Abstract
We study the Black Death pogroms to shed light on the factors determining when a minority group will face persecution. Negative shocks increase the likelihood that minorities are persecuted. But, as shocks become more severe, the persecution probability decreases if there are economic complementarities between majority and minority groups. The effects of shocks on persecutions are thus ambiguous. We compile city-level data on Black Death mortality and Jewish persecutions. At an aggregate level, scapegoating increases the probability of a persecution. However, cities which experienced higher plague mortality were less likely to persecute. Furthermore, for a given mortality shock, persecutions were more likely where people were more inclined to believe conspiracy theories that blamed the Jews for the plague and less likely where Jews played an important economic role.
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Notes
Many minority groups across the world still suffer violent persecutions today, with some recent examples of ethnic and religious cleaning in the Central African Republic, Myanmar, South Sudan, Sudan, Sri Lanka, and Syria.
Jha (2018) models the conditions under which trade can support peaceful coexistence between groups and those under which groups will be subject to violence.
In the medium- and long-run, wages increased due to greater labor scarcity. But the immediate economic impact of the plague was negative (Campbell 2016).
5% for “spared” or “escaped”, 10% for “partially spared” or “minimal”, 20% for “low”, 25% for “moderate”, 50% for “high”, 66% for “highly depopulated”, and 80% if the town is “close to being depopulated” or “decimated”.
For example, for Landshut in Germany we learn from Benedictow (2005, 190) that the epidemic went from Mühldorf to the neighboring town of Landshut (50 km). From Christakos et al. (2005), we know that Mühldorf and Regensburg were first infected in June and July 1349, respectively. Since Landshut is about one-half of the way between Mühldorf and Regensburg, it must have been infected in June or July 1349, but most probably in June 1349.
We use 10 km for the coast and river dummies and some controls described below, due to measurement error.
See Benedictow (2005, 2010). The importance of blocked fleas as the main vector of transmission is currently under debate. Other vectors such as lice may also have been at work. The literature agrees, however, that person-to-person transmission was probably rare and cannot account for the diffusion of the plague (Campbell 2016, 235).
According to Berngruber et al. (2013): “[...] selection for pathogen virulence and horizontal transmission is highest at the onset of an epidemic but decreases thereafter, as the epidemic depletes the pool of susceptible hosts [...] In the early stage of an epidemic susceptible hosts are abundant and virulent pathogens that invest more into horizontal transmission should win the competition. Later on, the spread of the infection reduces the pool of susceptible hosts and may reverse the selection on virulence. This may favor benign pathogens [...].”
Variation in sanitation does not explain this pattern. Gottfried (1983, 69) notes “it would be a mistake to attribute too much to sanitation” given the “failure of Venice’s excellent sanitation to stem the deadly effect of the plague”.
In addition, Web Appendix Table A.2 (see Web Appendix Section 9.) shows that there is no correlation when market access is computed using a lower elasticity than 3.8, whether 2 or 1, in particular to reflect the fact that only luxury goods tended to be traded over longer distances in the medieval period, or when relying on Euclidean distance instead of network distance since the speed parameters used for the four transportation modes could also be misestimated.
Dittmar and Meisenzahl (2018) use plague reoccurrences as an instrument for local shocks to the political economy of cities in Germany during the Reformation.
The outbreak of the plague in northern Italy in 1630 was unusually severe as is studied by Alfani (2013).
The term quarantine was first used in Ragusa, part of the Venetian empire in 1377 Gensini et al. (2004, 257).
Historians observe that “rulers concerned with attracting Jews offered promises of security and economic opportunity to Jewish settlers” (Chazan 2010, 103). This also appears in many entries of the Encyclopedia Judaica.
It was only years later that the labor shortage effect emphasized by Pamuk (2007) and Voigtländer and Voth (2013) was realized in rising wages. In addition, property rights were feudal and, as such, most property was owned by elites. While the Black Death did improve the bargaining position of peasants (e.g. Haddock and Kiesling 2002; Acemoglu and Robinson 2012), it took decades for contractual obligations to be renegotiated.
