The Longest March: Why China's Democratization Is Not Imminent

The Longest March: Why China’s Democratization Is Not Imminent

John J. Chin1

Post-Doctoral Fellow Institute for Politics and Strategy Carnegie Mellon University

Mailing Address: Porter Hall 208, 5000 Forbes Avenue, Pittsburgh, PA 15213 E-mail: [email protected] Tel: 412-268-3855

Abstract: Will China democratize? If so, how soon? Relying on classical modernization theory and observations of China’s extraordinary economic growth, many prominent scholars have recently predicted that China is destined for a “short march” to democracy over the next decade. This article problematizes such predictions. I replicate the prominent forecast model used by Henry Rowen and show that even such classical modernization models of democratic transitions actually do not predict democracy in China before 2030-35 at the earliest. I also survey major reasons to think that China’s march to democracy will be a very long march, not a short one.

Keywords: China; democratization; modernization theory; authoritarian resilience; forecasting

1 I first proposed the idea of replicating Henry Rowen’s “short march” forecasting model in a “methodology paper” for a comparative politics graduate seminar at Princeton University in the fall of 2010. I owe a debt to many people since then for helping transform that idea into reality. Earlier versions of this paper were presented at the 2014 Midwest Political Science Association annual conference, Princeton University’s Contemporary China Colloquium, the Pizza & Politics Seminar at Princeton University, Helen Milner’s summer 2013 graduate lunch seminar, and the University of Pennsylvania’s 2013 Symposium on Contemporary China. I thank Andreas Fuchs, Harry Harding, Michael Hoffman, Stephen Kotkin, Helen Milner, and Lynn White for encouragement and feedback on early drafts. I alone am responsible for the content of the paper. “When will China become a democracy? The answer is around the year 2015.” So began an influential article by Henry Rowen (1996) decades ago in which the well-respected Stanford economist and former president of Rand Corporation predicted that China’s road to democracy would entail a relatively “short march.” Professor Rowen himself passed away in late 2015, and though his earlier prediction was unfulfilled his hope for China’s “short march” was undimmed.

In his last years, Rowen doubled down on his prediction, arguing China would more likely than not transition to partial democracy by 2017 and full democracy by 2025 (Rowen 2007, 2011).

We would be remiss not to consider Rowen’s work seriously, for although events have not born out Rowen’s optimism thus far, his prediction framework—classical modernization theory— remains the cornerstone for many “short march” predictions by some prominent China watchers today, many of whom still predict democratic reform or revolution in China by 2030 or earlier.

In this article, I contribute to the lively debate on China’s democratic prospects by critically examining the logic and evidence of “short march” optimists. I proceed as follows.

First, I briefly survey the short march logic and predictions. Second, I replicate the widely-cited forecast model used by Henry Rowen and show that even his “short march” model now only predicts Chinese democracy by 2030-2035 at the earliest. Third, I present some stylized facts that further problematize the assumptions of short march forecasts of China’s democratic prospects. I argue that minor but sensible adjustments to the Rowen model drawing on insights from the literature on comparative democratization indicate China’s march to democracy may be much longer. I take an unabashedly comparative, quantitative, and “outside” approach to forecasting.

This complements the dominant self-contained, qualitative, and “inside” approach in the China field. A potential problem with such “inside” approaches is that analysts can get swept away by

“good stories” that may not be well-grounded in baseline “hazard rates” (Tetlock 2005, 194).

1 I. The Short March: Assumptions and Claims

At its core, short march optimism1 is rooted in five major assumptions or claims.

First, short march optimism is a manifestation of what Michael Mandelbaum (2002) called the liberal theory of history, particularly the claim from classical modernization theory that socio-economic modernization (entailing a wealthier, educated, urban middle class) strongly promotes democracy. From this perspective, the master narrative of China is that of a rapidly modernizing holdout that must reach the “end of history” sooner or later (and probably sooner).

Autocracies, defined as the least democratic regimes with polity scores less than -5 (on a scale from -10 to 10), have been in retreat over the last several decades. The number of autocracies in the world peaked at 89 in 1977, but by 2015 China was one of just 21 such regimes left in the world. The tides of historical progress, the assumption goes, will sink remaining autocratic boats.

For example, in his first New York Times foreign affairs column, Thomas Friedman (1995) argued that China was on the brink of a democratic revolution. “How long is China’s leadership…going to be able to keep the lid on a country that is economically becoming North

Carolina and politically still North Korea?”, he asked. His answer: “not much longer.” In their article “Why China Will Democratize”, Liu and Chen (2012, 41) argue that “China is moving closer to vindicating classical modernization theory” and will democratize around 2020 or so.

Second, short marchers assume or argue that classical modernization theory applies to

China and that China has already reached a level of development that makes the CCP vulnerable for a democratic transition. There are two assumptions behind this claim. The first is that China is no different than prior “third wave” cases of democratization (e.g. Rowen 1996, 67; Yang

2007, 60-61). As Bruce Gilley (2004, xiii) put it in China’s Democratic Future, “The laws of social science grind away in China as they do elsewhere.” The second assumption is about what

2 the “laws of social science” entail, namely the notion of a middle-income “transition zone” (e.g.

Huang 2013, 53). Minxin Pei (2012) summarized the short march logic this way:

“The political laws of modernization are also stacked against the party. It becomes almost impossible to maintain autocratic rule in non-oil based economies as per capita gross domestic product rises above a given level (about $4,000-$6,000 in purchasing power parity). With its per capita GDP close to $8,400 in PPP, China is already an outlier…The CCP may have defied the odds so far, but cannot do so indefinitely.”

Pei (2016a) similarly noted that 36 “third wave” countries that democratized since 1974 had a median GDP per capita (in constant PPP $2011) of $9,768. With a GDP per capita of over

$12,000 in 2014, Pei concludes “China has reached the upper region of the transition zone.”

Even the National Intelligence Council (NIC), in its Global Trends 2030 (2012), paid homage to this logic: “Under most scenarios, China is slated to pass the threshold of US$15,000 per capita

(PPP) in the next five years or so. This level is often a trigger for democratization, especially when coupled with high levels of education and a mature age structure,” wrote the NIC.

