ideological entrepreneurs and the diffusion of radical …ideological entrepreneurs and the...
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Ideological Entrepreneurs and the Diffusion of Radical Innovation Martin Luther’s Personal Ties and the Spread of the Early Reformation*
Sascha O. Becker
Monash University
Steven Pfaff
University of Washington
Yuan Hsiao
University of Washington
Jared Rubin
Chapman University
9 August 2019
Abstract
What makes societies adopt radically new institutions and ideas, especially when
they are likely to face (often violent) resistance? Is there room for ideological
entrepreneurs in this process? We address these questions in the context of Martin
Luther’s effect on the early spread of the Reformation, one of the most important
religious, political, and economic events of the last millennium. We employ
multiple newly-digitized panel datasets: the universe of known letters Luther sent
in his early career, the towns he visited, and the locations of publication of Luther’s
works. We use these data to construct a network of Luther’s pre-Reformation
contacts. Comparisons to trade networks indicate that towns in which he had ties
were significantly more likely to adopt the Reformation in its early “bottom-up”
stages.
JEL codes: D85, N34, Z12, N44, C81
Keywords: Martin Luther, Reformation, networks, diffusion, social movements
* We thank Robert Barro, Benjamin Elsner, Sean Everton, Rachel McCleary, James Moody, Kevin O’Rourke,
Alejandra Ramos, Mara Squicciarini, Guido Tabellini, Noam Yuchtman, and participants in workshops at Bocconi
University, Trinity College Dublin, Warwick University, the 2019 ASREC Conference, the 2019 Symposium on
Quantitative History (Yantai), and the North American Social Networks Conference for helpful comments. Song Yuan
and Hannah Ravitch provided excellent research assistance. All errors are our own.
1
I. Introduction
How important are leaders for the spread of social and political movements? Even if we accept
that the presence of a leader is important, does it matter who leads? Leaders are often ideological
entrepreneurs, who reframe grievances and offer new ways of understanding the world. Leaders
can help overcome practical issues such as coordination and collective action problems. They can
also help formulate a coherent ideology that binds the movement together and attracts new
followers. They model courage and commitment to the cause. All this may be especially important
for movements that disturb the status quo, since followers may face serious, even violent,
repercussions for joining the movement. In addition, effective leadership may make the
movements they lead especially infectious by crafting persuasive appeals and by forging personal
ties to sympathizers and potential supporters.
Intuitively, we know that leadership can make an enormous contribution to the spread of
movements. But how important are ideological innovators like Martin Luther King or Nelson
Mandela to the success of their movements, conditional on other factors? Identifying the unique
effect of such figures is difficult: we rarely have counterfactual worlds that exclude those
individuals. Without such counterfactuals, it is difficult to parse out the role that ideological
entrepreneurs play relative to macro or institutional phenomena.1
Network data provides a solution. Leaders influence people to achieve success, and via the
connections made by the leader we can capture the scope of their influence. To isolate the role of
ideological entrepreneurs, we need significant data about the individuals and their network—who
they knew, what they did, where they went—to estimate their influence. Moreover, we need
1 A recent literature in economics suggests that “superstars” can affect a host of economic and scientific outcomes
(Johnson et al. 1985; Bertrand and Schoar 2003; Jones and Olken 2005; Azoulay et al. 2010; Waldinger 2010; Moser
et al. 2014; Borowiecki 2017).
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network data to be able to simulate the spread of a movement with and without the unique role
played by the leader.
In this paper we provide insight into the role that leadership can play in facilitating social and
political movements by studying the network of the leader of one of the most important movements
of the last millennium: Martin Luther, the father of the Reformation. Within a decade of Luther’s
posting of the Ninety-Five Theses in 1517, many towns and cities across the Holy Roman Empire
adopted the reforms Luther advocated. In a little over a decade, about ten percent of German cities
were already Protestant, a share that would expand much further after 1530 (Rubin 2014). Yet,
Luther did much more than simply spark the Reformation. Over its first decade, Luther was its
tireless proponent and leader, risking his life to defy the will of the emperor and the pope,
reorganizing Wittenberg University to provide it with an institutional home, printing a blizzard of
pamphlets, and writing hundreds of letters that facilitated its spread. The combination of his
intellect and organizational capabilities raises the question of whether an event as monumental as
the Reformation could have succeeded without someone so capable leading it.
We analyze the role that Luther’s personal influence—as determined by a newly-digitized data
set of his personal correspondence, the tracking of places he visited, and the students he taught—
played in the early spread of the Reformation. Specifically, we ask whether the social network ties
between Luther and the cities forged by correspondence, visits and teaching, can help explain the
early adoption of Protestantism by German towns and cities.2 To test whether personal ties to
Luther made a city more prone to adopt Protestantism, we code a number of characteristics of
Luther’s ego-centric network as revealed by his collected correspondence, visits, and students by
2 In social network analysis, social ties between people are relations that serve as conduits through which information,
opinions, resources and influence can flow. The spread of religious movements is a topic especially well-suited to
social network concepts and methods, as recently demonstrated by Everton (2018).
3
the end of 1522. This period represents the formation of Luther as a dissident theologian,
prominent critic of the Roman Church, and proponent of radical religious reform. It ends before
the formal adoption of Protestant reforms, which began in 1522 following Luther’s defiance of the
emperor and the pope at the Diet of Worms in 1521 and his year-long protective incarceration on
the Wartburg.
Our study contributes to both empirical and theoretical puzzles. Empirically, our analysis sheds
new light on one of the great, enduring puzzles in the social sciences: why the Reformation spread
so rapidly and where it did so (for a review of the literature, see Becker, Pfaff, and Rubin 2016).
This is a puzzle because previous attempts at reform, many of which raised similar complaints to
Luther were violently suppressed or failed to diffuse widely. It has been argued that, on the demand
side, the increasingly temporal and avaricious actions of the Church placed numerous “consumers”
on the “margin of defection” from the Roman Catholic Church (Ekelund et al. 2002). Yet, this had
been the case for centuries—focusing only on the demand side leaves the “when” and “where”
questions unanswered. On the supply side, the recent spread of the movable type printing press
(invented in 1450 by Gutenberg in Mainz, Germany) helped the reformers rapidly spread their
anti-papal propaganda before the Church and its secular allies could respond. Rubin (2014) finds
that cities that were early adopters of the press were 29 percentage points more likely to be
Protestant by 1600.3
However, even if the press were important for spreading the message of the reformers, social
network theory suggests that the success of a movement in the face of (probable and violent)
resistance requires broad social influence on the part of the initial instigators (Centola 2018;
3 Another important factor allowing for the spread of the Reformation was the Ottoman advance into South-Eastern
Europe (Iyigun 2008). The Ottomans threatened the eastern flank of the Holy Roman Empire—reaching the gates of
Vienna—at precisely the time of Luther’s movement. This diverted Catholic resources away from Luther’s movement
and towards the more “existential threat” imposed by the Ottomans (Iyigun 2015).
4
Centola and Macy 2007). Otherwise, not enough individuals will join the cascade of revolt, even
if their private preferences are that it succeeds (Granovetter 1978; Oliver 1993; Kuran 1989, 1995;
Lohmann 1994; Rasler 1996; Kim and Bearman 1997; Siegel 2009; Slater 2009; Ellis and Fender
2011).4
Rubin (2014) found that cities which were early adopters of printing were about 29 percentage
points more likely to adopt Protestantism. Does printing account for the rapid diffusion of
Protestantism? Whereas printing could have facilitated the spread of the Reformation chiefly
through the mechanism of informational diffusion,5 the role of relational diffusion has been
relatively neglected in explaining the rise of Protestantism.6 Social relations are implicated in the
diffusion of the Reformation because the spread of heterodox ideologies and their
institutionalization relies not only on private “infection” through contact with a novel idea, but
rather active conversion to and the promotion of that new faith through collective action. An
extensive literature in the social sciences has shown how movements tend to diffuse not through
ideological infection but through social linkages between actors (Centola 2018; Hedström 1994;
Hedström, Sandell, and Stern 2000; McAdam and Diani 2003; Siegel 2009, 2013).
However, this paradigm of relational diffusion runs into a theoretical puzzle. According to
theories of diffusion, behaviors that require significant costs to adopt, such as converting to a new
religion, are predicted to slowly spread via space neighbor by neighbor (Centola 2018; Hedström
1994; Strang and Soule 1998). This is because multiple connections are required to convince
4 Cantoni et al. (2019) present experimental evidence from Hong Kong on the role of beliefs about turnout of others
as a crucial factor for own participation in a protest movement. 5 See Crabtree, Kern, and Pfaff (2018) on the role of the mass media versus social diffusion in the spread of the East
German uprisings in 1953. 6 This is not true of the historical literature on Luther, which discusses in detail the relationships he forged early in his
career and the role they played in the early Reformation. For more, see (among many other studies) Brecht (1985),
Oberman (1989), Roper (2017), and Kolb (2018).
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people to join, and spatial proximity creates the channels of reinforcing ties to activate diffusion.
The process is often very slow. For a movement to spread from one region to another implies that
all locations in between need to adopt. However, contrary to this prediction, the Reformation
spread across the Holy Roman Empire within two decades. Considering that Wittenberg was an
isolated town, how could it have generated rapid spatial diffusion? Furthermore, the Reformation
did not spread as a spatial chain of cities, but rather as sparks throughout the Holy Roman Empire.
How can we explain this peculiar pattern?
Our analysis helps solve the puzzles of the Reformation’s success. We reveal the size and scope
of the “Luther effect” on the inception of institutional reform, its influence on subsequent
Protestant adoption, and the role played by spatial diffusion in its crucial breakout phase when it
went from being a local expression of religious dissent in a few Saxon cities to a movement
stretching across Central Europe. We find that Luther used correspondence, personal visits, and
his students to persuade cities to adopt the Reformation. This influence conspicuously increased
the odds that a city would become Protestant net of other factors which predisposed a city to reform
or made it resistant. At the same time, however, we posit that Luther’s influence was not enough
to account for the widespread adoption of Protestantism. It would have also benefitted from spatial
diffusion resulting from complex contagion dynamics unleashed by the adoption of the
Reformation by neighboring cities. To explore this possibility, we conducted simulations based on
agent-based modeling which allow us to demonstrate the dynamic and interdependent processes
which combined Luther’s influence with spatial diffusion to allow the early Protestant movement
to break out of regional isolation and overcome resistance. We find that the network diffusion
model we propose, which combines ego-centric effects and complex diffusion, accurately predicts
observed patterns of diffusion in agent-based simulations.
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II. The Diffusion of Radical Institutional Innovation
Social scientists have long be interested in the mechanisms which explain the spread and adoption
of innovations, whether technological, ideological, or institutional (Rodgers 2003; Valente
XXXX). What makes the diffusion of innovations of such profound sociological interest is that
adoption is understood to be dynamic and interdependent. The choice to adopt an innovation
involves uncertainty and is shaped by social information which influences the perception of the
risks, costs, and benefits at stake. Adopting the innovation occurs, at least in part, because people
assess their choices in the light of other people’s behavior.
Some kinds of behavioral innovations take the form of fashions or passing fads, but others are
radically transformative and enduring. For instance, social scientists have studied waves of
religious conversion, mobilization into social movements, industrial revolutions, and the changing
of political regimes. In these cases, adoption, or “infection” in the language of contagion models,
is followed by social action to consolidate or institutionalize the innovation. The work of
institutional innovators consists of a twofold process of expanding the reach of the innovation by
persuading others to adopt it and ensuring its persistence and coherence afterward.
Radical institutional innovation, of the kind championed by Luther and the Protestant
movement, poses additional complications. In those instances, the adoption of innovation is not
simply a matter of buying Emerson’s apocryphal “better mousetrap”7 but of accepting radical ideas
which reject or upset the prevailing social order. When the innovation challenges existing interests
or entails the abandonment of an existing institution, resistance is to be expected (Centola 2018;
7 Per the market reasoning of Ralph Waldo Emerson, “If a man has good corn, or wood, or boards, or pigs, to sell, or
can make better chairs or knives, crucibles or church organs, than anybody else, you will find a broad hard-beaten
road to his house, though it be in the woods.”
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Centola and Macy 2007). On the one hand, investment in the old and status quo bias may create
higher thresholds to embracing the new among potential adopters. On the other hand, the old order
may have its ardent defenders who actively work against the spread and institutionalization of the
innovation. The resistance would be especially great where heterodox ideas compete against an
incumbent orthodoxy (Kim and Pfaff 2012). In the face of high hurdles to adoption or resistance
to change, why does the innovation spread?
