West Virginia and Kansas had the lowest cost of living across all U.S. states, with composite costs being half of those found in Hawaii. This was according to a composite index that compares prices for various goods and services on a state-by-state basis. In West Virginia, the cost of living index amounted to **** — well below the national benchmark of 100. Virginia— which had an index value of ***** — was only slightly above that benchmark. Expensive places to live included Hawaii, Massachusetts, and California. Housing costs in the U.S. Housing is usually the highest expense in a household’s budget. In 2023, the average house sold for approximately ******* U.S. dollars, but house prices in the Northeast and West regions were significantly higher. Conversely, the South had some of the least expensive housing. In West Virginia, Mississippi, and Louisiana, the median price of the typical single-family home was less than ******* U.S. dollars. That makes living expenses in these states significantly lower than in states such as Hawaii and California, where housing is much pricier. What other expenses affect the cost of living? Utility costs such as electricity, natural gas, water, and internet also influence the cost of living. In Alaska, Hawaii, and Connecticut, the average monthly utility cost exceeded *** U.S. dollars. That was because of the significantly higher prices for electricity and natural gas in these states.

Abstract

In 1992, Bosnia-Herzegovina, one of the six republics in former Yugoslavia, became an independent nation. A civil war started soon thereafter, lasting until 1995 and causing widespread destruction and losses of lives. Following the Dayton accord, BosniaHerzegovina (BiH) emerged as an independent state comprised of two entities, namely, the Federation of Bosnia-Herzegovina (FBiH) and the Republika Srpska (RS), and the district of Brcko. In addition to the destruction caused to the physical infrastructure, there was considerable social disruption and decline in living standards for a large section of the population. Alongside these events, a period of economic transition to a market economy was occurring. The distributive impacts of this transition, both positive and negative, are unknown. In short, while it is clear that welfare levels have changed, there is very little information on poverty and social indicators on which to base policies and programs. In the post-war process of rebuilding the economic and social base of the country, the government has faced the problems created by having little relevant data at the household level. The three statistical organizations in the country (State Agency for Statistics for BiH -BHAS, the RS Institute of Statistics-RSIS, and the FBiH Institute of Statistics-FIS) have been active in working to improve the data available to policy makers: both at the macro and the household level. One facet of their activities is to design and implement a series of household series. The first of these surveys is the Living Standards Measurement Study survey (LSMS). Later surveys will include the Household Budget Survey (an Income and Expenditure Survey) and a Labour Force Survey. A subset of the LSMS households will be re-interviewed in the two years following the LSMS to create a panel data set.

The three statistical organizations began work on the design of the Living Standards Measurement Study Survey (LSMS) in 1999. The purpose of the survey was to collect data needed for assessing the living standards of the population and for providing the key indicators needed for social and economic policy formulation. The survey was to provide data at the country and the entity level and to allow valid comparisons between entities to be made. The LSMS survey was carried out in the Fall of 2001 by the three statistical organizations with financial and technical support from the Department for International Development of the British Government (DfID), United Nations Development Program (UNDP), the Japanese Government, and the World Bank (WB). The creation of a Master Sample for the survey was supported by the Swedish Government through SIDA, the European Commission, the Department for International Development of the British Government and the World Bank. The overall management of the project was carried out by the Steering Board, comprised of the Directors of the RS and FBiH Statistical Institutes, the Management Board of the State Agency for Statistics and representatives from DfID, UNDP and the WB. The day-to-day project activities were carried out by the Survey Management Team, made up of two professionals from each of the three statistical organizations. The Living Standard Measurement Survey LSMS, in addition to collecting the information necessary to obtain a comprehensive as possible measure of the basic dimensions of household living standards, has three basic objectives, as follows: 1. To provide the public sector, government, the business community, scientific institutions, international donor organizations and social organizations with information on different indicators of the population's living conditions, as well as on available resources for satisfying basic needs. 2. To provide information for the evaluation of the results of different forms of government policy and programs developed with the aim to improve the population's living standard. The survey will enable the analysis of the relations between and among different aspects of living standards (housing, consumption, education, health, labour) at a given time, as well as within a household. 3. To provide key contributions for development of government's Poverty Reduction Strategy Paper, based on analysed data.

Geographic coverage

National coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

(a) SAMPLE SIZE A total sample of 5,400 households was determined to be adequate for the needs of the survey: with 2,400 in the Republika Srpska and 3,000 in the Federation of BiH. The difficulty was in selecting a probability sample that would be representative of the country's population. The sample design for any survey depends upon the availability of information on the universe of households and individuals in the country. Usually this comes from a census or administrative records. In the case of BiH the most recent census was done in 1991. The data from this census were rendered obsolete due to both the simple passage of time but, more importantly, due to the massive population displacements that occurred during the war. At the initial stages of this project it was decided that a master sample should be constructed. Experts from Statistics Sweden developed the plan for the master sample and provided the procedures for its construction. From this master sample, the households for the LSMS were selected. Master Sample [This section is based on Peter Lynn's note "LSMS Sample Design and Weighting - Summary". April, 2002. Essex University, commissioned by DfID.] The master sample is based on a selection of municipalities and a full enumeration of the selected municipalities. Optimally, one would prefer smaller units (geographic or administrative) than municipalities. However, while it was considered that the population estimates of municipalities were reasonably accurate, this was not the case for smaller geographic or administrative areas. To avoid the error involved in sampling smaller areas with very uncertain population estimates, municipalities were used as the base unit for the master sample. The Statistics Sweden team proposed two options based on this same method, with the only difference being in the number of municipalities included and enumerated.

(b) SAMPLE DESIGN For reasons of funding, the smaller option proposed by the team was used, or Option B. Stratification of Municipalities The first step in creating the Master Sample was to group the 146 municipalities in the country into three strata- Urban, Rural and Mixed - within each of the two entities. Urban municipalities are those where 65 percent or more of the households are considered to be urban, and rural municipalities are those where the proportion of urban households is below 35 percent. The remaining municipalities were classified as Mixed (Urban and Rural) Municipalities. Brcko was excluded from the sampling frame. Urban, Rural and Mixed Municipalities: It is worth noting that the urban-rural definitions used in BiH are unusual with such large administrative units as municipalities classified as if they were completely homogeneous. Their classification into urban, rural, mixed comes from the 1991 Census which used the predominant type of income of households in the municipality to define the municipality. This definition is imperfect in two ways. First, the distribution of income sources may have changed dramatically from the pre-war times: populations have shifted, large industries have closed, and much agricultural land remains unusable due to the presence of land mines. Second, the definition is not comparable to other countries' where villages, towns and cities are classified by population size into rural or urban or by types of services and infrastructure available. Clearly, the types of communities within a municipality vary substantially in terms of both population and infrastructure. However, these imperfections are not detrimental to the sample design (the urban/rural definition may not be very useful for analysis purposes, but that is a separate issue).

