15 datasets found
  1. w

    National Demographic and Health Survey 2022 - Philippines

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Jun 7, 2023
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    Philippine Statistics Authority (PSA) (2023). National Demographic and Health Survey 2022 - Philippines [Dataset]. https://microdata.worldbank.org/index.php/catalog/5846
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    Dataset updated
    Jun 7, 2023
    Dataset authored and provided by
    Philippine Statistics Authority (PSA)
    Time period covered
    2022
    Area covered
    Philippines
    Description

    Abstract

    The 2022 Philippines National Demographic and Health Survey (NDHS) was implemented by the Philippine Statistics Authority (PSA). Data collection took place from May 2 to June 22, 2022.

    The primary objective of the 2022 NDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the NDHS collected information on fertility, fertility preferences, family planning practices, childhood mortality, maternal and child health, nutrition, knowledge and attitudes regarding HIV/AIDS, violence against women, child discipline, early childhood development, and other health issues.

    The information collected through the NDHS is intended to assist policymakers and program managers in designing and evaluating programs and strategies for improving the health of the country’s population. The 2022 NDHS also provides indicators anchored to the attainment of the Sustainable Development Goals (SDGs) and the new Philippine Development Plan for 2023 to 2028.

    Geographic coverage

    National coverage

    Analysis unit

    • Household
    • Individual
    • Children age 0-5
    • Woman age 15-49

    Universe

    The survey covered all de jure household members (usual residents), all women aged 15-49, and all children aged 0-4 resident in the household.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sampling scheme provides data representative of the country as a whole, for urban and rural areas separately, and for each of the country’s administrative regions. The sample selection methodology for the 2022 NDHS was based on a two-stage stratified sample design using the Master Sample Frame (MSF) designed and compiled by the PSA. The MSF was constructed based on the listing of households from the 2010 Census of Population and Housing and updated based on the listing of households from the 2015 Census of Population. The first stage involved a systematic selection of 1,247 primary sampling units (PSUs) distributed by province or HUC. A PSU can be a barangay, a portion of a large barangay, or two or more adjacent small barangays.

    In the second stage, an equal take of either 22 or 29 sample housing units were selected from each sampled PSU using systematic random sampling. In situations where a housing unit contained one to three households, all households were interviewed. In the rare situation where a housing unit contained more than three households, no more than three households were interviewed. The survey interviewers were instructed to interview only the preselected housing units. No replacements and no changes of the preselected housing units were allowed in the implementing stage in order to prevent bias. Survey weights were calculated, added to the data file, and applied so that weighted results are representative estimates of indicators at the regional and national levels.

    All women age 15–49 who were either usual residents of the selected households or visitors who stayed in the households the night before the survey were eligible to be interviewed. Among women eligible for an individual interview, one woman per household was selected for a module on women’s safety.

    For further details on sample design, see APPENDIX A of the final report.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    Two questionnaires were used for the 2022 NDHS: the Household Questionnaire and the Woman’s Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to the Philippines. Input was solicited from various stakeholders representing government agencies, academe, and international agencies. The survey protocol was reviewed by the ICF Institutional Review Board.

    After all questionnaires were finalized in English, they were translated into six major languages: Tagalog, Cebuano, Ilocano, Bikol, Hiligaynon, and Waray. The Household and Woman’s Questionnaires were programmed into tablet computers to allow for computer-assisted personal interviewing (CAPI) for data collection purposes, with the capability to choose any of the languages for each questionnaire.

    Cleaning operations

    Processing the 2022 NDHS data began almost as soon as fieldwork started, and data security procedures were in place in accordance with confidentiality of information as provided by Philippine laws. As data collection was completed in each PSU or cluster, all electronic data files were transferred securely via SyncCloud to a server maintained by the PSA Central Office in Quezon City. These data files were registered and checked for inconsistencies, incompleteness, and outliers. The field teams were alerted to any inconsistencies and errors while still in the area of assignment. Timely generation of field check tables allowed for effective monitoring of fieldwork, including tracking questionnaire completion rates. Only the field teams, project managers, and NDHS supervisors in the provincial, regional, and central offices were given access to the CAPI system and the SyncCloud server.

    A team of secondary editors in the PSA Central Office carried out secondary editing, which involved resolving inconsistencies and recoding “other” responses; the former was conducted during data collection, and the latter was conducted following the completion of the fieldwork. Data editing was performed using the CSPro software package. The secondary editing of the data was completed in August 2022. The final cleaning of the data set was carried out by data processing specialists from The DHS Program in September 2022.

    Response rate

    A total of 35,470 households were selected for the 2022 NDHS sample, of which 30,621 were found to be occupied. Of the occupied households, 30,372 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 28,379 women age 15–49 were identified as eligible for individual interviews. Interviews were completed with 27,821 women, yielding a response rate of 98%.

    Sampling error estimates

    The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and in 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 2022 Philippines National Demographic and Health Survey (2022 NDHS) to minimize this type of error, nonsampling 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 2022 NDHS is only one of many samples that could have been selected from the same population, using the same design and identical 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% 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 2022 NDHS sample was the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS using programs developed by ICF. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

    A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.

    Data appraisal

    Data Quality Tables

    • Household age distribution
    • Age distribution of eligible and interviewed women
    • Age displacement at age 14/15
    • Age displacement at age 49/50
    • Pregnancy outcomes by years preceding the survey
    • Completeness of reporting
    • Observation of handwashing facility
    • School attendance by single year of age
    • Vaccination cards photographed
    • Population pyramid
    • Five-year mortality rates

    See details of the data quality tables in Appendix C of the final report.

  2. i

    Census of Population and Housing 2000 - Philippines

    • catalog.ihsn.org
    • datacatalog.ihsn.org
    Updated Mar 29, 2019
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    National Statistics Office (2019). Census of Population and Housing 2000 - Philippines [Dataset]. https://catalog.ihsn.org/index.php/catalog/573
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    Dataset updated
    Mar 29, 2019
    Dataset authored and provided by
    National Statistics Office
    Time period covered
    2000
    Area covered
    Philippines
    Description

    Abstract

    Census of Population and Housing refers to the entire process of collecting, compiling, evaluating, analyzing, and publishing data about the population and the living quarters in a country. It entails the listing and recording of the characteristics of each individual and each living quarter as of a specified time and within a specified territory.

    Census 2000 is designed to take an inventory of the total population and housing units in the Philippines and to collect information about their characteristics. The census of population is the source of information on the size and distribution of the population as well as information about the demographic, social, economic and cultural characteristics. The census of housing, on the other hand, provides information on the supply of housing units, their structural characteristics and facilities which have bearing on the maintenance of privacy, health and the development of normal family living conditions. These information are vital for making rational plans and programs for national and local development.

    The Census 2000 aims to provide government planners, policy makers and administrators with data on which to base their social and economic development plans and programs.

    May 1, 2000 has been designated as Census Day for the 2000 Census of Population and Housing or Census 2000, on which date the enumeration of the population and the collection of all pertinent data on housing in the Philippines shall refer.

    Geographic coverage

    National Coverage Regions Provinces Cities and Municipalities Barangays

    Analysis unit

    Individuals Households Housing units

    Universe

    The Census 2000 covered all persons who were alive as of 12:01 a.m. of May 1, 2000 and who are: - Filipino nationals permanently residing in the Philippines; - Filipino nationals who are temporarily at sea or are temporarily abroad as of census date; - Filipino overseas workers as of census date, even though expected to be away for more than a year; - Philippine government officials, both military and civilian, including Philippine diplomatic personnel and their families, assigned abroad; and - Civilian citizens of foreign countries having their usual residence in the Philippines or foreign visitors who have stayed or are expected to stay for at least a year from the time of their arrival in this country.

    Kind of data

    Census/enumeration data [cen]

    Sampling procedure

    In the Census 2000, there are basically two types of questionnaires to be used for the enumeration of hosueholds memmbers. These are CPH Form 2 or the Common Household Questionnaire and the CPH Form 3 or the Sample Household Questionnaire. There are procedures for selecting those households to whom CPH Form 3 will be administered. All enumerators are required to strictly follow these procedures.

    The sampling rate, or the proportion of households to be selected as samples within each EA, varies from one EA to another. It can be either 100%, 20% or 10%. If the sampling rate applied to an EA is 100%, it means that all households in that EA will use CPH Form 3. IF it is 20% or 10%, it means that one-fifth or one-tenth, respectively, of all households will use CPH Form 3 while the rest will use CPH Form 2.

    The scheme for the selection of sample households is known as systematic sampling with clusters as the sampling units. Under this scheme, the households in an EA are grouped in clusters of size 5. Clusters are formed by grouping together households that have been assigned consecutive serial numbers as they are listed in the Listing Page.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The questionnaires for 2000 Census of Population and Housing were basically patterned from previous censuses except that it should be in Intelligent Character Recognition (ICR) format. The basic questionnaires designed for this undertaking were as follows:

    CPH Form 1 - Listing Page This is a sheet wherein all buildings, housing units, households and institutional living quarters within an enumeration area (EA) will be listed. Other information pertaining to the population of households and institutional living quarters will also be recorded in this form.

    CPH Form 2 - Common Household Questionnaire This is the basic census questionnaire, which will be used for interview and for recording information about the common or non-sample households. This questionnaire gathers information on the following demographic and social characteristics of the population: relationship to household head, family nucleus, date of birth, age, birth registration, sex, marital status, religious affiliation, disability, ethnicity, residence five years ago and highest educational attainment. This also gathers information on building and housing unit characteristics.

    CPH Form 3 - Sample Household Questionnaire This is the basic census questionnaire, which will be used for interview and for recording information about the sample households. This questionnaire contains the same question as in CPH Form 2 and additional questions, namely: citizenship, language, literacy, school attendance, type of school, place of school, usual activity/occupation, kind of business/industry, place of work and some items on fertility. It also asks additional questions on household characteristics and amenities and residence five years ago.

    CPH Form 4 - Institutional Population Questionnaire This questionnaire records information about persons considered part of the institutional population. It contains questions on residence status, date of birth, age, sex, marital status, religious affiliation, disability, ethnicity and highest educational attainment.

    CPH Form 5 - Barangay Schedule This questionnaire will gather indicators to update the characteristics of all barangays which will determine its urbanity.

    CPH Form 6 - Notice of Listing/Enumeration This is the sticker that will be posted in a very conspicuous place, preferably in front of the house or gate of the building after listing and interviewing. This sticker indicates that the Building/Housing Unit/Household has already been enumerated.