One town with a mortality rate of 0% did not persecute its community. However, since we use a bandwidth of 5% points of mortality for the local polynomial smooth plot, the mean persecution rate at the origin is 0.4.
Our finding is entirely consistent with that of Voigtländer and Voth (2012) who find that antisemitic attitudes can persist over centuries. Our results simply suggest that the direct “protective effect” of Black Death mortality on the likelihood of a persecution had dissipated several decades after the shock itself.
The \(R^{2}\) terms are not exactly equal to 0 when studying the correlation between mortality and trade and human capital (see (2), 0.12) or institutions (see (3), 0.15). This is because some of the variables are also correlated with latitude and longitude. For example, Roman roads were more dense in the South.
See Web Appendix Table A.3 and Web Appendix Section 9). This result holds even if we drop the 10 post-1352 periods since there were plague reoccurrences after the Black Death and consistent data does not exist on the specific mortality rate associated with each reoccurrence.
For example, in Marseille, the mortality rate of the Jewish population was 50% during the Black Death versus 55% for the whole city (Sibon 2011). In Avignon, it is reported that “the Jewish population was extremely hard hit by the plague” (Deaux 1957, 103–104). The argument that the Jewish practice of ritual bathing would lead to lower mortality rates is not well grounded as ritual baths often used stagnant water (see van Straten 2007, 47) and, contrary to common mythology, bathing was common among the Christian populations of medieval Europe.
For town i, and other towns j\(\in \)J (363 towns with a Jewish community circa 1347) or j\(\in \)A (all 1869 towns), the Jewish centrality index is equal to \(\sum _{j \in J} D_{ij}^{-\sigma } \div \sum _{j \in A} D_{ij}^{-\sigma } * 100\) with \(D_{ij}\) the travel time between city i and city j. If all surrounding towns have a Jewish community, it will be close to 100, and 0 otherwise.
We do not know how many Jews were persecuted in other towns. However, the fact that we could not find the number of victims for these other persecutions suggests that the numbers were not as high as for the 8 towns dropped as persecutions involving more victims should have been better documented than persecutions with fewer victims.
Note that we log market access because it is not bounded whereas mortality and persecution probability are.
Note that the correlation between the two market access measures is indeed lower than 1, at 0.51, since Northern European towns also had access to large towns other than Messina.
The correlation between log market access to Messina and log market access to Genoa is lower than 1, at 0.69.
We also use \(\sigma =3.8\) (from Donaldson (2018)), which implies a high cost of distance on trade.
Results also hold if market access to all towns exclude Messina (Web Appendix Table A.7A.9).
Web Appendix Table A.8 shows that this IV is not correlated with town population growth in 1200–1300.
Results hold if we use network distances instead of Euclidean distances (results available upon request).
We create a two-dimensional surface of predicted plague mortality using an inverse distance weighted function of known mortality rates for the full sample of 263 towns with mortality data. For every point on the surface a predicted mortality rate is then generated using the closest 15 cities within an approximately 1000 km radius circle around the point. Details can be found in Web Appendix Section 5 (map of extrapolated mortality rates shown in Web Appendix. Fig. A.3).
One problem here is that several towns now use the same provincial estimate [e.g., Aragon (7 towns) and Bohemia (5)]. Our results are then robust to dropping towns located within different modern country borders (Web Appx. Table A.13): France, Germany, Italy, Portugal and Spain. Other countries only contribute 7 towns or fewer.
The 12 towns include 8 French towns for which information is sparse following the expulsions of 1306–1322, and 3 Tuscan towns in which Jews settled in the fourteenth century, but for which we cannot be sure of the year. The 20 towns include towns for which sources mentioned a persecution, but without providing corroborating details about it.
Web Appendix Table A.5 shows results hold if we restrict the sample to towns where the community was likely to be large enough for the plague not to annihilate the community, i.e. towns with a Jewish synagogue/quarter/cemetery or towns where Jews have been living for a long time.
