The document presents a theoretical model of how authoritarian regimes use censorship in response to new communication technologies that facilitate protests. The model predicts that: 1) New technologies threaten regimes' survival, but less so in economies with low ICT intensity. 2) Less competent regimes are more likely to use coordination censorship, especially in low ICT economies. 3) Intermediate regimes are more likely to use content censorship. The paper tests these predictions using data on DDoS attacks and VPN usage as proxies for censorship.

1. Introduction Model Analysis Empirics Summary Appendix
Information and Communication Technologies,
Protests, and Censorship
Maxim Ananyev
University of Melbourne
Maria Petrova
University Pompeu Fabra and New Economic School
Dimitrios Xefteris
University of Cyprus
Galina Zudenkova
TU Dortmund University
Ananyev, Petrova, Xefteris & Zudenkova ICT, Protests, and Censorship

2. Introduction Model Analysis Empirics Summary Appendix Motivation Literature
Motivation
New communication technologies (Internet, online social
networks) can reduce the costs of collective action and pose a
threat to the stability of authoritarian regimes.
If new technologies indeed facilitate protests and revolutions,
can the regimes counteract it?
Do innovations in state censorship follow the innovations in
communication technologies?
Ananyev, Petrova, Xefteris & Zudenkova ICT, Protests, and Censorship

3. Introduction Model Analysis Empirics Summary Appendix Motivation Literature
Motivation
Advances in ICT (such as social media) played an important role
in protest movements in Egypt, Russia, China, and all over the
world.
Enikolopov et al. 2016; Acemoglu et al. 2018; Qin et al. 2017;
Steinert-Threlkeld et al. 2015; Aday et al. 2010; Frye et al. 2014.
However, improvements in communication technologies do not
necessarily lead to political changes.
E.g., no large-scale protests in Iran or Saudi Arabia despite the
fast growth of Internet and a quick increase of social media
penetration.
Ananyev, Petrova, Xefteris & Zudenkova ICT, Protests, and Censorship

4. Introduction Model Analysis Empirics Summary Appendix Motivation Literature
Motivation
Authoritarian regimes can counteract and use censorship techniques
(Morozov 2010, Esfandiari 2010, Guriev and Treisman 2015).
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5. Introduction Model Analysis Empirics Summary Appendix Motivation Literature
This paper
We develop a theoretical model of censorship where
new communication technologies might be used to organize
protests and revolutions;
these technologies allow for both spread of information and
coordination;
two types of censorship could be used by the government to
counteract:
content censorship (obfuscating news);
coordination censorship (temporary shutting down the channels
for coordination);
censorship costs can depend on its externalities on the production
sector of the economy (ICT intensity of the economy).
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6. Introduction Model Analysis Empirics Summary Appendix Motivation Literature
Our theory predicts that
New technologies hurt the chance of survival of authoritarian
governments, but less so in the economies with low ICT
intensity.
Less competent regimes are more likely to use coordination
censorship.
This effect is stronger in economies with low ICT intensity.
Intermediate-type regimes are more likely to use content
censorship.
Higher costs of staging protests lead to less censorship.
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7. Introduction Model Analysis Empirics Summary Appendix Motivation Literature
Empirically
We test the model predictions using high-frequency data.
We find that the within-country patterns of
DDoS attacks (our proxy for coordination censorship) and
VPN usage (our proxy for content censorship)
are consistent with the model predictions.
Ananyev, Petrova, Xefteris & Zudenkova ICT, Protests, and Censorship

8. Introduction Model Analysis Empirics Summary Appendix Motivation Literature
Literature
Models of state censorship under the threat of regime change
(Edmond 2013, Shadmehr and Bernhardt 2015, Redlicki 2016).
Neither of these papers considers coordination mechanism and
the possibility of coordination censorship.
Little (2015) considers coordination mechanism but no state
censorship (only partial equilibrium).
Empirical studies of state censorship are rare (King et al. 2013,
2014; Qin et al. 2016; Knight and Tribin 2016).