The use of historical data to demonstrate diffusion, as for example in the study of the spatial
spread of social movements (Hedström 1994), fertility transitions (Casterline 2001), or political
upheavals (Crabtree, Kern and Pfaff 2018), can pose evidentiary challenges even as they provide
compelling opportunities to test models. Causal identification of sociological diffusion processes
is difficult with observational data (for reviews, see Palloni 2001; Strang and Soule 1998). The
spread of an innovation—even if it is rapid—is inadequate evidence for social diffusion. Diffusion
processes can be difficult to isolate from structural changes and the operant mechanisms can be
hard to observe. The relative infectiousness of an ideological or institutional “contagion” is
difficult to quantify. Proneness to adoption or resistance to it are often left unmeasured. We want
evidence of the appeal of innovations, of contact between innovators and adopters, of the speed
and extent of diffusion, of social influence, and of the factors which constrain adoption or influence
the thresholds which have to be overcome for it (Valente 20XX).
Recent work on network topology and diffusion has complicated the picture. Diffusion in a
small-worlds setting suggests that “contagion” spreads thanks to weak ties and long bridges which
connect otherwise dispersed parts of a network universe (Granovetter 1973, 1983; Burt 1992). A
bridge is a relationship which spans a structural hole where there is no effective indirect connection
through third parties (Burt 2005, p. 24). Ronald S. Burt (2005, p. 13) argues, “whether
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communities in a geographic region, divisions in a corporation, groups in a profession, or people
in a team, people specialize within clusters and integrate via bridges across clusters.” People who
whose personal network spans structural holes have informational advantages and can engage in
strategic coordination across groups. They can detect and exploit opportunities and play a vital
role in fostering contagion between adjacent populations (Burt 1992). As Burt has observed in
many settings, “People whose networks bridge the holes are brokers rewarded for their integrative
work” (Burt 1992; 2005, p. 7).8
However, when diffusion relies on the adoption of a costly and potentially dangerous behavior
like the heretical Protestantism of the 1520s, it may not be effective if driven merely by viral
exposure to a new idea through a single contact. Siegel (2009, p. 803) summarizes the thinking
concerning social networks and participation in costly collective action: “We ask those to whom
we are connected what they think . . . and whether information is accurate or relevant; we consider
their behavior as potential models for our own; we worry about their responses to our own behavior
and opinions.” As Centola (2018, p. 14) argues, “The basic problem of diffusion—that is, the
failure to spread behavior—occurs whenever behavior change encounters resistance … The less
familiar an innovation is, and the more inconvenient, uncomfortable, or expensive it is, the greater
the resistance will be, and the less likely it will be to diffuse.” The reason that such behaviors may
not spread in viral fashion is that they require “legitimacy, credibility, or complementarity in order
to be adopted” (Centola 2018, p. 35).
Consequently, exposure to new information may be insufficient to promote what Centola calls
“complex” diffusion—the adoption of innovations which entail meaningful behavioral change or
the adoption of new institutions. When actors have to commit themselves to an undertaking which
8 On the limits of strategic brokerage, see Stovel, Golub, and Milgrom (2011) and Stovel and Shaw (2012).
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is costly, dangerous or uncertain, it may require broader social influence channeled through
multiple and reinforcing ties—“wide bridges”—to facilitate adoption under these conditions
(Centola 2018; Centola and Macy 2007). When the mobilization effort is risky, its success
“depends upon close-knit networks to establish trusted relationships and provide social
reinforcement for participation” (Centola 2018, p. 91). People do not need to be eager adopters or
early movers (“the critical mass”, see Marwell and Oliver 1993) in order to get swept up in a great
upheaval. Social reinforcement can persuade even those who were initially resistant to join the
movement (Centola 2018, p. 173).
In the domain of religious and cultural innovation in which Luther engaged, there was plenty
of opportunities for “bridging” activists in the Holy Roman Empire (Kim and Pfaff 2012). The
predominant social structures and patterns of informal relations among literate people in early
sixteenth-century Central Europe suggest a configuration of dense local clusters of relationships
separated from each other by gaps in the ties between clusters of actors (or “structural holes”; see
Centola 2018, p. 19–30; Burt 1992). The social and geographic characteristics of the Holy Roman
Empire were conducive to forming such structures. The population of the Holy Roman Empire
was largely rural but there were many small and medium-sized cities which served as local
administrative, cultural, and economic centers. Most trade and economic activity focused on local
markets, although the volume of long-distance trade (including in printed materials) expanded on
the eve of the Reformation (Kim and Pfaff 2012). While some prominent cities were located on
major trade and pilgrimage routes, most economic and religious exchange was limited to regional
centers (Pfaff 2013; Pfaff and Corcoran 2012).
We do not contend that Luther’s correspondence network, having originated before 1517, was
initially designed to facilitate the spread of the Reformation, which in its early days was in many
10
regards an emerging and still incoherent movement. Nevertheless, as Roper (2010: 294) observes,
“Always carefully crafted and mostly written with an eye to a public beyond the ostensible
correspondent, Luther’s letters were strategic masterpieces.” As became evident by the time of the
indulgences controversy in 1517–18, Luther’s correspondence seems to have connected an
emerging movement leader with locally influential people who otherwise would have lacked a
direct tie to the Wittenberg movement. Opinion leaders are people whose social exchanges make
innovation contagious. They “are in some ways structurally similar to the people they influence,
but in one important way distinct; they have strong connections to other groups” (Burt 2005, p.
85). They do not need to be high-status persons themselves, but typically they are more
cosmopolitan than others such that they communicate with diverse partners and tend to introduce
innovations into their group (Rogers 1995).
In the sixteenth-century context, the education, income and greater mobility of Luther’s
correspondents compared with others in their society might have made them prone to occupy the
local brokering roles characteristic of opinion leaders (Burt 2005, p. 85–6).9 In a society in which
literacy was limited to less than ten percent of the population, many of Luther’s correspondents
may have been well-suited to serving as conduits speeding the diffusion of Reformation ideas and
their institutional adoption in the towns where they resided. Luther’s correspondence was therefore
indicative of the personal network of a movement leader, linking him to a diverse set of potential
opinion leaders across the empire. As the central figure in the emerging Wittenberg movement,
Luther may not have recognized or intentionally tried to exploit a brokering role in the diffusion
of the Reformation. What matters is that he closed structural holes as a by-product of his activities
9 Burt (2005, p. 90-91) argues that “with early access to diverse information, beliefs, and behavior, people whose
networks span structural holes can expect to find themselves moving ideas from one group to another, proposing ideas
that are new to the recipient group, and so seeming within the recipient group to be gifted with creativity.”
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as an outspoken proponent of reformed theology and antagonist of the Roman Church. In so doing,
Luther’s written communication bridged gaps between dispersed circles of humanist intellectuals,
theological dissidents, and reform-minded rulers.
The ego-centered network data which can be coded from Luther’s correspondence does not
permit a direct test of network theories of individual adoption. Nevertheless, towns, the unit of
observation in our analysis, are meaningful adopters, particularly in the context of early modern
Central Europe where towns were governed by elected councils with substantial sovereign powers,
including the regulation of religious affairs (Palloni 2001). Perspectives from social network
analysis which suggest mechanisms to explain the effect of Luther’s ties on Protestant adoption by
towns are therefore highly relevant. Their implications for social diffusion based on Luther’s ties
and spatial diffusion based on proximity between towns can be tested using conventional
regression analysis.
In addition to the social influence which Luther exerted through his correspondence, he also
made a number of journeys which allowed him to make contacts, appeal to supporters, and attempt
to influence local notables. Although most of the journeys undertaken by Luther were to towns in
relative proximity to Wittenberg, he also undertook a number of journeys outside his native region
of Saxony. Some of these were undertaken on matters relating to his studies or the business of his
monastic order, including a journey on foot to Rome. Some arose in connection with the religious
controversies Luther entered into, including academic disputations in Heidelberg and Leipzig. A
few were connected with appearances before the papal officials or the Imperial Diet, as in his
journeys to Augsburg and Worms. Others were inspired by opportunities for public preaching or
meetings with prominent people.
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These journeys tended to provide abundant opportunities to make personal connections and
exercise influence. In most the towns he visited, Luther either enjoyed the hospitality of local
notables or else was hosted by a monastic community. In about half of the German towns Luther
visited, he preached, gave a public lecture, or faced an official hearing.
Finally, Luther had third vehicle through which to exercise social influence. He mobilized his
students at Wittenberg to become apostles of the Protestant cause. He converted them to his new
theology and then sent them back to their hometowns to preach and agitate in favor of the
Reformation (Kim and Pfaff 2012). We therefore propose:
Proposition 1: The personal influence of Luther upon a town prior to 1523, as proxied by the
presence of correspondents, visits and students in a town, increased the probability that the
town adopted the Reformation by 1530.
The implications of the complex diffusion model suggest that multiple interpersonal contacts
between Luther and correspondents in a given city would have facilitated the diffusion of the
Reformation by creating a circle of social influence. We therefore might expect that Luther’s
correspondence furthered the spatial diffusion of Protestantism to the extent that he had multiple
contacts (tie-intensity) with people in a given town. In other words, we propose:
Proposition 2: The greater Luther’s tie intensity with people in a given town prior to 1523, the
higher the probability it adopted the Reformation by 1530.
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The cohesiveness of local markets and economic activities indicates that the flow of people,
capital, and information followed these channels. We would thus expect cities connected to one
another via trade to emulate each other and contribute to a spatial diffusion of the Reformation.
We also follow theories of complex contagions (Centola 2018; Centola and Macy 2007) and
propose that there would need to be multiple neighboring cities to adopt to activate the spread of
the Reformation. We propose:
Proposition 3: The spread of the Reformation followed a spatial pattern via the mechanism of
complex contagion.
Finally, Luther’s influence and spatial diffusion are related to one another. It is very well possible
that Luther converted cities, which further spread the Reformation to its neighboring cities. The
success of the early Reformation may have also been a combination of Luther’s network and
spatial diffusion via trade routes. We therefore propose:
Proposition 4: The spread of the Reformation was an interdependent combination of Luther’s
influence and spatial diffusion
III. The Reformation as Case of Movement Diffusion
The questions of why and how the Reformation spread so rapidly are an enduring puzzle that is
still at the center of much research in the social sciences (Becker et al. 2016). Somehow, the
complaints made by an obscure monk in a marginal university town unleashed a religious and
political upheaval. Historians have argued that the main thrust of the popular movement that
propelled Protestantism took place in cities in the 1520s (Moeller 1972; Ozment 1975;
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Scribner 1986; Schilling 1988; Blickle 1992; Brady 1998; Mörke 2005). Across German-speaking
Europe, town councilors and other authorities were persuaded—or pressured—to ban the Catholic
mass, dissolve monasteries, expel priests and prominent defenders of the old order, introduce
reformed liturgy, and reorganize institutions of charity. Yet, at the global level, the movement was
neither well-coordinated nor well-institutionalized. In this early phase of the Reformation, the will
of the princes played a relatively small role in pressuring cities to reform. It was not until the
Imperial Diet, which met at Augsburg in 1530, that the Protestant movement attained cohesion
and clear political backing.10
If not through formal organization or the work of the princes, how did the Reformation achieve
its early breakthrough? We distinguish here between demand and supply-side reasons for the rapid
success of the Reformation. On the demand side, Ekelund et al. (2002, 2006, ch.5) argue that
individuals throughout late-medieval Europe who “demanded” spiritual services were placed on
the margin of defection by the increasingly avaricious and monopolistic practices of the Church.
In such a setting, rival “firms” had an opportunity to enter the religious marketplace by offering a
less costly path to salvation. The Protestant movement took advantage of this opportunity in the
spiritual marketplace, offering a substitute that was highly desired by large swaths of the
population.
Yet, demand driven theories of the Reformation leave much unexplained. The phenomena
described by Ekelund et al. (2002, 2006)—a monopolistic Church engaged in increasingly worldly
pursuits—existed for centuries prior to the Reformation. Indeed, such practices were among the
chief complaints of previous attempts at reform. Jean Gerson’s (1362–1429) conciliarism
10 At that assembly, an alliance of Protestant cities, princes and estates presented the “Augsburg Confession,” an
official theological explanation of their theological position and a de facto declaration of independence from the
Roman Catholic Church.
15
movement, Wyclif’s (d. 1384) Lollard movement, and Hus’s (c. 1372–1415) Bohemian rebellion
all put forth grievances similar to those that would engulf Luther’s movement in the 1520s (Rubin
2017, p. 130–31). On the other hand, two supply side features of the spread of the Reformation
can help account for its timing and location: the spread of the moveable type printing press and
the tireless efforts of one man: Martin Luther. His social influence allowed the Protestant
movement to gain a strong footing in the 1520s, the period before princes and urban patricians
took up the Reformation’s cause. We posit that these two contemporaneous phenomena—in
conjunction with significant built-up latent demand—accounts for the success of the Reformation.
