Integrated Household Living Conditions Assessment 2004
Myanmar, 2004
Identification
MMR_2004_IHLCA_v01_M
Integrated Household Living Conditions Assessment 2004
| Name | Country code |
|---|---|
| Myanmar | MMR |
Integrated Survey (non-LSMS) [hh/is]
In order to provide the Government and international funding agencies with a reliable and up to date integrated assessment of all major aspects of household living conditions in the Union of Myanmar, the United Nations Development Programme (UNDP) and the Government of the Union of Myanmar have agreed on the implementation of an Integrated Household Living Conditions Assessment (IHLCA) in 2003-2005.
The expected outputs of this project include:
- A nationwide qualitative study on people’s perceptions of poverty in Myanmar including 224 focus groups in December 2003. The results of this study were published in July 2004 in four volumes;
- A nationwide quantitative survey of 18,660 households with two rounds of data collection (November-December 2004 and May 2005);
- A Poverty Management Information System (PMIS).
The IHLCA involved two phases: (i) the first phase was a qualitative study which aimed at providing information on the perceptions of the people of Myanmar on living conditions to feed into the final selection of indicators to include in the questionnaire of the second quantitative phase of this baseline survey; (ii) this last phase included two rounds of data collection.
The first analysis of IHLCA data led to the preparation of four reports:
- Integrated Household Living Conditions Assessment in Myanmar: Poverty Profile;
- Integrated Household Living Conditions Assessment in Myanmar: Vulnerability–Relevant Information;
- Integrated Household Living Conditions Assessment in Myanmar: MDG-Relevant Information;
- Integrated Household Living Conditions Assessment in Myanmar: Quantitative Survey Technical Report.
SURVEY OBJECTIVES
In order to provide a holistic assessment of living conditions in Myanmar, drawing on reliable data that are representative of the country’s population, the IHLCA was a logical continuation of previous assessments of social and economic conditions and outcomes. On the basis of IHLCA results, it will be possible to better understand the situation of the population in relation to poverty, vulnerability and inequality. The information generated will allow for better planning of policies and programs for improving household living conditions.
The main objectives of the Survey were the following:
- To obtain an accurate and holistic assessment of population well-being by measuring a number of indicators related to living conditions from an integrated perspective;
- To provide reliable and updated data for identifying different levels of poverty in order to help better focus programmatic interventions and prioritize budget allocations;
- To provide quantitative and qualitative data for better understanding the dimensions of wellbeing and poverty in Myanmar and the endogenous and exogenous factors behind the observed patterns and trends in living conditions;
- To provide baseline information for monitoring progress towards the achievement of the Millennium Development Goals and other national and international targets;
- To develop a rigorous and standardized methodology for establishing a framework for monitoring living conditions and conducting future time-trend analysis.
Given the breadth of information that was to be generated by the integrated survey and the range of stakeholders involved in the project, there were also a number of secondary objectives including:
- The compilation of updated statistics for a series of indicators that were also addressed in previous surveys in Myanmar for comparative time-trend analyses on specific aspects of living conditions where appropriate;
- The compilation of precise statistics on the spatial distribution of poor and non-poor households for poverty mapping;
- For economic and social analysis, improved data for monitoring differentials in living conditions by urban-rural residence, gender and other population sub-groups;
- For policy and programmatic formulation, comprehensive data on the population’s perceptions of living conditions, in particular prioritization in terms of their preferences to improve well-being and reduce poverty across regions of the country.
Sample survey data [ssd]
Scope
Household questionnaire:
Module 1: Household Basic Characteristics;
Module 2: Housing;
Module 3: Education;
Module 4: Health;
Module 5: Consumption Expenditures;
Module 6: Household Assets;
Module 7: Labour and Employment;
Module 8: Business;
Module 9: Finance and Savings.