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9. Introduction Model Analysis Empirics Summary Appendix Outline Citizens Regime Censorship Timing
Model Outline
Consider an authoritarian regime and two representative citizens.
The regime wants to stay in power.
Each citizen decides independently and simultaneously
whether or not to participate in an upcoming uprising against the
regime,
and if so what tactic to use, tactic A or tactic B.
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10. Introduction Model Analysis Empirics Summary Appendix Outline Citizens Regime Censorship Timing
Model Outline
Tactic – any logistical details of the protest such as date, place,
strategy, maneuver, concessions, etc.
Neither the regime nor the citizens know what tactic is
successful, tactic A or tactic B.
They share a common prior that tactic A is successful with
probability p ∈ (0, 1).
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11. Introduction Model Analysis Empirics Summary Appendix Outline Citizens Regime Censorship Timing
Model Outline
The uprising succeeds and so the regime is overthrown if and
only if both citizens revolt using the successful tactic.
Otherwise, the protest fails and the regime stays in power.
It punishes the protestors severely (puts them in jail) if both
citizens take part in the uprising but fail to coordinate on the
successful tactic.
If only one citizen revolts then the regime introduces a less
severe punishment (Magaloni and Wallace 2008).
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12. Introduction Model Analysis Empirics Summary Appendix Outline Citizens Regime Censorship Timing
Citizens
The strategy space of each citizen: {PA, PB, NP}
(protest using tactic A, protest using tactic B, not protest).
γ > 0 – citizen’s cost of protesting.
Each citizen derives expected utility ∈ R in case of the regime
change,
and utility θ ∈ R in case of the regime survival.
θ – the regime’s competence.
If both citizens take part in the unsuccessful revolution, each
protestor incurs a large penalty cost κ ≥ κ > 0.
No penalty cost if only one citizen protests.
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13. Introduction Model Analysis Empirics Summary Appendix Outline Citizens Regime Censorship Timing
Citizens
Citizens’ payoffs:
PA PB NP
PA p + (1 − p) (θ − κ) −γ, θ − κ − γ, θ − γ,
p + (1 − p) (θ − κ) −γ θ − κ − γ θ
PB θ − κ − γ, p (θ − κ) + (1 − p) − γ, θ − γ,
θ − κ − γ p (θ − κ) + (1 − p) − γ θ
NP θ, θ, θ,
θ − γ θ − γ θ
The citizens share common priors about regime type θ ∼ f (·) and the
successful tactic, Pr (A is successful) = p.
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14. Introduction Model Analysis Empirics Summary Appendix Outline Citizens Regime Censorship Timing
Regime
The regime wants to survive and so maximizes the probability
that the protest fails.
It can use content and/or coordination censorship to strengthen
its chances of staying in power.
The regime knows its type θ.
It has a prior about the citizens’ expected utility from a new
government ∼ g (·).
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15. Introduction Model Analysis Empirics Summary Appendix Outline Citizens Regime Censorship Timing
Censorship
With probability 1 − q, mass media has no information about
regime type θ.
With probability q ∈ (0, 1), mass media has information about
regime type θ.
But the regime might censor, which leads to obfuscation.
Content censorship – the regime’s hidden action to prevent the
citizens from learning θ from the mass media.
c ≥ 0 – the regime’s cost of content censorship.
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16. Introduction Model Analysis Empirics Summary Appendix Outline Citizens Regime Censorship Timing
Censorship
The citizens obtain information about θ from the mass media if
the mass media has it and
the regime applies no content censorship.
Otherwise the citizens obtain no information about θ from the mass
media. Then
with probability r ∈ (0, 1), the citizens have no information
about θ,
but with probability 1 − r, the citizens still learn θ (e.g., from
international media).
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17. Introduction Model Analysis Empirics Summary Appendix Outline Citizens Regime Censorship Timing
Censorship
Information about successful tactic (A or B) is transmitted via
social media.
But the regime might censor social media.
Coordination censorship – the regime’s action to shut down the
social media and so prevent the citizens from learning the
successful tactic.
