Foreign Media and Protest Diffusion in German Revolution

Foreign Media and Protest Diffusion in
Authoritarian Regimes: The Case of the 1989 East
German Revolution
Holger Lutz Kern
Yale University†
November 2008
†
Postdoctoral Associate, Yale University, The MacMillan Center for International and Area Studies,
[email protected]. Chris Anderson, Walter Mebane, Steve Morgan, Na’ama Nagar, Jas Sekhon, and
Chris Way provided valuable comments. I am grateful to Siegfried Grundmann for making his data available and to Hans-Jörg Stiehler and Hartmut Siegel for information about radio reception in the Dresden
district. The usual disclaimer applies.
Abstract: Does access to foreign media facilitate the diffusion of protest in authoritarian
regimes? Apparently for the first time, I test this hypothesis by exploiting a natural
experiment in communist East Germany. I take advantage of the fact that West German
television broadcasts could be received in most but not all parts of East Germany and
conduct a matched analysis in which counties without access to West German television
are matched to a comparison group of counties with West German television. Comparing
these two groups of East German counties, I find no evidence that West German television
affected the speed or depth of protest diffusion during the 1989 East German revolution.
The “Monday demonstrations” that took place in East Germany in the autumn of 1989
heralded the beginning of the demise of communism in Eastern Europe. Inspired by the
peaceful East German revolution, people all over Eastern Europe took to the streets and
toppled the despised communist dictatorships (Oberschall 1996; O’Loughlin et al. 1998).
Because of its historical significance and the unparalleled wealth of primary sources that has
become available to researchers after German reunification, the East German revolution
has become an exemplary case in the literature on social movements and revolutionary
collective action (e.g., Hirschman 1993; Lohmann 1994; Pfaff and Kim 2003). But despite
an outpouring of recent research (e.g., Dale 2005, 2006; Pfaff 2006), our understanding of
how, within a matter of weeks, the East German people were able to bring down one of
the most oppressive communist regimes in Eastern Europe remains incomplete.
Research on the diffusion of protest in democratic societies has found that the mass
media are one of the channels through which protests are transmitted and sustained (Myers
2000; Roscigno and Danaher 2001; Andrews and Biggs 2006). But in authoritarian regimes
with tightly controlled and orchestrated mass media (such as the former communist regimes
in Eastern Europe and many contemporary authoritarian regimes), it is highly unlikely
that domestic media will facilitate the diffusion of protest. Instead of increasing citizen’s
awareness of protest events and the demands voiced by protesters, domestic media in such
regimes often ignore protest events entirely or portray them as the work of foreign agents
provocateurs (Friedrich and Brzezinski 1966; de Sola Pool 1974; Holzweissig 2002). It then
becomes natural to ask to what extent foreign media sources could serve as a substitute
for state-controlled domestic media in authoritarian regimes. Throughout the Cold War,
Western policy-makers indeed operated under the assumption that Western radio stations
(e.g., Radio Liberty, Radio Free Europe, and the BBC ) could provide the peoples behind
the Iron Curtain with a substitute for their censored domestic media (Presidential Study
Commission on International Radio Broadcasting 1973; Lisann 1975; Quester 1990; Nelson
1997; Puddington 2000; Parta 2007). Similar expectations are the basis of recent U.S.
international broadcasting efforts to Asia and the Middle East (El-Affendi 2005).
1
Anecdotal evidence suggests that foreign media played a key role in the East German
revolution. In the beginning, only West German television covered the mounting political
crisis in East Germany. While East German media at first ignored the protests and later
denounced them as the work of a few “anti-social thugs,” each evening West German
television beamed news about the protests right into East German living rooms. The
literature suggests that demonstrators were inspired by the actions of others elsewhere,
which they usually learned about from West German television. By spreading knowledge
of successful protests in other parts of East Germany, West German television altered
perceptions of political opportunity and facilitated the diffusion of protest (Kuran 1991;
Opp, Voss and Gern 1993; Opp and Gern 1993; Hirschman 1993; Jarausch 1994; Lohmann
1994; Grix 2000; Dale 2005).
In this paper, I make use of a natural experiment to assess the extent to which West
German television facilitated the diffusion of protest in the autumn of 1989. In order to
identify the causal impact of West German television, I exploit the fact that West German
television broadcasts could be received in most but by no means all parts of East Germany.
My matched comparison of East German counties in which over-the-air West German
television was available and East German counties in which it was not available provides
no support for the widely held view that West German television facilitated the diffusion
of protest during the 1989 East German revolution.
I should note at the outset that the scope of my analysis is restricted to the impact of
West German television. I do not offer a comprehensive explanation for the emergence and
diffusion of public protest in East Germany. I also do not attempt to explain its success in
toppling the East German regime. Instead, I seek to test, apparently for the first time, the
hypothesis that access to foreign media facilitates the diffusion of protest in authoritarian
regimes by providing information to potential protesters that is not available from the statecontrolled domestic media. Spatial variation in access to West German television in East
Germany, the availability of detailed protest event data, and its historical and theoretical
significance (e.g., Pfaff 2006) make the East German revolution an ideal test case for such
2
an investigation.
I. The 1989 East German Revolution
For most of the 1980s, the communist regime in East Germany seemed to be quite stable.1
Standards of living in East Germany were noticeably higher than in the rest of Eastern
Europe. Throughout the 1970s and 80s, even Western observers were impressed with the
German Democratic Republic’s (GDR) economic performance and regarded it as a socialist
success story (Kopstein 1997). Communist rule in East Germany was based on an implicit
social contract which rewarded political acquiescence with steadily improving living standards (Pollack 2000; Dale 2005). In the second half of the 1980s, however, the East German
regime became increasingly incapable to buy off its citizens. East German economic successes in the 1970s were due to easy access to international credit, economic aid from the
Soviet Union in the form of cheap raw materials, and the high investments of the 1960s. The
1970s oil shocks, rising interest rates, and reduced Soviet subsidies laid bare the structural
weaknesses of East Germany’s centrally planned economy. The East German economy
with its focus on heavy industry and the extensive use of factor inputs was ill-equipped to
participate in the technological revolution taking place in Western economies. It also did
not follow the shift from industry to the service sector that propelled growth in Western
economies (Stiglitz 1994). By the late 1980s, stagnation had become evident (Gutmann
and Buck 1996; Kopstein 1997; Steiner 2004). Even though nominal wages continued to
rise, inflation and frequent consumer-goods shortages left many East Germans with the
impression that their standards of living were stagnating, if not declining (Schneider 1996).
