The current protests in China make many people wonder whether the situation will escalate further.

For a demographics-based analysis (youth bulge theory), read on!

I also created a video for this post (in German):

A series of protests against COVID-19 lockdowns began in mainland China middle of November 2022. The protests started in response to measures taken by the Chinese government to prevent the spread of COVID-19, including implementing a zero-COVID policy, which confines many people to their homes without work and left some even unable to purchase daily necessities.

Protesters demanded the end of the government’s zero-COVID policy and lockdowns, and some extended their protest towards the leadership of Xi Jinping and the Chinese Communist Party.

The question now is, will those protests spread and spark something bigger, perhaps even a revolution? Or will they just subside again? In this post, we will use the powerful youth bulge theory to analyze the situation. The basis of this theory is the demographics of a country, especially the form of the population pyramid.

The gist of the theory is that the larger the proportion of younger people compared to older people, the more violent political and social conflicts there will be. We showed a highly significant correlation between those two based on World Bank data. On top of that, we found a tipping point at about 24% for the age group 0-14.

More details can be found here: The “Youth Bulge” of Afghanistan: The Hidden Force behind Political Instability and here: Youth Bulge Theory: Why there won’t be an Uprising in Russia.

Now, let us dive into the situation in China and compare it with the US, Germany, and Afghanistan to provide some context:

library(WDI)
## Warning: package 'WDI' was built under R version 4.2.1
age0_14 <- WDI(indicator = "SP.POP.0014.TO.ZS", start = 2020, end = 2020) # proportion of 0-14 year olds 
pol_stab <- WDI(indicator = "PV.EST", start = 2020, end = 2020) # political stability indicator

data <- merge(age0_14, pol_stab)[c(2, 4, 5)] |> na.omit()
colnames(data) <- c("country", "age0_14", "pol_stab")

plot(data$age0_14, data$pol_stab, col = "darkgrey", xlab = "Proportion of young people (in %)", ylab = "Political stability", main = "Youth Bulge Theory")
lm.out <- lm(pol_stab ~ age0_14, data = data) 
abline(lm.out, col = "black", lwd = 3)
abline(v = 23.9, col = "red", lwd = 2)

country <- "China"
points(data$age0_14[data$country == country], data$pol_stab[data$country == country], col = "red", lwd = 8)
text(data$age0_14[data$country == country], data$pol_stab[data$country == country], labels = country, pos = 4)

country <- "Germany"
points(data$age0_14[data$country == country], data$pol_stab[data$country == country], col = "orange", lwd = 8)
text(data$age0_14[data$country == country], data$pol_stab[data$country == country], labels = country, pos = 4)

country <- "United States"
points(data$age0_14[data$country == country], data$pol_stab[data$country == country], col = "blue", lwd = 8)
text(data$age0_14[data$country == country], data$pol_stab[data$country == country], labels = "USA", pos = 4)

country <- "Afghanistan"
points(data$age0_14[data$country == country], data$pol_stab[data$country == country], col = "darkgreen", lwd = 8)
text(data$age0_14[data$country == country], data$pol_stab[data$country == country], labels = country, pos = 4)

As we can see the proportion of 0–14-year-olds is way below the critical tipping point (= the narrow red line). That alone of course doesn’t give a “guarantee” that there won’t be any serious uprising or revolution but it can provide a good heuristic with about 80% accuracy.

Comparing this with other countries shows that, with Germany and Afghanistan on different ends of the spectrum, the US and China are not too far apart, which is another indicator that the situation will probably not escalate quickly but calm down again after some time. The proportion of young people is even lower in China (17.7%) than in the US (18.4%).

What do you think will happen in China? And what do you think about the youth bulge theory in this context? Please let us know in the comments!