In 2023, there was one active barangay health worker (BHW) for about 98 people in the Philippines. The highest population-to-barangay health worker ratio was in the National Capital Region (NCR) with one active BHW for 768 residents. In contrast, both Region 8 and CARAGA had one active BHW catering to 49 residents.

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.

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

In 2023, about ****** barangay health stations provided health care services to about ****** barangays in the Philippines. Meanwhile, there were *** municipal health centers, *** city health centers, and ***** rural health units.

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 -

Abstract

This impact evaluation (IE) was designed to evaluate the integration of sanitation into the Pantawid Pamilyang Pilipino Program (4Ps), with an overall aim to test the effectiveness of a combination of hardware and financial subsidies to encourage adoption of improved sanitation facilities among the poorest households in rural areas of the Philippines. While the original research endeavored to measure health and nutrition outcomes, the final evaluation primarily focused on the upgrade and construction of latrines with the goal of achieving improved sanitation at the household level.

Geographic coverage

For this evaluation we included 17 municipalities in the provinces of Negros Oriental, Cebu and Bohol (Region 7), and Leyte and Eastern Samar (Region 8). We selected those municipalities based on the levels of poverty, open defecation, unimproved sanitation and inclusion in the ZOD coverage area.

Figure 11 of the annex to the survey report (see report under the resources tab) shows the geographic distribution of study barangays in one of the five study provinces (see Appendix for additional maps of other provinces).

Analysis unit

Household

Universe

All study participants were 4Ps beneficiaries, who are required to attend Family Development Sessions (FDS) that included a module on sanitation promotion.

Kind of data

Sample survey data [ssd]

Sampling procedure

In each barangay, we used the National Household Targeting System (NHTS-PR) list to randomly select 15 4Ps beneficiary households to be included in our sample. At baseline 4,080 households from 272 sample barangays were interviewed. The sample was reduced at the endline survey by 30% due to budget constraints. Therefore, the endline survey included 2,849 households from 190 barangays. Additional sampling details are provided in the Study Design Annex of the report provided under the resources tab.

Sampling deviation

A small number of barangays were replaced due to safety concerns.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Baseline and questionnaires are structured and provided in English as related resources. The questionnaire differed at baseline and endline, based on feedback from 4P project staff for reasons provided in the data appraisal section.

Response rate

At endline 2,849 study households were sampled, but 154 baseline households were not reached, because their members had permanently moved to another location or the household refused to participate in the endline survey. This represents a response rate of 95%.

Data appraisal

Data quality was checked using spot-checks and back-checks.

The IE originally intended to look at child diarrhea prevalence as a secondary outcome. However due to the shift in the focus of the evaluation and the different methodology of collecting the child health roster in each survey round, diarrhea was dropped as an outcome of the study. At baseline households were asked about each child’s health status separately, while at endline households were asked about the aggregate incidence of diarrhea and other symptoms for all children under 5 years old in the household. This prevents us from supplementing the definition of child diarrhea using multiple symptoms, like blood or mucus in the stool. This is important as some primary caregivers are unable to accurately diagnose diarrhea in children. Additionally, our statistical power reduces by almost two thirds, because the number individual data points goes down from 2246 at baseline to 831 at endline.

Additional information on data appraisal is provided in the Study Design annex of the survey report provided under the resources tab.

As of June 2022, SOCSKARGEN had 40 established botika ng barangay outlets, making it the region with the most number of such drug outlets in the Philippines. The presence of such establishments was in relation to the Botika ng Barangay(BNB) project of the national government to make affordable medicines, which were 50 to 70 percent cheaper than branded medicines, accessible to rural areas in the country.

Abstract

Philippines Population Census 2015 was designed to take an inventory of the total population in the country and collect information about its characteristics. The census of population is the source of information on the size, distribution, and composition of the population in each barangay, city/municipality, province, and region in the country, as well as information about its demographic, social, and economic characteristics. These indicators are vital in the formulation of rational plans and programs towards national and local development.

Specifically, POPCEN 2015 gathered data on: - size and geographic distribution of the population; - population composition in terms of age, sex, and marital status; - religious affiliation; - school attendance, literacy, highest grade/year completed, and technical/vocational course obtained; - usual activity/occupation, and whether overseas worker for members 15 years old and over; - registration of birth and death; - household-level characteristics such as fuel used for lighting and source of water supply for drinking and cooking; - housing characteristics such as the type of building, construction materials of the roof of the building, construction materials of the outer walls of the building/housing unit, and tenure status of the housing unit/lot; and - barangay characteristics such as the presence of selected facilities and establishments; and presence of informal settlers, relocation areas, and in-movers in the barangay due to natural and man-made disasters.

August 1, 2015 was designated as Census Day for the POPCEN 2015, on which date the enumeration of the population in the Philippines was referred. For the purpose of this census, all information collected about the population were as of 12:01 a.m., Saturday, August 1, 2015.