And in direct comparison with West Germany, facilitated by the availability of West German television and visits to and from West Germany, the gap in living standards had never
been as plainly visible as in the late 1980s (Dale 2005).
Throughout the 1980s, the sorry state of the environment further fueled East Germans’
discontent. The East German economy was geared towards maximizing output regardless
1
This historical account is necessarily brief. Detailed historical accounts in English can be found in Jarausch 1994, Zelikow and Rice 1995, and Maier 1997. German works include Kuhrt, Buck, and Holzweissig
1996, Neubert 1998, and Pollack 2000.
3
of the ecological consequences. East Germany’s large chemical industry and the use of
lignite (brown coal) for energy production, compounded by a shortage of effective pollution
abatement technology, led to severe ecological damages (Stinglwagner 1999). The GDR’s
emission rates of pollutants such as particulate matter, sulfur dioxide (SO2 ), and nitrogen
oxides (NOx ) were among the highest in Europe. In 1988–89, East German per capita
SO2 and particulate matter emissions were more than 15 times as high as West German
emissions (Buck 1996b).
There existed no recognized opposition that could have given voice to East Germans’
grievances. Dissent was not tolerated in the GDR. Many dissatisfied East Germans thus
left the country, either legally after they had received exit visas (after a waiting period
that could last many years) or illegally (Mayer 2002). Only within the Protestant church
did dissenting voices find some breathing space. A small number of clergymen supported
small groups of political activists concerned with issues of peace, sustainable development,
the environment, and human rights by giving them access to modest resources such as
telephones, copying machines, and meeting spaces (Neubert 1998; Pollack 2000; Dale 2005).
Some activists dismissed from their state jobs also found employment with the church. In
the late 1980s, a tiny East German samizdat press emerged that attempted to create a
public sphere independent of the regime. However, the alternative lifestyle of most activists
and their leftist outlook and advocacy of a reformed “socialism with a human face” did
not resonate with the majority of East Germans who primarily cared about higher living
standards and the freedom to travel to the West (Oberschall 1996; Pollack 2000; Dale 2005).
Opposition groups neither organized nor played a large role in the protests that erupted in
September and October 1989 (Opp, Voss and Gern 1993; Opp and Gern 1993). The first
“Monday demonstrations” in Leipzig were predominantly led by East Germans who had
applied for exit visas and were hoping that public protest would make them enough of a
nuisance to the regime to be allowed to leave the country (Pollack 2000).
In contrast to Hungary and Poland, no significant impetus for reform arose from within
the ruling party. Erich Honecker, General Secretary of the Socialist Unity Party’s (Sozial-
4
istische Einheitspartei Deutschlands, SED) Central Committee since 1971, insisted on a
narrow and inflexible interpretation of Marxism-Leninism and enforced strict norms of
party discipline. Following Mikhail Gorbachev’s accession to the leadership of the Soviet
Communist Party in 1985, relations between the GDR and the Soviet Union quickly soured.
Whereas before the SED had stressed that “Learning from the Soviet Union means learning
to win,” it now distanced itself from Gorbachev’s reform program. Most East Germans on
the other hand welcomed Gorbachev’s reforms and hoped for similar changes in East Germany (Süss 1996, 1999). In the late 1980s, public opinion polls conducted by the Central
Institute for Youth Research in Leipzig showed growing discontent among East German
youths. Between 1986 and 1989, trust in the SED fell dramatically while sympathies for
Gorbachev were soaring (Friedrich 1990; Friedrich, Förster, and Starke 1999).
The international situation also became increasingly difficult for the East German
regime when Hungary and Poland both effectively left the Soviet bloc at the beginning
of 1989 (Roberts 1999). In January, non-communist parties were legalized in Hungary. In
February, round-table talks began in Poland. In June, the Polish Communist Party relinquished its hold on power. In May, Hungary had already started to dismantle its border
fortifications with Austria. Throughout the summer, thousands of East Germans vacationing in Hungary made use of what to them seemed like a once-in-a-lifetime opportunity to
escape to West Germany. Others occupied the West German embassies in Prague, Warsaw,
and Budapest to force their emigration to the West. The East German regime eventually
relented and allowed all East Germans occupying West German embassies to leave for
West Germany (Zelikow and Rice 1995). East Germany’s demand that the trains carrying
them to West Germany had to cross East German territory so that they could be formally
deprived of their citizenship and expelled from East Germany backfired, however. Many
East Germans learned about this compromise solution from West German television, and
along the train route riots broke out between the police and desperate East Germans who
attempted to board the trains (Urich 2001). The East German leadership, focused on the
celebrations of the 40th anniversary of the GDR on October 7, had seriously misread the
5
public mood. While East German media remained silent about the mass exodus or printed
snide remarks about the emigrees, West German television broadcast dramatic footage
showing the elation of East Germans who had finally made it to the West. It was this mass
exit that significantly fueled protest against the regime (Hirschman 1993; Lohmann 1994;
Pfaff and Kim 2003).
