Sampling Scheme for 2003 General Social Survey of China

Transcription

1 Sampling Scheme for 2003 General Social Survey of China 1. Sampling Unit This survey uses a five-stage stratified sampling scheme with unequal probabilities. The sampling units at each stage are as follows: The first stage: the primary sampling units (PSUs) are districts and counties (including county-level municipality). Here districts refer to urban districts and suburban districts of prefecture-level municipalities, provincial capital cities and central-government designated municipalities [henceforth, central municipality ]. The second stage: the second stage units are townships, town seats and city sub-districts (streets). The third stage: the third stage units are neighborhood committees and villagers' committees. The forth stage: the fourth stage units are households. The fifth stage: one eligible household member is selected to be the survey respondent at this stage. 2. Sampling Frame According to national administrative district data, mainland China consists of 2,801 countyor district-level administrative units (including 22 provinces, 4 autonomous regions and 4 central municipalities. Tibet, a provincial level unit, is excluded from the sampling frame in consideration of feasibility of survey implementation.), and these county- or district-level units serve as PSUs and comprise the population. All PSUs are stratified into five major strata. The 1 st stratum: the city districts of the three central municipalities The 1 st stratum includes a total of 44 city districts in Beijing, Tianjin and Shanghai. Chongqing, another central municipality, is excluded from this stratum for the following reasons: (1) Viewed from the time of establishment, Chongqing as a municipality directly under the center government was established in However, Beijing, Tianjing and Shanghai have been the central municipalities since 1949; (2) Viewed from the rank of Human Development Index (HDI) in the nation, there is a major gap between Chongqing and other three municipalities (Beijing, Tianjin and Shanghai) (see Table 1 for details); (3) Viewed from the geographic location in the country, Chongqing locates in the inland, and other three municipalities (Beijing, Tianjin and Shanghai) locate in the costal region; (4) Viewed from the economic development levels, there is a major gap in GDP per capita between Chongqing and other three municipalities (Beijing, Tianjin and Shanghai) (see Table 1 for details); (5) Viewed from the ratio of non-agricultural population to agricultural population, there is a 1

2 major gap between Chongqing and other three municipalities (Beijing, Tianjin and Shanghai) (see Table 1 for details). Table 1. Some socio-economic indicators, Chongqing and other three municipalities (Beijing, Tianjin and Shanghai) Indicator Beijing Tianjin Shanghai Chongqing Human Development Index (HDI) GDP per capita (in 1,000 yuan) % of non-agricultural population 60% 56% 67% 23% In summary, Chongqing is different to other three municipalities (Beijing, Tianjin and Shanghai) in many aspects, such as cultural, economy, the ratio of non-agricultural population to agricultural population, geography, history, etc. It is necessary to distinguish Chongqing from other three municipalities in sampling. The 2 nd stratum: the city districts of provincial capital cities The 2 nd stratum includes a total of 175 city districts in 26 provincial capital cities and Chongqing. All PSUs in this stratum are stratified into three sub-strata according to the economic and geographic location in the country. The eastern region: Shenyang, Ji nan, Hangzhou, Nanjing, Fuzhou, Guangzhou The central region: Haerbin, Changchun, Shijiazhuang, Zhengzhou, Taiyuan, Hefei, Nanchang, Wuhan, Changsha, Haikou, Nanning The western region: Huhehaote, Wulumuqi, Yinchuan, Lanzhou, Xining, Kunming, Guiyang, Xi an, Chengdu, Chongqing The 3 rd stratum: the eastern region The 3 rd stratum includes a total of 611 city districts and counties in Beijing, Tianjin, Shanghai and six provinces in the eastern region, excluding urban districts of Beijing, Tianjin, Shanghai and six provincial capital cities, namely, Beijing (excludes urban districts), Tianjin (excludes urban districts), Shanghai (excludes urban districts), Liaoning (excludes urban districts of Shenyang city), Shangdong (excludes urban districts of Jinan city), Zhejiang (excludes urban districts of Hangzhou city), Jiangsu (excludes urban districts of Nanjing city), Fujian (excludes urban districts of Fuzhou city), Guangdong (excludes urban districts of Guangzhou city). The 4 th stratum: the central region The 4 th stratum includes a total of 1,136 city districts and counties in eleven provinces in the central region, excluding urban districts of eleven provincial capital cities, namely, Heilongjiang (excludes urban districts of Haerbin city), Jilin (excludes urban districts of Changchun city), Hebei (excludes urban districts of Shijiazhuang city), Henan (excludes urban districts of Zhengzhou city), Shanxi (excludes urban districts of Taiyuan city), Anhui (excludes 2