Third, short marchers argue that the Chinese Communist Party is in a state of decline and

“atrophy.” Cheng Li (2012), who has long-predicted the growth of “inner-party democracy”, says that the 2012 Bo Xilai scandal has discredited the CCP and unmasked serious rifts in the party. Even scholars such as Andrew Nathan and David Shambaugh, pioneers of the study of the

CCP’s “authoritarian resilience” and adaptability, have about faced. “The consensus is stronger than at any time since the 1989 Tiananmen crisis that the resilience of the authoritarian regime in the People’s Republic of China (PRC) is approaching its limits”, wrote Nathan (2013). In a much discussed Wall Street Journal op-ed, Shambaugh (2015) likewise declared that “The endgame of

Chinese communist rule has now begun”. Having retrenched since 2009, Shambaugh (2016, ch.

4) argues that the CCP’s propaganda has lost its power as economic elites leave the country. He concludes that China must return to the path of political reform or fall into a middle-income trap.

3 Fourth, short marchers often point to an ongoing “culture shift” and popular support for democracy in China. Using World Values Survey data, Inglehart and Welzel (2005) identified a strong correlation between an index of “self-expression values” and democracy around the world, which led them to predict China’s democratization by 2025. One of Inglehart’s students,

Zhengxu Wang (2007, 2008), analyzed the same survey data in East Asia and came to a similar conclusion. Using a simple model to predict self-expression scores based on economic variables and using those scores to predict democracy levels, he argues that the rise of self-expression values portends China’s democratization by 2015-2020 once its self-expression index reaches about -1, about the level of Taiwan when it democratized. Inglehart and Welzel (2009, 48) similarly note that “China is now approaching the level of mass emphasis on self-expression values at which Chile, Poland, South Korea, and Taiwan made their transitions to democracy.”

Fifth, short march optimists have over time said “goodbye to gradualism” (Wang 2013).

Many now argue that China’s economy faces an imminent slow-down or crisis, perhaps driven by a property bubble or banking problems, that will make corruption less tolerable to the masses and will accelerate capital flight, which will force the CCP to “democratize or die” in ten years

(e.g. Huang 2013; Pei 2016b). Though he used to suspect Rowen’s short march predictions were too optimistic and Chinese democracy was at least 25-30 years away, Larry Diamond (2012, 11-

12), co-editor of the Journal of Democracy, now says CCP rule may end in the next ten years (by

2022). He asserts that “Rowen’s projections were a bit mechanical in assuming that economic growth would necessarily drive gradual political change toward democracy in China. Instead, it seems increasingly likely that political change in China will be sudden and disruptive.”

Short marchers correctly point to a number of stylized facts that support their narrative.

Of the 21 autocracies left in the world in 2015, half (ten) were major oil producers and five were

4 monarchies. By contrast, China has a small natural resource base relative to its population (and has been a net importer of oil since 1993). As such, the CCP cannot use a rent-based patronage system to survive. Only three autocracies--Singapore, Belarus, and Thailand—have managed to reach higher per capita GDP’s than China’s current level, Pei (2016) notes. Second, short marchers note that no one-party autocratic regime has ever survived much longer than 70 years

(e.g. the Communist Party in the Soviet Union and PRI in Mexico), implying that the CCP will approach its maximum life expectancy around 2020 to 2030. In short, given a growing middle class and the rise of “mass incidents” across the country, in order to secure modernity, short marchers see China poised for a revolution of rising expectations awaiting a precipitating crisis.

II. Forecasting A Short March? A Replication of the Classical Barro-Rowen Model

As a group, then, short marchers implicitly endorse a classical modernization model of democratization in building their narrative. Henry Rowen was unique among short marchers only in formalizing such a model and using quantitative data to make relatively precise forecasts in terms of the timing of China’s short march. His work is still cited by more qualitatively oriented short march scholars to this date (e.g. Pei 2016). But how did Rowen come to such a precise forecast anyways? To forecast China’s short march, it turns out that Rowen adopted the model of the determinants of democracy levels developed by fellow economist Robert Barro (1999). In this section, I describe the original Barro-Rowen forecast model and replicate and update its forecast in order to elucidate the mechanics and limitations of such a “short march” quantitative forecast model and point to potential avenues for improving such statistical forecast models.

The original Barro model sought to predict democracy levels (based on a Freedom House index that ranged from 1-7) at 5-year intervals for the 1972-1995 period. The Barro model included the following covariates as its core predictors of democracy: five-year and ten-year

5 lagged dependent variables (to control for state dependence), real per capita GDP (logged), average years of primary schooling for persons 25 and older, the schooling gender gap for persons 25 and older, the urbanization rate, population (logged), and a dummy term for oil exporters. All covariates were lagged by five years to allay concerns of endogeneity. He found the lagged dependent variables were positive and highly significant, indicating that democracy levels are extremely persistent over time. He also found a positive and significant effect for GDP per capita and education (weaker effects for population), and a negative and significant effect for the schooling gender gap and oil exporter dummy (weaker effects for urbanization).

Rowen, in turn, took the coefficients from the Barro model, and combined them with assumptions about continued Chinese growth in GDP per capita, education, population, and urbanization after 1995, to compute a gradual increase in predicted Freedom House scores for

China. I replicated this Barro-Rowen approach with observed panel data on 140 countries over the 1950-2015 period at 5-year intervals, with some minor adjustments. Instead of the Freedom

House index (which has been criticized for its subjective and non-transparent coding rules and is restricted to the post-1972 period), I test the robustness of the Barro-Rowen forecast using five alternative measures for my dependent variable: (1) a continuous polity index ranging from 0 to

1, (2) partial democracy (which equals 1 if a country has a normalized polity score ≥ .5, and is 0 otherwise), (3) democracy (1 if normalized polity score ≥ .8, 0 otherwise), (4) full democracy (1 if normalized polity score ≥ .9, 0 otherwise),2 and (5) binary Geddes et al. (GWF, 2014) measure.

Binary democracy measures are required to model the hazard rate for an abrupt transition rather than gradual liberalization, which is consistent with short marchers’ shift away from gradualism.

My benchmark Barro-Rowen models include the same predictors of democracy3, with two substitutions. Instead of years of primary education, I control for the aggregate mean years

6 of schooling (primary, secondary, or tertiary), which is a stronger predictor empirically across most models.4 Instead of an oil exporter dummy term, I include a more precise measure of oil and gas income per capita (logged).5 Table 1 presents panel estimates of the Barro-Rowen model on democracy levels.6 The results are similar but not identical to those of Barro (1999).

