Average Family Income: Philippines: All Income Classes data was reported at 267,000.000 PHP in 2015. This records an increase from the previous number of 235,000.000 PHP for 2012. Average Family Income: Philippines: All Income Classes data is updated yearly, averaging 146,019.500 PHP from Dec 1988 (Median) to 2015, with 10 observations. The data reached an all-time high of 267,000.000 PHP in 2015 and a record low of 40,408.000 PHP in 1988. Average Family Income: 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.H021: Family Income and Expenditure Survey: Average Annual Income: By Family Size and Income Group.

Avg Family Income: By Income Class and Family Size: Philippines data was reported at 267,000.000 PHP in 2015. This records an increase from the previous number of 235,000.000 PHP for 2012. Avg Family Income: By Income Class and Family Size: Philippines data is updated yearly, averaging 146,019.500 PHP from Dec 1988 (Median) to 2015, with 10 observations. The data reached an all-time high of 267,000.000 PHP in 2015 and a record low of 40,408.000 PHP in 1988. Avg Family Income: By Income Class and Family Size: Philippines data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H021: Family Income and Expenditure Survey: Average Annual Income: By Family Size and Income Group.

Context

The Philippine Statistics Authority (PSA) spearheads the conduct of the Family Income and Expenditure Survey (FIES) nationwide. The survey, which is undertaken every three (3) years, is aimed at providing data on family income and expenditure, including, among others, levels of consumption by item of expenditure, sources of income in cash, and related information affecting income and expenditure levels and patterns in the Philippines.

Content

Inside this data set is some selected variables from the latest Family Income and Expenditure Survey (FIES) in the Philippines. It contains more than 40k observations and 60 variables which is primarily comprised of the household income and expenditures of that specific household

Acknowledgements

The Philippine Statistics Authority for providing the publisher with their raw data

Inspiration

Socio-economic classification models in the Philippines has been very problematic. In fact, not one SEC model has been widely accepted. Government bodies uses their own SEC models and private research entities uses their own. We all know that household income is the greatest indicator of one's socio-economic classification that's why the publisher would like to find out the following:

1) Best model in predicting household income 2) Key drivers of household income, we want to make the model as sparse as possible 3) Some exploratory analysis in the data would also be useful

In 2023, the average annual income of families in the Philippines increased to ******* Philippine pesos, indicating a significant growth from the 2021 average. In the same year, the average annual expenditure of families in the country was ******* Philippine pesos.

Average Family Income: Philippines: Two Persons data was reported at 192,000.000 PHP in 2015. This records an increase from the previous number of 167,000.000 PHP for 2012. Average Family Income: Philippines: Two Persons data is updated yearly, averaging 179,500.000 PHP from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 192,000.000 PHP in 2015 and a record low of 167,000.000 PHP in 2012. Average Family Income: Philippines: Two Persons data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H021: Family Income and Expenditure Survey: Average Annual Income: By Family Size and Income Group.

According to a survey on consumer expectations in the fourth quarter of 2024, about ** percent of households with savings in the Philippines were high-income earners. The share of households with savings fluctuated since 2020.

Average Family Income: Philippines: Six Persons data was reported at 289,000.000 PHP in 2015. This records an increase from the previous number of 259,000.000 PHP for 2012. Average Family Income: Philippines: Six Persons data is updated yearly, averaging 274,000.000 PHP from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 289,000.000 PHP in 2015 and a record low of 259,000.000 PHP in 2012. Average Family Income: Philippines: Six Persons data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H021: Family Income and Expenditure Survey: Average Annual Income: By Family Size and Income Group.

The National Capital Region recorded the highest average annual family income in the Philippines, amounting to 513,520 Philippine pesos, according to preliminary figures for 2023. Meanwhile, the BARMM region had the average family income, with 206,880 Philippine pesos. Overall, the country's average annual family income was reported at approximately 353,230 Philippine pesos for that year.