II. The Dynamics of Revolutionary Collective Action
Kuran (1989, 1991, 1995) has offered an elegant explanation for why revolutions, including
the East German one, are so often unanticipated. In his view, people who dislike an authoritarian regime tend to publicly support it as long as the opposition seems weak since
the costs of siding with the seemingly unpopular opposition are higher than the psychological costs of pretending to support the secretly despised status quo. However, because of
this preference falsification even slight surges in the strength of the opposition can lead to
“revolutionary bandwagons” in which authoritarian regimes that once appeared unshakeable quickly see their support crumble.2 Others have explicitly modeled “informational
cascades” (Bikhchandani, Hirshleifer, and Welch 1988) in which information about the aggregate level of participation in revolutionary collective action conveys information about
others’ political preferences. These informational cues then allow potential participants to
update their beliefs about the value of participation in the collective enterprise (Lohmann
1994, 2000). What is missing from the classic studies by Kuran and Lohmann, however,
is a detailed discussion of the channels that transmit information about the size of the
opposition, as in Kuran (1989, 1991, 1995), or aggregate turnout in protest events, as in
Lohmann (1994, 2000). The widely-cited article by Susanne Lohmann (1994), for example,
succeeds admiringly in describing how the Monday demonstrations in Leipzig helped to
shift public perceptions of the vulnerability and popularity of the East German regime. It
notes that mass demonstrations in Leipzig “triggered a wave of political protest throughout
the GDR”(Lohmann 1994: 42), but what is missing is a discussion of how East Germans
were able to become informed about protest events that the vast majority of them could
2
See Schelling 1978 on bandwagon processes more generally.
6
not directly observe.
Demonstrations spread quickly across East Germany. The first Monday demonstration
in Leipzig on September 4 attracted only 800 participants (Schwabe 1999). But within little
more than one month, tens of thousands of East Germans were marching through East
German cities proclaiming “We are the people!” Figure 1 displays the cumulative number
of East German counties that experienced protest events over time.3 The cumulative
sum curve is roughly S-shaped, or sigmoid, which is typical for many diffusion processes
(Rogers 2003). Figure 1 shows that some isolated protests took place after the Monday
demonstration in Leipzig on September 4, but that protests did not really start to spread
until the beginning of October. From the beginning to the end of October, protests erupted
in 126 additional counties. By November 9, the day the Berlin Wall was breached, protests
had erupted in 180 out of 217 East German counties.
A. Media and Collective Action
Information networks such as family and friendship ties (McAdam 1986; Hechter 1987;
Gould 1991, 1993) increased awareness of the Monday demonstrations and motivated potential participants to join (Opp, Voss, and Gern 1993; Opp and Gern 1993; Goodwin and
Pfaff 2003; Pfaff 2006). However, it is unlikely that such interpersonal networks were the
primary channel of protest diffusion. The East German transportation and telecommunications infrastructure was in a disastrous state; for example, only 17 % of East German households had a telephone in 1989 (Staatliche Zentralverwaltung für Statistik 1990). Moreover,
in authoritarian regimes feigned loyalty (Kuran 1989, 1991, 1995) tends to diminish the effectiveness of social networks in supplying politically sensitive information and motivating
people to participate in potentially high-cost anti-regime collective action. The effects of
preference falsification were especially pronounced in East Germany’s niche society (Gaus
1983; Diewald 1995; Grix 2000). The state security police (Staatssicherheit) had implemented a comprehensive program of surveillance, carried out by more than 250,000 paid
agents and “unofficial collaborators” (Inoffizielle Mitarbeiter ) in a country of less than 17
3
The data on which this graph is based are discussed in more detail below.
7
million people (Fricke 1991). Since virtually anyone — colleagues, friends, and even spouses
— could be an informer, people withdrew into small circles of close family members and
trusted friends. Such private niches afforded East Germans some respite from the political
and social conformity expected from them in their public lives. While the strong ties that
people developed within these niches facilitated the mobilization of protest (Opp, Voss,
and Gern 1993; Opp and Gern 1993), they tended to be spatially clustered and of small
size and therefore less conductive to the diffusion of protest.
What other channels could have transmitted the “informational cascade” identified by
Lohmann (1994)? We know that opposition groups neither organized nor played a large
role in protest activities (Opp, Voss and Gern 1993; Opp and Gern 1993; Pfaff 1996), so
it is unlikely that they significantly contributed to protest diffusion. Lots of anecdotal
evidence however links West German television to the diffusion of protest. Kuran (1991:
37) for example writes with respect to the demonstrations that took place in East Berlin
during the celebrations of the 40th anniversary of the GDR that “West German television
immediately played these events back to the rest of East Germany. The scenes alerted
disgruntled citizens in every corner of the country to the pervasiveness of discontent, while
the government’s weak response revealed its vulnerability.” Opp and Gern (1993: 675–676)
note that “the [Leipzig] Monday prayers, together with the demonstrations, contributed
to the emergence of protest in other East German cities. People were informed, primarily
on West German television, about the events in Leipzig, and the expectation formed that
citizens in each city would meet spontaneously on the city square for Monday demonstrations.” With regard to the exiting crisis, Hirschman (1993: 198) suggests that “pictures
of the exodus soon flooded the TV screens, with the result of not just causing established
critics [. . . ] to sharpen their criticism but also of making activists out of long-passive average citizens.” Jarausch (1994: 44), Opp, Voss, and Gern (1993: 254–255, 260), Grix (2000:
32–33, 137), and Dale (2005: 151) similarly suggest that West German television alerted
East Germans to protest events in other places, increased awareness of the widespread
discontent and apparent vulnerability of the regime, and thus contributed to the diffusion
8
of protest. While apparently widely accepted, this conjecture about the impact of West
German television has not been subjected to any empirical tests so far.
The media-driven diffusion of social movements has attracted only limited scholarly
attention (Tarrow 1989; Oberschall 1989; McAdam and Rucht 1993; Soule 1997; Oliver
and Myers 2003). Few studies have examined whether media coverage of protest events
can inspire additional protests in other places. Andrews and Biggs (2006) analyze the wave
of sit-ins that swept through the American South in the spring of 1960 and show that
newspapers were a crucial channel for the transmission of information about protests in
other places. Roscigno and Danaher (2001) demonstrate that during the southern textile
workers’ strikes of 1929–34, radio broadcasts of itinerant musicians and presidential “fireside
chats” led to the diffusion of strike activities across mill towns. Myers (2000) detects
diffusion caused by television broadcasts in his analysis of the 1964–71 urban racial riots
in the U.S. To the best of my knowledge, empirical work on the media-driven diffusion
of collective action has exclusively examined the effects of domestic media in democratic
societies. However, the importance of the mass media, and especially of foreign mass media,
for the revolutions of 1989 has frequently been noted in the literature (Garton Ash 1990;
Huntington 1991; Whitehead 1996; Schmitter 1996; Pridham 1997; O’Neil 1998).