3 urban districts of Hefei city), Jiangxi (excludes urban districts of Nanchang city), Hubei (excludes urban districts of Wuhan city), Hunan (excludes urban districts of Changsha city), Hainan (excludes urban districts of Haikou city), Guangxi (excludes urban districts of Nanning city). The 5 th stratum: the western region The 5 th stratum includes a total of 835 city districts and counties in ten provinces in the western region, excluding urban districts of ten provincial capital cities, namely, Inner Mongolia (excludes urban districts of Huhehaote city), Xinjiang (excludes urban districts of Wulumuqi city), Ningxia (excludes urban districts of Yinchuan city), Gansu (excludes urban districts of Lanzhou city), Qinghai (excludes urban districts of Xining city), Yunnan (excludes urban districts of Kunming city), Guizhou (excludes urban districts of Guiyang city), Shaanxi (excludes urban districts of Xi an city), Sichuan (excludes urban districts of Chengdu city), Chongqing (excludes urban districts). 3. Total Sample Size The sample size is determined by the required total sample size for estimating a population proportion p under the simple random sampling (SRS) method. Subject to an absolute sampling error of not greater than 3% and a confidence level of 95%, an appropriate sample size is, n u p(1 p) 2 α 0 = = 2 d 1,067 where, d presents the absolute sampling error (with a value of 0.03), u α takes 1.96 when confidence level is 0.95, p(1-p) takes the maximum value of Because the survey uses a complex multi-stage sampling method, the design effect (deff) ranges between 2 and 2.5. We let deff take the value of 2 for the survey, and the sample size required is 2,000. The major factors that we consider in deciding sample size include: sampling error, survey cost, and feasibility of survey implementation. In addition, our previous experiences also require us to consider other factors, such as failures of locating eligible respondents in sampled households and no responses from some of the respondents for unknown reasons. The population is stratified into five strata, because of the need to compare among different strata, the preliminary estimate of sample size is determined as 10,000. This total sample size ensures the appropriate estimation of not only the population parameters at the national level but also the parameters of each stratum s population, making it an appropriate and acceptable sample size for the survey. 4. Sample Distribution The total sample size is 10,000, and the survey uses a five-stage sampling scheme. Each PSU (city district/rural county) selects 4 city sub-districts/townships/town seats; each city sub-district/township/town seat selects 2 neighborhood committee/villagers' committee; each sampled neighborhood committee/villagers' committee selects 10 households; and one person is 3

