According to forecast data from Tellusant, **** percent of the population in the Philippines in 2024 would earn at least the equivalent of the top 40 percent of global earners in 2022 constant purchasing power parity. Out of those 98.7 percent, *** percent would earn the equivalent of the top 10 percent of global earners in 2022 constant purchasing power parity.

Number of Families: Philippines - All Income Classes data was reported at 22,730,000.000 Unit in 2015. This records an increase from the previous number of 21,426,000.000 Unit for 2012. Number of Families: Philippines - All Income Classes data is updated yearly, averaging 15,874,827.500 Unit from Dec 1988 (Median) to 2015, with 10 observations. The data reached an all-time high of 22,730,000.000 Unit in 2015 and a record low of 10,533,925.000 Unit in 1988. Number of Families: Philippines - All Income Classes data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H014: Family Income and Expenditure Survey: No of Families: By Income Class and Main Source of Income.

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata. DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted. REGION: Africa SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available. Philippines data available from WorldPop here.

Abstract

The 1997 Family Income and Expenditute Survey had the following objectives: 1. to gather data on family income and family living expenditures and related information affecting income and expenditure levels and patterns in the Philippines;

1. to determine the sources of income and income distribution, levels of living and spending patterns, and the degree of inequality among families;

2. to provide benchmark information to update weights in the estimation of consumer price index (CPI); and

3. to provide inputs in the estimation of the country's poverty threshold and incidence.

Geographic coverage

National coverage

Analysis unit

Household Consumption expenditure item Income by source

Universe

The 1997 FIES has as its target population, all households and members of households 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/her spouse, children, parent, brother/sister, son-in-law/daughter-in-law, grandson/granddaughter and other relatives. Household membership likewise includes boarders, domestic helpers and non-relatives. A person who lives alone is considered a separate household.

Institutional population is not within the scope of the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling design of the 1997 FIES adopted that of the Integrated Survey of Households (ISH). Starting July 1996, the sampling design of the ISH uses the new master sample design. The multi-stage sampling design of the master sample consists of 3,416 PSUs in the expanded sample for provincial level estimates with a sub-sample of 2,247 PSUs designated as the core master sample for regional levels estimates. The 1997 FIES was based on the expanded sample.

Domains The urban and rural areas of each province are the principal domains for the survey. In addition, areas with 150,000 or more population as of 1995 Census of Population (POPCEN) are also domains of the survey with rural and urban dimensions. The domains for the new master sample are similar to that of the previous ISH design with an addition of 23 newly created domains.

The multi-stage sampling design of the master sample involves the selection of the sample barangays for the first stage, selection of sample enumeration areas for the second stage, and the selection of sample households for the third stage in each stratum for every domain.

The frame for the first stage and second stages of sample selection were based mainly on the results of the 1995 POPCEN. The 1995 list of barangays with the household and population counts is used in the first stage of sample selection. The stratification of barangays included in the frame, however are based on the 1990 Census of Population and Housing (CPH) and other administrative reports from the field offices of NSO. An enumeration area (EA) is a physical delineated portion of the barangay. For barangays that were not divided into EAs, the barangay was treated as an EA.

The enumeration areas which constitutes the secondary sampling units are those that were formed during the 1995 POPCEN. The sample barangays were selected systematically with probability proportional to size from the list of barangays that were implicitly stratified.

The frame for the third stage of sample selection is the list of households from the 1995 POPCEN. The selection of sample households for the third stage was done systematically from the 1995 POPCEN List of Households.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire has five main parts consisting of the following: Part I. Identification and Other Information (Geographic Identification, Other Information and Particulars about the Family)

Part II. Expenditures and Other Disbursements Section A. Food, Alcoholic Beverages and Tobacco Section B. Fuel, Light and Water, Transportation and Communication, 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 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 E. Family Sustenance Activities

Part IV. Entrepreneurial Activities Section A1. Crop Farming and Gardening Section A2. Livestock and Poultry Raising Section A3. Fishing Section A4. Forestry and Hunting Section A5. Wholesale and Retail Section A6. Manufacturing Section A7. Community, Social, Recreational and Personal Services Section A8. Transportation, Storage and Communication Services Section A9. Mining and Quarrying Section A10. Construction Section A11. Entrepreneurial Activities Not Elsewhere Classified

Part V: Health - Care Section A. Health - care Expenditures Section B. Health Insurance

Cleaning operations

The 1997 FIES questionnaire contains about 800 data items and a guide for comparing income and expenditures. The questionnaires were subjected to a rigorous manual and machine edit checks for completeness, arithmetic accuracy, range validity and internal consistency.