The citizens observe the regime’s choice of coordination
censorship.
d ≥ 0 – the regime’s cost of coordination censorship.
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18. Introduction Model Analysis Empirics Summary Appendix Outline Citizens Regime Censorship Timing
Timing
Nature randomly draws the regime type θ, citizens’ expected
utility from a new government and successful tactic of the
uprising (A or B) from the corresponding distributions.
The regime decides whether to apply content and/or coordination
censorship.
The citizens decide independently and simultaneously whether
or not to participate in the revolt, and if so what tactic to use.
The regime is either overthrown or not, and the citizens get their
corresponding payoffs.
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19. Introduction Model Analysis Empirics Summary Appendix Outline Citizens Regime Censorship Timing
Equilibrium Concept
Perfect Bayesian equilibrium:
the citizens’ beliefs about the regime type,
their protest participation decisions and tactic choices,
the regime’s censorship actions.
Equilibrium selection:
risk dominance criterion (see Harsanyi and Selten 1988).
WLG, assume that the successful tactic is A.
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20. Introduction Model Analysis Empirics Summary Appendix Citizens Regime Equilibrium Comparative Statics
Citizens’ Problem
If the regime uses coordination censorship then the citizens
do not protest.
Intuition.
They realize that without learning the tactic, they might fail to
coordinate during the uprising.
The regime would survive and punish them severely, which
implies low expected payoffs from protesting.
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21. Introduction Model Analysis Empirics Summary Appendix Citizens Regime Equilibrium Comparative Statics
Citizens’ Problem
If the regime does not apply coordination censorship then the
citizens’ decision about protesting is determined by the regime
competence (or the expectation of it).
If the citizens observe or expect that the regime is competent
enough then they do not protest.
Otherwise, they protest using the successful tactic learnt via
social media.
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22. Introduction Model Analysis Empirics Summary Appendix Citizens Regime Equilibrium Comparative Statics
Citizens’ Problem
Lemma
1 Suppose that the regime applies no coordination censorship and
the citizens observe θ.
They do not protest if θ ≥ − 2γ, and protest using tactic A
otherwise.
2 Suppose that the regime applies no coordination censorship and
the citizens do not observe θ.
They do not protest if E [θ|b] ≥ − 2γ, and protest using tactic A
otherwise;
b – the citizens’ beliefs about θ in this information set.
3 Suppose that the regime uses coordination censorship.
Then the citizens do not protest.
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23. Introduction Model Analysis Empirics Summary Appendix Citizens Regime Equilibrium Comparative Statics
Regime’s Problem
If the mass media has no information about regime type θ then:
No content censorship.
The regime decides whether or not to use coordination
censorship.
The regime’s expected utility:



1 − d if coordination censorship,
rG (E [θ|b] + 2γ) + (1 − r) G (θ + 2γ) otherwise,
G (·) – CDF of the regime’s prior about the citizens’ expected
utility from a new government .
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24. Introduction Model Analysis Empirics Summary Appendix Citizens Regime Equilibrium Comparative Statics
Regime’s Problem
If the mass media has information about regime type θ then:
The regime decides whether or not to use content and/or
coordination censorship.
The regime will not use both types of censorship simultaneously.
The regime’s expected utility:



1 − d if coordination censorship,
rG (E [θ|b] + 2γ) + (1 − r) G (θ + 2γ) − c if content censor.,
G (θ + 2γ) otherwise.
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25. Introduction Model Analysis Empirics Summary Appendix Citizens Regime Equilibrium Comparative Statics
Regime’s Problem
Theorem
For any parameter configuration, every equilibrium is characterized
by an ordered pair (θ , θ ) ∈ (R ∪ {−∞, +∞})2 with θ ≤ θ such
that
1. a regime of type θ ≤ θ opts for coordination censorship,
2. a regime of type θ < θ < θ uses content censorship,
3. and a regime of type θ ≥ θ applies no censorship.
This result specifies a unique order of censorship choices as a
function of θ.