B. Media in East Germany
If West German television facilitated the diffusion of protest in East Germany, it should
have done so primarily during the early phase of the revolution.4 Once East German media
began to cover the political crisis, East Germans no longer needed to rely on foreign media
sources to become informed politically.
East German media, for decades tightly controlled by the SED and considered the
“keenest weapon of the party” (Holzweissig 2002), achieved a measure of independence
4
West German television refers to ARD and ZDF, the two primary West German public broadcasting
stations. Commercial television (RTL, SAT 1 ) was introduced in West Germany in the mid-1980s, but it
did not broadcast to East Germany and could only be received in some areas near West Berlin. ARD and
ZDF have a public service orientation and devoted a great deal of attention to politics in East Germany
(e.g., the political magazines Kontraste and Kennzeichen D ). They were much more popular in East
Germany than East German television (Stiehler 2001).
9
from the regime after Erich Honecker was forced to resign as General Secretary of the
SED’s Central Committee on October 18. Until the fall of the Berlin Wall his successor
Egon Krenz attempted to salvage at least some of the control over the media that the
SED had enjoyed for decades (Holzweissig 1999, 2002). But by the end of October, East
German media had essentially become independent from the SED. From then on, they
covered protest events in at least as much detail as West German television (Holzschuh
1990; Ludes 1990; Kapitza 1997; Holzweissig 1999, 2002; Bösenberg 2004).
The best indicator for the dramatic changes that took place in the East German media
landscape are audience ratings for East German television’s prime news show Die Aktuelle
Kamera. For thirty years, it had glorified the East German regime in formulaic, ideological
prose (Heym 1977). In the late 1980s, average viewer ratings were less than 5%.5 But
throughout October 1989, viewer ratings steadily rose to over 40% and reached 54% on
November 8 with a report on the resignation of the Politburo (Holzschuh 1990).
Given these dramatic changes in the East German media landscape, I expect West
German television to have facilitated the diffusion of protest especially during September
and October 1989, when East Germans still had to turn to foreign news sources to stay
abreast of the latest political developments. Moreover, as seen in Figure 1, by the end of
October protests had already spread to most parts of the country. Afterwards, the scope
for any further media-driven protest diffusion was limited.
III. Research Design
Not all parts of East Germany had access to West German television. The map in Figure 2
shows over-the-air signal strength of West German television broadcasts in East Germany.
Especially the Northeastern part of East Germany around the city of Greifswald and the
Dresden district in the Southeast were largely cut off from West German television due to
topographical features and their distance from West German broadcasting towers. For the
5
Analyse der Ergebnisse der alternativen Programgestaltung um 20.00 Uhr im 1. Quartal 1989 (9.1. –
31.3.) und Schlussfolgerungen [Analysis of the results of the alternative programming at 8 pm during the
first quarter 1989 (1/9 – 3/31) and conclusions]. Deutsches Rundfunkarchiv [German National Broadcasting
Archives], Programmredaktion Analyse I/1989.)
10
Dresden district, I also have detailed county-level information on West German television
signal strength. The map shown as Figure 3 was submitted to the Politburo as part of a
larger collection of material on West German television in East Germany.6 It distinguishes
between counties without access to West German television (white), counties with partial
access to West German television, depending on the weather and exact location (light
grey), and counties with full access to West German television (dark grey). Together with
the map shown as Figure 2, it allows me to divide East German counties into two groups:
a “treated” group of counties that had access to West German television and a “control”
group of counties in which West German television was not available.7
The causal question of interest is “Would protest activities have been different in counties that had no West German television if they had had West German television?” This
quantity of interest is known as the average treatment effect for the controls (e.g. Rubin
1974, 1977, 1978; Holland 1986; Rosenbaum 2002).8 Outcome measures are the diffusion
rate and the depth of diffusion. Both measures are common in the diffusion-of-innovation
literature (Rogers 2003; Frenzel Baudisch and Grupp 2006). The diffusion rate (also called
the rate of adoption) measures the speed with which an innovation is adopted by members
of a social system (e.g., individuals, firms, or industries). In our case, it measures the speed
with which protest events break out in hitherto unaffected counties. The depth of diffusion
measures the degree to which a new innovation is adopted within a unit of analysis (e.g.,
6
Bundesarchiv [Federal Archives] SAPMO DY 30/J IV2/2/2317.
The following (conservative) coding rule was used. In the Northeast, for which detailed county-level
measures of West German television signal strength are not available, counties that in Figure 2 are shown
as predominantly without access are coded as controls. All other counties are coded as treated. For the
Dresden district, I made use of the more detailed map shown as Figure 3. Counties that are predominantly white (no access to West German television) are coded as controls; all other counties are coded as
treated. According to this rule, the following 22 East German counties are controls: Greifswald, Grimmen, Stralsund-Land, Wolgast, Rügen, Stralsund (Stadt), Greifswald (Stadt), Anklam, Demmin, Malchin,
Teterow, Weisswasser, Bautzen, Bischofswerda, Görlitz-Land, Löbau, Niesky, Pirna, Sebnitz, Zittau, Dresden (Stadt), Görlitz (Stadt). All other counties are considered treated. For 4 control counties (Bautzen,
Bischofswerda, Anklam, Malchin), the coding is somewhat ambiguous. Coding these counties as treated
instead of control does not substantively change my results.
8
Why do I estimate the average treatment effect for the controls instead of the more common average
treatment effect for the treated or the average treatment effect for the whole sample? Note that most East
German counties had access to West German television. For many of them, it is impossible to find good
comparison units among the 22 counties that had no West German television. The average treatment effect
for the controls is therefore the only treatment effect than can realistically be estimated from these data.
7
11
all firms within an industry vs. only some of them). Here, the depth of diffusion measures
the extent of protest activities in a given county, i.e., the number of protest events and the
total number of protest participants.
I match the 22 control counties to 22 treated counties selected from the total number of 183 treated counties.9 I use one-to-one nearest-neighbor matching with replacement.