Abstract

The 1994 Family Income and Expenditure Survey (FIES) is a nationwide survey of households undertaken by the National Statistics Office (NSO). Similar surveys were conducted in 1956-1957, 1961, 1965, 1971, 1975, 1979, 1985 and 1988. Like the previous surveys, this undertaking aims to accomplish the following primary 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;

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 (CPI)

Geographic coverage

National coverage

Analysis unit

Household Consumption expenditure item Income by source

Universe

The 1994 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 1994 FIES adopts that of the Integrated Survey of Households (ISH), which uses a stratified two-stage cluster sampling design. It is prepared by the National Economic and Development Authority (NEDA) Technical Committee on Survey Design and first implemented in 1984. It is the same sampling design used in the ISH modules starting in 1986.

The urban and rural areas of each province are the principal domains of the survey. In addition, the urban and rural areas of cities with a population of 150,000 or more as of 1990 are also made domains of the survey with rural and urban dimensions. These include the four cities and five municipalities of Metro Manila (Manila, Quezon City, Pasay and Caloocan; Valenzuela, Parañaque, Pasig, Marikina and Makati), and other key cities such as Baguio, Angeles, Cabanatuan, Olongapo, Batangas, Lipa, Lucena, San Pablo, Bacolod, Iloilo, Cebu, Mandaue, Zamboanga, Butuan, Cagayan de Oro, Davao, General Santos, and Iligan and key municipalities such as San Fernando, Pampanga and Tarlac, Tarlac.

Sampling Units and Sampling Frame The primary sampling units (PSUs) under the sample design are the barangays and the households within each sample barangay comprise the secondary sampling units (SSUs).

The frame from which the sample barangays are drawn is obtained from the 1990 Census of Population and Housing (CPH). Hence, all the approximately 40,000 barangays covered in the 1990 CPH are part of the primary sampling frame.

The sampling frame for the SSUs, that is, the households, is prepared by listing all households in each of the selected sample barangays. The listing operation is conducted regularly in the sample barangays to update the secondary sampling frame from where the sample households are selected.

Sample Size and Sampling Fraction The size of the sample is envisioned to meet the demand for fairly adequate statistics at the domain level. Taking this need into account and considering cost constraints as well, the decision reached is for a national sample of about 26,000 households.

In general, the sample design results in self-weighting samples within domains, with a uniform sampling fraction of 1:400 for urban and 1:600 for rural areas. However, special areas are assigned different sampling fractions so as to obtain "adequate" samples for each. Special areas refer to the urban and rural areas of a province or large city which are small relative to their counterparts.

Selection of Samples For the purpose of selecting PSUs, the barangay in each domain are arranged by population size (as of the 1990 Census of Population) in descending order and then grouped into strata of approximately equal sizes. Four independent PSUs are drawn with probability proportional to size with complete replacement.

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 F. 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 1994 FIES questionnaire contains about 800 data items and a guide for comparing income and expenditures and internal consistency.

Upon submission of the data diskettes containing first and second visit data, a summary file was extracted from the entire file through a computer program.

The questionnaires were further subjected to a rigorous manual and machine edit checks for completeness, arithmetic accuracy, range validity and internal consistency. Items failing any of the edit checks were either corrected automatically by the computer on the basis of pre-determined specifications or, when needed, examined in a clerical error-reconciliation operation.

The electronic data-processing (EDP) system developed by the NSO Data Processing Staff and used in the 1985 and 1988 FIES was generally adopted in processing the 1991 FIES with few modifications. There are thirteen (13) major steps in the machine processing of the 1991 FIES 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. Extraction of summary file for preliminary results 9. Matching of visit records (big edit) 10. Internal consistency checks (big edit) 11. Reject lists verification/correction 12. Update 13. Expansion 14. Tabulation 15. Generation of CPI weight tables 16. 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 offices. In addition, except for NCR, Region 3, 6, 7 and the province of Basilan, Sulu, Tawi-tawi and Zamboanga City which were handled by the Central Office. Steps 10 and 11 were likewise undertaken in the regional offices. The first passes of reject listings were sent to the regional offices for verification and correction/updates are sent back to the Central Office for data file updating. Meanwhile, steps 8, 9 and all the concluding steps were handles by the Central Office.

