Does a Wife Shortage in China Mean More Crime Too?
In China, approximately 120 boys are born for every 100 girls. This issue stems in part from the infamous one-child policy that China put in place in 1979. The combination of a cultural bias favoring boys and this policy has created a gender disparity that is not seen in any other country. Between 1998 and 2004, China has also seen a rise in criminal offenses by 13.6 percent. An increase in the number of young unmarried men, who are traditionally more crime prone, can help account for the increase in crime in China according to the December 2013 article “Sex Ratios and Crime: Evidence from China” by Lena Edlund, Hongbin Li, Junjian Yi, and Junsen Zhang in The Review of Economics and Statistics. Ultimately, the authors recognize that, while the rise in sex ratios has coincided with a dramatic increase in crime, a causal link is difficult to establish.
From 1998 to 2004, the male to female gender ratio of young adults (ages 16 to 25 years old) in China rose from 1.02 to 1.06, which suggests an increasing surplus of men. The authors use province-year panel data for their core analysis combined with 2000 census information on the provinces of birth and residence of the subjects. They found that over the study period, the sex ratio rose by 4 percent and crime rates by 82.4 percent. It is important to note that the authors focus on province-level sex ratios for a number of reasons, but most prominently the implementation of birth planning policies was delegated to the provinces and, until the early 1990s, inter-province migration was strictly regulated (arguably rendering marriage markets more provincial than national).
The authors look at monogamous marriage in terms of a lottery model, in which a man can only win one wife. Those who marry are removed from the lottery, which creates a nested structure problem for the rest. Ultimately, the authors want to see how the decreased number of women relative to the number of men affects the level of premarital investments in human capital is made. The authors note that lower investment increases the likelihood of crime. They focus on an equilibrium at which the men make identical human capital investment decisions. If the sex ratios were equal, then all men would be guaranteed a wife and there would be no marriage market returns to premarital investments. The existence of fewer women lowers the value of the lottery, causing men to reduce their investments, since the likelihood of getting a mate diminishes. Men are less likely to invest in themselves, and crime may be easier than said investment.
The authors try to build on a long tradition in sociobiological literature that links male behavior – risk taking, dominance, male-to-male aggression – to competition for partners, but based upon the results of the analysis, they conclude that there is not a relationship here. The authors calculate that higher sex ratios overall could account at maximum for up to one-seventh of the overall rise in crime, but this is not seen when controlling for certain data.
It is worth noting that the authors do not define the differences between violent and nonviolent crime in their study. This may be relevant because violent and non-violent crime are very different, frequently are motivated by vastly different things, and ultimately can have very disparate outcomes. Ultimately, the authors acknowledge that they fail to make a firm connection between the excess of men and crime using the data provided. For the authors, it appears that the low barriers to entry and the possibility of some upside to committing crime may give it particular appeal to low-skilled men looking for a break from being at the receiving end of the wife shortage. This shows that the one-child policy in China not only created a preference for boys over girls but also created a female shortage in the marriage market, which may have serious unintended policy consequences.
Source: Sex Ratios and Crime: Evidence from China, Lena Edlund, Hongbin Li, Junjian Yi and Junsen Zhang, The Review of Economics and Statistics, December 2013.
Feature Photo: cc/(FromTheNorth)