MERITOCRATIC BUREAUCRACY AND ECONOMIC OUTCOMES

Since Weber made the distinction between bureaucracy and patrimonialism, political scientists have argued that government bureaucracies fall into either the meritocratic, impersonal type or the corrupt, clientelist type (Evans Reference Evans1995; Frye and Shleifer Reference Frye and Shleifer1997; Schneider Reference Schneider1993; Weber [1921] Reference Weber, Gerth and Mills1958). Explanations for why bureaucracies develop in disparate ways range from social capital (Putnam, Leonardi, and Nanetti Reference Putnam, Leonardi and Nanetti1993), to the level of external threat (Kang Reference Kang2002), to colonial legacies (Acemoglu, Johnson, and Robinson Reference Acemoglu, Johnson and Robinson2000). In turn, bureaucratic types are thought to explain complex economic outcomes. Thus, when market enhancing policies are implemented or when growth is high, some scholars attribute this to a meritocratic bureaucracy (Evans Reference Evans1995; Schneider and Maxfield Reference Schneider, Maxfield, Schneider and Maxfield1997).

In contemporary social science, the tendency to infer bureaucratic meritocracy from high growth is perhaps strongest in the study of China. Spectacular growth in the past three decades has motivated scholars to develop a variety of explanations of China's success, ranging from a proreform leadership (Fewsmith Reference Fewsmith1994; Shirk Reference Shirk1993), to de facto federalism (Qian, Weingast, and Montinola Reference Qian, Weingast and Montinola1995), to labor market mobility (Lin Reference Lin1992; Sachs et al. Reference Sachs, Woo, Fischer and Hughes1994).

Scholars have also looked to the efficiency or the institutional configuration of the Chinese bureaucracy as explanations of China's rapid growth. Unlike the Soviet Union, which had a unitary system of governance, the primary organizational principle in China was geography-based, thus giving rise to a multidivisional form (M-form) bureaucracy. Some claim the M-form bureaucracy, coupled with an extensive cadre evaluation system, provided strong incentives for regional administrators to compete with each other to generate high economic growth, in order to win promotion in the ruling CCP (Chen, Li, and Zhou Reference Chen, Li and Zhou2005; Li and Zhou Reference Li and Zhou2005; Maskin, Qian, and Xu Reference Maskin, Qian and Xu2000). This body of literature presents mixed evidence that the top two provincial officials (governors and party secretaries) in the reform period were typically rewarded with promotions for realizing better economic performance than their predecessors or their peers (Chen, Li, and Zhou Reference Chen, Li and Zhou2005; Li and Zhou Reference Li and Zhou2005; Tao et al. Reference Tao, Fubing, Lu and Zhu2010).

In addition to the quantitative findings, a larger qualitative literature on the evolution of the cadre evaluation system also seems to support the view of a performance-based elite promotion system in China. After the founding of the People's Republic of China, the CCP introduced formal methods of evaluating cadres, which were formally linked to their promotion. As Burns (Reference Burns1989) puts it, the cadre management system centered on “lists of leading positions, over which party units exercise the power to make appointments and dismissals; lists of reserves or candidates for these positions; and institutions and processes for making the appropriate personnel changes.” The Central Organization Department emerged as the key human resource manager of the CCP, although senior-level promotions were ultimately decided by members of the Politburo (Nathan and Gilley Reference Nathan and Gilley2002).

During his reign, Mao focused on ensuring the survival of the CCP regime according to his vision. Thus, he promoted cadres who shared or at least were willing to go along with his radical vision of society (Lee Reference Lee1991). After reform began in 1978, education credentials came to play a prominent role in the advancement of lower level cadres, and older cadres were strongly encouraged to retire (Cui Reference Cui2003; Landry Reference Landry2008; Manion Reference Manion1993; Walder, Li, and Treiman Reference Walder, Li and Treiman2000). Furthermore, the post-Mao leadership formalized a system of scoring junior and senior cadres, which served to keep track of their administrative performance on a series of “soft” and “hard” targets. Hard targets reflected core tasks crucial to the regime, including economic growth, fiscal collection, and maintaining stability, whereas soft targets included recruiting party members and propaganda work. Shortfalls on the soft targets could be outweighed by impressive performance in key areas. However, failing to fulfill hard targets led either to low overall scores or to mandatory administrative punishment (yipiao foujue), a powerful tool in the CCP's arsenal for political control (Edin Reference Edin2003). The existence of a comprehensive system for scoring officials on their policy performance seems to suggest that the Chinese elite was motivated by the scoring system to perform well (Edin Reference Edin2003; Landry Reference Landry2008; Whiting Reference Whiting, Yang and Naughton2004).

