Abstract

The Living Standards Measurement Survey (LSMS) is a multi-purpose household survey conducted to measure living conditions and poverty situation, and to help policymakers in monitoring and developing social programs.

LSMS has been carried out in Albania in the context of continuing monitoring of poverty and the creation of policy evaluation system in the framework of the National Strategy for Development and Integration (previously the National Strategy for Economic and Social Development).

The first Albania LSMS was conducted in 2002, followed by 2003, 2004, 2005, 2008 and 2012 surveys. In 2012, 6,671 households participated in the survey.

Geographic coverage

National

Analysis unit

• Households
• Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey includes a sample of 6,671 households that constitute the survey units. The sample is chosen randomly by two rounds of selection. The sample frame was provided from Population and Housing Census done on October 2011. In the first round, 834 Primary Selection Units (PSUs) have been chosen randomly to represent the whole territory of the country. Then, 8 households for each PSU were chosen to be interviewed in the second round through a procedure of systematic sample. To handle cases of non response or no contact other 4 households for each PSU were chosen as substitutes that ensured the target of 6,671 completed questionnaires near the households.

The methodology of the 2012 LSMS has been kept similar with the surveys conducted in the previous years. However, the geographic domains of analysis have been expanded to include the 12 individual prefectures of Albania, by urban and rural strata, compared to four geographic regions (Central, Coastal, Mountain and Tirana) by urban and rural strata defined previously as domains for the survey. This required a considerable increase in the sample size from 3,600 to 6,671 households making possible to calculate indicators of living standard for 24 strata and even for the four main areas of the country in order to compare the regional results to those from the 2002, 2005 and 2008 surveys and study the regional trends for various indicators.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was divided in two sections, and was administered to households in two visits, one section per visit. During the second visit the interviewer would also collect additional information of use for the eventual tracking of the household in the next waves of the panel.

The Booklet for Recording Daily Household Consumption was left with the household by the interviewer during the first visit for the household to compile, and collected during the second visit. Upon collection, interviewers took care of checking the entries (also with the help of a checklist provided at the end of the booklet) and correct them as appropriate with the help of the most knowledgeable person in the household.

A specific column was provided for the household to record the reference period for any purchases of food. The checklist was compiled by the interviewer, with the help of the most knowledgeable person in the household, upon collection of the diary. Interviewers were instructed to check, for 14 main food staples, whether any consumption of the item had been recorded in the diary. Whenever an item had not been recorded the interviewer would ask the respondent to report whether the item (a) had not been used in the 14-day period, or (b) had been consumed but the household had forgotten to record its consumption, or else (c) had been consumed by the household drawing on stocks purchased or produced outside the 14-day period. If the inclusion of an item had simply been forgotten the interviewer would then fill the appropriate section of the diary by asking the household to recall the details of that consumption. If the household reported consuming an item purchased before the beginning of the 14-day period, then information on the frequency of purchase, quantity, unit of measure and value of the purchase were recorded in the columns provided to this end in the checklist.

Abstract copyright UK Data Service and data collection copyright owner.

Background:
A household food consumption and expenditure survey has been conducted each year in Great Britain (excluding Northern Ireland) since 1940. At that time the National Food Survey (NFS) covered a sample drawn solely from urban working-class households, but this was extended to a fully demographically representative sample in 1950. From 1957 onwards the Family Expenditure Survey (FES) provided information on all household expenditure patterns including food expenditure, with the NFS providing more detailed information on food consumption and expenditure. The NFS was extended to cover Northern Ireland from 1996 onwards. In April 2001 these surveys were combined to form the Expenditure and Food Survey (EFS), which completely replaced both series. From January 2008, the EFS became known as the Living Costs and Food (LCF) module of the Integrated Household Survey (IHS). As a consequence of this change, the questionnaire was altered to accommodate the insertion of a core set of questions, common to all of the separate modules which together comprised the IHS. Some of these core questions are simply questions which were previously asked in the same or a similar format on all of the IHS component surveys. For further information on the LCF questionnaire, see Volume A of the LCF 2008 User Guide, held with SN 6385. Further information about the LCF, including links to published reports based on the survey, may be found by searching for 'Living Costs and Food Survey' on the ONS website. Further information on the NFS and Living Costs and Food Module of the IHS can be found by searching for 'Family Food' on the GOV.UK website.

History:
The LCF (then EFS) was the result of more than two years' development work to bring together the FES and NFS; both survey series were well-established and important sources of information for government and the wider community, and had charted changes and patterns in spending and food consumption since the 1950s. Whilst the NFS and FES series are now finished, users should note that previous data from both series are still available from the UK Data Archive, under GNs 33071 (NFS) and 33057 (FES).

Purpose of the LCF
The Office for National Statistics (ONS) has overall project management and financial responsibility for the LCF, while the Department for Environment, Food and Rural Affairs (DEFRA) sponsors the food data element. As with the FES and NFS, the LCF continues to be primarily used to provide information for the Retail Prices Index, National Accounts estimates of household expenditure, analysis of the effect of taxes and benefits, and trends in nutrition. The results are multi-purpose, however, providing an invaluable supply of economic and social data. The merger of the two surveys also brings benefits for users, as a single survey on food expenditure removes the difficulties of reconciling data from two sources.

Design and methodology The design of the LCF is based on the old FES, although the use of new processing software by the data creators has resulted in a dataset which differs from the previous structure. The most significant change in terms of reporting expenditure, however, is the introduction of the European Standard Classification of Individual Consumption by Purpose (COICOP), in place of the codes previously used. An additional level of hierarchy has been developed to improve the mapping to the previous codes. The LCF was conducted on a financial year basis from 2001, then moved to a calendar year basis from January 2006 (to complement the IHS) until 2015-16, when the financial year survey was reinstated at the request of users. Therefore, whilst SN 5688 covers April 2005 - March 2006, SN 5986 covers January-December 2006. Subsequent years cover January-December until 2014. SN 8210 returns to the financial year survey and currently covers April 2015 - March 2016.

Northern Ireland sample
Users should note that, due to funding constraints, from January 2010 the Northern Ireland (NI) sample used for the LCF was reduced to a sample proportionate to the NI population relative to the UK.

Family Food database:
'Family Food' is an annual publication which provides detailed statistical information on purchased quantities, expenditure and nutrient intakes derived from both household and eating out food and drink. Data is collected for a sample of households in the United Kingdom using self-reported diaries of all purchases, including food eaten out, over a two week period. Where possible quantities are recorded in the diaries but otherwise estimated. Energy and nutrient intakes are calculated using standard nutrient composition data for each of some 500 types of food. Current estimates are based on data collected in the Family Food...

