台灣
2013 Manpower Utilization Survey
Study Documentation
February 24, 2017
Metadata Production
Metadata Producer(s) Survey Research Data Archive, Center for Survey Research, RCHSS, Academia Sinica (SRDA) Production Date February 20, 2014
Identification AA020036en
Table of Contents
Overview... 4
Scope & Coverage... 4
Producers & Sponsors...4
Sampling...4
Data Collection...5
Data Processing & Appraisal...5
Accessibility... 5
Files Description... 6
mu2013... 6
Variables Group(s)... 7
ID...7
Part I: Manpower... 7
PartⅡ: Manpower Utilization...9
weight... 14
Variables Description...15
mu2013... 16
2013 Manpower Utilization Survey
2013 Manpower Utilization Survey
Overview
Type Manpower Utilization Survey
Identification AA020036en
Version Production Date: 2014-10-20 v2
Abstract
The survey has been conducted every year since 1978 with an aim to gain understanding of manpower utilization in Taiwan Area, with results of the survey to enrich the data required by manpower research. The survey was done concomitantly with the Manpower Survey (originally called the Labor Force Survey) in May . In terms of contents, the survey this time was mostly the same as those in the preceding years. All civilian population aged 15 years and over,
currently registering in ordinary household or institutional households, undertaking economic activities are included but those in military services or in prison are excluded. There are about 20,000 households( near 60,000 persons aged 15 and above) in these sampled households.
The Manpower Survey, used as a base, was supplemented with following data: (1) labor participation by married women; (2)income ,number of hours per week usually worked, duration of the present job, way to obtain the present job, and changing job of an employed person; (3) job opportunities and desired wage of a jobless person; and (4)supply of potential labor. Through face-to-face interviews, the sampled households are surveyed by well-trained interviewers who are recruited and assigned by local governments.
Kind of Data 抽樣調查資料 (Sample survey data)
Scope & Coverage
Countries 台灣
Geographic Coverage Taiwan
Universe
The geographic scope of this survey covers Taiwan Province and 5 municipalities (Taipei City, New Taipei City, Taichung City, Tainan City and Kaohsiung City). All civilian population aged 15 years and over, currently living in ordinary household or institutional households, undertaking economic activities are included but those in military services or in prison are excluded.
Producers & Sponsors
Other Producer(s) Directorate-General of Budget, Accounting and Statistics, Executive Yuan, R.O.C.(Taiwan)
Sampling
Sampling Procedure (1)Sample design:
(a)Sample frames: the recent 1 year's TSUN/LIs household registration data file sorted by other register data.
(b)A two-stage stratified sampling is schemed to sample households for this survey : sample units drawn in the first stage of sampling are TSUN/LIs , while those drawn in the second stage are households.
(c) For first stage sampling, one must sort out with household registration data, the descriptive statistics of TSUN/LIs and then stratify TSUN/LIs according to the type of industrial structure,age and the level of education attainment. Each of 20 counties/cities in Taiwan Area is a single subpopulation for the stratification mentioned above.
(d) In the second stage, households are sampled inside TSUN/LIs drawn in the first stage conducted above.
- 5 -
(2)Sample size: Approximately 500 TSUN/LIs were drawn in the first stage of sampling and about 20,300 households were than sampled in the second stage, overall sampling fraction is 2.6?. There are near 60,000 persons aged 15 and above in these sampled households.
(3)Sample drawing:DGBAS conducted the first stage sampling. All TSUN/LIs were firstly stratified according to criteria proposed and then serialized them with their households numbers. After that, a serial number was randomly selected as a start point to sample TSUN/LIs systematically with a given span. A systematic sampling method was also adopted in the second stage which was conducted by the Office of Accounting and Statistics in local governments, the results of second- stage sampling was later handed to survey interviewers who were to compile respective sample frames.
(4)sample rotation:TSUN/LIs stratified for the first stage of sampling is categorized into 4 groups named as A,B,C and D. These groups are further chopped into 8 subgroups and then sorted as two packs(A1B1C1D1) and (A2B2C2D2) when one pack shift to another each year, three TSUN/LIs are drawn from each packed subgroup so that 12 TSUN/LIs available and are rotatively assigned to surveys in given year. It takes 4 months to exercise such rotation across subgroups in each pack so that each subgroup would be rotated 3 times. Generally speaking, January, May and September would be the months for group A ( either subgroup A1 or subgroup A2 drawn); February , June and October for group B (either B1 or B2 drawn ); March, July and November for group C (either C1 or C2 drawn): April , August and December for group D(either D1 or D2 drawn).From each TSUN/LI drawn in the first stage, two sets of households are sampled in the second stage. After consecutively surveyed for two months, the set of households would be alternatively shifted to another for next two months. After surveying for one year, the packed subgroups A1B1C1and D1 would be alternatively shifted to A2B2C2D2; and vice versa next year.
(5)handing of institutional households:The population of institutional households in TSUN/LIs last year is taken as the sample frame to draw persons in there for institutional portion of this survey later on.
Data Collection
Data Collection Mode face-to-face interviews or telephone interviews
Data Processing & Appraisal
Data Editing
CSR has checked wild codes and out-of-range values, to validate and clean data.
Accessibility
Contact(s) Survey Research Data Archive, Center for Survey Research, RCHSS, Academia Sinica (SRDA) , https://srda.sinica.edu.tw/ , [email protected]
Distributor(s) Survey Research Data Archive, Center for Survey Research, RCHSS, Academia Sinica Depositor(s) Directorate-General of Budget, Accounting and Statistics, Executive Yuan, R.O.C.(Taiwan) Access Conditions
會員版(一般會員、院內會員)--申請審核通過後下載
Files Description
Dataset contains 1 file(s)
mu2013
# Cases 57235
# Variable(s) 107
- 7 -
Variables Group(s)
Dataset contains 4 group(s)
Group ID
# Name Label Type Format Valid Invalid Question
1 id Sample code discrete character-17 57235 0 -
2 area Region discrete numeric-1.0 57235 0 -
3 stage Stratum discrete numeric-1.0 57235 0 -
4 county County code discrete numeric-2.0 57235 0 -
5 town Virtual townships code continuous numeric-5.0 57235 0 -
6 id1 Household continuous numeric-3.0 57235 0 -
7 no Persons aged 15 years
or over in each sampled household
discrete numeric-2.0 57235 0 -
8 id2 Serial no. of interviewees in household
discrete numeric-2.0 57235 0 -
Group Part I: Manpower
# Name Label Type Format Valid Invalid Question
1 a0 Are questions answered by interviewees himself/herself
discrete numeric-1.0 57235 0 -
2 a1 Relationship to householder discrete numeric-2.0 57235 0 -
3 a2 Sex discrete numeric-1.0 57235 0 -
4 a3 Current age in full years continuous numeric-3.0 57235 0 -
5 a4 Marital status discrete numeric-1.0 57235 0 -
6 a5_1 Are you attending schools currently
discrete numeric-1.0 57235 0 -
7 a5_2 Educational attainment (highest)
discrete numeric-2.0 57235 0 -
8 a6 Academic or professional specialty
discrete numeric-2.0 57235 0 -
9 a7 Have you ever retired
from any public/private establishments before?