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26. Introduction Model Analysis Empirics Summary Appendix Citizens Regime Equilibrium Comparative Statics
Equilibrium Characterization
We prove equilibrium existence and uniqueness for all
admissible parameters of the model.
While the order of censorship choices cannot be reversed in
equilibrium, it is possible that a particular type of censorship
does not occur in equilibrium.
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27. Introduction Model Analysis Empirics Summary Appendix Citizens Regime Equilibrium Comparative Statics
Equilibrium
The regime’s content obfuscation is effective in equilibrium.
The citizens cannot perfectly infer θ in the absence of a media
report.
The citizens play a coordination game.
This intensifies the effectiveness of censorship since the citizens’
actions are strategic complements.
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28. Introduction Model Analysis Empirics Summary Appendix Citizens Regime Equilibrium Comparative Statics
Comparative Statics
Assumption: regimes with higher ICT intensity face higher costs of
coord. censorship (Ackermann 2017).
Theorem
1. Less competent regimes are more likely to use coordination
censorship.
This effect is stronger in economies with low ICT intensity.
2. Intermediate-type regimes are more likely to use content
censorship.
3. Higher costs of staging protests lead to less overall censorship and,
in particular, less coordination censorship.
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29. Introduction Model Analysis Empirics Summary Appendix Strategy Data Empirical Results
Empirical Strategy
We test the model predictions using within-country data.
A conceptually novel approach.
Idea: relevant policy questions change often, even within a
country headed by the same government.
Assumption: each period, the government decides about
censorship and the citizens decide about protests ignoring
information on the government’s prior behavior because of
quickly changing environment.
It allows us to test the model predictions using high-frequency
within-country data on censorship.
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30. Introduction Model Analysis Empirics Summary Appendix Strategy Data Empirical Results
Data: Sovereign Bond Yields
We measure the quality of a regime by the sovereign bond yields
(daily data).
Those yields measure the financial market’s estimates of the
probability that a government will default on its obligations.
A useful operationalization of the concept of “regime quality”
from the model.
64 autocratic countries, Investing.com.
For most of the countries, we use yields of 10-year bonds (daily
data).
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31. Introduction Model Analysis Empirics Summary Appendix Strategy Data Empirical Results
Data: DDoS attacks
We use the data on Distributed Denial-of-Service attacks (DDoS
attacks) to measure coordination censorship (daily data).
DDoS attacks happen when a certain website is flooded by the
automated requests that exceed the website’s capacity, and the
website temporarily goes down.
Daily data on attacks that happened between June 1, 2013 (when
the website was launched) until Feb 28, 2015.
We control for other reasons (apart from coordination
censorship) that make DDoS attacks more likely: level of GDP
per capita, a share of people having access to Internet and Polity
2 score.
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32. Introduction Model Analysis Empirics Summary Appendix Strategy Data Empirical Results
Data: DDoS attacks
Website Digital Attack Map – a collaboration between Google Ideas
and a software security firm Arbor Networks.
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33. Introduction Model Analysis Empirics Summary Appendix Strategy Data Empirical Results
Data: DDoS attacks
Adjusted for the regime type, level of economic development and
Internet penetration, Freedom of the Net scores are positively
correlated with the number of DDoS attacks.
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34. Introduction Model Analysis Empirics Summary Appendix Strategy Data Empirical Results
Data: DDoS attacks
After the adjustment for GDP, Internet penetration and regime type,
higher number of DDoS attacks is associated with higher levels of
political filtering.
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35. Introduction Model Analysis Empirics Summary Appendix Strategy Data Empirical Results
Data: VPN services
We employ data on the usage of VPN services as a proxy of
content censorship (quarterly data).
People use VPN services to access prohibited content.
globalwebindex.net
VPN quality is unstable and VPNs slow down already imperfect
speed of the Internet
⇒ it allows the citizens to eventually get access to censored
information, but does not allow its users to smoothly and quickly
coordinate their collective action.
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36. Introduction Model Analysis Empirics Summary Appendix Strategy Data Empirical Results
Data: Snow and ICT
We use the indicator for snow as a proxy for cost of protest (daily
data).
wunderground.com.