The Poverty and Social Exclusion Living Standards Survey provided crucial information about the living standards experienced by UK households, with particular interest in issues of income inequality, poverty and social exclusion. Survey fieldwork was conducted separately in Great Britain (England, Scotland, Wales) and Northern Ireland. In Great Britain the study was conducted by the NatCen Social Research on behalf of the University of Bristol. In Northern Ireland the study was conducted by Central Survey Unit (CSU) of the Northern Ireland Statistics and Research Agency (NISRA) on behalf of Queen's University Belfast.

This statistic shows the results of a survey conducted in Venezuela from 2010 to 2013 on the standard of living. In 2013, 35 percent of respondents said the standard of living was getting worse. In 2012, only 11 percent of respendents said the standard of living was getting worse.

Inflation is generally defined as the continued increase in the average prices of goods and services in a given region. Following the extremely high global inflation experienced in the 1980s and 1990s, global inflation has been relatively stable since the turn of the millennium, usually hovering between three and five percent per year. There was a sharp increase in 2008 due to the global financial crisis now known as the Great Recession, but inflation was fairly stable throughout the 2010s, before the current inflation crisis began in 2021. Recent years Despite the economic impact of the coronavirus pandemic, the global inflation rate fell to 3.26 percent in the pandemic's first year, before rising to 4.66 percent in 2021. This increase came as the impact of supply chain delays began to take more of an effect on consumer prices, before the Russia-Ukraine war exacerbated this further. A series of compounding issues such as rising energy and food prices, fiscal instability in the wake of the pandemic, and consumer insecurity have created a new global recession, and global inflation in 2024 is estimated to have reached 5.76 percent. This is the highest annual increase in inflation since 1996. Venezuela Venezuela is the country with the highest individual inflation rate in the world, forecast at around 200 percent in 2022. While this is figure is over 100 times larger than the global average in most years, it actually marks a decrease in Venezuela's inflation rate, which had peaked at over 65,000 percent in 2018. Between 2016 and 2021, Venezuela experienced hyperinflation due to the government's excessive spending and printing of money in an attempt to curve its already-high inflation rate, and the wave of migrants that left the country resulted in one of the largest refugee crises in recent years. In addition to its economic problems, political instability and foreign sanctions pose further long-term problems for Venezuela. While hyperinflation may be coming to an end, it remains to be seen how much of an impact this will have on the economy, how living standards will change, and how many refugees may return in the coming years.

The Integrated Living Conditions Survey (ILCS), conducted annually by the NSS National Statistical Service of the Republic of Armenia, formed the basis for monitoring living conditions in Armenia. The ILCS is a universally recognized best-practice survey for collecting data to inform about the living standards of households. The ILCS comprises comprehensive and valuable data on the welfare of households and separate individuals which gives the NSS an opportunity to provide the public with up to date information on the population’s income, expenditures, the level of poverty and the other changes in living standards on an annual basis.

The UK inflation rate was 3.4 percent in May 2025, down from 3.5 percent in the previous month, and the fastest rate of inflation since February 2024. Between September 2022 and March 2023, the UK experienced seven months of double-digit inflation, which peaked at 11.1 percent in October 2022. Due to this long period of high inflation, UK consumer prices have increased by over 20 percent in the last three years. As of the most recent month, prices were rising fastest in the communications sector, at 6.1 percent, but were falling in both the furniture and transport sectors, at -0.3 percent and -0.6 percent respectively.
The Cost of Living Crisis High inflation is one of the main factors behind the ongoing Cost of Living Crisis in the UK, which, despite subsiding somewhat in 2024, is still impacting households going into 2025. In December 2024, for example, 56 percent of UK households reported their cost of living was increasing compared with the previous month, up from 45 percent in July, but far lower than at the height of the crisis in 2022. After global energy prices spiraled that year, the UK's energy price cap increased substantially. The cap, which limits what suppliers can charge consumers, reached 3,549 British pounds per year in October 2022, compared with 1,277 pounds a year earlier. Along with soaring food costs, high-energy bills have hit UK households hard, especially lower income ones that spend more of their earnings on housing costs. As a result of these factors, UK households experienced their biggest fall in living standards in decades in 2022/23. Global inflation crisis causes rapid surge in prices The UK's high inflation, and cost of living crisis in 2022 had its origins in the COVID-19 pandemic. Following the initial waves of the virus, global supply chains struggled to meet the renewed demand for goods and services. Food and energy prices, which were already high, increased further in 2022. Russia's invasion of Ukraine in February 2022 brought an end to the era of cheap gas flowing to European markets from Russia. The war also disrupted global food markets, as both Russia and Ukraine are major exporters of cereal crops. As a result of these factors, inflation surged across Europe and in other parts of the world, but typically declined in 2023, and approached more usual levels by 2024.

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 50% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)

The Household Income, Expenditure and Consumption Survey (HIECS) is of great importance among other household surveys conducted by statistical agencies in various countries around the world. This survey provides a large amount of data to rely on in measuring the living standards of households and individuals, as well as establishing databases that serve in measuring poverty, designing social assistance programs, and providing necessary weights to compile consumer price indices, considered to be an important indicator to assess inflation.

The First Survey that covered all the country governorates was carried out in 1958/1959 followed by a long series of similar surveys . The current survey, HIECS 2012/2013, is the eleventh in this long series.

Starting 2008/2009, Household Income, Expenditure and Consumption Surveys were conducted each two years instead of five years. this would enable better tracking of the rapid changes in the level of the living standards of the Egyptian households.

CAPMAS started in 2010/2011 to follow a panel sample of around 40% of the total household sample size. The current survey is the second one to follow a panel sample. This procedure will provide the necessary data to extract accurate indicators on the status of the society. The CAPMAS also is pleased to disseminate the results of this survey to policy makers, researchers and scholarly to help in policy making and conducting development related researches and studies

The survey main objectives are:

• To identify expenditure levels and patterns of population as well as socio- economic and demographic differentials.

• To measure average household and per-capita expenditure for various expenditure items along with socio-economic correlates.

• To Measure the change in living standards and expenditure patterns and behavior for the individuals and households in the panel sample, previously surveyed in 2008/2009, for the first time during 12 months representing the survey period.

• To define percentage distribution of expenditure for various items used in compiling consumer price indices which is considered important indicator for measuring inflation.

• To estimate the quantities, values of commodities and services consumed by households during the survey period to determine the levels of consumption and estimate the current demand which is important to predict future demands.

• To define average household and per-capita income from different sources.

• To provide data necessary to measure standard of living for households and individuals. Poverty analysis and setting up a basis for social welfare assistance are highly dependent on the results of this survey.

• To provide essential data to measure elasticity which reflects the percentage change in expenditure for various commodity and service groups against the percentage change in total expenditure for the purpose of predicting the levels of expenditure and consumption for different commodity and service items in urban and rural areas.

• To provide data essential for comparing change in expenditure against change in income to measure income elasticity of expenditure.

• To study the relationships between demographic, geographical, housing characteristics of households and their income.