The electronic data processing system developed since 1985 FIES by the Information System Development Section was used in processing the 1997 FIES with few modifications.

There were thirteen major steps in the machine processing and these are as follows: 1. Data entry and verification 2. Structural editing (minor edit) 3. Edit list verification/correction 4. Update 5. Completeness check 6. Completeness check list verification/correction 7. Identification verification 8. Identification verification extraction of summary file for preliminary results 9. Matching of visit records 10. Expansion 11. Tabulations 12. Generation of CPI weights 13. Variance analysis

Steps 1 to 8 were performed right after each visit while the remaining steps were carried out upon completion of the data collection for the first and second visits.

Steps 1 to 7 were implemented at the regional office while the concluding steps were handled at the Central Office.

Response rate

The response rate for the 1997 FIES is 96.4%.

Sampling error estimates

As in all surveys, two types of non-response were encountered in the 1997 FIES: Interview non-response and item non-response. Interview non-response refers to a sample household that could not be interviewed. Since the survey requires that the sample households be interviewed in both visits, households that transferred to another dwelling unit, temporarily away, on vacation, not at home, household unit demolished, destroyed by fire/typhoon and refusal to be interviewed in the second visit contributed to the number of interview non-response cases.

Item non-response, or the failure to obtain responses to particular survey items, resulted from factors such as respondents being unaware of the answer to a particular question, unwilling to provide the requested information or ENs' omission of questions during the interview. Deterministic imputation was done to address item nonresponse. This imputation is a process in which proper entry for a particular missing item was deduced from other items of the questionnaire where the non-response item was observed. Notes and remarks indicated in the questionnaire were likewise used as basis for imputation.

In 2020, the estimated size of the middle class population in the six selected Southeast Asian countries Indonesia, Malaysia, Philippines, Singapore, Thailand, and Vietnam amounted to around 200 million. That year, approximately 80 million people of Indonesia's total population were part of the middle class.

Includes median household income in the past twelve months (in 2022 inflation-adjusted dollars). Geography-specific median household income are calculated as the population-weighted averages of the median household incomes within their respective 2020 census tracts. Median household income is defined as the amount that divides the household income distribution of a population into two equal groups; half of the population has a household income above that amount, whereas the other half has a household income below that amount. Household income is an important driver of life expectancy and other health outcomes, as individuals with higher household incomes, on average, experience better health and live longer than individuals with lower household incomes. This is largely due to increased access to opportunities, resources, and healthier living conditions that higher income individuals experience compared to lower income individuals.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