discrete numeric-1.0 57235 0 -
10 a8 What were you mainly doing during last week
discrete numeric-2.0 57235 0 -
11 a9 Were you undertaking any paid or unpaid family work last week
discrete numeric-1.0 57235 0 -
12 a10_1a How many hours did you work last weekFor the major job:full time _____hours (Go to Q11 if total hours less than 35otherwise skip to Q21)
discrete numeric-3.0 57235 0 -
13 a10_1b How many hours did you work last weekFor the major job:part time _____hours (Go to Q11 if total hours
discrete numeric-2.0 57235 0 -
# Name Label Type Format Valid Invalid Question less than 35otherwise skip to
Q21)
14 a10_2a How many hours did you work last weekFor the secondary job:full time _____hours (Go to Q11 if total hours less than 35otherwise skip to Q21)
discrete numeric-2.0 57235 0 -
15 a10_2b How many hours did you work last weekFor the secondary job:part time _____hours (Go to Q11 if total hours less than 35otherwise skip to Q21)
discrete numeric-2.0 57235 0 -
16 a11 Why did you work less than 35 hours last week
discrete numeric-2.0 57235 0 -
17 a12 Do you expect an increase of working hours
discrete numeric-1.0 57235 0 -
18 a13 Why were you absent from work last week
discrete numeric-1.0 57235 0 -
19 a14 Did you earn any pay from work last week
discrete numeric-1.0 57235 0 -
20 a15 If there is a job offer, can you take it at once
discrete numeric-1.0 57235 0 -
21 a16_1 How did you seek a job(multiple choices)
discrete numeric-1.0 57235 0 -
22 a16_2 How did you seek a job(multiple choices)
discrete numeric-1.0 57235 0 -
23 a16_3 How did you seek a job(multiple choices)
discrete numeric-1.0 57235 0 -
24 a16_4 How did you seek a job(multiple choices)
discrete numeric-1.0 57235 0 -
25 a16_5 How did you seek a job(multiple choices)
discrete numeric-1.0 57235 0 -
26 a16_6 How did you seek a job(multiple choices)
discrete numeric-1.0 57235 0 -
27 a17 Do you expect to take a full- time job (35 or more hours per week) or a part-time job?
discrete numeric-1.0 57235 0 -
28 a18 How long did you take for current job seeking or waiting for a recall to work since you were jobless ? _______weeks (go to Q19)
discrete numeric-2.0 57235 0 -
29 a19 Did you have a job before discrete numeric-1.0 57235 0 -
30 a20 What was the main reason you left the last job mentioned in Q19
discrete numeric-1.0 57235 0 -
31 a21_a1 What is the main workplace you are/were in(1)Location
discrete numeric-4.0 57235 0 -
32 a21_a2 What is the main workplace you are/were in(2)Major products or business
discrete numeric-2.0 57235 0 -
- 9 -
# Name Label Type Format Valid Invalid Question
33 a21_a3 What is the main workplace you are/were in(3)Number of employees
discrete numeric-1.0 57235 0 -
34 a21_b2 What is the secondary workplace you are/were in(2)Major products or business
discrete numeric-2.0 57235 0 -
35 a22_a What is/was your duty in the main workplace mentioned in Q21 A.Description of the major job( go to Q23)
discrete numeric-2.0 57235 0 -
36 a22_b What is/was your duty in the main workplace mentioned in Q21 B.Description of the secondary job( go to Q23)
discrete numeric-2.0 57235 0 -
37 a23_a What is/was the class of workers you are/were in for the undertaken workA.For the major job
discrete numeric-1.0 57235 0 -
38 a23_b What is/was the class of workers you are/were in for the undertaken workB.For the secondary job
discrete numeric-1.0 57235 0 -
Group PartⅡ: Manpower Utilization
# Name Label Type Format Valid Invalid Question
1 b1_a A.How much monthly
income did you earn from your major job? Monthly income: NT$______ (Unpaid family workers skip this question)
discrete numeric-6.0 57235 0 -
2 b1_b B.How much monthly
income did you earn from your major job? Type of salary payment (Employees only)
discrete numeric-1.0 57235 0 -
3 b2_a A.Do you work full-time or part-time at your main job?
discrete numeric-1.0 57235 0 -
4 b2_b B.How many hours per
week do you usually work in average? ______ Hours (go to Q3)
discrete numeric-2.0 57235 0 -
5 b2_c C. Is it a temporary or dispatched work or not?
discrete numeric-1.0 57235 0 -
6 b3 How long have you been
working at the present place? Duration of present employment: ______ Years ______ Months (If the length of working period is less than 1 year and 5 months, go to Q4; otherwise skip to Q8)
discrete character-4 57235 0 -
7 b3_y How long have you been working at the present place? Duration of present employment: ______ Years
discrete numeric-2.0 57235 0 -
# Name Label Type Format Valid Invalid Question 8 b3_m How long have you been
working at the present place? Duration of present employment: ______ Months
discrete numeric-2.0 57235 0 -
9 b4 Before working at the present place, had you ever taken a gainful job or an unpaid family work for at least three months
discrete numeric-1.0 57235 0 -
10 b5 How many times have you
changed your working places during 2012 ?
discrete numeric-1.0 57235 0 -
11 b6_a1 Where was the place you previously worked and what sort of work did you mainly do up there A.Major working site (1)Location
discrete numeric-4.0 57235 0 -
12 b6_a2 Where was the place you previously worked and what sort of work did you mainly do up there A.Major working site (2)Major product or business and company title
discrete numeric-2.0 57235 0 -
13 b6_a3 Where was the place you previously worked and what sort of work did you mainly do up there A.Major working site (3)Number of employees
discrete numeric-1.0 57235 0 -
14 b6_b Where was the place you previously worked and what sort of work did you mainly do up there B.Description of work contents, job title and branch/department
discrete numeric-2.0 57235 0 -
15 b6_c Where was the place you previously worked and what sort of work did you mainly do up there C.Is it a part-time, temporary or dispatched work
discrete numeric-1.0 57235 0 -
16 b7 Why did you leave the place where you previously worked at
discrete numeric-2.0 57235 0 -
17 b8 How did you get the present job?
discrete numeric-2.0 57235 0 -
18 b9 Do you expect to change job or add an additional job in the meantime?
discrete numeric-1.0 57235 0 -
19 b10 Have you begun to seek a job? (If single, stop here;
otherwise skip to Q19.)
discrete numeric-1.0 57235 0 -
20 b11_a What kind of job do you wish to seek? A.Your expected job title?
discrete numeric-2.0 57235 0 -
21 b11_b What kind of job do you wish to seek? B.Your expected monthly pay?
discrete numeric-6.0 57235 0 -
22 b11_c What kind of job do you wish to seek? C.Is it a part-time,
discrete numeric-1.0 57235 0 -
- 11 -
# Name Label Type Format Valid Invalid Question
temporary or dispatched work?
23 b11_d1 What kind of job do you wish to seek? D.Can you accept work shift, regular overtime or rotational leave?
(1)Cannot accept any one above
discrete numeric-1.0 57235 0 -
24 b11_d2_1 What kind of job do you wish to seek? D.Can you accept work shift, regular overtime or rotational leave? (2)Can accept (multiple choices)
discrete numeric-1.0 57235 0 -
25 b11_d2_2 What kind of job do you wish to seek? D.Can you accept work shift, regular overtime or rotational leave? (2)Can accept (multiple choices)
discrete numeric-1.0 57235 0 -
26 b11_d2_3 What kind of job do you wish to seek? D.Can you accept work shift, regular overtime or rotational leave? (2)Can accept (multiple choices)
discrete numeric-1.0 57235 0 -
27 b12_a1 Where is the location of the job you searched? A.