Enumeration lasted for about 25 days, from 10 August to 6 September 2015. In some areas, enumeration was extended until 15 September 2015 for large provinces.

Geographic coverage

The population count is available at the barangay, city/municipal, provincial, regional, and national levels. Demographic, social, and economic characteristics are tabulated at the city/municipal, provincial, regional, and national levels.

Analysis unit

The following are the units of analysis in POPCEN 2015: 1. Individual person 2. Household 3. Housing unit 4. Institutional Population 5. Barangay

Universe

The POPCEN 2015 covered all persons who were alive as of 12:01 a.m. August 1, 2015, and who were members of the household and institution as follows:

Persons Enumerated as Members of the Household:

1. Those who were present at the time of visit and whose usual place of residence was the housing unit where the household lived;

2. Family members who were overseas workers and who were away at the time of the census and were expected to be back within five years from the date of last departure. These included household members who may or may not have had a specific work contract or had been presently at home on vacation but had an existing overseas employment to return to. Undocumented overseas workers were still considered as members of the household for as long as they had been away for not more than five years. Immigrants, however, were excluded from the census.

3. Those whose usual place of residence was the place where the household lived but were temporarily away at the time of the census for any of the following reasons: a. on vacation, business/pleasure trip, or training somewhere in the Philippines and was expected to be back within six months from the date of departure. An example was a person on training with the Armed Forces of the Philippines for not more than six months; b. on vacation, business/pleasure trip, on study/training abroad and was expected to be back within a year from the date of departure; c. working or attending school outside their usual place of residence but usually came home at least once a week; d. confined in hospitals for a period of not more than six months as of the time of enumeration, except when they were confined as patients in mental hospitals, leprosaria/leper colonies or drug rehabilitation centers, regardless of the duration of their confinement; e. detained in national/provincial/city/municipal jails or in military camps for a period of not more than six months as of the time of enumeration, except when their sentence or detentionwas expected to exceed six months; f. on board coastal, interisland, or fishing vessels within Philippine territories; and g. on board oceangoing vessels but expected to be back within five years from the date of departure.

4. Boarders/lodgers of the household or employees of household-operated businesses who did not return/go home to their respective households weekly;

5. Citizens of foreign countries who resided or were 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;

6. Filipino balikbayans with usual place of residence in a foreign country but resided or were expected to reside in the Philippines for at least a year from their arrival; and

7. Persons temporarily staying with the household who had no usual place of residence or who were not certain to be enumerated elsewhere.

Persons Enumerated as Members of the Institutional Population:

1. Permanent lodgers in boarding houses;

2. Dormitory residents who did not usually go home to their respective households at least once a week;

3. Hotel residents who stayed in the hotel for more than six months at the time of the census;

4. Boarders in residential houses, provided that their number was 10 or more. However, if the number of boarders in a house was less than 10, they were considered as members of regular households, not of institutions;

5. Patients in hospitals who were confined for more than six months;

6. Patients confined in mental hospitals, leprosaria or leper colonies, and drug rehabilitation centers, regardless of the length of their confinement;

7. Wards in orphanages, homes for the aged, and other welfare institutions;

8. Prisoners of corrective and penal institutions;

9. Seminarians, nuns in convents, monks, and postulants;

10. Soldiers residing in military camps; and

11. Workers in mining and similar camps.

All Filipinos in Philippine embassies, missions, and consulates abroad were also included in the enumeration.

Kind of data

Census/enumeration data [cen]

Sampling procedure

The POPCEN 2015 is a complete enumeration of all persons, households and institutional population in the country. No sampling was done.

Mode of data collection

Face-to-face interview [f2f] and self-administered; Paper and Pencil

Research instrument

Listed below are the basic census forms that were used during the field enumeration:

• CP Form 1 - Listing Booklet This booklet was used to list the buildings, housing units, households, and ILQs within an EA. It was also used to record other information such as the address of the household head or ILQ, total population, and number of males and females corresponding to each household and ILQ listed.

• CP Form 2 - Household Questionnaire This four-page questionnaire was used to record information about the households. Specifically, this form was used to gather information on selected demographic and socio-economic characteristics of the population and some information on housing characteristics.

• CP Form 4 - Institutional Population Questionnaire This four-page questionnaire was used to record information on selected demographic and socio-economic characteristics of the population residing in ILQs.

• CP Form 5 - Barangay Schedule This four-page questionnaire was used to record the physical characteristics (e.g. street pattern) and the presence of service facilities and establishments by kind and emplyment size in the barangay. It was also used to record the presence of informal settlers, relocation areas, and in-movers in the barangay due to natural and man-made disasters.

• CP Form 7 - Household Self-Administered Questionnaire Instructions This form contains specific and detailed instructions on how to fill out/accomplish each item in CP Form 2. It was used as guide/reference by respondents who were not, for some reasons, personally interviewed by the EN.