To estimate county of residence of Filipinx healthcare workers who died of COVID-19, we retrieved data from the Kanlungan website during the month of December 2020.22 In deciding who to include on the website, the AF3IRM team that established the Kanlungan website set two standards in data collection. First, the team found at least one source explicitly stating that the fallen healthcare worker was of Philippine ancestry; this was mostly media articles or obituaries sharing the life stories of the deceased. In a few cases, the confirmation came directly from the deceased healthcare worker's family member who submitted a tribute. Second, the team required a minimum of two sources to identify and announce fallen healthcare workers. We retrieved 86 US tributes from Kanlungan, but only 81 of them had information on county of residence. In total, 45 US counties with at least one reported tribute to a Filipinx healthcare worker who died of COVID-19 were identified for analysis and will hereafter be referred to as “Kanlungan counties.” Mortality data by county, race, and ethnicity came from the National Center for Health Statistics (NCHS).24 Updated weekly, this dataset is based on vital statistics data for use in conducting public health surveillance in near real time to provide provisional mortality estimates based on data received and processed by a specified cutoff date, before data are finalized and publicly released.25 We used the data released on December 30, 2020, which included provisional COVID-19 death counts from February 1, 2020 to December 26, 2020—during the height of the pandemic and prior to COVID-19 vaccines being available—for counties with at least 100 total COVID-19 deaths. During this time period, 501 counties (15.9% of the total 3,142 counties in all 50 states and Washington DC)26 met this criterion. Data on COVID-19 deaths were available for six major racial/ethnic groups: Non-Hispanic White, Non-Hispanic Black, Non-Hispanic Native Hawaiian or Other Pacific Islander, Non-Hispanic American Indian or Alaska Native, Non-Hispanic Asian (hereafter referred to as Asian American), and Hispanic. People with more than one race, and those with unknown race were included in the “Other” category. NCHS suppressed county-level data by race and ethnicity if death counts are less than 10. In total, 133 US counties reported COVID-19 mortality data for Asian Americans. These data were used to calculate the percentage of all COVID-19 decedents in the county who were Asian American. We used data from the 2018 American Community Survey (ACS) five-year estimates, downloaded from the Integrated Public Use Microdata Series (IPUMS) to create county-level population demographic variables.27 IPUMS is publicly available, and the database integrates samples using ACS data from 2000 to the present using a high degree of precision.27 We applied survey weights to calculate the following variables at the county-level: median age among Asian Americans, average income to poverty ratio among Asian Americans, the percentage of the county population that is Filipinx, and the percentage of healthcare workers in the county who are Filipinx. Healthcare workers encompassed all healthcare practitioners, technical occupations, and healthcare service occupations, including nurse practitioners, physicians, surgeons, dentists, physical therapists, home health aides, personal care aides, and other medical technicians and healthcare support workers. County-level data were available for 107 out of the 133 counties (80.5%) that had NCHS data on the distribution of COVID-19 deaths among Asian Americans, and 96 counties (72.2%) with Asian American healthcare workforce data. The ACS 2018 five-year estimates were also the source of county-level percentage of the Asian American population (alone or in combination) who are Filipinx.8 In addition, the ACS provided county-level population counts26 to calculate population density (people per 1,000 people per square mile), estimated by dividing the total population by the county area, then dividing by 1,000 people. The county area was calculated in ArcGIS 10.7.1 using the county boundary shapefile and projected to Albers equal area conic (for counties in the US contiguous states), Hawai’i Albers Equal Area Conic (for Hawai’i counties), and Alaska Albers Equal Area Conic (for Alaska counties).20

This includes all measure of poverty among family and population at the regional level for the years 1991, 2006, 2009, 2012, and 2015. These are Poverty Incidence and Magnitude, Poverty and Food Thresholds, Poverty Gap, Income Gap, and Extent of Poverty. These data were derived from the result of Family Income and Expenditure Surveys and Labor Force Surveys.Map Displays at Scale: 1:12,000,000 to 1:147,000,000. Download detailed metadata about Philippine SDG 1.

Abstract

The 2009-2010 HIES collected information on key topics such as family demography, education, health, employment and consumption. The scope of 2009-2010 HIES was broader than the previous survey, with more indicators and more households surveyed, including questions on living standards and other related subject areas. One key goal was to collect data on income and expenditure, and to enable a rebasing of the Consumer Price Index (CPI). This will assist future policy decisions and analysis to be better based on reliable evidence, such that they can better support improvements in the living standards of Papua New Guinea’s people.

As the 2009-2010 HIES was a multi-topic survey, the following types of information were collected:

1. Household level information on housing characteristics, ownership of consumer durables, non- food consumption, access to various types of public services, and incidence and resolution of different types of disputes.

2. Person-level information on age, sex, education, health, employment status, receipt of remittances, and personal security. This was supplemented by anthropometric data for children aged six years or younger.

3. Personal record of all food and nonfood purchases for 14 consecutive days for all household.

Geographic coverage

National

Analysis unit

• Household
• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design PNG is the largest nation in the South Pacific in both land area and population. It is comprised of around 600 islands, and the interior of the country is mountainous. Administratively, the country is divided into 22 provinces, within four geographic regions: Southern Region comprising of the following provinces: Western, Gulf, Central, Milne Bay, Northern Oro, and the National Capital District Highlands Region comprising of the following provinces: Southern Highlands, Enga, Western Highlands, Chimbu, Eastern Highlands, Hela, and Jiwaka Momase Region comprising of the following provinces: Moroboe, Madang, East Sepik, and West Sepik Island Region comprising of Manus, New Ireland, East New Britain, West New Britain, and the Autonomous Region of Bougainville.

