Autocrats Untying Their Hands-Political Prosecution of...

ISA Hong Kong 2017 Jia Li June 15 [email protected]

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Autocrats Untying Their Hands: Political Prosecution of

Corruption in a Limited Autocracy

Jia Li, University of Chicago

Abstract

Autocrats have an incentive to purge rival elites in the course of anticorruption. But

can an autocrat purge his rivals by political prosecution in a limited autocracy where

power-sharing arrangements tie his hands? Empirical observation from China, an

institutionalized autocracy with a history of politicized anticorruption, sheds light on

this question. Xi Jinping’s anticorruption campaign provides network evidence that the

autocrat is untying his hands and purging rivals despite the constraints on his power.

Studying the network where purged elites are nodes and their colleague relations are ties,

this paper argues that the emphasis on political prosecution against an elite explains his

centrality in the purged network, which suggests that political prosecution drives the

campaign as much as cleansing graft does. The independent variable, emphasis on

political prosecution, is estimated by the ratio of intraparty duration to procuratorial

duration. Centrality, as the dependent variable, is constructed by PageRank algorithm.

The finding suggests that an autocrat in a limited autocracy is capable of reneging on

power sharing.

Keywords: limited autocracy; network analysis; corruption; China


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Autocrats with hands tied: can they purge rivals by political prosecution?

Autocrats have an incentive to purge rival elites in the course of anticorruption. As a strategy

to enforce political order, they manipulate judicial processes and employ courts to monitor

regime elites (Magaloni, 2008b). Cleansing graft is a convenient excuse for purging rivals.

Autocrats use anticorruption agencies as political instruments to repress regime elites (Svensson,

2005). In autocracies, anticorruption is enforced in a highly selective way, based on political

considerations as well as economic graft (Manion, 1998). It is a politicized cause that serves to

consolidate autocrats’ power.

In limited autocracies, however, the power of autocrats is substantially constrained by

power-sharing arrangements. Autocrats rule on the consent of small-sized selectorate (Bueno de

Mesquita, et al., 2003). They have to credibly commit themselves to sharing power in institutions

with regime elites in order to build and secure the loyalty of their winning coalitions (Gandhi &

Przeworski, 2007; Magaloni, 2008a; Boix & Svolik, 2013). Institutionalization reduces the risk

of coup, but the rule of autocrats remains under threat of allies’ rebellion (Svolik, 2012). Regime

elites may challenge autocrats via power-sharing institutions. The power of autocrats in limited

autocracies is therefore constrained. It leads us to question to what extent those autocrats can

prioritize their personal agenda at the expense of regime elitesat large when they wield

autocratic power.

Can an autocrat, with his hands tied by power-sharing arrangements in a limited autocracy,


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take advantage of anticorruption and massively purge his rivals? China is an example of

institutionalized durable autocracy. This paper provides evidence from Xi Jinping’s

anticorruption campaign that power-sharing arrangements can be fragile. This paper shows that

the network structure of purged elites is shaped by political prosecution as much as by the efforts

to cleanse graft. It means that the Chinese autocrat is untying his hands and breaking down the

established power-sharing deals.

China: anticorruption in a limited autocracy

The regime of the Communist Party of China (CCP1) provides an example of

institutionalized and durable autocracy. After Mao Zedong, the regime has developed a system

of reciprocal accountability: the Central Committee under the command of the Politburo, and the

Politburo in turn held accountable to the Central Committee (Shirk, 1993). Power sharing has

been effectively established in the post-Deng China. In the absence of a strongman,

arrangements that divide the party-state’s supreme power between standing members of the

Politburo emerge and consolidate. This institutional design of “collective leadership” (jiti

lingdao) is the key to China’s developmental miracle (Hu, 2014b). Some scholars go as far as

calling it a “collective presidency (jitizongtong zhi)” (Hu, 2012; 2014a). The party-state

delegates power to its bureaucrats in functional and local agencies who enforce policies made by

1 The party uses “CPC” as its official abbreviation, but “CCP” is more commonly used in the English-speaking world. This paper refers the party as “CCP”.


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the party center, and bureaucratic interests significantly dictate policy outcomes (Lieberthal &

Oksenberg, 1988). Moreover, conventions on power transition have emerged and functioned

effectively on recent occasions: from Deng Xiaoping to Jiang Zemin and to Hu Jintao (Kou,

2010), and most lately to Xi Jinping. The durability of CCP regime is largely attributed to its

power-sharing institutions that alleviate the monitoring problems between autocrats and regime

elites (Svolik, 2012). This durability, however, comes with a cost. An autocrat selected by

institutionalized rules is fettered thereby, and so he can hardly overturn the regime’s fundamental

programs (Kou, 2006; 2010). His personal autocracy is vulnerable to potential challenges by

regime elites at large. Power-sharing arrangements tie his hands when he seeks to meet critical

challenges in governance – the “tough bones” (Chan, 2014) – and leave a legacy in CCP history

(Zhai, 2014).

Many China watchers expect Xi to try untying his hands and striking down his enemies in

an anticorruption campaign (Huang, 2014; Sternberg, 2014; Tiezz, 2014; Wang, 2014). This

means that he will effectively break down the power-sharing arrangements. Power sharing,

indeed, can be fragile. It frequently fails in the emergence of an established autocracy: if the

autocrat is able to repress regime elites in the course of his personalizing power, regime elites

may eventually lose their capacity of allies’ rebellion that keeps the autocrat in check (Svolik,

2012). In the case of China, a massive anticorruption campaign can evidence such a process. If

we observe a campaign that is structurally driven by political prosecution, we may infer that the


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autocrat is pursuing his own agenda against the will of regime elites at large and thus power

sharing is falling apart.

China has a long record of politicized anticorruption. Cleansing graft is never the only

rationale behind (Wedeman, 2005). In part, China’s periodic and concerted anticorruption efforts

are by-products of its economic policies (Quade, 2007). The “higher” goals of CCP, including

state transformation in 1949-1953, regime consolidation in 1954-1966 and national

modernization since 1978, fuel its fight against corruption (Gong, 1994). Leaders in communist

regimes are well aware that corruption undermines the foundation of their regimes and

sometimes take proactive measures (Holmes, 1993). The regimes wage campaigns when they

expect to gain incremental legitimacy therefrom (Manion, 2004).

They do not, however, crack down corruption at all cost. In China, CCP omits high-level,

high-stakes corruption cases so as to prevent damage to the party’s image (Fabre, 2001).

Punishing senior officials results in a waste of the regime’s human capital investment on those

fallen cadres (Zhu, 2015). Besides, corruption enhances CCP’s control over its party apparatuses

because graft provides elites with economic compensation (Fan & Grossman, 2001).