We use data on ICT intensity of the economy.
Country-level ICT intensity is calculated from the employment
data from UNIDO, and industry-level ICT intensity of the US
industries from the Wall Street Journal.
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37. Introduction Model Analysis Empirics Summary Appendix Strategy Data Empirical Results
Coordination Censorship and Regime Competence
Sovereign Bond Yield and DDoS Attacks: Daily Data.
One percent increase in sovereign yield is associated with 2
percentage point increase in the daily risk of a DDoS attack.
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38. Introduction Model Analysis Empirics Summary Appendix Strategy Data Empirical Results
Coordination Censorship and Regime Competence
Competence-censorship effect is stronger in economies with low ICT
intensity.
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39. Introduction Model Analysis Empirics Summary Appendix Strategy Data Empirical Results
Coordination Censorship and Costs of Protest
Snow and DDoS Attacks: Daily Data.
An instance of snow is associated with the decrease of the probability
of a DDoS attack by 4-6 percentage points.
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40. Introduction Model Analysis Empirics Summary Appendix Strategy Data Empirical Results
Content Censorship and Regime Competence
Sovereign Bond Yield and VPN Usage: Quarterly Data.
The signs are consistent with the theory but the results are noisy.
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41. Introduction Model Analysis Empirics Summary Appendix Strategy Data Empirical Results
Content Censorship and Cost of Protests
Snow and VPN Usage: Quarterly Data.
Results are not driven by northern countries like Russia, but rather by
the incidence of snow in southern countries like Turkey, Iran, Mexico.
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42. Introduction Model Analysis Empirics Summary Appendix
Summary
We contribute to the literature on regime change by
differentiating between two types of state censorship:
coordination censorship (which prevents people from
coordinating an anti-regime collective action),
and content censorship (which prevents people from learning
about the regime quality).
We develop a model that explicitly considers the regime’s choice
of censorship type.
The model generates predictions that relate the choice of
censorship to the costs of protests and the regime quality.
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43. Introduction Model Analysis Empirics Summary Appendix
Summary
We test the model predictions and find that they are corroborated by
the data:
coordination censorship is used by less competent governments;
this effect is stronger in countries with low ICT intensity;
content censorship is used by intermediate-type governments;
higher costs of protests are associated with less censorship.
Clear prediction for future political dynamics of authoritarian
regimes:
As ICT intensity of the economy increases, the regime might find it
more costly to use censorship to suppress coordination.
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44. Introduction Model Analysis Empirics Summary Appendix Literature Equilibrium
Literature
Informational cascades:
Bikhchandani, Hirshleifer and Welch (1992),
Lohmann (1994, 2000).
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45. Introduction Model Analysis Empirics Summary Appendix Literature Equilibrium
Equilibrium Characterization
For the sake of tractability, we focus on a simpler case c = 0.
We prove equilibrium existence and uniqueness for all
admissible parameters of the model.
θ1 ∈ R – a regime type indifferent between coord. and no
censorship when the mass media has no info about θ, and
between coord. and content censorship when the mass media has
info about θ:
1 − d = rG (E [θ|b] + 2γ) + (1 − r) G (θ1 + 2γ) .
θ2 ∈ R – a regime type indifferent between content and no
censorship when the mass media has info about θ:
θ2 = E [θ|b] .
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46. Introduction Model Analysis Empirics Summary Appendix Literature Equilibrium
Belief Updating
E [θ|b]?
The citizens do not observe θ but know that the regime doesn’t
use coord. censorship.
They realize that either
1 the media has no info about θ and the regime doesn’t censor ⇒
the regime is of type θ > θ1, or
2 the media has info about θ and the regime censors content ⇒ the
regime is of type θ1 < θ < θ2.
The media has info about θ with probability q ⇒
E [θ|b] =
(1−q) +∞
θ1
zf(z)dz+q
θ2
θ1
zf(z)dz
(1−q)(1−F(θ1))+q(F(θ2)−F(θ1)).
Ananyev, Petrova, Xefteris & Zudenkova ICT, Protests, and Censorship