A two-stage stratified cluster sample design was used in order to ensure independent estimates for the "rural", "urban", and "metro" areas of each of these regions. "Metro" denotes the two large urban centres of Port Moresby in Southern region and Lae in the Momase region. All the other urban areas in all regions were included in the "urban" stratum. The sample was thus divided into 10 strata. Sample size in each cluster was set to ensure reliable strata-level representative estimates; in addition, the sample size in the metropolitan areas was set large enough to support the development of a new CPI expenditure basket. In each stratum, households were chosen in two stages. In the first stage, using the sampling frame of the 2000 Census, clusters (or Primary Sampling Units) (PSU) were chosen using probability proportional to size. A full listing of households was done in all chosen clusters and a pre-set number of households were then selected randomly from this list. In the non-metropolitan areas, 18 households were chosen per cluster whereas in the metropolitan areas, 6 households were chosen per PSU. Replacement census units or replacement households in each cluster are used in the case of emergencies or when selected households could not be interviewed because of refusal, absence, illness in the family etc, were also selected using the same methodology.

Mode of data collection

Face-to-face [f2f]

Research instrument

The HIES is a complex application with a hierarchical set of questionnaires. For example, the main questionnaire consists of a household roster and other household information, and there are separate questionnaires for eligible members in the household. The data entry application may then contain two levels-one for the household and one for each eligible member in the household. The set of forms corresponding to the household, make up level one. The set of forms corresponding to each eligible member make up level two. Each case would consist of a level one and a variable number of level occurrences for level two. Most applications consist of a single level.

The survey questionnaires contain the following FORMS: 1) From A: Household Control Form 2) Form B: Household Schedule Form 3) Form C: Personal Schedule 4) Form D: Personal Diary 5) Form E: Personal Notepad

Abstract

The primary purpose of this survey was to gather more accurate and detailed information on income and expenditure levels and flows in the Marshall Islands (MHL) and to update and revise the MHL Consumer Price Index (a separate series of publications document the CPI revision efforts).

Geographic coverage

National coverage; urban and rural.

Analysis unit

Household and Individual.

Universe

All usual household residents in private dwellings.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE SIZE: In determining an appropriate sample size for a survey of this nature, numerous factors come into the equation. These include:

a) The degree of accuracy required for key estimates; b) The population size of the country; c) The manner in which the sample is selected; d) Cost or staffing constraints which may exist; e) Whether or not estimates are required for sub-populations; f) The level of variability in the data being collected.

Each of these factors have different magnitudes of importance, but the major priority should always be on selecting a sample big enough to produce results of suitable accuracy. Many of these issues are generally known as well - for instance:

· A user group may pre-specify what level of accuracy they may wish to achieve for the survey · The population of a country can normally be estimated to a reasonable level of accuracy · The sample selection technique adopted is known · Cost and staff constraints are generally known, and · A user group can once again provide information on whether estimates for sub-populations are required.

The Marshall Islands 2020 Household Income and Expenditure Survey (HIES) aims to release outputs at the Urban Rural level and National level.

The sampling strategy has been developed around a stratification of urban and rural domains of the Marshall Islands. This stratification aims to improve the robustness of the indicators at urban and rural level. The urban sector has been stratified in 2 different atolls (Majuro and Kwajalein) and the rural region has been stratified in group of atolls that show similarities as follow: - Rural 1: peri urban atolls; located close to Majuro and Kwajalein (Arno, Mili) - Rural 2: most important rural atolls with facilities (boarding schools; health center…) (Jaluit; Wotje) - Rural 3: atolls where population benefit from US Government for nuclear testing (Enewatak, Kili, Utirik) - Rural 4: other atolls

The targeted sample size has been determined around 880 households based on the results of the previous 2011 population census that provided the mean and standard deviation of the total cash household income at the strata level:

The cluster size has been determined at 12 households.

-Urban 1 & 2: respectively 400 and 150 households spread across 33 and 13 EAs lead to 7.9% RSE in Urban domain
-Rural: respectively 2, 3, 10 and 13 EAs in rural1, 2, 3 and 4 (24, 36, 120 and 150 households) lead to 7.3% RSE in Rural domain -At the National level this total sample size of 880 households spead across those 6 stratas as mentioned lead to a RSE of 7.1%

SAMPLE SELECTION: The 2020 Marshall Islands HIES is based on a stratified cluster sampling strategy. The households are selected in 2 steps: - Step1: the random selection of EA based on the sampling strategy parameters (Primary sampling unit) - Step2: the random selection of 12 households (+6 replacements) within each selected EA

The final probability of selection combines both probabilities of EA getting selected within the strata and households getting selected with the EA.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire was produced in English and Marshallese languages. The English questionnaire can be found in the External Resources.

