Many sources of data can be useful for poverty analysis and the evaluation of policy interventions. Some data, such as central public finance data and national accounts, exist only at the national level. Often, these data are collected centrally by the statistical institute or the central bank. Local-level data are often collected through local offices of the statistical institute or the Ministry of Finance. Such data -- for example, data by region, province, or district -- often include availability and use of services, such as education, health, water, and electricity, and may include economic and price information, such as regional inflation. Few countries produce national accounts at the sub-national level.
Household or individual-level data on welfare components, such as income, consumption, illness patterns, and household priorities and perceptions, present the most disaggregated data. These data are typically gathered through household surveys, and they can be summarized at higher levels (at the local or national level) to produce aggregate statistics. For example, household-level data are needed to determine whether the members of a particular household are income poor. Aggregation across households will provide regional or national estimates of poverty. (See Household surveys and Accessing surveys for more information.)
Along with providing national averages, local-level data can be important because local realities vary, and so do the key dimensions of poverty and the indicators that are useful to analyze and monitor. Moreover, some decisions—increasingly more as decentralization advances—are made at the local level and require local information. In many instances, however, the collection and monitoring of local level data will be set up differently, since local capacities vary and there is greater potential for community involvement.Table: Data Types and Agencies
|National-level data : |
|National accounts: GDP, Consumption, Investment, Exports, Imports, and so on||Central statistical agency||System of National Accounts, trade statistics||Monthly or quarterly where possible--trade statistics, for example; at least yearly|
|Public finance data: revenues, spending by category||Ministry of Finance, central statistical agency, sectoral ministries||Budgets and actuals||Monthly or quarterly where possible--trade statistics for example; at least yearly|
|Consumer and producer prices||Central statistical agency, central bank||Price surveys||Monthly; CPI basket updated at least every five years|
|Social Indicators||Management information systems (MIS) of sectoral ministries||Administrative systems||Yearly where possible|
|Consumer and producer prices, climatic data, national accounts at regional level||Central statistical agency, central bank||Price surveys, systems of national accounts||Monthly; CPI basket updated at least every five years|
|Availability of services||Local administration, sectoral ministries||Multi-topic household surveys; employment surveys, qualitative studies||Yearly|
|Use of services||Local service providers||Rapid Monitoring and Satisfaction Surveys||Yearly|
|Individual and household-level data: |
|Household consumption and income; living conditions, social indicators||Central statistical agency, Ministry of Labor/Employment||Household budget, expenditure, income surveys, multi-topic household surveys, demographic and health surveys||Every three to five years|
|Population statistics, access to services—no consumption or income; literacy ||Central statistical agency ||Population census ||Every five or ten years |
|Household living standards —no detailed consumption or income; illness patterns, malnutrition, education profile||Central statistical agency, Ministry of Labor/Employment, others||Rapid Monitoring Surveys, demographic and health surveys||Yearly|
|Household priorities, perceptions of well-being, user satisfaction||Central statistical agency, sectoral ministries, others||Qualitative studies; Rapid Monitoring Surveys||Every one to three years|
The role of administrative data and the population census are worth commenting upon:
In many countries, administrative data are the most accessible data source. Usually provided by line ministries and specialized agencies, these data describe specific activities and programs such as school enrollment, disease prevalence, malnutrition information, hospital expenses, road network information, and income and expenditure for decentralized units. This information is important in assessing levels of public and private inputs, outputs, and outcomes, as well as their distribution within the country. For example, it is possible to compare how the distribution of enrollment rates matches spending on primary schools; how the structure of health spending-- primary versus tertiary care --reflects disease patterns; or how agricultural productivity of main crops varies with land tenure patterns.
Administrative data can often provide an important entry into poverty analysis, especially if it they are used to compare need and demand for services. However, administrative data do not allow for cross-tabulating or analyzing poverty across different dimensions. For example, it is generally not possible to look at enrollment rates of children by the income group of their parents. (Multi-topic household surveys, which are discussed below, differ from administrative systems in that they allow the analyst to relate indicators with each other.)