    CPH Form 7 - Common Household Questionnaire Self Administered Questionnaire (SAQ) Instructions This form contains the detailed instructions on how to fill up/answer CPH Form 2. It will accompany CPH Form 2 to be distributed to households who will answer the form themselves, such as those in designated SAQ areas or those where three callbacks or four visits have been made.

    CPH Form 8 - Institutional Population Questionnaire SAQ Instructions This form describes the instructions on how to accomplish CPH Form 4 - Institutional Population Questionnaire. It will accompany CPH Form 4 to be distributed to head of institutions who will accomplish the form.

    CPH Form 9 - Appointment Slip This form will be used to set an appointment with the household head or any responsible member of the household in case you were unable to interview any one during your first visit or second visit. You will indicate in this form the date and time of your next visit.

    Blank Barangay Map This form will be used to enlarge map of each block of an enumeration area/barangay especially if congested areas are being enumerated.

    The main questionnaires were developed in English and were translated to major dialects: Bicol, Cebuano, Hiligaynon, Ifugao, Ilocano, Kapampangan, Tagalog, and Waray.

  3. w

    National Demographic and Health Survey 2017 - Philippines

    • microdata.worldbank.org
    • catalog.ihsn.org
    • +1more
    Updated Oct 4, 2018
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    Philippines Statistics Authority (PSA) (2018). National Demographic and Health Survey 2017 - Philippines [Dataset]. https://microdata.worldbank.org/index.php/catalog/3220
    Explore at:
    Dataset updated
    Oct 4, 2018
    Dataset authored and provided by
    Philippines Statistics Authority (PSA)
    Time period covered
    2017
    Area covered
    Philippines
    Description

    Abstract

    The 2017 Philippines National Demographic and Health Survey (NDHS 2017) is a nationwide survey with a nationally representative sample of approximately 30,832 housing units. The primary objective of the survey is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the NDHS 2017 collected information on marriage, fertility levels, fertility preferences, awareness and use of family planning methods, breastfeeding, maternal and child health, child mortality, awareness and behavior regarding HIV/AIDS, women’s empowerment, domestic violence, and other health-related issues such as smoking.

    The information collected through the NDHS 2017 is intended to assist policymakers and program managers in the Department of Health (DOH) and other organizations in designing and evaluating programs and strategies for improving the health of the country’s population.

    Geographic coverage

    National coverage

    Analysis unit

    • Household
    • Individual
    • Children age 0-5
    • Woman age 15-49

    Universe

    The survey covered all de jure household members (usual residents) and all women age 15-49 years resident in the sample household.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sampling scheme provides data representative of the country as a whole, for urban and rural areas separately, and for each of the country’s administrative regions. The sample selection methodology for the NDHS 2017 is based on a two-stage stratified sample design using the Master Sample Frame (MSF), designed and compiled by the PSA. The MSF is constructed based on the results of the 2010 Census of Population and Housing and updated based on the 2015 Census of Population. The first stage involved a systematic selection of 1,250 primary sampling units (PSUs) distributed by province or HUC. A PSU can be a barangay, a portion of a large barangay, or two or more adjacent small barangays.

    In the second stage, an equal take of either 20 or 26 sample housing units were selected from each sampled PSU using systematic random sampling. In situations where a housing unit contained one to three households, all households were interviewed. In the rare situation where a housing unit contained more than three households, no more than three households were interviewed. The survey interviewers were instructed to interview only the pre-selected housing units. No replacements and no changes of the preselected housing units were allowed in the implementing stage in order to prevent bias. Survey weights were calculated, added to the data file, and applied so that weighted results are representative estimates of indicators at the regional and national levels.

    All women age 15-49 who were either permanent residents of the selected households or visitors who stayed in the households the night before the survey were eligible to be interviewed. Among women eligible for an individual interview, one woman per household was selected for a module on domestic violence.

    For further details on sample design, see Appendix A of the final report.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    Two questionnaires were used for the NDHS 2017: the Household Questionnaire and the Woman’s Questionnaire. Both questionnaires, based on The DHS Program’s standard Demographic and Health Survey (DHS-7) questionnaires, were adapted to reflect the population and health issues relevant to the Philippines. Input was solicited from various stakeholders representing government agencies, universities, and international agencies.

    Cleaning operations

    The processing of the NDHS 2017 data began almost as soon as fieldwork started. As data collection was completed in each PSU, all electronic data files were transferred via an Internet file streaming system (IFSS) to the PSA central office in Quezon City. These data files were registered and checked for inconsistencies, incompleteness, and outliers. The field teams were alerted to any inconsistencies and errors while still in the PSU. Secondary editing involved resolving inconsistencies and the coding of openended questions; the former was carried out in the central office by a senior data processor, while the latter was taken on by regional coordinators and central office staff during a 5-day workshop following the completion of the fieldwork. Data editing was carried out using the CSPro software package. The concurrent processing of the data offered a distinct advantage, because it maximized the likelihood of the data being error-free and accurate. Timely generation of field check tables allowed for more effective monitoring. The secondary editing of the data was completed by November 2017. The final cleaning of the data set was carried out by data processing specialists from The DHS Program by the end of December 2017.

    Response rate

    A total of 31,791 households were selected for the sample, of which 27,855 were occupied. Of the occupied households, 27,496 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 25,690 women age 15-49 were identified for individual interviews; interviews were completed with 25,074 women, yielding a response rate of 98%.

    The household response rate is slightly lower in urban areas than in rural areas (98% and 99%, respectively); however, there is no difference by urban-rural residence in response rates among women (98% for each).

    Sampling error estimates

    The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling 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 Philippines National Demographic and Health Survey (NDHS) 2017 to minimize this type of error, nonsampling 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 NDHS 2017 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 among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

    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% 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 NDHS 2017 sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS, using programs developed by ICF. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

    A more detailed description of estimates of sampling errors are presented in Appendix B of the survey final report.

    Data appraisal

    Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months

    See details of the data quality tables in Appendix C of the survey final report.

  4. w

    Philippines - National Demographic and Health Survey 2008 - Dataset -...

    • wbwaterdata.org
    Updated Mar 16, 2020
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    (2020). Philippines - National Demographic and Health Survey 2008 - Dataset - waterdata [Dataset]. https://wbwaterdata.org/dataset/philippines-national-demographic-and-health-survey-2008
    Explore at:
    Dataset updated
    Mar 16, 2020
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Philippines
    Description

    The 2008 National Demographic and Health Survey (2008 NDHS) is a nationally representative survey of 13,594 women age 15-49 from 12,469 households successfully interviewed, covering 794 enumeration areas (clusters) throughout the Philippines. This survey is the ninth in a series of demographic and health surveys conducted to assess the demographic and health situation in the country. The survey obtained detailed information on fertility levels, marriage, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of women and young children, childhood mortality, maternal and child health, and knowledge and attitudes regarding HIV/AIDS and tuberculosis. Also, for the first time, the Philippines NDHS gathered information on violence against women. The 2008 NDHS was conducted by the Philippine National Statistics Office (NSO). Technical assistance was provided by ICF Macro through the MEASURE DHS program. Funding for the survey was mainly provided by the Government of the Philippines. Financial support for some preparatory and processing phases of the survey was provided by the U.S. Agency for International Development (USAID). Like previous Demographic and Health Surveys (DHS) conducted in the Philippines, the 2008 National Demographic and Health Survey (NDHS) was primarily designed to provide information on population, family planning, and health to be used in evaluating and designing policies, programs, and strategies for improving health and family planning services in the country. The 2008 NDHS also included questions on domestic violence. Specifically, the 2008 NDHS had the following objectives: Collect data at the national level that will allow the estimation of demographic rates, particularly, fertility rates by urban-rural residence and region, and under-five mortality rates at the national level. Analyze the direct and indirect factors which determine the levels and patterns of fertility. Measure the level of contraceptive knowledge and practice by method, urban-rural residence, and region. Collect data on family health: immunizations, prenatal and postnatal checkups, assistance at delivery, breastfeeding, and prevalence and treatment of diarrhea, fever, and acute respiratory infections among children under five years. Collect data on environmental health, utilization of health facilities, prevalence of common noncommunicable and infectious diseases, and membership in health insurance plans. Collect data on awareness of tuberculosis. Determine women's knowledge about HIV/AIDS and access to HIV testing. Determine the extent of violence against women. MAIN RESULTS FERTILITY Fertility Levels and Trends. There has been a steady decline in fertility in the Philippines in the past 36 years. From 6.0 children per woman in 1970, the total fertility rate (TFR) in the Philippines declined to 3.3 children per woman in 2006. The current fertility level in the country is relatively high compared with other countries in Southeast Asia, such as Thailand, Singapore and Indonesia, where the TFR is below 2 children per woman. Fertility Differentials. Fertility varies substantially across subgroups of women. Urban women have, on average, 2.8 children compared with 3.8 children per woman in rural areas. The level of fertility has a negative relationship with education; the fertility rate of women who have attended college (2.3 children per woman) is about half that of women who have been to elementary school (4.5 children per woman). Fertility also decreases with household wealth: women in wealthier households have fewer children than those in poorer households. FAMILY PLANNING Knowledge of Contraception. Knowledge of family planning is universal in the Philippines- almost all women know at least one method of fam-ily planning. At least 90 percent of currently married women have heard of the pill, male condoms, injectables, and female sterilization, while 87 percent know about the IUD and 68 percent know about male sterilization. On average, currently married women know eight methods of family planning. Unmet Need for Family Planning. Unmet need for family planning is defined as the percentage of currently married women who either do not want any more children or want to wait before having their next birth, but are not using any method of family planning. The 2008 NDHS data show that the total unmet need for family planning in the Philippines is 22 percent, of which 13 percent is limiting and 9 percent is for spacing. The level of unmet need has increased from 17 percent in 2003. Overall, the total demand for family planning in the Philippines is 73 percent, of which 69 percent has been satisfied. If all of need were satisfied, a contraceptive prevalence rate of about 73 percent could, theoretically, be expected. Comparison with the 2003 NDHS indicates that the percentage of demand satisfied has declined from 75 percent. MATERNAL HEALTH Antenatal Care. Nine in ten Filipino mothers received some antenatal care (ANC) from a medical professional, either a nurse or midwife (52 percent) or a doctor (39 percent). Most women have at least four antenatal care visits. More than half (54 percent) of women had an antenatal care visit during the first trimester of pregnancy, as recommended. While more than 90 percent of women who received antenatal care had their blood pressure monitored and weight measured, only 54 percent had their urine sample taken and 47 percent had their blood sample taken. About seven in ten women were informed of pregnancy complications. Three in four births in the Philippines are protected against neonatal tetanus. Delivery and Postnatal Care. Only 44 percent of births in the Philippines occur in health facilities-27 percent in a public facility and 18 percent in a private facility. More than half (56 percent) of births are still delivered at home. Sixty-two percent of births are assisted by a health professional-35 percent by a doctor and 27 percent by a midwife or nurse. Thirty-six percent are assisted by a traditional birth attendant or hilot. About 10 percent of births are delivered by C-section. The Department of Health (DOH) recommends that mothers receive a postpartum check within 48 hours of delivery. A majority of women (77 percent) had a postnatal checkup within two days of delivery; 14 percent had a postnatal checkup 3 to 41 days after delivery. CHILD HEALTH Childhood Mortality. Childhood mortality continues to decline in the Philippines. Currently, about one in every 30 children in the Philippines dies before his or her fifth birthday. The infant mortality rate for the five years before the survey (roughly 2004-2008) is 25 deaths per 1,000 live births and the under-five mortality rate is 34 deaths per 1,000 live births. This is lower than the rates of 29 and 40 reported in 2003, respectively. The neonatal mortality rate, representing death in the first month of life, is 16 deaths per 1,000 live births. Under-five mortality decreases as household wealth increases; children from the poorest families are three times more likely to die before the age of five as those from the wealthiest families. There is a strong association between under-five mortality and mother's education. It ranges from 47 deaths per 1,000 live births among children of women with elementary education to 18 deaths per 1,000 live births among children of women who attended college. As in the 2003 NDHS, the highest level of under-five mortality is observed in ARMM (94 deaths per 1,000 live births), while the lowest is observed in NCR (24 deaths per 1,000 live births). NUTRITION Breastfeeding Practices. Eighty-eight percent of children born in the Philippines are breastfed. There has been no change in this practice since 1993. In addition, the median durations of any breastfeeding and of exclusive breastfeeding have remained at 14 months and less than one month, respectively. Although it is recommended that infants should not be given anything other than breast milk until six months of age, only one-third of Filipino children under six months are exclusively breastfed. Complementary foods should be introduced when a child is six months old to reduce the risk of malnutrition. More than half of children ages 6-9 months are eating complementary foods in addition to being breastfed. The Infant and Young Child Feeding (IYCF) guidelines contain specific recommendations for the number of times that young children in various age groups should be fed each day as well as the number of food groups from which they should be fed. NDHS data indicate that just over half of children age 6-23 months (55 percent) were fed according to the IYCF guidelines. HIV/AIDS Awareness of HIV/AIDS. While over 94 percent of women have heard of AIDS, only 53 percent know the two major methods for preventing transmission of HIV (using condoms and limiting sex to one uninfected partner). Only 45 percent of young women age 15-49 know these two methods for preventing HIV transmission. Knowledge of prevention methods is higher in urban areas than in rural areas and increases dramatically with education and wealth. For example, only 16 percent of women with no education know that using condoms limits the risk of HIV infection compared with 69 percent of those who have attended college. TUBERCULOSIS Knowledge of TB. While awareness of tuberculosis (TB) is high, knowledge of its causes and symptoms is less common. Only 1 in 4 women know that TB is caused by microbes, germs or bacteria. Instead, respondents tend to say that TB is caused by smoking or drinking alcohol, or that it is inherited. Symptoms associated with TB are better recognized. Over half of the respondents cited coughing, while 39 percent mentioned weight loss, 35 percent mentioned blood in sputum, and 30 percent cited coughing with sputum. WOMEN'S STATUS Women's Status and Employment.