Genetic matching (Diamond and Sekhon 2006) is used to balance a large number of countylevel covariates plausibly related to levels of protest activities.10 I match on all covariates,
some interactions and higher-order terms of the covariates, and the propensity score, estimated using logistic regression of the treatment indicator on the covariates. Covariates
are listed in Table 1. The first set of covariates (population size, population density, sector shares (industry, agriculture, crafts and construction, and services and transportation),
the share of skilled and unskilled labor, and the proportion of the population that holds
a college degree, is female, and of working age) captures broad socioeconomic differences
between counties. The rest of the covariates captures disparities in three dimensions of
quality of life that were particulary salient in East Germany (Buck 1996a, 1996b): housing
quality (housing space per capita and the proportion of apartments with bathrooms, interior toilets, and modern heating), access to medical services (people per medical doctor
and people per dentist), and environmental pollution (particulate matter, sulfur dioxide
(SO2 ), and nitrogen oxides (NOx ) emissions).11 Counties are weighted by the square root
of their population size.
9
I exclude East Berlin and Halle-Neustadt from the pool of treated counties. Living conditions in East
Berlin were much better than in the rest of the GDR, making it a poor comparison case for any other East
German county. Halle-Neustadt was unique in that it was a dormitory town for people working in the Buna
and Leuna chemical plants. Also note that many previous works on the media-driven diffusion of protests
have used event history analysis (e.g., Myers 2000). In contrast to these studies, which exploit variation
in local media coverage of protest events elsewhere, I analyze the effects of a national media source that is
the same across the country. The only contrast I can exploit for causal inference is the contrast between
counties with access to this media source and counties without access.
10
Covariates are taken from Grundmann 1997 and Staatliche Zentralverwaltung für Statistik 1989.
11
Should I also adjust for direct measures of regime support such as the proportion of party members or
the proportion of the population that has applied for exit visas? The problem with such direct measures
of regime support is that they are themselves affected by West German television (Kern and Hainmueller
2008). Adjustment for such intermediate outcomes would introduce post-treatment bias (Rosenbaum 1984;
Frangakis and Rubin 2002).
12
Covariate balance before and after matching is also shown in Table 1. Balance is
measured both in terms of standardized bias (the difference between treatment and control
group means divided by the pooled standard deviation) and p-values from bootstrapped
Kolmogorov-Smirnoff tests (Abadie 2002; Sekhon 2006). For any variable, the closer the
standardized bias is to 0 and the larger the p-value the better the balance. As one can
see, treated and control groups differ noticeably before matching. Even though genetic
matching cannot completely eliminate these imbalances, balance is much better in the
matched sample. Before matching, the smallest p-value is essentially 0; after matching,
the smallest p-value is 0.22 (% bathroom). After matching, the standardized bias for most
variables is either eliminated almost completely or at least noticeably reduced. Overall,
genetic matching eliminates about 81 percent of the standardized bias. Finally, balance
can also be assessed in a multivariate way by testing the null hypothesis of no difference
in the distributions of the estimated propensity scores in both groups using a KolmogorovSmirnoff test. The bootstrapped p-value from this test is 0 before matching and 0.17
afterwards, confirming that matching has considerably improved balance between control
and treated counties.
Protest event data are taken from Schwabe (1999), which provides a detailed countrywide compilation of county-level protest events between September 4, 1989 and March 18,
1990, the date of the first free election in East Germany. This compilation is based on
records from the East German Ministry of the Interior, which assembled daily crisis reports submitted by local police forces, the records of the Ministry of State security, and
numerous published secondary sources. Schwabe’s compilation of protest events is the most
comprehensive source of protest event data available for the East German revolution. It
provides details on 2652 occurrences of politically motivated illegal assemblies, demonstrations, and violations of public order. The records of the Ministry of the Interior, which
constitute a subset of these data, have been used in previous work on the East German
revolution (Pfaff and Kim 2003).
13
A. Missing Data
For most protest events recorded in the dataset the approximate number of participants
is known. For 333 out of 2652 (12.5%) of these observations, however, no information
on protest size is available.12 I assume that data are missing at random (MAR) in the
sense of Little and Rubin (2002), i.e., I assume that missing data carry no information
about the probability of missingness conditional on the other variables included in the
imputation model. The appendix shows that my results are not sensitive to violations
of this assumption. Under MAR, I can multiply impute the missing protest sizes in a
relatively straightforward manner. The main complication is that the event-level data take
the form of an unbalanced panel. Between September 1989 and March 18, 1990, protest
events took place in almost all East German counties. The number of protests per county
however varied between 1 and 52. I therefore need a multiple imputation method that
takes the grouped and time-series nature of the data into account. Imputation is simplified
by the fact that I only have missing information on the outcome variable (protest size); all
covariates are fully observed. In the Bayesian framework these missing outcomes can simply
be modeled together with the observed outcomes. I use WinBUGS (Lunn et al. 2000) to
estimate a hierarchical varying-intercept Poisson regression that allows for overdispersion
by the inclusion of a multiplicative error term (Gelman and Hill 2006; Stauffer 2007: 110–
112).
y ∼ Poisson(eαc +Xβ+ǫ )
ǫ ∼ N(0, σǫ )
αc ∼ N(µα , σα )
µα = Zγ,
12
There is no clear temporal pattern in this missingness. Protest events that took place in September
or October 1989 are just as likely to have missing information as protests that took place in January or
February 1990. By far the highest level of missingness occurs in March 1990, presumably because East
German security agencies were being dismantled and had lost their capacity to monitor (and interest in)
protests. Even though protest sizes reported by different bureaucracies do not always agree with each
other, Schwabe (1999) finds no systematic differences between these sources.
14
where y denotes protest size, X is a set of time-varying event-level covariates and Z is
a set of time-invariant county-level covariates including a constant term. β and γ are
the associated parameters. σα represents variation in protest sizes among counties and σǫ
represents variation in the data beyond that explained by the Poisson model. X contains a
third-order polynomial in time (weeks since September 1, 1989), indicator variables for day
of the week, an indicator variable for the period after the fall of the Berlin Wall, and all
interactions between this indicator and the day of the week indicators. Z contains all the
covariates listed in Table 1. I use uninformative uniform priors for the variance parameters
and uninformative Normal priors for the others. After convergence had been ascertained
100 draws from the posterior distribution were taken to create 100 imputed datasets in
which fitted values were used to impute missing protest sizes. All results reported below
average over these 100 imputed datasets and properly account for imputation uncertainty
using Rubin’s rule (Little and Rubin 2002).