Anticorruption is, therefore, a mere “symbolic” issue (Guo, 2014). When the regime does decide

to prosecute top leaders for corruption, it is often more about power struggle than cleansing graft

per se (Wedeman, 2012). In China, the issue of corruption has turned a weapon against political

enemies (Shirk, 1993). For example, Zhou Yongkang’s downfall is deemed as a result of his


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conspiracy with Bo Xilai to challenge Xi’s position (Guo, 2014). In this paper, we go beyond

analyzing individual cases and look for evidence at the campaign’s structural level.

Argument: political prosecution and network centrality

The elites prosecuted in an anticorruption campaign can be analyzed in the purged network

where each purged elite is a node and their colleague relations are ties. Figure 1 is a sketch that

illustrates how such a network may be structured. Some nodes are obviously more central than

others in this illustrative network. A number of individual attributes of political elites may

account for the varying centrality. First, an elder elite is more likely to occupy a central network

position, as an elite with a longer career can form more colleague relations in the course. Second,

political mobility of an elite has an impact on his position. If an elite has served in many an

institution, he is more likely to be central in the network than someone else who builds the entire

career in one single place. Third, political seniority affects centrality. A higher-ranking elite has

formed colleague relations at various levels in the political hierarchy of the regime, and so he is

expected to occupy a central position.

The network we are interested in is not composed of all elites; rather, it is a purged network.

Some attributes specific to purged elites also explain their centrality. Centrality of an elite in the

purged network is about how many colleagues of his are prosecuted and therefore in the purged

network. Ties in this purged network are not colleague relations per se: colleague relations are


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mere “trellis” that hold the actually meaningful interrelations between the purged elites.2 This

paper is to discover what these meaningful interrelations are.

Figure 1: Illustrative Network

The purged network is a subset of the entire elite network. It grows as the anticorruption

campaign unfolds, evidence of economic or political corruption emerges that links one elite to

others, and thus other elites are put under investigation as well. Structurally, an elite is central in

the purged network if his case leads anticorruption agencies to many of his colleagues. For

example, if an elite is involved in a large amount of graft in numerous cases, there is a good

chance that many of his colleagues collude with him. The more corrupt one elite is, the more

evidence of graft should emerge during his investigation, and so the more colleagues in collusion

with him will be further inspected. If the campaign aims only at cleansing graft, we should

interpret the ties in the purged network as the collusion of economic graft. The centrality of an

elite, therefore, is determined by the value of graft in his case.

2 They are “trellis” in a way similar to how Andrew Nathan (1973) theorizes the relationship between formal bureaucracies and factional ties in Chinese politics.


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Conversely, as this paper would argue, an elite may be central in the purged network

because his investigation emphasizes on political prosecution. If the autocrat deems an elite as a

potential threat and intends to unseat him, the autocrat will not prosecute the threatening

individual alone but also purge those who are close to him. Anticorruption agencies will find

evidence of a clique around the targeted elite. The emphasis on political prosecution against an

elite makes him the hub of a clique. If political prosecution structurally drives the anticorruption

campaign, the meaningful interrelations underlying the ties should be potential political alliance.

Centrality, in this case, is a product of the emphasis on political prosecution.

Figure 2: Causal Mechanism

Figure 2 presents the argument. The emphasis on political prosecution against an elite is the

independent variable that causally leads to his centrality in the purged network. Emphasis on

political prosecution is estimated by its relative duration, that is, the ratio of intraparty duration

to procuratorial duration. This paper uses PageRank to measure centrality.

Network: elites prosecuted for corruption in Xi’s early reign

PageRank score of a node

�

DV: Centrality of an elite in purged network

�measured by�

IV: Emphasis on political prosecution against an elite

Statistical correlation�

Causal mechanism�

Relative duration of political prosecution

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Purged elites as nodes

This paper studies the network of CCP elites, at or above vice-provincial/ministerial/army

level,3 who are prosecuted for corruption during Xi Jinping’s early reign from November 2012

to March 2015. There are 104 elites in the sample, including 72 civilian cadres and 32 military

generals (see Appendix and Table 1). The unit of analysis is individual elite.

Table 1: Elites Prosecuted for Corruption in Xi Jinping’s Early Reign

Civilian Cadres Rank Level1 FS VS FP VP Total

Number of Elites 1 2 7 62 72 Military Generals

Rank Level2 VS FMR VMR FA VA Total Number of Elites 1 0 6 10 15 32

Note: Data for civilian cadres from CCDI website at http://www.ccdi.gov.cn/jlsc/, and for military generals from the

website of People’s Liberation Army (PLA) at http://www.81.cn/.

1. Civilian rank levels: FS: full-state level; VS: vice-state level; FP: full-provincial level; VP: vice-provincial level.

2. Military rank levels: VS: vice-state level; FMR: full-military-regional level; VMR: vice-military-regional level;

FA: full-army level; VA: vice-army level. The vice-/full-military-regional levels are considered between the state

levels and the provincial levels.

The campaign during Xi’s early reign is impressive because of the number and seniority of

the “big tigers” it hunts down. For the first time in CCP history, a retired standing member of the

Politburo, Zhou Yongkang, is put in jail for corruption. Also a first-timer, a retired

Vice-Chairman of Central Military Commission (CMC), Xu Caihou, is hunted down.4 Two

incumbent national leaders, both as Vice-Chairman of the National Committee of the Chinese

3 Provincial level (sheng ji), ministerial level (bu ji) and army level (jun ji) refer to the same rank level in different institutions. “Provincial level” is used in local hierarchies in provinces, provincial-level municipalities or their equivalents. “Ministerial level” applies to positions or cadres in central institutions, e.g. ministries of the State Council, central departments of CCP Central Committee, etc. “Army level” is a rank level in the military. In this paper, we mostly use “provincial level” for short. 4 Guo Boxiong, the other Vice-Chairman of CMC during Hu Jintao’s reign, was investigated for corruption in April 2015. He is the second vice-state-level military leader who ever falls down due to corruption in CCP history.


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People’s Political Consultative Conference (CPPCC), are prosecuted.

March 2015 marks the end of Xi’s early reign for three reasons. First, by that time Xi had

assumed offices of all major positions that grant him the autocratic power. He was elected the

General Secretary of CCP and the Chairman of CMC in November 2012, became the President

of the People’s Republic of China in March 2013, found and chaired the Central Leading Group

for Comprehensively Deepening Reform and the National Security Commission in January 2014,

and found and chaired the CMC Leading Group for Deepening National Defense and Military

Reform in March 2014. The general secretaryship of the party, the chairmanship of the military

and the presidency of the state compose the trinity of supreme power in post-Deng China, and

the three newly founded coordinating institutions are critical to the expansion of Xi’s power

beyond his two predecessors.