Overall, the models correctly predict over 90% of country-year observations. However, modernization variables (income, education, urbanization) do little of the predictive work in any of the statistical models. The effect of income is only positive and statistically significant for one of the five democracy measures (full democracy) and the effect of urbanization is positive but statistically insignificant.7 Among the modernization variables, only mean years of education has a consistently positive and statistically significant effect. By itself, these results indicate that short marchers obsession with GDP per capita figures is misplaced. Instead of focusing on an

“income trigger”, scholars should instead be investigating if there is an “education trigger.”

Instead, almost all of the work done by the models in Table 1 comes from the coefficients on the lagged dependent variables (DVs, particularly the 5-year lag), a testament to the high levels of temporal autocorrelation in democracy levels. Running models including only lagged

DVs reduces their explanatory power (R2 or pseudo-R2) marginally by 5-8%, whereas running models on the modernization variables alone reduces the R2 or pseudo-R2 by 40-52%. Based on the first model, using 2010 data for all covariates yields a predicted polity score in China in 2015 of .28 (nearly double China’s actual polity score of .15). Actual 2015 data also yields a predicted polity score of .28 in China in 2020, lower than the 0.5 level first predicted by Rowen for 2015.

If not by 2020, when does China reach a 50% probability of democracy in these models?

The answer, of course, depends on the assumptions for projecting the covariates over the coming decades. As a benchmark, I use off-the-shelf forecasts by leaders in their fields. First, I adopt the

7 long-run income forecast developed by Fouré et al. (2013), which assumes China’s per capita

GDP growth slows gradually from about 8% in 2016 to 4.8% by 2050 (compared to 9.7% a year from 1995-2015).8 At these rates, China would reach Singapore’s current level of wealth in

2050. Second, I adopt the educational attainment forecast of Barro and Lee (2015), who assume that China’s average years of schooling continues to increase gradually from 8 years to 10.5 years by 2040 and whose gender schooling gap of .7 years disappears by 2030. Third, I adopt the

United Nations’ (2014) World Urbanization Prospects forecast and assume China’s urbanization rate increases from 56% in 2015 to 67% in 2025 and 75% in 2040. Fourth, I adopt the United

Nations’ (2015) World Population Prospects medium fertility forecast that China’s total population increases from 1.37 billion in 2015 to a peak of 1.42 billion by 2030 back down to under 1.4 billion by 2040. Finally, in order to favor the short march prediction, I assume China’s oil income remains at current levels, even though it has quadrupled over the past fifteen years.

Figure 1 shows the forecast of China’s polity score using the Barro-Rowen model in column 1 of Table 1 using the forecast of the independent variables just described through 2040, which enables me to plot predicted polity scores through 2045 (due to the five-year lag period).

In the spirit of Rowen, this model indicates that polity scores will increase gradually to close to

0.5 after about 15 years, a short march to democeacy around 2030-2035 (see the dashed red line).

This is virtually the same trajectory Rowen predicted in 1995 when he predicted a short march from 1995-2015. In fact, Figure 1 also shows a simulated forecast of China’s polity score from

2000-2020 using actual observed values of the independent variables up to 2015. We again see the rough path that Rowen marked out to predict a Chinese democracy in 2015, except that in my model China actually reached the point Rowen predicted in 2010 (see the dashed green line).

My replication uncovers three key findings that call into question “short march” forecast.

Figure 1: Replicating the Barro-Rowen ''Short March'' Forecast Model .75

≅ 15 years ≅ 15 years

.5 .25

The black line shows China's observed polity2 score

Polity 2 Score2 from Polity(Normalized0-1) 0

1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050

Barro-Rowen Model Polity Forecast Using Observed Data for 1995-2015 Barro-Rowen Model Polity Forecast Using Forecast Data for 2015-2040

Note: Based on model 1 in Table 1, which replicates the empirical model of Barro (1999) used by Rowen (1996, 2007).

First, even in the Barro-Rowen models of democracy levels, China does not become a democracy

before 2030-35 regardless of democracy measure. China only passes a 50% predicted probability

of democracy between 2040 or later using any of the four binary measures. Second, there are no

plausible values of income or education that portend an endogenous transition to democracy

before 2030 in these models, in part because of temporal autocorrelation in regime type. Third,

the models in Table 1 overstate the effects of modernization variables by including democracies

in the sample. In Table 2, I replicate the Barro-Rowen models on democratic transitions rather

than democracy levels. To do so, I model positive changes in the polity index in the first column

and model dynamics of transition by restricting my sample to only non-democracies in the

previous five-year period for the models that have a binary democracy indicator. The effect of

modernization weakens in these transition models. None of the transition models predict China

reaching a polity score of 0.5 or a predicted probability of democracy over 0.5 by 2045, the last

9 forecast year. Thus, even using the same model famously employed by Rowen, I find that if

China had to wait on modernization alone, China’s march to democracy could be very long.

Can we trust these predictions from the Barro-Rowen forecast model? In short, no. The

Barro-Rowen models in Table 2 are very good at predicting cases of autocratic survival, but are much worse at successfully predicting democratic transitions (this is why the R2 values are so low at less than 0.1). The reason is that they almost always predict autocratic survival in the subsequent five years. The point is: structural and slow-moving modernization variables by themselves tell us very little about the pace and timing of democratization. Short march scholars who wish to build and improve upon the Barro-Rowen model would do well to take into account many other sets of variables, such as the number or prior democratic transitions, regime type, military power variables, measures of the strength of civil society, trade openness, and so on.

Such a modeling effort is beyond the scope of this article. One practical difficulty with creating such a forecast drawing on these other theoretically important variables is that there are no off- the-shelf of long-term forecasting models for these other variables to the best of my knowledge.

Scholars would thus have to expand the range of forecasted variables to gain explanatory power.

Another challenge in any such effort would be simulating the effect of economic crises and incorporating cross-national diffusion effects into more complex dynamic forecasting models.9

III. China’s Political Future: Vindicating Classical Modernization Theory?

Having laid out key components of prominent short marchers predictions, I now critically interrogate the two core short march assumptions which are explicitly comparative in nature, namely (1) the general validity of classical modernization theory and “transition zone” concepts, and (2) the claim that China is no different than prior modernizing “third wave” democratizers.

