In 2023, 17.9 percent of Black people living in the United States were living below the poverty line, compared to 7.7 percent of white people. That year, the total poverty rate in the U.S. across all races and ethnicities was 11.1 percent. Poverty in the United States Single people in the United States making less than 12,880 U.S. dollars a year and families of four making less than 26,500 U.S. dollars a year are considered to be below the poverty line. Women and children are more likely to suffer from poverty, due to women staying home more often than men to take care of children, and women suffering from the gender wage gap. Not only are women and children more likely to be affected, racial minorities are as well due to the discrimination they face. Poverty data Despite being one of the wealthiest nations in the world, the United States had the third highest poverty rate out of all OECD countries in 2019. However, the United States' poverty rate has been fluctuating since 1990, but has been decreasing since 2014. The average median household income in the U.S. has remained somewhat consistent since 1990, but has recently increased since 2014 until a slight decrease in 2020, potentially due to the pandemic. The state that had the highest number of people living below the poverty line in 2020 was California.

This dataset includes the ethnicity of applicants for Insurance Affordability Programs (IAPs) who identified their ethnicity as Hispanic with the ethnic origin as Guatemalan, Mexican/Mexican American/Chicano, Other, Puerto Rican, Salvadoran, Mixed, or Cuban, Hispanic with ethnic origin not reported, not Hispanic, or ethnicity not reported by reporting period. The ethnicity data is from the California Healthcare Eligibility, Enrollment and Retention System (CalHEERS) and includes data from applications submitted directly to CalHEERS, to Covered California, and to County Human Services Agencies through the Statewide Automated Welfare System (SAWS) eHIT interface. This dataset is part of public reporting requirements set forth by the California Welfare and Institutions Code 14102.5.

This statistic shows the share families that have received income-related benefits in the United Kingdom (UK) in the period from 2015 to 2018, by ethnic group of household head. In this period, 29 percent of the families with head of the family being black/African black/Caribbean or British black received some form of income-related benefit.

In 2022, with more than 303,000 people, the ethnic Malay was the largest group of public assistance recipients from the Department of Social Welfare in Malaysia. The second-largest group was the Chinese Malaysian with more than 82,000 recipients of financial assistance in the same year.

Ethnic Diversity and Preferences for Redistribution attempts to explain if individual's preferences for redistribution change if the ethnic diversity increases in a municipality. In this case, selected parts of the Swedish Election Studies has been matched with municipal data for the time period between 1985 and 1994, when Sweden had an active placement program of refugees. This meant that the refugees themselves were not allowed to decide where to settle, but instead they were places in municipalities which had contracts with the Swedish Integration Board (Invandrarverket). Originally the idea of the program was to direct the refugees to municipalities with good labor market conditions, but since the number of refugees arriving to Sweden were larger than expected, so in practice more or less all municipalities were a part of the program. With the placement program refugees spread more across the country, than before the program. Ethnic Diversity and Preferences for Redistribution focus primarily on refugees from nations which not were members in the OECD 1994 and Turkey.

The data comes from the Swedish Election Studies survey waves for the elections in 1982, 1985, 1988, 1991 and 1994. Primarily it consists of various background variables and variables about individual's preferences for private health care, nuclear power and social benefits. The municipal data primarily consist of various socio-economic and political variables, such as population, tax base, welfare spending and share of refugees. Some of these variables are the average of the term (1986-1988, 1989-1991, and 1992-1994).

Purpose:

Investigate the causal link between the ethnic diversity in a society and its inhabitants´ preferences for redistribution.

Poverty and low-income statistics by visible minority group, Indigenous group and immigration status, Canada and provinces.

The number of people receiving social benefits in Denmark decreased from 2013. This is mainly because the number of people of Danish origin receiving social benefits has declined. Moreover, both the number of immigrants and descendants of immigrants who are social beneficiaries decreased since 2013. The Danish government implemented a reform in 2014 that tightened the conditions for receiving social benefits. In 2022, around 34,000 people of Danish origin and 15,000 immigrants received social benefits in Denmark.