However, on both theoretical and empirical grounds, there are strong reasons to be skeptical of an easy linkage between a formal system of cadre evaluation and economic growth in China. Theoretically, linking a limited set of policy or economic outcomes with bureaucratic characteristics may result in a false causal inference. For one thing, bureaucratic characteristics tend to be time-invariant, whereas policy and growth outcomes change frequently over time. Moreover, seemingly reform policies can mask underlying corruption or inefficiencies. In Pinochet's Chile, for example, liberalization policies implemented by the “Chicago Boys” also allowed favored conglomerates to borrow heavily overseas to buy up prized financial assets, laying the groundwork for the financial crisis in the early 1980s (Haggard and Maxfield Reference Haggard, Maxfield, Keohane and Milner1996; Silva Reference Silva1996). The empirical findings on corruption also cast doubt on the linkage between bureaucratic characteristics and economic outcomes. Except in extreme cases, high growth generally is not harmed by a moderate degree of corruption (Svensson Reference Svensson2005).

Although meritocratic criteria may influence elite ranking in China, concluding that economic performance is the dominant criterion driving elite ranking goes too far. A merit or performance dominant bureaucracy assumes that the Chinese regime is unified and far-horizoned, and thus is motivated to maximize performance and long-term output (Olson and McGuire Reference Olson and McGuire1996). But leaders of nondemocratic regimes face constant threats of dethronement from mass uprisings or coups by regime insiders (Tullock Reference Tullock1987; Wintrobe Reference Wintrobe1998). Thus, autocratic rulers likely place a greater priority on maintaining short-term state capacity and buying the support of winning coalitions than on providing broadly encompassing goods such as economic growth (Bueno de Mesquita et al. Reference Bueno de Mesquita, Smith, Siverson and Morrow2003; Gandhi and Przeworski Reference Gandhi and Przeworski2006). China has witnessed its share of large-scale uprisings and intense political struggle at the top. Even after the chaotic Cultural Revolution, the top leader of the CCP was twice removed from power by irregular means.Footnote ¹ Besides the Tiananmen protests in 1989, China also dealt with a series of large-scale protests motivated by ethnic and economic grievances in recent years (Pei Reference Pei2006). Huang (Reference Huang1996) and Sheng (Reference Sheng2007) argue that the conflict of interest between central and local governments compels the center to use its appointment control to obtain preferred outcomes, thus implicitly forgoing the appointment of the most capable officials. Because top Chinese leaders must address urgent concerns of stability and retaining office on a daily basis, we expect that the CCP often uses the personnel management system to promote these immediate goals, while neglecting more encompassing objectives like growth or fairness.

If political survival is a main concern, the top leader of a regime may shape policies, including the appointment of subordinates, to serve that end. One elite faction may pursue policies purely to undermine a rival faction, thus risking overall regime stability (Ramseyer and Rosenbluth Reference Ramseyer and Rosenbluth1998). Instead of expending resources to prevent a general uprising, leaders seeking to thwart an elite challenger may devote those resources to monitoring or cultivating the loyalty of senior officials (Svolik Reference Svolik2005). And instead of promoting officials with the strongest performance record, rival leaders may promote untalented but loyal followers to prevent a coup or to raise their relative standing (Easter Reference Easter1996; Egorov and Sonin Reference Egorov and Sonin2011; Nathan Reference Nathan1973). In other cases, an insecure leader may shuffle or promote officials simply to prevent an alliance between ambitious local officials and the populace (Debs Reference Debs2007).