Although a number of conditions facilitated the Reformation’s breakthrough, including
fortunate timing, Emperor Charles V’s preoccupation with his wars with the Ottoman Turks and
Valois France, and an ally in the court of Elector Fredrick of Saxony, Luther’s achievement should
not be understated. During the period we study, Luther began as an Augustinian friar and professor
of Biblical theology in a small provincial city. Beginning in the 1510s, his biblical studies and
perceptions of the shortcomings of the Roman Catholic Church led him toward an increasingly
critical position toward the Church. From 1517 onward, Luther led a mounting attack on Rome’s
position as the monopoly provider of spiritual services and ultimate salvation of the soul. In the
remarkable period through 1522, Luther embarked upon three lines of attack against the Church’s
seemingly incontestable monopoly. First, he cast doubt on the efficacy of its doctrine and practices
of justification and penance. Second, he assailed the holiness of the Church as an institution,
criticizing the papacy, monasticism, and the sacramental role of the priesthood. Finally, he offered
a rival set of doctrines and practices of putatively greater quality and value than those of Rome.
They would become the basis of the Reformation and of the rival goods which the new Protestant
churches would offer (Goldman and Pfaff 2017).
16
From the inception of his rebellion against Roman Catholic authority, Luther understood the
struggle in missionary terms. He saw Wittenberg as the cradle of the reform movement and
assumed leadership there not only in the domain of theology but also in spreading the Reformation
(Grendler 2004; Schwiebert 1996). Using his personal influence to sway people to join the
movement, he hoped to promote its adoption across Central Europe. He pressured the professors
at Wittenberg to join the fight. Writing to Phillip Melanchthon, Luther evoked biblical imagery to
underscore the spiritual urgency of the cause: “you lecture; Amsdorf lectures; Jonas will lecture;
do you want the kingdom of God to be proclaimed only in your town? Do not others need the
gospel? Will your Antioch not release a Silas or a Paul or a Barnabas for some other work of the
spirit?” (Hendrix 2010, p. 25).
Communication and persuasion have long been understood as vital to the spread of the
Reformation (Pettegree 2005). Above all, scholars have depicted the unmistakable importance of
the printing press in unleashing the Protestant upheaval. Luther wrote tirelessly to advance the
cause of reform and proved a master polemicist against the Roman Church. His output of
theological works and popular pamphlets was prodigious. In the decade after 1517, Luther wrote
several major theological treatises. His influential translation of the New Testament from Greek
into colloquial German appeared in 1522. He also wrote hundreds of lively pamphlets and sermons
which often responded forcefully to Catholic criticism and lambasted his adversaries. By the time
of the Augsburg Confession, his works had been widely circulated and reprinted by presses across
the Holy Roman Empire and beyond (Edwards 1994; Eisenstein 1979; Pettegree 2015).
Luther himself quickly realized how powerful the printed word had become in his hands,
declaring “printing is God’s latest and best work to spread the true religion throughout the world”
(Holborn 1942). Historians have generally agreed that printing made the Protestant breakthrough
17
possible. Luther’s biographer Martin Brecht (1985, p. 208–9) argues that, “Without the new
medium of the printing press Luther’s thoughts would never have achieved such a rapid and wide
distribution.” Mark U. Edwards (1994, p. 1) nails this point home by beginning his book on Luther
and the printing press with the statement, “the Reformation saw the first major, self-conscious
attempt to use the recently invented printing press to shape and channel a mass movement.”
Besides his skill as a writer and indefatigability as a polemicist, Luther intuitively understood the
print business and was tactically astute in exploiting it (Pettegree 2015). Roper (2017, p. 108)
contends that “the logic of the market and its craving for novelty was part of what propelled
Luther’s cause.” The eminent Bernd Moeller (1979) pronounces simply, “No printing, no
Reformation.” Studies by economic historians have providing compelling evidence to suggest the
causal role that printing played in the spread of Protestantism (Rubin 2014; Dittmar and Seabold
2018).
Our approach builds upon recent studies which have begun to apply relational concepts to the
explain the case of the Reformation. Cantoni (2012) shows how adoption of the Reformation was
influenced by considerations of security as well as by emulation. He finds that the princes of the
Holy Roman Empire were more likely to adopt the Reformation if neighboring rulers did because
potential coalition partners could help withstand expected Catholic and imperial retaliation. The
demand side also mattered; princes were more prone to favor Protestantism as Luther’s ideas
spread among their population, as suggested by Cantoni’s results that show that a city’s distance
from Wittenberg is strongly and negatively correlated with Reformation adoption.
Kim and Pfaff (2012) focus on bottom-up pressure, showing how ideologically-mobilized
students spread religious contention by bridging the social distance between university centers and
their hometowns. Their analysis measures the influence of insurgent Protestantism and orthodox
18
Catholicism through university enrollments. An analysis of hundreds of towns in the Holy Roman
Empire shows that the greater a city’s exposure to heterodox ideology through city-to-university
ties (Wittenberg and Basel), the greater its odds of instituting the Reformation, net of covariates
and a control for spatial diffusion. But diffusion was contested; links to leading orthodox
universities (Cologne and Louvain) decreased a city’s odds of reform.
Wurpts, Corcoran, and Pfaff (2018) take a further step by directly employing network methods
to explain Protestant adoption. They argue that the Reformation spread through northern Germany
through a combination of informational diffusion and social influence. Employing new historical
data on the institutional and personal connections between towns in the Hanseatic League, they
reconstruct the social network between northern trading towns which enabled the spread of
Protestantism. They find evidence that a combination of strong ties cemented through shared
participation in League governance and weak, cross-cutting membership ties fostered early
Protestant adoption by Hanseatic cities.
IV. Why Luther’s Network Might Have Mattered for the Diffusion of the Reformation
A. Luther’s Correspondence
The decades between 1501, when we observe his first recorded correspondence, through the end
of 1522, when he returned from protective custody on the Wartburg, were Luther’s crucial
formative years. It was during this period that Luther studied at Erfurt, abandoning legal studies to
enter the Augustinian monastic order, became a heterodox professor of Biblical theology at
Wittenberg, made his public stand against the doctrine of indulgences, defended his new theology
in public disputations in Heidelberg and Leipzig, and withstood official scrutiny at the Imperial
Diets at Augsburg and Worms. During the period of his protective custody in Wartburg castle in
19
1521-22, he completed his German translation of the New Testament and set out principles for an
emerging Protestant church.
Luther was a prolific correspondent. Historian Lyndal Roper (2010, p. 283) observed, “There
is probably no other sixteenth-century figure who has left such a wealth of ego-documents as
Martin Luther.” Luther’s wide-ranging correspondence shaped and sustained the emerging
Reformation movement. Luther put his correspondence to use in establishing and shoring up the
“vivid friendships” that sustained him. Letters to friends, supporters, and foes also shaped the
development of his emerging theology and the movement which propelled it (Roper 2017, p. xxiii).
It may be surprising that so much correspondence could have been exchanged in late medieval
Europe. However, by the early sixteenth century an informal postal system had evolved which
made sending and receiving letters relatively reliable and inexpensive (Greengrass 2016).
Correspondence expanded between merchants and bankers, as well as among princes and prelates
and their secretaries, who discussed official matters of Church and state. Parallel to this, a lively
culture of intellectual exchange thrived among the small, but growing, literate minority dispersed
across the cities and university towns of the empire. Humanist intellectuals reimagined the letter
as something more than an instrumental exchange (McLean 2007).11 Although it remained an
important medium by which to transact business, the letter also became a means to conduct
“conversations between absent friends,” including among correspondents who never met in
person. Letters were understood as semi-private, and were frequently passed along by recipients
and, in the case of Luther and other famous people, collected and printed for a wider readership
(Greengrass 2016; Roper 2010).
11 Similarly, Mokyr (2016) employs letters sent by Enlightenment intellectuals to argue that a “culture of (economic)
growth” emerged during that period in Europe.
20
Luther used letters to stay in contact with students and colleagues, to rally supporters, to
respond to theologians and critics, to answer requests for assistance or advice, and, finally, to
persuade influential people like the rulers of cities and princes to adopt the cause of reform (Brecht
1985, p. 77-80; Greengrass 2016; Roper 2010, 2017). People apparently liked corresponding with
Luther. He was a “brilliant, engaging correspondent” (Roper 2017, p. xxxiii), capable of affecting
several personas, including deferential subject, pious professor, tender pastor, irreverent wit, and
vituperative critic, depending on his partner and the circumstances. In short, Luther was well-
steeped in the art of humanist letter-writing (Greengrass 2016; McLean 2007). Over the course of
his life, his correspondence was voluminous such that collected letters run to several volumes in
the Weimar edition of his collected works, as we detail in the next section.
V. Data and what they Reveal about Luther’s Network
A. Data
We employ numerous data sources to test the connection between Luther’s network and the spread
of the Reformation. Our universe of observations is cities in the (de jure) Holy Roman Empire that
are part of the data set collected by Rubin (2014). This includes cities in modern day Germany,
Belgium, Netherlands, Switzerland, Austria, Czech Republic, northern Italy (e.g., duchies of
Milan, Savoy, and Tyrol), eastern France, western Poland.12 Data on Reformation adoption (by
1530, 1560, and 1600), printing press adoption, and a host of control variables are from Rubin
(2014).
12 We distinguish this from the de facto HRE, which does not include Switzerland, the Netherlands, or northern Italy,
all of which gained some form of independence by the end of the period in question. We run robustness checks,
reported in the Appendix, using the de facto HRE as the universe of observations. Results are largely similar.
21
We reconstruct Luther’s early ego-centric social network (Perry et al. 2018) through a novel
source of data: his correspondences and the towns he visited. We propose that letters from Luther
which were received by correspondents in a given place can be taken as a measure of its social
proximity to the Reformation operating through the influence of the movement’s central actor
(Luther) on literate residents prone to have played the role of local opinion leaders. Similarly, we
propose that the number of correspondents in a given town (the number of “tie-alters” in network
terminology) and the number of letters exchanged, would have enabled greater social influence in
favor of Protestantism which, more than information about the emerging Wittenberg movement,
may have been necessary to overcome skepticism, hesitancy, and opposition to the new theology.
We restrict all of the variables to correspondence/visits/ties prior to 1523, when the Protestant
reforms were first formally adopted.
Luther’s correspondence has been digitized as part of a project to digitize the Weimar edition
of Luther’s collected works (Luthers Werke 2018). The original Weimar collection, published in
1883, contains 127 volumes and is believed to hold the entirety of Luther’s surviving
correspondence.13 Each entry contains a transcription of the entire letter and, in most cases, a date
and where the letter was sent to/from. We coded these data and produced three variables. On the
extensive margin, we coded a “Luther letter by 1522” dummy, which equals one if Luther wrote a
letter to an individual in the town prior to 1522 (inclusive). On the intensive margin, we created
variables denoted “number of Luther letters by 1522,” and “tie alters by 1522.” These variables
are a count of the Luther letters and a count of Luther’s personal ties in the town, respectively.
13 At Luther’s time, it was common practice to keep copies of outgoing letters. However, early in his career Luther
lacked a secretary, was besieged with incoming correspondence, and had no deliberate policy of saving letters (Brecht
1985, p. 77; Roper 2017, p. xxxi-ii). However, historians argue that Luther's outgoing letters must have had a high
survival rate because they were intentionally saved by their recipients and frequently copied and distributed among
friends, supporters, and enemies. Indeed, Luther complained about this because it meant that it was hard for him to
write confidential letters with any hope of privacy (Greengrass 2016, p. 437).
22
Figure 1 shows how Luther’s exchange of letters evolved over time, while Figure 2 reveals where
Luther’s network resided, as measured by his correspondence network. Not surprisingly, his
network was denser around his residence in Wittenberg. Moreover, we characterized the letters
based on two of their features: the language they were written in (Latin or German) and the identity
of the recipient (church figure, political figure, burgher, and other).14 Both of these aspects of the
letters might have mattered for the spread of the Reformation because they reflected the audience
to which Luther was appealing.
Figure 1: Luther’s Exchange of Letters, 1501-1522
Source: Clemens, ed. Luthers Briefwechsel (1930-1985).
Looking deeper at Figure 2 reveals key spatial aspects of Luther’s network. Besides Wittenberg, a
few other cities stand out because of Luther’s frequent correspondence with their residents.
Nuremberg and Augsburg were rich and influential imperial cities which Luther visited and where
he had a number of friends and supporters among their theologians and prominent burghers. Erfurt
was a large city with a famous university which Luther attended before entering the Augustinian
14 Note: we have not yet coded the “identity of the recipient” data.
0
20
40
60
80
100
120
140
23
monastery in that city. Luther retained many friends from his Erfurt days but had an antagonistic
relationship with many of the academics and theologians at the university. Altenburg was a Saxon
city where the mayor took an early interest in Luther’s ideas and Wenceslaus Link settled there to
preside over its church reform in 1522. Other cities which feature prominently in Luther’s
exchange of letters were centers of opposition to the Reformation, including Leipzig (home of
Dungersheim) and Mainz, the seat of Prince-Bishop Albrecht, the principal target of Luther’s
criticisms during the indulgences controversy.