4 selected from each sampled household. The 1 st stratum (the city districts of the three central municipalities) totally samples 15 PSUs with 5 PSUs in each municipality; The 2 nd stratum (the city districts of provincial capital cities) totally samples 16 PSUs, and the 16 city districts are to be selected according to the PPS sampling method based on the urban area population, resulting in 5 PSUs in eastern provincial capital cities, 6 PSUs in central provincial capital cities, and 5 PSUs in western provincial capital cities; A total of 94 PSUs are samples from the 3 rd, the 4 th and the 5 th stratum. According to the PPS sampling method based on the total population excluding that in the 1 st and the 2 nd stratum, 30 PSUs are to be selected from the 3 rd stratum, 42 PSUs from the 4 th stratum, and 22 PSUs from the 5 th stratum. See Table 2 for details of designed distribution of samples Table 2. Designed distribution of samples Stratum PSU City district (rural county) SSU City sub-district (township, town seat) TSU Neighborhood committee (villagers' committee) USU Household (household member) The 1 st stratum ,200 Beijing 5 5 4= = =400 Tianjin 5 5 4= = =400 Shanghai 5 5 4= = =400 The 2 nd stratum ,280 Eastern 5 5 4= = =400 Central 6 6 4= = =480 Western 5 5 4= = =400 The 3 rd stratum = = =2,320 The 4 th stratum = = =3,360 The 5 th stratum = = =1,760 Total ,000 10, Sampling Procedure 5.1 The first stage: selection of PSUs (city districts/rural counties) Selection of PSUs in the 1 st stratum Each central municipality selects 5 PSUs according to the SRS sampling method, resulting in a total of15 PSUs Selection of PSUs in the 2 nd stratum Provincial capital cities are stratified into the three strata of the coastal, central, and western regions, allocated a total of 16 city districts to all these three strata. Within each stratum, PSUs are ranked by percent middle-school education, and 16 city districts are to be selected according to the PPS systematic sampling method based on the urban area population Selection of PSUs in the 3 rd stratum In the survey design, the total numbers of urban and rural household samples will be determined by an urban-rural ratio of 6,000:4,000. Each PSU in the 1 st and 2 nd stratum selects 4 4

5 city sub-districts as the SSU, and the corresponding ultimate sampling unites are urban samples. To allow for comparisons between rural and urban areas, the sampling scheme allocates the number of city sub-districts, townships and town seats in the 3 rd, the 4 th, and the 5 th stratum as shown in Table 3. Table 3. Scheme to allocate SSUs in the 3 rd, 4 th, and 5 th stratum SSU Stratum % of non-agricultural population # of city # of sub-districts townships % and above [22.53%, 43.37%) [14.75%, 22.53%) [11.34%, 14.75%) % and below 0 4 City districts and counties in the 3 rd stratum are stratified into the five strata as shown in Table 3. Within each stratum, PSUs are ranked by percent middle-school education, and a total of 30 PSUs are to be selected in the 3 rd stratum according to the PPS systematic sampling method based on the total population. PSUs in the 4 th and the 5 th stratum are to be sampled by following the same procedure in the 3 rd stratum. For a total of 376 SSUs in the 3 rd, the 4 th and the 5 th stratum, the ratio of city sub-districts to townships and town seats is 176:200, and the numbers of urban and rural household samples will be determined by an urban-rural ratio of 3,520:4,000 (i.e. [ ]:[ ]). 5.2 The second stage: sampling city sub-districts (townships or town seats) within a city district (rural county) We select SSUs by following the below steps based on population size reported from the 2000 national census Sampling city sub-districts (1) In each sampled county-level unit, compute the number of persons aged in all neighborhood committees for each sub-district level unit, and give a random number to each sub-district level unit with any neighborhood committee population. (2) Rank sub-district level units by the given random numbers in ascending order; (3) Choose k sub-districts according to the PPS systematic sampling method (here, k is the number of city sub-districts assigned for each PSU listed in Table 4. If the population size for a specific city sub-district is huge, this city sub-district may be chosen for more than once). Do this by: 1) Listing all city sub-districts and townships with any neighborhood committee population, together with the size of neighborhood committee population. 2) Cumulating the distribution of neighborhood committee population size of the city sub-districts and townships to produce an array that cumulates to the total 5

