expansion of Education, Clark, C., 2007. Iron Kingdom. The Rise and Fall of Prussia, 1600-1947, London: Penguin Books. Collier, P. & Hoeffler, A., 2004. Greed and grievance in civil war. Oxford Economic Papers, 56, pp.563–595. Dahlberg, M., Edmark, K. & Lundqvist, H., 2012. Ethnic Diversity and Preferences for Redistribution. Journal of Political Economy, 120(1), pp.41–76. Duclos, J.Y., Esteban, J. & Ray, D., 2004. Polarization: Concepts, measurement, estimation. Econometrica, 72(6), pp.1737–1772. Esteban, J., Mayoral, L. & Ray, D., 2012. Ethnicity and Conflict: An Empirical Study. American Economic Review, 102(4), pp.1310–1342. Esteban, J. & Ray, D., 2012. Comparing Polarization Measures. In M. R. Garfinkel & S. Skaperdas, eds. The Oxford Handbook of the Economics of Peace and Conflict. Oxford.

26 Esteban, J. & Ray, D., 1994. On the Measurenment of Polarization. Econometrica, 62(4), pp.819– 851. Fearon, J.D. & Laitin, D.D., 2003. Ethnicity, Insurgency and Civil War. American Political Science Review, 97(1), pp.75–90. Gallego, F., 2010. Historical Origins of Schooling: The Role of Democracy and Political Decentralization. Review of Economics and Statistics, 92(2), pp.228–243. Gerdes, C., 2011. The Impact of Immigration on the Size of Government: Empirical Evidence from Danish Municipalities. Scandinavian Journal of Economics, 113(1), pp.74–92. Glück, H., 1979. Die preußisch-polnische Sprachenpolitik: eine Studie zur Theorie und Methodologie der Forschung über Sprachenpolitik, Sprachbewußtsein und Sozialgeschichte am Beispiel der preußisch-deutschen Politik gegenüber der polnischen Minderheit vor 1914, Hamburg: Buske. Groeben, K. van der, 1992a. Provinz Ostpreußen. In G. Heinrich, F.-W. Henning, & K. G. A. Jeserich, eds. Verwaltungsgeschichte Ostdeutschlands 1815-1945. Organisation - Aufgaben - Leistungen der Verwaltung. Stuttgart/Berlin/Köln: Verlag W. Kohlhammer, pp. 147–260. Groeben, K. van der, 1992b. Provinz Westpreußen. In G. Heinrich, F.-W. Henning, & K. G. A. Jeserich, eds. Verwaltungsgeschichte Ostdeutschlands 1815-1945. Organisation - Aufgaben - Leistungen der Verwaltung. Stuttgart/Berlin/Köln: Verlag W. Kohlhammer, pp. 261–348. Grzes, B., 1992. Die Schulprobleme der Polen in Preussen in den Jahren 1815-1871. In R. Rexheuser, ed. Bildung und Nationalismus. Die Schule in ethnischen Mischgebieten. (19. und 20. Jahrhundert). Lüneburg: Institut Nordostdeutsches Kulturwerk, pp. 439–456. Hansen, G. & Wenning, N., 2003. Schulpolitik für andere Ethnien in Deutschland. Zwischen Autonomie und Unterdrückung, Münster/New York/München/Berlin: Waxmann. Hanushek, E.A., Link, S. & Woessmann, L., 2013. Does school autonomy make sense everywhere? Panel estimates from PISA. Journal of Development Economics, 104, pp.212–232. Heinrich, G., 1992a. Staatsverwaltung, Kirchen und Religionsgemeinschaften. In G. Heinrich, F.- W. Henning, & K. G. A. Jeserich, eds. Verwaltungsgeschichte Ostdeutschlands 1815-1945. Organisation - Aufgaben - Leistungen der Verwaltung. Stuttgart/Berlin/Köln: Verlag W. Kohlhammer, pp. 129–146. Heinrich, G., 1992b. Wissenschaftsverwaltung, Bildungswesen und Kulturaustausch. In G. Heinrich, F.-W. Henning, & K. G. A. Jeserich, eds. Verwaltungsgeschichte Ostdeutschlands 1815- 1945. Organisation - Aufgaben - Leistungen der Verwaltung. Stuttgart/Berlin/Köln: Verlag W. Kohlhammer, pp. 102–128.