  5. i

    Census of Population and Housing 2010 - Philippines

    • catalog.ihsn.org
    • datacatalog.ihsn.org
    Updated Oct 10, 2017
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    National Statistics Office (2017). Census of Population and Housing 2010 - Philippines [Dataset]. https://catalog.ihsn.org/catalog/7171
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    Dataset updated
    Oct 10, 2017
    Dataset authored and provided by
    National Statistics Office
    Time period covered
    2010
    Area covered
    Philippines
    Description

    Abstract

    Census of Population and Housing (CPH) refers to the entire process of collecting, compiling, evaluating, analyzing, publishing, and disseminating data about the population and the living quarters in a country. It entails the listing and recording of the characteristics of each individual and each living quarter as of a specified time and within a specified territory. In other words, the CPH offers a “snapshot” of the entire population on a specific date, that is, how many people reside within the national borders, who they are, and where they live during such specified date. Also, included are the characteristics of the housing units where they reside.

    The 2010 CPH is designed to take an inventory of the total population and housing units in the Philippines and collect information about their characteristics. The census of population is the source of information on the size and distribution of the population, as well as their demographic, social, economic, and cultural characteristics. The census of housing, on the other hand, provides information on the stock of housing units and their structural characteristics and facilities which have bearing on the maintenance of privacy and health, and the development of normal family living conditions. These information are vital for making rational plans and programs for local and national development.

    Specifically, the 2010 CPH aims to: - obtain comprehensive data on the size, composition, and distribution of the population of the Philippines; - gather data on birth registration, literacy, school attendance, place of school, highest grade/year completed, residence 5 years ago, overseas worker, usual occupation, kind of business or industry, class of worker, place of work, fertility, religion, citizenship, ethnic group, disability, and functional difficulty, and determine their geographic distribution; - take stock of the housing units existing in the country and to get information about their geographic location, structural characteristics, and facilities, among others; - obtain information on the characteristics of the barangay, which will be used as basis for urban-rural classification; and - serve as sampling frame for use in household-based surveys.

    Data collected in this census were compiled, evaluated, analyzed, published, and disseminated for the use of government, business, industry, social scientists, other research and academic institutions, and the general public. Among the important uses of census data are the following:

    In government: - redistricting and apportionment of congressional seats; - allocation of resources and revenues; - creation of political and administrative units; - formulation of policies concerning population and housing; and - formulation of programs relative to the delivery of basic services for health, education, housing, and others

    In business and industry: - determination of sites for establishing businesses; - determination of consumer demands for various goods and services; and - determination of supply of labor for the production of goods and services

    In research and academic institutions: - conduct of researches on population and other disciplines; and - study of population growth and distribution as basis in preparing projections

    Geographic coverage

    National coverage Regions Provinces Cities and Municipalities Barangays

    Analysis unit

    household questionnaire: individuals (household members), households, housing units institutional questionnaire: individuals (institutional population), institutional living quarters barangay questionnaire: barangay

    Universe

    Census-taking in the Philippines follows a de-jure concept wherein a person is counted in the usual place of residence or the place where the person usually resides. Information on the count of the population and living quarters were collected with 12:01 a.m. of May 1, 2010 as the census reference time and date.

    The following individuals were enumerated:

    • Those who were present at the time of visit and whose usual place of residence is the housing unit where the household lives.

    • Those whose usual place of residence is the place where the household lives but are temporarily away at the time of the census.

    • Boarders/lodgers of the household or employees of household-operated businesses who do not usually return/go to their respective homes weekly.

    • Overseas workers and who have been away at the time of the census for not more than five years from the date of departure and are expected to be back within five years from the date of last departure.

    • Filipino "balikbayans" with usual place of residence in a foreign country but have resided or are expected to reside in the Philippines for at least a year from their arrival.

    • Citizens of foreign countries who have resided or are expected to reside in the Philippines for at least a year from their arrival, except members of diplomatic missions and non-Filipino members of international organizations.

    • Persons temporarily staying with the household who have no usual place of residence or who are not certain to be enumerated elsewhere.

    Kind of data

    Census/enumeration data [cen]

    Sampling procedure

    In the 2010 CPH, there are basically two types of questionnaires used for the enumeration of household members. These are CPH Form 2 or the Common Household Questionnaire and CPH Form 3 or the Sample Household Questionnaire. CPH Form 3 contains more questions than CPH Form 2.

    The 2010 CPH was carried out through a combination of complete enumeration and sampling. For this census, systematic cluster sampling was adopted. This sampling method is designed in such a way that efficient and accurate estimates will be obtained at the city/municipality level.

    The sampling rate or the proportion of households to be selected as samples depends on the size of the city/municipality where the Enumeration Area (EA) is located. For the cities/municipalities with estimated number of households of 500 and below, 100 percent sampling rate was used. While for those cities/municipalities with estimated number of households of 501 and above, a sampling rate of 20 percent was implemented.

    In this sampling scheme, each city/municipality was treated as a domain. For city/municipality with 100 percent sampling rate, all households in all the EAs within this city/municipality were selected as samples. For those with a 20 percent sampling rate, systematic cluster sampling was adopted. That is, sample selection of one in five clusters with the first cluster selected at random. Thus in effect, the EAs belonging to the city/municipality with 20 percent sampling rate are divided into clusters of size 5. Random start is pre-determined for each EA.

    If the sampling rate applied to a city/municipality is 100 percent, it means that all households in that municipality were administered with CPH Form 3. If it is 20 percent, it means that 20 percent of all households used CPH Form 3 while 80 percent used CPH Form 2.

    The random start used by EA is a number from 1 to 5 which was used to select the cluster where the first sample households in an EA, and subsequently the other sample households, were included.

    Clusters are formed by grouping together households that have been assigned consecutive serial numbers as they were listed in the Listing Booklet. For a 20 percent sampling rate, clusters were formed by grouping together five households.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    CPH Form 1 - Listing Booklet This form is a booklet used to list the buildings, housing units, households, and the Institutional Living Quarters (ILQs) within an EA. This form also records other important information such as the name of household heads and name and type of institutions and their addresses, population totals, and counts of males and females.

    CPH Form 2 - Common Household Questionnaire This is the basic census questionnaire, which was used to interview and record information about the common or nonsample households. This questionnaire gathered information on the following demographic and socio-economic characteristics of the population: relationship to household head, sex, date of birth, age, birth registration, marital status, religion, ethnicity, citizenship, disability, functional difficulty, highest grade/year completed, residence 5 years ago, and overseas worker. It also contains questions on the type of building/house, construction materials of the roof and outer walls, state of repair of the building/house, year the building/house was built, floor area of the housing unit, and tenure status of the lot.

    CPH Form 3 - Sample Household Questionnaire This is the basic census questionnaire, which was used to interview and record information about the sample households. This questionnaire contains ALL questions asked in CPH Form 2 PLUS additional population questions: literacy, school attendance, place of school, usual occupation, kind of business or industry, class of worker, place of work, and some items on fertility. Moreover, there are additional questions on household characteristics: fuel for lighting and cooking, source of water supply for drinking and/or cooking and for laundry, and bathing, tenure status of the housing unit, acquisition of the housing unit, source of financing of the housing unit, monthly rental of the housing unit, tenure status of the lot, usual manner of garbage disposal, kind of toilet facility, and land ownership. It also asked questions on the language/dialect generally spoken at home, residence five years from now, and presence of household conveniences/devices, and access to internet.