Location of searched job:
(1)Only limited in ______
County/City
discrete numeric-2.0 57235 0 -
28 b12_a2_1 Where is the location of the job you searched? A.
Location of searched job:
(2)Not limited in one County/
City, including area below (multiple choices)
discrete numeric-1.0 57235 0 -
29 b12_a2_2 Where is the location of the job you searched? A.
Location of searched job:
(2)Not limited in one County/
City, including area below (multiple choices)
discrete numeric-1.0 57235 0 -
30 b12_a2_3 Where is the location of the job you searched? A.
Location of searched job:
(2)Not limited in one County/
City, including area below (multiple choices)
discrete numeric-1.0 57235 0 -
31 b12_a2_4 Where is the location of the job you searched? A.
Location of searched job:
(2)Not limited in one County/
City, including area below (multiple choices)
discrete numeric-1.0 57235 0 -
32 b12_a2_5 Where is the location of the job you searched? A.
Location of searched job:
(2)Not limited in one County/
City, including area below (multiple choices)
discrete numeric-1.0 57235 0 -
33 b12_a2_6 Where is the location of the job you searched? A.
Location of searched job:
discrete numeric-1.0 57235 0 -
# Name Label Type Format Valid Invalid Question (2)Not limited in one County/
City, including area below (multiple choices) 34 b12_a2_7 Where is the location of
the job you searched? A.
Location of searched job:
(2)Not limited in one County/
City, including area below (multiple choices)
discrete numeric-1.0 57235 0 -
35 b12_b Where is the location of the job you searched? B.
Have you ever applied for manufacturing or construction fundamental work?
discrete numeric-1.0 57235 0 -
36 b13_a1 Did you have any job opportunity in seeking process? A.Yes. What was the main reason that you did not go for it?
discrete numeric-1.0 57235 0 -
37 b13_a2 Did you have any job opportunity in seeking process? A.Yes. What was the secondary reason that you did not go for it?
discrete numeric-1.0 57235 0 -
38 b13_a3 Did you have any job opportunity in seeking process? A.Yes. What was the sub-secondary reason that you did not go for it?
discrete numeric-1.0 57235 0 -
39 b13_b1 Did you have any job opportunity in seeking process? B-1.No. What was the main reason that you could not find a job?
discrete numeric-1.0 57235 0 -
40 b13_b2_1 Did you have any job opportunity in seeking process? B-2.No. What was the major difficulty that you faced in job seeking process?
discrete numeric-2.0 57235 0 -
41 b13_b2_2 Did you have any job opportunity in seeking process? B-2.No. What was the secondary difficulty that you faced in job seeking process?
discrete numeric-2.0 57235 0 -
42 b13_b2_3 Did you have any job opportunity in seeking process? B-2.No. What was the sub-secondary difficulty that you faced in job seeking process?
discrete numeric-2.0 57235 0 -
43 b14 What did you depend on for living while seeking a job?
(stop, if single; otherwise, skip to Q19.)
discrete numeric-1.0 57235 0 -
44 b15_1 Were you employed more than 3 months or worked as an unpaid family worker in 2012? (1)Yes. What kind of work did you do? Job title
discrete numeric-2.0 57235 0 -
- 13 -
# Name Label Type Format Valid Invalid Question
45 b15_2 Were you employed more than 3 months or worked as an unpaid family worker in 2012?
discrete numeric-1.0 57235 0 -
46 b16 Why did you quit your job?
(Unpaid family workers skip this question)
discrete numeric-1.0 57235 0 -
47 b17 Had you sought for a job in 2012? Why did you stop seeking?
discrete numeric-1.0 57235 0 -
48 b18_a1 If the work condition (pay, working site, working hours, working environment and so on) of a job ideally meet your requirement, are you willing to work? A.Yes. Your expected job title
discrete numeric-2.0 57235 0 -
49 b18_a2 If the work condition (pay, working site, working hours, working environment and so on) of a job ideally meet your requirement, are you willing to work? A.Yes. Your expected working location
discrete numeric-4.0 57235 0 -
50 b18_a3 If the work condition (pay, working site, working hours, working environment and so on) of a job ideally meet your requirement, are you willing to work? A.Yes. Your expected monthly pay( NT$)
discrete numeric-6.0 57235 0 -
51 b18_a4 If the work condition (pay, working site, working hours, working environment and so on) of a job ideally meet your requirement, are you willing to work? A.Yes. Your expected Job type?
discrete numeric-1.0 57235 0 -
52 b18_a5 If the work condition (pay, working site, working hours, working environment and so on) of a job ideally meet your requirement, are you willing to work? A.Yes. Is it a temporaty or dispatched work?
discrete numeric-1.0 57235 0 -
53 b18_b If the work condition (pay, working site, working hours, working environment and so on) of a job ideally meet your requirement, are you willing to work? B. No. Why not willing to work?
discrete numeric-1.0 57235 0 -
54 b19_a1 How many children do you have? A. Have children:
children aged under 3 years ______persons (Male or unmarried female interviewees skip this question)
discrete numeric-1.0 57235 0 -
# Name Label Type Format Valid Invalid Question 55 b19_a2 How many children do you
have? A. Have children:
children aged 3-6 years ______persons (Male or unmarried female interviewees skip this question)
discrete numeric-1.0 57235 0 -
56 b19_a3 How many children do you have? A. Have children:
children aged 6-12 years ______persons (Male or unmarried female interviewees skip this question)
discrete numeric-1.0 57235 0 -
57 b19_a4 How many children do you have? A. Have children:
children aged 12-15 years ______persons (Male or unmarried female interviewees skip this question)
discrete numeric-1.0 57235 0 -
58 b19_a5 How many children do you have? A. Have children:
children aged 15-18 years ______persons (Male or unmarried female interviewees skip this question)
discrete numeric-1.0 57235 0 -
59 b19_a6 How many children do you have? A. Have children:
children aged over 18 years ______persons (Male or unmarried female interviewees skip this question)
discrete numeric-2.0 57235 0 -
60 b19_b How many children do you have? (Male or unmarried female interviewees skip this question)
discrete numeric-1.0 57235 0 -
Group weight
# Name Label Type Format Valid Invalid Question
1 weight Weight continuous numeric-4.0 57235 0 -