• To provide data necessary for national accounts especially in compiling inputs and outputs tables.

• To identify consumers behavior changes among socio-economic groups in urban and rural areas.

• To identify per capita food consumption and its main components of calories, proteins and fats according to its nutrition components and the levels of expenditure in both urban and rural areas.

• To identify the value of expenditure for food according to its sources, either from household production or not, in addition to household expenditure for non-food commodities and services.

• To identify distribution of households according to the possession of some appliances and equipments such as (cars, satellites, mobiles ,…etc) in urban and rural areas that enables measuring household wealth index.

• To identify the percentage distribution of income earners according to some background variables such as housing conditions, size of household and characteristics of head of household.

• To provide a time series of the most important data related to dominant standard of living from economic and social perspective. This will enable conducting comparisons based on the results of these time series. In addition to, the possibility of performing geographical comparisons.

Compared to previous surveys, the current survey experienced certain peculiarities, among which :

1- The total sample of the current survey (24.9 thousand households) is divided into two sections:

a- A new sample of 16.1 thousand households. This sample was used to study the geographic differences between urban governorates, urban and rural areas, and frontier governorates as well as other discrepancies related to households characteristics and household size, head of the household's education status, ....... etc.

b- A panel sample of 2008/2009 survey data of around 8.8 thousand households was selected to accurately study the changes that may have occurred in the households' living standards over the period between the two surveys and over time in the future since CAPMAS will continue to collect panel data for HIECS in the coming years.

2- Some additional questions that showed to be important based on previous surveys results, were added to the survey questionnaire, such as:

a- The extent of health services provided to monitor the level of services available in the Egyptian society. By collecting information on the in-kind transfers, the household received during the year; in order to monitor the assistance the household received from different sources government, association,..etc.

b- Identifying the main outlet of fabrics, clothes and footwear to determine the level of living standards of the household.

3- Quality control procedures especially for fieldwork are increased, to ensure data accuracy and avoid any errors in suitable time, as well as taking all the necessary measures to guarantee that mistakes are not repeated, with the application of the principle of reward and punishment.

The raw survey data provided by the Statistical Agency were cleaned and harmonized by the Economic Research Forum, in the context of a major project that started in 2009. During which extensive efforts have been exerted to acquire, clean, harmonize, preserve and disseminate micro data of existing household surveys in several Arab countries.

Geographic coverage

Covering a sample of urban and rural areas in all the governorates.

Analysis unit

1- Household/family. 2- Individual/person.

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 50% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)

The sample of HIECS 2012/2013 is a self-weighted two-stage stratified cluster sample, of around 24.9 households. The main elements of the sampling design are described in the following.

1- Sample Size The sample has been proportionally distributed on the governorate level between urban and rural areas, in order to make the sample representative even for small governorates. Thus, a sample of about 24863 households has been considered, and was distributed between urban and rural with the percentages of 45.4 % and 54.6, respectively. This sample is divided into two parts: a- A new sample of 16094 households selected from main enumeration areas. b- A panel sample of 8769 households (selected from HIECS 2010/2011 and the preceding survey in 2008/2009).

2- Cluster size The cluster size in the previous survey has been decreased compared to older surveys since large cluster sizes previously used were found to be too large to yield accepted design effect estimates (DEFT). As a result, it has been decided to use a cluster size of only 8 households (In HIECS 2011/2012 a cluster size of 16 households was used). While the cluster size for the panel sample was 4 households.

3- Core Sample The core sample is the master sample of any household sample required to be pulled for the purpose of studying the properties of individuals and families. It is a large sample and distributed on urban and rural areas of all governorates. It is a representative sample for the individual characteristics of the Egyptian society. This sample was implemented in January 2012 and its size reached more than 1 million household (1004800 household) selected from 5024 enumeration areas distributed on all governorates (urban/rural) proportionally with the sample size (the enumeration area size is around 200 households). The core sample is the sampling frame from which the samples for the surveys conducted by CAPMAS are pulled, such as the Labor Force Surveys, Income, Expenditure And Consumption Survey, Household Urban Migration Survey, ...etc, in addition to other samples that may be required for outsources.

New Households Sample 1000 sample areas were selected across all governorates (urban/rural) using a proportional technique with the sample size. The number

Abstract

The GLSS collected detailed information on the following topics: demographic characteristics of the population, education, health, employment, time use, migration, housing conditions and household agriculture. Consequently section four of the GLSS 6 addressed and collected information on the labor issues. It was expanded to address more representative sampling and possibly additional indicators pertaining to the northern savannah ecological zone, where a major government of Ghana initiative on Savannah Accelerated Development (SADA) had just commenced. The survey was spread over a 12-month period in order to ensure a continuous recording of household consumption, expenditures and changes occurring thereof. The specific objectives of the survey were as follows: 1. To provide information on patterns of household's consumption and expenditure at a lower level of disaggregation. 2. To serve as the basis for the construction of a new basket for the next rebasing of the Consumer Price Index. 3. To provide information for updating national accounts. 4. To provide information on household access and use of financial services. 5. To provide information that will enable credible comparison between growth rates in the northern savannah ecological zone and those in the south of Ghana. 6. To provide information on the systematic monitoring of the extent of poverty reduction in the northern savannah ecological zone. 7. Estimate the number of persons in the labor force (employed, underemployed and unemployed) and their distribution by sex, major age groups, educational level, geographical and rural/ urban spread, as well as the ecological manifestations of these, in particular, the northern savannah ecological zone which is a known source of migrant and child labor. 8. Estimate the number of child workers (or children in employment) aged 5-17 years, and its distribution by sex, major age groups, educational status, geographical, ecological and rural/urban spread, etc. 9. For both adult workers and children in employment, their distribution by status in employment, occupation and industry, as well as weekly hours worked, location of place of work, earnings, occupational injury and hazards at the work place, contractual status, informal / formal sector employment, etc. 10. Provide benchmark data needed for progress monitoring of labor policies, programs and law-making. 11. Provide up-to-date information for assessing the child labor and labor force situation. 12. Provide current child labor and labor force indicators. 13. Provide data needed for monitoring progress towards the elimination of Worst Forms of Child Labor (WFCL). 14. Estimate the prevalence of child labor (as distinct from 'children in employment' of which child labor is a subset). 15. Identify the causes and consequences of child labor in terms of socio-economic factors. 16. Establish a national database on decent work indicators, including LF and CL statistics. 17. Strengthen technical capacity of GLSS in the design and implementation of such surveys. 18. Help set targets and priorities in the fight against child labor. 19. Assess the nature and extent of child labor.