• CP Form 8 - Institutional Population Self-Administered Questionnaire Instructions This form contains specific and detailed instructions for the managers/administrators to guide them in accomplishing each item in CP Form 4. It was used as guide/reference by managers or administrators of an ILQ.

Listed below are the major administrative and accomplishment forms that were also used to facilitate data collection and supervision, and monitoring of enumeration and personnel:

• Mapping Form This form was used to plot buildings, either occupied by households or vacant, ILQs and important physical landmarks in the area. It was also used to enlarge a map or a block of an EA/barangay if the area being enumerated is too large or congested. CP Form 1 - Listing Booklet

• CP Form 6 - Notice of Listing/Enumeration This form is a sticker. After listing and interviewing a household or ILQ, this sticker was posted in a very conspicuous place, preferably in front of the house or at the gate of the building. This form was used for control and monitoring purposes as its presence indicates that a particular housing unit or ILQ had already been listed/interviewed.

• CP Form 9 - Appointment Slip to the Household/Institution/Barangay Official This form was used to set an appointment with the

These datasets are derived from the boundaries of the Barangays as observed at the end of April 2016 as per the Philippine Geographic Standard Code (PSGC) dataset. It has been generated on the basis of the layer created by the Philippine Statistics Authority (PSA) in the context of the 2015 population census. These datasets have been vetted by staff at The Carl Vinson Institute of Government's Office of Information Technology Outreach Services (ITOS) according to their COD assessment protocol found in the COD Technical Support Package (https://sites.google.com/site/commonoperationaldataset/geodata-preparation-manual/itos-process).
Acknowledge PSA and NAMRIA as the sources. LMB is still the source of official administrative boundaries of the Philippines. In the absence of available official administrative boundary, the IMTWG have agreed to clean and use the PSA administrative boundaries which are used to facilitate data collection of surveys and censuses. The dataset can only be considered as indicative boundaries and not official. * For administrative level 4 (Barangay) please contact the contributor (OCHA Philippines) via this page. This COD replaces https://data.humdata.org/dataset/philippines-administrative-boundaries

Philippines administrative levels:

(0) Country

(1) Region (Filipino: rehiyon)

(2) Provinces (Filipino: lalawigan, probinsiya) and independent cities (Filipino: lungsod, siyudad/ciudad, dakbayan, lakanbalen)

(3) Municipalities (Filipino: bayan, balen, bungto, banwa, ili) and component cities (Filipino: lungsod, siyudad/ciudad, dakbayan, dakbanwa, lakanbalen)

These shapefiles are suitable for database or ArcGIS joins to the sex and age disaggregated population statistics found on HDX here.

The National Capital Region (NCR) had the highest share of drug-affected barangays in the Philippines in 2022. In that year, about 54 percent, or 922 out of the 1,710 total barangays in the region reported and validated the presence of people using drugs or illegal drug activities. In contrast, MIMAROPA had the lowest drug affectation rate.

The dataset used the list of affected municipalities based on DSWD DROMIC to identify affected barangays by Typhoon Haiyan/Yolanda. It contains the list of barangays within affected municipalities based on DSWD DROMIC (Typhoon Haiyan/Yolanda)

Abstract

The 2002 Census of Agriculture (CA 2002) is a large-scale government operation geared towards the collection and compilation of statistics in the agriculture sector of the country. The collected data will constitute the bases from which policymakers and planners will formulate plans for the country's development.

The following were the objectives of CA 2002:

1. To determine the structure and characteristics of agricultural holdings;
2. To determine the number and distribution of households and enterprises engaged in agriculture and to gather information on the operation of these households and enterprises;
3. To provide the basis for sampling frame for other statistical undertakings; and
4. To provide basic data for use in national as well as sub-national development planning.

Specifically, it aims to: 1. Obtain comprehensive data on farm characterisitcs such as size, location, tenure status, irrigation system, crops planted, livestock/poultry raised, etc.; 2. Determine the type and number of equipment, machineries and facilities used in the operation of agricultural activities whether owned or rented; and 3. Provide benchmarks for the various statistical series which are designed to measure progress in agriculture.

Major findings include the following: 1. Central Visayas accounted for the highest number of farms but Bicol Region had the biggest farm area. 2. Almost all farms in the country were operated individually. 3. Most farms were owned by the agricultural operators. 4. More than half of the farms in the country were under temporary crops. 5. Palay remained as the major temporary crop in the country. 6. Coconut also remained as the dominant permanent crop. 7. Individual system irrigation was the most common in the country. 8. Number of hogs reared and tended increased by 1.1 milliion heads. 9. Raising of chicken was the prevalent poultry raising activity. 10. Ornamental and flower gardening (excluding orchid) was also common in the country. 11. Male operators dominated the agriculture sector. 12. Almost 80 percent of the household members engaged in agricultural activity were working in own agricultural holding. 13. Plow was the most common farm equipment in the country.

Geographic coverage

National Coverage

Analysis unit

Households

Universe

The census covered all households, agricultural operators, and agricultural establishments.