IV. Results
A. Diffusion Rate
Once the first Monday demonstration had taken place in Leipzig on September 4, do we see
a difference in the speed with which protests diffused to counties with and without West
German television? Figure 4 contrasts the rate of diffusion in control counties with the rate
of diffusion in matched treated counties. The solid curve shows the cumulative number of
treated counties that experienced protests; the dashed curve shows the cumulative number
of control counties that experienced protests. The first protests erupted in Leipzig, which
is part of the matched treated group, so throughout September the solid curve is above
the dashed curve. From then on, the dashed cumulative sum curve for counties without
West German television for the most part is above the solid curve; differences however
are generally small. By the middle of November, protests had spread to most counties in
both groups. Overall, the rate at which counties in the control group adopted protests
might have been somewhat higher, but differences between the two groups are quite small.
At conventional test levels, I cannot reject the null hypothesis that the two curves are
15
identical.13 The hypothesis that the rate of protest diffusion in counties without West
German television would have been higher if these counties had had West German television
is clearly not supported by these data.
B. Depth of Diffusion
Even though protests did not diffuse any slower in the group of counties without West
German television (and might actually have diffused somewhat faster), it could still be the
case that the lack of West German television reduced the reach of the emerging protest
movement (i.e., the depth of diffusion), resulting in a lower number of protest events or
fewer protest participants. I investigate these possibilities next.
Figures 5 and 6 display cumulative sum plots.14 In both plots, time is shown on the
horizontal axis. The vertical axis in Figure 5 denotes the number of daily protest events
in control counties minus the number of daily protest events in matched treated counties.
These daily differences are shown as vertical histogram-like bars. The dashed horizontal
line denotes a zero difference between control and matched treated counties in the number
of daily protests. The jagged red curve shows the cumulative sum of the differences in
the number of daily protest events with a bootstrapped point-wise .90 rejection region
denoted by dashed curves.15 The height of the red curve at each point in time equals the
cumulative sum of the differences in the numbers of daily protests up to that date. When
this cumulative sum curve is sloping upwards more protests are taking place in counties
without West German television (control counties). When it is sloping downwards, more
protests are taking place in counties with West German television (treated counties). Figure
6 is identical to Figure 5 except that the vertical axis denotes the number of protesters
in control counties minus the number of protesters in treated counties and the cumulative
sum is taken over the differences in the numbers of protesters, again shown as vertical
13
The p-value from a bootstrapped Kolmogorov-Smirnov test of equality of distributions is 0.11.
See Hawkins and Olwell 1998 for a rigorous treatment of cumulative sum plots.
15
The areas above the upper dashed curve and below the lower dashed curve form the region in which
we can reject the null hypothesis of a zero cumulative sum. This rejection region is conditional on the
matched dataset. It is adjusted for multiple imputation uncertainty and autocorrelation in the number of
protest events within counties over time.
14
16
histogram-like bars around the dashed zero baseline.16
In Figure 5, the cumulative sum has a negative slope throughout September because
the first protest events took place in Leipzig, which is part of the matched treatment
group. Afterwards, however, it generally slopes upwards until the middle of February,
indicating that over this period, more protests took place in counties without West German
television than in the matched group of counties with West German television. In the
second half of February and in March, this relationship reverses. Matched treated counties
now experience more protest events than control counties. By March 18, the cumulative
sum is 17, indicating that over the September 4 – March 18 period, a county without West
German television on average experienced about 17 ÷ 22 ≈ .8 more protest events than a
county with West German television. Between November and the middle of February, the
cumulative sum falls inside the rejection region, so for days in this period we can reject the
null hypothesis that differences between counties with and without West German television
are due to chance variation.
Figure 6 shows the cumulative sum curve for the number of protesters (×100, 000). With
some exceptions, the cumulative sum curve is downwards sloping over the whole period,
indicating that the number of protesters in counties without West German television is
constantly lower than the number of protesters in the matched sample of counties with
West German television. By March 18, the cumulative sum is −43, so over the September
4 – March 18 period on average 43 ÷ 22 × 100, 000 ≈ 195, 000 more protesters took to
the streets in a matched county with West German television than in a county without
West German television. To put this estimate into context, in 1988 the mean population
size of East German counties was around 71,000 (with a median of around 57,000), but of
course many protesters will have repeatedly participated in demonstrations. I should note
though that the cumulative sum curve never falls inside the rejection region, so we should
be cautious in interpreting these differences between treated and control counties.
To what extent do these results support the hypothesis that West German television
16
Note that this is the total number of daily protesters in each group and not the number of protesters
per protest event. Figure 6 is thus not affected by differences in the number of protest events.
17
had a positive effect on the depth of protest diffusion? Recall that I expect West German
television to facilitate protest diffusion only during the early stages of the East German
revolution. In September and October, the number of protests should be lower in counties
without West German television than in counties with West German television. While
this seems to be the case in September (mainly due to the first Monday demonstrations in
Leipzig), throughout October, many more protest events take place in the control group
than in the matched treatment group (note the positive slope of the cumulative sum curve
in Figure 5). Results for the number of protests are thus not consistent with the hypothesis
under study.
Turning to the number of protesters, we see from Figure 6 that while differences in
the number of protesters are quite small in September, throughout October the number of
protesters in control counties is generally lower than the number of protesters in matched
treated counties. At first glance, this seems to support the hypothesis that access to
West German television had a positive effect on the depth of protest diffusion. Several
things should be noted, however. First, there is a lot of variability in the data (note
that the sign of the slope of the cumulative sum curve in Figure 6 changes frequently
throughout October). Second, between November and March, when I would no longer
expect information provided by West German television to facilitate protest diffusion, the
number of protesters in counties without West German television continues to be lower
than the corresponding number in matched counties with West German television (the
slope of the cumulative sum curve in Figure 6 remains negative). And third, as pointed out
above, the cumulative sum curve never falls inside the rejection region, so the differences
between control and matched treated counties we see in Figure 6 could be simply due to
chance. Overall, the results provide little support for the hypothesis that West German
television had a positive impact on the rate or depth of protest diffusion during the East
German revolution. Strictly speaking, my results are of course only informative about what
would have happened in a counterfactual world in which counties without West German
television had had West German television. Nevertheless, it seems highly unlikely that
18
only the protest diffusion in these 22 counties would have been unaffected by West German
television.