Geographic coverage

National

Analysis unit

• Household
• Indivdual
• Community

Kind of data

Sample survey data [ssd]

Sampling procedure

The sixth round of the GLSS like the previous rounds was designed to provide nationally and regionally representative indicators. It applied the same sampling methodology, a two-stage sampling procedure. In the first stage 1,200 enumeration areas (EA's) consisting of 655 (54.6%) rural EA's and 545 (45.4%) urban EA's were selected based on the 2010 Population and Housing Census, with probability proportional to size (number of households). At the second stage a fixed number of about 1,800 households were selected by systematic sampling within each of the selected enumeration areas. The fieldwork lasted twelve months and was divided into 10 cycles of 35 days. Thirty teams were involved in the data collection.

Mode of data collection

Face-to-face [f2f]

Research instrument

The GLSS was comprised of the following questionnaires: 1. Household questionnaire Part A 2. Household questionnaire Part B 3. Non- farm enterprise questionnaire 4. Rural community questionnaire 5. Price questionnaire

Abstract

Bhutan Living Standards Survey (BLSS) 2012 gathered data on household consumption expenditure, and thereby provided a means of assessing the level of poverty and well-being in Bhutan. It also collected data on the demographic characteristics of household members, household assets, credit and income, remittances, housing, access to public facilities and services, education, employment, health of household members, and prices of commodities. An additional module pertained to social capital and questions on happiness and selfrated poverty.

The survey was done to collect comprehensive socioeconomic information for use in updating the poverty profile of the country and monitoring poverty–related indicators, assessing the 10th Five-Year Plan and planning socioeconomic policy for the 11th Five-Year Plan, and updating weights required for the estimation of the consumer price index.

Geographic coverage

National

Analysis unit

• Household
• Individual
• Consumption expenditure item/ product

Universe

The survey population coverage included all households in the country except (a) diplomatic and expatriates households; (b) institutional households, i.e., residents of hotels, boarding and lodging houses, monasteries, nunneries, school hostels, orphanages, rescue homes, and under trials in jails and indoor patients of hospitals; and, (c) barracks of military and paramilitary forces, including the police.

A person not of Bhutanese nationality who has been residing in Bhutan for at least 6 months. The household of a non-Bhutanese resident who is an employee of the government or of private enterprises in Bhutan is not considered an expatriate household and is included in BLSS 2012.

Kind of data

Sample survey data [ssd]

Sampling procedure

The selection of sample households for BLSS 2012 was based on two mutually exclusive sampling frames for the rural and urban areas. Household counts for the 2005 Population and Housing Census of Bhutan (PHCB 2005) at the chiwog (village) level, updated after more recent listing activities, e.g., those for the Bhutan Multiple Indicator Survey, were used in constructing the sampling frame of primary sampling units (PSUs) for rural areas. Urban block counts from PHCB 2005, which were greatly supplemented by the NSB's household listing operations in the most densely populated urban areas in December 2011-February 2012, became the basis for the sampling frame of PSUs for the urban areas.

(Refer Section 1.3 (Survey Methodology and Sampling Design) in the final report for detail sampling design information)

Mode of data collection

Face-to-face [f2f]

Research instrument

Three main sets of schedules were used in BLSS 2012. Two sets of schedules were used in listing households for sample selection (one urban and one rural). The third set of schedules comprised the household questionnaire with 12 sections, called “blocks,” for the collection of data on household consumption expenditure, prices, and other socioeconomic variables. Each block of the questionnaire collected detailed information on a specific subject. Some blocks were further divided into subblocks according to the nature of the topic covered.

Cleaning operations

CSPro version 3.2 software was used in designing the data entry application. Twenty temporary data coders entered the data into the computer under the close supervision of NSB programmers. Computer editing, validation, and cleaning went through several stages.

Response rate

There were nonresponses despite the best efforts of the field enumerators and supervisors. After three unproductive revisits, a household was treated as unresponsive. The response rate was 93.1% overall, 91.6% for urban areas, and 94.8% for rural areas. In Reserbu town (Trashigang, urban) and Kanaldang town (Pema Gatshel, urban), both of which were included in the original sampling frame, the response rates were zero.

A major reason for nonresponse, common in both urban and rural areas according to the field staff, was failure to establish contact with any adult member of the household even after at least three attempts. Some living quarters were locked or the survey teams encountered communication problems. In rare cases, households refused to cooperate, particularly in the urban areas. When this happened, the supervisors concerned made serious efforts to obtain participation in the survey by explaining its merits to the heads of households and assuring them that the data collected and their household status would remain confidential.

(Refer Table 1.4 in the final report, response rates by urban/rural)

Geographic coverage

National coverage

Analysis unit

households/individuals

Kind of data

survey

Frequency of data collection

Yearly

Sampling procedure

Sample size:

Abstract

The Pakistan Social and Living Standards Measurement Survey (PSLM) was carried out between July 2011 and June 2012. The survey is aimed at providing detailed outcome indicators on Education, Health, Population Welfare, Water supply & Sanitation and Income & Expenditure. The data provided by this survey is used by the government in formulating the policies in social sector initiated under Poverty Reduction Strategy Paper (PRSP) and Medium Term Development Framework (MTDF) in the overall context of MDGs.

The study provides both national and provincial level findings. During this round, 15,807 households were covered across urban and rural communities. Information was collected from households on a range of social sector issues. These are primarily focussed on the sectors covered under Poverty Reduction Strategy Paper (PRSP) and monitor MDGs i.e. Education, Health, Population Welfare, Immunisation, Pre/Post Natal care, Family planning and Water supply and sanitation.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual

Universe

The universe of this survey consists of all urban and rural areas of all four provinces. Military restricted and protected areas have been excluded from the scope of the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame

Urban area: FBS has developed its own urban area frame. All urban areas comprising cities/towns have been divided into small compact areas known as enumeration blocks (E.Bs) identifiable through map. Each enumeration block comprises about 200-250 households and categorized into low, middle and high-income group, keeping in view the socio economic status of the majority of households. Urban area sampling frame consists of 26,698 enumeration blocks has been updated in 2003.

Rural area: With regard to the rural areas, the lists of villages/mouzas/dehs according to Population Census, 1998 have been used as sampling frame. In this frame, each village/mouza/deh is identifiable by its Name, Had Bast Number, Cadastral map etc. This frame is comprised of 50590 villages/mouzas.

Stratification Plan

Urban Areas: Large sized cities having population five lacs and above have been treated as independent stratum. Each of these cities has further been sub-stratified into low, middle and high income groups. The remaining cities/towns within each defunct administrative division have been grouped together to constitute an independent stratum.

Rural Areas: The entire rural domain of a district for Punjab, Sindh and KPK provinces has been considered as independent stratum, whereas in Balochistan province defunct administrative division has been treated as stratum

Sample Size and its Allocation: To determine optimum sample size for this survey, analytical studies based on the results of Pakistan Demographic Survey, Labour Force and Pakistan Integrated Households Sample Survey were undertaken. Keeping in view the variability that exists within the population for the characteristics for which estimates are to be prepared, population distribution, level of estimates and field resources available a sample of size 17,056 households to be enumerated from 1,217 PSUs (604 urban and 613 rural) has been considered sufficient to produce reliable estimates in respect of all provinces. Out of these 1,217 PSUs, 59 PSUs (19 urban and 40 rural PSUs) were dropped and the remaining 1,158 PSUs (585 urban and 573 rural) comprised of 15807 households were covered.