Second, Xi proclaimed his pivotal programs, the “Four Comprehensives”, in February 2015

(“Renmin ribao”, 2015). Those programs include: to comprehensively build a moderately

prosperous society; to comprehensively deepen reform; to comprehensively govern the nation

according to law; and to comprehensively strictly govern the party. In February 2015, the four

programs were fabricated to form an organic whole that pointed to the direction of Xi’s “Chinese

Dream”. They set the tone for the subsequent national “Two Sessions”, the annual meetings of

the National People’s Congress and the National Committee of CPPCC, in the following March.

Third, and most significantly, March 2015 witnesses the first national Two Sessions after Xi


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had assumed all his significant offices and proclaimed his pivotal programs. People’s Congress

and CPPCC are the legislative and political advisory institutions. Constitutionally, the National

People’s Congress is the supreme power organ in the People’s Republic of China, and all

executive, judicial, procuratorial and military branches are ultimately accountable to the National

People’s Congress. CPPCC, on the other hand, serves as the United-Front council that coopts

elites from satellite parties and a wide range of social strata. It makes political sense to set the

end time of Xi’s early reign on a national Two Sessions.

Colleague relations as ties

We code each and every political position that an elite has held in his career. For each

position, we code both its vertical and horizontal affiliation and its start and end time. We then

construct a matrix form where every prosecuted elite occupies a column and a row. Each cell in

this 104×104 matrix denotes whether the column elite and the row elite have any colleague

relation. It is a dummy variable, with 1 denoting the existence of colleague relation – and thus a

tie in the purged network – and 0 for nonexistence.

A colleague relation is coded if two elites have worked in the same institution at the same

time (see Figure 3). They are considered colleagues only if they work in the same unit on the

lowest shared rank level and their full rank levels are the same or next to each other. For example,

a vice provincial governor and a municipal party chief in that province can be colleagues. On the


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other hand, a minister cannot have colleague relation with someone lower than a departmental

vice-director in his ministry.

Figure 3: Coding of Ties

Note: Reprinted from “Xi Jinping’s Tiger Hunt: Fighting Corruption or Fighting Enemies?” by J. Li, 2014, paper presented at Annual Conference of Chinese Association of Political Science, Taipei, Taiwan (ROC).

The purged network

With the nodes and ties coded as above, we apply the Fruchterman-Reingold algorithm for a

force-directed layout (Fruchterman & Reingold, 1991) in R to transform the cadres and their

colleague relations into a sociogram (see Figure 4). The purged network includes 18 isolated

nodes, 4 isolated dyads, and 78 interrelated nodes that form the major component.

The size of each node signifies the elite’s rank level: the higher-ranking an elite, the larger

his node. The only full-state-level elite, Zhou Yongkang, is positioned in the center of the major

component. He took charge of law enforcement from 2007 to 2012 when he was a standing

member of the Politburo. In this network, he has ties with his subordinate cadres from China

National Petroleum Corporation, Sichuan Province, Ministry of Public Security, Politics and

Provincial Party Chief�Provincial Deputy Party Chief�

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Vice-Mayor

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Deputy Director of Department X


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Law Commission, among others.

Figure 4: Network of Purged Elites in Xi’s Early Reign

Note: Data for nodes from CCDI website at http://www.ccdi.gov.cn/jlsc/ and PLA website at http://www.81.cn/, and

for ties from “Chinese Political Elites Database” at http://cped.nccu.edu.tw and “Leading Cadres of CPC and Chinese Government Database” at http://cpc.people.com.cn/gbzl/index.html.

There are three vice-state-level elites in the network. Ling Jihua was a Vice-Chairman of

the National Committee of CPPCC and a former top aide of Hu Jintao. He was the Director of

the General Office of CCP, a position that makes him a broker between numerous nodes. Xu

Caihou, a Vice-Chairman of CMC between 2002 and 2012, is relatively peripheral in the

network because he has few colleague relations with civilian cadres. Su Rong, another

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Vice-Chairman of the National Committee of CPPCC, is tied with cadres who are mostly his

former subordinates in Jiangxi Province. All the four national leaders are marked in brackets.

The Shanxi Clique marked in a dotted-line circle is the only clique5 of more than three

nodes. Those ten prosecuted elites are all colleagues in the standing committee or government of

Shanxi Province, which connects each pair of them.

Research design

Dependent variable: centrality

The dependent variable is centrality, a measurement of a node’s position relative to others

in network. Literature of social network analysis provides various measurements to quantify

different characteristics of nodes. John Padgett and Christopher Ansell (1993) attribute the rise of

Medici family in medieval Florence to their unique position of structural hole between the old

and new prominent families in the city-state. Padgett (2012) also studies China’s economic

reform under Deng Xiaoping and suggests that Deng’s brokerage position, which connects him

with the elders, military elites and reformist faction, facilitates his success.

Besides brokerage, centrality provides a classical perspective of measuring the importance

of a node. People in central positions in network have better opportunities to access and spread

information (de Nooy, Mrvar & Batagelj, 2005). Three basic structural attributes indicate

5 In graph theory, “clique” refers to a maximal complete subnetwork containing at least three nodes and every two of them are connected. It has the maximal density that any two of the nodes that are possible to be connected are connected. For a detailed explanation of concepts like component, clique, faction, density and others, see Chapter 3 in de Nooy, Mrvar & Batagelj (2005) and Chapter 11 in Borgatti, Everett & Johnson (2013).


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centrality in different ways. First, studies of communication activity prefer degree centrality that

counts the number of ties incident with a node. Second, studies concerning control of

communication require betweenness centrality, that is, the number of shortest paths from all

nodes to all others that pass through a given node. Third, studies that focus on independence

suggest closeness centrality, the inverse of the sum of distances between one node and all others

(Freeman, 1979).

This paper uses PageRank, an eigenvector centrality that measures both quantity and quality

of a node’s ties. Google develops the algorithm to rank web pages (Brin & Page, 1998):

𝑃𝑅! = 1− 𝑑 + 𝑑𝑃𝑅!𝐶!!

In the algorithm, PR! is the PageRank score of node i, the one we are interested in. j

stands for all nodes with ties to node i, and C! is the number of ties of node j. We usually set

the damping factor, d, at 0.85 (Brin & Page, 1998). In this paper, PageRank measures the

relative importance of an elite in the purged network. If an elite scores high in PageRank, it

suggests that he occupies a central position among all prosecuted elites.