Logically, the short march argument could be found wanting for the following reasons: (a) the

10 drivers and dynamics of democratization in general have not or will not rely mainly on economic modernization (that is, they are drawing the wrong inferences from the historical “third wave” cases of transition), or (b) China in fact is different from previous historical cases in ways that continue to bolster its authoritarian resilience. If the first assumption is wrong, short marchers hopes are misplaced. If only the second assumption is wrong, their hopes are simply premature.

Let us now consider both possibilities in turn, beginning by reviewing a number of “inconvenient facts” about democratic transition in general that bear on China’s probability of democratization.

First, democratic transitions are low probability events for autocracies in general. In fact, only about one percent of autocracies transition to partial or full democracy in any given year.10

The percentage of autocracies that undergo transition to partial or full democracy rises to about

7% over a period of 5 years, 14% over 10 years, 22% over 15 years, 28% over 20 years, and 36% over 25 years (see Table 3). Nevertheless, that means nearly two-thirds of autocracies remain non-democracies 25 years later. Democratization is generally a much better long-term bet than a short-term one. What reason do we have to think that the same isn’t true for China today?

Second, as the number of autocracies in the world has declined over time, the number mixed regimes (what the polity IV project calls “anocracies”) have been on the rise. Even if autocracy is a regime type destined for extinction, it is not clear why China will democratize rather marginally liberalize or anocratize. Indeed, Table 3 shows that over a 25-year year time horizon, autocracies are just as likely to transition to more liberal non-democracies (or “closed anocracies”) rather than transition to partial or full democracy. Even if one assumes that China is otherwise “no different”, China becoming a full democracy by 2040 is still the least likely ex ante outcome. As shown in Table 4, anocratization is also more likely than democratization for each subset of autocracies that share key economic and political characteristics with China.

11 Third, development shapes prospects for democratic consolidation far more than it does for democratic transitions. Przeworski et al. (2000) famously showed that democracies become

“immortal” at high levels income, but that income doesn’t increase probabilities of democratic transition after a certain point. In fact, the richest autocracies like China (with GDP per capita >

$13,000 in $2011 PPP) are less than half as likely to democratize than their poorer counterparts

(see Table 4). A similar pattern is true of levels of human capital (proxied by average years of schooling). Highly uneducated non-democracies are unlikely to transition to democracy, and the hazard of democratic transition is rising in education levels from less than a year to about 5-7 years. However, after this point, higher levels of education do not predict much higher rates of democratization than countries with less education. With a GDP per capita of $13,572 and 8 years of schooling on average in 2015, China is undoubtedly one of the fastest developing autocracies ever, but this does not have to imply an ever rising hazard rate for democratization.

Fourth, the predictive power of economic development variables—such as per capita

GDP, urbanization, literacy, and size of the agricultural sector—for democracy has weakened over time (Boix et al. 2012), varies by region, and is less strong outside of Europe. In fact, the correlation between income levels and polity scores dropped from a robust 0.65 in 1949 to only

0.04 by 2015 (the last year of observed data). At the same time, the correlation between log of

GDP per capita and democracy is strongest in Europe (ρ = 0.60) and the Americas (ρ = 0.49), moderate in in Asia (ρ = 0.42), weak in Africa (ρ = 0.19), and non-existent in the Middle East (ρ

= -0.09). If anything, this regional variation points to a shorter march for remaining democratic holdouts in Europe and Latin America such as such as Belarus and Cuba than it does for China.

Fifth, autocracies can survive a long time even after becoming economically modern.

Consider a model of the determinants of democracy with only two variables: per capita GDP (a

12 positive predictor) and per capita oil and gas income (a negative predictor, both logged). With high GDP per capita ($13,572) and modest per capita oil income ($110), such a model suggests

China had a 76% predicted probability of being at least a partial democracy in 2015 (see Table

5). It has been 15 years since China passed the simply model threshold of a probability of democracy greater than 50%. By contrast, the previous 13 non-democracies that reached a GDP per capita of at least $10,000 before democratizing survived above the model’s “income trigger” for an average of 25 years (and as long as 43 years in Mexico and 40 years in the Soviet Union).

Among wealthy non-democracies in 2015, Singapore has passed the income trigger and been in the “transition zone” for a record of 47 years and counting. If China were to replicate the success of these other developing single-party regimes, China’s autocracy could survive to 2035 or later without even being a significant outlier in terms of the number of years in “the transition zone.”

Taken as a whole, these stylized facts shake our confidence in short marchers reliance on classical modernization theory for their predictions. What of their claim that China is no different than prior cases of “third wave” democratization? Of course, even short marchers recognize that

China is different in a number of respects from prior “third wave” cases, it’s just that they discount these differences and argue that they are not insurmountable obstacles to a transition.

The key question up for debate is whether the ways in which China is different matter or not for its democratic prospects. Let us consider a few more stylized facts concerning the ways that

China is different from prior cases that may cast a longer shadow over “short march” optimism.

First, only three countries have seen a comparable and prolonged period of economic development in the post-war period as China: Taiwan, South Korea, and Singapore. Isn’t it possible that China’s political future will remain non-democratic (looking more like Singapore) rather than transition to democracy (like South Korea and Taiwan)? Short marchers would note

13 that in 1987, the year when mass student protests ousted military dictator Chun Doo-hwan, and the same year when Chiang Ching-Kuo liberalized the quasi-Leninist Nationalist Party (KMT) regime by lifting martial law, South Korea’s per capita GDP was $9,000 and Taiwan’s was

$16,163. China’s GDP per capita in 2015 falls right in between. By contrast, Singapore has reached OECD income levels (~$80,000 in 2015). Even if China continued robust economic growth, it would not reach Singapore’s current level of wealth for at least three more decades.

The contrasting income and democracy trends for Taiwan, Singapore, and China are shown in

Figure 2. Short march proponents often assert that Singapore is the exception, doubting that

China can replicate a model based on a city-state of 5 million people. But China is also much larger than Taiwan (23 million people) or even South Korea (50 million). So if size were the key determinant of similarity, there would still be no standing for comparisons to any other case.