Community questionnaire :
Module 1.1: Village/Ward Infrastructure;
Module 1.2: Population;
Module 1.3: Housing;
Module 1.4: Labour and Employment
Module 1.5: Business Activities;
Module 1.6: Agricultural Activities;
Module 1.7: Finance and Savings;
Module 2: Schools
Module 3: Health facilities
Module 4: Pharmacies and Drug Stores
Coverage
Administratively, the Union of Myanmar is divided into 17 States/Divisions. These in turn are subdivided into 61 Districts. Districts are further subdivided into Townships, Wards, Village Tracts and Villages.
The IHLCA Survey covered both the urban and rural areas at the regional and national levels.
The Survey aimed to produce data at the regional level for each of the 17 States/Divisions. No Township estimates were to be provided as this would necessitate too large a sample size. The sample was large enough to provide good sample estimates of a number of important living conditions characteristics at the national level, and reasonably good sample estimates at the State/Division level.
Producers and sponsors
| Name |
|---|
| Planning Department (PD) |
| Central Statistical Organization (CSO) |
| Name | Role |
|---|---|
| United Nations Development Programme | Technical and financial support |
| Name |
|---|
| IHLCA Steering Committee |
| IHLCA Technical Committee |
| Foreign Economic Relations Department (FERD) |
| National Nutrition Center |
| Department of Health Planning |
| Department of Medical Research, the Institute of Economics |
| Department of Basic Education |
| Ministry of Labor |
| Settlements and Land Records Department |
| Department of Population |
Sampling
In order to minimise sampling errors, the careful design of a statistically sound sampling plan was deemed of critical importance. The starting point of such a plan was a sampling frame, or complete listing of communities and households from which a sample can be drawn, and the desired precision level for key indicators, to be used in the determination of the expected sample size. The sampling plan was designed to collect representative information from a stratified multiple-stage random sample of around 18888 households across all regions of the country.
A number of factors had to be addressed in the determination of a survey design, including the sampling plan. Factors to be considered with regard to sampling were:
- The specific objectives of the survey;
- The country’s characteristics, in particular its administrative divisions;
- The level of precision desired for the resulting estimates;
- The desired timeframe for availability of results;
- The availability of human and financial resources.
On the one hand, designing a plan to include a very large sample of households would allow for more precise estimates of the selected indicators and enable greater degrees of disaggregation at the sub-national level.
On the other hand, in favor of a sample size that was not too big were the needs of concerned stakeholders to have results available in a timely manner (within a few weeks or months from the end of fieldwork) as well as the workload and budget constraints. Experience has shown that surveys with very large samples: (i) have a high probability of becoming bogged down, creating delays of several years in results publication; (ii) are prone to poor data quality, in particular due to non-sampling errors; and (iii) represent a major disturbing factor for other statistical operations that technical and reporting agencies must conduct. While from an international perspective the financial costs of conducting surveys may be relatively low in Myanmar, the opportunity cost of the time and resources spent on a very large-scale survey and not on other productive activities was taken into account.
Another consideration was the desired level of disaggregation by the IHLCA main data users. It was decided to ensure collection of representative data for the following spatial units:
- National level;
- States/divisions (17);
- Urban/rural areas by state/division.
This breakdown suggested a total of 34 strata (2 area types * 17 states/divisions).
One significant constraint to the design of the sampling plan for the IHLCA quantitative survey was the absence of a reliable updated sampling frame or complete listing of households across the country from which a sample could be drawn. Usually such frames are based on the results of the most recent population census; however there had been no national count in Myanmar since 1983. Updated population estimates were to be obtained from The Department of Population (DOP) of the Ministry of Population. The frame was imperfect. In addition a number of areas were excluded by PD because of inaccessibility for fieldwork implementation due to transportation/communication problems or ongoing security concerns.
The options for selecting households for questionnaire implementation ranged from simple random sampling of households across the country (the most efficient methodology from a purely statistical viewpoint, but one for which fieldwork costs may be prohibitive), to multi-stage random selection based on probability proportional to size (a more commonly used approach given the costs-benefits tradeoffs). However, considering the lack of reliable population numbers at the lowest levels of geographic disaggregation for Myanmar, the sampling plan had to rely on probability proportional to estimated size (PPES) approaches and the measures of size used were the number of households at different geographical levels.