Empirically, the literature linking China's cadre evaluation system and growth produces highly ambiguous and problematic results. First, the qualitative literature provides an in-depth description of the cadre evaluation system, which suggests a causal link between cadre evaluation and growth. However, the existence of an evaluation system as such does not prove a causal link. Furthermore, quantitative studies of city and county officials do not find much evidence for growth-based promotions (Guo Reference Guo2007; Landry Reference Landry2008). At the city level, for example, Landry (Reference Landry2008) finds that exceptional economic performance has almost no effect on the most likely internal promotion of mayors, to the position of party secretary.

Quantitative studies on provincial officials provide some evidence that exceptional economic growth in a province is correlated with the promotion of the top two officials in a province (Chen, Li, and Zhou Reference Chen, Li and Zhou2005; Li and Zhou Reference Li and Zhou2005; Maskin, Qian, and Xu Reference Maskin, Qian and Xu2000). These studies present a number of empirical shortcomings, however. First, they focus only on provincial officials, leaving out the majority of the party elite, who served in the central party apparatus, the army, and the central economic bureaucracy. A comprehensive analysis of elite incentive should include all full and alternate members of the CC, who make up the bulk of the power elite in the CCP (Kung and Chen Reference Kung and Chen2011; Shirk Reference Shirk1993). Measures of promotion are often poor: Li and Zhou (Reference Li and Zhou2005) define promotion as movement to a ministerial position or higher, but in the state bureaucracy, movement from provincial governorship to a ministerial position is horizontal, as provinces and ministries have the same bureaucratic rank. To measure whether such a rotation constituted a promotion, it is more useful to see whether a person's party rank improved, a clearer sign of advancement.

Methodologically, no previous study of elite promotion has taken into account the potential for selection bias (Chen, Li, and Zhou Reference Chen, Li and Zhou2005; Guo Reference Guo2007; Landry Reference Landry2008; Li and Zhou Reference Li and Zhou2005; Maskin, Qian, and Xu Reference Maskin, Qian and Xu2000). Aspiring provincial governors and party secretaries may perceive certain provinces as strong economic performers prior to a rotation, and may use political connections to engineer their appointments to claim credit. Under strategic appointment, observed correlation between exceptional growth and advancement might have been caused by strong political connections, rather than by economic performance per se.

HYPOTHESES

There are good theoretical and empirical reasons to doubt whether economic performance was the dominant factor driving elite advancement, despite China's geography-based administrative system and elaborate cadre evaluation system. Instead of only testing the impact of economic performance on elite ranking, we draw on the political economy literature on authoritarianism to derive two different sets of hypotheses. If we assumed that China was a unified regime with a long time horizon, we would expect performance, merit, and representation to play the dominant role in elite ranking. However, theories of elite power struggle in authoritarian regimes suggest that factional affiliation and princeling ties may play an important role in CCP elite ranking.

If the top leadership in China were unified and had a long time-horizon, it would have had a “sufficiently encompassing interest” in generating long-term growth and in developing tax collection capacity in an optimal way (Olson and McGuire Reference Olson and McGuire1996). Furthermore, to prevent large-scale collective action threatening the regime, a unified Chinese leadership would have combined repression with limited redistribution of its resources or greater representation for certain groups (Acemoglu and Robinson Reference Acemoglu and Robinson2006; Desai, Olofsgard, and Yousef Reference Desai, Olofsgard and Yousef2009; Gandhi and Przeworski Reference Gandhi and Przeworski2006; Olson and McGuire Reference Olson and McGuire1996; Wintrobe Reference Wintrobe1998). To accomplish these ends, a unified CCP regime would have promoted officials with a talent for generating growth, collecting taxes, and repressing dissent so that “no matter how strong a candidate's factional backing, he cannot be promoted without a record of administrative achievement” (Nathan and Gilley Reference Nathan and Gilley2002). From this understanding of elite ranking in China, we derive the following hypotheses:

Finally, ensuring female and minority representation in the higher reaches of the party may enhance the regime's legitimacy. Furthermore, minority representation may enhance stability by coopting potentially restive minority groups into the system (Dreyer Reference Dreyer1976, 113). Thus a unified authoritarian regime might systematically promote women and minorities.