Sample Design: A two-stage stratified sample design has been adopted for this survey.

Selection of primary sampling Units (PSUs): Enumeration blocks in the urban domain and mouzas/dehs/villages in rural domain have been taken as primary sampling units (PSUs). In urban domain sample PSUs from each stratum have been selected by probability proportional to size (PPS) method of sampling scheme; using households in each block as measure of size (MOS). Similarly in rural areas, population of each village has been taken as MOS for selection of sample villages using probability proportional to size method of selection.

Selection of Secondary Sampling Units (SSUs): Households within each sample Primary Sampling Unit (PSU) have been considered as Secondary Sampling Units (SSUs). 16 and 12 households have been selected from each sample village and enumeration block respectively by systematic sampling scheme with a random start.

Mode of data collection

Face-to-face [f2f]

Research instrument

At both individual and household level, the PSLM Survey collects information on a wide range of topics using an integrated questionnaire. The questionnaire comprises a number of different sections, each of which looks at a particular aspect of household behavior or welfare. Data collected under Round VII includes education, diarrhea, immunization, reproductive health, pregnancy history, maternity history, family planning, pre and post-natal care and access to basic services.

Cleaning operations

Data quality in PSLM Survey has been ensured through a built in system of checking of field work by the supervisors in the field as well as teams from the headquarters. Regional/Field offices ensured the data quality through preliminary editing at their office level. The entire data entry was carried at the PBS headquarter Islamabad and the data entry programme used had a number of in built consistency checks. To determine the reliability of the estimates.

In 2024, the average monthly income per capita in Vietnam reached approximately *** million Vietnamese dong, indicating a slight increase from the previous year. 2020 and 2021 were particularly difficult years for the country’s population when per capita income decreased due to the negative impacts of the COVID-19 epidemic. Income distribution in Vietnam As a rapidly developing country in Southeast Asia, Vietnam has made significant efforts to improve income distribution among its population. One of the key factors contributing to a more balanced income distribution is Vietnam’s robust economic growth. Although the COVID-19 pandemic posed challenges to the country’s economy, Vietnam has been enjoying gradual GDP growth over the past few years, which explains the increase in job opportunities and higher wages for many Vietnamese citizens. Over the years, the Vietnamese government has implemented various policies and strategies to reduce the poverty rate and narrow the income gap in the country. However, the difference in income between urban and rural areas is inevitable. According to a governmental report in 2022, earnings per capita improved steadily across the whole country regardless of area; nonetheless, the monthly average income in urban areas was 1.5 times higher than that of their rural counterparts. Among the five major cities, Ha Noi and Ho Chi Minh City recorded the highest income per capita due to their higher living expenses compared to other areas. Monthly household expenditures in Vietnam While Vietnam has made noticeable progress in reducing poverty and improving income distribution, challenges remain in shaping the overall living standard for the population. The cost of living varies across different regions, with urban areas generally having higher expenses compared to rural areas. The largest portions of household expenditures are mainly used for nutrition, followed by housing, transportation, and healthcare. Education and entertainment also contributed to the monthly expenses, especially after the COVID-19 pandemic recovery and many restrictions were lifted in the country.

Abstract

In the past decades, Nigeria has experienced substantial gaps in producing adequate and timely data to inform policy making. In particular, the country is lagging behind in producing sufficient and accurate agricultural production statistics. The current set of household and farm surveys conducted by the NBS covers a wide range of sectors. Except for the Harmonized National Living Standard Survey (HNLSS) which covers multiple topics, these different sectors are usually covered in separate surveys none of which is conducted as a panel. As part of the efforts to continue to improve data collection and usability, the NBS has revised the content of the annual General household survey (GHS) and added a panel component. The GHS-Panel is conducted every 2 years covering multiple sectors with a focus to improve data from the agriculture sector.

The Nigeria General Hosehold Survey-Panel, is the result of a partnership that NBS has established with the Federal Ministry of Agriculture and Rural Development (FMARD), the National Food Reserve Agency (NFRA), the Bill and Melinda Gates Foundation (BMGF) and the World Bank (WB). Under this partnership, a method to collect agricultural and household data in such a way as to allow the study of agriculture's role in household welfare over time was developed. This GHS-Panel Survey responds to the needs of the country, given the dependence of a high percentage of households on agriculture activities in the country, for information on household agricultural activities along with other information on the households like human capital, other economic activities, access to services and resources. The ability to follow the same households over time, makes the GHS-Panel a new and powerful tool for studying and understanding the role of agriculture in household welfare over time as it allows analyses to be made of how households add to their human and physical capital, how education affects earnings and the role of government policies and programs on poverty, inter alia.

The objectives of the survey are as follows 1. Allowing welfare levels to be produced at the state level using small area estimation techniques resulting in state-level poverty figures 2. With the integration of the longitudinal panel survey with GHS, it will be possible to conduct a more comprehensive analysis of poverty indicators and socio-economic characteristics 3. Support the development and implementation of a Computer Assisted Personal Interview (CAPI) application for the paperless collection of GHS 4. Developing an innovative model for collecting agricultural data 5. Capacity building and developing sustainable systems for the production of accurate and timely information on agricultural households in Nigeria. 6. Active dissemination of agriculture statistics

The second wave consists of two visits to the household: the post-planting visit occurred directly after the planting season to collect information on preparation of plots, inputs used, labour used for planting and other issues related to the planting season. The post-harvest visit occurred after the harvest season and collected information on crops harvested, labour used for cultivating and harvest activities, and other issues related to the harvest cycle.

Geographic coverage

National Coverage

Analysis unit

Households

Universe

Agricultural farming household members.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample is designed to be representative at the national level as well as at the zonal (urban and rural) levels. The sample size of the GHS-Panel (unlike the full GHS) is not adequate for state-level estimates.

The sample is a two-stage probability sample:

First Stage: The Primary Sampling Units (PSUs) were the Enumeration Areas (EAs). These were selected based on probability proportional to size (PPS) of the total EAs in each state and FCT, Abuja and the total households listed in those EAs. A total of 500 EAs were selected using this method.

Second Stage: The second stage was the selection of households. Households were selected randomly using the systematic selection of ten (10) households per EA. This involved obtaining the total number of households listed in a particular EA, and then calculating a Sampling Interval (S.I) by dividing the total households listed by ten (10). The next step was to generate a random start 'r' from the table of random numbers which stands as the 1st selection. Consecutive selection of households was obtained by adding the sampling interval to the random start.