Below is the list of all questionnaire modules: -1. Household ID -2. Household member roster -3. Person details: Profile; Education; Health; Physical; Communication; Alcohol & tobacco; Other individual expenses; Labour force; Fisheries hunting; Handicraft & home processed food) -4. Food away from home: Breakfast; Lunch; Dinner; Snacks; Hot drinks; Bottked water; Non-alcoholic drinks -5. Own production -6. Deprivation (persons) -7. Food recall -7.1. Partaker -8. Non-food recall -9. Household details: Dwelling characteristics; Household assets; Other household items & services; Ceremonies; Remittances; Food insecurity; Copra production; Livestock & aquaculture; Agriculture; Legal services -10. Deprivation and financial inclusion (household) -11. Migrant worker -12. Geographic information + photo.

Cleaning operations

Data editing was done using the software Stata.

Response rate

Below are the response rates by urban-rural region for Set A (households selected from the sample): -Urban: 85.3% -Rural: 89% -NATIONAL: 86.7%

Below are the response rates by urban-rural region for Set B (households selected from the sample + replacements): -Urban: 99.8% -Rural: 95.8% -NATIONAL: 98.3%

Sampling error estimates

-RELATIVE SAMPLING ERRORS (RSEs): Below are the RSEs for total expenditure throughout all COICOP divisions, by urban and rural areas: .Urban: 3.6%; Mean expenditure: 5,119; Lower 95% confidence interval: 4,747; Upper 95% confidence interval: 5,490. .Rural: 6.3%; Mean expenditure: 3,280; Lower 95% confidence interval: 2,870; Upper 95% confidence interval: 3,691. .NATIONAL: 3.3%; Mean expenditure: 4,659; Lower 95% confidence interval: 4,348; Upper 95% confidence interval: 4,969.

Below are the RSEs for total income throughout all PACCOI divisions, by urban and rural areas: .Urban: 7.6%; Mean income: 3,612; Lower 95% confidence interval: 3,061; Upper 95% confidence interval: 4,162. .Rural: 9.2%; Mean income: 3,585; Lower 95% confidence interval: 2,928; Upper 95% confidence interval: 2,928. .NATIONAL: 6.2%; Mean income: 3,605; Lower 95% confidence interval: 3,161; Upper 95% confidence interval: 3,161.

The detailed relative sampling errors (RSEs) for the 2019 Marshall Islands Household Income and Expenditure Survey (HIES) will be included in the Appendix section of the final analytical report (when released).

Abstract

The 2000 Family Income and Expenditute Survey had the following objectives:

1.to gather data on family income and family living expenditures and related information affecting income and expenditure levels and patterns in the Philippines;

1. t o determine the sources of income and income distribution, levels of living and spending patterns, and the degree of inequality among families;

2. to provide benchmark information to update weights in the estimation of consumer price index (CPI); and

3. to provide inputs in the estimation of the country's poverty threshold and incidence.

Geographic coverage

National coverage

Analysis unit

Household Consumption expenditure item Income by source

Universe

The 2000 FIES has as its target population, all households and members of households nationwide. Institutional population is not within the scope of the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling design of the 2000 FIES adopted that of the Integrated Survey of Households (ISH). Starting July 1996, the sampling design of the ISH uses the new master sample design. The multi-stage sampling design of the master sample consists of 3,416 sample barangays in the expanded sample for provincial level estimates with a sub-sample of 2,247 Primary Sampling Units (PSUs) designated as core master sample for regional level estimates. The 2000 FIES was based on the expanded sample.

1. Domains: The domains for the new master sample are similar to that of the previous ISH design with an addition of 23 newly created domains. The urban and rural areas of cities and municipalities with a population of 150,000 or more are considered as separate domains. The other urban and rural areas in each of the 77 provinces are likewise treated as separate domains. In view of the creation of ARMM and the separation of Marawi City and Cotabato City from Lanao del Sur and Maguindanao, respectively, the urban and rural areas of the two cities also form separate domains.

2. Sampling Units: The multi-stage sampling design of the master sample involves the selection of the sample barangays for the first stage, selection of sample enumeration areas for the second stage, and the selection of sample households for the third stage in each stratum for every domain.