We expect the centrality distribution to be right-skewed since most elites are not densely

connected to others and only a few are well connected in the purged network. So we perform

logarithmic transformation on PageRank scores in the models so as to make the skewed

distribution proximate to normal.


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Independent variable: political prosecution

We take advantage of the two-stage prosecution procedure in China (see Figure 5) to

estimate the emphasis on political prosecution in a case. The first stage is intraparty inspection.

The Central Commission for Discipline Inspection (CCDI), the principal intraparty

anticorruption agency (Guo, 2014), initiates preliminary inspection against a cadre and decides

whether to go into formal disciplinary inspection. It then takes a varying period of time for CCDI

to conclude party sanction.6 For years, the intraparty inspection and its opaque and coercionary

“double designated” (shuanggui7) have earned a forbidding reputation of brutal torture and

suspects often end up with forced confession (Human Rights Watch, 2016). The second stage is

procuratorial investigation. The Supreme People’s Procuratorate (SPP) investigates into the cases

of senior CCP cadres and files complaints of prosecution with designated provincial courts. The

cases are then heard and cadres sentenced.

6 For a more detailed description of CCDI’s inspection procedure, see Guo (2014). 7 “Shuanggui”, in its literal meaning, refers to the directive that a party member “be present at a designated time and designated location” in order to comply with disciplinary inspection (CCDI, 1994, Article 28 Section 3).


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Figure 5: Intraparty Inspection and Procuratorial Investigation

Among the 104 purged elites in Xi’s early reign, we are able to retrieve complete data of 57

cases. The dates of case proceeding of these cadres are publicly available, either covered in news

reports or publicized by party or state agencies. In the intraparty stage from putting an elite under

disciplinary inspection to concluding the party sanction, CCDI spends 181.79 days on average.

The maximal record, 512 days, belongs to Song Lin, the chairman of board and party chief of a

Hong Kong-based state-owned enterprise. In contrast, it takes CCDI only 50 days to conclude

inspection on Yang Baohua, a Vice-Chairman of Hunan Provincial CPPCC, which sets the

minimal record. In the procuratorial stage from opening criminal investigation to filing a

complaint of prosecution, the average duration is 355.63 days. Chen Chuanping, the Party Chief

of Taiyuan Municipality in Shanxi Province, holds the maximal record of 579 days. The famous

Zhou Yongkang case sets the minimal record at 118 days.

Two-stage prosecution�

Procuratorial investigation�

Intraparty inspection�

2. Announcement of disciplinary

inspection�

3. Dismissal from office�

4. Conclusion of disciplinary

sanction�

6. Prosecution by filing a complaint�

5. Prosecurate opens

investigation�

7. Trial�

Judicial proceeding�

8. Sentence�

1. Preliminary inspection�


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Figure 6: Correlation between Intraparty Duration and Procuratorial Duration

Note: Data for intraparty duration from CCDI website at http://www.ccdi.gov.cn/jlsc/, and for procuratorial duration

from SPP reports at http://www.spp.gov.cn/qwfb/ and other media resources.

It is reasonable to expect that the more complicated or severe a case is, the longer it should

take both party and state agencies to investigate into it. Therefore, the intraparty duration and

procuratorial duration should be highly correlated in a positive way. Counter-intuitively, though,

they are not. Figure 6 presents the intraparty duration versus procuratorial duration of the 57

cases. The Pearson’s r is only 0.036, indicating a very weak correlation.

The puzzling weak correlation results from the difference of substance under investigation

in the two stages (see Table 2). CCDI performs political prosecution as well as inspection on

economic graft. In contrast, the procuratorate is only concerned with offenses of state law and,

0

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300

400

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0 100 200 300 400 500 600

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with few exception, elites are prosecuted for economic graft only. Although the procuratorate

often relies on the evidence and confession obtained in the previous intraparty stage, it has to go

all the way through formal procedures to verify and, if necessary, re-investigate into the facts of

economic graft that have been established by intraparty agencies.

Table 2: Different Substance under Investigation in the Two Stages

Economic Graft Political Prosecution First Stage: Intraparty Inspection

- Taking, seeking or offering bribe;

- Accepting huge amount of gift by oneself or family;

- Embezzlement; - Taking advantage of public

office; etc.

- Forming cliques within the party; - Inappropriate open discussion of

party policy; - Violation of political practices and

political disciplines; - Disloyalty and dishonesty to the

party; etc. Second Stage: Procuratorial Investigation

- Accepting and offering bribe; - Embezzlement; - Huge property without

identified sources; etc.

Note: Data for intraparty inspection from CCDI notices and reports at http://www.ccdi.gov.cn/jlsc/, and for

procuratorial investigation from SPP reports at http://www.spp.gov.cn/qwfb/ and other media resources.

This difference of substance allows us to estimate the emphasis on political prosecution.

Intraparty duration is a function of both effort of political prosecution and value of economic

graft, whereas procuratorial duration is only related to economic graft. The independent variable,

relative duration of political prosecution, is thus estimated by:

𝑝𝑜𝑙𝑖 =d!"#$d!"#$

In this equation, 𝑝𝑜𝑙𝑖 is the relative duration of political prosecution, d!"#$ refers to the

intraparty duration and d!"#$ is the procuratorial duration. Both durations are measured in day.


20

The more emphasis put on political prosecution against an elite, the larger the ratio. We can

show the validity of this estimation by the following proof. Let us suppose that α is an

institutional coefficient that measures the efficiency of intraparty inspection on economic graft, β

is an institutional coefficient that measures the efficiency of intraparty inspection on political

prosecution, and λ is an institutional coefficient that measures the efficiency of procuratorial

investigation into economic graft. Let x be the value of economic graft and y be the emphasis on

political prosecution. We have:

𝑝𝑜𝑙𝑖 =d!"#$d!"#$

=𝛼𝑥 + 𝛽𝑦𝜆𝑥 =

𝛼𝜆 +

𝛽𝜆 ×

𝑦𝑥

Since all cases in our sample are handled by CCDI and under SPP’s direction, the three

institutional coefficients, α, β and λ, are constant in all cases. Therefore, !!, the emphasis on

political prosecution divided by the value of graft, is the only moving part that accounts for the

variation in 𝑝𝑜𝑙𝑖. We can thus conclude that this variable of political prosecution is a valid

estimator of relative emphasis on political prosecution against an elite.

Control variables

1) Graft

We measure economic graft by the monetary value of bribe and embezzlement (million

Chinese Yuan, RMB). If anticorruption agencies only focus on cleansing graft, this variable

should have a larger effect on centrality than political prosecution has.