Kind of data

Census/enumeration data [cen]

Sampling procedure

The CA 2002 adopted a one-stage stratified systematic sampling design where selection of sample barangays was done by city/muncipality (by district for the National Capital Region or NCR) and by stratum. However, for the provinces of Laguna, Isabela, Bukidnon, and Batanes, a full sample-census was adopted.

Except for the cities/municipalities of the full-sample barangays, all cities/municipalities (6 districts for NCR) were treated as domains and the barangays as the ultimate sampling units. The six districts of NCR are as follows: NCR I - Manila; NCR II - Quezon City; NCR III - San Juan, Cities of Mandaluyong, Marikina and Pasig; NCR IV - Malabon, Navotas, Cities of Kalookan and Valenzuela; NCR V - Pateros, Taguig and Makati City; and NCR VI - Cities of Pasay, Las Piñas, Muntinlupa, Parañaque

The sampling frame was based on the list of barangays taken from the results of the 2000 Census of Population and Housing (Census 2000) as of June 2002.

In each domain, all barangays were grouped into three strata, as follows: Stratum 1 - Barangays with the largest Total Farm Area (TFA) in the municipality based on the 1991 Census of Agriculture and fisheries (CAF) Stratum 2 - All other sample barangays of the 1991 CAF Stratum 3 - All other barangays in the sampling frame

The 1991 sample barangays in each domain were ranked by descending values of TFA. The barangays with the largest TFA in 1991, referred to as the certainty barangays, were included in Stratum 1. In cases where the certainty barangay was split into two or more barangays as a result of the creation of a new barangay (as of June 2002 master list of barangays), the new barangay was also treated as a certainty barangay. Sample barangays of the 1991 CAF not included in Stratum 1 were assigned in Stratum 2. Barangays with no TFA because they were not samples during the 1991 CAF were arranged in ascending order of the total number of households based on Census 2000. These barangays were assigned in Stratum 3.

All barangays in Stratum 1 were automatically taken as samples. Sample barangays in Strata 2 and 3 were systematically selected using a 25-percent sampling rate, except for NCR. The sampling rates for NCR were 50 percent and 10 percent for Stratum 2 and Stratum 3, respectively. In each sampled barangay, all households were covered.

All agricultural establishments identified in the 2002 List of Establishments, whether or not located in the sample barangays of CA 2002, and new agricultural establishments in the sample barangays during the enumeration of CA 2002, were enumerated.

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

The accomplished census forms undergone several stages of data editing. These stages include the following:

1. Field editing which consisted of checking of consistency, correctness and completness of entries while in the field.
2. Manual Processing of accomplished questionnaires at the Provincial Offices where the following were done: a. Verification of geographic identification and completeness of forms b. Checking for legibility of entries c. Coding
3. Machine Processing which includes machine validation, consistency checking and completeness checking of entries.

Sampling error estimates

In order to provide a basis for assessing the reliability or precision of CA estimates, the estimation of the magnitude of sampling error in the census data was undertaken by the NSO for the 2002 CA. The standard error (SE) and coefficient of variation (C.V.) were used as measures of sampling error.

Abstract

The Integrated Farm Household Survey (IFHS) supported the agricultural Research and Development Program in terms of benchmark data on the characteristics of farms and farmers. The IFHS results provided inputs for the development and/or improvement of the performance indicators system in agriculture. Further, the survey results could quantify the impact of agricultural policies of the government.

The survey gathered household level data on the following; Household Information, Farm Particulars, Inventory of Farm Investments, Household Income, Household Expenditures and Credit Information.

Specifically, the following data are generated: 1. Level, structure and/or sources of farm household income; 2. Characteristics of farms/farm enterprises and the farm households; 3. Access of farm households to agricultural support services; 4. Farm management such as input use and cultivation practices; 5. Expenditure patterns of the farm households; 6. Farm and households investments; and 7. Other socio-economic data.

Geographic coverage

National Coverage.

Analysis unit

Households

Universe

The survey covered farm households with farming/fishing operations.

Kind of data

Sample survey data [ssd]

Sampling procedure

The IFHS utilized different sampling frames at the barangay and household levels. At the barangay level, the list of agricultural barangays covered in the 1999 Barangay Screening Survey (BSS) served as the sampling frame while at the household level, the listing of households generated from the 2000 Census of Population and Housing (CPH) of the National Statistics Office (NSO) was used as basis for drawing the samples. The 2000 CPH listing was utilized as sampling frame for the IFHS despite the limitation that households were not classified into farming and non-farming categories for two major considerations. First, the 2000 CPH provided the most updated lists of households by barangay. Second, budgetary constraints precluded the conduct of household screening in the selected sample barangays for the survey.

The domain of the survey was the province. A two-stage stratified sampling design was adopted with the barangay as primary sampling unit and the farming household as secondary sampling unit. The number of farming households was used as the stratification variable. Primary and secondary sampling units were both drawn using simple random sampling.