In order to capture another channel of social influence which may have been operating besides
Luther’s correspondence, we also coded the location of all the towns Luther visited in the course
of his career through the end of 1522. These data are recorded in the Luther-Kalendarium, an
exhaustive register of all of Luther’s known activities (Buchwald 1929).15 As in the case of
Luther’s letters, we code both the extensive margin (whether Luther visited a town prior to 1523)
and the intensive margin (the number of times he visited a town prior to 1523).
We measure two other means by which Luther may have exerted influence on the diffusion of
the Reformation. First, we measure the extent of Luther’s influence over a town in terms of the
number of his printed works which appeared in a town prior to 1523. This variable is coded using
data from the Universal Short Title Catalogue (USTC).16 Second, following Kim and Pfaff (2012),
we measure the number of students who enrolled at Wittenberg University from a given town
during the crucial years of 1517-1522, the period when Luther first cultivated a cadre of supporters
15 We supplement Buchwald’s (1929) Kalendarium, which contains few details about Luther’s mission to Rome, with
the more complete documentation provided by Schneider (2011). We double-checked the entries in Buchwald (1929)
and Schneider (2011) by coding all locations Luther visited that are references in the all-encompassing biography of
Luther by Martin Brecht (Brecht 1985, vol. 1). These sources are overwhelmingly consistent with each other. 16 The USTC is designed as a universal catalogue of all known books printed in Europe in 1450–1600 and provides
information for each book on the city in which it was published, the language, and the year of publication. It was used
in the seminal work by Dittmar and Seabold (2018), and more recently by Becker and Pascali (2019).
24
with the intention of sending them back to their native towns to promote the Reformation. The
data are coded from the Wittenberg matriculation book edited by Förstemann (1841).
Figure 2: Map of Cities that Received a Luther Letter, 1501-1522
Notes: Shaded region is the boundaries of the Holy Roman Empire in 1500. Dot size corresponds to the number of
Luther letters received.
25
Table 1: Summary Statistics
Standard
Variable Mean Deviation
Dependent Variable
Protestant in 1530 0.19 0.02
Primary Independent Variables
Extensive Margin
Luther letter by 1522 dummy 0.11 0.02
Luther letter in Latin dummy 0.10 0.02
Luther letter in German dummy 0.04 0.01
Luther letter sent to burgher dummy
Luther letter sent to Church figure dummy
Luther letter sent to political figure dummy
Luther visit by 1522 dummy 0.07 0.01
Luther printed works dummy 0.10 0.02
Luther students (1517-22) dummy 0.38 0.03
Intensive Margin
Number of Luther letters by 1522 1.53 0.85
Number of Luther letters in German by 1522 1.33 0.73
Number of Luther letters in Latin by 1522 0.21 0.13
Tie alters by 1522 0.28 0.06
Number of Luther visits by 1522 0.15 0.04
Number of Luther printed works (/100) 0.03 0.01
Number of Luther students 2.24 0.27
Control Variables
Printing Press by 1500 0.35 0.03
Log of Population in 1500 (1000s) 1.68 0.05
Independent City dummy 0.13 0.02
University by 1450 dummy 0.04 0.01
Bishopric by 1517 dummy 0.19 0.02
Lay Magnate dummy 0.78 0.02
Market Potential in 1500 23.09 0.28
Water dummy 0.72 0.02
Hanseatic dummy 0.16 0.02
Log distance to Wittenberg (miles) 5.55 0.04
Log distance to Zurich (miles) 5.46 0.04
Only cities in the de jure Holy Roman Empire included. N = 340.
Finally, we construct variables derived from principal component analyses of our four primary
extensive margin Luther network variables (Luther letter, Luther visit, Luther printed works, and
Luther students) and another set of variables from principal component analyses of our four
26
primary intensive margin Luther network variables. In all regressions employing these variable,
we only include the first principal component.17 Summary statistics of variables are available in
Table 1.
In order to motivate the analysis, we show the proportion of towns adopting the Reformation
by 1530 for five of our key (extensive margin) variables: the presence of a printing press, a Luther
letter by 1522, a Luther visit by 1522, a Luther printed work by 1522, and a Luther student (1517-
22). Figure 3 reports this breakdown of the raw data. It suggests that press towns and non-press
towns were similar in their propensity to adopt the Reformation; if anything, non-press towns were
more likely to adopt the Reformation.18 However, the relationship between the spread of the
Reformation and the various Luther network variables is much more striking. Of the towns which
had people who corresponded with Luther by 1522, 47% were Protestant by 1530. Meanwhile, of
the towns which contained no one who corresponded with Luther only 15% were Protestant by
1530.19 A similar—and stronger—relationship can be seen with respect to Luther’s visits. Of the
towns he visited (did not visit), 63% (15%) were Protestant by 1530. A similar pattern holds with
respect to towns that published Luther’s works and from which students at Wittenberg resided.
38% of towns that printed Luther’s works adopted the Reformation by 1530, whereas only 16%
of those towns not printing his works adopted the Reformation. Likewise, 37% of towns that sent
17 The principal components were derived using the pca command in Stata. We also ran all regressions using the first
two components. In each of these regressions, the coefficient on the first component is positive and statistically
significant and the coefficient on the second component is statistically insignificant. 18 This may seem inconsistent with the results reported in Rubin (2014), who shows a positive relationship between
the spread of printing and the Reformation. But the raw correlations reported in Rubin are weak, especially for the
Holy Roman Empire. It is only after controlling for numerous city level characteristics and addressing endogeneity
concerns related to the press that Rubin finds a positive and statistically significant relationship between the spread of
printing and the Reformation. 19 Moreover, of the towns which Luther had correspondence with prior to 1523, 71% were Protestant by 1560 and
74% were Protestant by 1600. Meanwhile, of the towns which Luther had no correspondence with prior to 1523, 38%
were Protestant by 1560 and 51% were Protestant by 1600.
27
students to Wittenberg adopted the Reformation by 1530, whereas only 7% of towns that did not
send students were early adopters of the Reformation.
Figure 3: Proportion of Cities that Adopted Protestantism by 1530, by Various Characteristics
B. The Social Network Revealed by Luther’s Letters
The social-structural data which can be coded from Luther’s collected correspondence can be
thought of as revealing a unidirectional ego-centered network (Perry et al. 2018). It is incomplete
because it is based only on Luther’s correspondence with others and not on ties between alters in
his network (in other words, it is not a “friends of friends” network). It is unidirectional because
Luther did not archive the letters which he received. Outgoing letters which survive to today are
0.0
0.2
0.4
0.6
0.8
1.0
Yes No Yes No Yes No Yes No Yes NoPro
po
rtio
n o
f C
itie
s P
rote
stan
t b
y 1
53
0
Press
by 1500
Luther
Letter
Luther
Visit
Luther
Printed
Work
Luther
Student
28
collected from those who had received his correspondence (Greengrass 2016; Roper 2010).20 All
historical evidence suggests that corpus of letters sent by Luther is nearly complete. Fortunately,
ego-centered network analysis is less sensitive to missing ties than is sociometric analysis, which
assumes a universe of nodes and ties (Perry et al. 2018).
As a result of its value and importance at the time, the correspondence Luther sent out was
routinely archived and reproduced by recipients, suggesting that the data that we can gather from
outgoing letters is largely complete (Roper 2017: xxxi-ii). Nevertheless, the incompleteness of the
data could bias our understanding of Luther’s ties to other people and places if he was
systematically addressed by different people than those to whom he sent letters. Substantively, this
does not appear to be the case. The exchange of letters was vital to the humanist culture that
flourished in the sixteenth century. It was guided by a strong norm of reciprocity which operated
among correspondents, meaning that Luther’s outgoing correspondence included replies sent to
those from whom he received letters even if he had not initiated the exchange (Greengrass 2016;
McLean 2007; Roper 2010, 2017).
During his early career, Luther sent hundreds of letters. The data analyzed for this paper
included 564 letters written between 1501 and 1522, only 31 of which pre-date 1517. His
correspondents were friends and collaborators, theologians, prelates of the Church, princes and
burghers. Figure 4 provides a star-shaped diagram of Luther’s incomplete ego network in which
line width indicates the number of letters exchanged. Luther’s correspondents were a large and
diverse group, consisting of 105 distinct tie-alters. They appear to consist of a mixture of “strong”
ties linking him to friends and colleagues with whom Luther engaged in frequent exchange, and a
20 “One may be certain that Luther’s contacts with other places were more numerous than is known today.
Unfortunately, he was not especially concerned with preserving his correspondence” (Brecht 1995: 77).
29
greater number of “weak” ties to people with whom Luther had infrequent or occasional
exchanges.
Figure 4: Luther’s Ego Network, with Links to Alters
(line width indicates number of letters exchanged, top 10 links listed)
In this period of his life, no one was more important in his circle of correspondents than Georg
Spalatin, who exchanged more than a third of all of Luther’s correspondence during his early
career. Spalatin played several key roles in Luther’s life. A close friend and confidant to Luther,
he was also a humanist intellectual, a university official, and a state secretary and advisor to Prince-
Elector Fredrick of Saxony (Roper 2010). Spalatin served an essential function, serving “as the
middleman between his prince and Luther, gently guiding Frederick into policies that protected
and supported the reforms that his professor and colleagues were promoting” (Kolb 2018: 59).
Although Luther sometimes wrote to the prince directly, communication between him and Fredrick
30
was usually mediated through Spalatin. In spite of the undeniable role that Fredrick played in
shielding Luther and providing an opportunity for his movement to expand, he was cool toward
the renegade professor and the two never met before the prince’s death in 1525. Spalatin ensured
that Luther could remake the university according to his reformed vision, arranged for him to enjoy
the prince’s patronage, and convinced Fredrick to protect the upstart monk from the emperor and
the pope.
Alongside Spalatin, Luther’s friends and colleagues in Wittenberg were among his most
important early supporters. Wenceslaus Link was a fellow Augustinian and member of the
theology faculty at the university. Link backed Luther’s radical ideas in Wittenberg and in their
order. His office as vicar-general of the order gave Link a chance to visit dozens of Augustinian
priories around the empire and thereby spread the Wittenberg movement. Link accompanied
Luther during his interview with Cardinal Cajetan in Augsburg in 1518 where they resisted
pressure to submit to papal authority. Philip Melanchthon arrived at Wittenberg in 1518 as a
professor of Greek and quickly embraced Luther’s new theology. Luther championed
Melanchthon’s overhaul of the university’s curriculum, which was remade on a humanist basis.
Spalatin soon reported to Fredrick that four hundred students were regularly attending Luther’s
theology seminar and five or six hundred Melancthon’s lectures (Schwiebert 1996, p. 471).
Practically overnight, Wittenberg became one of the most important universities in Europe and the
center of an emerging movement (Grendler 2004; Kim and Pfaff 2012).
Luther also frequently exchanged letters with partners beyond Wittenberg. Luther exchanged
many letters with Christoph Scheurl, a lawyer and former Wittenberg professor, who had taken up
an important post in his native Nuremberg. Scheurl was an intellectual, master diplomat, and state
official in an influential imperial city. He did much to advance Luther’s cause and tried to shelter
31
him from imperial retribution. Scheurl also promoted Luther’s thoughts, helping to arrange the
Leipzig Disputation in 1519, which allowed the reformer to defend his position in a widely-
publicized debate against the leading Catholic theologian Johannes Eck.
The inferences we can draw about the potential influence of Luther’s letters is not limited by
the possibility that he wrote only to people who were his friends or already convinced by his ideas.
Luther’s long-distance correspondents included many who were straddling the fence, were
skeptics, or even outright antagonists. Not everyone was persuaded. For instance, during these
years, he exchanged letters frequently with Duke Georg, the ruler of the Albertine duchy of
Saxony. The duke was unusually interested in theological and ecclesiastical questions. His interest
in religious politics led him initially to be sympathetic to Luther’s criticisms and he hosted the
Leipzig Disputation. He soon rejected Luther, however, when he recognized him as an enemy of
the established Roman Church. The correspondence between the two became acrimonious and
Georg became an avowed enemy of the Reformation.
As the case of Duke Georg suggests, Luther did not limit even repeated exchanges to friends
and supporters. He also sparred with theologians like Hieronymus Dungersheim, a prominent
scholastic thinker and professor of theology at Leipzig University. Dungersheim was a forceful
defender of orthodoxy and a persecutor of the Bohemian Brethren, followers of the banned (and
burned) Czech theologian Jan Hus. After failing to persuade Luther to repudiate his attacks on the
Church, he consistently and vehemently opposed the Wittenberg movement. Another prominent
antagonist was Johann Eck, a well-regarded scholastic theologian at the University of Ingolstadt.
Sharing a commitment to reforming simony and the abuse of indulgences, Eck was initially
sympathetic to Luther’s writings. Eck turned against him when he realized that Luther was a threat
to the existing order, however. Eck debated Luther and his Wittenberg colleague Andreas Karlstadt
32
at the Leipzig Disputation. After he compelled Luther openly to state his position that both the
pope and the councils of the Church could err (and had done so), Eck traveled to Rome to denounce
him and speed the process leading to Luther’s excommunication.