The purpose of this study was to provide an appropriate theoretical and empirical approach to concepts, measures, and methods in the study of black Americans. The questionnaire was developed over two years with input from social scientists, students, and a national advisory panel of black scholars. The final instrument is comprehensive, encompassing several broad areas related to black American life. The study explores neighborhood-community integration, services, crime and community contact, the role of religion and the church, physical and mental health, and self-esteem. It examines employment, the effects of chronic unemployment, the effects of race on the job, and interaction with family and friends. The survey includes questions about racial attitudes, race identity, group stereotypes, and race ideology. Demographic variables include education, income, occupation, and political behavior and affiliation. The sample includes 2,107 black United States citizens, 18 years of age or older. A national multistage probability sample was selected. Therefore, the sample is self-weighting and every black American household in the continental United States had an equal probability of being selected. The Murray Research Archive has available numeric file data from the study. A subset of numeric file data comprised of 500 respondents and 152 variables created specifically for use in research methodology and statistics courses is also available. Additional waves of data for this study have been collected and are available through ICPSR.

Florida Poverty Rate Statistics for 2023. Analyze over 60 metrics of the Florida poverty database including by age, education, race, gender, work experience and more. In Florida, an estimated 2,762,679 of 21,764,366 people live in poverty, which is 12.7%. Compared to the national average of 12.6%, the poverty rate in Florida is 0.79% higher.

In 2022, the public assistance given to the ethnic Malay by the Malaysian Department of Social Welfare amounted to around 163 million Malaysian ringgit. The second-largest amount went to the indigenous ethnic group in Sabah, East Malaysia, with more than 53 million Malaysian ringgit in public assistance.

Graph and download economic data for Income Before Taxes: Public Assistance, Supplemental Security Income, SNAP by Race: White and All Other Races, Not Including Black or African American (CXUWELFARELB0903M) from 2003 to 2023 about supplements, assistance, social assistance, public, SNAP, food stamps, tax, white, food, income, and USA.

The Moving to Opportunity (MTO) program was a randomized housing experiment administered by the United States Department of Housing and Urban Development (HUD) that gave low-income families living in high-poverty areas the chance to move to lower-poverty areas. This Restricted Access Dataset (RAD) includes data from the 3,273 adults interviewed as part of the MTO long-term evaluation and is comprised of variables analyzed for the article "Neighborhood Effects on the Long-Term Well-Being of Low-Income Adults" that was published in the journal Science on September 21, 2012. The article focused on subjective well-being, physical and mental health, social networks, neighborhoods, housing, and economic self-sufficiency. Families were tracked from the baseline survey (1994-1998) through the long-term evaluation survey fielding period (2008-2010) with the purpose of determining the effects of "neighborhood" on participating families from five United States cities. Households were randomly assigned to one of three groups: The low-poverty voucher (LPV) group (also called the experimental group) received Section 8 rental assistance certificates or vouchers that they could use only in census tracts with 1990 poverty rates below 10 percent. The families received mobility counseling and help in leasing a new unit. One year after relocating, families could use their voucher to move again if they wished, without any special constraints on location.The traditional voucher (TRV) group (also called the Section 8 group) received regular Section 8 certificates or vouchers that they could use anywhere; these families received no special mobility counseling.The control group received no certificates or vouchers through MTO, but continued to be eligible for project-based housing assistance and other social programs and services to which they would otherwise be entitled.The dataset contains all outcomes and mediators analyzed for the Science article, as well as a variety of demographic and other baseline measures that were controlled for in the analysis. Demographic information includes age, gender, race/ethnicity, employment status, and education level.