Determination of the sample size at the household level was based on the experience gained from previous rounds of the GHS, in which 10 households per EA are usually selected and give robust estimates.

In all, 500 clusters/EAs were canvassed and 5,000 households were interviewed. These samples were proportionally selected in the states such that different states had different samples sizes depending on the total number of EAs in each state.

Households were not selected using replacement. Thus the final number of household interviewed was slightly less than the 5,000 eligible for interviewing. The final number of households interviewed was 4,986 for a non-response rate of 0.3 percent. A total of 27,533 household members were interviewed. In the second, or Post-Harvest Visit, some household had moved as had individuals, thus the final number of households with data in both points of time (post planting and post harvest) is 4,851, with 27,993 household members.

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

Data Entry This survey used a concurrent data entry approach. In this method, the fieldwork and data entry were handled by each team assigned to the state. Each team consisted of a field supervisor, 2-4 interviewers and a data entry operator. Immediately after the data were collected in the field by the interviewers, the questionnaires were handed over to the supervisor to be checked and documented. At the end of each day of fieldwork, the questionnaires were then passed to the data entry operator for entry. After the questionnaires were entered, the data entry operator generated an error report which reported issues including out of range values and inconsistencies in the data. The supervisor then checked the report, determined what should be corrected, and decided if the field team needed to revisit the household to obtain additional information. The benefits of this method are that it allows one to: - Capture errors that might have been overlooked by a visual inspection only, - Identify errors early during the field work so that if any correction required a revisit to the household, it could be done while the team was still in the EA

The CSPro software was used to design the specialized data entry program that was used for the data entry of the questionnaires.

The data cleaning process was done in a number of stages. The first step was to ensure proper quality control during the fieldwork. This was achieved in part by using the concurrent data entry system which was, as explained above, designed to highlight many of the errors that occurred during the fieldwork. Errors that are caught at the fieldwork stage are corrected based on re-visits to the household on the instruction of the supervisor. The data that had gone through this first stage of cleaning was then sent from the state to the head office of NBS where a second stage of data cleaning was undertaken.

During the second stage the data were examined for out of range values and outliers. The data were also examined for missing information for required variables, sections, questionnaires and EAs. Any problems found were then reported back to the state where the correction was then made. This was an ongoing process until all data were delivered to the head office.

After all the data were received by the head office, there was an overall review of the data to identify outliers and other errors on the complete set of data. Where problems were identified, this was reported to the state. There the questionnaires were checked and where necessary the relevant households were revisited and a report sent back to the head office with the corrections.

The final stage of the cleaning process was to ensure that the household- and individual-level data sets were correctly merged across all sections of the household questionnaire. Special care was taken to see that the households included in the data matched with the selected sample and where there were differences these were properly assessed and documented. The agriculture data were also checked to ensure that the plots identified in the main sections merged with the plot information identified in the other sections. This was also done for crop- by-plot information as well.

Response rate

The response rate was very high. Response rate after field work was calculated to be 93.9% while attrition rate was 6.1% for households. During the tracking period, 52.4% of the attrition was tracked while at the end of the whole exercise, the response rate was: Post Harvest: 97.1%

Sampling error estimates

No sampling error

This statistic shows the average weekly housing costs in the United Kingdom (UK) in 2012, by tenure. In 2012, 58 percent of all households were paying between £60 and £119 housing costs per week.

Abstract copyright UK Data Service and data collection copyright owner.

Carried out every four years, the European Quality of Life Survey (EQLS) examines both the objective circumstances of European citizens' lives and how they feel about those circumstances and their lives in general. It collects data on a range of issues, such as employment, income, education, housing, family, health and work-life balance. It also looks at subjective topics, such as people's levels of happiness, life satisfaction, and perceived quality of society. By running the survey regularly, it has also become possible to track key trends in the quality of people's lives over time. Previous surveys have shown, for instance, that people are having greater difficulty making ends meet since the economic crisis began. In many countries, they also feel that there is now more tension between people from different ethnic groups. And across Europe, people now trust their governments less than they did before. However, people still continue to get the greatest satisfaction from their family life and personal relationships.

Over the years, the EQLS has developed into a valuable set of indicators which complements traditional indicators of economic growth and living standard such as GDP or income. The EQLS indicators are more inclusive of environmental and social aspects of progress and therefore are easily integrated into the decision-making process and taken up by public debate at EU and national levels in the European Union.

In each wave a sample of adult population has been selected randomly for a face to face interview. In view of the prospective European enlargements the geographical coverage of the survey has expanded over time from 28 countries in 2003 to 34 countries in 2011-12.

Further information about the survey can be found on the European Foundation for the Improvement of Living and Working Conditions (Eurofound) EQLS web pages.

For the second edition (January 2014) the data file has been updated with a new total weighting variable. See documentation for further details and see also the updated version of the EQLS integrated file, held under SN 7348).


Main Topics:

The survey covers multiple dimensions of quality of life: employment and work-life balance, income and deprivation, housing and local environment, family and social contacts, health and mental wellbeing, subjective wellbeing (e.g. happiness, life satisfaction), social exclusion, perceived quality of society (e.g. tensions, trust in institutions) as well as access to and perceived quality of public services.

Abstract

The Household Income, Expenditure and Consumption Survey (HIECS) is of great importance among other household surveys conducted by statistical agencies in various countries around the world. This survey provides a large amount of data to rely on in measuring the living standards of households and individuals, as well as establishing databases that serve in measuring poverty, designing social assistance programs, and providing necessary weights to compile consumer price indices, considered to be an important indicator to assess inflation.

The first survey that covered all the country governorates was carried out in 1958/1959 followed by a long series of similar surveys. The current survey, HIECS 2012/2013, is the eleventh in this long series.

Starting 2008/2009, Household Income, Expenditure and Consumption Surveys were conducted each two years instead of five years. This would enable better tracking of the rapid changes in the level of the living standards of the Egyptian households.

