THA_1994_SES_v01_M
Household Socio-Economic Survey 1994
Name | Country code |
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Thailand | THA |
Socio-Economic/Monitoring Survey [hh/sems]
The National Statistical Office (NSO) first conducted the household Expenditure Survey in 1957. Comparable survey known as "The Socio-Economic Survey" was varied out in 1968 - 1969 and was repeated every five years. In 1986, due to the rapid economic expansion and the importance of the survey in order to set the anti-poverty policy, the Ministerial Cabinet passed an approval on September 8, 1987 for the NSO to carry out the survey for every two years. The 1994 survey is the twelfth survey of this kind.
The primary objective is to collect information on household income and consumption expenditures, changes in assets and liabilities, housing characteristics as well as the ownership of some durable goods.
The survey provides information relevant in setting up the anti-poverty policy of the country. Its primary objective is to collect information on household income and consumption expenditures, changes in assets and liabilities, housing characteristics as well as the ownership of some durable goods.
Sample survey data [ssd]
Household, Individual
The scope of the 1994 SES includes household income and consumption expenditures, changes in assets and liabilities, housing characteristics, and ownership of some durable goods.
National
block/village
The survey covered all private, non-institutional households residing permanently in municipal areas, sanitary districts and villages. Excluded from the survey are population living in transient hotels and rooming houses, boarding schools, military barracks, wats, hospitals, prisons and other such institutions, as well as households of foreign diplomats and other temporary residents.
Name |
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National Statistical Office |
Sample Design
A stratified two-stage sampling was adopted for the survey. Provinces in all regions were constituted strata and types of local administration in each province were sub-strata. The primary and secondary sampling units were blocks for municipal areas/villages for non-municipal areas and private households respectively.
Stratification
There were altogether 76 strata (provinces). Each stratum was divided into three parts according to type of local administration, namely, Municipal Areas, Sanitary Districts and Non-municipal Areas - outside sanitary districts.
Selection of Primary Sampling Unit
In each type of local administration, the sample selection of blocks/villages was performed separately and independently in each part by using probability proportional to size (the total number of households). The total sample blocks/villages was 3,359 from 79,835 blocks/villages.
Selection of Secondary Sampling Unit
Private households are our ultimate sampling units. A new listing of households was made for every sample block/village to serve as the sampling frame. A systematic sample of 15 private households was selected from each of the sample blocks, while 9 and 7 private households were selected from each of the sample villages in sanitary districts and non-municipal areas - outside sanitary districts respectively. Before selecting sample households, the list of households was rearranged by household's size, i.e. the member of the household and type of economic household.
The total number of sample private households selected for enumeration by region and type of local administration was 31,143.
Sample weights for the household data were computed as the inverse of the probability of selection of the household. The weight variable for households is a26, found in the data file r1 - Household characteristics, household head.
Two questionnaires were used:
Start | End |
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1994-02-01 | 1995-01-01 |
Name | Affiliation |
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Interviewwes from the NSO Central Office | National Statistical Office |
Provincial Branch Offices | National Statistical Office |
Supervisors were expected to assist interviewers if problems occurred. Members of the Central Office Staff conducted periodic visits to the field to review questionable reports and clarify data collection procedures.
Data Collection Method
The survey data were collected by interviewing method. The interviewers from the NSO provincial branch offices were sent out to interview the heads of the sample households or other household members. The information obtained was recorded on the questionnaire forms.
Collection Period
All sample households were divided into 12 equally representative sub-samples, and each sub-sample household group was interviewed for a one month period. All households residing in sample blocks and villages were listed one or two weeks before the scheduled interview period in order to avoid a great time lapse between sample selection and interview.
Data Reference Period
During the first two weeks of the interview month, questions were asked about household composition, income of household members, housing facilities, saving and debts, and expenditures for goods and services as well. Various reference periods were used for collecting income and expenditure data. Data for all goods and services were obtained for the preceding month. In addition, for items usually purchased infrequently and also for sources of income, data were obtained for the past 12 months.
Limitations of the Data
Generally, income and expenditure data are under-reported in household sample surveys. Income data are under reported more than expenditures. The extent of under-reporting varies for income from different sources. For example, wage and salary earnings are probably much more accurately reported than profits from business. Households are likely to forget to report some expenditures made during the reference period of the survey and household members may be reluctant to report certain types of purchases, for example, alcoholic drinks, cigarettes and entertainment costs.
Non-money income was imputed by respondent. Commodities produced individually and consumed by household and goods received free were valued at the local current retail prices. The rental value of owner-occupied home was the value that would have been received per month has the house been rented out to other households.
Stages at which data editing took place:
a) In the field:
Descriptive information was coded numerically for computer processing. All annual expenditure and income values were converted to a one-month base by dividing annual values by 12. For 7-day food consumption, values were multiplied by 4.3 which was the average number of weeks per month (52 weeks/12 months = 4.3 weeks/month). Income from farm or non-farm enterprises was calculated on the basis of total annual value of production less operating expenses. From this estimate, the value of products held or withdrawn for household consumption was subtracted to arrive at an estimate of money income.
Formulas for coefficient of variations (CV) for totals and averages for characteristics (Y) of households is presented in Chapter 2 of the Report of the 1994 Household Socio-Economic Survey.
Name |
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National Statistical Office |
Is signing of a confidentiality declaration required? | Confidentiality declaration text |
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yes | Section 16 of The Statistics ACT B.E. 2550 (2007), 30 August, B.E. 2550 guarantees that "anyone performing duties in an agency or the National Satistics Office shall not use the personal information provided by the owner or given in the questionnaire for any purpose other than the statistical analysis or research." |
Use of the dataset must be acknowledged using a citation which would include:
Example:
Thailand National Statistical Office (TNSO). Thailand Household Socio-Economic Survey 1994. Dataset downloaded from http://web.nso.go.th/ on [date].
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Affiliation | URL |
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National Statistical Office | http://web.nso.go.th/ |
DDI_THA_1994_SES_v02_M
Name | Affiliation | Role |
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Shine Cagas | ADP | Conversion to DDI |
2010-10-15
Version 2 (October 2010). In this version, the datasets r3, r4, r6 to r10 were restructured from wide to long formats.