One threat to the validity of my results is the possibility that East Germans who
could not watch West German television had access to other Western media sources, in
particular West German radio.17 If East Germans who could not watch West German
television listened to West German radio instead, comparing counties without West German
television to counties with West German television would not be very informative. However,
the topographical features that in parts of East Germany prevented the reception of West
German television signals also impeded the reception of West German radio signals. East
German radio audience ratings for September 1989 show that East Germans living in the
Dresden district were 45% less likely to listen to foreign radio stations than East Germans
living in districts with access to West German television.18
V. Discussion
Work on preference falsification (Kuran 1989, 1991, 1995) and “informational cascades”
(Lohmann 1994, 2000) has significantly contributed to our understanding of how an authoritarian government that is detested by the vast majority of its people can nonetheless
remain in power. It has also demonstrated that small perturbations in publicly available
information about others’ political preferences can set off “revolutionary bandwagons” in
which authoritarian regimes that once appeared unshakeable quickly see their support
crumble. Left underdeveloped in this literature on collective action under conditions of
authoritarian rule is a discussion of how politically relevant information is actually transmitted in these societies. Several authors have studied the informational role of family and
friendship ties (Opp, Voss and Gern 1993; Opp and Gern 1993; Goodwin and Pfaff 2003;
Pfaff 2006), but no research has been conducted on the role of foreign media in sustaining
17
Western print media such as newspapers were not available in East Germany.
Hörbeteiligung September 1989 [Audience ratings September 1989]. (Zentralarchiv für empirische
Sozialforschung ZA 6548.) East German radio audience surveys did not explicitly ask about foreign radio
stations but contained an additional category euphemistically labeled “others.” Since the surveys listed all
East German stations the “others” category could only refer to foreign, primarily West German, stations.
18
19
and spreading revolutionary collective action in authoritarian regimes. To the best of my
knowledge, this paper is the first that explicitly tests the hypothesis that access to foreign
media facilitates the diffusion of protest in such regimes.
I have exploited a natural experiment in East Germany, making use of the fact that
West German television broadcasts could only be received in parts of East Germany. The
conjecture that West German television informed potential protesters of successful protests
elsewhere, altered perceptions of political opportunity, and thereby facilitated the diffusion
of protest (Kuran 1991; Hirschman 1993; Jarausch 1994; Lohmann 1994; Grix 2000; Dale
2005) is quite plausible. In fact, East Germany can probably be considered a “most likely”
case for the impact of foreign media on protest diffusion in authoritarian regimes. There
existed no significant language or cultural barriers between East and West Germans. Moreover, West German television, which was extremely popular in East Germany, devoted a
lot of attention to East German politics while East Germany’s domestic media were tightly
controlled by the communist regime. Yet surprisingly, I have found no evidence that West
German television affected the rate or depth of protest diffusion during the 1989 East
German revolution.
There are several avenues for further research. We know from the survey that Opp, Voss
and Gern (1993) conducted in Leipzig that interpersonal networks increased awareness of
the Monday demonstrations and motivated potential participants to join. But since the
authors could not interview people living in other parts of East Germany, their survey
data are not informative about the role of interpersonal networks in the spatial diffusion of
protest. Future work should examine how face-to-face interactions, perhaps operationalized
through spatial proximity (Hedström 1994), affected the spatial diffusion of protest in East
Germany.
There exist many historical and contemporary instances of countries penetrated by
foreign media whose non-democratic governments would prefer the populace to have less
rather than more political information. In fact, in 2008 alone the U.S. is spending almost
$700 million on international broadcasting in order to provide the public in such countries
20
with alternative and more trustworthy news sources (e.g., Radio Sawa and Alhurra TV,
Radio Free Asia, Radio/TV Martı́). It would be interesting to study the impact of this international broadcasting effort on public opinion and anti-regime collective action. Finally,
one particularly exciting avenue for future research are newer communication technologies
such as the internet which have made transboundary communication much easier than in
the past (Boas and Kalanthil 2003; Myers 2008). We need to know more about their effects
on social movements and revolutionary collective action in authoritarian regimes.
21
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28
Table 1: Balance
29
population size
population density (pop./km2 )
% working age
% female
% industry
% agriculture
% crafts and construction
% services and transportation
% college
% skilled
% unskilled
housing space (m2 )
% bathroom
% interior toilet
% modern heating
people per medical doctor
people per dentist
nitrogen oxides (tons/km2 )
sulfur dioxide (tons/km2 )
particulate matter (tons/km2 )
Before Matching
Control
Treated
mean
mean
86213.63 124023.49
404.83
685.99
0.64
0.64
0.52
0.52
0.37
0.36
0.15
0.15
0.10
0.09
0.36
0.38
0.20
0.21
0.62
0.61
0.13
0.14
27.21
26.67
81.98
76.74
74.34
67.23
44.33
38.92
570.81
585.79
1524.07
1534.79
6.89
8.20
92.43
91.59
35.34
38.64
SB
0.60
0.55
−0.57
−0.22
−0.10
−0.04
−0.17
0.26
0.38
−0.94
0.73
−0.43
−1.09
−0.70
−0.57
0.11
0.06
0.12
−0.01
0.07
Control
mean
127539.16
625.83
0.64
0.52
0.37
0.15
0.09
0.36
0.21
0.61
0.14
26.94
77.72
68.93
40.38
582.43
1521.24
7.74
125.62
40.19
After Matching
Treated
mean
SB
124023.49 −0.02
685.99
0.06
0.64 −0.04
0.52 −0.12
0.36 −0.09
0.15 −0.01
0.09
0.00
0.38
0.14
0.21
0.04
0.61 −0.06
0.14
0.12
26.67 −0.11
76.74 −0.14
67.23 −0.10
38.92 −0.10
585.79
0.02
1534.79
0.04
8.20
0.03
91.59 −0.20
38.64 −0.03
% SB
reduction
96
89
93
43
11
83
97
44
89
94
83
73
87
85
83
84
36
76
−3236
57
Before
After
p-value
0.97
0.86
0.01
0.12
0.84
0.79
0.63
0.38
0.66
0.13
0.24
0.00
0.00
0.17
0.01
0.13
0.94
0.50
0.27
0.86
p-value
0.81
0.62
0.28
0.27
0.95
0.28
0.61
0.61
0.82
0.27
0.82
0.25
0.22
0.39
0.25
0.42
0.62
0.82
0.62
0.62
Note: Table shows balance between the control and treatment group before and after matching. SB (“standardized bias”) denotes the difference
between the treatment and control group means divided by the pooled standard deviation. % SB reduction denotes the percent improvement
in standardized bias achieved through matching. The last two columns show p-values from bootstrapped Kolmogorov-Smirnoff tests (10,000
bootstrap samples).