Second, as shown in Table 4, China has several properties that make it less likely to transition to partial or full democracy compared to your average run-of-the-mill autocracy. For example, older autocratic regimes tend to be more stable than younger regimes, not less so. The most dangerous period for any autocratic regime is the first five years. By contrast, among autocratic regimes like China that have survived over 65 years, only a few have transitioned to closed anocracy (of which only a subset transition again to partial or full democracy). The very fact that China has survived longer than other autocracies is prima facie evidence that it is more resilient than prior cases. Communist single-party regimes like China are also less likely to anocratize or democratize than other kinds of regimes that are more unstable (such as military regimes). Finally, China almost totally lacks usable “democratic capital” relative to the average autocracy,11 and as shown in Table 4, countries with a similar total lack of a recent democratic history were less than half as likely to democratize in the short-run than the average autocracy.

14 Figure 2: Models for China? Taiwan vs. Singapore Anocratic Singapore Democratic Taiwan Autocratic China 1 80,000 1 80,000 1 80,000

.75 60,000 .75 60,000 .75 60,000

.5 40,000 .5 40,000 .5 40,000

Polity Score Polity

GDP PerCapita GDP

GDP PerCapita GDP GDP PerCapita GDP

.25 20,000 .25 20,000 .25 20,000

0 0 0 0 0 0 1950 1990 1950 1990 1950 1990 1970 2010 1970 2010 1970 2010

Democracy GDP per cap. Democracy GDP per cap. Democracy GDP per cap.

Note: Polity IV Index is normalized from 0 (most autocratic) to 1 (most democratic). Per capita income is measured on a purchasing power parity basis in Constant $2011.

Third, a number of transition paths taken by prior third wave cases seem highly unlikely,

as even short marchers such as Pei (2016) acknowledge. For example, having largely barred

elections above the village level, an electoral revolution in the mold of the Color Revolutions

would seem impossible at present. Non-electoral democratic revolutions like the one China

experienced in 1989 is at least feasible. Given the contingent nature of democratic revolution, we

cannot totally dismiss the possibility of a nonviolent anti-regime campaign12; at the same time,

the baseline hazard rate is shockingly low (less than 2 percent of countries see any nonviolent

conflict, and a third of these are territorial campaigns that do not seek democracy). Given major

investments in repressive capacity, a non-violent revolution is less likely to emerge or succeed in

China.13 If a “Tiananmen II” campaign were to emerge, its likelihood of success would be

hampered by the CCP’s forestalling preexisting opposition groups from mobilizing. “Feeling the

river by crossing the stones” is not a reliable path to victory during a nonviolent revolution.

15 Svolik (2012) shows that most autocrats since 1946 have been overthrown in coups.

Although coups more often lead to new dictatorships, some democratic transitions are also preceded by coup activity that weakens incumbent autocratic regimes (Thyne and Powell 2014).

Yet China has no history of coup attempts and scores very low on most lists of coup forecasts.14

A “coup path” to democracy is therefore a highly unlikely for China. The People’s Liberation

Army (PLA) remains a party (not state) army, and the CCP is vigilant against ‘statification’

(guojiahua) and ‘depoliticization’ (feizhengzhihua) of the PLA. This is in no small part due to the fact that CCP succession politics are increasingly norm-bound (Nathan 2003). If Xi Jinping serves his full term, the next leadership transition (and potential succession crisis) will not take place until 2022. With decade-long succession cycles, the window of political instability is relatively small. If the CCP survives past 2022, the next window may not be for another decade.

China also seems unlikely to democratize as a result of a major external shock like a defeat in war (a la Argentina after the Falklands War in 1982). Unlike most other third wave cases, China is a geopolitical great power. In the twentieth century, it took two catastrophic world wars to democratize the illiberal but capitalist Germany and Japan (Gat 2010). One can imagine scenarios in which conflict breaks out and escalates in the Taiwan Strait or South or East

China Sea, but an intentional major power war to democratize a nuclear China is unthinkable.

The cure would be worse than the disease. Although the risks of major power war may be low, the rise of regional security tensions in Asia actually benefit the CCP. Conflict in Asia bolsters

Chinese leaders’ nationalist narrative that a strong state led by the CCP is necessary to protect

China’s interests in the South China Sea, to reunify Taiwan, and restore China to national greatness. Whereas international and territorial peace fosters conditions favorable to democracy

(Gibler 2012), China has one of the highest probabilities of being involved in a fatal militarized

16 interstate dispute in the world (Nordhaus et al. 2012); accordingly, China has made massive investments in the People’s Liberation Army (PLA) and People’s Armed Police, which in turn enhances the regime’s capacity to repress democratic opponents (Albertus and Menaldo 2012).

China’s size and status also make it less vulnerable to the pressures of democratic diffusion. Work by Carles Boix (2011) and Kevin Narizny (2012) indicates that the hierarchy of power in the international system conditions the causal effect of development on democracy.

Clients or former colonies of democratic hegemons (the United States and United Kingdom) are the states most likely to democratize. Both Taiwan and South Korea were largely dependent on the United States for their military security when they began democratizing in the 1980’s, and the U.S. applied pressure on those regimes to liberalize at crucial moments.15 The same leverage is not available with China. As a nuclear great power that sees itself as the center of East Asia

(Friedman 2009), diffuse international pressure and spillover effects from democratic diffusion are less effective on China (Chin 2014, 112; Diamond 2008). Thus, even if there is a coming

“wave” of democracy in Asia, China may well be the last to catch it, if it catches it at all.

Previous research has also shown that democratic transitions are often preceded by acute economic crises that delegitimize the regime and generate discontent (e.g. Haggard and Kaufman

1995). In the past, short marchers have posited that China could be forced to democratize in a manner similar to Indonesia (e.g. Pei 1999). Although China’s growth will inevitably slow down, many respected economists remain confident in China’s long-term growth potential (e.g. Fogel

2010; Subramanian 2011). Though short marchers often point to problems of over-investment and “ghost cities” (e.g. Cheng 2013), Chinese rural migrants unstoppable desire to move to cities mean an imminent property bubble may be premature (Miller 2012, Ch. 5). With the Renminbi now a global reserve currency at the IMF and with the People’s Bank of China sitting on trillions

17 in reserves, it seems highly unlikely that China will soon be crippled by a Latin American-style debt crisis. On the whole, gloom on the economic front is not shared in the most recent forecasts of China’s economy by the OECD, World Bank, and IMF, which forecast a gradual decline in economic growth to over 6% growth by 2018.16 To the extent China is poised for long-run economic growth (albeit at a lower level than in the past), this should bolster the CCP’s survival.