A population census contains basic information on all citizens of a country. The census is carried out for all households to obtain basic information on the population, its demographic structure, and its location. The census is typically carried out by the national statistics institute, which then provides data to lower levels of government tailored to local information needs. Since the census covers the whole population, it is costly, and most countries conduct a census only once a decade. The census can provide policymakers with important data for planning in the years directly following its implementation, but its usefulness diminishes after that.
Since the census is carried out across millions of households, the information gathered is, by necessity, limited. Information on household income, consumption, disease patterns, and poverty perceptions are generally not included. However, the census usually contains descriptive statistics of the housing stock, access to basic services such as water, electricity, and sanitation; information on education and employment patterns, and population statistics. The census has the advantage of being able to provide information at low levels of aggregation, such as the municipality level. Census data are also an important tool to check how representative other surveys are. The usefulness of sample surveys can be increased substantially if they are combined with census information, for example for providing poverty maps.
Household surveys are essential for the analysis of welfare distribution and poverty characteristics. At the same time, aggregate household-level analysis can provide only limited understanding of the intra-household distribution of resources, especially of income and consumption. Moreover, while the census covers the whole population in the country, surveys interview only a subset, generally a small fraction, of all households. This sample of households must be carefully chosen so that the results of the survey accurately describe living conditions in the country, and different parts of the country.
Sampling should be based on mapping of actual settlements, including newly-formed informal urban settlements. Sampling is most often informed by a recent population census. The sample size -- the number of households interviewed -- will vary with several factors, including:
the indicator that is to be measured (a survey that aims to measure countrywide averages of income may require a larger sample than a survey designed to measure the percentage of the population with water connection, in part because the later is easier to measure);
the level at which the policymaker needs the information (a national electricity connection rate will require fewer households to be interviewed than regional or district rates).
Different types of household surveys are presented in Table A, directly below.Table A: Household Survey Types
|Household Survey ||Advantage ||Limitations|
|Multi-topic surveys||Measurement and analysis of different poverty dimensions, their inter-relationships, and correlates||Time-intensive (collection and evaluation)|
|Demographic and health surveys||Health-poverty measurement, health behavior analyses, basic poverty diagnostics||Measurement of other dimensions of poverty limited, diagnostics limited|
|Employment surveys||Analysis of employment patterns, wage income analysis (link to education)||Limited use for poverty measurement and diagnostics|
|Single-topic surveys||Income-poverty measurement (or one other dimension)||Limited diagnostics possible|
|Rapid monitoring surveys and service satisfaction surveys||Quick and cost-effective monitoring of key welfare indicators||Income-poverty measurement not possible, limited diagnostics|
Living Standard Measurement Study (LSMS) surveys and other multi-topic surveys
Multi-topic welfare surveys, like the LSMS, are geared towards measuring and analyzing poverty and are important instruments for poverty diagnostics. LSMS surveys collect information on household expenditures and income, health, education, employment, agriculture, the ownership of assets such as housing or land, access to services, and social programs. Dozens of countries have implemented multi-topic surveys and many now have several rounds of surveys that allow rich comparisons across time. Multi-topic surveys can also be used to measure the impact of public policies and programs on poverty.
Demographic and Health Surveys
These are special household surveys geared to exploring the incidence of diseases and use of health facilities. They collect anthropometric data—height, weight, and age of children, that can be used to calculate malnutrition rates--and many other health and health behavior-related variables that enable such factors as survival rates, birth histories, and disease incidences to be computed. The surveys also contain basic data about housing conditions, educational attainments, and employment patterns. Although they do not include income or expenditure data, they can be used to calculate household wealth and carry out important poverty diagnostics.
Labor ministries use employment surveys to gather information on employment and wages. These surveys include questions about household income, demographics, and housing features. They can be good sources for employment statistics, income-based poverty indicators—if the income module is good—and input indicators such as access to basic services. Employment surveys tend to be more important information sources for heavily urbanized countries.
Expenditure and income surveys
Contrary to multi-topic surveys, expenditure and income surveys are narrower in scope. They are useful instruments to measure different dimensions of poverty—such as income- or education-poverty—but are limited in their ability to relate household well-being to underlying causes such as asset distribution or productive activities.