27 Heinrich, G., Henning, F.-W. & Jeserich, K.G.A. eds., 1992. Verwaltungsgeschichte Ostdeutschlands 1815-1945. Organisation - Aufgaben - Leistungen der Verwaltung, Stuttgart/Berlin/Köln: Verlag W. Kohlhammer. Hornung, E., 2014. Immigration and the Diffusion of Technology: The Huguenot Diaspora in Prussia. American Economic Review, 104(1), pp.84–122. Hühner, M., 1998. Kommunalfinanzen, Kommunalunternehmen und Kommunalpolitik im Deutschen Kaiserreich. In R. Tilly, ed. Münsteraner Beiträge zur Cliometrie und quantitativen Wirtschaftsgeschichte. Münster: LIT Verlag. Inman, R.P. & Rubinfeld, D.L., 1997. Rethinking Federalism. Journal of Economic Perspectives, 11(4), pp.43–64. Kahlert, H., 1978. Prolegomena zur Geschichte der Bildungsökonomie: Bibliographie und Darstellung (1850- 1945), Weinheim: Beltz. Königliches Statistisches Bureau in Berlin, 1884a. Beitragë zur Finanzstatistik der Gemeinden in Preussen : Die Einnahmen u. Ausgaben d. preussischen Stadtë u. Landgemeinden, sowie d. Sollaufkommen an direkten Staatssteuern, Kreis-, Provinzial-, Schul-u. Kirchensteuern in denselben fur̈ das Jahr 1883/84, Berlin. Königliches Statistisches Bureau in Berlin, 1898. Das gesammte niedere Schulwesen im preußischen Staate im Jahre 1896. In Preussische Statistik Vol. 151. Berlin: Verlag des Königlichen Statistischen Bureaus. Königliches Statistisches Bureau in Berlin, 1889. Das gesammte Volksschulwesen im preußischen Staate im Jahre 1886. In Preussische Statistik Vol. 101. Berlin: Verlag des Königlichen Statistischen Bureaus. Königliches Statistisches Bureau in Berlin, 1893. Das gesammte Volksschulwesen im preußischen Staate im Jahre 1891. In Preussische Statistik Vol. 120. Berlin: Verlag des Königlichen Statistisches Bureaus. Königliches Statistisches Bureau in Berlin, 1903. Das gesamte niedere Schulwesen im preußischen Staate im Jahre 1901. In Preussische Statistik Vol. 176. Berlin: Verlag des Königlichen Statistischen Bureaus. Königliches Statistisches Bureau in Berlin, 1908. Das gesamte niedere Schulwesen im Preußischen Staate im Jahre 1906. In Preussische Statistik Vol. 209. Berlin: Verlag des Königlichen Statistischen Bureaus. Königliches Statistisches Bureau in Berlin, 1888. Die endgültigen Ergebnisse der Volkszählung vom 1.01.1885 im Preußischen Staate sowie in den Fürstentümern Waldeck und Pyrmont:

28 nebst e. 15 aktenmäßige Berichte über d. Ausführung dieser Zählung. In Preussische Statistik Vol. 96. Berlin: Verlag des Königlichen Statistischen Bureaus. Königliches Statistisches Bureau in Berlin, 1884b. Die Ergebnisse der Berufsstatistik vom 5. Juni 1882 im preussischen Staat. In Preussische Statistik Vol. 76 a-c. Berlin: Verlag des Königlichen Statistischen Bureaus. Königliches Statistisches Bureau in Berlin, 1875. Die Ergebnisse der Volkszählung und Volksbeschreibung im Preussischen Staate vom 1. December 1871. In Preussische Statistik Vol. 30. Berlin: Verlag des Königlichen Statistischen Bureaus. Kremer, M., Moulin, S. & Namunyu, R., 2003. Decentralization : A Cautionary Tale. Lamberti, M., 1989. State, Society and the Elementary School in Imperial Germany, New York/Oxford: Oxford University Press. Lindert, P., 2004. Growing Public. Social Spending and Economic Growth since the Eighteenth Century, Cambridge, MA: Cambridge University Press. Lindert, P.H., 2003. Voice and Growth: Was Churchill Right? The Journal of Economic History, 63(2), pp.315–350. Lundgreen, P., 1976. Educational Expansion and Economic Growth in 19th-Century Germany. A Quantitative Study. In L. Stone, ed. Schooling and Society. Studies in the History of Education. Baltimore, pp. 20–66. Michalopoulos, S., 2012. The Origins of Ethnolinguistic Diversity. American Economic Review, 102(4), pp.1508–1539. Miguel, E. & Gugerty, M.K., 2005. Ethnic diversity, social sanctions, and public goods in Kenya. Journal of Public Economics, 89, pp.2325–2368. Moderow, H.-M., 2007. Das kirchliche Stiftungsvermögen der evangelischen Volksschulen und sein Schicksal bis in das 20. Jahrhundert. Untersuchungen zu einem grundlegenden Problem der Volksschulfinanzierung am Übergang zur Moderne - Sachsen, Brandenburg und Württemberg im Vergl. In J. Flöter & C. Ritzi, eds. Bildungsmäzenatentum. Privates Handeln - Bürgersinn - kulturelle Kompetenz seit der Frühen Neuzeit. Köln: Böhlau Verlag, pp. 207–232. Montalvo, J.G. & Reynal-Querol, M., 2005. Ethnic diversity and economic development. Journal of Development Economics, 76, pp.293–323. Neubach, H., 1992. Die Verwaltung Schlesiens zwischen 1845 und 1945. In G. Heinrich, F.-W. Henning, & K. G. A. Jeserich, eds. Verwaltungsgeschichte Ostdeutschlands 1815-1945. Organisation - Aufgaben - Leistungen der Verwaltung. Stuttgart/Berlin/Köln: Verlag W. Kohlhammer, pp. 878–942.

29 Neugebauer, W., 1992. Das Bildungswesen in Preußen seit der Mitte des 17. Jahrhunderts. In O. Büsch, ed. Handbuch der Preußischen Geschichte, Band II, Das 19. Jahrhundert und Große Themen der Geschichte Preußens. Berlin/New York: Walter de Gruyter, pp. 605–789. Oates, W.E., 1972. Fiscal Federalism, New York: Harcourt Brace. Schmitt, B., 2013. Der polnische Adel in den Armen Preußens und der Habsburgermonarchie. Inklusion und Exklusion neuer Untertanen im Militär. In H.-J. Bömelburg, A. Gestrich, & H. Schnabel-Schüle, eds. Die Teilungen Polen-Litauens. Inklusions- und Exklusionsmechanismen – Traditionsbildung – Vergleichsebenen. Osnabrück: fibre Verlag, pp. 359–376. Stichnoth, H. & Van der Straeten, K., 2013. Ethnic diversity, public spending, and individual support for the welfare state: A review of the empirical literature. Journal of Economic Surveys, 00(0), pp.1–26. Struve, R., 2013. Die Institutionalisierung des Justizwesens in den Preußischen Teilungsgebieten Süd- und Neuostpreußen. In H.-J. Bömelburg, A. Gestrich, & H. Schnabel-Schüle, eds. Die Teilungen Polen-Litauens. Inklusions- und Exklusionsmechanismen – Traditionsbildung – Vergleichsebenen. Osnabrück: fibre Verlag, pp. 321–358. Unruh, G.-C. von, 1992a. Provinz (Großherzogtum) Posen. In G. Heinrich, F.-W. Henning, & K. G. A. Jeserich, eds. Verwaltungsgeschichte Ostdeutschlands 1815-1945. Organisation - Aufgaben - Leistungen der Verwaltung. Stuttgart/Berlin/Köln: Verlag W. Kohlhammer, pp. 366–474. Unruh, G.-C. von, 1992b. Provinz Pommern. In G. Heinrich, F.-W. Henning, & K. G. A. Jeserich, eds. Verwaltungsgeschichte Ostdeutschlands 1815-1945. Organisation - Aufgaben - Leistungen der Verwaltung. Stuttgart/Berlin/Köln: Verlag W. Kohlhammer, pp. 592–678. Willis, E., Garman, C.C.B. & Haggard, S., 1999. The Politics of Decentralization in Latin America. Latin American Research Review, 34(1), pp.7–56. Wünsch, T., 2008. Deutsche und Slawen im Mittelalter: Beziehungen zu Tschechen, Polen, Südslawen und Russen, Zbroschzyk, M., 2014. Die preußische Peuplierungspolitik in den rheinischen Territorien Kleve, Geldern und Moers im Spannungsfeld von Theorie und räumlicher Umsetzung im 17. – 18. Jahrhundert. Zernack, K., 2008. The Middle Ages. In C. W. Ingrao & F. A. J. Szabo, eds. The Germans and the East. West Lafayette: Purdue University Press, pp. 9–15.