If a regime experiences concealed or overt power struggles at the top, faction-based promotion predominates. In factional politics, loyalty counts more than skills or performance on core tasks such as growth, revenue collection, and stability. Skills may even be a liability. Egorov and Sonin (Reference Egorov and Sonin2005) provide a convincing theoretical argument that dictators facing the threat of a coup will not always choose the most competent advisors: Clever subordinates may be too good at figuring out the expected payoffs of betraying the dictator; less capable officials are more loyal. Bueno de Mesquita et al. (Reference Bueno de Mesquita, Smith, Siverson and Morrow2003) also argue that autocrats find ways to channel resources to their supporters, including promoting them to senior regime positions. In a similar vein, China scholars long have postulated that Chinese leaders built networks of loyal followers to mitigate the fundamental uncertainty in elite politics (Dittmer Reference Dittmer1995; Nathan Reference Nathan1973; Pye Reference Pye1980, Reference Pye1992). These factional networks bound the interests of followers to their patrons through the distribution of economic resources and offices (Nathan Reference Nathan1973; Nathan and Tsai Reference Nathan and Tsai1995; Shih Reference Shih2008a).

When a factional patron comes under attack, followers remain loyal because they expect large payoffs for protecting the patron, who in turn promotes followers to the upper echelons of the regime. If elite political struggles loomed large in the minds of top CCP leaders, then followers’ records of loyalty would have been more important criteria for promotion than economic performance. When the factional logic dominates, individual leaders promote close allies rather than the most capable individuals, even if these appointments lead to the underprovision of regime-wide public goods such as economic growth. In this case, ambitious officials face incentives to signal their loyalty to factional patrons, instead of performing tasks for the regime (Shih Reference Shih2008b). However, even when confronted with intense elite struggle, authoritarian leaders may still prioritize tax collection capacity, to finance both private goods for regime supporters and the regime's repressive capacity (Acemoglu and Robinson Reference Acemoglu and Robinson2006; Bueno de Mesquita et al. Reference Bueno de Mesquita, Smith, Siverson and Morrow2003).

The main implication of the factional view of Chinese politics is the following factional hypothesis:

In testing this hypothesis, we consider only the followers of the de facto or de jure leaders of the party because as the most powerful leaders, they had the strongest incentive to avoid factional politics and to ensure high regime performance. Thus, if factional politics was not pervasive, we would not expect the highest officials in the regime to rank CC members according to factional considerations.

A related hypothesis concerns the children of senior officials, or “princelings,” who entered the CCP elite. Although their parents were never their direct superiors, other senior officials might expect to win some advantage from the families of princelings by promoting them. But helping princelings does not make sense in the context of a unified leadership, because princeling status per se does not help further regime goals. To the extent that CCP elites were divided and were tempted to draw on princeling resources, we expect the following.

DATA

We test our hypotheses on data measuring elite ranks within the CCP. Our dependent variable is the rank ordering of officials in the upper echelon of the Chinese Communist Party, for the 12th through 16th Party Congresses (1982–2007), a difficult quantity to measure. This (still imperfect) metric of pecking order improves on existing measures, which limit analysis to provincial officials. In this section we outline what we do know about these ranks; in the next, we explain how to use ranks we know well to infer ranks we observe imprecisely, a useful strategy for exploring the distribution of political power in authoritarian regimes.

The ranking of CCP elites in the CC took place roughly once every five years at the National Party Congress. Formally, this ranking comprised three different processes, but fundamentally, all three steps reflect a single ranking highly coordinated by the PSC. Starting at the 12th Party Congress in 1982, delegates received ballots with more names than there were seats in the Central Committee. Delegates then voted for the candidates by placing checks next to their names, and delegates could check as many names as there were seats in the Central Committee. Candidates were accepted into the CC in the order of their vote totals, with the lowest-vote receipients eliminated (Organizational Division of the Central Organization Department 2001). Alternate members of the CC were also elected in this way. The elected CC then voted the Politburo, the PSC, and the party secretary general into office. In this final round of voting, there were as many candidates as there were seats, and CC members without exception voted everyone on the ballot into offce.