Mode of data collection

Face-to-face [f2f]

Cleaning operations

(a) DATA ENTRY

An integrated approach to data entry and fieldwork was adopted in Bosnia and Herzegovina. Data entry proceeded side by side with data gathering to ensure verification and correction in the field. Data entry stations were located in the regional offices of the entity institutes and were equipped with computers, modem and a dedicated telephone line. The completed questionnaires were delivered to these stations each day for data entry. Twenty data entry operators (10 from Federation and 10 from RS) were trained in two training sessions held for a week each in Sarajevo and Banja Luka. The trainers were the staff of the two entity institutes who had undergone training in the CSPro software earlier and had participated in the workshops of the Pilot survey. Prior to the training, laptop computers were provided to the entity institutes, and the CSPro software was installed in them. The training for the data entry operators covered the following elements:

• Introduction to the LSMS Survey questionnaire; Introduction to the personal computers/ lap top computers; Copying data on diskette and printing of output
• The Data entry programme (CSPro). Understanding of the Round 1 data entry screens (Modules 1-10)
• Practice of Round 1 (data entry trainees enter questionnaires completed by interviewer trainees during practice interviews)
• Understanding of Round 2 Data entry screen (Modules 11-13)
• Practice of Round 2 Data entry screens (data entry trainees entered the questionnaires completed by interviewer trainees)
• Control Procedures; Copying

Quality of life is a measure of comfort, health, and happiness by a person or a group of people. Quality of life is determined by both material factors, such as income and housing, and broader considerations like health, education, and freedom. Each year, US & World News releases its “Best States to Live in” report, which ranks states on the quality of life each state provides its residents. In order to determine rankings, U.S. News & World Report considers a wide range of factors, including healthcare, education, economy, infrastructure, opportunity, fiscal stability, crime and corrections, and the natural environment. More information on these categories and what is measured in each can be found below:

Healthcare includes access, quality, and affordability of healthcare, as well as health measurements, such as obesity rates and rates of smoking. Education measures how well public schools perform in terms of testing and graduation rates, as well as tuition costs associated with higher education and college debt load. Economy looks at GDP growth, migration to the state, and new business. Infrastructure includes transportation availability, road quality, communications, and internet access. Opportunity includes poverty rates, cost of living, housing costs and gender and racial equality. Fiscal Stability considers the health of the government's finances, including how well the state balances its budget. Crime and Corrections ranks a state’s public safety and measures prison systems and their populations. Natural Environment looks at the quality of air and water and exposure to pollution.

Abstract

The main objectives of the 2018/19 NLSS are: i) to provide critical information for production of a wide range of socio-economic and demographic indicators, including for benchmarking and monitoring of SDGs; ii) to monitor progress in population's welfare; iii) to provide statistical evidence and measure the impact on households of current and anticipated government policies. In addition, the 2018/19 NLSS could be utilized to improve other non-survey statistical information, e.g. to determine and calibrate the contribution of final consumption expenditures of households to GDP; to update the weights and determine the basket for the national Consumer Price Index (CPI); to improve the methodology and dissemination of micro-economic and welfare statistics in Nigeria.

The 2018/19 NLSS collected a comprehensive and diverse set of socio-economic and demographic data pertaining to the basic needs and conditions under which households live on a day to day basis. The 2018/19 NLSS questionnaire includes wide-ranging modules, covering demographic indicators, education, health, labour, expenditures on food and non-food goods, non-farm enterprises, household assets and durables, access to safety nets, housing conditions, economic shocks, exposure to crime and farm production indicators.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING PROCEDURE The 2018/19 NLSS sample is designed to provide representative estimates for the 36 states and the Federal Capital Territory (FCT), Abuja. By extension. The sample is also representative at the national and zonal levels. Although the sample is not explicitly stratified by urban and rural areas, it is possible to obtain urban and rural estimates from the NLSS data at the national level. At all stages, the relative proportion of urban and rural EAs as has been maintained. Before designing the sample for the 2018/19 NLSS, the results from the 2009/10 HNLSS were analysed to extract the sampling properties (variance, design effect, etc.) and estimate the required sample size to reach a desired precision for poverty estimates in the 2018/19 NLSS.

EA SELECTION: The sampling frame for the 2018/19 NLSS was based on the national master sample developed by the NBS, referred to as the NISH2 (Nigeria Integrated Survey of Households 2). This master sample was based on the enumeration areas (EAs) defined for the 2006 Nigeria Census Housing and Population conducted by National Population Commission (NPopC). The NISH2 was developed by the NBS to use as a frame for surveys with state-level domains. NISH2 EAs were drawn from another master sample that NBS developed for surveys with LGA-level domains (referred to as the “LGA master sample”). The NISH2 contains 200 EAs per state composed of 20 replicates of 10 sample EAs for each state, selected systematically from the full LGA master sample. Since the 2018/19 NLSS required domains at the state-level, the NISH2 served as the sampling frame for the survey. Since the NISH2 is composed of state-level replicates of 10 sample EAs, a total of 6 replicates were selected from the NISH2 for each state to provide a total sample of 60 EAs per state. The 6 replicates selected for the 2018/19 NLSS in each state were selected using random systematic sampling. This sampling procedure provides a similar distribution of the sample EAs within each state as if one systematic sample of 60 EAs had been selected directly from the census frame of EAs.

A fresh listing of households was conducted in the EAs selected for the 2018/19 NLSS. Throughout the course of the listing, 139 of the selected EAs (or about 6%) were not able to be listed by the field teams. The primary reason the teams were not able to conduct the listing in these EAs was due to security issues in the country. The fieldwork period of the 2018/19 NLSS saw events related to the insurgency in the north east of the country, clashes between farmers and herdsman, and roving groups of bandits. These events made it impossible for the interviewers to visit the EAs in the villages and areas affected by these conflict events. In addition to security issues, some EAs had been demolished or abandoned since the 2006 census was conducted. In order to not compromise the sample size and thus the statistical power of the estimates, it was decided to replace these 139 EAs. Additional EAs from the same state and sector were randomly selected from the remaining NISH2 EAs to replace each EA that could not be listed by the field teams. This necessary exclusion of conflict affected areas implies that the sample is representative of areas of Nigeria that were accessible during the 2018/19 NLSS fieldwork period. The sample will not reflect conditions in areas that were undergoing conflict at that time. This compromise was necessary to ensure the safety of interviewers.