9.89
10.89
11.89
12.89
1.90
2.90
3.90
100
50
Counties
150
200
First Monday
demonstration
in Leipzig
0
Berlin Wall
falls
9.89
10.89
11.89
12.89
First free
elections
1.90
2.90
3.90
Time
Figure 1: Diffusion of protest in East Germany, September 1989 – March 1990
30
Figure 2: Over-the-air signal strength of West German television broadcasts in East Germany
Source: Adapted from Die Welt 1973.
31
Figure 3: Over-the-air signal strength of West German television broadcasts within the
Dresden district
The map shows spatial variation in access to West German television across the 17 counties in the Dresden
district. White areas had no access, areas shaded in light grey had partial access, and areas shaded in dark
grey had full access to West German television.
Source: Adapted from original map in Bundesarchiv [Federal Archives] SAPMO DY 30/J IV2/2/2317: 75.
32
9.89
10.89
11.89
12.89
1.90
2.90
3.90
10
5
Counties
15
20
First Monday
demonstration
in Leipzig
treated group
Berlin Wall
falls
0
control group
9.89
10.89
11.89
12.89
First free
elections
1.90
2.90
3.90
Time
Figure 4: Rates of protest diffusion in counties with and without West German television
The graph contrasts protest diffusion in 22 counties without West German television with protest diffusion
in 22 matched counties with West German television. The dashed curve is the cumulative sum of control
counties with protests and the solid curve is the cumulative sum of treated counties with protests. Counties
are weighted by the square root of their population size.
33
60
30
0
−30
control − treated protest events
−60
First Monday
demonstration
in Leipzig
9.89
10.89
Berlin Wall
falls
11.89
12.89
First free
elections
1.90
2.90
3.90
Time
Figure 5: Cumulative sum plot of the difference in the number of daily protests in counties
with and without West German television
The graph displays differences (vertical histogram-like bars) in the number of daily protest events in control
and matched treated counties. The horizontal axis shows time; the vertical axis the difference in the number
of protests. The horizontal line at zero denotes the baseline of no difference between the treated and control
groups. The jagged red line is the cumulative sum of the differences in the number of protest events with
a bootstrapped point-wise .90 rejection region denoted by dashed curves. Counties are weighted by the
square root of their population size.
34
40
20
0
−20
−40
control − treated protest participants (x 100,000)
First Monday
demonstration
in Leipzig
9.89
10.89
Berlin Wall
falls
11.89
12.89
First free
elections
1.90
2.90
3.90
Time
Figure 6: Cumulative sum plot of the difference in the number of protesters in counties
with and without West German television
The graph displays daily differences (vertical histogram-like bars) in the number of protesters in control
and matched treated counties (× 100,000). The horizontal axis shows time; the vertical axis the difference
in the number of protesters (× 100,000). The horizontal line at zero denotes the baseline of no difference
between the treated and control groups. The jagged red line is the cumulative sum of the differences in the
number of protesters (× 100,000) with a bootstrapped point-wise .90 rejection region denoted by dashed
curves. Counties are weighted by the square root of their population size.
35
Foreign Media and Protest Diffusion in
Authoritarian Regimes: The Case of the 1989 East
German Revolution
Appendix
Not intended for publication
Holger Lutz Kern
Yale University
November 2008
This appendix contains a sensitivity analysis for the multiple imputation procedure. It is
my hope that, if the paper is accepted for publication, this appendix can simply be made
available to readers via a dedicated web page for the paper.
I. Sensitivity Analysis for Multiple Imputation
The missing at random (MAR) assumption would be violated if smaller protests had a
higher probability of lacking information about the number of protesters even conditional
on covariates such as population density and population size. In order to ascertain what
consequences such a violation of the MAR assumption would have for my results, I implement a sensitivity test proposed by Rubin (1987). If smaller protests were more likely
to have missing information, the imputation algorithm would systematically overpredict
missing protest sizes. I therefore systematically reduce these imputed protest sizes (while
leaving the observed protest sizes as they are), assuming that imputed values are 33 %,
100 %, and 300 % too large. Figure A shows the results. The black curve is identical
to the cumulative sum curve shown in Figure 6 in the paper; it is based on the multiple
imputations generated by my standard imputation model. The blue lines are cumulative
sum curves conditional on varying amounts of overprediction (33 %, 100 %, and 300 %).
As one can see, up to the end of November the cumulative sum curve is not at all affected
by overprediction. Beginning in December, overprediction would lead to small changes in
the shape of the cumulative sum curve but these changes are quite small and substantively
irrelevant. Clearly, my analysis is insensitive to violations of the MAR assumption that
would lead to severe upward bias in the multiple imputation of missing protest sizes.
1
40
20
0
−20
−40
control − treated protest participants (x 100,000)
First Monday
demonstration
in Leipzig
9.89
10.89
Berlin Wall
falls
11.89
12.89
First free
elections
1.90
2.90
3.90
Time
Figure A: Sensitivity analysis for multiple imputations
The graph replicates Figure 6 in the paper but adds three additional cumulative sum curves (blue lines)
that would result from varying amounts of overprediction (33 %, 100 %, and 300 %).
2