Group19 Proposal

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Sex Ratio At Birth in China

Proposal

Poster

Application

Report

Male or Female, that is a question!!

Motivation

Based on “The Global Gender Gap Report 2017”, China remains the world’s lowest ranked country with regard to the gender gap in its sex ratio at birth(1-a). Tracing back to previous census data and demographic statistics, sex ratio at birth in China has been on the high side since the early 1980s and rising continuously. “In the human species the ratio between males and females at birth is slightly biased towards the male sex. The natural “sex ratio at birth is often considered to be around 105. This means that at birth on average, there are 105 males for every 100 females.” “The sex ratio of total population is expected to equalize at 0.9445(female-to-male ratio) . But in the third, fourth, fifth and sixth censuses, the sex ratios at birth in China is 108.5, 111.3, 116.9 and 118.1, respectively. China has become the populous nation with highest sex ratio at birth and in most serious gender imbalance situation. We try to find out the socio-economic and cultural factors that leading to the increase of the sex ration at birth, which may be meaningful to curb the increase of birth sex ratio and restore it to normal level.

Objectives

Data Discovery

Based on the previous research, we explore the data from sixth census preliminarily, detect the expected and discover the unexpected patterns of sex ratio at birth from massive data, and select the variables related to sex ratio at birth.

Uncovering Relationships

We build up model to uncover the between the sex ratio at birth and the selected variables and verify the relationship by statistic test.

Data Visualization

Design the data visualization to show the relationship between sex ratio at birth and other factors from the time and spatial dimension.

Data description

Our data are mainly obtained from the Sixth Census of China (1st Nov, 2009-31st Oct,2010) and Chinese Statistical Yearbook in 2011. The details of the dataset are shown as follows:

The Sixth Census of China
1.1-1 Number of households, population and sex ratio by province
1.1-5 Population of agricultural households and non-agricultural households by sex and province
2.1-3 Population by sex, age and province
2.1-4 Population by sex, age
2.6-1 Number of newborn by sex, child order and province
2.6-2 Number of childbearing women by age, child order and level of education
2.6-11 Average number of live birth and survived children of women aged 15-64 by regions
2.6-13 Average number of live birth and survived children of women aged 15-64 by education level
Chinese Statistical Yearbook, 2011
3-10 Comparison of Population with Various Education Attainment Per 100 000 Persons by Region
3-7 Total Population and Sex Ratio by Region
10-15 Per Capita Annual Income of Urban Households by Sources and Region (2010)
3-4 Total population and birth rate, death rate, natural growth rate by region, 2010
21-7 Number of Beds in Health Institutions per 1000 Population by Region (2010)

Methodology

IDEA Method

Detect the expected and discover the unexpected patterns from massive data

Multiple linear regression model

The model requires that the data meet the following requirements: independent, normal distribution, and equal variance model assumptions. When the data does not meet the independent requirements, the model should not be used.

Global Spatial Autocorrelation Analysis

The technique is used to determine the variable of a position in a spatial region has a correlation with the same variable in its vicinity.

Spatial Regression Model

The technique is applicable to the data with spatial correlation. Spatial regression model included spatial lag model (SLM) and spatial error model (SEM).

Data Source

1. 2010中国人口普查资料
2. 2011中国统计年鉴