HOUSEHOLD SELECTION: Following the listing, the 10 households to be interviewed were selected from the listed households. These households were selected systemically after sorting by the order in which the households were listed. This systematic sampling helped to ensure that the selected households were well dispersed across the EA and thereby limit the potential for clustering of the selected households within an EA. Occasionally, interviewers would encounter selected households that were not able to be interviewed (e.g. due to migration, refusal, etc.). In order to preserve the sample size and statistical power, households that could not be interviewed were replaced with an additional randomly selected household from the EA. Replacement households had to be requested by the field teams on a case-by-case basis and the replacement household was sent by the CAPI managers from NBS headquarters. Interviewers were required to submit a record for each household that was replaced, and justification given for their replacement. These replaced households are included in the disseminated data. However, replacements were relatively rare with only 2% of sampled households not able to be interviewed and replaced.

Sampling deviation

Although a sample was initially drawn for Borno state, the ongoing insurgency in the state presented severe challenges in conducting the survey there. The situation in the state made it impossible for the field teams to reach large areas of the state without compromising their safety. Given this limitation it was clear that a representative sample for Borno was not possible. However, it was decided to proceed with conducting the survey in areas that the teams could access in order to collect some information on the parts of the state that were accessible.

The limited area that field staff could safely operate in in Borno necessitated an alternative sample selection process from the other states. The EA selection occurred in several stages. Initially, an attempt was made to limit the frame to selected LGAs that were considered accessible. However, after selection of the EAs from the identified LGAs, it was reported by the NBS listing teams that a large share of the selected EAs were not safe for them to visit. Therefore, an alternative approach was adopted that would better ensure the safety of the field team but compromise further the representativeness of the sample. First, the list of 788 EAs in the LGA master sample for Borno were reviewed by NBS staff in Borno and the EAs they deemed accessible were identified. The team identified 359 EAs (46%) that were accessible. These 359 EAs served as the frame for the Borno sample and 60 EAs were randomly selected from this frame. However, throughout the course of the NLSS fieldwork, additional insurgency related events occurred which resulted in 7 of the 60 EAs being inaccessible when they were to be visited. Unlike for the main sample, these EAs were not replaced. Therefore, 53 EAs were ultimately covered from the Borno sample. The listing and household selection process that followed was the same as for the rest of the states.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Two sets of questionnaires – household and community – were used to collect information in the NLSS2018/19. The Household Questionnaire was administered to all households in the sample. The Community Questionnaire was administered to the community to collect information on the socio-economic indicators of the enumeration areas where the sample households reside.

Household Questionnaire: The Household Questionnaire provides information on demographics; education; health; labour; food and non-food expenditure; household nonfarm income-generating activities; food security and shocks; safety nets; housing conditions; assets; information and communication technology; agriculture and land tenure; and other sources of household income.

Community Questionnaire: The Community Questionnaire solicits information on access to transported and infrastructure; community organizations; resource management; changes in the community; key events; community needs, actions and achievements; and local retail price information.

Cleaning operations

CAPI: The 2018/19 NLSS was conducted using the Survey Solutions Computer Assisted Person Interview (CAPI) platform. The Survey Solutions software was developed and maintained by the Development Economics Data Group (DECDG) at the World Bank. Each interviewer and supervisor was given a tablet which they used to

Abstract

In the implementation of the Party and State policy “Doi moi”, the General Statistical Office (GSO) has conducted many household living standards survey to collect information on the living standards of all social societies to serve policy-making and socio-economic development planning.

From 2002 to 2010, VHLSS are to be conducted (in every two- year) to monitor systematically the living standard of Vietnam's societies and at the same time, to exercise the monitoring and assessment of the implementation of the Comprehensive Poverty Alleviation and Growth Strategy defined in Country Strategy Paper approved by the Government Prime Minister. In addition, these surveys also serve the evaluation of realization of the Millennium Development Goals (MDGs) and the Socio-economic Development Goals set out by Vietnamese Government.

The 2002 VHLSS included all the keynote contents reflecting the living standards of the population and the basic socio-economic condition of communes/wards that might affect the living standards of the local people. As regards households, it collected data in relation to demographic characteristics of the household members, the education background, professional/ technical level of each member, income, expenditures, use of medical facilities of all kinds, employment, housing and amenity as possession, personal effects, utilities (power and water supply), sanitation and participation in the poverty alleviation programme.

As regards communes/wards, it collected a wide rage of information related to demography, nationality, infrastructure, farming, production promotion conditions, non-farming activity and law and order.

Household questionnaires and communes/wards questionnaires of the 2002 VHLSS were designed more scientifically to ensure feasibility. They had been, in fact, piloted in Bac Ninh, Binh Dinh and Dong Nai provinces prior to the actual survey.

Survey sample were selected, based on the Population and Housing Census 1999. The sample size included 75.000 households representative of the whole country, urban and rural area and 61 provinces. Survey samples were sub-divided into 4 minor samples for the quarterly surveys in 2002 for more thorough data collection in anticipation of the harvests that might somehow get in the way. To provide information on assessment of the living standards in 2001-2002, GSO developed and released the detailed results of the 2002 VHLSS, including relevant statistics and initial analysis. Expenditure related data were synthesized from samples of 30.000 households; others, from samples of 45.000 households.

To bring out the changes in the living standards, the 2002 VHLSS results were compared with the results obtained from other living standards surveys, e.g. the 1992-1993 living standards survey (1993 VLSS), the 1993 rich-poor status survey (1993 RPSS), the 1997-1998 living standards surveys (1998 VLSS), the Multipurpose household surveys throughout 1994 to 1997 and 1999 (MHPS)

The data on demography, labor, and employment ect… were collected from the 2002 VHLSS, not replace all the data already released from the surveys conducted in this area, but to shed more light on and make more on insightful analyses of the factors affecting the living standards.