30 Figure 1: Share state subventions

The mean of share state expenditures denotes state grants and state funds among total expenditures for primary education for the Prussian Empire east of the Elbe between 1886 and 1911. Sources: (Königliches Statistisches Bureau in Berlin 1889; Königliches Statistisches Bureau in Berlin 1893; Königliches Statistisches Bureau in Berlin 1898; Königliches Statistisches Bureau in Berlin 1903; Königliches Statistisches Bureau in Berlin 1908).

31 Table 1: Funding Sources in Six Eastern Provinces Branden- Posen Prussia Silesia Pomerania Saxony burg Tuition fee 0.32 3.06 11.73 15.47 24.14 19.29 Foundation 4.86 8.63 7.02 13.15 24.73 12.75 Society 61.92 21.67 15.08 18.44 8.38 9.31 Patronage 5.67 25.27 32.17 15.53 15.21 23.98 Municipality 4.34 23.37 22.97 17.99 19.18 25.55 Other 1.3 0.47 0.96 0.48 0.11 0.34 State 21.56 17.52 10.06 18.93 8.25 8.88 Local spending p. child 10.02 12.00 12.84 14.09 14.79 15.64 Polarization 0.72 0.47 0.22 0.03 0.00 0.07 Obs. 27 57 63 29 4 34 The grey shaded cells denote the source of funding contributing the highest share of spending. The bold cells denote the source of funding with the second highest share of spending.

32 Table 2: Descriptive Statistics Variable Mean Std. Dev. Min Max Log local school spending per child 2.524 0.249 2.047 3.612 Share teacher wages 0.632 0.070 0.339 0.778 Share infrastructure expenditures 0.219 0.033 0.124 0.400 Linguistic polarization 0.294 0.370 0 1 German share 0.754 0.336 0.058 1 Polish share 0.224 0.336 0 0.942 Lithuanian share 0.012 0.070 0 0.623 Wendish share 0.008 0.055 0 0.520 Slavic share 0.003 0.025 0 0.326 Other share 0.000 0.002 0 0.027 Protestants 1885 0.684 0.342 0.023 0.995 Log municipal tax per capita 1.017 0.539 -0.128 2.924 Urbanization rate 25.513 18.847 0.000 100.00 Population density 3.523 17.762 0.290 207.59 Fraction in manufacturing 9.555 5.061 2.166 27.069 Land inequality 0.686 1.009 -0.911 6.639 Time under Prussian rule 196.05 110.34 71 361 School density 6.642 2.214 0.396 11.466 Children per teacher 95.308 14.819 61.082 142.25 Student-teacher ratio 78.103 12.824 49.032 121.18 Teacher unit costs 6.546 0.260 5.936 7.422 The number of observation denotes 214 counties.

33

Map 1: Linguistic polarization across Prussia, 1886

34 Map 2: Geography of annexations

Margraviate of Brandenburg Silesia (1763) Duchy of Prussia First Partition of Poland (1772) Magdeburg (1541) Second and Third Partition of Poland (1793 and 1795) Eastern Pomerania (1648) Congress of Vienna (1815) Western Pomerania (1720)