An emerging body of research has robustly found a link between immigration and preferences for redistribution. In particular, immigration has been proved to undermine native support for the welfare state (Alesina et al., 2022; Dahlberg et al., 2012; Eger, 2010; Ford, 2006; Stichnoth, 2012). This link can be interpreted within a rational resource-competition framework (since increasing the number of potential net recipients has welfare consequences). Yet different social identity theories (Hornsey, 2008; Tajfel & Turner, 1986; Turner et al., 1987) have also been invoked to stress that natives’ attitudes towards redistribution and the welfare state are grounded on ethnic/national identity as well as on related conceptions of cultural distance (Brandt et al. 2014; Chambers et al. 2013). Perceptions of cultural distance, in turn, make the overall effect of immigration on attitudes towards redistribution dependent on the characteristics of the immigrant pool —because some immigrant groups are perceived as more (or less) disserving than others (Verkuyten et al. 1996). In the European context, immigrants’ coming from Middle East and North African countries of majoritarian Muslim faith (MENAM) and their European-born descendants are known to be particularly at risk of discrimination and prejudice ( Strabac & Listhaug 2008; Strabac et al. 2014; Di Stasio et al. 2021; Polavieja et al. 2023). An important gap in the literature on redistribution and welfare nativism, however, concerns the potential role of immigrant characteristics other than cultural-religious or socioeconomic background, specifically, the role of phenotype (i.e. color or racial appearance). The importance of racial appearance as an additional source of prejudice and discrimination has been long neglected in the European context and, to our knowledge, to date no study on the impact of immigration on attitudes towards redistribution has tested whether immigrants’ physical (“racial”) appearance can influence European natives’ attitudes toward welfare deservedness. Recent field experimental research on racial discrimination in hiring has brought the question of racial discrimination to the fore by showing European employers are less likely to hire immigrant descendants with non-white phenotypes and, hence, that having “visible” phenotypes constitutes a serious barrier for the socio-economic integration of the second-generation in Europe (Polavieja et al. 2023). Building on this research, we propose an experiment to address the distinctive role of ethnicity (treatment 1) and phenotype (treatment 2) on native’s attitudes regarding welfare deservedness chauvinism (research question 1). Additionally, we test for two mediating mechanisms, welfare competition (research question 2) and disgust sensitivity (research question 3), which allows us to also contribute to the expanding literature on the neurocognitive basis of prejudice and the role of visceral emotions. To this end we draw on recent developments in cognitive psychology, political psychology and behavioral science. Our main research questions can thus be summarized as follows: Research Question 1: What is the distinctive role of immigrant-descendants’ ethnicity and phenotype as potentially different drivers of welfare chauvinism? Research Question 2: To what extent (rational) concerns about competition might help us explain welfare chauvinist responses amongst natives? Research Question 3: To what extent (irrational) disgust sensitivity can help us explain welfare chauvinism and, in particular, chauvinist responses triggered by phenotypic racism?

Louisiana Poverty Rate Statistics for 2023. Analyze over 60 metrics of the Louisiana poverty database including by age, education, race, gender, work experience and more. In Louisiana, an estimated 829,565 of 4,467,616 people live in poverty, which is 18.6%. Compared to the national average of 12.6%, the poverty rate in Louisiana is 47.62% higher.

The project's primary research objective was to assess the degree to which violence, sabotage, and control present obstacles to waged work and job training for women in Allegheny County, Pennsylvania. It sought to develop and assess instruments and generate data to serve as guideposts for policy and service delivery. The study consisted of two parts: (1) a series of interviews with 40 female welfare recipients, and (2) a community literacy project that resulted in a collection of narratives by female welfare recipients. Interviews were conducted with 40 Temporary Assistance to Needy Families (TANF) recipients who were enrolled at the Reemployment Transition Center (RTC) in Allegheny County, Pennsylvania, between May 29, 2001, and June 27, 2001. After explaining the research project to the intake group, the interviewers met in private with interested potential subjects. The interviews consisted of an initial face-to-face retrospective interview (Parts 1 through 5), conducted when subjects enrolled at RTC, and three follow-up interviews designed to be administered quarterly. The first follow-up interview (Part 6) was conducted between October 15, 2001, and May 7, 2002. The second follow-up interview (Part 7) was conducted between March 12, 2002, and May 21, 2002. The final follow-up (Part 8) interview was conducted between July 3, 2002, and November 15, 2002. Follow-up interviews were in person or by telephone (depending on the respondent's preference). A key innovation of this research project was to gather data on school, work, welfare, and relationships with enough precision to trace the complex connections among battering, work, and welfare over the course of poor women's lives (Part 9). To do so, researchers collected data on the start and end dates of each period of education, each job, each period on welfare, and each relationship. These data enabled researchers to compare the number and length of spells at work and on welfare for women who did and women who did not report various obstacles, including battering. Finally, researchers summarized some elements of the longitudinal data such as relationship and employment information into a data file (Part 10). In all, there are 10 quantitative data files encompassing 1,895 variables. In addition to the 10 quantitative data files, there are respondent answers to open text questions (Part 11). Interviewers were able to record field notes, which included observations about the interview context, overall impressions of the process, elaborated answers to open-ended questions, etc. (Part 12). There are also 8 autobiographical narratives to serve as sources of qualitative data on the ways current and former welfare recipients experience and perceive work, welfare, and relationships (including abuse) (Part 13). The Part 1 (Retrospective Demographic and Hardship Data) data file contains demographic information including living arrangements and income. The Part 2 (Retrospective Education Data) data file contains information related to the respondent's prior education. The Part 3 (Retrospective Employment Data) data file contains information related to the respondent's employment history. The Part 4 (Retrospective Welfare Data) contains information related to the respondent's welfare history. The Part 5 (Retrospective Relationship Data) data file contains information related to the Work-Related Control, Abuse, and Sabotage Checklist (WORCASC) and the Work/School Abuse Scale (W/SAS), which asked questions about interference, sabotage, and violence in relationships. The Part 6 (First Follow-Up Interview Data), Part 7 (Second Follow-Up Interview Data), and Part 8 (Final Follow-Up Interview Data) data files include follow-up information to that collected in Parts 1-5. The Part 9 (Date and Spell Data) data file provides data on the start and end dates of each period of education, each job, each period on welfare, and each relationship, and the Part 10 (Summary Longitudinal Data) data file summarizes some elements of the longitudinal data.