    CPH Form 4 -

  6. Enterprise Survey 2015 - Philippines

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Mar 30, 2017
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    World Bank (2017). Enterprise Survey 2015 - Philippines [Dataset]. https://microdata.worldbank.org/index.php/catalog/2800
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    Dataset updated
    Mar 30, 2017
    Dataset provided by
    World Bank Grouphttp://www.worldbank.org/
    Authors
    World Bank
    Time period covered
    2014 - 2016
    Area covered
    Philippines
    Description

    Abstract

    This survey was conducted in Philippines between November 2014 and May 2016, as part of the Enterprise Survey project, an initiative of the World Bank. The objective of the survey is to obtain feedback from enterprises on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. Through interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries. Only registered businesses are surveyed in the Enterprise Survey.

    Data from 1,335 establishments was analyzed. Stratified random sampling was used to select the surveyed businesses. The data was collected using face-to-face interviews.

    The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90% of the questions objectively ascertain characteristics of a country's business environment. The remaining questions assess the survey respondents' opinions on what are the obstacles to firm growth and performance.

    Geographic coverage

    Metro Manila, NCR excluding Manila, Metro Cebu, Central Luzon, and Calabarzon

    Analysis unit

    The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

    Universe

    The whole population, or universe of the study, is the non-agricultural economy. It comprises: all manufacturing sectors according to the group classification of ISIC Revision 3.1: (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities-sectors.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sample was selected using stratified random sampling. Three levels of stratification were used in this country: industry, establishment size, and region.

    Industry stratification was designed in the way that follows: the universe was stratified into five manufacturing industries and two services industries: Food and Beverages (ISIC Rev. 3.1 code 15), Garments (ISIC code 18), Non-metallic mineral products (ISIC code 26), Fabricated metal products (ISIC code 28), Other Manufacturing (ISIC codes 16,17, 19-25, 27, 29-37), Retail (ISIC code 52) and Other Services (ISIC codes 45, 50, 51, 55, 60-64, and 72).

    Size stratification was defined following the standardized definition for the rollout: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees).

    Regional stratification for the Philippines ES was done across five regions: Metro Manila, NCR excluding Manila, Metro Cebu, Central Luzon, and Calabarzon.

    The sample frame consisted of listings of firms from two sources: First, for panel firms the list of 1326 firms from the Philippines 2009 ES was used. Second, for fresh firms (i.e., firms not covered in 2009), economic census data from Philippines Statistics Authority (PSA) was used.

    The quality of the frame was enhanced by the verification process conducted by OIJ Business Partners. However, the sample frame was not immune from the typical problems found in establishment surveys: positive rates of non-eligibility, repetition, non-existent units, etc.

    Given the impact that non-eligible units included in the sample universe may have on the results, adjustments may be needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of sampled establishments contacted for the survey was 3.7% (135 out of 3,649 establishments).

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The structure of the data base reflects the fact that two different versions of the survey instrument were used for all registered establishments. Questionnaires have common questions (core module) and respectfully additional manufacturing- and services-specific questions. The eligible manufacturing industries have been surveyed using the Manufacturing questionnaire (includes the core module, plus manufacturing specific questions). Retail firms have been interviewed using the Services questionnaire (includes the core module plus retail specific questions) and the residual eligible services have been covered using the Services questionnaire (includes the core module). Each variation of the questionnaire is identified by the index variable, a0.

    Cleaning operations

    Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

    Response rate

    Survey non-response must be differentiated from item non-response. The former refers to refusals to participate in the survey altogether whereas the latter refers to the refusals to answer some specific questions. Enterprise Surveys suffer from both problems and different strategies were used to address these issues.

    Item non-response was addressed by two strategies: a- For sensitive questions that may generate negative reactions from the respondent, such as corruption or tax evasion, enumerators were instructed to collect "Refusal to respond" (-8) as a different option from "Don't know" (-9). b- Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary.

    Survey non-response was addressed by maximizing efforts to contact establishments that were initially selected for interview. Attempts were made to contact the establishment for interview at different times/days of the week before a replacement establishment (with similar strata characteristics) was suggested for interview. Survey non-response did occur but substitutions were made in order to potentially achieve strata-specific goals.

    The number of interviews per contacted establishments was 0.36. This number is the result of two factors: explicit refusals to participate in the survey, as reflected by the rate of rejection (which includes rejections of the screener and the main survey) and the quality of the sample frame, as represented by the presence of ineligible units. The number of rejections per contact was 0.34.

  7. World Bank Enterprise Survey 2023 - Philippines

    • microdata.worldbank.org
    • datacatalog.ihsn.org
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    Updated Jan 22, 2025
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    World Bank Group (WBG) (2025). World Bank Enterprise Survey 2023 - Philippines [Dataset]. https://microdata.worldbank.org/index.php/catalog/6464
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    Dataset updated
    Jan 22, 2025
    Dataset provided by
    World Bank Grouphttp://www.worldbank.org/
    Authors
    World Bank Group (WBG)
    Time period covered
    2023 - 2024
    Area covered
    Philippines
    Description

    Abstract

    The World Bank Enterprise Survey (WBES) is a firm-level survey of a representative sample of an economy's private sector. The surveys cover a broad range of topics related to the business environment including access to finance, corruption, infrastructure, competition, and performance.

    Geographic coverage

    National coverage

    Analysis unit

    The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

    Universe

    The universe of inference includes all formal (i.e., registered) private sector businesses (with at least 1% private ownership) and with at least five employees. In terms of sectoral criteria, all manufacturing businesses (ISIC Rev 4. codes 10-33) are eligible; for services businesses, those corresponding to the ISIC Rev 4 codes 41-43, 45-47, 49-53, 55-56, 58, 61-62, 69-75, 79, and 95 are included in the Enterprise Surveys. Cooperatives and collectives are excluded from the Enterprise Surveys. All eligible establishments must be registered with the registration agency. In the case of the Philippines, the listing from the PSA’s List of Establishments (LE), a registrar of businesses operating in the Philippines, was used. The registration agency is the Securities and Exchange Commission (SEC).

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The WBES use stratified random sampling, where the population of establishments is first separated into non-overlapping groups, called strata, and then respondents are selected through simple random sampling from each stratum. The detailed methodology is provided in the Sampling Note (https://www.enterprisesurveys.org/content/dam/enterprisesurveys/documents/methodology/Sampling_Note-Consolidated-2-16-22.pdf). Stratified random sampling has several advantages over simple random sampling. In particular, it:

    • produces unbiased estimates of the whole population or universe of inference, as well as at the levels of stratification
    • ensures representativeness by including observations in all of those categories
    • produces more precise estimates for a given sample size or budget allocation, and
    • may reduce implementation costs by splitting the population into convenient subdivisions.

    The WBES typically use three levels of stratification: industry classification, establishment size, and subnational region (used in combination). Starting in 2022, the WBES bases the industry classification on ISIC Rev. 4 (with earlier surveys using ISIC Rev. 3.1). For regional coverage within a country, the WBES has national coverage.

    Note: Refer to Sampling Structure section in "The Philippines 2023 World Bank Enterprise Survey Implementation Report" for detailed methodology on sampling.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The standard WBES questionnaire covers several topics regarding the business environment and business performance. These topics include general firm characteristics, infrastructure, sales and supplies, management practices, competition, innovation, capacity, land and permits, finance, business-government relations, exposure to bribery, labor, and performance. Information about the general structure of the questionnaire is available in the Enterprise Surveys Manual and Guide (https://www.enterprisesurveys.org/content/dam/enterprisesurveys/documents/methodology/Enterprise-Surveys-Manual-and-Guide.pdf).

    The questionnaire implemented in the Philippines 2023 WBES included additional questions tailored for the Business Ready Report covering infrastructure, trade, government regulations, finance, labor, and other topics.

    Response rate

    Overall survey response rate was 68.0%.

  8. Enterprise Survey 2009 - Philippines

    • datacatalog.ihsn.org
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    • +2more
    Updated Mar 29, 2019
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    World Bank (2019). Enterprise Survey 2009 - Philippines [Dataset]. https://datacatalog.ihsn.org/catalog/729
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    Dataset updated
    Mar 29, 2019
    Dataset provided by
    World Bank Grouphttp://www.worldbank.org/
    Authors
    World Bank
    Time period covered
    2009
    Area covered
    Philippines
    Description

    Abstract

    This research was conducted in Philippines between May and December 2009 as part of the Enterprise Survey initiative.

    The objective of the survey is to obtain feedback from enterprises in client countries on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. Through interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries.

    The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.

    Geographic coverage

    National

    Analysis unit

    The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

    Universe

    The whole population, or the universe, covered in the Enterprise Surveys is the non-agricultural economy. It comprises: all manufacturing sectors according to the ISIC Revision 3.1 group classification (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this population definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities-sectors.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sample for Philippines was selected using stratified random sampling. Three levels of stratification were used in this country: industry, establishment size, and region.

    Industry stratification was designed in the way that follows: the universe was stratified into 6 manufacturing industries, 1 services industry -retail -, and two residual sectors. Each manufacturing industry had a target of 160 interviews. The services industry and the two residual sectors had a target of 120 interviews. For the manufacturing industries sample sizes were inflated by about 33% to account for potential non-response cases when requesting sensitive financial data and also because of likely attrition in future surveys that would affect the construction of a panel. An additional 85 interviews were added to the survey half way through the fieldwork. Targets were adjusted such that the manufacturing sectors' targets were increased to 160-180 interviews.

    Size stratification was defined following the standardized definition for the rollout: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees). For stratification purposes, the number of employees was defined on the basis of reported permanent full-time workers. This seems to be an appropriate definition of the labor force since seasonal/casual/part-time employment is not a common practice, except in the sectors of construction and agriculture.

    Regional stratification was defined in four regions: National Capital Region excluding Manila; Manila; Region III; Region IV; and Metro-Cebu (Region VII). These are the largest population and economic centers of the Philippines. National Capital Region and Manila were split because of the large size of the National Capital Region. Metro-Cebu specifically was surveyed, rather than the whole of Region VII, for logistical reasons as this region is widespread and includes many remote and sparsely populated locations.