35

Table 3: Polarization and School Spending Dep. Var.: Exp. (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) Ling. polarization -0.334*** -0.270*** -0.318*** -0.312*** -0.243*** -0.313*** -0.316*** -0.303*** -0.233*** -0.189*** -0.173*** (0.069) (0.058) (0.062) (0.093) (0.063) (0.065) (0.059) (0.038) (0.056) (0.052) (0.053) Protestant (share) 0.147** 0.138** 0.132* (0.062) (0.055) (0.069) Relig. fractionaliz. -0.072 -0.064 -0.089 -0.064 (0.087) (0.149) (0.059) (0.058) Ling. polar. x -0.024 Religious fract. (0.274) Polish (share) -0.163** 0.040 0.051 (0.062) (0.064) (0.070) Pop. density (per 0.006*** 0.002** 0.002** ha) (0.001) (0.001) (0.001) Years under 0.000 Prussian rule (0.000) Log tax p.c. (1884) 0.260*** 0.155*** 0.158*** (0.042) (0.039) (0.047) Urban (share) 0.007*** 0.004*** 0.005** (0.001) (0.001) (0.002) Large -0.003 -0.002 0.001 landownership (0.014) (0.014) (0.013) Sh. emp. in 0.002 0.009 0.009 agriculture (0.004) (0.006) (0.006) Sh. emp. in 0.009 0.011 0.011 manufacturing (0.005) (0.006) (0.009) Province FE No No No No No No No No No No Yes Observations 214 214 214 214 214 214 214 214 214 214 214 R-squared 0.2 0.3 0.2 0.2 0.3 0.4 0.3 0.6 0.6 0.7 0.7 * p<0.10, ** p<0.05, *** p<0.01. Robust standard errors in parentheses. Protestant (share) denotes the share of Protestants in 1885. Relig. fractionaliz. is the religious fractionalization index of 1871, constructed of five religious groups, namely, Protestants, Catholics, other Christians, Jews, and other religion. Polish (share) is the share of Polish-speaking students in 1886. Log tax p.c. (1884) denotes the log municipal tax per capita for the year 1883/1884. Urban (share) is the fraction of people living in cities in 1871. Large landownership denotes the standardized landownership concentration. Sh. emp. in agriculture denotes the share of people employed in agriculture in 1882. Sh. emp. in manufacturing denotes the share of people employed in manufacturing in 1882. Province FE denotes the province fixed effects.

36 Table 4: First Stage Dep. Var.: Linguistic Polarization (1) Protestant (share) -0.126 (0.117) Log tax p. c. (1884) 0.130** (0.060) Urban (share) -0.003** (0.001) Pop. density (per ha) 0.000 (0.001) Sh. emp. in manufacturing -0.010** (0.004) Large landownership -0.043** (0.020) Years under Prussian rule 0.000 (0.001) Log distance to eastern border -0.091** (0.041) Log distance x Margraviate -0.043 Brandenburg (0.052) Log distance x Duchy of Prussia -0.023 (0.062) Log distance x Farther Pomerania -0.046** (0.022) Log distance x Magdeburg -0.038 (0.028) Log distance x Western Pomerania -0.043* (0.022) Log distance x Silesia -0.056*** (0.021) Log distance x 1st Partition of 0.029 Poland (0.024) Log distance x 2nd Partition of 0.045* Poland (0.023) Observations 214 R-squared 0.6 * p<0.10, ** p<0.05, *** p<0.01. Robust standard errors in parentheses.

37 Table 5: Instrumental Variable Approach Dep. Var.: Log local school spending per child (1) OLS (2) IV (3) IV (4) IV (5) IV (6) IV (7) IV (8) IV Ling. polarization -0.208*** -0.319*** -0.295*** -0.267*** -0.288*** -0.298*** -0.364*** -0.395*** (0.045) (0.069) (0.064) (0.078) (0.065) (0.076) (0.091) (0.092) Protestant (share) 0.156*** 0.108** 0.089* 0.118** 0.098** 0.082 0.082 0.165*** (0.051) (0.049) (0.050) (0.048) (0.048) (0.054) (0.055) (0.048) Log municipal tax p.c. (1884) 0.152*** 0.170*** 0.188*** 0.181*** 0.180*** 0.160*** 0.162*** 0.188*** (0.030) (0.028) (0.028) (0.027) (0.028) (0.028) (0.036) (0.031) Urban (share) 0.003* 0.002** 0.002* 0.001 0.002* 0.001 0.001 0.002** (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) Pop. density (per ha) 0.002** 0.002*** 0.002*** 0.002*** 0.002*** 0.003*** 0.003*** 0.002*** (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) Sh. emp. in manufacturing 0.003 -0.000 -0.001 0.002 -0.000 0.005 0.004 -0.000 (0.003) (0.004) (0.004) (0.004) (0.003) (0.004) (0.004) (0.004) Large landownership -0.008 -0.010 -0.005 -0.003 -0.005 -0.006 -0.014 -0.011 (0.011) (0.011) (0.012) (0.012) (0.012) (0.013) (0.013) (0.011) Years under Prussian rule -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 0.000 -0.000* (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) Latitude (radius) 0.002 0.011 0.025 (0.007) (0.008) (0.017) Longitude (radius) -0.008** -0.022** -0.037*** (0.003) (0.011) (0.013) Dummy border county 0.053 0.005 0.028 (0.036) (0.038) (0.042) Terrain slope 0.007 0.029 0.050 (0.029) (0.033) (0.034) Temperature 0.002 0.004 0.008*** (0.002) (0.003) (0.003) Precipitation -0.000 -0.001** -0.001* (0.000) (0.000) (0.000) Distance prov. capital 0.000 0.000 0.001 (0.000) (0.000) (0.000) Distance to Berlin -0.000 0.001*** 0.001** (0.000) (0.000) (0.000) Polish (share) 0.130** (0.065) Province FE No No No No No No Yes No Observations 214 214 214 214 214 214 214 214 Kleibergen-Paap rk Wald F statistic 10.2 15.8 6.411.8 9.1 6.0 5.7 * p<0.10, ** p<0.05, *** p<0.01. Robust standard errors in parentheses. Distance to Berlin is the distance between the centroid of the county and Berlin. Longitude, latitude, and slope are constructed using ArcGIS. Temperature and precipitation are contemporary values. 37