- 15 -
Variables Description
Dataset contains 107 variable(s)
#
id: Sample code
Information [Type= discrete] [Format=character] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
#
area: Region
Information [Type= discrete] [Format=numeric] [Range= 0-5] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
0 Taiwan Province 28908 50.5%
1 Taipei City 5093 8.9%
2 Kaohsiung City 6080 10.6%
3 New Taipei City 6064 10.6%
4 Taichung City 5524 9.7%
5 Tainan City 5566 9.7%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
stage: Stratum
Information [Type= discrete] [Format=numeric] [Range= 1-6] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
1 17073 29.8%
2 14045 24.5%
3 14099 24.6%
4 7952 13.9%
5 2002 3.5%
6 2064 3.6%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
county: County code
Information [Type= discrete] [Format=numeric] [Range= 2-77] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
2 Yilan County 1899 3.3%
3 Taoyuan County 3558 6.2%
4 Hsinchu County 1469 2.6%
5 Miaoli County 1920 3.4%
7 Changhua County 3361 5.9%
8 Nantou County 1991 3.5%
9 Yunlin County 2375 4.1%
10 Chiayi County 1888 3.3%
13 Pingtung County 2886 5.0%
14 Taitung County 1130 2.0%
15 Hualien County 1436 2.5%
16 Penghu County 684 1.2%
17 Keelung City 1418 2.5%
18 Hsinchu City 1547 2.7%
- 17 -
#
county: County code
Value Label Cases Percentage
20 Chiayi City 1346 2.4%
63 Taipei City 5093 8.9%
64 Kaohsiung City 6080 10.6%
65 New Taipei City 6064 10.6%
66 Taichung City 5524 9.7%
67 Tainan City 5566 9.7%
75 Kinmen County and Matsu County 0
76 Mainland China (including Hong Kong and Macao) 0
77 Foreign Area 0
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
town: Virtual townships code
Information [Type= continuous] [Format=numeric] [Range= 2329-99598] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-] [Mean=54542.188 /-] [StdDev=20452.3 /-]
#
id1: Household
Information [Type= continuous] [Format=numeric] [Range= 1-502] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-] [Mean=22.891 /-] [StdDev=16.223 /-]
#
no: Persons aged 15 years or over in each sampled household
Information [Type= discrete] [Format=numeric] [Range= 1-14] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
1 4111 7.2%
2 12484 21.8%
3 12174 21.3%
4 14100 24.6%
5 8525 14.9%
6 3648 6.4%
7 1379 2.4%
8 512 0.9%
9 117 0.2%
10 90 0.2%
11 44 0.1%
12 24 0.0%
13 13 0.0%
14 14 0.0%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
id2: Serial no. of interviewees in household
Information [Type= discrete] [Format=numeric] [Range= 1-14] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
1 20540 35.9%
2 16429 28.7%
#
id2: Serial no. of interviewees in household
Value Label Cases Percentage
3 10187 17.8%
4 6129 10.7%
5 2604 4.5%
6 899 1.6%
7 291 0.5%
8 94 0.2%
9 30 0.1%
10 17 0.0%
11 8 0.0%
12 4 0.0%
13 2 0.0%
14 1 0.0%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a0: Are questions answered by interviewees himself/herself
Information [Type= discrete] [Format=numeric] [Range= 1-3] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
1 Yes, by himself/herself 21435 37.5%
2 Equivalent 35779 62.5%
3 No, proxy 21 0.0%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a1: Relationship to householder
Information [Type= discrete] [Format=numeric] [Range= 1-14] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
1 Householder 20540 35.9%
2 Spouse 11850 20.7%
3 Child 16908 29.5%
4 Grandchild 1973 3.4%
5 Parent 2006 3.5%
6 Grandparent 50 0.1%
7 Brother/Sister 996 1.7%
8 Child's spouse 2229 3.9%
9 Grandchild’s spouse 54 0.1%
10 Brother's/Sister's spouse 120 0.2%
11 Spouse's parent 140 0.2%
12 Spouse's brother/sister 37 0.1%
13 Other relatives 314 0.5%
14 Others 18 0.0%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a2: Sex
Information [Type= discrete] [Format=numeric] [Range= 1-2] [Missing=*]
- 19 -
#
a2: Sex
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
1 Male 28536 49.9%
2 Female 28699 50.1%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a3: Current age in full years
Information [Type= continuous] [Format=numeric] [Range= 15-102] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-] [Mean=46.727 /-] [StdDev=18.838 /-]
#
a4: Marital status
Information [Type= discrete] [Format=numeric] [Range= 1-4] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
1 Never married 18107 31.6%
2 Married and cohabited 31715 55.4%
3 Divorced or separated 2558 4.5%
4 Widowed 4855 8.5%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a5_1: Are you attending schools currently
Information [Type= discrete] [Format=numeric] [Range= 1-4] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
1 Yes (go to Q5-2) 6404 11.2%
2 No, had been graduated (go to Q5-2) 44748 78.2%
3 No, had been suspended (go to Q5-2) 2534 4.4%
4 No, never attended any school that is (was) approved by the 3549 6.2%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a5_2: Educational attainment (highest)
Information [Type= discrete] [Format=numeric] [Range= 1-10] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
1 Illiterate (skip to Q7) 2877 5.0%
2 Self-educated (skip to Q7) 672 1.2%
3 Primary school (skip to Q7) 9575 16.7%
4 Junior high school (skip to Q7) 8342 14.6%
5 Senior high school (skip to Q7) 6235 10.9%
6 Vocational school (go to Q6) 10879 19.0%
7 Junior college (go to Q6) 5232 9.1%
8 University (go to Q6) 11183 19.5%
9 Master's (go to Q6) 2023 3.5%
10 Ph. D's (go to Q6) 217 0.4%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a6: Academic or professional specialty
Information [Type= discrete] [Format=numeric] [Range= 0-13] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
0 Skip or N/A 27701 48.4%
1 Literature (go to Q7) 1456 2.5%
2 Law (go to Q7) 272 0.5%
3 Business , management, Journalism and Information (go to Q7) 10783 18.8%
4 Science (go to Q7) 664 1.2%
5 Engineering (go to Q7) 9719 17.0%
6 Agriculture (go to Q7) 754 1.3%
7 Medical (go to Q7) 1549 2.7%
8 Military and police (go to Q7) 557 1.0%
9 Education (go to Q7) 778 1.4%
10 Personal services (go to Q7) 1790 3.1%
11 Arts and design (go to Q7) 721 1.3%
12 Social Sciences and services (go to Q7) 461 0.8%
13 Others (go to Q7) 30 0.1%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a7: Have you ever retired from any public/private establishments before?