    The sample frame used in the Philippines was obtained from the 2008 National Statistics Office of the Philippines (NSO) Register of Establishments. A key limitation in using this sample frame was the cost of access, which significantly limited the size of sample available for survey limitation. As a result of concerns over confidentiality, NSO also required that sample selection was done by 3 NSO in-house under instruction of the World Bank team in Washington D.C.This database contained the following information: -Name of the firm -Location -Contact details -ISIC code -Number of employees.

    Given the impact that non-eligible units included in the sample universe may have on the results, adjustments may be needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of sampled establishments contacted for the survey was 16% (319 out of 2022 establishments). Breaking down by industry, the following numbers of establishments were surveyed: 15 (Food) - 166, 18 (Garments) - 154, 24 (Chemicals) - 162, 25 (Plastic & Rubber) - 163, 26 (Non-metallic mineral products) - 151, 31 & 32 (Electronics) - 164, Other manufacturing - 122, Retail & IT - 117, Other services - 127.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The current survey instruments are available: - Core Questionnaire + Manufacturing Module [ISIC Rev.3.1: 15-37] - Core Questionnaire + Retail Module [ISIC Rev.3.1: 52] - Core Questionnaire [ISIC Rev.3.1: 45, 50, 51, 55, 60-64, 72] - Screener Questionnaire.

    The “Core Questionnaire” is the heart of the Enterprise Survey and contains the survey questions asked of all firms across the world. There are also two other survey instruments - the “Core Questionnaire + Manufacturing Module” and the “Core Questionnaire + Retail Module.” The survey is fielded via three instruments in order to not ask questions that are irrelevant to specific types of firms, e.g. a question that relates to production and nonproduction workers should not be asked of a retail firm. In addition to questions that are asked across countries, all surveys are customized and contain country-specific questions. An example of customization would be including tourism-related questions that are asked in certain countries when tourism is an existing or potential sector of economic growth.

    The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance.

    Cleaning operations

    Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

    Response rate

    Complete information regarding the sampling methodology, sample frame, weights, response rates, and implementation can be found in "Description of Philippines Implementation 2009" in "Technical Documents" folder.

  9. i

    National Demographic and Health Survey 2013 - Philippines

    • catalog.ihsn.org
    • datacatalog.ihsn.org
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    Updated Jul 6, 2017
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    National Statistics Office (NSO) (2017). National Demographic and Health Survey 2013 - Philippines [Dataset]. https://catalog.ihsn.org/catalog/5449
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    Dataset updated
    Jul 6, 2017
    Dataset authored and provided by
    National Statistics Office (NSO)
    Time period covered
    2013
    Area covered
    Philippines
    Description

    Abstract

    The 2013 NDHS is designed to provide information on fertility, family planning, and health in the country for use by the government in monitoring the progress of its programs on population, family planning and health.

    In particular, the 2013 NDHS has the following specific objectives: • Collect data which will allow the estimation of demographic rates, particularly fertility rates and under-five mortality rates by urban-rural residence and region. • Analyze the direct and indirect factors which determine the level and patterns of fertility. • Measure the level of contraceptive knowledge and practice by method, urban-rural residence, and region. • Collect data on health, immunizations, prenatal and postnatal check-ups, assistance at delivery, breastfeeding, and prevalence and treatment of diarrhea, fever and acute respiratory infections among children below five years old. • Collect data on environmental health, utilization of health facilities, health care financing, prevalence of common non-communicable and infectious diseases, and membership in the National Health Insurance Program (PhilHealth). • Collect data on awareness of cancer, heart disease, diabetes, dengue fever and tuberculosis. • Determine the knowledge of women about AIDS, and the extent of misconception on HIV transmission and access to HIV testing. • Determine the extent of violence against women.

    Geographic coverage

    National coverage

    Analysis unit

    • Household
    • Individuals/ persons
    • Woman age 15 to 49

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sample selection methodology for the 2013 NDHS is based on a stratified two-stage sample design, using the 2010 Census of Population and Housing (CPH) as a frame. The first stage involved a systematic selection of 800 sample enumeration areas (EAs) distributed by stratum (region, urban/rural). In the second stage, 20 sample housing units were selected from each sample EA, using systematic random sampling.

    All households in the sampled housing units were interviewed. An EA is defined as an area with discern able boundaries consisting of contiguous households. The sample was designed to provide data representative of the country and its 17 administrative regions.

    Further details on the sample design and implementation are given in Appendix A of the final report.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The 2013 NDHS used three questionnaires: Household Questionnaire, Individual Woman’s Questionnaire, and Women’s Safety Module. The development of these questionnaires resulted from the solicited comments and suggestions during the deliberation in the consultative meetings and separate meetings conducted with the various agencies/organizations namely: PSA-NSO, POPCOM, DOH, FNRI, ICF International, NEDA, PCW, PhilHealth, PIDS, PLCPD, UNFPA, USAID, UPPI, UPSE, and WHO. The three questionnaires were translated from English into six major languages - Tagalog, Cebuano, Ilocano, Bicol, Hiligaynon, and Waray.

    The main purpose of the Household Questionnaire was to identify female members of the sample household who were eligible for interview with the Individual Woman’s Questionnaire and the Women’s Safety Module.

    The Individual Woman’s Questionnaire was used to collect information from all women aged 15-49 years.

    The Women’s Safety Module was used to collect information on domestic violence in the country, its prevalence, severity and frequency from only one selected respondent from among all the eligible women who were identified from the Household Questionnaire.

    Cleaning operations

    All completed questionnaires and the control forms were returned to the PSA-NSO central office in Manila for data processing, which consisted of manual editing, data entry and verification, and editing of computer-identified errors. An ad-hoc group of thirteen regular employees from the DSSD, the Information Resources Department (IRD), and the Information Technology Operations Division (ITOD) of the NSO was created to work fulltime and oversee data processing operation in the NDHS Data Processing Center that was carried out at the NSO-CVEA Building in Quezon City, Philippines. This group was responsible for the different aspects of NDHS data processing. There were 19 data encoders hired to process the data who underwent training on September 12-13, 2013.

    Data entry started on September 16, 2013. The computer package program called Census and Survey Processing System (CSPro) was used for data entry, editing, and verification. Mr. Alexander Izmukhambetov, a data processing specialist from ICF International, spent two weeks at NSO in September 2013 to finalize the data entry program. Data processing was completed on December 6, 2013.

    Response rate

    For the 2013 NDHS sample, 16,732 households were selected, of which 14,893 were occupied. Of these households, 14,804 were successfully interviewed, yielding a household response rate of 99.4 percent. The household response rates in urban and rural areas are almost identical.

    Among the households interviewed, 16,437 women were identified as eligible respondents, and the interviews were completed for 16,155 women, yielding a response rate of 98.3 percent. On the other hand, for the women’s safety module, from a total of 11,373 eligible women, 10,963 were interviewed with privacy, translating to a 96.4 percent response rate. At the individual level, urban and rural response rates showed no difference. The principal reason for non-response among women was the failure to find individuals at home, despite interviewers’ repeated visits to the household.

    Sampling error estimates

    The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling 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 2013 National Demographic and Health Survey (NDHS) to minimize this type of error, nonsampling 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 2013 NDHS is only one of many samples that could have been selected from the same population, using the same design and identical size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling error is a measure of the variability between the results of all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey data.

    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 2013 NDHS sample is the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 2013 NDHS is a SAS program. This program used the Taylor linearization method for variance estimation for survey estimates that are means or proportions. The Jackknife repeated replications method is used for variance estimation of more complex statistics such as fertility and mortality rates.

    The Taylor linearization method treats any percentage or average as a ratio estimate, r = y/x, where y represents the total sample value for variable y, and x represents the total number of weighted cases in the group or subgroup under consideration.

    Further details on sampling errors calculation are given in Appendix B of the final report.

    Data appraisal

    Data quality tables were produced to review the quality of the data: - Household age distribution - Age distribution of eligible and interviewed women - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months

    Note: The tables are presented in APPENDIX C of the final report.

  10. Food Insecurity Experience Scale 2018 - Philippines

    • catalog.ihsn.org
    • microdata.worldbank.org
    Updated Dec 5, 2019
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    FAO Statistics Division (2019). Food Insecurity Experience Scale 2018 - Philippines [Dataset]. https://catalog.ihsn.org/index.php/catalog/8439
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    Dataset updated
    Dec 5, 2019
    Dataset provided by
    Food and Agriculture Organizationhttp://fao.org/
    Authors
    FAO Statistics Division
    Time period covered
    2018
    Area covered
    Philippines
    Description

    Abstract

    Sustainable Development Goal (SDG) target 2.1 commits countries to end hunger, ensure access by all people to safe, nutritious and sufficient food all year around. Indicator 2.1.2, “Prevalence of moderate or severe food insecurity based on the Food Insecurity Experience Scale (FIES)”, provides internationally-comparable estimates of the proportion of the population facing difficulties in accessing food. More detailed background information is available at http://www.fao.org/in-action/voices-of-the-hungry/fies/en/ .

    The FIES-based indicators are compiled using the FIES survey module, containing 8 questions. Two indicators can be computed: 1. The proportion of the population experiencing moderate or severe food insecurity (SDG indicator 2.1.2), 2. The proportion of the population experiencing severe food insecurity. These data were collected by FAO through the Gallup World Poll. General information on the methodology can be found here: https://www.gallup.com/178667/gallup-world-poll-work.aspx. National institutions can also collect FIES data by including the FIES survey module in nationally representative surveys.

    Microdata can be used to calculate the indicator 2.1.2 at national level. Instructions for computing this indicator are described in the methodological document available under the "DOCUMENTATION" tab above. Disaggregating results at sub-national level is not encouraged because estimates will suffer from substantial sampling and measurement error.

    Geographic coverage

    National coverage

    Analysis unit

    Individuals

    Universe

    Individuals of 15 years or older.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The country was stratified by major areas (NCR, Balance Luzon, Visayas, and Mindanao). Exclusions: Some areas were excluded from the sampling frame, due to security concerns (such as barangays considered as war zones in Marawi) and areas that are remote or inaccessible. The excluded population from these areas represent less than 1% of the population. Design effect: 1.41

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The questionnaire is provided as an external resource in the Documentation Section.

    Cleaning operations

    Statistical validation assesses the quality of the FIES data collected by testing their consistency with the assumptions of the Rasch model. This analysis involves the interpretation of several statistics that reveal 1) items that do not perform well in a given context, 2) cases with highly erratic response patterns, 3) pairs of items that may be redundant, and 4) the proportion of total variance in the population that is accounted for by the measurement model.

