China fertility report,2006-2016 An analysis based on China fertility survey 2017

Based on China fertility survey 2017,this report presents the national fertility level,age-specific fertility rate and parity distribution.The survey results show that during 2006-2016 the mean ages at first marriage and first birth increased by 2.7 and 2.6 years respectively.From 2006 to 2011,the total fertility rate was around 1.60-1.70,and experienced notable fluctuations during 2012-2016.Compared the age-specific fertility in 2006 with in 2011,the curve in 2016 shifted significantly to the right side.Affected by the relaxation of the fertility policy,the proportion of second births among the total births had increased year by year since 2012.

China fertility survey 2017:design and implementation

This paper examines the design and the process used to carry out the China Fertility Survey 2017,a national representative survey that collected data on fertility desire,childbearing behavior,the use of childbearing services,and the determinants of childbearing behavior.The sampling method adopted was three-stage stratified probabilities proportional to size(PPS),and survey implementation made use of Computer Assisted Personal Interviewing(CAPI).CAPI played a significant role in survey design,last-stage sampling,interviewer training,face-to-face interviews,and questionnaire review and quality control.The survey results were compared with relevant data in the Integrated Management Information System for Population and Family Planning to check consistency.Ex post facto weighting was applied to correct sample structure bias.The process used to acquire accurate personal information is summarized.Suggestions based on consideration of sampling frame distortion by population mobility and other factors are put forward in the hope of improving similar sampling surveys in the future.

Non-sampling errors in questionnaire surveys: findings from a National Fertility Survey

Non-sampling errors can generally be divided into three types:sampling frame errors,non-response errors and measurement errors.Missing target units in the sam-pling frame,improper handling of non-responses,and misreporting or underreport-ing of key variables in the questionnaire can all cause deviations in a survey’s results.The widespread application of Computer-Assisted Personal Interviewing(CAPI)systems and the inclusion of administrative records from government sources in sur-veys has strengthened the ability to control non-sampling errors.Taking a national fertility sampling survey as an example,this study summarizes the sources of var-ious non-sampling errors and explains how to harness big data resources such as administrative records to control non-sampling errors throughout the survey.The study analyzes the impact of three types of non-sampling errors on the results of the fertility survey and examines the strategies used to address the problems caused by these non-sampling errors.The findings indicate that non-sampling errors were the main source of total error in the survey,and that the errors found came mainly from sampling frame errors;non-response errors and measurement errors were controlled and had little impact on the survey results.