For data entry, IMPS (Integrated Microcomputer Processing System) was used.

Response rate

The response rate is the ratio of the total responding households to the total number of eligible households. Eligible households include households who were completely interviewed, refused to be interviewed or were temporarily away or not at home or on vacation during the survey period.

Sampling error estimates

As in all surveys, two types of non-response were encountered in the 1994 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.

Based on preliminary results in 2023, the proportion of families in the Philippines with income below the poverty threshold was estimated at **** percent, lower than the estimate for 2018. In that year, the average per capita food threshold reached ****** Philippine pesos.

The average annual income of families of the city of Manila in the Philippines reached 482,790 Philippine pesos according to the preliminary figures for 2023. This reflected a 17 percent increase compared to the values for 2021.

The National Caputal Region (NCR) recorded the highest average annual family expenditure in the Philippines, amounting to 385,050 Philippine pesos, according to preliminary estimates for 2023. In contrast, BARMM had the lowest expenditure, with 168,910 Philippine pesos. Overall, the country's average annual family income was reported at approximately 258,050 Philippine pesos for that year.

In 2023, a family of five in the Philippines had a poverty threshold of a little 13,873 Philippine pesos per month. That was higher than the monthly poverty threshold in 2018, which amounted to around about 12,000 Philippine pesos.

Philippines Average Family Income: By Income Class (IC): Annual data was reported at 267,000.000 PHP in 2015. This records an increase from the previous number of 235,000.000 PHP for 2012. Philippines Average Family Income: By Income Class (IC): Annual data is updated yearly, averaging 146,019.500 PHP from Dec 1988 (Median) to 2015, with 10 observations. The data reached an all-time high of 267,000.000 PHP in 2015 and a record low of 40,408.000 PHP in 1988. Philippines Average Family Income: By Income Class (IC): Annual data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H018: Family Income and Expenditure Survey: Average Annual Income and Expenditure: By Income Class.

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

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.

Average Family Income: Philippines: Three Persons data was reported at 237,000.000 PHP in 2015. This records an increase from the previous number of 214,000.000 PHP for 2012. Average Family Income: Philippines: Three Persons data is updated yearly, averaging 225,500.000 PHP from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 237,000.000 PHP in 2015 and a record low of 214,000.000 PHP in 2012. Average Family Income: Philippines: Three Persons data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H021: Family Income and Expenditure Survey: Average Annual Income: By Family Size and Income Group.

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

Philippines No. of Families: IC: Annual: PhP 250,000 and over data was reported at 7,888,000.000 Unit in 2015. This records an increase from the previous number of 6,228,000.000 Unit for 2012. Philippines No. of Families: IC: Annual: PhP 250,000 and over data is updated yearly, averaging 7,058,000.000 Unit from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 7,888,000.000 Unit in 2015 and a record low of 6,228,000.000 Unit in 2012. Philippines No. of Families: IC: Annual: PhP 250,000 and over 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.

Philippines Avg Family Income: 5 persons or less: PhP 40,000 - 59,999 data was reported at 51,000.000 PHP in 2015. This stayed constant from the previous number of 51,000.000 PHP for 2012. Philippines Avg Family Income: 5 persons or less: PhP 40,000 - 59,999 data is updated yearly, averaging 51,000.000 PHP from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 51,000.000 PHP in 2015 and a record low of 51,000.000 PHP in 2015. Philippines Avg Family Income: 5 persons or less: PhP 40,000 - 59,999 data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H021: Family Income and Expenditure Survey: Average Annual Income: By Family Size and Income Group.