    Sampling error estimates

    The margin of error is estimated as 3.7. This is calculated around a proportion at the 95% confidence level. The maximum margin of error was calculated assuming a reported percentage of 50% and takes into account the design effect.

  11. a

    Canada's Military and Veteran Population by Age, Hamilton CMA, 2023

    • hamiltondatacatalog-mcmaster.hub.arcgis.com
    Updated Jul 12, 2024
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    koke_McMaster (2024). Canada's Military and Veteran Population by Age, Hamilton CMA, 2023 [Dataset]. https://hamiltondatacatalog-mcmaster.hub.arcgis.com/items/0865b00000614b9cae8b3bf6c1eae188
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    Dataset updated
    Jul 12, 2024
    Dataset authored and provided by
    koke_McMaster
    Area covered
    Hamilton, Canada
    Description

    Demographic characteristics of Canada's military and veteran population: Canada, provinces and territories, census metropolitan areas and census agglomerations with partsFrequency: OccasionalTable: 98-10-0142-01Release date: 2023-11-15Geography: Canada, Province or territory, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration partUniverse: Population aged 17 and over in private households, 2021 Census — 25% Sample dataVariable List: Visible minority (15), Religion (25), Generation status (4), Age (10B), Gender (3), Statistics (3), Military service status (4A)Footnotes: 1 Religion Religion refers to the person's self-identification as having a connection or affiliation with any religious denomination, group, body, or other religiously defined community or system of belief. Religion is not limited to formal membership in a religious organization or group. For infants or children, religion refers to the specific religious group or denomination in which they are being raised, if any. Persons without a religious connection or affiliation can self-identify as atheist, agnostic or humanist, or can provide another applicable response. 2 Generation status Generation status refers to whether or not the person or the person's parents were born in Canada. 3 Age 'Age' refers to the age of a person (or subject) of interest at last birthday (or relative to a specified, well-defined reference date). 4 Gender Gender refers to an individual's personal and social identity as a man, woman or non-binary person (a person who is not exclusively a man or a woman). Gender includes the following concepts: gender identity, which refers to the gender that a person feels internally and individually; gender expression, which refers to the way a person presents their gender, regardless of their gender identity, through body language, aesthetic choices or accessories (e.g., clothes, hairstyle and makeup), which may have traditionally been associated with a specific gender. A person's gender may differ from their sex at birth, and from what is indicated on their current identification or legal documents such as their birth certificate, passport or driver's licence. A person's gender may change over time. Some people may not identify with a specific gender. 5 Given that the non-binary population is small, data aggregation to a two-category gender variable is sometimes necessary to protect the confidentiality of responses provided. In these cases, individuals in the category “non-binary persons” are distributed into the other two gender categories and are denoted by the “+” symbol. 6 Visible minority Visible minority refers to whether a person is a visible minority or not, as defined by the Employment Equity Act. The Employment Equity Act defines visible minorities as persons other than Aboriginal peoples who are non-Caucasian in race or non-white in colour." The visible minority population consists mainly of the following groups: South Asian Chinese Black Filipino Arab Latin American Southeast Asian West Asian Korean and Japanese." 7 Military service status Military service status refers to whether or not the person is currently serving or has previously served in the Canadian military. Military service status is asked of all Canadians aged 17 and older. For the purposes of the 2021 Census, Canadian military service includes service with the Regular Force or Primary Reserve Force as an Officer or Non-Commissioned Member. It does not include service with the Cadets, Cadet Organizations Administration and Training Service (COATS) instructors or the Canadian Rangers. 8 For more information on religion variables, including information on their classifications, the questions from which they are derived, data quality and their comparability with other sources of data, please refer to the Religion Reference Guide, Census of Population, 2021. 9 For more information on generation status variables, including information on their classifications, the questions from which they are derived, data quality and their comparability with other sources of data, please refer to the Place of Birth, Generation Status, Citizenship and Immigration Reference Guide, Census of Population, 2021. 10 Visible minority" refers to whether a person is a visible minority or not as defined by the Employment Equity Act. The Employment Equity Act defines visible minorities as "persons other than Aboriginal peoples who are non-Caucasian in race or non-white in colour." The visible minority population consists mainly of the following groups: South Asian Chinese Black Filipino Arab Latin American Southeast Asian West Asian Korean and Japanese. In 2021 Census analytical and communications products the term "visible minority" has been replaced by the terms "racialized population" or "racialized groups" reflecting the increased use of these terms in the public sphere."11 For more information on visible minority and population group variables, including information on their classifications, the questions from which they are derived, data quality and their comparability with other sources of data, please refer to the Visible Minority and Population Group Reference Guide, Census of Population, 2021. 12 For more information on the military service status variable, including data quality and comparability with other sources of data, please refer to the Canadian Military Experience Reference Guide, Census of Population, 2021.

  12. e

    Data from: Exploring Adolescents’ Perceptions of a Self-Report Measure on...

    • b2find.eudat.eu
    • beta.ukdataservice.ac.uk
    Updated Oct 7, 2016
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    (2016). Exploring Adolescents’ Perceptions of a Self-Report Measure on Violence Against Children: A Multi-Country Study in Romania, South Africa, and the Philippines, 2018-2019 [Dataset]. https://b2find.eudat.eu/dataset/a202359b-8707-5f3e-bc1f-f13408c26270
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    Dataset updated
    Oct 7, 2016
    Area covered
    South Africa, Philippines
    Description

    This study aimed to investigate adolescent's cognitive processes and their thoughts and feelings when answering the International Society for the Prevention of Child Abuse and Neglect Child Abuse Screening Tool - ICAST-C. This study used face-to-face semi-structured cognitive interviews, employing a combination of think aloud, structured and spontaneous verbal probing, and observations. The sample in this study consisted of 53 adolescents aged 10-17 years across three contexts. Interviews were conducted with 17 participants in Romania, 20 participants in South Africa, and 16 participants in the Philippines. This study adopted a purposive sampling strategy. In addition to purposive sampling, this study employed maximum variation sampling. Maximum variation sampling is an appropriate strategy when the study aims to understand the variability of views existing in a particular group. Geographical and cultural variation, as well as variation in age, gender, and previous research exposure, were considerations in implementing this strategy. Both research-exposed (those who had answered a self-report violence measure) and research non-exposed (those who had not answered a self-report violence measure) participants were recruited. Apart from these considerations, participants were recruited on the basis of age (those aged between 10-17 years) and gender (male, female, and other gender identities).Globally, 95 million children become victims of physical, emotional and sexual child abuse every year. Child abuse has lifetime impacts including medical trauma, mental health distress, illness, school drop-out and unemployment. We know there is also a cycle of violence across generations. In other words, victims of child abuse are more likely to commit violent crime and to abuse their own children. They are also more likely to become a victim of violence again, both in childhood and in their adult relationships. Child abuse also has a hidden but massive impact on society because of illness and disability, costing an estimated 124 billion USD a year in the United States. But why do child abuse rates remain so inexplicably high? Child abuse is a complex problem that reaches across the home and community. In order to combat child abuse, we need to understand how many children are affected, where they are and who is most at risk. Then we need effective interventions to prevent and reduce child abuse. However, we know very little about either. A small number of high-income countries have social services data but these only identify the tip of the iceberg; most child abuse is never reported to services. To detect abuse within the whole population, we need to conduct surveys. That being said, the only child abuse measures available are lengthy and detailed, and they are therefore costly to carry out nationally. If a short child abuse measure existed, it could be included in larger, regularly conducted surveys (e.g. Demographic and Health Surveys or census). Interventions aim to prevent and reduce abuse, but there is currently no child abuse measure that can test whether such interventions have worked. A measure needs to be designed to detect changes in how severe and how often abusive behaviours occur. At the moment, researchers often use proxy measures for abuse, such as parenting stress. This study has two aims: (1) to develop a brief child abuse measure for the inclusion in large surveys, and (2) to test and validate a sensitive child abuse measure for use in intervention evaluation research. These will then be made available, together with a user manual, at no cost. To combat child abuse, we need strong collaborations between research and policy. I have already established strong partnerships with a number of academic institutions and international organisations in child protection. I have developed a prototype of the measure for intervention testing, and this is being used in six studies with 3800 participants in South Africa, Tanzania, the Democratic Republic of Congo and the Philippines. My collaborators will share the data, allowing me to conduct statistical analysis on how and whether the measure works. I will also conduct analyses testing whether the tool measures the same concepts across cultures. Finally, I will carry out qualitative research with key stakeholders in child protection to find the best questions for the short child abuse measure. To complement this, I will use statistical techniques on the pooled dataset to identify questions that can be used in surveys. This project can have a large impact on global child abuse prevention efforts. It will help researchers and policy-makers to measure accurately the number of children affected and determine whether interventions really work. It is an essential step in creating high quality evidence for protecting the world's children.

  13. i

    Family Income and Expenditure Survey 2006 - Philippines

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    Updated Mar 29, 2019
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    National Statistics Office (2019). Family Income and Expenditure Survey 2006 - Philippines [Dataset]. https://datacatalog.ihsn.org/catalog/2079
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    Dataset updated
    Mar 29, 2019
    Dataset authored and provided by
    National Statistics Office
    Time period covered
    2006 - 2007
    Area covered
    Philippines
    Description

    Abstract

    The 2006 Family Income and Expenditure Survey (FIES) had the following primary objectives:

    1) to gather data on family income and family expenditure and related information affecting income and expenditure levels and patterns in the Philippines; 2) to determine the sources of income and income distribution, levels of living and spending patterns, and the degree of inequality among families; 3) to provide benchmark information to update weights for the estimation of consumer price index; and 4) to provide information for the estimation of the country's poverty threshold and incidence.

    Geographic coverage

    The 2003 Master Sample (MS) considers the country's 17 administrative regions as the sampling domains. A domain is referred to as a subdivision of the country for which estimates with adequate level of precision are generated. It must be noted that while there is demand for data at the provincial level (and to some extent municipal and barangay levels), the provinces were not treated as sampling domains because there are more than 80 provinces which would entail a large resource requirement.

    Analysis unit

    The unit of analysis is the family. A family consists of the household head, spouse, unmarried children, ever-married children, son-in-law/daughter-in-law, parents of the head/spouse and other relatives who are members of the household.

    In households where there are two or more persons not related to each other by blood, marriage or adoption, only the income and expenditure of the member who is considered as the household head is included.

    Institutional population is not within the scope of the survey.