6 neighborhood committee population of the PSU. For example, suppose we had a city district (county) of 10 city sub-districts and townships, with neighborhood committee population of 50, 150, 90, 70, 180, 110, 40, 60, 120, and 130, for a total of 1,000. We would list them as follows: city sub-district 1:1-50 city sub-district 2: city sub-district 3: city sub-district 4: city sub-district 5: city sub-district 6: city sub-district 7: city sub-district 8: city sub-district 9: city sub-district 10: ) Suppose k, the number of city sub-districts assigned for this PSU listed in Table 4, is 2. Draw two city sub-districts by (1) choosing a random number between 1 and N/2, where N is the cumulative neighborhood committee population size in the city district (in our example, N=1,000) and picking the city sub-district that contains the randomly chosen number; (2) choosing a second city sub-district by adding N/2 to the first random number and picking the city sub-district that contains this number. For example, suppose the first random number in this example is 222. Since 222 falls in the range corresponding to city sub-district 3, this sub-district is picked. Then pick the city sub-district (city sub-district 8) corresponding to = Sampling townships or town seats (1) In each sampled county-level unit, compute the number of persons aged in all villagers committees for each township level unit, and give a random number to each township level unit with any villagers committee population. (2) Rank sub-district level units by the given random numbers in ascending order; (3) Choose k sub-districts according to the PPS systematic sampling method (here, k is the number of townships assigned for each PSU listed in Table 4. If the population size for a specific township is huge, this township may be chosen for more than once). Do this by: 1) Listing all townships with any villagers committee population, together with the size of villagers committee population. 2) Cumulating the distribution of villagers committee population size of the townships to produce an array that cumulates to the total villagers committee population of the PSU. For example, suppose we had a county of 10 townships, with villagers committee population of 50, 150, 90, 70, 180, 110, 40, 60, 120, and 130, for a total of 1,000. We would list them as follows: township 1:1-50 township 2:

7 township 3: township 4: township 5: township 6: township 7: township 8: township 9: township 10: ) Suppose k, the number of townships assigned for this PSU listed in Table 4, is 2. Draw two townships by (1) choosing a random number between 1 and N/2, where N is the cumulative villagers committee population size in the city district (in our example, N=1,000) and picking the township that contains the randomly chosen number; (2) choosing a second township by adding N/2 to the first random number and picking the township that contains this number. For example, suppose the first random number in this example is 222. Since 222 falls in the range corresponding to township 3, this sub-district is picked. Then pick the township (township 8) corresponding to = The third stage: sampling neighborhood committees (villagers' committees) within a city sub-district (township or town seat) The sample of neighborhood committees and villagers' committees is also obtained by using the PPS sampling method, and the detailed procedure is similar to that used to sample city sub-districts (townships or town seats): The first step is to obtain the size of the residential population aged of each neighborhood committee or villagers' committee and the calculate the total population T. The next step is to divide the total population T by the desired number of neighborhood committees and villagers' committees to be sampled (uniformly equaling to 2 in this design) to obtain the sampling interval K = T/2 (the integer part only). The third step is to get a random number R between 1 and K, and use this number to identify a corresponding first neighborhood committee/villagers' committee to be sampled from the list of units by using information about the cumulative population size. The fourth and final step is to select samples for every R interval until exhausting the list of units to be selected. 5.4 The fourth and fifth stage: sampling households within a neighborhood committee (villagers' committee) Because the difference in household size is rather insignificant, for simplicity an equal probability systematic sampling method with a random start (equal interval sampling) is used to sample households within a neighborhood committee/villagers' committee. To ensure that each eligible household member has the same probability of being selected in a household, the survey uses Kish method to select one eligible household member aged and live in this household within this week to be the respondent. See Appendix 6 Explanation of sampling households and 7

8 selection of household member for the detailed procedure. In summary, the sampling scheme results in a total of 125 PSUs (city districts and counties), 500 SSUs with an ratio of city sub-districts to townships being 295:205, and 1,000 TSUs with an ratio of neighborhood committees to villagers committees being 590:410. Finally, the numbers of urban and rural household samples will be determined by an urban-rural ratio of 5900:4100, which meets the requirements of comparisons between rural and urban areas. 8