Finally, many predictions of China’s coming democratization have already been falsified by history. Jack Goldstone (1995) predicted a CCP collapse by 2005-2010. Zbigniew Brzezinski,

I-tzu Chen, and Arthur Waldron (1998) each surmised the end of CCP one-party rule by 2008.

Gordon Chang (2001) famously predicted that the “shock therapy” of WTO accession would trigger the collapse of CCP rule by 2011. In 2011, he predicted collapse in 2012 (Chang 2011).

None of this came to pass. Similarly, predictions of China’s “creeping democratization” (e.g. Pei

1995) have not been born out. For example, village elections have not expanded to the township level as many had expected (e.g. Craner 2006). Nor has the National People’s Congress become

“a potential challenger to the CCP’s monopoly of power” (e.g. Pei 1998, 74). Similarly, the internet has yet to fully liberate China’s media and foster freedom of speech as many hoped.

IV. Conclusion

To wrap up this discussion, rather than summarize my argument I will instead briefly address a few potential objections. The first objection is that many may argue that it is a fool’s errand to attempt to predict China’s political future at all. There is some truth to the claim that

China’s future is both unknown and unknowable (Swaine et al. 2003; Fewsmith 2005). But whether and when China will democratize is vitally important not only for the nearly quarter of humanity that are Chinese citizens, but also for those in the west who worry that China is leading a global authoritarian resurgence that could define geopolitics for decades and threaten the U.S.-

18 led liberal-democratic global order (e.g. Gat 2007; Kurlantzick 2013). For example, Aaron

Friedberg (2011) cites China’s democratization as perhaps the only factor with the potential to foster stable strategic trust and thus stop a “contest for supremacy” between China and the

United States in Asia. If he is right, it matters greatly to policy planners that scholars accurately assess how likely China’s democratization is in coming years. Given that pundits and politicians will make predictions anyways, often by relying on selective or misleading analogical reasoning, there is a need for special issues like this one where scholars can raise the level of debate.

Second, some may object to the mostly “structural” or quantitative approach to forecasting democracy used by Rowen and replicated in this article; the models are admittedly mechanical projections. If and when China democratizes, choice and unexpected events—what

O'Donnell and Schmitter (1986, 5) call fortuna—will no doubt be present, but the fact that the political world is stochastic rather than deterministic is no reason to eschew a structural approach a priori. The limitations of the Barro-Rowen model are an invitation to create better models, not to throw our hands up. Also, to the extent the future is “unknowable”, short march predictions are on just as shaky ground, for on what basis could they claim the odds are ever in their favor?

Finally, in this article I have tried to take seriously the claim that China is a case that is not entirely sui generis. Like short march optimists, I reject the cultural determinist position that

China is unlikely to democratize because it has a hierarchical and undemocratic Confucian culture (Huntington 1991, 300-307). Nor should anything in my critique be construed as support for the notion that China will “rule the world” (e.g. Jacques 2009), establish a viable “Beijing consensus” (e.g. Halper 2010), or successfully find a meritocratic but non-democratic “third way” (e.g. Li 2013; Bell 2015). I do not dismiss the real possibility that China’s transition gets

“trapped” or derailed (Pei 2006). But that future also does not necessarily lead to democracy.

19 In his best-selling book The Future of Freedom (2003, 81), Fareed Zakaria aptly noted that “The single most important test of the connection between capitalism and democracy will take place in China over the next few decades.” Nearly fifteen years later, observers still wonder: will China finally democratize? Despite the failure of previous short march predictions, optimists still see democracy in China’s future over the next decade. I hope they are right, but the evidence

I have reviewed suggests that China’s democratization is not necessarily imminent. At present, the Chinese regime enjoys popular legitimacy and no major social groups appear ready or able to press for democracy (e.g. Whyte 2010; Chen 2013). China’s political system may indeed be forced to become more deliberative and responsive, but such political changes are just as likely to be bounded within an authoritarian system (or an “anocratic” one) as a democratic one.

This is not to say that democracy in China is impossible. Many futures remain possible.

But forecasting, of course, forces us to deal in probabilities. It would be foolhardy to make any deterministic predictions. After all, even our best forecasting models of democratic transitions only get it right less than a half of the time. Yet, if forced to bet, the safer bet is that the CCP regime will endure for the foreseeable future and set new records for autocratic endurance. In

1987, Deng Xiaoping was reportedly quoted as saying that national elections would come to

China in fifty years (2037). His message was clear: China’s road to democracy will be a very long march, not a short one. Only in the fullness of time will we know if Deng was right.

20 Tables

Table 1:Barro-Rowen Model of Democracy Levels at 5-Year Intervals, 1960-2015 Continuous Binary Democracy Measures Polity Polity > 0 Polity > 5 Polity > 7 GWF Index 5-year lag of DV 0.763** 3.728** 3.702** 4.590** 3.689** (0.04) (0.31) (0.33) (0.40) (0.32) 10-year lag of DV 0.061 0.846** 1.024** 0.459 1.147** (0.04) (0.28) (0.37) (0.48) (0.40) Log(GDP per capita) -0.008 -0.182 0.144 0.515** -0.023 (0.01) (0.18) (0.17) (0.18) (0.16) Years of Schooling 0.013** 0.290** 0.199** 0.170** 0.194** (0.00) (0.05) (0.04) (0.05) (0.05) Schooling Gender Gap 0.003 -0.067 -0.045 -0.257* 0.001 (0.00) (0.11) (0.11) (0.13) (0.11) Urbanization rate 0.038 0.558 0.724 0.244 1.141 (0.03) (0.73) (0.72) (0.83) (0.79) Log(population) 0.004 0.098 0.110 0.21* 0.116 (0.00) (0.07) (0.08) (0.09) (0.08) Log(oil inc. per capita) -0.005* -0.085+ -0.156** -0.192** -0.126* (0.00) (0.05) (0.05) (0.05) (0.05) Constant 0.071 -2.667+ -5.336** -9.358** -4.269** (0.06) (1.44) (1.41) (1.51) (1.36)

