Effects of gender ratio on saving rate, house price and crime rate in China

The gender ratio is defined as the relative number of males to 100 females. Usually, the gender ratio will be balanced in a region or country. However, the gender ratio is exceptionally imbalanced in China. The National Health and Family Planning Commission of China claims that in 2030, 30 million males will not get married in China, which is a prominent issue affecting many economic and social aspects of society. Moreover, geographically closer regions tend to have similar economic behaviour. This study challenges traditional econometrics by analysing economic behaviour related to gender imbalance. This thesis has examined whether; the saving rate, housing prices and the crime rate in China had a spatial effect and tested the effects of the gender ratio on; the saving rate, housing prices and the crime rate. The first objective was to test the impact of gender imbalance on the saving rate. This study found that China's household saving rate had a positive spatial autocorrelation. Using data from 30 provinces over the period 2000-2017 and accounting for the spatial effect, this study did not find any significant relationship between the gender ratio and saving rate. This result was because male children have higher income potential, allowing their parents to save less, offsetting the competitive saving hypothesis that males need to save more to increase their relative standing in the highly competitive marriage market with a skewed gender ratio. Moreover, the saving rate may not be a good proxy for men's relative standing in the marriage market. Females might focus more on items that convey higher socioeconomic status, such as; expensive houses and luxury cars. For the second objective, this study extended the existing research on the link between housing prices and the gender ratio. The result demonstrated that a positive spatial autocorrelation characterised housing prices in China. The result revealed a direct positive relationship between housing prices and the gender ratio using data from 30 provinces over the 2000-2017 period. This finding supported the competitive housing hypothesis, which predicts that a higher gender ratio will cause higher house prices if housing is viewed as a tool for improving one's status. Furthermore, the result showed that the adjacent province's gender ratios positively affected housing prices in the local province. This outcome may have been because some males migrate from adjacent provinces to the local province for marriage if they have a high gender ratio. However, they also need to buy a house to improve their status, as it is an essential pre-condition for marriage. This situation is likely to increase the demand for houses and lead to higher prices in the local province. The third objective has extended the literature on the link between the gender ratio and the crime rate. Similarly to the saving rate and house prices, the crime rate in China displayed a positive spatial autocorrelation. This study found a positive relationship between the crime rate and gender ratio using data from 30 provinces between 2000-2017 and controlling for spatial effects,. The results supported that the high gender ratio caused; maleness effect, incentive effect, and the civilizing effect resulting in more crimes. Furthermore, the result also revealed that the gender ratio in adjacent provinces positively affected the crime rate in the local province as the distance was negatively related to the migrant transfer intention. People in an adjacent province with a higher gender ratio were more likely to migrate to the local province. The crime rate would increase with more men based on the maleness effect. The men from a province with a higher gender ratio were more likely to have the civilising effect. This outcome may have explained the high crime rate in the local province. This study's findings have shed new light for policymakers to devise specific policies related to gender imbalances that will improve the quality of life for citizens.

Text SPE 2022 9 UPM IR.pdf Download (1MB)

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