In Ulm we are told that on Jan. 30, 1349, a mob “stormed” the Jewish quarter; in Magdeburg, the “citizens and peasants of the vicinity fell upon the Judendorf, pillaged it, and burned many Jews in their houses”.
In the eleventh century the Bishop of Speyer argued that “the glory of our town would be augmented a thousandfold if I were to bring Jews” (quoted in Chazan 2010, 101). Similarly, peasants in Tuscany petitioned for the admission of Jewish lenders to make credit more abundant (Botticini 2000). Rowan observes that “Mass demonstrations against Jews tended to be feared by patrician governments, since the Jews were still useful to them. The destruction of the Jews would have meant the loss of a major source of tax money which would have had to be made up by increasing the burden on some other social group” (Rowan 1984, 23).
We do not view this as incompatible with the argument of Cohn (2007) that elites often preempted or organized massacres of Jews. Given popular anger against the Jews, there were strong incentives for local authorities to take control and to organize the massacres (either to control them or perhaps to ensure they did not lead to wider social disorder).
Jews returned to Nuremberg soon after the plague persecutions (Berenbaum et al. 2007b). In Aragon, where the impact of the plague was severe, King Pedro strove to protect the Jews and in the wake of the plague “was determined to restore the Jewish aljamas to a healthy economic state”. He barred creditors from bringing lawsuits against Jews or collecting debts against them for a year while individuals who moved into settle land left empty due to the mortality associated with the plague were forced to inherit the debts owed to the Jews (Shirk 1981, 363).
Web Appendix Table A.18 shows that the interacted effects logically decrease when using higher percentiles, whether 15, 20, 25 or 50% (see Web Appendix Section 13). Interacted effects are thus larger the closer to the studied characteristic.
Historians have traditionally held the flagellants responsible for massacring Jews. Yet, we find no evidence that the path of the flagellant movement was associated with the mortality-persecution relationship (see Web Appx. Table A.14). We find, however, that the protective effect was accentuated very close to Narbonne (i.e., for towns in the bottom 5% of the Euclidean distance to it). There “beggars and mendicants”, and not Jews, were accused of having poisoned the wells, which could explain the lower effect of mortality on persecution probability (see Web Appx. Table A.14).
We do not find the same effects when considering older entries (see Web Appendix Table A.14).
The existence of a Jewish quarter meant that Jews were separated from Christians. This may have prevented non-Jews from seeing that Jews were also dying. However, it might also have simply reflected the larger size of a community.
There is no existing data on the layout of towns back then, so we do not know the location of the quarter relative to the main areas of the town then. The only other characteristic for which we have data is walled density (N = 56), but we find no differential effect across towns above and below median density (see Web Appendix Table A.14).
Schwarzfuchs (2007, 311) writes: “The sight of the wealthy Rhenish communities acted as an incentive to the crusaders, who decided to punish ‘the murderers of Christ’ wherever they passed”.
We find similar results if we use the main path of the First Crusade instead (see Web Appendix Table A.14). However, we do not find any effect if we use the places most associated with the main leaders of the First Crusade (ditto). The null effect is unsurprising since these are the locations from where the First Crusade was initially called for and organized and many Crusader leaders were not involved in pogroms which often involved local people. We also collected data on the pogroms that took place during the Crusades of 1147 and 1189 but the later Crusades were not characterized by large-scale antisemitic violence (Stacey 1999.).
Stacey (1998, 13) writes: “we begin to see Jews taking on a new role, as enemies not only of the body of Christ on the cross and of the body of Christ in the Church, but also as the enemies of the body of Christ in the eucharist. This is the notion that lies behind the host desecration charge—that Jews would torture [...] consecrated eucharistic hosts”.
The non-significant results for ritual murders in the first half of the fourteenth century and for host desecration in the thirteenth century are shown in Web Appendix Table A.14.