21

The distribution of graft is right-skewed. The mean value of economic graft of all purged

elites is significantly larger than the median value because of several cases of exceptionally huge

amount of economic corruption. So we log this variable in the models in order to normalize its

distribution.

2) Career length

A cadre with a longer career is likely to have more colleague relations in network. We

measure career length by the number of years of an elite’s public service, from the year he starts

working to the year he is put under disciplinary inspection.

3) Mobility

A mobile career means that an elite has served in numerous institutions, which increases the

chance of him being a colleague with more other elites. We measure mobility by the number of

institutions where an elite has worked. We count institutions at or above vice-provincial level,

such as provinces or provincial-level municipalities, central ministries of the State Council,

central departments of CCP Central Committee, etc.

4) Political seniority

A high-ranking elite has formed colleague relations at various administrative levels and is

thus expected to be central in network. In the models, political seniority is a categorical variable

with three values: state level, full-provincial level and vice-provincial level.


22

Data

We compile the list of prosecuted elites with information from CCP official media. CCDI

puts online its case notices and reports starting from December 2012.8 We compile the list of

civilian prosecuted elites with data retrieved there. The disciplinary actions against military

generals are released at the official PLA website9 from time to time. The list of prosecuted

military elites is compiled based on news reports retrieved there.

To estimate centrality, this paper collects information of colleague relations from the

“Chinese Political Elites Database” constructed by Chien-wen Kou at National Chengchi

University in Taiwan10 and the “Leading Cadres of CPC and Chinese Government Database”

constructed by the official news website of CCP.11 Both databases hold resumes that, in most

cases, include complete career information of senior CCP cadres. We also retrieve information of

career length, mobility and political seniority of purged elites from those databases.

For the variable of political prosecution, this paper relies primarily on public notices that

CCDI and SPP issue. The data of intraparty duration are compiled from CCDI reports.12 For

procuratorate duration, we retrieve information from the SPP website13 and a variety of official

8 See “Jilv Shencha (紀律審查, Disciplinary Inspection)” from Zhongyang jiwei jianchabu wangzhan (中央紀委監察部網站, the website of CCDI/Ministry of Supervision), at http://www.ccdi.gov.cn/jlsc/ 9 See Zhongguo junwang (中國軍網, the website of PLA), at http://www.81.cn/ 10 See “Zhonggong zhengzhi jingying ziliaoku (中共政治菁英資料庫, Chinese Political Elites Database)”, at http://cped.nccu.edu.tw 11 See “Zhongguo dangzheng lingdao ganbu ziliaoku (中國黨政領導幹部資料庫, Leading Cadres of CPC and Chinese Government Database)” constructed by Zhongguo gongchandang xinwen wang (中國共產黨新聞網, CPC News.cn), at http://cpc.people.com.cn/gbzl/index.html 12 See “Jilv Shencha (紀律審查, Disciplinary Inspection)” from Zhongyang jiwei jianchabu wangzhan (中央紀委監察部網站, the website of CCDI/Ministry of Supervision), at http://www.ccdi.gov.cn/jlsc/ 13 See “Quanwei Fabu (權威發布, Official Announcements)” from the website of Zuigao Renmin Jianchayuan (最高人民檢察院網站, SPP website), at http://www.spp.gov.cn/qwfb/


23

media of CCP and state agencies.

Value of graft is learned from procuratorate complaints and court judgments collected in the

same way as for procuratorate duration.

Results and discussion

Table 3 shows descriptive statistics. PageRank measures the network centrality of purged

CCP cadres, which refers to their connectedness to each other in the purged network. Zhou

Yongkang scores the highest PageRank at 0.0373. As a seasoned politician who retires as a

national leader after working in a wide range of party and state institutions, his outstanding

importance in the purged network is expected. In contrast, there are 7 purged cadres who do not

share a colleague relation with anyone else in the purged network and thus score 0 in PageRank.

Table 3: Descriptive Statistics

Civilian Cadres Min Max Mean Median SD Centrality

(PageRank) 0 0.0373 0.0104 0.0091 0.0075

Career Length (years of service)

25 49 38.44 40 5.74

Mobility (number of institutions)

1 10 3.86 4 2.00

Political Seniority (rank level)

1 3 1.23 1 0.54

Graft (million RMB)

0.91 537.97 54.18 20.86 86.58

Political Prosecution (relative duration)

0.14 1.58 0.55 0.44 0.36

N=57

Note: Political seniority: 1=vice-provincial level; 2=full-provincial level; 3=state level.


24

The 57 purged cadres generally started their careers in late 1970s, and so the mean value of

career length is 38.44 years. Their careers are mobile, as they have worked in 3.86 provinces or

ministries on average. Most of the purged cadres are at vice-provincial levels with the exceptions

of 3 national leaders and 7 full-provincial level cadres.

The distribution of the monetary value of their graft is highly right-skewed. The charges

against their economic corruption include bribery, embezzlement, possession of huge amount of

properties without identified sources, etc. The cadre who commits the least graft is Chen

Chuanping, who takes bribes worth 910 thousand RMB. In addition to bribery and

embezzlement, nonetheless, Chen as the Party Chief of Taiyuan Municipality also causes more

than 900 million RMB loss of national assets by his abuse of power. There are 8 cadres whose

bribery and embezzlement is worth more than 100 million RMB, 2 cadres more than 200 million,

and 1 cadre more than 500 million. This “champion of graft” is Wu Changshun, a

Vice-Chairman of Tianjin Municipal CPPCC and the Director of Municipal Department of

Public Security. Wu has once worked under Zhou Yongkang.

The mean ratio of intraparty duration to procuratorial duration is 0.55, which suggests that

the time that CCDI spends on disciplinary inspection of a case is on average about a half of what

the procuratorate spends on legal investigation. The least ratio is 0.14 recorded in the case of

Liang Bin, the Director of Hebei Provincial Organization Department. CCDI announces Liang’s

party sanction 67 days after putting him under inspection, and then it takes the procuratorate 465


25

days to file his prosecution. Li Chuncheng sets the largest ratio at 1.58. As a Deputy Party Chief

of Sichuan Province and an alternative member of CCP Central Committee, Li is the very first

“tiger” hunted down after Xi took power in November 2012. He waits as long as 509 days for his

disciplinary sanction from CCDI and another 323 days for his case to be prosecuted.