CAPMAS started in 2010/2011 to follow a panel sample of around 40% of the total household sample size. The current survey is the second one to follow a panel sample. This procedure will provide the necessary data to extract accurate indicators on the status of the society. The CAPMAS also is pleased to disseminate the results of this survey to policy makers, researchers and scholarly to help in policy making and conducting development related researches and studies

The survey main objectives are: - To identify expenditure levels and patterns of population as well as socio- economic and demographic differentials. - To measure average household and per-capita expenditure for various expenditure items along with socio-economic correlates. - To Measure the change in living standards and expenditure patterns and behavior for the individuals and households in the panel sample, previously surveyed in 2008/2009, for the first time during 12 months representing the survey period. - To define percentage distribution of expenditure for various items used in compiling consumer price indices which is considered important indicator for measuring inflation. - To estimate the quantities, values of commodities and services consumed by households during the survey period to determine the levels of consumption and estimate the current demand which is important to predict future demands. - To define average household and per-capita income from different sources. - To provide data necessary to measure standard of living for households and individuals. Poverty analysis and setting up a basis for social welfare assistance are highly dependent on the results of this survey. - To provide essential data to measure elasticity which reflects the percentage change in expenditure for various commodity and service groups against the percentage change in total expenditure for the purpose of predicting the levels of expenditure and consumption for different commodity and service items in urban and rural areas. - To provide data essential for comparing change in expenditure against change in income to measure income elasticity of expenditure. - To study the relationships between demographic, geographical, housing characteristics of households and their income. - To provide data necessary for national accounts especially in compiling inputs and outputs tables. - To identify consumers behavior changes among socio-economic groups in urban and rural areas. - To identify per capita food consumption and its main components of calories, proteins and fats according to its nutrition components and the levels of expenditure in both urban and rural areas. - To identify the value of expenditure for food according to its sources, either from household production or not, in addition to household expenditure for non-food commodities and services. - To identify distribution of households according to the possession of some appliances and equipments such as (cars, satellites, mobiles ,…etc) in urban and rural areas that enables measuring household wealth index. - To identify the percentage distribution of income earners according to some background variables such as housing conditions, size of household and characteristics of head of household. - To provide a time series of the most important data related to dominant standard of living from economic and social perspective. This will enable conducting comparisons based on the results of these time series. In addition to, the possibility of performing geographical comparisons.

Compared to previous surveys, the current survey experienced certain peculiarities, among which : 1) The total sample of the current survey (24.9 thousand households) is divided into two sections: a - A new sample of 16.1 thousand households. This sample was used to study the geographic differences between urban governorates, urban and rural areas, and frontier governorates as well as other discrepancies related to households characteristics and household size, head of the household's education status, ....... etc.

b - A panel sample of 2008/2009 survey data of around 8.8 thousand households were selected to accurately study the changes that may have occurred in the households' living standards over the period between the two surveys and over time in the future since CAPMAS will continue to collect panel data for HIECS in the coming years.

2) Some additional questions that showed to be important based on previous surveys results, were added to the survey questionnaire, such as: a - The extent of health services provided to monitor the level of services available in the Egyptian society. By collecting information on the in-kind transfers, the household received during the year; in order to monitor the assistance the household received from different sources government, association,..etc. b - Identifying the main outlet of fabrics, clothes and footwear to determine the level of living standards of the household.

3) Quality control procedures especially for fieldwork are increased, to ensure data accuracy and avoid any errors in suitable time, as well as taking all the necessary measures to guarantee that mistakes are not repeated, with the application of the principle of reward and punishment.

Geographic coverage

National coverage, covering a sample of urban and rural areas in all the governorates.

Analysis unit

• Household/family
• Individual/person

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample of HIECS 2012/2013 is a self-weighted two-stage stratified cluster sample, of around 24.9 households. The main elements of the sampling design are described in the following.

Sample Size The sample has been proportionally distributed on the governorate level between urban and rural areas, in order to make the sample representative even for small governorates. Thus, a sample of about 24863 households has been considered, and was distributed between urban and rural with the percentages of 45.4 % and 54.6, respectively. This sample is divided into two parts: a) A new sample of 16094 households selected from main enumeration areas. b) A panel sample of 8769 households (selected from HIECS 2010/2011 and the preceding survey in 2008/2009).

Cluster Size The cluster size in the previous survey has been decreased compared to older surveys since large cluster sizes previously used were found to be too large to yield accepted design effect estimates (DEFT). As a result, it has been decided to use a cluster size of only 8 households (In HIECS 2011/2012 a cluster size of 16 households was used). While the cluster size for the panel sample was 4 households.

Core Sample The core sample is the master sample of any household sample required to be pulled for the purpose of studying the properties of individuals and families. It is a large sample and distributed on urban and rural areas of all governorates. It is a representative sample for the individual characteristics of the Egyptian society. This sample was implemented in January 2012 and its size reached more than 1 million household (1004800 household) selected from 5024 enumeration areas distributed on all governorates (urban/rural) proportionally with the sample size (the enumeration area size is around 200 households). The core sample is the sampling frame from which the samples for the surveys conducted by CAPMAS are pulled, such as the Labor Force Surveys, Income, Expenditure And Consumption Survey, Household Urban Migration Survey, ...etc, in addition to other samples that may be required for outsources.

New Households Sample 1000 sample areas were selected across all governorates (urban/rural) using a proportional technique with the sample size. The number required for each governorate (urban/rural) was selected from the enumeration areas of the core sample using a systematic sampling technique.

A more detailed description of the different sampling stages and allocation of sample across governorates is provided in the Methodology document available among external resources in Arabic.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three different questionnaires have been designed as following: 1) Expenditure and Consumption Questionnaire. 2) Diary Questionnaire (Assisting questionnaire). 3) Income Questionnaire.

In designing the questionnaires of expenditure, consumption and income, we were taking into our consideration the following: - Using the recent concepts and definitions of International Labor Organization approved in the International Convention of

The Poverty and Social Exclusion in the United Kingdom project is the largest research project of its kind ever carried out in the UK. It examines levels of deprivation in the UK today. The research aims to answer the following questions:

• What are the best methods for measuring poverty, deprivation, social exclusion and standard of living?
• How are the different dimensions of poverty, deprivation and social exclusion related?
• What is the current extent and nature of poverty and how has it changed?
• What policies best address these problems?

Launched in May 2010, the project comprises four main pieces of research so far:

• Firstly, two major surveys into the public's perceptions of necessities and into living standards were carried out in 2012/13: an attitudinal UK Omnibus survey, gathering the public's perceptions of necessities and attitudes to services (held under SN 7878); and a large-scale survey of living standards to examine the nature, extent and causes of deprivation and social exclusion (SN 7879).
• In addition, two qualitative research studies have been undertaken: an investigation into the experiences of living on low income during recession in Gloucestershire, the West Midlands and Strathclyde (SN 7877); and an exploration of the role of the family when coping with poverty in Northern Ireland.

Further information about the project may be found on the Poverty and Social Exclusion project website.