Archer observes that “At a period in which the individual child was not looked upon with particular tenderness, parental sentiment found a communal channel in the idolization of the Christ child and of the Innocents, the baby boys butchered in the first attempt to kill Jesus by Herod, the Jewish King” (Archer 1984, 47).
This was the case in Trier where Jews gave six pounds of pepper and silks for his clothing to the archbishop and two pounds of pepper to the chamberlain. In Öttingen, each Jew over the age of twelve had to pay a gulden to the emperor on Christmas day (Adler and Singer 1906).
A favorite Easter sermon from St. Augustine provided a fictitious antisemitic account of Jesus’s death: “The Jews held him; the Jews insulted him; the Jews bound him; they crowned him with thorns, dishonored him by spitting on him; they scourged him; they heaped abuse on him ...” (Freudmann 1994, 300). Just as hostility to Jews at Christmas-time manifested itself with the association of Jews with Herod, so at Easter they were closely associated with Judas.
In Toulouse there was a tradition whereby the Jewish community had to choose a member of the community every year to be publicly slapped in the face on Good Friday. In the middle ages this ritual was waived on the condition that the Jews pay a special fee to the town (Blumenkranz et al. 2007).
The tensions around the month of April were further heightened by the fact that Passover typically coincides with Easter and Jews were accused of ritually murdering and sacrificing Christian children as part of this festival (Rubin 2004). Numerous studies suggest that this was a factor during the Black Death. The Jewish community of Toulon were massacred on 12–13 April 1348, at the same time as the plague reached the city (Cremieux 1930).
We investigate the effect for each month individually, by regressing the persecution dummy on the mortality rate, 12 month of infection dummies, and the 12 interactions of these dummies with the mortality rate. We then test whether the effect of each month is significantly different from our baseline effect of − 0.009. Web Appendix Figure A.7 (see Web Appendix Section 13) confirms that the protective effect of mortality was accentuated in February, March and December, and attenuated in January, May (significant at 15%) and October. There is no clear effect for April now (Easter took place in late April in 1348).
In ancien regime France, the passage of time was defined by “agro-liturgical calendars” (Moriceau 2010). These calendars provide information about the agricultural cycles of the medieval period. The agricultural cycle depends on whether one considers a town in the North or the South of Europe. In our sample, the mean latitude and longitude are 45.7 and 6.0, close to Chambéry. In France, December and February were “idle” months, January was the month fields had to be plowed for the spring sowing, March–April and October were the months of planting, April–May were the “lean” months, and July and October were the months of grain and grape harvesting.
Ramirez (2010, 64) writes for the region of Savoy in which Chambéry is located (translated): “Most of the loans [given by Jews] take place in the Spring and the Fall [...] during the planting season and during the lean season.”
In Web Appendix Table A.19, we show how the protective effect decreases as the large kingdom dummy progressively excludes more smaller kingdoms.
Nevertheless, as we showed above, conditional on Jews lending money to non-Jews, they were more likely to be persecuted when the arrival of the plague coincided with the period when their debts were due to be repaid.
This is unsurprising as the literature agrees that the importance of Jewish merchants had waned by the fourteenth century. Roth (1961) argues that guilds pushed Jews out of trade and manufacturing into moneylending. However, Botticini and Eckstein (2012, 238) argue that guilds cannot explain the shift towards moneylending because by the time they became powerful: “the Jews in western Europe had entered and then become specialized and prominent in moneylending for at least two centuries”. Instead Botticini and Eckstein (2012) argue that Jews shifted away from trade due to their comparative advantage in moneylending. For our purposes the cause of this shift is irrelevant.
This hypothesis is advanced in Stein (2007, 442) who notes that the First Crusade had a major “impact on the status and livelihood of the Jews in France, Germany, and England drove them out of trade through the lack of security arising from the inimical attitude of society in general”.