Figure 7: Centrality vs. Career Length, Mobility, Political Seniority, Graft and Political

Prosecution Note: Pearson’s r with centrality: career length=0.077; mobility=0.332; political seniority=0.739; log(graft)=0.352;

political prosecution=0.236. Political seniority is recoded into 6 values in Figure 7: 1=vice-provincial level;

2=vice-provincial level with alternative membership in the Central Committee; 3=full-provincial level;

4=full-provincial level with membership in the Central Committee or CCDI; 5=vice-state level; 6=full-state level.

Figure 7 presents the correlation between centrality and other variables. Most independent

and control variables are not highly correlated with centrality. The number of years of a cadre’s

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

(0.50) 0.50 1.50 2.50 3.50 4.50 5.50 6.50

Cen

tral

ity (P

age

Ran

k)

Graft: Log(Million RMB)�

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0.00 0.50 1.00 1.50 2.00

Political Prosecution (Relative Duration)�

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

20 25 30 35 40 45 50

Cen

tral

ity (P

age

Ran

k)

Career Length

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0 2 4 6 8 10

Mobility

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0 1 2 3 4 5 6

Political Seniority


26

public service is the least correlated with his PageRank score in the purged network, with the

Pearson’s r less than 0.1. None of political mobility, logged value of graft and relative duration

of political prosecution is a good predictor of PageRank either.

Political seniority appears to be the sole exception. In the correlation analysis, rank level is

recoded into 6 values. Some vice-provincial-level cadres are more powerful than others because

they sit in the Central Committee as alternative members; they are coded with a separate rank

level. Similarly, those full-provincial-level cadres with any membership in either the Central

Committee or CCDI are distinguished from others without. The three national leaders are

recoded into two groups: full-state level and vice-state level. Zhou Yongkang is the only

observation in the former, whereas Su Rong and Ling Jihua are the two in the latter category.

As Figure 7 shows, there is a clear positive correlation of seniority and centrality. The

Pearson’s r between the rank level of a prosecuted cadre and his PageRank is 0.739, indicating a

high correlation. Zhou Yongkang, the most senior tiger caught in Xi’s anticorruption campaign,

is the most central cadre in the purged network. The two vice-state-level leaders, Ling Jihua and

Su Rong, score the second and third highest PageRank. Vice-provincial-level cadres without

Central Committee membership, in contrast, are clustered in the bottom of centrality ranking.

We put the variables into four linear models. The dependent variable is an elite’s centrality

in the purged network. The independent variable of interest is political prosecution. It measures

the emphasis on political prosecution against an elite. We use the variable of graft to control the


27

monetary value of bribe and embezzlement. This variable provides the main competing

explanation that we consider in this paper. Other control variables include career length, political

mobility and political seniority. The length of an elite’s public service tells us how many years

an elite has worked. Mobility is the number of party or state institutions where an elite has served.

Lastly, we use political seniority to indicate the peak of an elite’s administrative rank level. Base

Model only includes control variables of career length, mobility and political seniority. The other

three are prosecution models. Graft Model and Political Model take in graft and political

prosecution, respectively, in addition to the three control variables. Full Model is the full model

that has all the five independent and control variables.

Table 4: Graft and Political Prosecution Upon Centrality

Dependent Variable: Log(Centrality) Civilian Cadres

Base Model Graft Model Political Model Full Model

Career Length: years of service

−0.005 (0.013)

−0.004 (0.013)

−0.005 (0.013)

−0.004 (0.013)

Mobility: number of institutions

−0.014 (0.041)

−0.012 (0.041)

−0.014 (0.041)

−0.013 (0.042)

Political Seniority Full-Provincial Level 0.469**

(0.219) 0.444* (0.226)

0.457** (0.225)

0.429* (0.233)

State Level 1.318*** (0.321)

1.258*** (0.345)

1.307*** (0.327)

1.242*** (0.352)

Log(Graft): million RMB

0.030 (0.059)

0.032 (0.060)

Political Prosecution relative duration

0.054 (0.191)

0.063 (0.194)

Observations 50 50 50 50 R-squared 0.330 0.334 0.331 0.335 *significant at 10%; **significant at 5%; ***significant at 1%


28

It is to be noted that testing statistical significance does not provide much analytical

leverage in this research. The dependent variable, centrality, is a network attribute derived from

the interrelations of nodes, and so its value is not independent and identically distributed.

Therefore, the test for statistical significance, which is based on the assumption that the random

variables are independent and identically distributed, cannot be used in this research. What we

are interested in, instead, is the direction of coefficients of graft and political prosecution in Graft

Model and Political Model, and the comparison of their effects on centrality in Full Model. In all

the four models, the values of centrality and graft are logged in order to normalize their

right-skewed distributions.

Table 4 presents the results. In the Base Model, we only use career length, mobility and

political seniority to predict centrality. As discussed previously, the longer an elite has worked,

the more institutions he has worked in, and the higher-ranking he is, the more central he is

expected to be in network. These variables should have positive effects on centrality. However,

neither career length nor mobility positively affects centrality. The only variable that falls in line

with our expectation is political seniority. It is also the only variable with statistically significant

effects. In all the four models, both dummies of full-provincial level and state level are positively

correlated with PageRank. For example, in Full Model, a state-level leader and a

full-provincial-level cadre, ceteris paribus, respectively scores 246.3% and 53.6% more in

PageRank than a cadre at vice-provincial level. The incremental advancement from provincial


29

level to state level has an even larger effect on centrality than the advancement from

vice-provincial level to full-provincial level.

We have three prosecution models to examine the effects of different investigation

emphasis. Graft Model includes graft, Political Model includes political prosecution, and Full

Model includes both. Full Model allows us to compare the effects of graft and political

prosecution on centrality. If investigation focuses on economic graft, it will trace from an elite to

his colleagues by the collusion of economic graft, and thus the variable of graft should have a

larger effect than political prosecution. If the anticorruption agencies emphasize on political

threat of an elite to the autocrat, the network should grow from this elite to his colleagues

following relations of political alliance. Therefore, the variable of political prosecution will have

a larger effect on centrality than graft does.

As Table 4 shows, the effects on centrality of the two variables of interest, graft and

political prosecution, are both positive as expected. In Graft Model, every 10% increase of graft

leads to a 0.29% increase of centrality. In Political Model, every one-tenth-unit increase of

political prosecution results in 0.54% increase of centrality. At the mean value of political

prosecution, a 10% increase makes centrality increase by 0.30%. In Full Model, both variables

are positively correlated with centrality too. An increase of graft by 10% is expected to bring

0.31% increase of PageRank. A one-tenth-unit increase of political prosecution expectedly leads

to a 0.63% increase of PageRank. When political prosecution is at its mean value at 0.55, a 10%


30

increase of relative duration makes centrality increase by 0.35%. In Full Model, therefore, we

can conclude that the effect of political prosecution on centrality is no less, if not larger, than that

of economic graft.