In getting the number of barangays as representative of the domain (province) level, the total number of agricultural barangays in the province reported in the 1999 Barangay Screening Survey (BSS) was used in proportionately allocating the target sample size of around 600 barangays to the Integrated Farm Household Survey (IFHS) provinces. Due to budgetary consideration, the total number of barangays included for small and large agricultural sampling of households with at least one member engaged in agricultural activity. provinces was set at six (6) and nine (9) barangays, respectively, depending on the computed total sample size for the province, that is,

        n' = 6 if n < 6, and
        n' = 9 otherwise.

Ten (10) sample households were allocated for each sample barangay. This procedure resulted in total sample size of 592 barangays and 5,920 households for the entire country.

A general feature of the design was the division of the primary sampling units into strata of approximately equal sizes relative to the number of farming households reported in the 1999 BSS. The division of the barangays within the province and the drawing of sample was done as follows:

The barangays were arrayed in descending order based on the total number of farming households. These barangays were then divided into three (3) strata such that the cumulative total number of farming households of all the barangays in any one stratum was approximately of the same magnitude as the rest of the individual strata. Thus, Stratum 1 barangays constitute all "large barangays", Stratum 2 barangays constitute all "medium barangays", and Stratum 3 barangays constitute all "small barangays"; with respect to total number of farming households.

Equal sample sizes were allocated and drawn from the three strata, resulting in two (2) and three (3) sample barangays, respectively, per stratum depending on the sample size for the province. Selection of sample barangays wss done at the BAS Central Office using simple random sampling. The generated lists of sample barangays were then submitted to NSO for the drawing of sample households and for the photocopying of corresponding barangay maps.

Drawing of sample households was made at the NSO field offices using simple random sampling of households with at least one member engaged in agricultural activity. The generated lists of samples were sent back to BAS Central Office for control and distribution to concerned Provincial Operations Centers (POCs).

Sampling deviation

As in any survey, there were cases wherein samples need to be substituted or replaced. Following were the guidelines in replacing sample barangays and/or households:

Sample Barangays - Only two general reasons were considered valid for substituting barangays: 1. Transportation costs were way above the allocated budget for operations; or 2. Unfavorable peace and order situation in the area.

The list of replacement barangays served as the only source of substitute barangays. It was emphasized that a replacement barangay should be taken only from the list of replacement barangays in the same stratum.

Sample Households - Only the reasons enumerated below are considered valid for replacing households. 1.Household was not a qualified IFHS sample: a. For regions except NCR: Candidate household was not a farming household; b. For NCR: Candidate household was not into agricultural activities, or into agricultural activities but produce was not intended to generate income for the household; c. Conditions (a) and (b) were satisfied but there was no agricultural operation during the reference period (July 2002 to June 2003); 2. Household was a qualified IFHS sample but any of the following situations arose during visit: a. No qualified respondent was available for interview during the entire survey period; b. Qualified respondent refused to be interviewed; c. Interview was terminated;

It was emphasized that reasons for substituting sample households should be validated first by the field supervisor before replacement is allowed. Replacement households should be taken only from the list of replacements for the barangay.

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

Consistencies of data items within and across record types were first verified and checked according to the Data Processing Guidelines of the study. First stage of the editing was done manualy. A second stage consistency check was a component of the Computerized Processing System.

Initial editing of data was done by the Contractual Data Collectors (CDCs) on every filled up questionaire. These questionnaires were turned over to their supervisors for checking. Editing/Checking for consistencies of data items in particular record types and accross record types were done.

Second stage of editing was done at the Central Office. The Data Processing System (DPS) was equipped with a customized editing program to filter out-of-range data items to generate an errorlist. The errorlist is a compilation of errors on specific data item that did not pass the specification. The errorlist list was checked based on the information in the questionnaire. The correction was reflected to the data file using the the CENTRY module of the Integrated Micro-computer Processing System (IMPS).

Response rate

From 5920 sample households, 5448 sample units were successfuly interviewed for a response rate of 92.03%.

Abstract

This study is an impact evaluation of the KALAHI-CIDSS (KC) program. The impact evaluation's key research questions can be divided into the following four themes:

1. Socio-Economic Effects: Does KC increase household consumption? Does KC increase labor force participation?
2. Governance Effects: Does KC increase government leader responsiveness to community needs? Does KC reduce corruption and increase transparency?
3. Community Empowerment Effects: Does KC increase participation in local governance? Does KC increase collective action and contribution to local public goods?
4. Social Capital Effects: Does KC build groups and networks? In what ways are these networks applied? Does KC enhance trust?