It is remarkable to note that, despite the fact that Luther had spent the majority of his career
through 1522 as an obscure monk and professor at a provincial university, his ego network during
this period was remarkably diverse, revealing a tendency to make ties not only with fellow
theologians but with people in other social positions. In terms of social categories, during the
period of Luther’s early career (through 1522) his correspondents included theologians and
preachers (45% of all correspondents), nobles (18.5%), higher ecclesiastical officials (18%), state
officials (11%), and a few prominent burghers (6.5%) (see Table 1). The diversity of Luther’s
network suggests a moderate tendency toward cosmopolitanism, with a mixture of strong ties to
friends, collaborators, and Wittenberg colleagues, and weak ties which linked him to a dispersed
set of correspondents in other cities (Perry et al. 2018, p. 166-173). This structure, which combines
densely-knit and intimate “provincial” ties with more dispersed and diverse ties (even to people in
far-off cities like Königsberg), is precisely the kind of network which has been shown to be a
favorable for the spread and adoption of religious movements across times and places (Everton
2018: 67-8).21
The language of Luther’s letters is telling. Fully 85 percent of Luther’s letters were written in
Latin. He addressed all priests, academics and those with Humanist educations exclusively in
21 It is noteworthy that no “strong” ties to family members can be observed in these data because the surviving
correspondence contains no letters to Luther’s relatives during our period of study. This is not surprising, given that
Luther’s family was descended from the peasantry and neither his parents nor his siblings were literate. Moreover,
there is good reason to believe that in his early adulthood, family and intimate relationships played a small role in
determining his social network. Luther left home at about twelve years old to pursue his education and rarely returned
home, particularly after entering the Augustinian monastery in Erfurt in 1505 (Brecht 1985; Oberman 1989). Although
Luther was excommunicated in 1520, he continued to live in an Augustinian monastery and wore a monk’s habit
through 1522. Luther did not marry until 1525.
33
Latin. He wrote letters in German only to “laymen”—nobles and burghers who were not members
of the clergy and had not studied at universities and Latin schools. Even though there were few of
these letters, they were important. Writing letters in German to Friedrich and other princes and
nobles was a good strategy for Luther. It help to build a personal connection with potentially
powerful allies. Writing in German allowed him to address them directly, instead of through their
secretaries had he written in Latin. This may have helped to create sympathy for him among the
princes he wrote but also deliberately reduced the status difference between a cleric and a layman,
an important principle of Luther's new theology. After all, Luther sought to abolish the priesthood
and eliminate the ontological superiority of the Catholic vocations over laypeople. In this sense,
he was practicing a radical innovation in his letter writing because according to Roman Catholic
norms priests were not supposed to engage in theological discussion with laypeople or address
them in vernacular languages.
The most important feature revealed Luther’s correspondence is that in most of the towns
included in Luther’s collected correspondence during this period there is a single exchange of
letters (see Figure 2). This pattern suggests a few wide bridges between Luther and friends and
supporters located in a few cities of the empire and many narrower bridging ties between Luther
and occasional correspondents in dispersed cities. These correspondents were a mix of
acquaintances, admirers, and antagonists, many of whom Luther never met in person. These
bridging ties may help to explain why, in both spatial and social terms, the reach of Luther’s
Wittenberg movement was surprisingly extensive during the early Reformation.
34
VI. Estimating the Relationship between Luther’s Network & Adoption of Protestantism
A. The Extensive Margin: The Effect of the Presence of Luther’s Network on the Reformation
To evaluate whether social ties to Luther affected the spatial diffusion of the early Reformation,
we code the various measures from Luther’s correspondence network up to the end of 1522. We
begin by examining the extensive margin—that is, the extent to which the presence of a town's
linkage to the Luther’s network affected the probability it would subsequently reform.
Our focus is the early Reformation up to 1530, the period in which religious reform was driven
by an urban social movement. We therefore estimate linear probability models predicting the
probability of adopting Protestantism by 1530.22 The dependent variable is coded 1 for cities that
are Protestant in 1530 and 0 otherwise.23 We include numerous measures, drawn from Luther’s
correspondence network, to capture relational diffusion. First, we measure the presence of a tie-
alter in a given city as a proxy for bridging ties through an indicator variable for a city being linked
to Luther through at least one correspondent. Second, we provide a variable indicating whether
Luther ever visited the city in question. Third, we measure whether a town ever printed a work of
Luther’s prior to 1523. Fourth, we provide an indicator variable which takes a value of 1 if any of
Luther’s students came from the town in question.
We also control for numerous co-variates that could be related to the diffusion of the
Reformation. In order to control for the possible effect of printing as a mechanism of informational
diffusion (Rubin 2014; Dittmar and Seabold 2019), we include an indicator variable for the
presence of a printing press in a city prior to 1500. We control for possible spatial diffusion by
22 In the Appendix, we report the same specifications estimated using probit models. Results are largely similar in
terms of both magnitude and statistical significance. 23 In Rubin (2014), this variable was coded from historical atlases and the Catholic Encyclopedia. A city receives a
value of 1 “if it accepted the Augsburg Confession, Catholics were forced to flee, or the [Catholic] encyclopedia
explicitly states the Protestantism was accepted” (Rubin 2014, p. 283).
35
including the log distance from Wittenberg and Zurich to a given city (Becker and Woessmann
2009; Cantoni 2012; Pfaff and Corcoran 2012). As in Rubin (2014), we control for numerous city-
level characteristics, including the log of the city’s population in 1500, its market potential in 1500,
and indicators for whether it was an independent city, had a university in 1450, had a bishop in
1517, was under the rule of a lay magnate, whether it is on water dummy, and whether it was a
member of the Hanseatic League. We also include imperial circle fixed effects in each of the
regressions.24 In other words, we test the following regressions specification, for each city i in
imperial circle j:25
Prob(city Protestant by 1530ij) = β0 + β1Luther_Networkij + βXij + Dj + εij, (1)
where Luther_Networkij is one of the various measures of Luther’s network noted above, Xij is a
vector of controls, and Dj are imperial circle fixed effects.
Table 2 reports marginal effects on the linear probability model coefficients of various tests of
the specification presented in equation (1). 26 We find that the ties revealed by Luther’s
correspondence are broadly positively associated with the adoption of the early Reformation.
Results reported in column (1) indicate that cities which Luther corresponded with were 28
percentage points more likely than other cities to adopt the Reformation by 1530, all else being
equal (p = 0.01). This supports our proposition that personal ties linking the Wittenberg movement
through Luther to a town would increase the probability that the town would adopt the Reformation
24 Much of the Holy Roman Empire was split into six Imperial Circles in 1500, and most of the remainder was split
into four Imperial Circles in 1512. 25 All regressions are clustered at the level of the local territory. 26 For the sake of brevity, we only present the coefficients of interest. Full results are available upon request.
36
by 1530. It suggests the importance of the bridging ties identified by Granovetter (1973) and Burt
(1992, 2005) in the diffusion of Protestantism.
Next, in column (2) we find that the association between Luther’s letters and Reformation
adoption was primarily driven by letters written in Latin. These letters were mainly written to
Churchmen, suggesting that Luther’s network may have been more important for convincing
people within the Church to adopt. This is not surprising; it is well known that traveling priests
were among the most important sources of Protestant propaganda in the early Reformation (Blickle
1984). In column (3), [TBD]
Results in column (4) indicate that the presence of a Luther correspondent in a city is strongly
associated with its probability of adopting Protestantism by 1530. Towns that Luther visited were
41 percentage points more likely to adopt the Reformation by 1530, all else being equal (p < 0.01).
Similarly, towns that printed Luther’s works were 16 percentage points more likely to adopt the
Reformation (p < 0.10, see column (5)), and towns that sent students to study with Luther were 13
percentage points more likely to adopt the Reformation (p < 0.05, see column (6)).
In column (7), we run a “horse race” between the various Luther network dummy variables.
Not surprisingly, given the multicollinearity among the variables, the magnitudes of the
coefficients for each of the variables decreases. Nonetheless, two of the four network dummies
retain statistical significance. The presence of a Luther visit is most highly associated with
adoption of the Reformation: towns receiving a visit were 31 percentage points more likely to
adopt the Reformation by 1530 (p < 0.05). The presence of a Luther letter (16 percentage points
more likely to adopt the Reformation, p < 0.10) is also statistically significantly associated with
Reformation adoption. Only the coefficients on the presence of a Luther student and a Luther
printed work variable are statistically insignificant in the “horse race.” Finally, the first component
37
of the principal components of all four Luther variables enters positively and strongly significantly
(p < 0.001). This provides further support that Luther’s network, as captured by our four variables
laid out above, is associated with the early adoption of the Reformation.
Table 2: Determinants of Reformation Adoption by 1530, the Extensive Margin
(1) (2) (3) (4) (5) (6) (7) (8)
Dependent Variable: Protestant by 1530
Luther letter dummy 0.28** 0.16*
(0.11) (0.09)
Luther letter in Latin dummy 0.32***
(0.11)
Luther letter in German dummy -0.01
(0.15)
Luther letter sent to burgher dummy
Luther letter sent to Church figure dummy
Luther letter sent to political figure dummy
Luther visit by 1522 dummy 0.41*** 0.31**
(0.15) (0.14)
Luther printed works dummy 0.16* 0.07
(0.08) (0.08)
Luther students dummy 0.13** 0.09
(0.06) (0.05)
First principal component of Luther 0.10***
variables (0.03)
City-level controls YES YES YES YES YES YES YES YES
Imperial Circle F.E. YES YES YES YES YES YES YES YES
Observations 300 300 300 300 300 300 300 300
No. of Clusters 138 138 138 138 138 138 138 138
R-squared 0.33 0.33 0.34 0.30 0.30 0.37 0.36 Notes: ***p < 0.01, **p < 0.05, *p < 0.1. Linear probability model, robust standard errors clustered by territory in parentheses. The cities Wittenberg, Mainz,
and Zurich are dropped in all regressions. All regressions include a constant term (not reported). City level controls include dummies for the printing press,
independent city, university, bishop, lay magnate, on water, Hanseatic league, and log of population in 1500, market potential in 1500, log distance to Wittenberg, and log distance to Zurich. In all regressions, Imperial Circle fixed effects include Austria, Bavaria, Bohemia, Burgundy, Electorate, Franconia,
the Italian States, Lower Saxon, Swabia, Upper Rhenish, and Westphalia.
B. The Intensive Margin: The Effect of the Depth of Luther’s Network on the Reformation
We proceed to measure the intensive margin of Luther’s network. In network terminology, we
seek to understand the possible effect of wide bridges of Luther’s network on the early adoption
of the Reformation. To this end, we re-estimate equation (1), replacing dummy measures of the
38
various Luther network variables with measures of the total interactions Luther had with a town.
In other words, we employ five “wide bridge” measures: the number of Luther letters, the number
of distinctive persons with whom Luther corresponded (number of tie-alters), the number of Luther
visits to a town, the number of Luther printed works, and the number of Luther’s students from a
town. We report results from these various specifications in Table 3.
The results reported in column (1) indicate that each letter Luther sent is associated with 2
percentage points greater probability of a town adopting the Reformation by 1530 (p < 0.0001).
This is not a trivial point estimate: of the 41 towns that received a Luther letter prior to 1523, 27
received at least 2 letters, 13 received at least 5, and 9 received at least 10. The results reported in
column (2) suggest that both letters in Latin and German are associated with Reformation adoption
(p < 0.01 for both). This is different from the extensive margin results, in which the presence of a
letter in German is not associated with Reformation adoption. This suggests the possibility that,
among the people Luther reached in the vernacular, the strength of the bridge mattered. The mere
presence of an alter did not affect the likelihood of Reformation adoption, but strong bridges
positively affected the probability of Reformation adoption.
Columns (3) and (4) provide further support for our proposition that Luther’s correspondence
furthered the spatial diffusion of Protestantism to the extent that he had multiple and repeated
contacts with people in a given town, increasing the probability of adoption possibly through the
mechanism of Centola’s wide bridges (Centola 2018; Centola and Macy 2007). For each unique
individual (tie alter) Luther corresponded with, a town had 9 percentage points higher probability
of a town adopting the Reformation (p < 0.01), while each of Luther’s visits is associated with 13
percentage points higher probability (p < 0.01). On the other hand, unlike on the extensive margin,
39
Luther’s printed works and students do not appear to be statistically related to Reformation
adoption on the intensive margin.