Table 6: Beyond the County Level Ordinary Least Squares Instrumental Variables Approach County-Level Pooled Urban Rural County-Level Pooled Urban Rural (1) (2) (3) (4) (5) (6) (7) (8) Ling. polarization -0.226*** -0.193*** -0.388*** -0.188*** -0.328*** -0.359*** -0.937*** -0.212*** (0.035) (0.031) (0.072) (0.035) (0.053) (0.058) (0.146) (0.055) Protestant (share) 0.111*** 0.150*** -0.268*** 0.193*** 0.061 0.074* -0.694*** 0.183*** (0.035) (0.035) (0.090) (0.038) (0.042) (0.045) (0.166) (0.039) Log municipal tax p.c. (1884) 0.168*** 0.160*** 0.027 0.163*** 0.173*** 0.160*** 0.053 0.164*** (0.025) (0.024) (0.050) (0.024) (0.025) (0.024) (0.052) (0.024) Urban (share) 0.004*** 0.232*** 0.004*** 0.222*** (0.001) (0.031) (0.001) (0.032) Observations 214 408 203 205 214 408 203 205 R-squared 0.6 0.6 0.1 0.5 Kleibergen-Paap rk Wald F statistic 14.4 16.0 22.3 11.2 * p<0.10, ** p<0.05, *** p<0.01. Robust standard errors in parentheses. The average of linguistic polarization in the pooled sample is 0.27 (s. dev. 0.36), 0.27 (s. dev. 0.38) in the urban sample, and 0.28 (s. dev. 0.36) in the rural sample. The average log local expenditures per child are 2.51 (s. dev. 0.31) in the pooled sample, 2.76 (s. dev. 0.35) in the urban sample, and 2.41 (s. dev. 0.22) in the rural sample. The observations in the pooled sample are weighted by the respective urban share of each county.

38

Table 7: Robustness Checks (1) (2) (3) (4)(5) (6) (7) Ling. polarization -0.302*** -0.261*** -0.313*** -0.364*** -0.317*** -0.319*** -0.308*** (0.068) (0.074) (0.068) (0.088) (0.069) (0.073) (0.102) Protestant (share) 0.114** 0.112** 0.114** 0.147*** 0.111** 0.107** 0.169*** (0.047) (0.046) (0.049) (0.049) (0.055) (0.049) (0.061) Log municipal tax p.c. (1884) 0.164*** 0.162*** 0.166*** 0.181*** 0.170*** 0.170*** 0.170*** (0.028) (0.027) (0.028) (0.030) (0.028) (0.034) (0.038) Urban (share) 0.002** 0.003*** 0.002* 0.002** 0.002** 0.002** 0.002* (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) Population density (per ha) 0.002*** 0.002*** 0.002*** 0.002*** 0.002*** 0.002*** 0.002*** (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) Emp. in manufacturing (share) -0.004 -0.002 0.000 -0.000 -0.000 -0.000 -0.004 (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) Large landownership -0.013 0.001 -0.011 -0.010 -0.010 -0.010 -0.005 (0.011) (0.012) (0.011) (0.011) (0.011) (0.011) (0.012) Years under Prussian rule -0.000 -0.000 -0.000 -0.000* -0.000 -0.000 -0.000 (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) Log state exp. in educ. (per child) -0.097** -0.075* (0.039) (0.042) Average household size -0.098*** -0.074* (0.036) (0.041) Perc. military population 0.008 0.004 (0.008) (0.008) German minority (dummy) 0.069 0.069 (0.047) (0.051) Share school inspectors 0.003 0.008 (0.031) (0.032) Schooling societies (share) -0.002 0.017 (0.071) (0.075) Observations 214 214 214 214214 214 214 Kleibergen-Paap rk Wald F statistic 10.2 10.1 9.7 6.1 9.4 9.5 4.8 * p<0.10, ** p<0.05, *** p<0.01. Robust standard errors in parentheses. Log state exp. in educ. (per child) denote school funding, collected by the state. Average household size of 1871. Perc. military population denotes the share of military personnel among the total county population. German minority is a dummy variable taking the value 1 if the share of Germans is below 50 percent. School inspectors denote the share of secular school inspectors among all county school inspectors. Controls include the share Protestants in 1885, the log of municipal taxes per capita in 1883/1884, the percentage of the urban population in 1871, the population density in 1885, the share employed in manufacturing in 1882, and the standardized landownership concentration.