Another issue that was considered in the determination of the sample size was the desired precision level by the IHLCA main data users. The calculation was based on observed variances for key variables in past survey experiences.
Sampling weights were applied for the calculation of all poverty measures and KRI indicators. Each household was attributed a sampling weight. The detailed procedure for the determination of sampling weights is presented under the section “Sampling Design and Estimation Procedure” of the technical report.
Survey instrument
The following survey questionnaires were used for the IHLCA survey3:
-
The household questionnaire, administered at household level, included 9 modules covering different aspects of household living conditions:
Module 1: Household Basic Characteristics;
Module 2: Housing;
Module 3: Education;
Module 4: Health;
Module 5: Consumption Expenditures;
Module 6: Household Assets;
Module 7: Labour and Employment;
Module 8: Business;
Module 9: Finance and Savings. -
The Community questionnaire, administered to local key informants, which included 4 modules which aimed at providing general information on the village/wards where the survey was being undertaken and at reducing the length of the household interview. The questionnaire was only administered in the first round. Modules included in the Community questionnaire were:
Module 1.1: Village/Ward Infrastructure;
Module 1.2: Population;
Module 1.3: Housing;
Module 1.4: Labour and Employment
Module 1.5: Business Activities;
Module 1.6: Agricultural Activities;
Module 1.7: Finance and Savings;
Module 2: Schools
Module 3: Health facilities
Module 4: Pharmacies and Drug Stores -
The Community Price Questionnaire which aimed at providing information on the prices of specific items in each village/ward surveyed. These prices were collected in case the quality of implicit prices calculated from the household survey was not satisfactory. Since there were no
problems with implicit prices, community level prices were not used. The Community Price Questionnaire comprised of only one module. -
The Township Profile questionnaire aimed at collecting administrative information about the Townships included in the survey. It was not used in the data analysis.
All final questionnaires were translated from English to Myanmar after pilot testing, and then back-translated into English for validation.
Data collection
| Start | End | Cycle |
|---|---|---|
| 2004-05 | 2004-06 | Round 1 |
| 2004-10 | 2004-11 | Round 2 |
With regard to potential non-sampling errors, when collecting information from the respondent it was important to plan for several controls: (i) immediately during the interview by the enumerator; (ii) after the interview during the review of the completed questionnaire by the field supervisor; and (iii) during data processing. For instance, ranges for data on the monetary value of household expenditures were set, such as minimum and maximum acceptable prices for a given quantity of each major food and non-food item (based on independently obtained data of market prices). The appropriate ranges were verified during questionnaire pre-testing, and flagged during manual and automatic data editing. Thus strong literacy skills and qualifications in calculations and statistics were used as a basis for the selection of field enumerators and supervisors, as well as data entry operators (skills generally verified during the recruitment processes by means of written examinations).
Moreover, in order to continually monitor the quality of the information being collected and correct any potential discrepancies as soon as possible, entry and validation of incoming data for the quantitative survey were conducted at the PD states/divisions offices, and then transferred to PD Central Level Office. The raw micro-datasets for all states/divisions were aggregated and processed at the national level by PD staff under the supervision of the Technical Unit at PD Central Level Office in Yangon.
The quantitative survey was designed to collect reliable and representative information on a number of dimensions of living conditions in Myanmar. Data collection tools included structured questionnaires to be administered to nationally representative samples of the population at different levels (community, household and individual), each divided into several modules for monitoring the different domains of living conditions. Some of the modules were repeated for the same households and individuals at different points in time throughout the year to allow for temporal comparisons, notably with regard to seasonality of food and non-food consumption patterns. The multi-round approach combined with a modular questionnaire design proved a very useful and convenient data collection tool.