Geographic coverage

National

Analysis unit

• Household
• Individual
• Community
• Consumption expenditure item/product

Kind of data

Sample survey data [ssd]

Sampling procedure

Vietnam household living standard survey 2002 was selected, based on the Population and Housing Census 1999. The sample size included 75.000 households representative of the whole country, urban and rural area and 61 provinces. Survey samples were sub-divided into 4 minor samples for the quarterly surveys in 2002 for more thorough data collection in anticipation of the harvests that might somehow get in the way.

Survey sample were designed by 2 samples: one big sample (45,000 households) which mostly concentrated on income of households to assess living standard for national, regional and provincial levels ; one smaller sample (30,000 households) with both information about income and expenditure to evaluate intensive living standard at central and provincial levels. Following are detail contents :

• Implementing survey in 2002 with income and expenditure questionnaire of 30,000 household sample (Income and expenditure survey). This sample was divided into 4 smaller ones, with 7,500 households of each which conducted in first month of four quarters in 2002 respectively. The 30,000 household sample showed estimations at national and regional levels for 2001-2002.

• In the first six months of 2002, survey was implemented on all sections, except for expenditure section (in Income and expenditure survey) for 45,000 household sample (Income survey). This sample was divided into 2 small samples with 22,500 households of each and conducted in quarter I, II/2002 respectively. Survey of 45,000 household sample combined with 15,000 households of Income and expenditure survey (30,000 household sample) which conducted in the first month in quarter I, II/2002 to establish one 60,000 household sample that showed estimations for national, regional and provincial levels for 2001.

The detail is shown as following:

Collecting data perriod Income and expenditure survey Income survey Total Total 30,000 45,000 75,000

Divided into : QI/2002 7,500 22,500 30,000 QII/2002 7,500 22,500 30,000 QIII/2002 7,500 7,500 QIV/2002 7,500 7,500

Mode of data collection

Face-to-face [f2f]

Research instrument

VLSS 2002 used 3 questionnaires: - Short household questionnaire (excluded most of consumption expenditure information) - Long household questionnaire (including detail consumption expenditure information) - Commune questionnaire

The household questionnaire contains 9 sections each of which covered a separate aspects of household activity. Here are sections: 1. Household Roster 2. Education 3. Employment 4. Health 5. Income and Household Production 6. Expenditure (collected only for long questionnaire) 7. Durable Good and Asset 8. Housing 9. Participation in Poverty Reduction Programs

The commune questionnaire includes 9 sections and was administered by the team leader and completed with the help of village chiefs, teachers, government officials and health care workers. The questionnaire was administered in both rural and urban areas but some section was only collected in rural area such as non-farm employment opportunities and infrastructure and transportation. Here are commune questionnaire sections: 0. Survey Information 1. Main Characteristics of The Commune/ Ward 2. General Economic Conditions and Aid Programs 3. Non-Farm Employment Opportunities 4. Agriculture 5. Physical Infrastructure and Transportation 6. Education 7. Health 8. Public Disorder and Other Social Affairs

According to a survey conducted in 2021, 40 percent of the Hungarian population believed that the living conditions at their settlement would get worse if the opposition won the next elections. Only 21 percent of the respondents thought that the living conditions would improve in case of a change of government.

Abstract

The principal objective of this survey is to collect basic data reflecting the actual living conditions of the population in Tajikistan. These data will then be used for evaluating socio-economic development and formulating policies to improve living conditions.

The first assessment of living standards in Tajikistan was conducted in 1999. This assessment is bringing about data in order to update the 1999 assessment.

The survey collects information on education, health, employment and other productive activities, demographic characteristics, migration, housing conditions, expenditures and assets.

The information gathered is intended to improve economic and social policy in Tajikistan. It should enable decision-makers to 1) identify target groups for government assistance, 2) inform programs of socio-economic development, and 3) analyse the impact of decisions already made and the current economic conditions on households.

Geographic coverage

National coverage. The 2003 data are representative at the regional level (4 regions) and urban/rural.

Analysis unit

• Households
• Individuals
• Communites

Kind of data

Sample survey data [ssd]

Sampling procedure

The Tajikistan Living Standards Survey (TLSS) for 2003 was based on a stratified random probability sample, with the sample stratified according to oblast and urban/rural settlements and with the share of each strata in the overall sample being in proportion to its share in the total number of households as recorded in the 2000 Census. The same approach was used in the TLSS 1999 although there were some differences in the sampling. First the share of each strata in the overall sample in 1999 was determined according to 'best estimates', as it was conducted prior to the 2000 Census. Second the TLSS 2003 over-sampled by 40 percent in Dushanbe, 300 percent in rural Gorno-Badakhshan Administrative Oblast (GBAO) and 600 percent in urban GBAO. Third the sample size was increased in 2003 in comparison with 1999 in order to reduce sampling error. In 2003, the overall sample size was 4,156 households compared with 2,000 households in 1999. [Note: Taken from "Republic of Tajikistan: Poverty Assessment Update", Report No. 30853, Human Development Sector Unit, Central Asia Country Unit, Europe and Central Asia Region, World Bank, January 2005.]

In addition to the capital city of Dushanbe, the country has several oblasts (regions): (i) Khatlon (comprising Kurban-Tube and Khulyab), which is an agricultural area with most of the country's cotton growing districts; (ii) the Rayons of Republican Subordination (RRS) with the massive aluminum smelter in the west and agricultural valleys in the east growing crops other than cotton; (iii) Sugd which is the most industrialized oblast; and (iv) Gorno-Badakhshan Administrative Oblast which is mountainous and remote with a small population.

The 2003 data are representative at the regional level (4 regions) and urban/rural.