The frame for the first and second stages of sample selection was based mainly on the results of the 1995 Census of Population (POPCEN). The 1995 POPCEN list of barangays with the household and population counts is used in the first stage of sample selection. The stratification of barangays included in the frame, however, are based on the 1990 Census of Population and Housing (CPH) and other administrative reports from field offices of the NSO. An enumeration area (EA) is a physical delineated portion of the barangay. For barangays that were not divided into EAs, the barangay was treated as an EA.

The enumeration areas which constitute the secondary stage sampling units are those that were formed during the 1995 POPCEN. The sample barangays were selected systematically with probability proportional to size from the list of barangays that were implicitly stratified.

Isolated barangays and/or barangays that are difficult and expensive to reach are excluded from the sampling frame. However, critical areas or barangays with peace and order problem, which is generally temporary in nature, are included in the frame.

The frame for the third stage of sample selection is the list of the households from the 1995 POPCEN. The selection of sample household for the third stage was done systematically from the 1995 POPCEN List of the Households.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire has four main parts consisting of the following: Part I. Identification and Other Information (Geographic Identification, Other Information and Particulars about the Family)

Part II. Expenditures Section A. Food, Alcoholic Beverages and Tobacco Section B. Fuel, Light and Water, Transportation and Communication, 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 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 F. Family Sustenance Activities

Part IV. Entrepreneurial Activities Section A1. Crop Farming and Gardening Section A2. Livestock and Poultry Section A3. Fishing Section A4. Forestry and hunting Section A5. Wholesale and Retail Section A6. Manufacturing Section A7. Community, Social, Recreational and Personal Services Section A8. Transportation, Storage and Communication Services Section A9. Mining and Quarrying Section A10. Construction Section A11. Entrepreneurial Activities Not Elsewhere Classified

A guide for comparing disbursements against receipts is found on the last page.

The general design of the questionnaire also includes codes inside the box usually located at the top of the framed questions. These codes are for automatic data processing purposes. Ignore them during the interview process. Take note that the paging of the questionnaire is located outside the frame on each page.

Cleaning operations

The 2000 FIES questionnaire contains about 800 data items and a summary for comparing income and expenditures. The questionnaires were subjected to a rigorous manual and machine edit checks for completeness, arithmetic accuracy, range validity and internal consistency.

The major steps in the machine processing are as follows: 1. Data entry 2. Structural, Range Edit and Consistency Edit (Minor Edit) 3. Completeness Check 4. Matching of visit records 5. Generation of the Binary file 6. Consistency and Macro Edit (Big Edit) 7. Expansion 8. Tabulation 9. Generation of CPI 10. Variance Analysis 11. Generation of the Public Use File (PUF)

Steps 1 to 3 were done right after each visit. The remaining steps were carried out only after the second visit had been completed.

Steps 1 to 6 were done at the Regional Office where Steps 4-6 were accomplished only after finishing the second visit. Steps 7 to 11 were completed in the Central Office.

After completing Steps 1 to 6, data files were transmitted to the Central Office where a summary file was generated. The summary file was used to produce the consistency tables as well as the preliminary and textual tables.

Where the generated tables showed inconsistencies, selected data items were subjected to further scrutiny and validation. The cycle of generation of consistency tables and data validation were done until questionable data items were verified.

Innovations for the 2000 FIES machine processing were carried out by the Information Technology System and Research Division of the NSO by introducing the FIES Integrated Processing System (FIPS). This is a Windows application system which facilitated data encoding, completeness and validity check.

The 2000 FIES machine processing was further enhanced using an interactive Windows-based system named FAME (FIES computer-Aided Consistency and Macro Editing). The interactive module of FAME enabled the following activities to be done simultaneously: a) Matching of visit records b) Generation of Binary files c) Consistency and Macro Edit (Big Edit) d) Range Check

The improved system minimized processing time as well as minimized, if not eliminated the need for paper to generate the reject listing.

Response rate

The response rate for the 2000 FIES is 96.6%

Number of people belonging to a visible minority group as defined by the Employment Equity Act and, if so, the visible minority group to which the person belongs. 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, Latin American, Arab, Southeast Asian, West Asian, Korean and Japanese.

Abstract

The Consultative Group to Assist the Poor (CGAP) and Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) have conducted a baseline demand-side study of person-to-person (P2P) remittances in Jordan to gather insight into existing customers, non-customers and potential customers. This study informed the implementation of a larger project to improve access to remittances and other financial services through digital solutions for financially excluded groups. The focal population for this study was low-income Jordanians (defined as those with a monthly household income of under 400 Jordanian Dinars) and Syrian refugees who have been in Jordan for at least a year.