The study charted Finnish opinions on welfare and inequality. The study was part of the Wellbeing and social cohesion in an unequal society (WEBE) project funded by the Academy of Finland (decision number: 252317). First, the respondents' satisfaction with their financial circumstances was charted with questions regarding, for example, whether they would want to earn more money, own more clothes, be able to eat out more often, and be able to go on holiday to exotic places more often. The respondents' self-perceived success in important areas of life, such as relationships and self-esteem, was charted next by using the Flourishing Scale (FS). The respondents were then asked about their general life satisfaction, mood, ability to achieve things and perceived status in society. Next, satisfaction with specific domains of life, such as standard of living, personal health and personal safety, was examined by using the Personal Wellbeing Index (PWI). Regarding income and personal finance, net income of the household and the ease of covering usual expenses with the income were surveyed. The respondents' perceptions regarding various different groups in Finland, for example, the homeless, immigrants, middle class, and rich, were surveyed. Some questions focused on the respondents' personal health, and they were asked, for example, whether they had had problems with moving or exercise, felt pain or suffering, or experienced fears or depression on the day the survey was conducted. The respondents were then asked to what extent they agreed or disagreed with various statements concerning work and family life, living circumstances, communities they belonged to, and environment and nature. Feelings of loneliness, depression, failure, happiness and being loved or in love in the past 12 months were charted. The respondents were also asked how well various statements described them (e.g. whether they thought people should live independently, spoke directly and openly with others, and liked talking to their neighbours). Next, the respondents were asked how much they cared about the well-being of different groups (e.g. the homeless, immigrants, refugees and asylum-seekers, children in poor families, the elderly). The respondents' opinions concerning the people living in their neighbourhood were charted and trust in other people was examined. The help the respondents received from people close to them was surveyed with questions on, for example, who helped them with practical issues and who would help them financially if they needed it. The respondents were then asked whether they thought Finnish society had offered or would offer them better or worse opportunities compared to others of the same age (e.g. in standard of living, income, hobbies and starting a family). Some questions concerned the respondents' life management, for instance, whether they ate healthy food, used alcohol or drugs, and took care of people close to them. Negative life events were surveyed with questions on whether the respondents, a family member or a friend had experienced challenging life circumstances (e.g. homelessness, substance abuse, over-indebtedness, disability). A number of statements about social assistance (the social security benefit of the last resort) and social security were presented (e.g. whether the respondents thought that many people apply for social assistance on fraudulent grounds or that EU membership is a disadvantage for social security). Finally, the respondents were asked whether differences in income, health, neighbourhoods and education were too high in Finland. Background variables included the respondent's gender, age, year of birth, marital status, household composition, type of accommodation, housing tenure, level of education, economic activity and occupational status, municipality and NUTS3 region of residence, and whether R's municipality of residence at present was the same as R's municipality of residence at birth.

Abstract

The World Bank is interested in gauging the views of clients and partners who are either involved in development in Bulgaria or who observe activities related to social and economic development. The World Bank Country Assessment Survey is meant to give the World Bank's team that works in Bulgaria, greater insight into how the Bank's work is perceived. This is one tool the World Bank uses to assess the views of its critical stakeholders. With this understanding, the World Bank hopes to develop more effective strategies, outreach and programs that support development in Bulgaria. The World Bank commissioned an independent firm to oversee the logistics of this effort in Bulgaria.

The survey was designed to achieve the following objectives: - Assist the World Bank in gaining a better understanding of how stakeholders in Bulgaria perceive the Bank; - Obtain systematic feedback from stakeholders in Bulgaria regarding: · Their views regarding the general environment in Bulgaria; · Their overall attitudes toward the World Bank in Bulgaria; · Overall impressions of the World Bank's effectiveness and results, knowledge and research, and communication and information sharing in Bulgaria; and · Perceptions of the World Bank's future role in Bulgaria. - Use data to help inform the Bulgaria country team's strategy.

Geographic coverage

National

Analysis unit

Stakeholder

Universe

Stakeholders of the World Bank in Bulgaria

Kind of data

Sample survey data [ssd]

Sampling procedure

In May and June 2012, 405 stakeholders of the World Bank in Bulgaria were invited to provide their opinions on the Bank's assistance to the country by participating in a country survey. Participants in the survey were drawn from among the office of the President or Prime Minister; the office of a Minister; the office of a Parliamentarian; employees of a ministry, ministerial department, or implementation agency; consultants/contractors working on World Bank supported projects/programs; project management units (PMUs) overseeing implementation of a project; local government officials or staff; European Commission staff or representatives; the diplomatic corps; private sector organizations; private foundations; financial sector/private banks; NGOs; the media; independent government institutions; trade unions; academia, research institutes or think tanks; and the judiciary branch.

Mode of data collection

Mail Questionnaire [mail]

Research instrument

The Questionnaire consists of 8 Sections:

A. General Issues facing Bulgaria: Respondents were asked to indicate whether Bulgaria is headed in the right direction, what they thought were the top three most important development priorities, which areas would contribute most to achieving convergence of Bulgarian living standards with the EU, and which areas would contribute most to generating economic growth.

B. Overall Attitudes toward the World Bank: Respondents were asked to rate their familiarity with the World Bank, the Bank's effectiveness in Bulgaria, the extent to which the Bank's staff is well prepared to help Bulgaria, the extent to which the Bank should seek to influence the global development agenda, their agreement with various statements regarding the Bank's work in Bulgaria, and the extent to which the Bank is an effective development partner. Respondents were also asked to indicate the sectoral areas on which it would be most productive for the Bank to focus its resources, the Bank's greatest values and greatest weaknesses in its work, the Bank instruments that are most and least effective in helping improve living standards, with which groups the Bank should work more, and to what reasons respondents attributed failed or slow reform efforts.

C. World Bank Effectiveness and Results: Respondents were asked to rate the extent to which the Bank's work helps achieve sustainable development results in Bulgaria, the extent to which the Bank meets Bulgaria's need for knowledge services and financial instruments, and the Bank's level of effectiveness across twenty development areas, such as climate change, governance, and economic growth.

D. The World Bank's Knowledge: Respondents were asked to indicate how frequently they consult World Bank knowledge and research, the areas on which the Bank should focus its research efforts and to rate the effectiveness and quality of the Bank's knowledge/research, including how significant of a contribution the Bank's knowledge and research make to development results, the technical quality of the Bank's knowledge and research, and the Bank's effectiveness at providing linkage to non-Bank expertise.

E. Working with the World Bank: Respondents were asked to rate their level of agreement with a series of statements regarding working with the Bank, such as the World Bank's "Safeguard Policy" requirements being reasonable, working with the World Bank increasing Bulgaria's institutional capacity, and the World Bank disbursing funds promptly.

F. The Future Role of the World Bank in Bulgaria: Respondents were asked to rate how significant a role the Bank should play in Bulgaria's development in the near future and to indicate what the Bank should do to make itself of greater value in Bulgaria.

G. Communication and Information Sharing: Respondents were asked to indicate where they get information about economic and social development issues, how they prefer to receive information from the Bank, their access to the Internet, and their usage and evaluation of the Bank's website. Respondents were asked about their awareness of the Bank's Access to Information policy, past information requests from the Bank, and their level of agreement that they use more data from the World Bank as a result of the Bank's Open Data policy. Respondents were also asked their level of agreement that they know how to find information from the Bank and that the Bank is responsive to information requests.

H. Background Information: Respondents were asked to indicate their current position, specialization, whether they professionally collaborate with the World Bank, their exposure to the Bank in Bulgaria, and their geographic location.

Response rate

A total of 173 stakeholders participated in the country survey (43% response rate).