39

Table 8: Alternative Public Goods INFRASTRUCTURE POOR RELIEF OLS IV OLS IV (1) (2) (3) (4) (5) (6) Ling. polarization -0.491*** -0.076 -0.334 0.252 0.300 0.799*** (0.142) (0.086) (0.228) (0.185) (0.241) (0.259) Protestant (share) 0.571*** 0.458*** -0.038 0.180 (0.165) (0.157) (0.268) (0.208) Log municipal taxes p.c. (1884) 0.553*** 0.595***0.354** 0.272** (0.124) (0.101) (0.122) (0.119) Urban (share) 0.016*** 0.015*** 0.009* 0.010*** (0.004) (0.003) (0.005) (0.003) Population density (per ha) -0.002 -0.002 -0.004 -0.004** (0.002) (0.002) (0.003) (0.002) Emp. in manufacturing (share) -0.000 -0.008 -0.013 0.002 (0.019) (0.014) (0.017) (0.013) Large landownership -0.145** -0.150*** 0.130 0.139*** (0.052) (0.042) (0.078) (0.048) Years under Prussian rule -0.001* -0.001** 0.000 0.001 (0.000) (0.000) (0.001) (0.001) Observations 214 214 214 214 214 214 R-squared 0.1 0.6 0.0 0.2 Kleibergen-Paap rk Wald F statistic 10.2 10.2 * p<0.10, ** p<0.05, *** p<0.01. Robust standard errors in parentheses.

40

Table 9: Distributional Effects (1) School per child (2) School per child (3) Children per teacher (4) Student per teacher (5) Log unit teacher wage w/o city counties Ling. polarization -2.025*** -1.864*** 26.560*** 14.504*** -0.311*** (0.548) (0.594) (5.065) (3.530) (0.066) Protestant (share) 2.469*** 2.303*** -11.736*** -10.550*** 0.039 (0.369) (0.362) (3.367) (2.405) (0.050) Log municipal tax p.c. (1884) 0.313 0.344 -12.681*** -11.377*** 0.109*** (0.283) (0.276) (2.508) (1.867) (0.029) Urban (share) -0.045*** -0.019* 0.113* -0.167*** 0.001* (0.009) (0.010) (0.065) (0.047) (0.001) Population density (per ha) -0.008 -0.121 -0.020 0.006 0.001** (0.007) (0.184) (0.063) (0.033) (0.001) Emp. in manufacturing (share) -0.215*** -0.210*** 1.586*** 1.300*** 0.019*** (0.031) (0.044) (0.308) (0.213) (0.003) Large landownership 0.150 0.134 -0.038 -1.044 -0.015 (0.134) (0.124) (0.946) (0.692) (0.011) Years under Prussian rule -0.003** -0.002* 0.018** 0.006 -0.000* (0.001) (0.001) (0.009) (0.007) (0.000) Observations 214 205 214 214 214 Kleibergen-Paap rk Wald F statistic 10.2 11.7 10.2 10.2 10.2 * p<0.10, ** p<0.05, *** p<0.01. Robust standard errors in parentheses. The average number of schools per children of mandatory school age is 6.65 (std. dev. 2.21). The average number of children per teacher is 95 (std. dev. 15). The average student-teacher ratio is 78 (std. dev. 13). The average unit teacher wage is 6.54 (std. dev. 0.26).

41