DATA COLLECTION
The design for the quantitative survey entailed a two-round data collection approach for monitoring household living conditions. There were several arguments in favor of conducting two rounds. Predominant was the important seasonal variations in household income, expenditure and consumption patterns. In particular, Myanmar is characterized by: (i) three distinct seasons (cold season from October until January, summer from February through May, and rainy season from June through September); (ii) a high dependence on agriculture for income-generating activities; and (iii) a high food/non-food expenditure ratio in household budgets. Thus it is of critical importance to capture these variations if the survey results are to be meaningful and representative. Two other reasons for improving the quality of the results were the evidence that that a multiple round survey increases the level of confidence between enumerators and respondents, and helps increase respondents’ memories thereby reducing recall errors.
Specific factors that were considered in determining the timing of such rounds included:
- The potential difficulties of conducting survey fieldwork during the rainy season in cerrain areas;
- The need for the results of the qualitative study to be finalised before starting the quantitative survey phase (with the ensuing implication that the tools for the quantitative survey could not be finalised before March 2004);
- The timing of important national holidays and cultural events (notably the Water Festival in April);
- The need for comparability of the IHLCA results with findings from previous surveys (notably the 1997 and 2001 HIES, for which data collection was conducted in October-November).
This led to the plan to conduct data collection activities for the first round of the quantitative survey in May-June 2004 and for the second round in October-November 2004. Unfortunately due to unforeseen circumstances, these dates had to be changed and data collection activities were rescheduled to take place respectively in November 2004 and May 2005. Depending on the nature of the information to be collected, different types of questions (current status and retrospective) were included in the survey instruments. For instance, current status questions were asked to assess level of education. On the other hand, retrospective questions were also asked to collect information on household consumption expenditures. Thus one important issue was the reference period for specific consumption items. In order to minimise recall errors, different reference periods were used for different types of items. In particular, shorter periods were used for smaller items (such as 7days for frequently bought food items and 30 days for less frequently bought food items and non-food items), and longer periods for larger items (such as six months for bulky non-food items and equipment).
Another issue relevant to the collection of quality data was cultural and gender sensitivity, particularly with regard to questions of a highly personal nature such as reproductive health. Field enumerators were recruited at the local level, in order to ensure that the interviews were conducted in the respondents’ own language. Field teams were composed of at least one female and one male enumerator, so that respondents could be interviewed by a person of the same sex. As previously mentioned, strong literacy and mathematical skills were required for all field staff.
Data processing
Data cleaning involved mainly:
- Checking and correcting for inconsistencies in the data;
- Identifying and correcting for outliers;
- Recoding of variables when necessary.
Data cleaning procedures are presented in details in the SPSS syntaxes.
Data appraisal
In The Union of Myanmar, the basic demands on the sample design of the 2004/2005 IHLCA were to provide good quality estimates for the main survey variables at the national level. Estimates of lower quality were to be provided for the 17 States/Divisions comprising of the country. It has been observed as a general trend that the relative amplitude of sampling error in comparison with other types of survey errors increases as we move from estimates for the total population (the nation) to estimates for individual subgroups (the States/Divisions).
The 2004/2005 IHLCA used a two-stage stratified cluster sample design. All estimates produced are therefore subject to sampling errors. The method used to compute sampling errors in the 2004/2005 IHLCA, is based on the comparison among estimates for independent primary selections within each stratum. The basic assumptions made were:
- The sample selection is independent between strata;
- These primary selections are drawn at random, independently and with replacement.
The term ‘primary selection’ refers to a PSU and stratum refers to either the rural/small-urban distinction or a region.
Given independent with replacement sampling of clusters, sampling theory can used to estimate the variance of stratum totals, means, and ratios for survey variables.
In general, the precision levels achieved at the National level are good and acceptable, quite in line with the expectations of the survey planning team.
Results of the computations of sampling errors are given in the Table 10.3(a) to Table 10.3(c) of the Technical Report for the national level and Table 10.4(a) to table 10.4(c) for sub national (State/Division) level.
Disclaimer and copyrights
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.
Metadata production
DDI_MMR_2004_IHLCA_v01_M_WB
| Name | Affiliation | Role |
|---|---|---|
| Development Economics Data Group | The World Bank | Documentation of the DDI |
2013-11-11
Metadata version
Version 01 (Nov 2013)
Version 02 (July 2015)