Although congressional delegates ostensibly voted freely, all the party congresses were tightly monitored and controlled by the party secretary general and members of the Politburo. To begin, the chairman or the party secretary general sent early signals to the rest of the political elite on who should or should not be on the list of CC candidates (Li Reference Li2007). As the congresses approached, candidates for the CC, the ACC, and the Politburo were chosen by leadership groups, which included the serving PSC and a few powerful retired cadres handpicked by the party secretary general (Organizational Division of the Central Organization Department 2001).

The selected candidates then underwent a vetting procedure carried out by the Central Organization Department, which also took instructions from the party secretary general and other members of the Politburo (Cui Reference Cui2003; Nathan and Gilley Reference Nathan and Gilley2002). When the delegates finally arrived in Beijing to vote, they were isolated from each other and received strict voting instructions from the party secretary general and other members of the Politburo on how to vote (Deng Reference Deng2005; Li Reference Li2007). In the famous case of Deng Liqun's surprising elimination from the 13th CC, it turns out that the party secretary general at the time, Zhao Ziyang, sent cadres to the provinces prior to the congress to instruct delegates not to vote for him (Deng Reference Deng2005).

Because of extensive intervention from PSC members, where one landed on the party pecking order largely reflected the priorities of the top leadership, which could change dramatically over time. Periodic appearance of “helicopters,” or officials who obtained rapid promotion from the ACC to the Politburo, further suggests that elite ranking at the Party Congress was a single exercise of elite reshuffling closely guided by the party secretary general and the Politburo, rather than three autonomous processes. At the end of a congress, highly ranked officials typically enjoyed much more formal and informal power for the subsequent five years, whereas those who were not selected even as ACC members missed being in the power center of the CCP (Kung and Chen Reference Kung and Chen2011).

We note that there is broad agreement on a set of tiers, with the PSC and the Politburo at the top, followed by the full members of the CC, and then the alternate members of the CC (Kung and Chen Reference Kung and Chen2011; Lieberthal Reference Lieberthal2004). In particular, we treat as top-ranked the party secretary general (who sets the agenda in the PSC) and the chairman of the Central Military Commission (CMC), who were usually the same person. Next came the members of the PSC, who voted on every major issue confronting the regime—and whose relative political status was implied by the order of their names in public announcements.Footnote ² Following in descending order of political power are the vice chairmen and members of the CMC (who controlled large segments of the armed forces), the Politburo (composed of regional party secretaries of major provinces, several vice premiers of the State Council, and senior military leaders), and a handful of alternate members of the Politburo. Next come the vast majority of the Central Committee who were not members of the higher party organs, whose members’ individual ranks were not precisely known, beyond the general importance of these tiers.

Finally, a key to our ranking strategy lies at the bottom of this hierarchy. Beneath full members of the CC lie the ACC members, who failed to win election to higher tiers at the party congress; for example, ACC members tended to be provincial governors rather than the more powerful regional party secretaries. Starting with the Eighth Party Congress, the official press announced ACC members in the order of votes received from delegates (the vote totals themselves remained secret). Because detailed instructions were given to delegates when they voted on the ACC slate, the votes received by ACC members should reflect the priorities of the top leadership in ranking cadres. This underexploited data on a large body of individuals contains a wealth of information about the factors influencing the ranking of all top officials. We will show in the next section how these data help us impute ranks for the entire hierarchy.