Mode of data collection

Face-to-face [f2f]

The VHLSS 2010 was conducted nationwide with a sample size of 69,360 households in 3,133 communes/wards which were representative at national, regional, urban, rural and provincial levels. The survey collected information during four periods, each period in one quarter from the second quarter to the forth quarter in 2010 and one period in the first quarter of 2011 through face-to-face interviews conducted by interviewers with household heads and key commune officials in communes containing sample enumeration areas. The survey collected information to be a base for assessment of living standard, poverty and the gap between the rich and the poor serving for policy making, planning and national targeted programs of the party and the State in order to continuously improve the living standard of citizen across the country, in all regions and localities

Out of all 50 states, New York had the highest per-capita real gross domestic product (GDP) in 2023, at 90,730 U.S. dollars, followed closely by Massachusetts. Mississippi had the lowest per-capita real GDP, at 39,102 U.S. dollars. While not a state, the District of Columbia had a per capita GDP of more than 214,000 U.S. dollars. What is real GDP? A country’s real GDP is a measure that shows the value of the goods and services produced by an economy and is adjusted for inflation. The real GDP of a country helps economists to see the health of a country’s economy and its standard of living. Downturns in GDP growth can indicate financial difficulties, such as the financial crisis of 2008 and 2009, when the U.S. GDP decreased by 2.5 percent. The COVID-19 pandemic had a significant impact on U.S. GDP, shrinking the economy 2.8 percent. The U.S. economy rebounded in 2021, however, growing by nearly six percent. Why real GDP per capita matters Real GDP per capita takes the GDP of a country, state, or metropolitan area and divides it by the number of people in that area. Some argue that per-capita GDP is more important than the GDP of a country, as it is a good indicator of whether or not the country’s population is getting wealthier, thus increasing the standard of living in that area. The best measure of standard of living when comparing across countries is thought to be GDP per capita at purchasing power parity (PPP) which uses the prices of specific goods to compare the absolute purchasing power of a countries currency.

Abstract

The study included four separate surveys:

1. The LSMS survey of general population of Serbia in 2002

2. The survey of Family Income Support (MOP in Serbian) recipients in 2002 These two datasets are published together separately from the 2003 datasets.

3. The LSMS survey of general population of Serbia in 2003 (panel survey)

4. The survey of Roma from Roma settlements in 2003 These two datasets are published together.

Objectives

LSMS represents multi-topical study of household living standard and is based on international experience in designing and conducting this type of research. The basic survey was carried out in 2002 on a representative sample of households in Serbia (without Kosovo and Metohija). Its goal was to establish a poverty profile according to the comprehensive data on welfare of households and to identify vulnerable groups. Also its aim was to assess the targeting of safety net programs by collecting detailed information from individuals on participation in specific government social programs. This study was used as the basic document in developing Poverty Reduction Strategy (PRS) in Serbia which was adopted by the Government of the Republic of Serbia in October 2003.

The survey was repeated in 2003 on a panel sample (the households which participated in 2002 survey were re-interviewed).

Analysis of the take-up and profile of the population in 2003 was the first step towards formulating the system of monitoring in the Poverty Reduction Strategy (PRS). The survey was conducted in accordance with the same methodological principles used in 2002 survey, with necessary changes referring only to the content of certain modules and the reduction in sample size. The aim of the repeated survey was to obtain panel data to enable monitoring of the change in the living standard within a period of one year, thus indicating whether there had been a decrease or increase in poverty in Serbia in the course of 2003. [Note: Panel data are the data obtained on the sample of households which participated in the both surveys. These data made possible tracking of living standard of the same persons in the period of one year.]

Along with these two comprehensive surveys, conducted on national and regional representative samples which were to give a picture of the general population, there were also two surveys with particular emphasis on vulnerable groups. In 2002, it was the survey of living standard of Family Income Support recipients with an aim to validate this state supported program of social welfare. In 2003 the survey of Roma from Roma settlements was conducted. Since all present experiences indicated that this was one of the most vulnerable groups on the territory of Serbia and Montenegro, but with no ample research of poverty of Roma population made, the aim of the survey was to compare poverty of this group with poverty of basic population and to establish which categories of Roma population were at the greatest risk of poverty in 2003. However, it is necessary to stress that the LSMS of the Roma population comprised potentially most imperilled Roma, while the Roma integrated in the main population were not included in this study.

Geographic coverage

The surveys were conducted on the whole territory of Serbia (without Kosovo and Metohija).

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample frame for both surveys of general population (LSMS) in 2002 and 2003 consisted of all permanent residents of Serbia, without the population of Kosovo and Metohija, according to definition of permanently resident population contained in UN Recommendations for Population Censuses, which were applied in 2002 Census of Population in the Republic of Serbia. Therefore, permanent residents were all persons living in the territory Serbia longer than one year, with the exception of diplomatic and consular staff.

The sample frame for the survey of Family Income Support recipients included all current recipients of this program on the territory of Serbia based on the official list of recipients given by Ministry of Social affairs.

The definition of the Roma population from Roma settlements was faced with obstacles since precise data on the total number of Roma population in Serbia are not available. According to the last population Census from 2002 there were 108,000 Roma citizens, but the data from the Census are thought to significantly underestimate the total number of the Roma population. However, since no other more precise data were available, this number was taken as the basis for estimate on Roma population from Roma settlements. According to the 2002 Census, settlements with at least 7% of the total population who declared itself as belonging to Roma nationality were selected. A total of 83% or 90,000 self-declared Roma lived in the settlements that were defined in this way and this number was taken as the sample frame for Roma from Roma settlements.

Planned sample: In 2002 the planned size of the sample of general population included 6.500 households. The sample was both nationally and regionally representative (representative on each individual stratum). In 2003 the planned panel sample size was 3.000 households. In order to preserve the representative quality of the sample, we kept every other census block unit of the large sample realized in 2002. This way we kept the identical allocation by strata. In selected census block unit, the same households were interviewed as in the basic survey in 2002. The planned sample of Family Income Support recipients in 2002 and Roma from Roma settlements in 2003 was 500 households for each group.

Sample type: In both national surveys the implemented sample was a two-stage stratified sample. Units of the first stage were enumeration districts, and units of the second stage were the households. In the basic 2002 survey, enumeration districts were selected with probability proportional to number of households, so that the enumeration districts with bigger number of households have a higher probability of selection. In the repeated survey in 2003, first-stage units (census block units) were selected from the basic sample obtained in 2002 by including only even numbered census block units. In practice this meant that every second census block unit from the previous survey was included in the sample. In each selected enumeration district the same households interviewed in the previous round were included and interviewed. On finishing the survey in 2003 the cases were merged both on the level of households and members.

Stratification: Municipalities are stratified into the following six territorial strata: Vojvodina, Belgrade, Western Serbia, Central Serbia (Šumadija and Pomoravlje), Eastern Serbia and South-east Serbia. Primary units of selection are further stratified into enumeration districts which belong to urban type of settlements and enumeration districts which belong to rural type of settlement.

The sample of Family Income Support recipients represented the cases chosen randomly from the official list of recipients provided by Ministry of Social Affairs. The sample of Roma from Roma settlements was, as in the national survey, a two-staged stratified sample, but the units in the first stage were settlements where Roma population was represented in the percentage over 7%, and the units of the second stage were Roma households. Settlements are stratified in three territorial strata: Vojvodina, Beograd and Central Serbia.