This statistic shows the share of United States citizens by their opinion on the welfare of animals in zoos in 2016, by ethnicity. During the survey, 24 percent of Hispanic respondents stated that they think most zoo animals are treated very well.

Ethnic Diversity and Preferences for Redistribution försöker att belysa om individers preferenser kring omfördelning förändras i och med att den etniska mångfalden i en kommun ökar. I detta fall har utvalda delar från Svensk valundersökning matchats ihop med kommundata under perioden 1985 till 1994, då Sverige hade ett aktivt utplaceringsprogram av flyktingar. Detta innebar att flyktingarna inte själva fick bestämma var de skulle bosätta sig, utan att de istället placerades i kommuner enligt kommunvisa avtal med Invandrarverket. Från början var tanken att styra flyktingarna mot kommuner som hade gynnsamma arbetsmarknadsförhållanden, men eftersom flyktinginvandringen blev större än förväntat kom i praktiken i stort sett alla kommuner att omfattas. I och med utplaceringsprogrammet blev flyktingmottagandet mer spritt över landet. I Ethnic Diversity and Preferences for Redistribution fokuserar främst på de flyktningar/invandrare som kommer från nationer som inte var medlemmar i OECD 1994 samt Turkiet.

Datamängden som är hämtad från den Svenska valundersökningen är från undersökningsvågorna för 1982, 1985, 1988, 1991 och 1994 års val. Främst handlar det om variabler kring olika bakgrundsfaktorer och kring individers preferenser för privat hälsovård, kärnkraft samt för sociala bidrag. Den kommunala datan består främst av olika socioekonomiska och politiska variabler såsom population, skattebas, välfärdsutgifter och andelen invandrare. Vissa av dessa variabler är genomsnittet för mandatperioden (1986-1988, 1989-1991 och 1992-1994)

Syfte:

Att undersöka orsakssambandet mellan den etniska mångfalden i ett samhälle och dess invånares preferenser för omfördelning.

This dataset includes race/ethnicity of newly Medi-Cal eligible individuals who identified their race/ethnicity as Hispanic, White, Other Asian or Pacific Islander, Black, Chinese, Filipino, Vietnamese, Asian Indian, Korean, Alaskan Native or American Indian, Japanese, Cambodian, Samoan, Laotian, Hawaiian, Guamanian, Amerasian, or Other, by reporting period. The race/ethnicity data is from the Medi-Cal Eligibility Data System (MEDS) and includes eligible individuals without prior Medi-Cal Eligibility. This dataset is part of the public reporting requirements set forth in California Welfare and Institutions Code 14102.5.