In order to isolate KC's effects, a randomized control trial evaluation design was chosen. The impact evaluation sample consists of 198 municipalities (with 33 to 69 percent poverty incidence), spread over 26 provinces and 12 regions. The 198 municipalities were paired based on similar characteristics (99 pairs) and then randomly assigned into treatment and control groups through public lotteries. The sample size is large enough to be able to detect MCC's projected eight percent change in household income as well as other smaller effects. As part of the impact evaluation, baseline quantitative data were collected in the study area from April to July 2012. The quantitative data came from 5,940 household surveys in 198 barangays (one from each municipality) and 198 barangay surveys implemented in these same barangays

Geographic coverage

National coverage: The sample consists of 5,940 households in 198 barangays in 198 municipalities in 26 provinces in 12 regions. The sample is representative of the KALAHI-CIDSS target population across the nation.

Analysis unit

Individuals, households, community

Universe

The study population consists of barangays (villages) from the Philippines' poorest provinces. Survey respondent were barangay captains (village captains) and randomly selected households (30 randomly selected per barangay) from the sample of 198 barangays (villages).

Kind of data

Sample survey data [ssd]

Sampling procedure

The impact evaluation focuses on municipalities with between 33-69% poverty incidence. A total of 198 eligible municipalities were matched on poverty incidence, population, land area, and number of barangays. The paired municipalities were then randomly assigned into treatment and control groups through public lotteries. This resulted in the final sample of 198 municipalities (when determining the number of treatment and control municipalities, we used sample size of 30 households per municipality, ensuring an 8% (positive) change in income would be detectable at 95% significance and 80% power). The large number of municipalities included in the evaluation will provide a sufficient level of precision to estimate KC's impacts nationwide in municipalities with a poverty incidence between 33-69%. One barangay within each of the 198 municipalities participating in the evaluation was randomly chosen, with a weighted probability favoring barangays with the highest poverty rates. Within each municipality, IPA divided barangays into quintiles based on poverty and dropped the quintile with the lowest poverty incidence. For each municipality, the barangay to be surveyed for the sample was then randomly selected from the remaining barangays. Within each barangay, 30 households were randomly selected from among all households to comprise the household surveyed sample.

Sampling deviation

N/A

Research instrument

The baseline study included a barangay (village) questionnaire and a household questionnaire implemented in the following four different languages: Tagalog, Bisaya, Cebuano, llongo and llocano.

1. Household questionnaire: This questionnaire was composed of modules on education, labor income sources, household assets and amenities, expenditures, social networks, and other topics.

2. Barangay questionnaire: The barangay captains (village leaders were the principal respondents. The questionnaire collected data on the barangay's development projects, budget, demographics, the relationship between the existing barangay captain and its previous leadership, and other topics.

Cleaning operations

In the field, the field supervisor and data editor checked the questionnaires before the first data entry. The survey firm then conducted the second data entry in the main office and then checked the discrepancies between the first and the second data entry. The data cleaning process implemented by the survey firm included the following: 1. Naming and labelling the data 2. Checking the unique identifiers 3. Range checks and setting variable bounds 4. Check skip patterns and misisng data 5. Check logical consistency 6. Standardize string variable coding

After receiving the clean datasets from the survey firm, IPA conducted a second stage of data cleaning needed to construct variables for the analysis. This process involved carefully creating, summarizing and cross-checking key indicators.

Response rate

100 percent

Sampling error estimates

N/A

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.

As of May 2025, there were about 26,500 barangay or village health stations in the Philippines. In addition, there were more than 6,000 general clinic laboratory and birthing homes combined. Overall, there were more than 42,000 health facilities in the country.

Abstract

The Corn Production Survey (CPS) 2009 was a quarterly survey conducted by the Bureau of Agricultural Statistics (BAS). It aimed to generate estimates on corn production, area and yield and other related information. It was conducted in four rounds, namely, April 2009, July 2009, October 2009 and January 2010. Each round generated estimates for the immediate past quarter and forecast for the next two quarters. Results of the survey served as inputs to planners and policy makers on matters concerning the corn industry.

Geographic coverage

National Coverage

Analysis unit

Households

Universe

All farming households

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling procedure used in the Corn Production Survey (CPS) 2009 was first implemented in 1994. This was a replicated two-stage stratified sampling design with province as the domain, barangay as the primary sampling unit (PSU) and farming household as the secondary sampling unit (SSU).

The results of the 1991 Census of Agriculture and Fisheries (CAF 1991) served as the basis of sampling frame at the PSU and SSU levels. In the said census, the largest barangay in a municipality was taken with certainty while a 50 percent sampling rate was used for selecting the remaining barangays in the municipality. This scheme effectively resulted in the generation of two sub universes: a sub universe of barangays with probability of selection equal to one (these barangays were called 'certainty barangays') and another sub universe of barangays with probability of selection equal to 0.5. This characteristic of the CAF 1991 data was used in the selection of sample barangays for the CPS.

The barangays were arrayed in ascending order based on corn area then stratified such that the aggregate corn area of the barangays belonging to one stratum is more or less equal to the aggregate corn area of the barangays in any other stratum. Ten (10) strata were formed for major corn producing provinces and five for minor producing provinces. In all these provinces, the last stratum consisted of the certainty barangays per CAF 1991 design.