Mode of data collection

Face-to-face [f2f]

Research instrument

In all surveys the same questionnaire with minimal changes was used. It included different modules, topically separate areas which had an aim of perceiving the living standard of households from different angles. Topic areas were the following: 1. Roster with demography. 2. Housing conditions and durables module with information on the age of durables owned by a household with a special block focused on collecting information on energy billing, payments, and usage. 3. Diary of food expenditures (weekly), including home production, gifts and transfers in kind. 4. Questionnaire of main expenditure-based recall periods sufficient to enable construction of annual consumption at the household level, including home production, gifts and transfers in kind. 5. Agricultural production for all households which cultivate 10+ acres of land or who breed cattle. 6. Participation and social transfers module with detailed breakdown by programs 7. Labour Market module in line with a simplified version of the Labour Force Survey (LFS), with special additional questions to capture various informal sector activities, and providing information on earnings 8. Health with a focus on utilization of services and expenditures (including informal payments) 9. Education module, which incorporated pre-school, compulsory primary education, secondary education and university education. 10. Special income block, focusing on sources of income not covered in other parts (with a focus on remittances).

Response rate

During field work, interviewers kept a precise diary of interviews, recording both successful and unsuccessful visits. Particular attention was paid to reasons why some households were not interviewed. Separate marks were given for households which were not interviewed due to refusal and for cases when a given household could not be found on the territory of the chosen census block.

In 2002 a total of 7,491 households were contacted. Of this number a total of 6,386 households in 621 census rounds were interviewed. Interviewers did not manage to collect the data for 1,106 or 14.8% of selected households. Out of this number 634 households

The Tajik Living Standards Survey (TLSS) was conducted jointly by the State Statistical Agency and the Center for Strategic Studies under the Office of the President in collaboration with the sponsors, the United Nations Development Programme (UNDP) and the World Bank (WB). International technical assistance was provided by a team from the London School of Economics (LSE). The purpose of the survey is to provide quantitative data at the individual, household and community level that will facilitate purposeful policy design on issues of welfare and living standards of the population of the Republic of Tajikistan in 1999.

How widely are the benefits of economic growth shared in advanced societies? Do the rich capture the gains of growth, with little or no improvement in the living standards of the middle? Is growth raising the incomes of the poor so that they keep pace with the middle, or is the gap between rich and poor closing? Addressing these questions requires careful analysis of both the growth and distributional aspects of incomes. This article looks at the growth of disposable incomes – incomes after the redistribution through the state – over time. We rely on the Incomes across the Distribution Database put together by researchers Brian Nolan, Stefan Thewissen, and Max Roser. This data set is directly available for download: Data and data description.

The data source for our database is the microdata published by the Luxembourg Income Study (LIS) Database. You can also access our database via the website of the LIS: Cross-National Data Center in Luxembourg.

Changing living standards

LEBEN IN EUROPA is the name of the German survey conducted within the scope of the Community statistics on income and living conditions (EU-SILC) conducted all over Europe. Issues of the survey are not only the various income elements, but also other important areas of life such as the housing situation or health. EU-SILC is the new standard data source used to measure poverty and living conditions in the European Union member states.

EU-SILC has been conducted since 2005 in all European Union member states as well as in Norway and Iceland. To ensure the comparability of results, the same variables are covered all over the European Union. Binding minimum standards apply to the survey methods. The survey has been tailored especially to calculating comparable indicators of social inclusion (so-called Laeken indicators) and, consequently, is a major basis for European social policy.

Abstract

The national initiatives at poverty tracking started in Nigeria in the early 1990s between Federal Office of Statistics and the World Bank. At the inception, the National Consumer Surveys data set series for 1980-1996 were analysed which charted the profile of poverty in Nigeria. This culminated in a Poverty Profile for Nigeria Report (1980-1996) which has since served as bench-mark for monitoring and evaluation of various government anti-government poverty and policies. The Poverty Profile for Nigeria 2004 is the latest and a good follow-up to the previous one.

With the recognition by the Nigerian Government of the multi-sectoral and multi-dimensional nature of poverty, a number of coordinated programmes and policies had been formulated to combat poverty in all its ramifications. Among the programmes are National Poverty Eradication Programme (NAPEP), the National Economic Empowerment and Development Strategy (NEEDS) and the Millennium Development Goals of the government which are aimed basically at poverty reduction. These programmes require a framework for poverty statistics production, management and tracking.

The Nigeria Living Standard Survey institutionalised by the Federal Office of Statistics provided a major survey mechanism framework for regular production, management and tracking of poverty programmes and policies. The recent Profile of Poverty for Nigeria as elucidated in this report is a commendable effort in providing current, timely and highly relevant poverty statistics and indicators for monitoring and evaluation of anti-poverty programmes and policies. The findings of the report chronicled the magnitude, nature, character and dimensions of poverty in Nigeria in 2004.

Geographic coverage

National Zone State Lga

Analysis unit

Household and individual

Universe

Household members

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE DESIGN The sampling designs for the NLSS was meant to give estimates at National, Zonal and State levels. The first stage was a duster of housing units called Enumeration Area (EA), while the second stage was the housing unit.

SAMPLE SIZE One hundred and twenty (120 EAs) were selected and sensitized in each state while sixty enumeration areas were selected at the Federal Capital Territory (FCT). Ten E.As with five housing units were studied per month. This meant that fifty housing units were canvassed per month in each state and twenty-five housing units in Abuja.