We combine our rank data with covariates measuring the characteristics of the members of the ACC, the CC, the Politburo, and the PSC. Most of these variables are drawn from a new biographical data set of Central Committee members developed by Shih, Shan, and Liu (Reference Shih, Shan and Liu2008). This database contains all CC and ACC members from the first party congress in 1921 to the sixteenth party congress in 2002, and follows the structure for political biographical data developed by Adolph (n.d.) in his work on the career trajectories of central bankers. Shih, Shan, and Liu collect and record nearly every state, party, and military position held by CC members throughout their careers, rather than just positions held by CC members at the time they served in the CC. Using start and end years for each position held, they reconstruct complete career histories for each member of the ACC, the CC, the Politburo, and the PSC as they stood at the start of each party congress.Footnote ³ They also collect demographic variables including birth year, gender, year of induction into the party, education, ethnicity, and princeling status.

These biographical data allow us to test whether education, performance, or factional affiliations are responsible for party rank. Basic demographic information captures merit criteria such as level of education, as well as representation criteria such as gender and minority status. We assume that factional ties occur between officials and leaders with shared birthplaces, as well as officials and leaders who overlapped in educational institutions or work units (Lieberthal and Oksenberg Reference Lieberthal and Oksenberg1988, 156).Footnote ⁴ If any such coincidence occur between a CC or ACC member and a top leader, we code that member as having a factional tie to that leader.

We also combine the CC database with provincial economic data to calculate the relative economic performance of provincial administrators (governors and party secretaries) who were also CC or ACC members (China Data Online 2005). In the five party congresses under consideration, provincial administrators made up between 14 and 20% of all CC members. We consider the fraction of provincial CC members to be both large from a substantive point of view, and sufficient to estimate whether provincial economic performance was rewarded with party advancement. Although we are only able to test the economic performance hypothesis on the provincial administrators in the pool, Maskin, Qian, and Xu (Reference Maskin, Qian and Xu2000) argue that China's success hinged on competition among provincial administrators, whose economic performance could be more readily observed than that of cadres in the central bureaucracy. If superior performance by provincial administrators did not lead to political rewards in the party, we doubt that nonprovincial officials received such rewards either.

We focus mainly on growth in GDP and fiscal revenue, but collect 22 other measures of performance for use in robustness analyses. We assume that each member of the CC hierarchy who was also a provincial party secretary or governor is judged based on the performance of his province in the five years between party congresses. In constructing our performance measures, we must solve two further problems. First, because competition for party rank is zero-sum, only officials who outperform their peers should advance. Thus we create relative performance scores that subtract rest-of-China performance from each province's growth rate. Second, provincial officials should not receive credit for growth trends determined before they took office. Thus, we subtract preappointment expected performance from each province's growth rate. The resulting variable measures the performance improvement in each province under its current leadership, relative to other provincial leaders. We create performance scores of this type for GDP growth, fiscal revenue growth, and other indicators of provincial performance. For example, the province of an official with a GDP growth score of +2 beat preappointment growth expectations by two percent more than the average province in China. Members of the ACC or CC who were not regional administrators in the five years prior to a party congress receive neutral performance scores of zero.Footnote ⁵

Estimating expected provincial performance is also the key to dealing with selection bias. Although high-flying officials might manuever themselves into provinces with strong growth prospects, or be sent to turn problem provinces around, we can purge these and other selection effects from our performance measures if we accurately model expectations of provincial performance on the eve of appointment. Party leaders doling out performance rewards share our problem of isolating the innovations in growth due to provincial leaders, rather than provincial trends or China-wide shocks. Because we cannot be certain how historical leaders solved this problem, we propose three strategies, and check whether any of them provide evidence of yardstick competition. The first strategy is the simplest: We subtract the growth rate in the preappointment year from growth during an official's tenure, attributing the change to the official's efforts. We use this performance measure in our baseline models. As an alternative, we employ standard time series methods to forecast growth over officials’ tenures using only preappointment data. We create forecasts using both the workhorse AR(1) model and the AIC-minimizing ARMA(p, q) model. We use these sharper estimates of expected growth in robustness checks that allow both sophisticated judgment of performance by party leaders and complex patterns of strategic appointment of provincial officials.Footnote ⁶ See the supplemental Online Appendix (available at http://www.journals.cambridge.org/psr2012004) for further details.