For each stratum, four (4) sample barangays were drawn independently using probability proportional to size (PPS) sampling with the barangay's corn area as size measure. This resulted in four (4) independent sets of barangays (i.e., four (4) replicates) for the province. Systematic sampling was used in drawing the sample faming households in each sample barangay.

For economic reasons, sample size per barangay was limited to a minimum of four (4) and a maximum of 25. To correct for this limitation of the design, the use of household weights was instituted. A detailed discussion of weighting in the CPS was included in the survey's estimation procedure attached as an external resource.

In November 2007, an updating of the list of farming households in all corn sample barangays nationwide was done to address the problem of non-response due to transfer of residence, stoppage of farm operation, passing away of operator etc. Consequently, a new set of sample households was drawn.

The following sample sizes were used in CPS 2009: - April 2009 Round: 935 barangays and 7,841 households - July 2009 Round: 1020 barangays and 8,449 households - October 2009 Round: 935 barangays and 7,833 households - January 2010 Round: 1,020 barangays and 8,457 households.

Less elements were sampled in April and October 2009 Rounds since less number of replicates were covered in minor-producing provinces during these periods.

Absent respondents such as refusals, unknown and those who transferred to another barangay were replaced at the Central Office for the next quarter's survey while not-at-home (temporarily away) cases were still included in the list of samples for the succeeding round. The replacement households were taken from the list of replacements (farming households) for the barangay and were reflected in the list of samples for the next round.

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

Data editing involved item-by-item check on the completeness of units and items covered, as well as the consistency and acceptability of the data collected. This activity took place at various stages of the survey, that is,

(a) During data collection by the Contractual Data Collectors (CDCs). The field supervisor also made random checks on the CDC's work as part of his/her supervision work.

(b) After data collection, before submitting the questionnaires for encoding: At this stage, the accomplished survey returns were manually edited and coded at the Provincial Operations Center (POC). Manual editing involved the checking of data items based on pre-set criteria, data ranges, completeness and consistency with other data items. Coding was the assignment of alpha-numeric codes to questionnaire items to facilitate data entry.

(c) After encoding at the POC, through a customized data cleaning program: Encoded data were subjected to computerized editing using a customized editing program. The editing program took into consideration the editing criteria such as validity, completeness and consistency with other data items. This activity was done to capture invalid entries that were overlooked during manual editing. An error list was produced as output of the process. The errors reflected in said lists were verified vis-à-vis the entries in the accomplished questionnaires. The data files were updated based on the corrections made. Completeness check was likewise done to compare the clean data file against a master file of barangays to check if the sample barangays have been completely surveyed or not. Editing and updating were performed iteratively until a clean, error-free data file was generated. The clean data file served as an input to the table generation (or estimation) process.

(d) At the Central Office: The clean raw data files generated at the POCs were sent to the Central Office for national consolidation at the Information and Communications Technology Division (ICTD). Prior to consolidation, these files were again submitted for re-editing, in accordance with the procedures elaborated in (c). This was done as another layer of data quality check for the survey.

Response rate

Response rate refers to the ratio of sample households who responded to the survey to the total number of sample households, expressed as a percentage. For Corn Production Survey (CPS), responding samples include farming households who are into corn farming (code 10), those who are into other agricultural activities or with no agricultural activities during the reference period (code 20).

CPS 2009 registered high response rates which averaged 87.53% across rounds. Higher proportions of actually enumerated sample households were noted in April and October 2009 rounds at 89.55% and 91.48%, respectively, than in July 2009 and January 2010 rounds which registered 83.56% and 85.53% response rates, respectively.

Data appraisal

To ensure the quality of its statistical services, the BAS has mainstreamed in its statistical system for generating agricultural statistics, a quarterly data review and validation process. This is undertaken in three levels: provincial, regional and national levels. The Corn Production Survey 2009 results passed through this rigid procedure before its final outputs were released for public use.

The data review process starts at the data collection stage and continues up to the processing and tabulation of results. However, data examination is formalized during the provincial data review since it is at this stage where the data at the province-level is analyzed as a whole. The process involves analyzing the survey data in terms of completeness, consistency among variables, trend and concentration of the data and presence of extreme observations. Correction of spotted errors in the data is done afterwards. The output of the process is a clean data file used in the re-computation of survey estimates.

The estimates generated from the clean data file are thoroughly analyzed and validated with auxiliary information to incorporate the impact of information and events not captured by the survey. These information include results of the Monthly Palay and Corn Survey Report (MPCSR), historical data series, report on weather condition, area and crop condition, irrigation, levels of inputs usage, supply and demand, marketing of agricultural products, and information on rice and corn program implementation.

According to a survey in 2021, ** percent of respondents said that there were no changes in the number of Barangay Health Workers (BHWs) during the COVID-19 pandemic in the Philippines. On the other hand, *** percent of respondents stated that there were fewer BHWs.