The study focused on remittance activity and awareness and access to technology, with market forecasting for a digital remittance product. Key findings elicited insights into potential barriers to a digital remittance product, as well as enabling factors, and revealed a small market opportunity.

Geographic coverage

West Amman, East Amman, Irbid, Zarqa, Mafraq, Karak, Ma’an, Azraq refugee camp, Zaatari refugee camp

Analysis unit

Individuals, households

Universe

Low-income Jordanians and Syrian refugees

Kind of data

Sample survey data [ssd]

Sampling procedure

The quantitative survey consisted of two independent samples:

• n= 1,091 low-income Jordanians (defined as those with less than 400JD of household income per month) • n= 1,041 Syrian refugees living in Jordan

Quotas were used for both groups so the sample better represented available univariate population data in terms of geographic distribution, age and gender. Refer to “Digittances Quantitative Data User Guide” for more information.

Mode of data collection

Face-to-face [f2f]

Research instrument

Refer to “Digittances Quantitative Data User Guide”

Cleaning operations

In addition to the quality control conducted during fieldwork, data cleaning was conducted after fieldwork was completed. This included checks for internal consistency, missing variables, blank variables, and outliers. Ipsos data storage is audited annually as part of our ISO 27001 and 20252 accreditations and is compatible with security accreditation.

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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 2008 Annual Poverty Indicators Survey (APIS) is conducted by the National Statistics Office (NSO) as a rider to the July 2008 Labor Force Survey (LFS). The 2008 APIS is the sixth in the series of annual poverty indicators surveys conducted nationwide. Since 1998, APIS has been conducted during the years when the Family Income and Expenditures Survey (FIES) is not conducted, except in 2001 and 2005 due to budgetary constraints.

The APIS is a nationwide survey designed to provide non-income indicators related to poverty at the national and regional levels. It is designed to gather data on the socio-economic profile of families and other information that are related to their living conditions. Specifically, it generates indicators which are correlated with poverty, such as indicators regarding the ownership or possession of house and lot, the types of the materials of the roofs and walls of their housing units, their access to safe water, the types of toilet facility they use in their homes, and presence of family members of specified characteristics such as children 6-12 years old enrolled in elementary, children 13-16 years old enrolled in high school, members 18 years old and over gainfully employed, working children 5-17 years old and family members with membership in any health, life and/or pre-need insurance system.

The APIS is being undertaken by the National Statistics Office as mandataed by Commonwealth Act 591 which authorizes the then Bureau of the Census and Statistics, now NSO, "to conduct by enumeration, sampling or other methods, for statistical purposes, studies of the social and economic situation of the country" and in consonance with the provision of Executive Order 121 which designated the office as the "major statistical agency responsible for generating general purpose statistics.

Geographic coverage

National Coverage Seventeen (17) Administrative Regions: National Capital Region (NCR) Cordillera Administrative Region (CAR) I - Ilocos II - Cagayan Valley III - Central Luzon IVA - CALABARZON IVB - MIMAROPA V - Bicol VI - Western Visayas VII - Central Visayas VIII - Eastern Visayas IX - Zamboanga Peninsula X - Northern Mindanao XI - Davao XII - SOCCSKSARGEN XIII - Caraga Autonomous Region in Muslim Mindanao (ARMM)

Analysis unit

Households

Universe

The survey covered all households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2008 APIS is a sample survey designed to provide data representative of the country and its 17 administrative regions. The survey's sample design helps ensure this representativeness. The 2008 APIS used the 2003 master sample created for household surveys on the basis of the 2000 Census of Population and Housing (CPH) results. The survey used four replicates of the master sample. For each region (domain) and stratum, a three-stage sampling scheme was used: the selection of primary sampling units (PSUs) for the first stage, of sample enumeration areas (EAs) for the second stage, and of sample housing units for the third stage. PSUs within a region were stratified based on the proportion of households living in housing units made of strong materials, proportion of households in the barangay engaged in agricultural activities and per capita income of the city/municipality.

As earlier mentioned, a three-stage sampling design was used in each stratum within a region. In the first stage, primary sampling units (PSUs) were selected with probability proportional to the number of households in the 2000 Census. PSUs consisted of a barangay or a group of contiguous barangays. In the second stage, in each sampled PSU, EAs were selected with probability proportional to the number of households in the 2000 Census. An EA is defined as an area with discernable boundaries consisting of approximately 350 contiguous households. In the third stage, from each sampled EA, housing units were selected using systematic sampling. For operational considerations, at most 30 housing units were selected per sample EA. All households in sample housing units were interviewed except for sample housing units with more than three households. In such a housing unit, three households were randomly selected with equal probability.