Abstract (en): Transatlantic Trends: Immigration, 2009 examined attitudes and policy preferences related to immigration in Europe, Canada, and the United States. The survey concentrated on issues such as: general perceptions of immigration and immigrants, perceptions of legal and illegal immigrants, the impact of immigration on society, admittance of immigrants, immigration policies, immigration and integration, decision-making level, socio-political rights, welfare, government evaluation and number of immigrants, interaction with immigrants, and economic crisis. In addition, a list experiment was implemented in this survey. Several questions were also asked pertaining to voting and politics including vote intention, political party attachment, whether candidate parties' agendas on immigration will influence their vote, and left-right political self-placement. Demographic and other background information includes age, gender, ethnicity, citizenship, origin of birth (personal and parental), religious affiliation, age when stopped full-time education and stage at which full-time education was completed, occupation, type of locality, region of residence, and language of interview. Please refer to the "Technical Note" in the ICPSR codebook for further information about weighting. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Created online analysis version with question text.; Checked for undocumented or out-of-range codes.. Response Rates: The total response rate for all countries surveyed is 13 percent. Please refer to the "Technical Note" in the ICPSR codebook for additional information about response rate. The adult population aged 18 years and over, with access to a landline telephone in eight countries: Canada, France, Germany, Great Britain, Italy, the Netherlands, Spain, and the United States. Smallest Geographic Unit: country (1) Stratified multi-stage random sampling (3 steps selection) was implemented. Sampling points were selected according to region and urbanization, and then random routes were conducted within these sampling points. (2) Random-digit dialing was implemented in all countries. Up to eight callbacks were used for each telephone number. The closest birthday rule was used to randomly select respondents within a household. computer-assisted telephone interview (CATI)The original data collection was carried out by TNS Opinion and Social -- Brussels, on request of the German Marshall Fund of the United States.The documentation and/or setup files may contain references to Poland, but Poland was not a participant in this Transatlantic Trends: Immigration survey. This collection contains no data for Poland.A split ballot was used for questions Q6, Q8, Q15, Q19, and Q25 in this survey. The variables Q6_SPLIT, Q8_SPLIT, Q15_SPLIT, Q19_SPLIT, and Q25_SPLIT define the separate groups for each of these questions. Additional information on the Transatlantic Trends Survey is provided on the Transatlantic Trends Web site.

Abstract

The Indonesia Demographic and Health Survey (IDHS), which is part of the Demographic and Health Surveys (DHS) Project, is one of prominent national surveys in the field of population, family planning, and health. The survey is not only important nationally for planning and evaluating population, family planning, and health developments, but is also important internationally since IDHS has been designed so uniquely that it can be compared with similar surveys in other developing countries.

The 1997 Indonesia Demographic and Health Survey (IDHS) is a follow-on project to the 1987 National Indonesia Contraceptive Prevalence Survey (NICPS), the 1991 IDHS, and the 1994 IDHS. The 1997 IDHS was expanded from the 1994 survey to include a module on family welfare; however, unlike the 1994 survey, the 1997 survey no longer investigated the availability of family planning and health services. The 1997 IDHS also included as part of the household schedule a household expenditure module that provided a means of identifying the household's economic status.

The 1997 IDHS was specifically designed to meet the following objectives: - Provide data concerning fertility, family planning, maternal and child health, maternal mortality, and awareness of AIDS that can be used by program managers, policymakers, and researchers to evaluate and improve existing programs - Provide data about availability of family planning and health services, thereby offering an opportunity for linking women's fertility, family planning, and child care behavior with the availability of services - Provide household expenditure data that which can be used to identify the household's economic status - Provide data that can be used to analyze trends over time by examining many of the same fertility, mortality, and health issues that were addressed in the earlier surveys (1987 NICPS, 1991 IDHS and 1994 IDHS) - Measure changes in fertility and contraceptive prevalence rates and at the same time study factors that affect the changes, such as marriage patterns, urban/rural residence, education, breastfeeding habits, and the availability of contraception - Measure the development and achievements of programs related to health policy, particularly those concerning the maternal and child health development program implemented through public health clinics in Indonesia - Provide indicators for classifying families according to their welfare status.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men