The KALAHI-CIDSS program was set up in 2002 to alleviate rural poverty in the Philippines. It provides resources to poor rural municipalities to invest in public goods and by reviving local institutions to enhance people’s participation in governance. The project targeted the poorest 25 percent of municipalities in each of the poorest 42 provinces. The government of the Philippines committed $82 million to the project, which was complemented by a $100 million loan from the World Bank. As of December 2010, the project had covered 4,583 barangays (villages) in 200 municipalities and supported 5,645 subprojects, worth Php 5.7 billion and benefiting about 1.26 million households. The program's impact evaluation was designed in 2003 to evaluate general impacts on poverty reduction, social capital, empowerment, and governance. The team collected quantitative and qualitative data before, during, and after project implementation in a sample of KALAHI-CIDSS municipalities that received support ("treatment" municipalities) and from comparable municipalities that did not receive support ("control" municipalities). The quantitative baseline survey was carried out in September-October 2003, the quantitative midterm in October-November 2006 and the quantitative endline survey in February-March 2010. Data were collected on a broad range of indicators: service delivery (access to health, education), poverty (employment, per capita consumption, self-rated poverty), empowerment and governance (group membership, participation in barangay assemblies, collective action). The quantitative sample includes 2,400 households in 135 barangays in 16 municipalities in 4 provinces.

Abstract

The survey aimed to generate updated data on levels and structure of production costs and returns. Specifically, it was conducted to detemine the indicators of profitability such as gross and net returns, returns above cash costs, net profit - cost ratio, etc.; usage of materials and labor inputs; and other related socio-economic variables including information on new production technologies.

Geographic coverage

National Coverage

Analysis unit

Households

Universe

The survey covered farmers who harvested camote (potato) within the reference period and knowledgeable on the details of camote (potato) farming particularly on investments, material inputs, labor expenses incurred and disposition of produce.

Kind of data

Sample survey data [ssd]

Sampling procedure

The domain of the survey was the province. A two-stage sampling design was employed with the barangay as the primary sampling unit and the sample farmer as the secondary sampling unit. The top producing barangays were selected from an ordered list of barangays. The sample farmers were identified in each sample barangay using snowball approach during data collection.

The total number of sample barangays per province was fifteen or less. If the number of major producing barangays that contributed to 80 percent based on area planted were more than 15, 15 barangays were selected. Those provinces with less than 15 barangays that produced sweet potato were completely enumerated. This approach ensured representation of the barangays in the province in terms of area planted to sweet potato. The total number of sample farmers per province was set at 75 and equally allocated to the sample barangays. The list of sample barangays per province and corresponding number of samples were provided to the Provincial Operations Center (POC) of the former Bureau of Agricultural Statistics (BAS) prior to the survey.

During data collection, the names and addresses of sweet potato farmers residing in the barangay were obtained from the office of the barangay chairman or any other key informants in the barangay. It served as the data collector's starting point in searching for potential sample farmers. The target numbers of sweet potato farmers in the sample barangays were obtained using snowball sampling. A set of screening questions was applied to confirm if those listed actually harvested sweet potato during the reference period and satisfied the other criteria to qualify for enumeration.

Whether the interviewed farmer was qualified for the survey or not, he/she was asked to identify other sweet potato farmers in the barangay to be added in the initial list. The search continued, and the farmer who met the criteria specified in the screening questions was qualified as sample for the survey and was interviewed using the questionnaire for the 2014 Survey on Costs and Returns of Sweet Potato (camote (potato)) Production. If the interview was successfully carried out (meaning, all the needed information had been supplied), the household number, full name and residential address of the sample farmer were written in the List of Sample Farmers. The enumerator selected again any farmer in the initial list as the next potential sample for the survey. The process continued until the required number of samples in the barangay was obtained.

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

Editing and coding of data were done at the provincial offices upon submission of the accomplished questionnaires by the CDCs. These activities were undertaken to ensure the quality of data that were collected.

A five (5) day training/workshop on data processing was conducted to facilitate the generation of survey results. It was attended by the Provincial Processing Officers (PPOs) or staff in-charge of other crops and selected staff of the Agricultural Accounts and Statistical Indicators Division (AASID).

The training/workshop covered data encoding, data review, cleaning and updating of flat files using MS Excel program developed by AASID. During the training/workshop, completeness check, consistency checks and accuracy checks were done to ensure quality of data. The output of the data review and cleaning was the final set of raw data file which was used for the generation of data tables. These data tables were validated and compared with the results of the 1998 Costs and Returns of Cassava Production and results of other relevant surveys.

The document on Editing Guidelines is provided as a Related Material.

Response rate

The survey has a response rate of 100 percent

Data appraisal

Series of reviews were done to assess the quality of the data in terms of reliability and acceptability. A comparison with the results of past surveys on input usage, labor utilization, production cost and return structure of camote (potato) was made.