FINDINGS

Overall, our findings do not suggest any linkage between growth performance of regional administrators who were also ACC, CC, or Politburo members and their party ranking in the CCP. However, some regime-strengthening factors, such as education and, to a lesser extent, fiscal performance and minority status, had positive impacts on ranking in the party elite. At the same time, there is considerable evidence that factional affiliation played a large role in political advancement.

Because the raw parameters estimated in our models are on a latent scale of no direct interest, and because we estimate five separate models, each with numerous covariates, it is easiest to explore our results through graphical summaries. These graphics show either the expected ranks of members with differing characteristics (for the 16th Party Congress see Figure 2; for other years, see the supplemental Online Appendix), or the expected change in rank associated with a change in one covariate, all else equal (Figures 3 and 4). To guide readers through our results, we first explore how different factors affected expected elite ranking at the most recent party congress for which we had data, the 16th Party Congress (2002). Then we take a broader view, and examine how the impact of these factors has waxed or waned between the 12th Party Congress and the 16th. Finally, we consider a broad range of alternative specifications to confirm the robustness of our findings.

FIGURE 2.

Formal Selection Criteria and Rank in the 16th Party Congress: Estimated Relationships

Note: For each row of the plot, we set the indicated covariate at one (for binary covariates) or the mean plus one standard deviation (for continuous covariates), and hold all other variables at their means. The black circles indicate expected rank for an individual with these observed covariates and an average random effect (or degree of unmeasured political ability). Gray diamonds show expected ranks for members with random effects one standard deviation above or below the mean. Thick horizontal lines mark 67% Bayesian confidence intervals and thin horizontal lines indicate 95% Bayesian confidence intervals. The dotted vertical line shows the expected rank of a member with the average covariates. The light gray region indicates the actual ranks of ACC members, the medium gray region shows the CC, and the dark gray region the ranks of the Standing Committee.

FIGURE 3.

The Effects of Factional Ties, Performance, Demography, and Education on Political Rank: Estimated First Differences over Time

Note: Each plot shows the estimated change in rank percentile for a member with otherwise average measured and unmeasured characteristics, but a higher value for the listed covariate. For performance measures, we estimate the impact on rank of performance 1 standard deviation above the mean. For education variables, we show the difference in rank associated with a switch from less than high school to the listed degree. All other covariates are binary, so we estimate the effect on rank of switching from a 0 to 1. Shaded regions show 67% Bayesian confidence intervals, and dashed lines mark 95% Bayesian confidence intervals.

FIGURE 4.

The Interactive Effect of Age and Party Tenure on Rank by Party Congress: Estimated First Differences

Note: Plots display the estimated change in rank percentile associated with switching from the average age to the age shown on the horizontal axis. A separate line traces out the effects of age for early, average, and late CCP joiners. All other covariates are held at their means. To avoid extrapolation, each line is limited to show only counterfactuals drawn from inside the convex hull (King and Zeng 2006).

Robustness of Results

We find no relationship between growth performance and party ranking, and a strong relationship between factional ties and rank. Because these findings are debated both for China and for the broader field of authoritarian politics, we conduct additional robustness tests to raise our confidence in the results. In particular, we drop the assumption that the order of votes received for the ACC measures political strength, consider more specific measures of factional affiliation to protect against measurement error, add controls for educational institutions and fields of study, add broader measures of economic performance in case political ranks are awarded holistically, and finally, exploit our provincial performance data to mitigate selection bias. Because the details of these tests could fill a second article, we relegate discussion of theory, measurement, design, and ancillary results to the supplemental Online Appendix. Here, we focus on the consistency of our estimated results for the impact of faction, performance, and education on expected party rank.

Figure 5 displays results for all robustness checks overlapped. The similarity of these results to each other and the baseline estimates is striking, and the few deviations worthy of note.

FIGURE 5.

The Effects of Factional Ties, Performance, Demography, and Education on Political Rank: Robustness Checks

Note: As in Figure 3, each plot shows the estimated change in rank percentile for a member with otherwise average measured and unmeasured characteristics, but a higher value for the listed covariate. Estimates from nine different specifications join the original model. Shaded regions show 67% Bayesian confidence intervals for the original models. See the supplemental Online Appendix (available at http://www.journals.cambridge.org/psr2012004) for confidence intervals for other models.