    Universe

    All households and members of households nationwide

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The 2003 Master Sample (MS) considers the country's 17 administrative regions as defined in Executive Orders (EO) 36 and 131 as the sampling domains. A domain is referred to as a subdivision of the country for which estimates with adequate level of precision are generated. It must be noted that while there is demand for data at the provincial level (and to some extent municipal and barangay levels), the provinces were not treated as sampling domains because there are more than 80 provinces which would entail a large resource requirement.

    As in most household surveys, the 2003 MS made use of an area sample design. For this purpose, the Enumeration Area Reference File (EARF) of the 2000 Census of Population and Housing (CPH) was utilized as sampling frame. The EARF contains the number of households by enumeration area (EA) in each barangay.

    This frame was used to form the primary sampling units (PSUs). With consideration of the period for which the 2003 MS will be in use, the PSUs were formed/defined as a barangay or a combination of barangays with at least 500 households.

    The 2003 MS considers the 17 regions of the country as the primary strata. Within each region, further stratification was performed using geographic groupings such as provinces, highly urbanized cities (HUCs), and independent component cities (ICCs). Within each of these substrata formed within regions, the PSUs were further stratified, to the extent possible, using the proportion of strong houses (PSTRONG), indicator of engagement in agriculture of the area (AGRI), and a measure of per capita income (PERCAPITA) as stratification factors.

    The 2003 MS consists of a sample of 2,835 PSUs. The entire MS was divided into four sub-samples or independent replicates, such as a quarter sample contains one fourth of the total PSUs; a half sample contains one-half of the four sub-samples or equivalent to all PSUs in two replicates. The final number of sample PSUs for each domain was determined by first classifying PSUs as either selfrepresenting (SR) or non-self-representing (NSR). In addition, to facilitate the selection of sub-samples, the total number of NSR PSUs in each region was adjusted to make it a multiple of 4. SR PSUs refers to a very large PSU in the region/domain with a selection probability of approximately 1 or higher and is outright included in the MS; it is properly treated as a stratum; also known as certainty PSU. NSR PSUs refers to a regular too small sized PSU in a region/domain; also known as non certainty PSU. The 2003 MS consists of 330 certainty PSUs and 2,505 non-certainty PSUs. To have some control over the sub-sample size, the PSUs were selected with probability proportional to some estimated measure of size. The size measure refers to the total number of households from the 2000 CPH. Because of the wide variation in PSU sizes, PSUs with selection probabilities greater than 1 were identified and were included in the sample as certainty selections.

    At the second stage, enumeration areas (EAs) were selected within sampled PSUs, and at the third stage, housing units were selected within sampled EAs. Generally, all households in sampled housing units were enumerated, except for few cases when the number of households in a housing unit exceeds three. In which case, a sample of three households in a sampled housing unit was selected at random with equal probability.

    An EA is defined as an area with discernable boundaries within barangays consisting of about 150 contiguous households. These EAs were identified during the 2000 CPH. A housing unit, on the other hand, is a structurally separate and independent place of abode which, by the way it has been constructed, converted, or arranged, is intended for habitation by a household.

    The 2006 FIES involved the interview of a national sample of about 51,000 sample households deemed sufficient to gather data on family income and family expenditure and related information affecting income and expenditure levels and patterns in the Philippines at the national and regional level. The sample households covered in the survey were the same households interviewed in the July 2006 and January 2007 round of the LFS.

    Sampling deviation

    The estimates from the 2006 FIES include results of the first FIES visit for the NCR based on questionnaires recovered from fire. The fire that hit the NCR’s Statistics Office on October 3, 2006 damaged 58 percent of the total questionnaires for the FIES first visit. Questionnaires that were encoded and processed cover around 42 percent of these questionnaires. In the preliminary results, values for the burned questionnaires were imputed using a ratio which requires data from the recovered questionnaires and data from corresponding questionnaires from the second visit. The ratio was computed by getting the sums of the total income and total expenditure in the recovered questionnaires from the first visit and the sums of the same data from corresponding second visit questionnaires and then by dividing the sums from the second visit by the sums from the first visit. The annual estimates on income and expenditure for NCR were computed by dividing the second visit values by the computed ratio. For the final results, the annual estimates for the NCR were computed by multiplying by 2 the second visit data. This imputation procedure was opted after it has been established that there was no significant difference between using the ratio and the multiplier ‘2’.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The 2006 FIES adopts a questionnaire design wherein separate questionnaire with the same sets of questions for both visits will be used. The sample household is interviewed in two separate operations each time using the half-year period preceding the interview as reference period. This scheme envisions to improve the quality of data gathered since it minimizes memory bias of respondents and at the same time captures the seasonality of income and expenditure patterns. The use of separate questionnaire with the same set of questions for both visits was used starting 2003 FIES. In previous FIES, the same set of questions for each semester (two enumeration periods) were contained in one questionnaire.

    To further reduce memory bias, the concept of "average week" consumption for all food items shall be utilized for the 2006 FIES. Moreover, the reference period for Fuel, Light and Water, Transportation and Communication, Household Operations and Personal Care and Effects is limited to the past month and in some specified cases, the concept of average month consumption shall be used. For all other expenditure groups, the past six months shall be used as reference period.

    The questionnaire has four main parts consisting of the following:

    Part I. Identification and Other Information (page 1-3) (Geographic Identification, Other Information and Particulars about the Family)

    Part II. Expenditures (page 4-45) Section A. Food, Alcoholic Beverages and Tobacco Section B. Fuel, Light and Water, Transportation and Communication, and Household Operations Section C. Personal Care and Effects, Clothing Footwear and Other Wear Section D. Education, Recreation, and Medical Care Section E. Furnishings and Equipment Section F. Taxes Section G. Housing, House Maintenance and Minor Repairs Section H. Miscellaneous Expenditures Section I. Other Disbursements

    Part III. Income (page 46-55) Section A. Salaries and Wages from Employment Section B. Net Share of Crops, Fruits and Vegetables Produced and/or Livestock and Poultry Raised by Other Households Section C. Other Sources of Income Section D. Other Receipts Section

  14. i

    World Values Survey 2012, Wave 6 - Philippines

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    Updated Jan 16, 2021
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    Jorge V. Tigno (2021). World Values Survey 2012, Wave 6 - Philippines [Dataset]. https://datacatalog.ihsn.org/catalog/9029
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    Dataset updated
    Jan 16, 2021
    Dataset provided by
    Linda Luz Guerrero
    Jorge V. Tigno
    Joseph Licudine
    Time period covered
    2012
    Area covered
    Philippines
    Description

    Abstract

    The World Values Survey (www.worldvaluessurvey.org) is a global network of social scientists studying changing values and their impact on social and political life, led by an international team of scholars, with the WVS association and secretariat headquartered in Stockholm, Sweden.

    The survey, which started in 1981, seeks to use the most rigorous, high-quality research designs in each country. The WVS consists of nationally representative surveys conducted in almost 100 countries which contain almost 90 percent of the world’s population, using a common questionnaire. The WVS is the largest non-commercial, cross-national, time series investigation of human beliefs and values ever executed, currently including interviews with almost 400,000 respondents. Moreover the WVS is the only academic study covering the full range of global variations, from very poor to very rich countries, in all of the world’s major cultural zones.

    The WVS seeks to help scientists and policy makers understand changes in the beliefs, values and motivations of people throughout the world. Thousands of political scientists, sociologists, social psychologists, anthropologists and economists have used these data to analyze such topics as economic development, democratization, religion, gender equality, social capital, and subjective well-being. These data have also been widely used by government officials, journalists and students, and groups at the World Bank have analyzed the linkages between cultural factors and economic development.

    Geographic coverage

    National.

    Analysis unit

    Household Individual

    Universe

    National Population, Both sexes,18 and more years.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Sample size: 1200

    Sampling scheme. The Philippines was divided into four study areas: National Capital Region (NCR), Balance Luzon, Visayas, and Mindanao. Multi-stage probability sampling will be used in the selection of sample spots. For the National Capital Region - Stage 1. Selection of Sample Spots (Barangays); Stage 2. Selection of Sample Households; Stage 3. Selection of Sample Adult. For the rest of the Philippines - Stage 1. Allocation and Selection of Sample Provinces; Stage 2. Allocation and selection of sample municipalities; Stage 3. Allocation and Selection of Sample Spots; Stage 4. Selection of Sample Households and; Stage 5. Selection of Sample Respondents. For more information on the sampling procedure refer to the related materials section.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    For each wave, suggestions for questions are solicited by social scientists from all over the world and a final master questionnaire is developed in English. Since the start in 1981 each successive wave has covered a broader range of societies than the previous one. Analysis of the data from each wave has indicated that certain questions tapped interesting and important concepts while others were of little value. This has led to the more useful questions or themes being replicated in future waves while the less useful ones have been dropped making room for new questions.

    The questionnaire is translated into the various national languages and in many cases independently translated back to English to check the accuracy of the translation. In most countries, the translated questionnaire is pre-tested to help identify questions for which the translation is problematic. In some cases certain problematic questions are omitted from the national questionnaire.

    WVS requires implementation of the common questionnaire fully and faithfully, in all countries included into one wave. Any alteration to the original questionnaire has to be approved by the EC. Omission of no more than a maximum of 12 questions in any given country can be allowed.

    Sampling error estimates

    Estimated error: 2.9

  15. i

    Labor Force Survey 2011 - Philippines

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    Updated Mar 29, 2019
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    National Statistics Office (2019). Labor Force Survey 2011 - Philippines [Dataset]. https://catalog.ihsn.org/index.php/catalog/4198
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    Dataset updated
    Mar 29, 2019
    Dataset authored and provided by
    National Statistics Office
    Time period covered
    2011
    Area covered
    Philippines
    Description

    Abstract

    The Labor Force Survey (LFS) aims to provide a quantitative framework for the preparation of plans and formulation of policies affecting the labor market.

    Specifically, the survey is designed to provide statistics on levels and trends of employment, unemployment and underemployment for the country as a whole, and for each of the administrative regions.

    Importance of the Labor Force Survey:

    a. It provides a quantitative framework for the preparation of plans and formulation of policies affecting the labor market towards 1) creation and generation of gainful employment and livelihood opportunities 2) reduction of unemployment and promotion of employment 3) improvement of working conditions 4) enhancement of the welfare of a working person b. It provides statistics on levels and trends of employment and unemployment and underemployment for the country and regions; c. It is used for the projection of future manpower, which when compared with the future manpower requirements, will help identify employment and training needs; d. It helps in the assessment of the potential human resource available for economic development; and e. It identifies the differences in employment, unemployment, and underemployment according to the different economic, social and ethnic groups existing within the population.