Information [Type= discrete] [Format=numeric] [Range= 1-2] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
1 Yes (go to Q8) 3652 6.4%
2 No (go to Q8) 53583 93.6%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a8: What were you mainly doing during last week
Information [Type= discrete] [Format=numeric] [Range= 1-13] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
1 Undertaking some kind of work (skip to Q10) 28350 49.5%
2 Undertaking works after school hours (skip to Q10) 197 0.3%
3 Undertaking works after housekeeping hours(skip to Q10) 145 0.3%
4 Having a job but not at work (skip to Q13) 181 0.3%
5 jobless and seeking work or waiting for an offer after job s 897 1.6%
6 Intending and being able to work but not seeking (skip to MU 271 0.5%
7 Attending schools or rebrushing to take entrance exams (go t 6056 10.6%
8 Housekeeping (go to Q9) 6797 11.9%
9 Elderly (aged 65 and over) or disable persons (go to Q9) 10433 18.2%
10 Idleness (go to Q9) 2272 4.0%
11 Wound or illness (go to Q9) 730 1.3%
12 In armed force, prison or missing (stop) 810 1.4%
13 Others (go to Q9) 96 0.2%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
- 21 -
#
a9: Were you undertaking any paid or unpaid family work last week
Information [Type= discrete] [Format=numeric] [Range= 0-4] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
0 Skip or N/A 30846 53.9%
1 Undertaking work after school or housekeeping hours (go to Q 0
2 Undertaking some kind of work (go to Q10) 4 0.0%
3 Having a job but not at work (skip to Q13) 1 0.0%
4 Not undertaking any job (skip to MU Q19, if elderly or disab 26384 46.1%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a10_1a: How many hours did you work last weekFor the major job:full time _____hours (Go to Q11 if total hours less than 35otherwise skip to Q21)
Information [Type= discrete] [Format=numeric] [Range= 0-120] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
0 Skip or N/A 29316 51.2%
4 7 0.0%
7 1 0.0%
8 26 0.0%
9 1 0.0%
10 9 0.0%
12 9 0.0%
14 3 0.0%
15 11 0.0%
16 87 0.2%
18 8 0.0%
20 96 0.2%
21 19 0.0%
22 4 0.0%
23 1 0.0%
24 249 0.4%
25 37 0.1%
26 7 0.0%
27 5 0.0%
28 38 0.1%
30 175 0.3%
32 195 0.3%
33 2 0.0%
35 837 1.5%
36 424 0.7%
37 22 0.0%
38 111 0.2%
39 22 0.0%
40 11671 20.4%
#
a10_1a: How many hours did you work last weekFor the major job:full time _____hours (Go to Q11 if total hours less than 35otherwise skip to Q21)
Value Label Cases Percentage
41 37 0.1%
42 724 1.3%
43 140 0.2%
44 796 1.4%
45 958 1.7%
46 228 0.4%
47 26 0.0%
48 6019 10.5%
49 90 0.2%
50 1469 2.6%
51 30 0.1%
52 289 0.5%
53 16 0.0%
54 375 0.7%
55 225 0.4%
56 763 1.3%
57 9 0.0%
58 58 0.1%
59 20 0.0%
60 983 1.7%
62 15 0.0%
63 48 0.1%
64 24 0.0%
65 32 0.1%
66 29 0.1%
67 2 0.0%
68 5 0.0%
69 1 0.0%
70 198 0.3%
72 153 0.3%
74 3 0.0%
75 4 0.0%
76 1 0.0%
77 10 0.0%
78 3 0.0%
80 4 0.0%
82 1 0.0%
84 36 0.1%
90 5 0.0%
91 4 0.0%
96 1 0.0%
98 6 0.0%
105 1 0.0%
- 23 -
#
a10_1a: How many hours did you work last weekFor the major job:full time _____hours (Go to Q11 if total hours less than 35otherwise skip to Q21)
Value Label Cases Percentage
120 1 0.0%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a10_1b: How many hours did you work last weekFor the major job:part time _____hours (Go to Q11 if total hours less than 35otherwise skip to Q21)
Information [Type= discrete] [Format=numeric] [Range= 0-48] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
0 Skip or N/A 56462 98.6%
2 2 0.0%
3 2 0.0%
4 9 0.0%
5 4 0.0%
6 6 0.0%
7 1 0.0%
8 40 0.1%
9 4 0.0%
10 34 0.1%
11 1 0.0%
12 23 0.0%
13 1 0.0%
14 8 0.0%
15 41 0.1%
16 78 0.1%
17 3 0.0%
18 19 0.0%
20 130 0.2%
21 14 0.0%
22 3 0.0%
23 3 0.0%
24 112 0.2%
25 32 0.1%
26 2 0.0%
28 33 0.1%
30 114 0.2%
32 9 0.0%
35 36 0.1%
36 3 0.0%
38 1 0.0%
40 4 0.0%
48 1 0.0%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a10_2a: How many hours did you work last weekFor the secondary job:full time _____hours (Go to Q11 if total hours less than 35otherwise skip to Q21)
Information [Type= discrete] [Format=numeric] [Range= 0-35] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
0 Skip or N/A 57198 99.9%
6 1 0.0%
8 1 0.0%
10 5 0.0%
12 5 0.0%
15 2 0.0%
16 6 0.0%
20 14 0.0%
25 1 0.0%
30 1 0.0%
35 1 0.0%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a10_2b: How many hours did you work last weekFor the secondary job:part time _____hours (Go to Q11 if total hours less than 35otherwise skip to Q21)
Information [Type= discrete] [Format=numeric] [Range= 0-25] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
0 Skip or N/A 57107 99.8%
3 1 0.0%
4 4 0.0%
5 4 0.0%
6 4 0.0%
7 1 0.0%
8 17 0.0%
9 1 0.0%
10 16 0.0%
12 17 0.0%
14 1 0.0%
15 13 0.0%
16 14 0.0%
18 4 0.0%
20 22 0.0%
21 2 0.0%
22 1 0.0%
24 2 0.0%
25 4 0.0%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a11: Why did you work less than 35 hours last week
Information [Type= discrete] [Format=numeric] [Range= 0-12] [Missing=*]
- 25 -
#
a11: Why did you work less than 35 hours last week
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
0 Skip or N/A 55564 97.1%
1 Unfavorable conditions of business (go to Q12) 419 0.7%
2 Unable to find a job which should work more than 35 hours pe 97 0.2%
3 Seasonal reasons (go to Q12) 135 0.2%
4 Bad weather or natural calamities (go to Q12) 300 0.5%
5 Work itself only need to work less than 35 hours per week (g 337 0.6%
6 Take care of children (skip to Q21) 36 0.1%
7 Take care of elders (skip to Q21) 12 0.0%
8 Busy in housekeeping (skip to Q21) 50 0.1%
9 Busy in studying/attending school (skip to Q21) 147 0.3%
10 Wound or illness, official holidays, personal leaves or spec 65 0.1%
11 Unwilling to work longer (skip to Q21) 57 0.1%
12 Others (go to Q12) 16 0.0%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a12: Do you expect an increase of working hours
Information [Type= discrete] [Format=numeric] [Range= 0-2] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
0 Skip or N/A 55931 97.7%
1 Yes (skip to Q21) 950 1.7%
2 No (skip to Q21) 354 0.6%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a13: Why were you absent from work last week
Information [Type= discrete] [Format=numeric] [Range= 0-7] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
0 Skip or N/A 57054 99.7%
1 Wound of illness (skip to Q21) 51 0.1%
2 Seasonal reasons (skip to Q21) 21 0.0%
3 Official holidays, personal leaves or special days off (skip 48 0.1%