Our first robustness check is the toughest, because it discards much potentially useful information. We now treat the ranks of ACC members as missing, and allow the rank data model to impute ACC ranks along with CC ranks and other parameters. Remarkably, there is enough information in the tier bounds on the ACC and CC to estimate our models, and for every party congress, the new, more conservative results agree remarkably well with the baseline models on the effects of factions, performance, and education (see the dotted lines in Figure 5). Our main conclusions no longer depend on whether ACC votes are informative, as they do not enter the model. The principal change in the results is that minorities and women both fare poorly, which we take as evidence of a glass ceiling. It is apparently easier for women and minorities to rise in the ACC ranks than it is for them to leave the ACC for higher tiers.

Our factional tie measures are also vulnerable to measurement error. Designed to be sensitive to affiliations hinted at by shared birthplaces, school ties, and shared work environments, our baseline measures may include false positives because of coincidences of birth and school attendance. A more specific measure counts only cases where an official worked closely with the faction leader in one of China's hundreds of ministerial and vice-ministerial work units or state-owned enterprises. Substituting these measures leaves most estimates of faction unchanged, and strengthens results for Mao and Deng, perhaps by zeroing in on core faction members or by excluding marginal members (see the dashed–dotted lines in Figure 5). As a further check against spurious factional results, we confirm that our factional measures also explain considerably more variance in rank than randomly generated factional variables do (see the supplemental Online Appendix for details).

As our remaining robustness checks all agree so closely with each other and with the original model as to be mostly indistinguishable, Figure 5 plots them all as dashed lines. The first such test allows for the possibility that not all college and graduate degrees are equal, and adds to the model controls for the origin of each official's highest university degree (whether from the Central Party School or abroad) and for fields of study (either natural science or social science/administration/law). The average effect of education is unchanged, as is the impact of faction and performance covariates, whereas the effects of degree origins and fields of study vary over time (see the supplemental Online Appendix).

We perform two tests of our findings on performance. In the first, we consider the possibility that GDP growth is too narrow a yardstick, and substitute a set of five orthogonal factors of performance summarizing 24 provincial performance variables. For this model, the quantity plotted under “GDP Growth” in Figure 5 is the effect on rank of the largest factor from our factor analysis, which loads heavily on growth in industrial output, retail sales, gross capital investment, and, of course, GDP itself. Even with this broader measure, we still find no evidence of incentives for growth. Nor do we see any correlation between higher party rank and improvement in the other factors: urban and rural standards of living, social service provision, and employment (see the supplemental Online Appendix for factor analysis details and full results).

In our final test, we return to the problem of selection bias. Our baseline measures of GDP growth provide some protection against selection effects by subtracting preappointment growth rates in each province. Still, better preappointment forecasts—such as AR(1) or ARMA(p, q) forecasts from historical data—should offer more protection against selection bias, and more closely capture the kind of performance most relevant for political rewards. In our remaining robustness checks, also shown as dashed lines in Figure 5, we isolate the surprising performance of provincial officials left over after removing expected growth, as forecast from preappointment data by either an AR(1) model or by the best available ARMA(p, q) model. We use the same forecasting techniques to isolate surprising performance on the five latent performance factors. Across all four of these robustness checks, the rewards to unexpected economic growth hover near zero, whereas the rank effects of factional ties, education, and demographics remain unchanged.

We consider the breadth and consistency of these results to be a strong refutation of the widespread claim that Chinese leaders advance based on yardstick competition. There is no hint that higher provincial growth leads to political advancement: not for officials who perform well compared to the past performance of their own province, not for officials who beat their peers’ performance in other provinces, not for officials who perform well on a broad range of factors, and not even for officials who beat the specific expectations one could form of their likely performance on appointment. Factional ties, on the other hand, appear to be strong predictors of party rank no matter what the specification of the model.