    Geographic coverage

    The geographic coverage consists of the country's 17 administrative regions defined in Executive Order (EO) 36 and 131. The 17 regions are:

    National Capital Region (NCR), Cordillera Administrative Region (CAR), Region I - Ilocos Region, Region II - Cagayan Valley, Region III - Central Luzon, Region IV-A - CALABARZON, Region IV-B - MIMAROPA, Region V - Bicol Region, Region VI - Western Visayas, Region VII - Central Visayas, Region VIII - Eastern Visayas, Region IX - Zamboanga Peninsula, Region X - Northern Mindanao, Region XI - Davao Region, Region XII - SOCCSKSARGEN, Caraga, Autonomous Region in Muslim Mindanao (ARMM)

    Analysis unit

    Individuals

    Universe

    The LFS has as its target population, all household members of the sample housing units nationwide. A household is defined as an aggregate of persons, generally but not necessarily bound by ties of kinship, who live together under the same roof and eat together or share in common the household food. Household membership comprises the head of the household, relatives living with him such as his or her spouse, children, parent, brother or sister, son-in-law or daughter-in-law, grandson or granddaughter, and other relatives. Household membership likewise includes boarders, domestic helpers and non-relatives. A person who lives alone is considered a separate household.

    Persons who reside in the institutions are not within the scope of the survey.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sampling design of the Labor Force Survey (LFS) uses the sampling design of the 2003 Master Sample (MS) for Household Surveys that started July 2003.

    Sampling Frame

    As in most household surveys, the 2003 MS used an area sample design. The Enumeration Area Reference File (EARF) of the 2000 Census of Population and Housing (CPH) was utilized as sampling frame. The EARF contains the number of households by enumeration area (EA) in each barangay. This frame was used to form the primary sampling units (PSUs). With consideration of the period for which the 2003 MS will be in use, the PSUs were formed/defined as a barangay or a combination of barangays with at least 500 households.

    Stratification Scheme

    Startification involves the division of the entire population into non-overlapping subgroups called starta. Prior to sample selection, the PSUs in each domain were stratified as follows: 1) All large PSUs were treated as separate strata and were referred to as certainty selections (self-representing PSUs). A PSU was considered large if it has a large probability of selection. 2) All other PSUs were then stratified by province, highly urbanized city (HUC) and independent component city (ICC). 3) Within each province/HUC/ICC, the PSUs were further stratified or grouped with respect to some socio-economic variables that were related to poverty incidence. These variables were: (a) the proportion of strongly built houses (PSTRONG); (b) an indication of the proportion of households engaged in agriculture (AGRI); and (c) the per-capita income (PERCAPITA).

    Sample Selection

    To have some control over the subsample size, the PSUs were selected with probability proportional to some estimated measure of size. The size measure refers to the total number of households from the 2000 CPH. Because of the wide variation in PSU sizes, PSUs with selection probabilities greater than 1 were identified and were included in the sample as certainty selections.

    At the second stage, enumeration areas (EAs) were selected within sampled PSUs, and at the third stage, housing units were selected within sampled EAs. Generally, all households in sampled housing units were enumerated, except for few cases when the number of households in a housing unit exceeds three. In which case, a sample of three households in a sampled housing unit was selected at random with equal probability.

    An EA is defined as an area with discernable boundaries within barangays, consisting of about 150 contiguous households. These EAs were identified during the 2000 CPH. A housing unit is a structurally separate and independent place of abode which, by the way it has been constructed, converted, or arranged, is intended for habitation by a household

    Sample Size

    The 2003 Master Sample consist of a sample of 2,835 PSUs of which 330 were certainty PSUs and 2,505 were non certainty PSUs. The number of households for the 2000 CPH was used as measure of size. The entire MS was divided into four sub-samples or independent replicates, such as a quarter sample contains one fourth of the PSUs found in one replicate; a half-sample contains one-half of the PSUs in two replicates.

    Strategy for non-response

    Replacement of sample households within the sample housing units is allowed only if the listed sample households had moved out of the housing unit. Replacement should be the household currently residing in the sample housing unit previously occupied by the original sample.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    ISH Form 2 (LFS questionnaire) is a four-page, forty four-column questionnaire that is being used in the quarterly rounds of the Labor Force Survey nationwide. This questionnaire gathers data on the demographic and economic characteristics of the population.

    On the first page of the questionnaire, the particulars about the geographic location, design codes and household auxiliary information of the sample household that is being interviewed are to be recorded. Certifications by the enumerator and his supervisor regarding the manner by which the data are collected are likewise to be made on this page.

    The inside pages of the questionnaire contain the items to be determined about each member of the sample household. Columns 2 to 11 are for the demographic characteristics; columns 2 to 7A are to be ascertained of all members of the household regardless of age. Columns 8 to 9 are asked for members 5 years old and over, while column 10 is asked for members 5 to 24 years old, column 11, for 15 years old and over, while columns 12 to 16 are asked for members 5 years old and over. Items 18 to 44 on the other hand, are the series of items that will be asked of all the members 15 years old and over to determine their labor force and employment characteristics.

    Most of the questions have pre-coded responses. The possible answers with their corresponding codes are printed at the bottom of the page for easy reference. Only the appropriate codes need to be entered in the cells. Other items, however, require write-in entries such as column 14 (primary occupation) and column 16 (kind of business/industry), etc. For such items, it is required that the enumerator describes the primary occupation or kind of business/industry.

    The ISH Form 2 is provided as external resources.

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Philippine Statistics Authority (PSA) (2023). National Demographic and Health Survey 2022 - Philippines [Dataset]. https://microdata.worldbank.org/index.php/catalog/5846

National Demographic and Health Survey 2022 - Philippines

Explore at:
Dataset updated
Jun 7, 2023
Dataset authored and provided by
Philippine Statistics Authority (PSA)
Time period covered
2022
Area covered
Philippines
Description

Abstract

The 2022 Philippines National Demographic and Health Survey (NDHS) was implemented by the Philippine Statistics Authority (PSA). Data collection took place from May 2 to June 22, 2022.

The primary objective of the 2022 NDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the NDHS collected information on fertility, fertility preferences, family planning practices, childhood mortality, maternal and child health, nutrition, knowledge and attitudes regarding HIV/AIDS, violence against women, child discipline, early childhood development, and other health issues.

The information collected through the NDHS is intended to assist policymakers and program managers in designing and evaluating programs and strategies for improving the health of the country’s population. The 2022 NDHS also provides indicators anchored to the attainment of the Sustainable Development Goals (SDGs) and the new Philippine Development Plan for 2023 to 2028.

Geographic coverage

National coverage

Analysis unit

  • Household
  • Individual
  • Children age 0-5
  • Woman age 15-49

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, and all children aged 0-4 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling scheme provides data representative of the country as a whole, for urban and rural areas separately, and for each of the country’s administrative regions. The sample selection methodology for the 2022 NDHS was based on a two-stage stratified sample design using the Master Sample Frame (MSF) designed and compiled by the PSA. The MSF was constructed based on the listing of households from the 2010 Census of Population and Housing and updated based on the listing of households from the 2015 Census of Population. The first stage involved a systematic selection of 1,247 primary sampling units (PSUs) distributed by province or HUC. A PSU can be a barangay, a portion of a large barangay, or two or more adjacent small barangays.

In the second stage, an equal take of either 22 or 29 sample housing units were selected from each sampled PSU using systematic random sampling. In situations where a housing unit contained one to three households, all households were interviewed. In the rare situation where a housing unit contained more than three households, no more than three households were interviewed. The survey interviewers were instructed to interview only the preselected housing units. No replacements and no changes of the preselected housing units were allowed in the implementing stage in order to prevent bias. Survey weights were calculated, added to the data file, and applied so that weighted results are representative estimates of indicators at the regional and national levels.

All women age 15–49 who were either usual residents of the selected households or visitors who stayed in the households the night before the survey were eligible to be interviewed. Among women eligible for an individual interview, one woman per household was selected for a module on women’s safety.

For further details on sample design, see APPENDIX A of the final report.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Two questionnaires were used for the 2022 NDHS: the Household Questionnaire and the Woman’s Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to the Philippines. Input was solicited from various stakeholders representing government agencies, academe, and international agencies. The survey protocol was reviewed by the ICF Institutional Review Board.

After all questionnaires were finalized in English, they were translated into six major languages: Tagalog, Cebuano, Ilocano, Bikol, Hiligaynon, and Waray. The Household and Woman’s Questionnaires were programmed into tablet computers to allow for computer-assisted personal interviewing (CAPI) for data collection purposes, with the capability to choose any of the languages for each questionnaire.

Cleaning operations

Processing the 2022 NDHS data began almost as soon as fieldwork started, and data security procedures were in place in accordance with confidentiality of information as provided by Philippine laws. As data collection was completed in each PSU or cluster, all electronic data files were transferred securely via SyncCloud to a server maintained by the PSA Central Office in Quezon City. These data files were registered and checked for inconsistencies, incompleteness, and outliers. The field teams were alerted to any inconsistencies and errors while still in the area of assignment. Timely generation of field check tables allowed for effective monitoring of fieldwork, including tracking questionnaire completion rates. Only the field teams, project managers, and NDHS supervisors in the provincial, regional, and central offices were given access to the CAPI system and the SyncCloud server.

A team of secondary editors in the PSA Central Office carried out secondary editing, which involved resolving inconsistencies and recoding “other” responses; the former was conducted during data collection, and the latter was conducted following the completion of the fieldwork. Data editing was performed using the CSPro software package. The secondary editing of the data was completed in August 2022. The final cleaning of the data set was carried out by data processing specialists from The DHS Program in September 2022.

Response rate

A total of 35,470 households were selected for the 2022 NDHS sample, of which 30,621 were found to be occupied. Of the occupied households, 30,372 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 28,379 women age 15–49 were identified as eligible for individual interviews. Interviews were completed with 27,821 women, yielding a response rate of 98%.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and in 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 2022 Philippines National Demographic and Health Survey (2022 NDHS) to minimize this type of error, nonsampling 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 2022 NDHS is only one of many samples that could have been selected from the same population, using the same design and identical 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% 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 2022 NDHS sample was the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS using programs developed by ICF. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.

Data appraisal

Data Quality Tables

  • Household age distribution
  • Age distribution of eligible and interviewed women
  • Age displacement at age 14/15
  • Age displacement at age 49/50
  • Pregnancy outcomes by years preceding the survey
  • Completeness of reporting
  • Observation of handwashing facility
  • School attendance by single year of age
  • Vaccination cards photographed
  • Population pyramid
  • Five-year mortality rates

See details of the data quality tables in Appendix C of the final report.

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