One hundred and twenty (120) EAs were selected in 12 replicates in each State from the NISH master sample frame in replicates (4-15). However, 60 EAs were selected in the Federal Capital Territory. Five (5) housing units (HUs) were scientifically selected in each of the selected EAs. One replicate consisting of 10 EAs in the State and 5 EAs in the Federal Capital Territory were covered every month. Fifty (50) HUs were covered in each State and 25 HUs in the Federal Capital Territory per month. This implied that the survey had an anticipated national sample size of twenty-one thousand and nine hundred (21,900) HUs for the country for the 12-month survey period. Each State had a sample size of 600 HUs, while the Federal Capital Territory had a sample size of 300. The sample size is robust enough to provide reasonable estimates at national and sub-national (State) levels. ESTIMATION PROCEDURE The following statistical notations were used: N = the number of EAs in each State ni = Size of replicates rth r = number of replicates in a State H = number of housing units listed in the ith selected EA. Xhj = number of housing units selected from ith selected EA.
Wrij = weight of the replicate =????????nhijNxH Yrij = total value of variable from the ith HU of ith selected EA.
Replicate Estimate (Monthly Estimate) ()??=yWyi Annual State Estimate ??? NOTE See page 91 and 92 of the report

Sampling deviation

Sampling Error (Variance) Estimate The Jacknife indefinite method of variance estimation was used for the survey because the method required replication and clustering. An estimate of State variance was first obtained. Cluster estimate is ()ywijiji???= Mean Estimate rnrz??= Therefore mean variance is ()rSnrV2=? where ()()221-?-?=?rnrSr
NOTE See page 93 of the report

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire is a structured questionnaire developed as a joint effort of the National Bureau of Statistics, the World Bank and National Planning Commission. After series of meeting and two consultative workshops, seven survey instruments were developed: Household Diary Record Book. Questionnaire Part A: Household Questionnaire. Questionnaire Part B: Household Consumption Questionnaire. The interviewer's manuals . Supervisor's manuals. Occupation and Industry Code Booklets . Prices Questionnaire.

Cleaning operations

Headquarters Training of Trainers (T0T) The first level of training at the headquarter consisted of three categories of officers, namely, the trainers at the zonal level, fieldwork monitoring officers and data processing officers who were crucial to the successful implementation of the survey. The intensive and extensive training lasted for five days. Zonal Level Training The training took place in the six zonal FOS [now NBS] offices representing the six geo-political zones of the country. These are Ibadan (South West) Enugu (South East), Calabar (South South), Jos (North Central), Maiduguri (North East) and Kaduna (North West). The composition of the team from each State to the six different zones were the State officer, one scrutiny officer and two field officers, making four persons per state. Two resource persons from the headquarters did the training with the zonal controllers participating and contributing during the five-day regimented and intensive training. State Level Training The third level training was at the State level. A total of 40 officers were trained, comprising 20 enumerators, 10 editing staff and 10 supervisors. The State Statistical Agencies, as a matter policy, contributed 5-10 enumerators. The ten-day exercise was also regimented, intensive and extensive because the enumerators were also crucial for effective implementation of data collection.

Response rate

The response rate was very high

Abstract

The first Vietnam Living Standards Survey (VLSS) was conducted in 1992-93 by the State Planning Committee (SPC) (now Ministry of Planning and Investment) along with the General Statistical Office (GSO). The second VLSS was conducted by the GSO in 1997-98. Both VLSS surveys were funded by UNDP and Swedish International Development Authority (SIDA). The survey was part of the Living Standards Measurement Study (LSMS) household surveys conducted in a number of developing countries with technical assistance from the World Bank.

The second VLSS was designed to provide an up-to-date source of data on households to be used in policy design, monitoring of living standards and evaluation of policies and programs. The timing of the second VLSS approximately five years after the first allows analysis of medium term trends in living standards as a large part of the questionnaire is the same in both surveys.

In addition to the purpose of obtaining a comprehensive and comparable data set to the 1992-93 VLSS for policy analysis, the survey also served as a medium for training and improving survey methods and analysis within the General Statistical Office of Vietnam (GSO), the agency in charge of designing and implementing the second round of the VLSS as well as other government agencies involved in social statistics.

Geographic coverage

National

Analysis unit

• Households
• Individuals
• Community
• Schools
• Health Centers

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey sample was selected to be representative for the whole country, taking into account available funding, geographical conditions, organizational capacity and staff competence. The sample size was set at 6000 households selected from provinces and cities throughout the country, but excluding islands due to logistical difficulties in traveling and conducting the survey in those locations.

The sample for the 1997-1998 VLSS was primarily selected from the households selected in the original 150 communes/wards of the 1992-1993 VLSS. The sample was increased by 1200 households with these additional households obtained from the sample of the Multi-purpose Household survey (MPHS) which was based on a similar sampling methodology. Replacement households were selected randomly from within the clusters of the survey and used where necessary.

The selection of the original sample of 4800 households from VLSS 1992-1993 followed a method of stratified random cluster sampling. The basic sample frame was obtained from the 1989 Population Census. The sampling procedures took into account that communes or wards are the basic local level administrative unit, and each commune/ward has a number of villages or urban residential blocks. The number of households selected in a given cluster was determined primarily based on the requirements for organization of interview teams and time needed for each household interview on location.

Based on the sampling frame including two lists, list of communes and list of wards (or equivalent administrative units) throughout the country with the number of households in each commune/ward obtained from the 1989 Population Census, the sample of the 1992-1993 VLSS was selected in three steps, independently for urban and rural areas:

Step 1: Random selection of 120 communes and 30 wards throughout the country based on the method of probability proportional to the number of households in those villages or wards. The selection of primary sampling units (communes) was stratified by urban and rural areas based on the results of the 1989 Census that 80% of the population was living in rural areas and 20% in urban areas.

Step 2: Within each selected commune, two villages or urban residential blocks were selected randomly by the method of probability proportional to the number of households as in the first stage of sampling. Thus, 240 villages and 60 residential blocks were selected.

Step 3: Within each selected village or residential block, 20 households were randomly selected by systematic method with equal probability, including 16 official and 4 alternate households. To eliminate the effect of the seasonal differences, the rotation method of sample was adopted: the 6000 surveyed households were divided into 10 sub-samples and each sub-sample was surveyed for one month.

Sampling procedure is explained in details in the document called "Vietnam Living Standards Survey (VLSS), 1997-98", available in this documentation.

Mode of data collection

Face-to-face [f2f]

Research instrument

The second round of the VLSS used 5 questionnaires: household, commune, price, school and clinic. - Household Questionnaire: The household questionnaire contains 15 sections each of which covered a separate aspect of household activity.

• Commune/Ward Questionnaire: A completely new commune questionnaire was developed for the 1997-98 VLSS survey with a greatly expanded content. A few questions in the 1992-93 questionnaire were dropped or moved to other questionnaires (see below). The commune questionnaire was administered by the team supervisor and completed with the help of village chiefs, teachers, government officials and health care workers. The questionnaire was administered only in rural and minor urban areas, i.e. communes 37 to 194, corresponding to villages 73 to 388. Some sections of the questionnaire contain village/block level information, while most of the commune questionnaire refers to the commune. The commune questionnaire contains 10 sections.