4 Deciding to start working in the near future but no pay curr 5 0.0%
5 Not starting to work yet for some reasons even though have e 1 0.0%
6 Waiting for a recall to work (go to Q14) 36 0.1%
7 Others (skip to Q21) 19 0.0%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a14: Did you earn any pay from work last week
Information [Type= discrete] [Format=numeric] [Range= 0-2] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
0 Skip or N/A 57199 99.9%
#
a14: Did you earn any pay from work last week
Value Label Cases Percentage
1 Yes (skip to Q21) 2 0.0%
2 No (skip to Q18) 34 0.1%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a15: If there is a job offer, can you take it at once
Information [Type= discrete] [Format=numeric] [Range= 0-8] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
0 Skip or N/A 56338 98.4%
1 Yes (go to Q16) 808 1.4%
3 No, because of attending school or rebrushing to take entran 1 0.0%
4 No, because of housekeeping (skip to MU Q15) 3 0.0%
5 No, because of old age (elders aged 65 or over) or disable p 0
6 No, because of idleness (skip to MU Q15) 0
7 No, because of wound or illness (skip to MU Q15) 3 0.0%
8 No, because of others (skip to MU Q15) 82 0.1%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a16_1: How did you seek a job(multiple choices)
Information [Type= discrete] [Format=numeric] [Range= 0-6] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
0 Skip or N/A 57235 100.0%
1 Referenced by relatives, friends or teachers (go to Q17) 0
2 Through private employment agencies (go to Q17) 0
3 Referring recruiting advertisements or posters (go to Q17) 0
4 Through public employment offices (go to Q17) 0
5 Through civil service exams and placement (go to Q17) 0
6 Others (go to Q17) 0
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a16_2: How did you seek a job(multiple choices)
Information [Type= discrete] [Format=numeric] [Range= 0-6] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
0 Skip or N/A 57235 100.0%
1 Referenced by relatives, friends or teachers (go to Q17) 0
2 Through private employment agencies (go to Q17) 0
3 Referring recruiting advertisements or posters (go to Q17) 0
4 Through public employment offices (go to Q17) 0
5 Through civil service exams and placement (go to Q17) 0
6 Others (go to Q17) 0
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
- 27 -
#
a16_3: How did you seek a job(multiple choices)
Information [Type= discrete] [Format=numeric] [Range= 0-6] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
0 Skip or N/A 57193 99.9%
1 Referenced by relatives, friends or teachers (go to Q17) 42 0.1%
2 Through private employment agencies (go to Q17) 0
3 Referring recruiting advertisements or posters (go to Q17) 0
4 Through public employment offices (go to Q17) 0
5 Through civil service exams and placement (go to Q17) 0
6 Others (go to Q17) 0
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a16_4: How did you seek a job(multiple choices)
Information [Type= discrete] [Format=numeric] [Range= 0-6] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
0 Skip or N/A 57018 99.6%
1 Referenced by relatives, friends or teachers (go to Q17) 144 0.3%
2 Through private employment agencies (go to Q17) 70 0.1%
3 Referring recruiting advertisements or posters (go to Q17) 3 0.0%
4 Through public employment offices (go to Q17) 0
5 Through civil service exams and placement (go to Q17) 0
6 Others (go to Q17) 0
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a16_5: How did you seek a job(multiple choices)
Information [Type= discrete] [Format=numeric] [Range= 0-6] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
0 Skip or N/A 56715 99.1%
1 Referenced by relatives, friends or teachers (go to Q17) 183 0.3%
2 Through private employment agencies (go to Q17) 190 0.3%
3 Referring recruiting advertisements or posters (go to Q17) 142 0.2%
4 Through public employment offices (go to Q17) 5 0.0%
5 Through civil service exams and placement (go to Q17) 0
6 Others (go to Q17) 0
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a16_6: How did you seek a job(multiple choices)
Information [Type= discrete] [Format=numeric] [Range= 0-6] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
0 Skip or N/A 56427 98.6%
1 Referenced by relatives, friends or teachers (go to Q17) 60 0.1%
2 Through private employment agencies (go to Q17) 70 0.1%
#
a16_6: How did you seek a job(multiple choices)
Value Label Cases Percentage
3 Referring recruiting advertisements or posters (go to Q17) 379 0.7%
4 Through public employment offices (go to Q17) 205 0.4%
5 Through civil service exams and placement (go to Q17) 90 0.2%
6 Others (go to Q17) 4 0.0%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a17: Do you expect to take a full-time job (35 or more hours per week) or a part-time job?
Information [Type= discrete] [Format=numeric] [Range= 0-2] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
0 Skip or N/A 56427 98.6%
1 A full-time job (go to Q18) 792 1.4%
2 A part-time job (go to Q18) 16 0.0%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a18: How long did you take for current job seeking or waiting for a recall to work since you were jobless ? _______weeks (go to Q19)
Information [Type= discrete] [Format=numeric] [Range= 0-99] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
0 Skip or N/A 56388 98.5%
1 27 0.0%
2 59 0.1%
3 39 0.1%
4 43 0.1%
5 38 0.1%
6 29 0.1%
7 12 0.0%
8 53 0.1%
9 14 0.0%
10 17 0.0%
11 2 0.0%
12 40 0.1%
13 7 0.0%
14 14 0.0%
15 7 0.0%
16 32 0.1%
17 4 0.0%
18 6 0.0%
19 5 0.0%
20 19 0.0%
21 2 0.0%
22 2 0.0%
23 5 0.0%
- 29 -
#
a18: How long did you take for current job seeking or waiting for a recall to work since you were jobless ? _______weeks (go to Q19)
Value Label Cases Percentage
24 46 0.1%
25 8 0.0%
26 8 0.0%
28 19 0.0%
29 4 0.0%
30 7 0.0%
31 2 0.0%
32 7 0.0%
33 1 0.0%
34 7 0.0%
35 1 0.0%
36 9 0.0%
39 1 0.0%
40 19 0.0%
41 1 0.0%
42 3 0.0%
43 1 0.0%
44 10 0.0%
45 3 0.0%
46 3 0.0%
47 14 0.0%
48 8 0.0%
49 3 0.0%
50 10 0.0%
51 16 0.0%
52 15 0.0%
53 12 0.0%
54 8 0.0%
55 2 0.0%
56 10 0.0%
57 5 0.0%
58 3 0.0%
59 2 0.0%
60 7 0.0%
64 3 0.0%
65 1 0.0%
67 1 0.0%
68 4 0.0%
69 1 0.0%
70 1 0.0%
72 7 0.0%
73 2 0.0%
74 2 0.0%
#
a18: How long did you take for current job seeking or waiting for a recall to work since you were jobless ? _______weeks (go to Q19)
Value Label Cases Percentage
76 5 0.0%
78 2 0.0%
80 6 0.0%
81 3 0.0%
82 1 0.0%
83 1 0.0%