# of Countries 140 140 140 140 132 # of Observations 1409 1409 1409 1409 1302 R2 or Pseudo- R2 0.81 0.63 0.64 0.71 0.64 AUC Score 0.95 0.96 0.97 0.95 Estimator OLS Logit Logit Logit Logit First Year that 2035 >2045 >2045 2040 >2045 Pr(China Dem.) > 0.5 Note: Robust standard errors clustered by country are in parentheses. The forecast that relies on a continuous measure, as in the original Barro-Rowen model and column 1, imply a shorter march to democracy for China. The reason is simply that positive predicted polity scores in prior years generate increases in future predicted polity scores though the lagged dependent variables. By contrast, binary measures equal 0 in all previous periods for China. Thus, increases in predicted probabilities must come through other independent variables. + p<0.10, * p<0.05, ** p<0.01

21 Table 2: Barro-Rowen Model of Democratic Transitions at 5-Year Intervals, 1960-2015 Continuous Binary Democracy Measures Polity Polity > 0 Polity > 5 Polity > 7 GWF Index Upswing 5-year lag of DV -0.031** (0.01) 10-year lag of DV -0.004 0.728+ 0.892 0.381 1.126* (0.01) (0.37) (0.56) (0.73) (0.52) Log(GDP per capita) -0.006* -0.515** -0.276 0.007 -0.337+ (0.00) (0.20) (0.23) (0.24) (0.19) Years of Schooling 0.003** 0.229** 0.197** 0.114+ 0.182** (0.00) (0.07) (0.05) (0.06) (0.05) Schooling Gender Gap 0.001 -0.010 -0.131 -0.304 0.029 (0.00) (0.14) (0.16) (0.19) (0.14) Urbanization rate 0.011 1.661+ 1.707+ 2.091+ 1.320

Log(population) (0.01) (0.99) (1.02) (1.07) (0.94) 0.000 0.139 0.232* 0.315* 0.129 Log(oil inc. per capita) (0.00) (0.12) (0.11) (0.12) (0.11) -0.001 -0.084 -0.164* -0.193** -0.114+ Constant (0.00) (0.06) (0.06) (0.07) (0.06) 0.057** -0.615 -3.332+ -6.545** -1.912

# of Countries 140 98 104 110 99 # of Observations 1408 670 804 919 744 R2 or Pseudo- R2 0.03 0.07 0.08 0.09 0.06 AUC Score 0.70 0.73 0.74 0.69 Estimator OLS Logit Logit Logit Logit First Year that >2045 >2045 >2045 >2045 >2045 Pr(China Dem.) > 0.5 Note: These results replicate those in table 1 but predicting democratic transitions rather than levels. That is, the estimation sample in the models with binary democracy measures is restricted to non-democracies in the previous five-year period, which is why the five-year lag of the DV is omitted. The DV in the first column is a measure of the 5-year change in polity score, where negative changes have been set to zero. Following Teorell (2010), this variable is the analog to isolating the determinants of democratization, as opposed to democratic survival. Robust standard errors clustered by country are in parentheses. Note that the implied time to a democratic transition for China is longer than in the original Barro-Rowen model tabulated in levels. The reason is that models in levels conflate the effect of income on democratic survival (higher) with the effect of income on democratic transition (lower). The last column model covers the 1960-2005 period due to data limitations on the DV. + p<0.10, * p<0.05, ** p<0.01

22 Table 3: The Time-Horizon of Democratic Transitions, 1946-2015

Current Year Non Democracy Democracy Previous Autocracy Closed Anocracy Partial Full Autocracy: [Polity2 ≤ -6] [-6 < Polity2 ≤ 0] [0 < Polity2 ≤ 7) [Polity2 > 7] 1 year ago 3,181 94 34 7 [95.93%] [2.83%] [1.03%] [0.21%] 5 years ago 2,659 307 170 68 [82.99%] [9.58%] [5.31%] [2.12%] 10 years ago 2,179 442 292 141 [71.35%] [14.47%] [9.56%] [4.62%] 15 years ago 1,745 515 404 230 [60.30%] [17.80%] [13.96%] [7.95%] 20 years ago 1,386 555 459 305 [51.24%] [20.52%] [16.97%] [11.28%] 25 years ago 1,037 564 516 383 [41.48%] [22.56%] [20.64%] [15.32%]

Table 4: Transition Probabilities by China’s Key Characteristics, 1946-2015 Pr(Transition to Pr(Transition to Partial Closed Anocracy) or Full Democracy) By Region and Time Period All Autocracies, 1945-2015 94 / 3,323 (2.83%) 41 / 3,323 (1.23%) Post-Cold War Autocracies, 1991- 37 / 770 (4.81%) 19 / 770 (2.43%) East Asian Autocracies, 1945-2015 9 / 461 (1.95%) 4 / 461 (0.87%) Post-Cold War East Asian Autocracies, 1991- 2 / 130 (1.54%) 1 / 130 (0.77%)

By Country or Regime Characteristic Age of Ruling Regime > 65 years 3 / 130 (2.31%) 0 / 130 (0.00%) GDP Per Capita (PPP $2011) > $13,000 5 / 483 (1.04%) 2 / 483 (0.41%) Mean Years of Schooling > 8 years 10 / 590 (1.69%) 7 / 590 (1.19%) Communist Party Regime 5 / 705 (0.71%) 5 / 705 (0.71%) Urbanization Rate > 50% 27 / 1,002 (2.69%) 13 / 1,002 (1.30%) No History of Coup Attempts 14 / 1,142 (1.23%) 10 / 1,142 (0.88%) Any Kind of Party-Based Regime 23 / 1,576 (1.46%) 11 / 1,576 (0.70%) Little to No Democratic Capital 45 / 1,981 (2.27%) 11 / 1,981 (0.56%) Not a Major Oil Producer (<90% Globally) 87 / 2,721 (3.20%) 41 / 2,271 (1.51%) Note: The numerator is the total number of transitions and denominator is total country-years of autocracy with that characteristic. China is included in each of the listed categories as of 2015.