Rapid Monitoring and Satisfaction Surveys
These surveys are generally large, contain relatively short questionnaires, and include predetermined data entry packages. They are easy to implement and have a rapid turnaround time. The Core Welfare Indicator Questionnaire (CWIQ)—widely applied in Africa—is one example. Unlike other surveys, the CWIQ is not designed to serve as a tool for measuring whether poverty levels are increasing or decreasing. It is intended only to measure whether or not public services and development programs are reaching the poor and benefiting them, and to monitor selected indicators—those that contain advance warnings of the future impact of policies and events—and assess household living conditions, access to basic social and infrastructure services, and the satisfaction of the population with these services. Satisfaction surveys are best viewed as complements to multi-topic household surveys and have been used in many countries to monitor access to and quality of basic services.
Many other, specialized surveys exist that can be used for poverty diagnostics. These can range from violence surveys--for example, in Lima, Peru--to opinion surveys--for example, those conducted by the Social Weather Station in the Philippines. Several countries also have surveys of health centers, schools, or other public institutions. Firm surveys can be essential to understanding the impact of crisis on employment and specific groups at risks and were used extensively in understanding the impact of the East Asian crisis. Food security assessments identify high-risk groups and are often used by relief organizations. Typically, the websites of national statistical institutes and international organizations will provide information about the availability of such data.
Qualitative research tools range from participatory assessments to ethnographic and sociological case studies, and institutional to political investigations. Some of these tools are described below in Table C. These tools help in gathering information that household surveys are not able to capture, or can capture only partially, including:
- Subjective dimensions of poverty and variations in perceptions along gender, urban/rural, or ethnicity lines;
- Barriers that poor people themselves believe are stopping them from advancing;
- Intra-household inequalities; poor people’s priorities for action;
- Cultural factors determining poverty, such as gender roles and some traditional beliefs;
- Political factors determining poverty, such as trust, corruption, and conflict;
- Certain social factors determining poverty, such as the role of community networks.
The tools may also help in the design appropriate household survey questionnaires-- for example, in the section on reasons for use or non-use of health and education facilities. Finally, the tools may help for assessing the validity of survey results at the local level and to evaluate how much general policy design should consider the heterogeneity of local conditions.
Table C: Data Collection Methods for Qualitative and Participatory Assessments
|Data Collection in:||Methods|
|Beneficiary Assessments ||Participant observation and more systematic data collection methods like structured interviews over a limited time span.|
|Ethnographic Investigations||Anthropological research techniques, especially direct observation, to analyze the influence of ethnicity, gender, and village stratification on the household and group well-being and behavior.|
|Longitudinal Village Studies||Wide variety of methods ranging from direct observation and recording (tabulation), periodic semi-structured interviews with key informants (for example, health center staff) and village population, to survey interviews in several different observation periods.|
|Participatory Assessments ||Ranking, mapping, diagramming, and scoring methods are prominent besides open interviews and participant observation. The time horizon of participatory assessments is often short. They build on local populations describing and analyzing their own reality surrounding poverty and well-being.|
Participatory assessments can help policy makers determine the type of indicators important for the poor—is it housing, employment, or income?. They can also capture information that other sources cannot capture, for example, the incidence and effect of domestic violence.
Beneficiary and participatory assessments, which can take different forms, also involve the population more than household surveys. In town-hall or village meetings, citizen groups or their representatives can discuss poverty problems and policies, rank what they consider the causes of poverty, and map out new infrastructures in actual planning exercises. Individual interviews can investigate the problems of women or children in households. Participatory methods do not necessarily guarantee, though, that all groups in the community are given an equal voice. There is a danger that women may be under-represented. This danger may be even more present for the very poor. (See Beneficiary Assessment and Participatory Poverty Assessments in the PSIA website for more information).
Whenever possible, it is important to link participatory and qualitative investigations with household surveys and population censuses in a formal way. This can be done by:
collecting variables in participatory studies that allow for easy comparison with regional or national averages obtained from quantitative sources;
designing qualitative case studies so that they are done on sub-samples of larger surveys; and
following formal sampling and data recording procedures that allow for systematic analysis and replicability of qualitative results.
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