Kind of data

Sample survey data

Sampling procedure

Indonesia is divided into 27 provinces. For the implementation of its family planning program, the National Family Planning Coordinating Board (NFPCB) has divided these provinces into three regions as follows:

• Java-Bali: DKI Jakarta, West Java, Central Java, DI Yogyakarta, East Java, and Bali
• Outer Java-Bali I: Dista Aceh, North Sumatra, West Sumatra, South Sumatra, Lampung, West Nusa Tenggara, West Kalimantan, South Kalimantan, North Sulawesi, and South Sulawesi
• Outer Java-Ball II: Riau, Jambi, Bengkulu, East Nusa Tenggara, East Timor, Central Kalimantan, East Kalimantan, Central Sulawesi, Southeast Sulawesi, Maluku, and Irian Jaya

The 1990 Population Census of Indonesia shows that Java-Bali accounts for 62 percent of the national population, Outer Java-Bali I accounts for 27 percent, and Outer Java-Bali II accounts for 11 percent. The sample for the 1997 IDHS was designed to produce reliable estimates of fertility, contraceptive prevalence and other important variables for each of the provinces and urban and rural areas of the three regions.

In order to meet this objective, between 1,650 and 2,050 households were selected in each of the provinces in Java-Bali, 1,250 to 1,500 households in the ten provinces in Outer Java-Bali I, and 1,000 to 1,250 households in each of the provinces in Outer Java-Bali II, for a total of 35,500 households. With an average of O.8 ever-married women 15-49 per household, the sample was expected to yield approximately 28,000 women eligible for the individual interview.

Note: See detailed description of sample design in APPENDIX A of the survey report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 1997 IDHS used three questionnaires: the household questionnaire, the questionnaire on family welfare, and the individual questionnaire for ever-married women 15-49 years old. The general household and individual questionnaires were based on the DHS Model "A" Questionnaire, which is designed for use in countries with high contraceptive prevalence. Additions and modifications to the model questionnaire were made in order to provide detailed information specific to Indonesia. The questionnaires were developed mainly in English and were translated into Indonesian. One deviation from the standard DHS practice is the exclusion of the anthropometric measurement of young children and their mothers. A separate survey carried out by MOH provides this information.

The household questionnaire includes an expenditure schedule adapted from the core Susenas questionnaire model. Susenas is a national household survey carried out annually by CBS to collect data on various demographic and socioeconomic indicators of the population. The family welfare questionnaire was aimed at collecting indicators developed by the NFPCB to classify families according to their welfare status. Families were identified from the list of household members in the household questionnaire. The expenditure module and the family welfare questionnaire were developed in Indonesian.

Cleaning operations

The first stage of data editing was carried out by the field editors who checked the completed questionnaires for thoroughness and accuracy. Field supervisors then further examined the questionnaires. In many instances, the teams sent the questionnaires to CBS through the regency/municipality statistics offices. In these cases, no checking was done by the PSO. In other cases, Technical Coordinators are responsible for reviewing the completeness of the forms. At CBS, the questionnaires underwent another round of editing, primarily for completeness and coding of responses to open-ended questions. The data were processed using microcomputers and the DHS computer program, ISSA (Integrated System for Survey Analysis). Data entry and office editing were initiated immediately after fieldwork began. Simple range and skip errors were corrected at the data entry stage. Data processing was completed by February 1998, and the preliminary report of the survey was published in April 1998.

Response rate

A total of 35,362 households were selected for the survey, of which 34,656 were found. Of the encountered households, 34,255 (99 percent) were successfully interviewed. In these households, 29,317 eligible women were identified, and complete interviews were obtained from 28,810 women, or 98 percent of all eligible women. The generally high response rates for both household and individual interviews were due mainly to the strict enforcement of the rule to revisit the originally selected household if no one was at home initially. No substitution for the originally selected households was allowed. Interviewers were instructed to make at least three visits in an effort to contact the household or eligible woman.

Note: See summarized response rates by place of residence in Table 1.2 of the survey report.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (I) non-sampling errors and (2) sampling errors. Non-sampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 1997 IDHS to minimize this type of error, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 1997 IDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 1997 IDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 1997 IDHS is the ISSA Sampling Error Module. This module