23 Table 5: How Long Can Developmental Non-Democracies Be in the “Transition Zone”? Per Capita ($): # Previous Autocratic Years of Prob. GDP Fuel Democratic Spell Pr(Dem) Transition Country (Dem) (PPP) Income Transitions Duration > 0.5 Year

Historical Democratic Transitions in Wealthy “Developmental” Non-Democracies E. Germany 0.85 21,361 106 0 39 32 1989 Taiwan 0.84 20,698 8 0 42 23 1992 Czechoslov. 0.79 13,566 2 1 41 39 1990 Spain 0.78 13,130 19 3 36 23 1976 Bulgaria 0.77 11,985 2 1 70 23 1990 Croatia 0.77 13,478 74 0 7 5 1999 Greece 0.77 12,987 0 3 6 4 1974 Hungary 0.76 12,391 91 0 121 28 1989 Russia 0.75 18,128 1,271 0 191 40 1992 Portugal 0.73 9,642 0 2 46 16 1975 Thailand 0.72 11,105 189 4 1 21 2008 Tunisia 0.71 10,505 254 0 51 27 2011 Mexico 0.71 10,602 354 0 171 43 1994

Average Years of Pr(Dem) > 0.5 Prior to Democratic Transition 25

Wealthiest “Developmental” Non-Democracies in 2015 Singapore 0.97 80,192 0 50 47 ? Belarus 0.85 16,662 103 0 20 18 ? Bahrain 0.81 43,754 2,687 0 44 5 ? Thailand 0.78 15,347 184 5 1 7 ? China 0.76 13,572 110 1 102 15 ? Jordan 0.74 10,240 4 0 69 17 ? Egypt 0.71 10,250 259 1 63 18 ? Iran 0.70 15,547 1,597 1 11 9 ? Swaziland 0.68 8,122 0 0 47 28 ? Uzbekistan 0.66 5,716 332 0 24 8 ? Morocco 0.66 7,365 1 0 172 26 ? Kazakhstan 0.65 23,522 3,252 0 24 22 ? Note: Pr(Dem) is the probability a country is a partial democracy (polity2 > 0) given lagged values of two variables: GDP per capita (logged) and oil and gas income per capita (logged) based on a standard logit regression of 172 countries from 1950-2015 (regression results not shown). The probabilities thus model the “income trigger” often invoked by “short marchers.”

24 Bibliography

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End Notes

1 Here I refer to a class of arguments by scholars whom I deem have similar assumptions. None of the scholars here necessarily ascribes to each assumption nor self-identify as a short-marcher. 2 The cutoff points for partial and full democracy in the polity index follow the convention set first by Epstein et al. (2006). Data for the polity2 index comes from Marshall et al. (2016). 3 GDP per capita is mainly from the Penn World Tables version 9.0 (Feenstra et al. 2015), but with gaps for missing countries filled in other sources such as the World Bank and Bolt and van Zanden (2013). All income is reported in constant $2011 at “purchasing power parity” levels. Population and urbanization data is from the United Nations (2014; 2015). 4 Educational attainment data is from the most recent dataset by Barro and Lee (2013). 5 Oil and gas data is primarily from Ross and Mahdavi (2015), with missing data imputed from Haber and Menaldo (2011) data. The two oil income measures are highly correlated (ρ = 0.94). 6 I present simple OLS and logit specifications. Barro (1999) prefers seemingly unrelated regression (SUR) methods, where a separate equation is used to model democracy in each time period. This effectively allows him to include period fixed effects. Despite technical differences, the SUR results or those with year fixed effects are similar to the ones presented here. 7 This is true even when I restrict the models to the 1970-1995 period analyzed by Barro (1999). The difference in results is thus not a function of different time periods, but instead must be a function of either (a) revisions in income data or (b) peculiarities of the Freedom House measure.

8 Similar results obtain if I instead use the forecast of the USDA’s International Macroeconomic Data Set forecast, which assumes a slower GDP per capita growth rate for China through 2030. https://www.ers.usda.gov/data-products/international-macroeconomic-data-set.aspx 9 In the Barro-Rowen models, each country is a “closed polity”, and what happens outside of China has no effect on Chinese politics. This, of course, is not a realistic assumption. One could attempt to model regional diffusion, though this is no simple straightforward task, as China has 18 neighbors, 14 by land and 4 within 400 miles by sea. As of 2014, six of China’s neighbors were full democracies: Mongolia, Taiwan, Japan, India, and the Philippines. Four qualified as partial democracies: Russia, Kyrgyzstan, Bhutan, and Pakistan. The remaining neighbors were non-democracies: Tajikistan, Kazakhstan, North Korea, Myanmar, Laos, and Vietnam. Not surprisingly, short march predictions also argue that a wave of democracy is coming to Asia (e.g. Diamond 2012). However, such forecasts also tend to rest on the same logic as the Barro- Rowen model. Nevertheless, modelling diffusion effects would require us to also consider broader democratic trends in Asia. Research indicates that autocracies that are surrounded by a higher share of democracies have a higher likelihood of transitioning to democracy (Brinks and Coppedge 2006). If true, then advances or setbacks in other countries should also affect China. 10 I use the polity IV project’s definition of autocracy here. 11 I adopt the operationalization of democratic capital proposed by Persson and Tabellini (2009), a discounted sum of prior years of democracy (results are similar regardless of the discount rate). 12 Chenoweth and Ulfelder (2015) argue it is hard to predict the onset of nonviolent revolutions. 13 The civil resistance literature shared the possibilist orientation of short march scholars in arguing that nonviolent anti-regime campaigns can emerge or succeed anywhere (Chenoweth and Stephan 2011). However, more recent research indicates that prior results along these lines are largely a function of poor measurement of repressive capacity, e.g. CINC scores. More precise measures of military power do in fact deter people power movements (Chin 2015). 14 For example, China ranks only 80 of 161 countries in Andreas Beger and Michael Ward’s 2017 forecast. See http://andybeger.com/2017/02/10/coup-forecasts-2017/, accessed March 1, 2017. Nathan and Scobell (2012, 294) point out that the only coup-like incident in CCP history was the 1976 arrest of the Gang of Four, which was part of the succession struggle after Mao’s death. The Lin Biao affair, meanwhile, remains a mysterious alleged coup plot. 15 For U.S. congressional pressure on Taiwan to liberalize, see Bush (2004, 197-218). For U.S. diplomatic pressure on South Korea not to repress students as in Kwangju, see Fowler (1999) and Lilley and Lilley (2004, 264-280). 16 For the OECD, see http://www.oecd.org/economy/china-economic-forecast-summary.htm. For the IMF World Economic Outlook, see http://www.imf.org/external/pubs/ft/weo/2017/update/01/ For the World Bank, see http://www.worldbank.org/en/publication/global-economic-prospects. accessed 1 March 2016.