86 3 0.0%
88 1 0.0%
90 1 0.0%
92 1 0.0%
94 3 0.0%
96 1 0.0%
98 1 0.0%
99 Over 99 weeks 45 0.1%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a19: Did you have a job before
Information [Type= discrete] [Format=numeric] [Range= 0-2] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
0 Skip or N/A 56388 98.5%
1 Yes (go to Q20) 677 1.2%
2 No (skip to .Q11) 170 0.3%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a20: What was the main reason you left the last job mentioned in Q19
Information [Type= discrete] [Format=numeric] [Range= 0-8] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
0 Skip or N/A 56558 98.8%
1 Business shrunk or establishment closed (go to Q21) 232 0.4%
2 Unsatisfied to that job (go to Q21) 303 0.5%
3 Ill health (go to Q21) 29 0.1%
4 Seasonal or temporary work finished (go to Q21) 77 0.1%
5 Got married or gave birth (if interviewee is female) (go to 9 0.0%
6 Retired (go to Q21) 3 0.0%
7 Busy in housekeeping (go to Q21) 5 0.0%
8 Others (go to Q21) 19 0.0%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a21_a1: What is the main workplace you are/were in(1)Location
Information [Type= discrete] [Format=numeric] [Range= 0-7700] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
- 31 -
#
a21_a1: What is the main workplace you are/were in(1)Location
Value Label Cases Percentage
0 Skip or N/A 27724 48.4%
200 Yilan County 2 0.0%
201 Yilan City, Yilan County 338 0.6%
202 Luodong Township, Yilan County 77 0.1%
203 Suao Township, Yilan County 35 0.1%
204 Toucheng Township, Yilan County 92 0.2%
205 Jiaosi Township, Yilan County 92 0.2%
206 Jhuangwei Township, Yilan County 40 0.1%
207 Yuanshan Township, Yilan County 51 0.1%
208 Dongshan Township, Yilan County 30 0.1%
209 Wujie Township, Yilan County 25 0.0%
210 Sansing Township, Yilan County 34 0.1%
211 Datong Township, Yilan County 0
212 Nanao Township, Yilan County 26 0.0%
300 Taoyuan County 4 0.0%
301 Taoyuan City, Taoyuan County 467 0.8%
302 Jhongli City, Taoyuan County 515 0.9%
303 Dasi Township, Taoyuan County 71 0.1%
304 Yangmei Township, Taoyuan County 147 0.3%
305 Lujhu Township, Taoyuan County 181 0.3%
306 Dayuan Township, Taoyuan County 121 0.2%
307 Gueishan Township, Taoyuan County 175 0.3%
308 Bade City, Taoyuan County 85 0.1%
309 Longtan Township, Taoyuan County 123 0.2%
310 Pingjhen City, Taoyuan County 110 0.2%
311 Sinwu Township, Taoyuan County 52 0.1%
312 Guanyin Township, Taoyuan County 70 0.1%
313 Fusing Township, Taoyuan County 0
400 Hsinchu County 3 0.0%
401 Jhubei City, Hsinchu County 251 0.4%
402 Jhudong Township, Hsinchu County 93 0.2%
403 Sinpu Township, Hsinchu County 52 0.1%
404 Guansi Township, Hsinchu County 16 0.0%
405 Hukou Township, Hsinchu County 159 0.3%
406 Sinfong Township, Hsinchu County 34 0.1%
407 Cyonglin Township, Hsinchu County 25 0.0%
408 Hengshan Township,Hsinchu County 2 0.0%
409 Beipu Township, Hsinchu County 0
410 Baoshan Township, Hsinchu County 33 0.1%
411 Emei Township, Hsinchu County 1 0.0%
412 Jianshih Township, Hsinchu County 0
413 Wufong Township, Hsinchu County 0
500 Miaoli County 0
#
a21_a1: What is the main workplace you are/were in(1)Location
Value Label Cases Percentage
501 Miaoli City, Miaoli County 194 0.3%
502 Yuanli Township, Miaoli County 75 0.1%
503 Tongsiao Township, Miaoli County 49 0.1%
504 Jhunan Township, Miaoli County 131 0.2%
505 Toufen Township, Miaoli County 89 0.2%
506 Houlong Township, Miaoli County 36 0.1%
507 Jhuolan Township, Miaoli County 59 0.1%
508 Dahu Township, Miaoli County 33 0.1%
509 Gongguan Township, Miaoli County 11 0.0%
510 Tongluo Township, Miaoli County 16 0.0%
511 Nanjhuang Township, Miaoli County 24 0.0%
512 Touwu Township, Miaoli County 11 0.0%
513 Sanyi Township, Miaoli County 10 0.0%
514 Sihu Township, Miaoli County 3 0.0%
515 Zaociao Township, Miaoli County 3 0.0%
516 Sanwan Township, Miaoli County 40 0.1%
517 Shihtan Township, Miaoli County 3 0.0%
518 Taian Township, Miaoli County 2 0.0%
700 Changhua County 4 0.0%
701 Changhua City, Changhua County 364 0.6%
702 Lugang Township, Changhua County 163 0.3%
703 Hemei Township, Changhua County 128 0.2%
704 Siansi Township, Changhua County 78 0.1%
705 Shengang Township, Changhua County 28 0.0%
706 Fusing Township, Changhua County 15 0.0%
707 Sioushuei Township, Changhua County 22 0.0%
708 Huatan Township, Changhua County 83 0.1%
709 Fenyuan Township, Changhua County 10 0.0%
710 Yuanlin Township, Changhua County 79 0.1%
711 Sihu Township, Changhua County 59 0.1%
712 Tianjhong Township, Changhua County 51 0.1%
713 Dacun Township, Changhua County 53 0.1%
714 Puyan Township, Changhua County 32 0.1%
715 Pusin Township, Changhua County 17 0.0%
716 Yongjing Township, Changhua County 35 0.1%
717 Shetou Township, Changhua County 30 0.1%
718 Ershuei Township, Changhua County 3 0.0%
719 Beidou Township, Changhua County 105 0.2%
720 Erlin Township, Changhua County 10 0.0%
721 Tianwei Township, Changhua County 9 0.0%
722 Beitou Township, Changhua County 47 0.1%
723 Fangyuan Township, Changhua County 24 0.0%
724 Dacheng Township, Changhua County 36 0.1%
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#
a21_a1: What is the main workplace you are/were in(1)Location
Value Label Cases Percentage
725 Jhutang Township, Changhua County 1 0.0%
726 Sijhou Township, Changhua County 36 0.1%
800 Nantou County 0
801 Nantou City, Nantou County 213 0.4%
802 Puli Township, Nantou County 166 0.3%
803 Caotun Township, Nantou County 65 0.1%
804 Jhushan Township, Nantou County 107 0.2%
805 Jiji Township, Nantou County 42 0.1%
806 Mingjian Township, Nantou County 73 0.1%
807 Lugu Township, Nantou County 7 0.0%
808 Jhongliao Township, Nantou County 3 0.0%
809 Yuchih Township, Nantou County 33 0.1%
810 Guosing Township, Nantou County 8 0.0%
811 Shueili Township, Nantou County 76 0.1%
812 Sinyi Township, Nantou County 78 0.1%
813 Renai Township, Nantou County 6 0.0%
900 Yunlin County 7 0.0%
901 Douliou City, Yunlin County 283 0.5%
902 Dounan Township, Yunlin County 118 0.2%
903 Huwei Township, Yunlin County 115 0.2%
904 Siluo Township, Yunlin County 85 0.1%
905 Tuku Township, Yunlin County 25 0.0%
906 Beigang Township, Yunlin County 54 0.1%
907 Gukeng Township, Yunlin County 21 0.0%
908 Dabi Township, Yunlin County 4 0.0%
909 Cihtong Township, Yunlin County 56 0.1%
910 Linnei Township, Yunlin County 5 0.0%
911 Erlun Township, Yunlin County 42 0.1%
912 Lunbei Township, Yunlin County 51 0.1%