The 2008 APIS was conducted simultaneously with the July 2008 Labor Force Survey (LFS). All sample households of the July 2008 LFS were interviewed for the 2008 APIS. Only household members related to the household head by blood, marriage or adoption were considered as members of the sample household in APIS. Family members of the household head who are working abroad were excluded.

Sampling deviation

NA

Mode of data collection

Face-to-face [f2f]

Research instrument

Although questions on 'Changes in Welfare' were dropped and some items were modified for the 2008 APIS, most of the questions/items in the previous APISs were retained as requested by data users. Nine items were added in order to generate data that will be more useful in assessing the poverty situation in the country. The new questionnaire for the 2008 contains the abridged version of the module on entrepreneurial activities resulting to the reduction of the number of pages from 24 to 12. The decision to use the abridged version was based on the results of the study entitled “Redesigning APIS as a Poverty Monitoring Tool” undertaken by the Demographic and Social Statistics Division in 2006. The redesigned questionnaire produced results which are not statistically different from results based on the original design in 2004. The use of the redesigned questionnaire is also cost-efficient.

A round table discussion was held for the 2008 APIS before the conduct of the pretest. The redesigned APIS questionnaire based from the project's output was presented. It was agreed upon during this meeting to adopt the redesigned APIS for this round of APIS, with the addition of item on 'Hunger'.

Cleaning operations

Flow of Processing Activity

In order to implement a systematic flow of the processing activities and reduce the movement of questionnaires from one employee to another, the same processor performed the following specific activities for the same folio. 1. General screening; 2. Editing and coding of APIS questionnaires and computations of totals ; and 3. General review of edited APIS questionnaire.

Folioing

To facilitate handling during manual and machine processing, APIS questionnaires were folioed in the Provincial Office before the start of manual processing.

The APIS questionnaires for one sample barangay/EA contained in the folio was arranged consecutively according to the sample housing serial number (SHSN) from lowest to highest.

General Screening

General screening was done by going over the submitted accomplished questionnaires and checking for the completeness of the geographic identification and other information called for in the cover page.

General screening for APIS questionnaires was done to ensure that the geographic and household identification and the entire sample households are the same with the MS Form 6.

General Instructions on Manual Processing

The following instructions was observed in manual processing.

1. Prior to editing and coding of items, the questionnaires were checked if they were properly folioed. Folioing was done in the province. Regional Offices checked if folioing was done properly by the Provincial Offices.

2. All questionnaires for one folio was assigned to only one editor/coder, unless otherwise necessary (e.g., when the one who is processing a folio is absent for more than a day).

3. In general, the editors assumed that the original entries are correct. Editing was done only when an entry is obviously incorrect. A doubtful or inconsistent item was verified in the field.

Response rate

Of the 43,020 eligible sample households for the 2008 APIS, 40,613 were successfully interviewed. This translated to a response rate of 94.4 percent at the national level. Households which were not interviewed either refused to be interviewed or were not available or were away during the enumeration period.

Sampling error estimates

Sampling errors have been calculated for the following variables: 1) Percentage of Families with Own or Ownerlike Possession of House and Lot they Occupy 2) Percentage of Families Living in Houses with Roof Made of Strong Materials 3) Percentage of Families Living in Houses with Outer Walls Made of Strong Materials 4) Percentage of Families with Electricity in the Building/House They Reside in 5) Percentage of Families with Access to Safe Water Supply 6) Percentage of Families with Sanitary Toilet 7) Percentage of Families with Children 6-12 Years Old in Elementary Grades 8) Percentage of Families with Children 13-16 Years Old in High School 9) Percentage of Families with Members 18 Years Old and Over Gainfully Employed 10) Percentage of Families with Working Children 5-17 Years Old 11) Average Family Income 12) Average Family Expenditure

Data appraisal

A series of data quality tables were generated to review the quality of the data and include the following: - Age distribution of the household population - Highest grade completed versus current grade - Highest grade completed versus age - Current grade versus age - Reason for not attending school versus highest grade completed - Reason for not attending school versus current grade - Marital status versus age - Consistency of income vs. expenditure