Table 3: Determinants of Reformation Adoption by 1530, the Intensive Margin
(1) (2) (3) (4) (5) (6) (7) (8)
Dependent Variable: Protestant by 1530
Number of Luther letters 0.02*** 0.01
(0.00) (0.01)
Number of Luther letters in Latin 0.02***
(0.00)
Number of Luther letters in German 0.05***
(0.02)
Tie alters 0.09***
(0.03)
Number of Luther visits 0.13*** 0.13**
(0.04) (0.06)
Number of Luther printed works 0.01 -0.27*
(0.15) (0.16)
Number of Luther students 0.01 0.00
(0.01) (0.01)
First principal component of Luther 0.05**
variables (0.02)
City-level controls YES YES YES YES YES YES YES YES
Imperial Circle F.E. YES YES YES YES YES YES YES YES
Observations 300 300 300 300 300 300 300 300
No. of Clusters 138 138 138 138 138 138 138 138
R-squared 0.31 0.31 0.32 0.33 0.29 0.29 0.34 0.31 Notes: ***p < 0.01, **p < 0.05, *p < 0.1. Linear probability model, robust standard errors clustered by territory in parentheses. The cities Wittenberg, Mainz,
and Zurich are dropped in all regressions. All regressions include a constant term (not reported). City level controls include dummies for the printing press, independent city, university, bishop, lay magnate, on water, Hanseatic league, and log of population in 1500, market potential in 1500, log distance to
Wittenberg, and log distance to Zurich. In all regressions, Imperial Circle fixed effects include Austria, Bavaria, Bohemia, Burgundy, Electorate, Franconia,
the Italian States, Lower Saxon, Swabia, Upper Rhenish, and Westphalia.
In column (7) we run a “horse race” between the various intensive margin measures of Luther’s
network. On the intensive margin, it appears that Luther’s visits are the most associated with
Reformation adoption: each visit is associated with a 13 percentage point higher probability of
Reformation adoption (p < 0.05), a result similar to the one found in column (4). In particular,
Luther’s visits appears to be more strongly associated with the Reformation than do Luther’s
letters; the latter are not statistically significant in the “horse race.” Interestingly, the number of
Luther’s printed works appears to be negatively correlated with Reformation adoption, although
40
this might be an artefact of the high degree of multicollinearity among the various network
variables. Finally, the first principal component of the intensive margin Luther variables enters
positively and significantly (p < 0.05, column (8)).
One issue with the Luther network variables is that Luther’s network was not random. There
must have been supply and demand side features that affected Luther’s network. We control for
most of the key demand side features: Luther was a churchman and a professor, and his network
included numerous churchmen and academics. By controlling for universities and bishoprics—as
well as numerous other marks of socio-economic status—we believe we have largely controlled
for potentially omitted demand-side variables. However, controls for the supply-side of Luther’s
network—determined by the cost of establishing such a network—are weak at best. While we
control for distance to Wittenberg and Zurich and employ Imperial Circle fixed effects, these do
not come close to fully accounting for the costs of establishing a network. Surely connecting with
individuals on or close to well-trodden travel paths was less expensive than connecting with people
in the hinterlands, even if the latter were closer as the crow flies. To address this issue, in the next
section we include in our analysis a network analysis using the roads of the Holy Roman Empire.
VII. Road Networks in the Holy Roman Empire
A. Establishing the road networks in the Holy Roman Empire
In reaching a causal interpretation of the relationship between Luther’s ties and the adoption of the
Reformation, an obvious problem arises in that the places Luther wrote to or visited may have
simply been more prone to the diffusion of innovations by virtue of their network position vis-à-
vis other towns. How do we know if Luther’s influence increased the odds of a town adopting the
Reformation net of its underlying structural vulnerability to diffusion? We address thus alternative
41
hypothesis of structural vulnerability to diffusion via including measures of town network
centrality, which capture the trade connectedness of towns. Towns with higher centrality indicate
that they are more exposed to other towns and thus are structurally prone to being exposed to the
Reformation. On the other hand, if effect of Luther’s letters or visits remains significant in a model
predicting reform when measures of a town’s network centrality are included, then we can have
greater confidence that the effect of Luther’s personal ties is not simply reflecting a towns
underlying vulnerability to relational diffusion.
To address this problem, we reconstructed the social network between a subset of cities in the
Holy Roman Empire as revealed by location on the contemporaneous regional and long-distance
(Fernhandelstrassen) European trade routes. Based on the historical atlases of Berthold (1976)
and Magocsci (2018), cities were coded as having a direct tie to another city if they occupied
adjoining positions on overland trade routes or if they could be reached directly through river
traffic or sea routes. The resulting network’s characteristics are described in Table 4 below, and
graphically depicted in Figure 6, revealing a global network which was relatively sparse, with
obvious evidence of regional clustering.27 Notably, Wittenberg appears on the periphery of the
graph, occupying a relatively parochial position in the trade route network.
Table 4: Descriptive statistics of the whole road network
Variable Value
Density 0.010
Transitivity 0.231
Number of cliques 1067
Mean distance 7.236
Diameter 18.0
27 In Figure 6, each circle is a city, while each line indicates a direct trade route. We label Wittenberg and cities that
are the highest ten in centrality (for any of the centrality measures).
42
Figure 5: Connections in the Road Network of the Holy Roman Empire
This structure squares with much of what we know about late medieval Central European
geography. Long-distance trade, particularly overland, was expensive and the road network was
underdeveloped. Medium-sized cities usually served as regional trading centers, generally spaced
from 20 to 35 miles apart. Shipping was cheaper, of course, and the larger Central European trading
centers tended to be located along navigable rivers or sea harbors (Nicholas 2003; Rozman 1978;
Russell 1972; Scott and Scribner 1996). Nevertheless, trade was expanding in the 16th century and,
as suggested by Wurpts et al. (2018), commercial exchange also generated economic, political and
social ties between cities which could have facilitated the spread of Protestant ideas.
We calculate degree, closeness, betweenness, and eigenvector centrality scores for each city in
the trade route network subsample which we then include in regression analyses predicting
adoption of the Reformation (see Table 5 for summary statistics of the network measures).28 Table
28 In network theory there are various ways of conceptualizing the most important actors in a network. Centrality
measures are a common way to estimate the social influence of a node based on its position within the network. A
Antwerp
Bruges
Hamburg
Amsterdam
Wittenberg
Edam
Enkhuizen
HoornKampen
Monnikendam
Naarden
43
6 reports the cities with the greatest values across these different measures, revealing clear
consistency across them. It is noteworthy, that many of the most central cities in our sample were
on the North Sea or at the mouth of the Rhine, where commercial development, urban density,
trade route intersections, and access to river and seas apparently exerted strong influence on the
structure of the network.
Table 5: Summary Statistics, Network Measures
Standard
Variable Mean Deviation
Degree 3.38 0.13
Closeness (x1000) 0.22 0.00
Betweenness (/1000) 1.05 0.12
Eigenvector 0.05 0.01
N = 286.
Table 6: Top Ten Centralities in the Holy Roman Empire for each Network Measure
Degree Closeness Betweenness Eigenvector
Antwerp Hamburg Hamburg Amsterdam
Amsterdam Bruges Bruges Kampen
Hamburg Antwerp Antwerp Edam
Bruges Amsterdam Amsterdam Hoorn
Kampen Kampen Kampen Monnikendam
Naarden Naarden Naarden Naarden
Edam Edam Edam Bruges
Hoorn Hoorn Hoorn Hamburg
Monnikendam Monnikendam Monnikendam Enkhuizen
Enkhuizen Enkhuizen Enkhuizen Antwerp
B. Regression Analysis with Network Data
These measures of the Holy Roman Empire road network help address an important omitted
variable in the previous analysis: the cost of travel. There is reason to believe that this cost could
central actor can be one thought of as one with many ties others (degree centrality), closest in path distance to others
(closeness), who lies on the shortest path between any two nodes (betweeness) and who has ties to other central actors
(eigenvector). For elaboration of these concepts see Borgatti 2005; Freeman 1979; and Wasserman and Faust 1995,
Chapter 5; for application to the study of religious groups, see Everton 2018.
44
have affected both Luther’s network and, independently, the spread of the Reformation. Indeed,
the cost of travel is an omitted variable whose absence likely upwardly biased the coefficients on
the regressions presented in Section VI. In this section, we include various network variables in
our analyses to address this issue.
The results reports in Table 7 reveal that the inclusion of various network parameters does not
much affect the results reports in Table 2 and Table 3. First, consider the upper panel, which reports
the regressions on the extensive margin.29 Nearly all the coefficients on the Luther network
variables are smaller, although not necessarily significantly smaller, than their counterparts in
Table 2. In columns (1)-(4), the Luther network variables all enter positively and significantly.
Depending on the metric used, the presence of Luther’s influence is associated with a 14-32
percentage point larger probability of a city becoming Protestant by 1530. As in Table 2, the Luther
visit coefficient is the largest of the Luther network coefficients in the horserace regression
(column (5)), although it is not statistically significant. Only the Luther letter and students
dummies enter the horserace regressions as statistically significant. It is not surprising that the
inclusion of road network characteristics decreases the coefficient on Luther visits more than the
other variables: the road network almost certainly impinged on the cost of a Luther visit more than
any of the other features of Luther’s network. Finally, also as in Table 2, the first principal
component is strongly statistically related to early adoption of the Reformation.
29 These regressions include all of the network variables. Results are very similar in terms of magnitude and statistical
significance if we include just one of any of the four network variables. Results are available upon request.
45
Table 7: Determinants of Reformation Adoption by 1530, including Network Variables
(1) (2) (3) (4) (5) (6)
Dependent Variable: Protestant by 1530
Extensive Margin
Luther letter dummy 0.25** 0.16*
(0.12) (0.10)
Luther visit by 1522 dummy 0.32** 0.21
(0.16) (0.14)
Luther printed works dummy 0.14* 0.08
(0.08) (0.07)
Luther students dummy 0.15** 0.11*
(0.07) (0.06)
First principal component of Luther 0.09***
Variables (0.03)
Degree 0.02 0.03 0.03 0.02 0.02 0.02
(0.02) (0.02) (0.02) (0.02) (0.02) (0.02)
Closeness (x1000) -0.37 -0.15 -0.32 -0.33 -0.37 -0.40
(1.06) (1.06) (1.06) (1.11) (1.11) (1.08)
Betweenness (/1000) 0.01 0.01 0.01 0.02 0.01 0.01
(0.02) (0.02) (0.02) (0.02) (0.02) (0.02)
Eigenvector -0.03 -0.06 -0.10 -0.11 -0.01 -0.01
(0.16) (0.16) (0.15) (0.15) (0.18) (0.18)
Intensive Margin
Number of Luther letters 0.02*** 0.01*
(0.00) (0.01)
Number of Luther visits 0.10** 0.09
(0.05) (0.07)
Number of Luther printed works -0.05 -0.28*
(0.13) (0.15)
Number of Luther students 0.01 0.00
(0.01) (0.01)
First principal component of Luther 0.04
Variables (0.02)
Degree 0.02 0.02 0.03 0.03 0.02 0.02
(0.02) (0.02) (0.02) (0.02) (0.02) (0.02)
Closeness (x1000) -0.04 -0.07 -0.24 -0.17 0.13 -0.11
(1.10) (1.09) (1.06) (1.10) (1.13) (1.10)
Betweenness (/1000) 0.01 0.01 0.02 0.01 0.01 0.01
(0.02) (0.02) (0.02) (0.02) (0.02) (0.02)
Eigenvector -0.05 -0.07 -0.13 -0.10 -0.05 -0.06
(0.15) (0.15) (0.14) (0.14) (0.15) (0.16)
City-level controls YES YES YES YES YES YES
Imperial Circle F.E. YES YES YES YES YES YES
Observations 262 262 262 262 262 262
No. of Clusters 129 129 129 129 129 129 Notes: ***p < 0.01, **p < 0.05, *p < 0.1. Linear probability model, robust standard errors clustered by territory in parentheses.
The cities Wittenberg, Mainz, and Zurich are dropped in all regressions. All regressions include a constant term (not reported). City level controls include dummies for the printing press, independent city, university, bishop, lay magnate, on water, Hanseatic league,
and log of population in 1500, market potential in 1500, log distance to Wittenberg, and log distance to Zurich. In all regressions,
Imperial Circle fixed effects include Austria, Bavaria, Bohemia, Burgundy, Electorate, Franconia, the Italian States, Lower Saxon, Swabia, Upper Rhenish, and Westphalia.
46
The bottom panel of Table 7 reports regressions focusing on the intensive margin. The results
are quite similar to results reported in Table 3. One key difference between these results and those
in Table 3 is that the coefficient on number of Luther letters is positive and significant (p < 0.10)
in the horserace regression (column (5)). The rest of the coefficients in the horserace are smaller
and of similar significance to those reported in Table 3. Moreover, the first principal component
is not statistically significant (p = 0.14). However, in (unreported) regressions in which the first
two components enter as independent variables, the first component is positively and significantly
related to early adoption of the Reformation (p = 0.054).