Note that since the First Crusade pogroms reduced the protective effect of mortality (see row 10 of Table 8), not simultaneously controlling for the interaction of the first crusade and mortality should, if anything, make us under-estimate the protective effect of moneylending.
Florence was the most important financial center in fourteenth century Europe (de Roover 1963). Genoa, Milan, Sienna and Venice were also important financial and banking centers (Mueller 1997). Cahors in southern France was a city known for its Christian moneylenders (Noonan 1957). Cahorsins are explicitly mentioned alongside “Lombards” (Milan is the capital of Lombardy) as direct substitutes for Jewish lenders (see, e.g. the entry for “Switzerland”’ in the Encyclopedia Judaica). Dorin (2013, 2016) discusses the extent to which the decision to expel Jews were intertwined with attitudes to Christian usury.
While we directly control for the individual effect of financial centers on persecution, the interacted effect could nonetheless be endogenous. However, as we discuss in Web Appendix Section 13, the prominence of Christian moneylenders or banks in these cities reflects long-standing historical factors specific to each city, and hence is less likely to be endogenous than is the location of Jewish moneylending.
The Jewish Encyclopedia notes that while Jews were mostly concentrated in moneylending after 1200, they could be found involved in trade in cities like Marseille and cities in Castile and Portugal where they continued to engage in commerce with the Muslims states of North Africa (Gottheil et al. 1906).
Jew merchants, for instance, frequented the fairs of Cologne, Frankfurt, and Friedberg (Reviv et al. 2007, 82).
Periods: 1100–1200, 1200–1300, 1300–1400, 1400–1500, 1500–1600, 1600–1700, 1700–1750, 1750–1800 and 1800–1850.
Note that mortality is not a valid instrument for persecutions since it may affect future city growth.
Specifically, it is comparable to a 1/3 improvement in potato suitability. In a separate paper, Johnson and Koyama (2017) use several identification strategies to further investigate the role of Jews in European city growth in 1400–1850, and find similar growth effects of 30% per century.
Web Appendix Table A.20 shows baseline results hold if we use: (i) two lags of log population, to control for past growth trends, (ii) drop towns not in the Bairoch sample; and (iii) do not replace by 500 inhabitants the population of the towns with a missing population, presumably because they were below the 1000 threshold used by Bairoch.
Of course it is also possible that persecutions had institutional effects beyond the effects on Jewish community size, so we are cautious in interpreting these results.
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We are grateful to the editor, three anonymous referees, and Daron Acemoglu, Guido Alfani, Sascha Becker, Michael Bordo, Quoc-Anh Do, Rowan Dorin, Jose-Antonio Espin-Sanchez, James Fenske, Raphael Franck, Jonathan Hersh, Francisco Gallego, Saumitra Jha, Naomi Lamoreaux, Moses Shayo, Oliver Vanden-Eynde, Joachim Voth, Ekaterina Zhuravskaya, and seminar audiences at American, ASREC, Ben Gurion, Chapman, CIREQ Conference (Université de Montréal), the EHA Meetings (Montreal), the EHS Meetings (Royal Holloway), Florida State, George Mason, George Washington, Hebrew, Hitsubashi, Pontificia Universidad Católica de Chile, Rosario, Rutgers, Sciences Po, the SEA Meetings (Washington D.C.), Sussex, the Washington Area Economic History Workshop (George Mason), the Washington Area Development Economics Symposium (George Mason) and Yale. We gratefully acknowledge the support of the Institute for International Economic Policy at George Washington University and the Mercatus Center at George Mason University.
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Jedwab, R., Johnson, N.D. & Koyama, M. Negative shocks and mass persecutions: evidence from the Black Death. J Econ Growth 24, 345–395 (2019). https://doi.org/10.1007/s10887-019-09167-1
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DOI: https://doi.org/10.1007/s10887-019-09167-1
Keywords
- Economics of mass killings
- Inter-group conflict
- Minorities
- Persecutions
- Scapegoating
- Biases
- Conspiracy theories
- Complementarities
- Pandemics
- cities