To sum up the empirical results, political seniority is the only variable with a statistically

significant positive effect on centrality. The state-level leaders and full-provincial-level cadres

are more central in the purged network than vice-provincial-level cadres in all models. As for the

variables of interest, both graft and political prosecution are positively correlated with centrality

in prosecution models. In Full Model that includes all independent and control variables, the

positive effect of political prosecution on centrality is as much as that of the monetary value of

bribe and embezzlement.

Conclusion and limitations

This paper finds that political prosecution drives Xi Jinping’s anticorruption campaign as

much as cleansing corruption does. The two-stage prosecution procedure in China provides us

with the analytical leverage to measure the varying emphasis on political prosecution across

corruption cases. We measure political prosecution by relative duration, i.e. the duration ratio of

intraparty inspection to procuratorial investigation. The “tigers” hunted down in Xi’s early reign

are analyzed in the network of purged elites, where colleague relations are ties that connect

prosecuted cadres as nodes. We use the network attribute of centrality to observe the general


31

structure of Xi’s campaign. Empirical results show that political prosecution explains network

positions of purged elites as much as the magnitude of their economic graft does.

These findings suggest that the Chinese autocrat is indeed breaking down the institutional

constraints on his power and taking advantage of anticorruption to unseat his rivals. Contrary to

the prediction of some literature on limited autocracy, even in a highly institutionalized

authoritarian regime like CCP, an autocrat can still prioritize his personal agenda when he wields

the power of the party-state. Committed power-sharing arrangements, the alleged key to political

survival of autocrats and autocracies, are in fact fragile.

This study has two notable limitations. First, it only reveals the positioning mechanisms that

determine the network positions of elites in the purged network. It does not discuss why these

elites are purged in the first place, which may bear equal theoretical and empirical importance for

our understanding of anticorruption in autocracies. Future studies can construct a network of all

relevant elites and explain the purging mechanisms that decide which elites are picked by the

autocrat to prosecute.

Second, this study uses cross-section data that cut in March 2015. This choice of empirical

strategy is based on the assumption that March 2015, the end time of Xi’s early reign, concludes

a distinct stage of his anticorruption campaign. Much as this assumption makes good political

sense, it may be relaxed in future research to extend the time scope. Moreover, time-series data

can be used in order to capture the temporal dynamics of Xi’s anticorruption campaign.


32

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Appendix: Cadres Prosecuted for Corruption in Xi Jinping’s Early Reign

Pinyin Name Last Institution of Service Rank Date 1 Li Chuncheng 李春城 Sichuan Province VP (AM) 2012/12/5 2 Wu Yongwen 吳永文 Hubei Province VP 2013/1/5 3 Yi Junqing 衣俊卿 Central Compilation and

Translation Bureau VP 2013/1/17

4 Liu Tienan 劉鐵男 National Development and Reform Commission

VP 2013/5/12

5 Ni Fake 倪發科 Anhui Province VP 2013/6/4 6 Guo Yongxiang 郭永祥 Sichuan Province VP 2013/6/23 7 Wang Suyi 王素毅 Inner Mongolia Autonomous

Region VP 2013/6/30

8 Li Daqiu 李達球 Guangxi Zhuang Autonomous Region

VP 2013/7/6

9 Wang Yongchun

王永春 China National Petroleum Corporation

VP (AM) 2013/8/26

10 Jiang Jiemin 蔣潔敏 State-owned Assets Supervision and Administration Commission

FP (FM) 2013/9/1

11 Ji Jianye 季建業 Jiangsu Province VP 2013/10/17 12 Liao Shaohua 廖少華 Guizhou Province VP 2013/10/28 13 Wang Minggui 王明貴 PLA General Staff Department VA 2013/11 14 Chen Baihuai 陳柏槐 Hubei Province VP 2013/11/19 15 Guo Youming 郭有明 Hubei Province VP 2013/11/27 16 Chen Anzhong 陳安眾 Jiangxi Province VP 2013/12/6 17 Fu Xiaoguang 付曉光 Heilongjiang Province VP 2013/12/17 18 Tong Mingqian 童名謙 Hunan Province VP 2013/12/18 19 Li Dongsheng 李東生 Ministry of Public Security FP (FM) 2013/12/20 20 Yang Gang 楊剛 General Administration of

Quality Supervision, Inspection and Quarantine

VP 2013/12/27

21 Li Chongxi 李崇禧 Sichuan Province FP 2013/12/29 22 Ji Wenlin 冀文林 Hainan Province VP 2014/2/18 23 Zhu Zuoli 祝作利 Shaanxi Province VP 2014/2/19 24 Jin Daoming 金道銘 Shanxi Province VP 2014/2/27 25 Fang Wenping 方文平 PLA Shaanxi Provincial Military

District FA 2014/3


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Pinyin Name Last Institution of Service Rank Date 26 Shen Peiping 沈培平 Yunnan Province VP 2014/3/9 27 Xu Caihou 徐才厚 Central Military Commission VS 2014/3/15 28 Yao Mugen 姚木根 Jiangxi Province VP 2014/3/22 29 Wei Jin 衛晉 PLA Tibet Military District FA 2014/4 30 Shen Weichen 申維辰 Chinese Associations for

Science and Technology FP (DM) 2014/4/12

31 Song Lin 宋林 China Resources (Holdings) Company Limited

VP 2014/4/17

32 Mao Xiaobing 毛小兵 Qinghai Province VP 2014/4/25 33 Chen Qiang 陳強 PLA Second Artillery Force VA 2014/5 34 Ye Wanyong 葉萬勇 PLA Sichuan Provincial Military

District FA 2014/5

35 Fu Linguo 符林國 PLA General Logistics Department

VA 2014/5

36 Tan Qiwei 譚棲偉 Chongqing Municipality VP 2014/5/3 37 Wang Shuaiting 王帥廷 China National Travel Service

(HK) Group Corporation VP 2014/5/16

38 Yang Baohua 陽寶華 Hunan Province VP 2014/5/26 39 Zhao Zhiyong 趙智勇 Jiangxi Province VP 2014/6/3 40 Su Rong 蘇榮 National Committee of the

Chinese People’s Political Consultative Conference

VS 2014/6/14

41 Du Shanxue 杜善學 Shanxi Province VP 2014/6/19 42 Ling Zhengce 令政策 Shanxi Province VP 2014/6/19 43 Wan Qingliang 萬慶良 Guangdong Province VP (AM) 2014/6/27 44 Yang Jinshan 楊金山 PLA Chengdu Military Region VMR