VIII. The Effect of Luther’s Network via Network Contagion Simulation
The analyses in the previous two sections included controls for numerous city-specific features
that might have affected the adoption of the Reformation (and the spread of Luther’s network). If
these regressions were perfectly specified without any omitted variables, we could interpret the
coefficients on the Luther network coefficients causally. Unfortunately, this is unlikely to be the
case. Luther’s network—even prior to 1523—was not random. We address this issue in this and
this section by posing counterfactuals via simulations that help isolate Luther’s influence on the
spread of the Reformation.
Simulations have been widely used in the social sciences (e.g., Centola 2018; Heckathorn
1993; Macy 1990), as they bear two advantages. First, simulations can help test causal effects, as
the researcher can arbitrary “turn on” or “turn off” factors and examine subsequent outcomes
without worrying about confounding. Second, simulations allow for interdependent processes
between factors that are not easily captured by regression analyses. For instance, suppose Luther
converted city A, and via trade routes city A converted two additional cities B and C, then B and
47
C further converted cities D, E, and F. This snowballing effect originating from Luther’s influence
is a path dependent process that is not revealed through conventional regression analyses.
Following recent research on contagion processes of social phenomena (Centola 2018; Centola
and Macy 2007), we use an epidemiological approach to study the spread of the Reformation. We
imagine the Reformation as a “disease” emanating from Wittenberg. We consider two possible
routes through which it might spread. The first is a trade network in the Holy Roman Empire,
which also captures routes of transportation or migration via space. This is also the trade network
used to calculate the centrality measures in the previous section. Second, we construct Luther’s
influence network, defined as a link between Wittenberg and the city if Luther wrote a letter to a
recipient in the city, personally visited the city, or had a student present in the city. We identified
these three factors from the regression analyses.
The basic unit of analysis is a city. Each city, either adopts or does not adopt the Reformation
according to a decision rule based on the cities it is connected to via the network(s). We then
calculate the number of cities that adopted the Reformation in equilibrium (i.e., until no cities
further change their adoption status), and compare this to the actual historical number. Thus, the
final number of adopted cities depends on (1) the decision rule and (2) the configuration of the
network(s). In our dataset, 59 cities adopted the Reformation by 1530, so the target of the
simulations would be to recover this number as close as possible. If our simulations predict much
fewer adopted cities, then it is plausible that we are not capturing the correct diffusion mechanisms.
Likewise, if our simulations predict many more adopted cities than the actual value, then we are
probably not capturing the correct diffusion mechanisms either.
There are two major differences between our simulations and previous research on diffusion
(e.g., Centola 2018; Heckathorn 1993; Macy 1990). First, previous research often conducted the
48
simulations in hypothetical networks and experimented with structural network factors such as
density or transitivity. In our simulations, instead of hypothetical networks we draw from empirical
networks constructed from historical sources, and thus the structural characteristics of the networks
are fixed. Second, previous research studied diffusion in a single network and a single decision
rule.30 In contrast, we conceptualize the diffusion process as the interaction of multiplex networks
and multiple decision rules. In other words, both the trade network and the Luther network may
contribute to the spread of the Reformation, and the decision rule for the trade network and the
Luther network may differ. We argue that the dynamic process of multiplex networks and multiple
decision rules are critical for understanding the spread of social behavior.
The goal of the simulations is to examine how Luther’s influence altered the number of cities
adopting the Reformation. Luther’s influence had two potential pathways. First, Luther broadened
the reach of the Reformation, as more cities that were not connected to Wittenberg via trade routes
were connected to the Reformation movement via Luther’s network. Second, Luther may have
been particularly “infectious,” as we showed in the regressions that Luther’s contact significantly
increased the odds of adoption. In other words, Luther may not only have had a wide range of
contacts, but he was very effective at persuading these contacts to adopt the Reformation.
For each scenario, we run the simulation procedure as follows.
1. Following Centola (2018), we setup Wittenberg and its neighbors connected via trade, and
the neighbors of neighbors to adopt the Reformation (with a total of 7 cities). This provides
an initial cluster that solidifies the initial basis of diffusion.
2. Depending on the scenario, the decision rule for subsequent adoption will change. For each
iteration, each city will either adopt or remain unadopted depending on the decision rule.
30 This refers to each simulation run. The network and decision rule may vary across different simulations.
49
Also, once a city adopts the Reformation, it cannot revert to the unadopted status. We make
this assumption because we find no evidence of reversion (prior to 1530) in our data.
3. We run the simulation until we achieve an equilibrium (i.e., no cities change their adoption
status) and calculate the number of cities adopted.
4. Since each simulation is a stochastic process, the outcome would be slightly different for
each simulation. We replicate the simulations 50 times and calculate the average number
of cities which adopted the Reformation
5. We compare the average number of cities adopted to the actual number of cities adopted
by 1530, which is 59 cities. The simulations should attempt to recover this number.
We consider four counterfactual scenarios in the simulations:
Scenario 1: Spatial diffusion via trade routes
In this scenario, the Reformation spreads from the Wittenberg cluster via spatial diffusion. The
network is the trade network. The decision rule is a minimal complex contagion with threshold
equal two (Centola 2018). If two cities connected to the focal city adopt the Reformation, the focal
city adopts also. Otherwise, the focal city remains unadopted.
Scenario 2: Spatial diffusion with additional connections by Luther, but Luther is not infectious
In this scenario, in addition to the trade network, we add connections to Wittenberg via Luther’s
influence. This scenario examines Luther’s influence on broadening the reach of the movement,
but not the “infectiousness” of Luther. The network is the trade network plus additional
connections to Wittenberg via Luther’s influence. In other words, we merge the trade network and
Luther’s network into one network. The decision rule the same as above. If two cities connected
50
to the focal city adopt the Reformation, the focal city adopts also. Otherwise, the focal city remains
unadopted.
Scenario 3: The infectious Luther, but no spatial diffusion
In contrast to Scenario 2, in this scenario we investigate the infectiousness of Luther but without
the spatial diffusion process. The network is the Luther network. To address the infectiousness of
Luther, we assign a parameter Infect P to construct the decision rule.31 For the cities influenced by
Luther, with probability Infect P the city adopts the Reformation.
Scenario 4: The infectious Luther with spatial diffusion
This scenario considers the interaction between the infectious Luther via Luther’s network, and
spatial diffusion via the trade network. The networks are the trade network and the Luther network.
There are two sets of decision rules, each for different networks. For the trade network we again
apply the decision rule of minimal complex contagion of threshold two. For the infectious Luther
we again assign the parameter Infect P and the associated decision rule.
Results for Scenario 1
For Scenario 1, the average number of adopted cities is 7, which is exactly the cities we initially
set up to adopt. This number is far below the target number of 59 in the data. In other words, a
theory of complex contagions via space is not supported. This is because Wittenberg and its
surrounding cities are isolated in the periphery with very few connections to other cities. Unlike
31 This single parameter is a simplification of the true process, as we treat equally cities that Luther visited one time
and cities Luther visited multiple times. However, the theoretical goal is to examine if a small probability of
infectiousness under one single contact (Luther) creates insight on the diffusion process of the Reformation.
51
the present, when modern communication tools allow many connections between cities, during the
16th century cities had far fewer contacts, which were mainly built through trade routes that ran
through limited road and sea paths. Thus, there was not enough social reinforcement to form “wide
bridges” (Centola 2018) to further the spread of the Reformation. Under this scenario, the
Reformation would remain a regional sect surrounding Wittenberg and not spread as a large
movement.
Results for Scenario 2
For Scenario 2, the average number of adopted cities is still 7, which is exactly the cities we
initially set up to adopt. The reason is because these additional connections to Wittenberg are all
structurally weak ties that do not benefit complex contagions. Adding another source of contact
from Wittenberg does not spread the Reformation because there are no other sources of
reinforcement to persuade the connected cities to adopt the Reformation. This would still render
the Reformation a regional sect.
From Scenario 1 and Scenario 2, it appears that structurally there is no pathway for the
Reformation to diffuse far beyond Wittenberg. From the theory of complex contagions (Centola
2018; Centola and Macy 2007), a significant behavioral change such as adopting a new religion
would require multiple contacts to activate. It seems that the Reformation is trapped under these
circumstances. However, in the following scenarios we show that this structural trap can be
overcome by Luther’s infectiousness.
52
Results for Scenario 3
In this scenario, depending on the parameter Infect P, the average number of adopted cities differ,
as seen in Table 7. Overall, even with a small probability of infectiousness, the number of adopted
cities exceeds far beyond the results in Scenario 1 and Scenario 2. However, for the target number
of 59 cities to adopt, the infectious probability would have to be as high as 50%, which indicates
that one in two cities influenced by Luther would adopt. This probability is too high and not
supported by the data. According to the data only 38% of the cities with Luther's influence adopted,
which predicts that fewer than 50 cities would adopt.
Table 7. Average number of adopted cities by Luther’s infectiousness.
Infect P Number of adopted cities
0.1 17.54
0.2 27.50
0.3 39.08
0.4 50.24
0.5 60.82
0.6 71.66
0.7 81.22
Results for Scenario 4
Again in this scenario, depending on the parameter Infect P, the average number of adopted cities
differ, as seen in Table 8. When subsequent spatial diffusion after Luther’s infectiousness, Luther’s
infectiousness does not need to be as high in order for the movement to spread. The infectious
probability of 30% predicts a number close to the target number of 59. This scenario is the most
plausible.
53
Thus, the diffusion of the early Reformation appears to be a two stage process. First, Luther
infected a certain proportion of the cities in which he had influence in, and then because of the
spatial structure of these adopted cities, these cities created local social reinforcement to persuade
other cities to further adopt, even if they were not directly under Luther's influence. Luther did not
randomly target cities, but strategically selected cities that were connected to one another so that
he could create a "cluster activation" that is critical for complex contagions to further spread via
space. This created a snowball effect that raised the number of adopted cities from 39 (see Table
7) to around 60 (see Table 8). In other words, it is the interaction of multiplex networks (trade and
Luther) via multiple diffusion processes (complex contagion and Luther’s infectiousness) that
jointly facilitated the spread of the early Reformation.
Table 8. Average number of adopted cities by Luther’s infectiousness (spatial diffusion included).
Infect P Number of adopted cities
0.1 23.62
0.2 43.92
0.3 61.06
0.4 77.78
0.5 90.94
0.6 104.48
0.7 118.38
54
Figure 7. Plot of networks and Reformation adoption
Note: grey nodes are cities that did not adopt the Reformation, red nodes are cities that adopted the Reformation. The
lines between nodes indicate trade routes. Square nodes are cities that Luther influenced (also labeled by text), while
circle nodes are cities Luther did not influence.
We check our hypothesis from the simulations via a visual diagnosis. We plot the trade network,
Luther’s influence, and whether the city adopted in Figure 7. If our theory is right, we should
expect to see cities that Luther influenced to be more likely to adopt. We should also expect these
cities to be connected to one another as dyads, triads, or even small clusters. This is what we
observe. We see that a high proportion of square nodes (cities Luther influenced) are also red nodes
55
(cities that adopted the Reformation). Furthermore, the red nodes tend to connect as clusters, such
as the Bremen cluster in the bottom left of the plot, the Rostock cluster in the bottom of the plot,
and the Erfurt cluster in the top of the plot. In these clusters there are many circle red nodes,
indicating that although they were not directly influenced by Luther, they were indirectly
influenced by Luther by being connected to cities Luther visited via trade routes. All the evidence
further supports Scenario 4, and thus our theory of multiplex networks and multiple diffusion
processes.
IX. Content Analysis of Luther’s Letters and the Supply and Demand of the Reformation
TBD.
X. Discussion
Luther has often been treated as a “great man” in past historiography. For instance, he was “the
Great Man as Priest,” according to Thomas Carlyle’s influential book on the role of the heroic in
history (Carlyle 1841, lecture IV). We should make clear, however, that we do not claim that
Luther’s actions or beliefs were “great” in the normative sense. Whatever his talents, Luther was
notoriously intolerant and anti-Semitic, and this legacy remained in the Protestant lands well
beyond his death (Becker and Pascali 2019).
Our analysis contributes to numerous literatures. First, our results provide more evidence in
favor of the role that “superstars” can play in determining social outcomes. We do so in the context
of one of the most important movements in the Western world over the last millennium. Second,
our results have implications for the growing literature on the causes and consequences of the
Reformation (Becker et al. 2016). While our analysis does not dismiss the previous contributions
56
to our understanding of the Reformation’s spread, it provides new insight into one of its key causes
that was long considered important by historians, but until now was not substantiated with
systematic empirical evidence. It also provides evidence for why the “distance to Wittenberg”
instrument for the Reformation, pioneered by Becker and Woessmann (2009), works. The idea
behind the instrument is that the Reformation spread out from Wittenberg, an otherwise
unimportant city. Our findings suggest why this was the case: the early adoption of the
Reformation was especially likely in what one may think of as “Lutherland”—the areas of
Germany proximate to Wittenberg. This is because Luther’s social network was knit through
personal ties forged through his correspondence and personal journeys. Although Luther did make
more extensive ties, all else equal, they were more likely to link him to towns near Wittenberg. At
the same time, our analysis shows why the early spread of the Reformation was not confined to
Lutherland: his ties to more distant correspondents and his travels during which he recruited
friends and supporters beyond his neighborhood, bridged structural holes between the Wittenberg
movement and more distant locations. This planted seeds from which the Reformation could
spread more rapidly after political opportunities expanded after 1530.