• Price Questionnaire: Price data were collected in all clusters, both urban and rural by the anthropometrist for 36 food items, 33 non-food items, 6 services, 10 pharmaceutical products, and 7 agricultural inputs. Three separate observations were made and these did not necessarily involve actual purchase. However, it is possible that as the anthropometrist is not a local person, the prices quoted are not the true prices of the locality. This information was utilized in checking unit prices in the consumption modules, and for calculating poverty lines. Price indices utilized for adjusting monetary figures to real values were obtained from the GSO CPI unit. Details on how and where prices were to be collected can be found in the anthropometry manual. The actual locations of price collection were recorded in the questionnaires, but unfortunately not entered in the computer files.

• School Questionnaire: The school questionnaires were implemented by the team supervisor to all schools within the two villages selected within a commune. There are between 1 and 7 school questionnaires filled in per commune.

• Commune Health Station Questionnaire: The commune health station questionnaire was implemented by the team supervisor. The respondent could be the director, doctor or physician’s assistant of the health station.

Response rate

Response rates are shown in details in the document called "Vietnam Living Standards Survey (VLSS), 1997-98 Basic Information", available in this documentation.

Abstract

The principal focus of the survey is an issue of interest to us all - the welfare level of Tajik individuals and households. The survey data will be used in analyses to determine what proportion of Tajiks are unable to meet their basic needs to enjoy an adequate standard of living and are living in poverty. These studies will also consider what accounts for some households being able to attain and sustain such a standard of living and what might be done to assist those households and individuals now living in poverty to escape poverty. The information collected in the TLSS09 also will be used in a range of other studies, including examining employment, health, nutritional status, agriculture, as well as better understanding how households respond to changes in the macroeconomic environment. As you will learn, the data collected using the TLSS09 is particularly rich because it integrates such a wide range of aspects of household and individual characteristics.

Geographic coverage

National coverage; the sample is representative at the national, regional level (4 regions and Dushanbe), and urban/rural

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample size is 1,500 households

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire for the survey was developed in English and then translated into Tajik and Russian. During the translation process, there were some questions which were not translated completely or in which the response options were not translated complete.

Results of post estimation diagnostic and stability tests.

International Indicators — Living Conditions: States, Years

Geographic coverage

National

Analysis unit

• Households
• Individuals
• Communites

Kind of data

Sample survey data [ssd]

Sampling procedure

A detailed description of the sampling methodology is available in appendix to the document "Basic Information Document".

The TLSS sample was designed to allow reliable estimation of poverty and most variables for a variety of other living standard indicators at the various domains of interest based on a representative probability sample on the level of: • Tajikistan as a whole
• Total urban and total rural areas • The five main administrative regions (oblasts) of the country: Dushanbe, Rayons of Republican Subordination (RRS), Sogd, Khatlon, and Gorno-Badakhshan Autonomous Oblast (GBAO)

The last census was conducted in 2000 and covered all five main administrative regions (oblasts) of the country (Dushanbe, RRS, Sogd, Khatlon, and GBAO). Each oblast was further subdivided into smaller areas called census section, instructor's sector and enumeration sector (ES). Each ES is either totally urban or rural. The list of ESs has census information on the population of each ES, and the ES lists were grouped by oblast.

In 2005, UNICEF implemented a Multiple Indicator Cluster Survey (MICS05) in Tajikistan during which an electronic database of the ES information was created. Information in this database included: oblast, rayon, jamoat, settlement type, city/village, ES code, and population. Information from this database was used in the sample design of the TLSS07.

The total number of clusters for the TLSS07 was established as 270 and total number of households per cluster was established as 18, resulting in a sample size of 4,860. The sample size was determined by taking into account: • The reliability of the survey estimates on both regional and national level • Quality of the data collected for the survey • Cost in time for the data collection • An oversample in 7 rayons in Khatlon

The final cluster allocation is as follows:

Region: Urban / Rural / Total Dushanbe 50 / 0 / 50 RRP 9 / 45 / 54 Sogd 18 / 38 / 56 Khatlon 12 / 59 / 71 GBAO 6 / 33 / 39 Total 95 / 175 / 270

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were used to collect information for the TLSS07: a household questionnaire, a female questionnaire for recording information about women of child bearing age, and a community questionnaire. These questionnaires were based on the TLSS questionnaires used in 2003, but had some changes. Questions were added to existing modules and new modules were added to collect information to be used for MICS analyses. These included HIV/AIDS awareness, and Immunizations and Anthropometric Measurements for children 0 to 5 years old. Other new modules on Migration, Financial Services, Subjective Poverty and Food Security, and Subjective Beliefs were also added. The Labor Market Module was changed substantially from 2003 to better look at the informal labor market. The food expenditures module included additional food products. The HIV/AIDS questions were removed from the female questionnaire and were applied to all household members 12 to 49 years old.

The Second Round Household Questionnaire was shorter and was used primarily to collect additional information that was not possible to collect in the First Round. Because the First Round questionnaire was very long, it was decided to collect some information in a second round of visits to the households. The Household Questionnaire was the main instrument used during the Second Round. The female questionnaire was only used if females were added to the household after the First Round and the community questionnaire was not repeated. In the Second Round Household Questionnaire, the time reference period for the Food Security module was reduced from 4 weeks to 2 weeks. This was done because in the households visited at the beginning of the Second Round, a 4 week period would have included the last portion of the Ramadan period.

Cleaning operations

Data Entry and Cleaning

The data entry program was designed using CSPro, a data entry package developed by the US Census Bureau. This software allows programs to be developed to perform three types of data checks: (a) range checks; (b) intra-record checks to verify inconsistencies pertinent to the particular module of the questionnaire; and (c) inter-record checks to determine inconsistencies between the different modules of the questionnaire.

The data from the First Round were key entered at the Goskomstat headquarters in Dushanbe starting 4 October 2007 through 25 November 2007. The Second Round and Sughd data were key entered from 26 November 2007 through 12 December 2007. All of the data were double entered with both the First Round, Second Round and Sughd re-collection double entry being completed by 22 January 2008.

The data cleaning process began in February 2008 and was completed at the end of May 2008.

In 2021, Amazonas was the Venezuelan state with the highest rate of households with inadequate housing, as 25 percent of dwellings didn't meet the proper living standards. Delta Amacuro, where 24.8 percent of households were found unsuitable for living, ranked second. Mérida was the state with the lowest rate of inadequate housing, at 7.4 percent.