913 Mailiao Township, Yunlin County 72 0.1%
914 Dongshih Township, Yunlin County 2 0.0%
915 Baojhong Township, Yunlin County 47 0.1%
916 Taisi Township, Yunlin County 1 0.0%
917 Yuanchang Township, Yunlin County 20 0.0%
918 Sihhu Township, Yunlin County 10 0.0%
919 Kouhu Township, Yunlin County 2 0.0%
920 Shueilin Township, Yunlin County 24 0.0%
1000 Chiayi County 4 0.0%
1001 Taibao City, Chiayi County 57 0.1%
1002 Puzih City, Chiayi County 63 0.1%
1003 Budai Township, Chiayi County 82 0.1%
1004 Dalin Township, Chiayi County 94 0.2%
1005 Minsyong Township, Chiayi County 139 0.2%
#
a21_a1: What is the main workplace you are/were in(1)Location
Value Label Cases Percentage
1006 Sikou Township, Chiayi County 47 0.1%
1007 Singang Township, Chiayi County 56 0.1%
1008 Liujiao Township, Chiayi County 22 0.0%
1009 Dongshih Township, Chiayi County 5 0.0%
1010 Yijhu Township, Chiayi County 10 0.0%
1011 Lucao Township, Chiayi County 4 0.0%
1012 Shueishang Township, Chiayi County 14 0.0%
1013 Jhongpu Township, Chiayi County 59 0.1%
1014 Jhuci Township, Chiayi County 27 0.0%
1015 Meishan Township, Chiayi County 23 0.0%
1016 Fanlu Township, Chiayi County 56 0.1%
1017 Dapu Township, Chiayi County 2 0.0%
1018 Alishan Township, Chiayi County 6 0.0%
1300 Pingtung County 1 0.0%
1301 Pingtung City, Pingtung County 339 0.6%
1302 Chaojhou Township, Pingtung County 118 0.2%
1303 Donggang Township, Pingtung County 43 0.1%
1304 Hengchun Township, Pingtung County 75 0.1%
1305 Wandan Township, Pingtung County 37 0.1%
1306 Changjhih Township, Pingtung County 40 0.1%
1307 Linluo Township, Pingtung County 4 0.0%
1308 Jiouru Township, Pingtung County 40 0.1%
1309 Ligang Township, Pingtung County 78 0.1%
1310 Yanpu Township, Pingtung County 32 0.1%
1311 Gaoshu Township, Pingtung County 30 0.1%
1312 Wanluan Township, Pingtung County 50 0.1%
1313 Neipu Township, Pingtung County 46 0.1%
1314 Jhutian Township, Pingtung County 24 0.0%
1315 Sinbi Township, Pingtung County 3 0.0%
1316 Fangliao Township, Pingtung County 6 0.0%
1317 Sinyuan Township, Pingtung County 37 0.1%
1318 Kanding Township, Pingtung County 31 0.1%
1319 Linbian Township, Pingtung County 9 0.0%
1320 Nanjhou Township, Pingtung County 11 0.0%
1321 Jiadong Township, Pingtung County 36 0.1%
1322 Liouciu Township, Pingtung County 1 0.0%
1323 Checheng Township, Pingtung County 16 0.0%
1324 Manjhou Township, Pingtung County 1 0.0%
1325 Fangshan Township, Pingtung County 0
1326 Sandimen Township, Pingtung County 13 0.0%
1327 Wutai Township, Pingtung County 1 0.0%
1328 Majia Township, Pingtung County 4 0.0%
1329 Taiwu Township, Pingtung County 1 0.0%
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#
a21_a1: What is the main workplace you are/were in(1)Location
Value Label Cases Percentage
1330 Laiyi Township, Pingtung County 3 0.0%
1331 Chunrih Township, Pingtung County 0
1332 Shihzih Township, Pingtung County 0
1333 Mudan Township, Pingtung County 2 0.0%
1400 Taitung County 2 0.0%
1401 Taitung City, Taitung County 312 0.5%
1402 Chenggong Township, Taitung County 19 0.0%
1403 Guanshan Township, Taitung County 14 0.0%
1404 Beinan Township, Taitung County 52 0.1%
1405 Luye Township, Taitung County 23 0.0%
1406 Chishang Township, Taitung County 3 0.0%
1407 Donghe Township, Taitung County 2 0.0%
1408 Changbin Township, Taitung County 1 0.0%
1409 Taimali Township, Taitung County 21 0.0%
1410 Dawu Township, Taitung County 2 0.0%
1411 Lyudao Township, Taitung County 0
1412 Haiduan Township, Taitung County 11 0.0%
1413 Yanping Township, Taitung County 9 0.0%
1414 Jinfong Township, Taitung County 0
1415 Daren Township, Taitung County 0
1416 Lanyu Township, Taitung County 0
1500 Hualien County 2 0.0%
1501 Hualien City, Hualien County 234 0.4%
1502 Fonglin Township, Hualien County 29 0.1%
1503 Yuli Township, Hualien County 79 0.1%
1504 Sincheng Township, Hualien County 65 0.1%
1505 Jian Township, Hualien County 31 0.1%
1506 Shoufong Township, Hualien County 32 0.1%
1507 Guangfu Township, Hualien County 12 0.0%
1508 Fongbin Township, Hualien County 3 0.0%
1509 Rueisui Township, Hualien County 13 0.0%
1510 Fuli Township, Hualien County 22 0.0%
1511 Sioulin Township, Hualien County 22 0.0%
1512 Wanrong Township, Hualien County 1 0.0%
1513 Jhuosi Township, Hualien County 10 0.0%
1600 Penghu County 8 0.0%
1601 Magong City, Penghu County 194 0.3%
1602 Husi Township, Penghu County 13 0.0%
1603 Baisha Township, Penghu County 13 0.0%
1604 Siyu Township, Penghu County 18 0.0%
1605 Wangan Township, Penghu County 0
1606 Cimei Township, Penghu County 0
1700 Keelung City 425 0.7%
#
a21_a1: What is the main workplace you are/were in(1)Location
Value Label Cases Percentage
1701 Jhongjheng Dist., Keelung City 0
1702 Cidu Dist., Keelung City 0
1703 Nuannuan Dist., Keelung City 0
1704 Renai Dist., Keelung City 0
1705 Jhongshan Dist., Keelung City 0
1706 Anle Dist., Keelung City 0
1707 Sinyi Dist., Keelung City 0
1800 Hsinchu City 1124 2.0%
1801 East Dist., Hsinchu City 0
1802 North Dist., Hsinchu City 0
1803 Siangshan Dist., Hsinchu City 0
2000 Chiayi City 623 1.1%
2001 East Dist., Chiayi City 0
2002 West Dist., Chiayi City 0
6300 Taipei City 3838 6.7%
6400 Kaohsiung City 3144 5.5%
6500 New Taipei City 2900 5.1%
6600 Taichung City 3373 5.9%
6700 Tainan City 2921 5.1%
7500 Kinmen County and Matsu County 5 0.0%
7600 Mainland China (including Hong Kong and Macao) 86 0.2%
7700 Foreign Area 34 0.1%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
#
a21_a2: What is the main workplace you are/were in(2)Major products or business
Information [Type= discrete] [Format=numeric] [Range= 0-96] [Missing=*]
Statistics [NW/ W] [Valid=57235 /-] [Invalid=0 /-]
Value Label Cases Percentage
0 Skip or N/A 27724 48.4%
1 Agriculture and Animal Husbandry 2039 3.6%
2 Forestry 17 0.0%
3 Fishing 142 0.2%
5 Extraction of Crude Petroleum and Natural Gas 5 0.0%
6 Quarrying of Stone, Sand and Clay 30 0.1%
7 Other Mining and Quarrying 0
8 Manufacture of Food Products 467 0.8%
9 Manufacture of Beverages 52 0.1%
10 Manufacture of Tobacco Products 1 0.0%
11 Manufacture of Textiles 268 0.5%
12 Manufacture of Wearing Apparel and Clothing Accessories 213 0.4%
13 Manufacture of Leather, Fur and Related Products 139 0.2%
14 Manufacture of Wood and of Products of Wood and Bamboo 89 0.2%
15 Manufacture of Paper and Paper Products 165 0.3%
16 Printing and Reproduction of Recorded Media 152 0.3%