Finally, our findings contribute to the long-dormant debate on the “great (wo)man” theory of
history. We by no means wish to claim that “great people” are the true drivers of history. Yet, our
analysis suggests that going too far in the opposite direction—i.e., claiming that individuals do not
matter for historical processes—may also by foolhardy.
It is hardly worth noting that the German Reformation began with Luther and that he was the
towering figure in the development and spread of the new theology. However, when we consider
the characteristics of his alters, there is good reason to think of Luther’s correspondence as
indicative of an opinion-leader network in which Luther, the clear leader of the Reformation during
57
this period, corresponded frequently with other potential opinion leaders across the empire. Some
of these correspondents were antagonists and foes, but many more were potential allies. Even so,
Luther was the unmistakable leader of the early Reformation. He was its intellectual visionary—
its ideological entrepreneur—developing a new theology informed by Biblical Humanism and
refashioning Wittenberg University, thereby making it an exciting center of learning and reform.
He was the Protestant movement’s first political hero who openly defied the emperor and the pope
and survived to tell of it. That much is well known, but our paper shows that Luther was an
ideological entrepreneur of uncommon skill. In the years immediately before and after 1517,
Luther developed and learned to exploit his social capital, that is, “the advantage created by a
person’s location in a structure of relationships” (Burt 2005, p. 4). Through an extensive
correspondence, he cultivated relationships with theologians, humanist intellectuals, prelates of
the Church, influential burghers, and noblemen. Many were converted to his heterodox thinking
through their ties with Luther and enlisted as proponents of reform, creating pockets of supporters
in cities across the empire.
The early diffusion of the Reformation suggests that, in addition to being driven by the efficient
spread of information through printing press, it was propelled by complex diffusion facilitated by
the moderate social consolidation of the self-governing towns of the Holy Roman Empire and the
cross-cutting social ties made by Luther. Social structures of this kind provide enough social
homophily to create meaningful collective identities without being so cohesive as to eliminate
extra-local ties. Deliberate social action, such as Luther’s correspondence with influential people
outside of academic and theological circles, may have succeeded in reducing network
consolidation by increasing the number of cross-cutting ties across social circles. This created the
bridging ties that enhanced social diffusion.
58
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APPENDIX
Table A. 1: Determinants of Reformation Adoption by 1530, the Extensive Margin, Probit Model
(1) (2) (3) (4) (5) (6) (7) (8)
Dependent Variable: Protestant by 1530
Luther letter dummy 0.31** 0.15*
(0.10) (0.08)
Luther letter in Latin dummy
Luther letter in German dummy
Luther letter sent to burgher dummy
Luther letter sent to Church figure dummy
Luther letter sent to political figure dummy
Luther visit by 1522 dummy 0.40*** 0.29**
(0.12) (0.11)
Luther printed works dummy 0.22** 0.11
(0.10) (0.09)
Luther students dummy 0.17*** 0.12**
(0.06) (0.06)
First principal component of Luther 0.11***
variables (0.02)
City-level controls YES YES YES YES YES YES YES YES
Imperial Circle F.E. YES YES YES YES YES YES YES YES
Observations 193 193 193 193 193 193 193 193
No. of Clusters 103 103 103 103 103 103 103 103
pseudo R-squared 0.25 0.27 0.21 0.22 0.31 0.31 Notes: ***p < 0.01, **p < 0.05, *p < 0.1. Robust standard errors clustered by territory in parentheses. Average marginal effects of probit coefficients reports
for all regressions. The cities Wittenberg, Mainz, and Zurich are dropped in all regressions. City-level controls are the same as those used in previous regressions. All regressions include a constant term (not reported). Distance to Wittenberg and Zurich are in miles. In all regressions, Imperial Circle fixed
effects include Austria, Bavaria, Bohemia, Burgundy, Electorate, Franconia, the Italian States, Lower Saxon, Swabia, Upper Rhenish, and Westphalia.
64
Table A. 2: Determinants of Reformation Adoption by 1530, the Intensive Margin, Probit Model
(1) (2) (3) (4) (5) (6) (7) (8)
Dependent Variable: Protestant by 1530
Number of Luther letters 0.02** 0.01
(0.01) (0.01)
Number of Luther letters in Latin
Number of Luther letters in German
Tie alters 0.09***
(0.03)
Number of Luther visits 0.14*** 0.13***
(0.04) (0.05)
Number of Luther printed works 0.00 -0.28*
(0.11) (0.14)
Number of Luther students 0.01 0.00
(0.01) (0.01)
First principal component of Luther 0.04**
variables (0.02)
City-level controls YES YES YES YES YES YES YES YES
Imperial Circle F.E. YES YES YES YES YES YES YES YES
Observations 193 193 193 193 193 193 193 193
No. of Clusters 103 103 103 103 103 103 103 103
pseudo R-squared 0.23 0.23 0.25 0.20 0.20 0.27 0.22 Notes: ***p < 0.01, **p < 0.05, *p < 0.1. Robust standard errors clustered by territory in parentheses. Average marginal effects of probit coefficients reports for all regressions. The cities Wittenberg, Mainz, and Zurich are dropped in all regressions. City-level controls are the same as those used in previous
regressions. All regressions include a constant term (not reported). Distance to Wittenberg and Zurich are in miles. In all regressions, Imperial Circle fixed
effects include Austria, Bavaria, Bohemia, Burgundy, Electorate, Franconia, the Italian States, Lower Saxon, Swabia, Upper Rhenish, and Westphalia.
65
Table A. 3: Determinants of Reformation Adoption by 1530, the Extensive Margin, de facto Holy
Roman Empire only
(1) (2) (3) (4) (5) (6) (7) (8)
Dependent Variable: Protestant by 1530
Luther letter dummy 0.32*** 0.19*
(0.12) (0.10)
Luther letter in Latin dummy
Luther letter in German dummy
Luther letter sent to burgher dummy
Luther letter sent to Church figure dummy
Luther letter sent to political figure dummy
Luther visit by 1522 dummy 0.44*** 0.33**
(0.16) (0.14)
Luther printed works dummy 0.17* 0.10
(0.09) (0.08)
Luther students dummy 0.13* 0.07
(0.07) (0.07)
First principal component of Luther 0.11***
variables (0.03)
City-level controls YES YES YES YES YES YES YES YES
Imperial Circle F.E. YES YES YES YES YES YES YES YES
Observations 226 226 226 226 226 226 226 226
No. of Clusters 112 112 112 112 112 112 112 112
R-squared 0.31 0.33 0.27 0.28 0.36 0.35 Notes: ***p < 0.01, **p < 0.05, *p < 0.1. Linear probability model, robust standard errors clustered by territory in parentheses. The cities Wittenberg, Mainz,
and Zurich are dropped in all regressions. All regressions include a constant term (not reported). City level controls include dummies for the printing press,
independent city, university, bishop, lay magnate, on water, Hanseatic league, and log of population in 1500, market potential in 1500, log distance to Wittenberg, and log distance to Zurich. In all regressions, Imperial Circle fixed effects include Austria, Bavaria, Bohemia, Burgundy, Electorate, Franconia,
the Italian States, Lower Saxon, Swabia, Upper Rhenish, and Westphalia.
66
Table A. 4: Determinants of Reformation Adoption by 1530, the Intensive Margin, de facto Holy
Roman Empire only
(1) (2) (3) (4) (5) (6) (7) (8)
Dependent Variable: Protestant by 1530
Number of Luther letters 0.02*** 0.01
(0.00) (0.01)
Number of Luther letters in Latin
Number of Luther letters in German
Tie alters 0.10***
(0.04)
Number of Luther visits 0.14*** 0.16***
(0.05) (0.06)
Number of Luther printed works -0.05 -0.36**
(0.13) (0.16)
Number of Luther students 0.01 0.00
(0.01) (0.01)
First principal component of Luther 0.04*
variables (0.02)
City-level controls YES YES YES YES YES YES YES YES
Imperial Circle F.E. YES YES YES YES YES YES YES YES
Observations 226 226 226 226 226 226 226 226
No. of Clusters 112 112 112 112 112 112 112 112
R-squared 0.29 0.30 0.31 0.26 0.27 0.34 0.29 Notes: ***p < 0.01, **p < 0.05, *p < 0.1. Linear probability model, robust standard errors clustered by territory in parentheses. The cities Wittenberg, Mainz,
and Zurich are dropped in all regressions. All regressions include a constant term (not reported). City level controls include dummies for the printing press,
independent city, university, bishop, lay magnate, on water, Hanseatic league, and log of population in 1500, market potential in 1500, log distance to Wittenberg, and log distance to Zurich. In all regressions, Imperial Circle fixed effects include Austria, Bavaria, Bohemia, Burgundy, Electorate, Franconia,
the Italian States, Lower Saxon, Swabia, Upper Rhenish, and Westphalia.
67
Table A. 5: Determinants of Reformation Adoption by 1530, including Network Variables, Probit
Model
(1) (2) (3) (4) (5) (6)
Dependent Variable: Protestant by 1530
Extensive Margin
Luther letter dummy 0.27** 0.15*
(0.11) (0.09)
Luther visit by 1522 dummy 0.33*** 0.20*
(0.12) (0.11)
Luther printed works dummy 0.21** 0.11
(0.09) (0.09)
Luther students dummy 0.21*** 0.16**
(0.08) (0.07)
First principal component of Luther 0.10***
variables (0.02)
Intensive Margin
Number of Luther letters 0.02** 0.02**
(0.01) (0.01)
Number of Luther visits 0.11** 0.08*
(0.04) (0.05)
Number of Luther printed works -0.04 -0.32**
(0.10) (0.14)
Number of Luther students 0.01 0.00
(0.01) (0.01)
First principal component of Luther 0.04*
variables (0.02)
Network variables YES YES YES YES YES YES
City-level controls YES YES YES YES YES YES
Imperial Circle F.E. YES YES YES YES YES YES
Observations 166 166 166 166 166 166
No. of Clusters 98 98 98 98 98 98 Notes: ***p < 0.01, **p < 0.05, *p < 0.1. Robust standard errors clustered by territory in parentheses. Average marginal effects of
probit coefficients reports for all regressions. The cities Wittenberg, Mainz, and Zurich are dropped in all regressions. City-level controls are the same as those used in previous regressions. All regressions include a constant term (not reported). Distance to
Wittenberg and Zurich are in miles. In all regressions, Imperial Circle fixed effects include Austria, Bavaria, Bohemia, Burgundy,
Electorate, Franconia, the Italian States, Lower Saxon, Swabia, Upper Rhenish, and Westphalia.
68
Table 8: Determinants of Reformation Adoption by 1530, including Network Variables, de facto
Holy Roman Empire only
(1) (2) (3) (4) (5) (6)
Dependent Variable: Protestant by 1530
Extensive Margin
Luther letter dummy 0.30** 0.20*
(0.12) (0.10)
Luther visit by 1522 dummy 0.37** 0.24*
(0.16) (0.13)
Luther printed works dummy 0.16* 0.10
(0.09) (0.08)
Luther students dummy 0.16** 0.10
(0.08) (0.07)
First principal component of Luther 0.11***
variables (0.03)
Intensive Margin
Number of Luther letters 0.02*** 0.01*
(0.00) (0.01)
Number of Luther visits 0.11** 0.11*
(0.05) (0.06)
Number of Luther printed works -0.07 -0.34**
(0.12) (0.15)
Number of Luther students 0.01 0.00
(0.01) (0.01)
First principal component of Luther 0.04
variables (0.02)
Network variables YES YES YES YES YES YES
City-level controls YES YES YES YES YES YES
Imperial Circle F.E. YES YES YES YES YES YES
Observations 202 202 202 202 202 202
No. of Clusters 105 105 105 105 105 105 Notes: ***p < 0.01, **p < 0.05, *p < 0.1. Linear probability model, robust standard errors clustered by territory in parentheses.
The cities Wittenberg, Mainz, and Zurich are dropped in all regressions. All regressions include a constant term (not reported). City level controls include dummies for the printing press, independent city, university, bishop, lay magnate, on water, Hanseatic league,
and log of population in 1500, market potential in 1500, log distance to Wittenberg, and log distance to Zurich. In all regressions,
Imperial Circle fixed effects include Austria, Bavaria, Bohemia, Burgundy, Electorate, Franconia, the Italian States, Lower Saxon, Swabia, Upper Rhenish, and Westphalia.