(FM) 2014/7

45 Zhang Gongxian 張貢獻 PLA Jinan Military Region VMR 2014/7 46 Tan Li 譚力 Hainan Province VP 2014/7/8 47 Zhang Tianxin 張田欣 Yunnan Province VP 2014/7/12 48 Han Xiancong 韓先聰 Anhui Province VP 2014/7/12 49 Wu Changshun 武長順 Tianjin Municipality VP 2014/7/20 50 Chen Tiexin 陳鐵新 Liaoning Province VP 2014/7/24 51 Zhou Yongkang 周永康 Standing Committee of

Politburo; Central Politics and Law Commission

FS 2014/7/29

52 Zhang Qibin 張祁斌 PLA Jinan Military Region FA 2014/8 53 Zhu Heping 朱和平 PLA Chengdu Military Region FA 2014/8


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Pinyin Name Last Institution of Service Rank Date 54 Chen Chuanping 陳川平 Shanxi Province VP (AM) 2014/8/23 55 Nie Chunyu 聶春玉 Shanxi Province VP 2014/8/23 56 Bai Yun 白雲 Shanxi Province VP 2014/8/29 57 Bai Enpei 白恩培 Yunnan Province FP 2014/8/29 58 Ren Runhou 任潤厚 Shanxi Province VP 2014/8/29 59 Sun Zhaoxue 孫兆學 Aluminum Corporation of China VP 2014/9/15 60 Pan Yiyang 潘逸陽 Inner Mongolia Autonomous

Region VP (AM) 2014/9/17

61 Qin Yuhai 秦玉海 Henan Province VP 2014/9/22 62 Cai Guangliao 蔡廣遼 Guangdong Province VP 2014/10 63 Yuan Shijun 苑世軍 PLA Hubei Provincial Military

District FA 2014/10

64 He Jiacheng 何家成 Chinese Academy of Governance

FP 2014/10/11

65 Zhao Shaolin 趙少麟 Jiangsu Province VP 2014/10/11 66 Liu Zheng 劉錚 PLA General Logistics

Department VMR 2014/11

67 Dai Weimin 戴維民 PLA General Political Department

VA 2014/11

68 Gao Xiaoyan 高小燕 PLA General Staff Department VA 2014/11 69 Wang Aiguo 王愛國 PLA Shenyang Military Region FA 2014/11 70 Huang Xianjun 黃獻軍 PLA Shanxi Provincial Military

District VA 2014/11

71 Duan Tianjie 段天杰 PLA National Defense University

FA 2014/11

72 Liang Bin 梁濱 Hebei Province VP (DM) 2014/11/20 73 Sui Fengfu 隋鳳富 Heilongjiang Province VP 2014/11/27 74 Zhu Mingguo 朱明國 Guangdong Province FP (AM) 2014/11/28 75 Ma Xiangdong 馬向東 PLA General Political

Department VA 2014/12

76 Zhang Daixin 張代新 PLA Heilongjiang Provincial Military District

VA 2014/12

77 Fang Changmi 范長秘 PLA Lanzhou Military Region VMR (AM)

2014/12

78 Yu Daqing 于大清 PLA Second Artillery Force VMR 2014/12 79 Wang Min 王敏 Shandong Province VP (AM) 2014/12/19 80 Han Xuejian 韓學鍵 Heilongjiang Province VP 2014/12/22 81 Ling Jihua 令計劃 National Committee of the VS (FM) 2014/12/22


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Pinyin Name Last Institution of Service Rank Date Chinese People’s Political Consultative Conference; United Front Department of the Central Committee

82 Sun Hongzhi 孫鴻志 State Administration for Industry and Commerce

VP 2014/12/26

83 Huang Xing 黃星 PLA Academy of Military Science

FA 2015/1

84 Zhang Dongshui 張東水 PLA Second Artillery Force VMR 2015/1 85 Cheng Jie 程杰 PLA Navy VA 2015/1 86 Chen Jianfeng 陳劍鋒 PLA Guangzhou Military

Region VA 2015/1

87 Lan Weijie 蘭偉杰 PLA Hubei Provincial Military District

VA 2015/1

88 Liu Hongjie 劉洪杰 PLA General Staff Department VA 2015/1 89 Fu Yi 傅怡 PLA Zhejiang Provincial

Military District FA 2015/1

90 Yang Weize 楊衛澤 Jiangsu Province VP (AM) 2015/1/4 91 Ma Jian 馬建 Ministry of State Security VP 2015/1/16 92 Lu Wucheng 陸武成 Gansu Province VP 2015/1/23 93 Chen Hongyan 陳紅岩 PLA Air Force VA 2015/2 94 Wang Sheng 王聲 PLA Air Force VA 2015/2 95 Guo Zhenggang 郭正鋼 PLA Zhejiang Provincial

Military District VA 2015/2

96 Si Xinliang 斯鑫良 Zhejiang Province VP 2015/2/16 97 Xu Aimin 許愛民 Jiangxi Province VP 2015/2/17 98 Jing Chunhua 景春華 Hebei Province VP 2015/3/3 99 Li Zhi 栗智 Xinjiang Uyghur Autonomous

Region VP 2015/3/11

100 Qiu He 仇和 Yunnan Province VP (AM) 2015/3/15 101 Xu Jianyi 徐建一 China FAW Group Corporation VP 2015/3/15 102 Liao Yongyuan 廖永遠 China National Petroleum

Corporation VP 2015/3/16

103 Xu Gang 徐剛 Fujian Province VP 2015/3/20 104 Zhao Liping 趙黎平 Inner Mongolia Autonomous

Region VP 2015/3/20

Note: Data for civilian cadres from CCDI website at http://www.ccdi.gov.cn/jlsc/, and for military generals from the

website of the People’s Liberation Army (PLA) at http://www.81.cn/. This list only includes those tigers that were


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publicly put under disciplinary inspection after the 18th Party Congress as of March 2015. Those who fell down in

Hu Jintao’s era and received trial under Xi Jinping’s reign are excluded.

Civilian rank levels: FS: full-state level; VS: vice-state level; FP: full-provincial level; VP: vice-provincial

level.

Military rank levels: VS: vice-state level; FMR: full-military-regional level; VMR: vice-military-regional level;

FA: full-army level; VA: vice-army level.

Auxiliary rank levels in parentheses: FM: full membership of the Central Committee; AM: alternative

membership of the Central Committee; DM: membership of the Central Commission for Discipline Inspection.

Date: the day when the cadre was publicly put under disciplinary inspection.

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