The United States reported the highest number of emigrants from the Philippines in 2022, with about **** thousand Filipinos choosing to live there permanently. In comparison, Spain had *** Filipino emigrants that year.An emigrant is a person who has left their country to live permanently in another.

Philippines Overseas Filipinos: Permanent: World data was reported at 4,869,766.000 Person in 2013. This records a decrease from the previous number of 4,925,797.000 Person for 2012. Philippines Overseas Filipinos: Permanent: World data is updated yearly, averaging 3,407,967.000 Person from Dec 1997 (Median) to 2013, with 17 observations. The data reached an all-time high of 4,925,797.000 Person in 2012 and a record low of 2,153,967.000 Person in 1997. Philippines Overseas Filipinos: Permanent: World data remains active status in CEIC and is reported by Commission on Filipinos Overseas. The data is categorized under Global Database’s Philippines – Table PH.G020: Stock Estimate of Overseas Filipinos. The Stock Estimate is the aggregate of all Filipinos residing or working overseas at a given time. It included the permanent, temporary and irregular migrants · Permanent migrants- immigrants and legal permanent residents abroad, Filipinos naturalized in their host country, Filipino dual citizens · Temporary Migrants/Contract Worker- land-based and sea-based Filipino workers and others whose stay abroad is six month or more, and their accompanying dependents · Irregular Migrants- Filipinos not properly documented residence or work permits, in a foreign country

Overseas Filipino workers (OFWs) based in the United States were the leading source of remittances received by the Philippines in 2024. Remittances from the U.S. amounted to around ** billion U.S. dollars. Singapore follows, with remittances amounting to around **** billion U.S. dollars. Economic contribution of remittances  Remittances, in case or kind, have been a fundamental source of income in the Philippines. In fact, in 2020, the county ranked second to India when it comes to the total personal remittances received in the Asia Pacific region. Overall, personal remittances contributed about **** percent to the country's GDP. Demographics of OFWs  Of the **** million Filipino labor migrants employed worldwide in 2023, women accounted for the higher share of OFWs compared to men. In terms of age, most women OFWs were between the age of 30 and 34, while the majority of male OFWs were 45 years old and above.

Abstract

The Survey on Overseas Filipinos (SOF) was conducted as a rider to the October 2008 Labor Force Survey (LFS).

The survey was designed to gather national estimates on the number of overseas workers, their socio economic characteristics and other information pertaining to the overseas workers who worked or have worked abroad from April to September 2008. The remittances of the Overseas Filipino Workers (OFWs) in cash or in kind were also accounted for the specified reference period. The SOF data are useful inputs to government planners, migrant advocates, researchers, academes, concerned citizens, and other data users to the formulation of policies and programs for the welfare of the overseas Filipino.

Geographic coverage

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

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

Analysis unit

Individuals

Universe

Overseas Filipinos whose departure occured within the last five years and who are working or had worked abroad during the past six months (April to September) of the survey period.

For purposes of this survey, overseas workers are the following:

Filipino overseas contract workers (OCW) who are presently and temporarily out of the country to fulfill an overseas work contract for a specific length of time or who are presently at home on vacation but still has an existing contract to work abroad. They may be landbased or seabased.

Landbased workers ? these are overseas contract workers who are hired either by direct hiring of an employer abroad; or through the assistance of Philippine Overseas Employment Administration (POEA); or through a private and licensed recruitment agency. They may have returned to the Philippines for a vacation (annual or emergency leave), or have transferred to other employers, or were rehired by their former employer.

Seabased workers ? these are overseas contract workers who worked or are working in any kind of international fishing/passenger/cargo vessels. Included also are OCWs who worked or are working for a shipping company abroad.

Other Filipino workers abroad with a valid working visa or work permits. Included also are crew members of airplanes such as pilots, stewards, stewardesses, etc. example: Filipinos working in countries such as U.S., Taiwan, Saipan, etc. with a working visa.

Filipinos abroad who are holders of other types of non-immigrant visa such as tourist/visitor, student, medical and others but are presently employed and working full time.

Persons not considered as overseas workers are:

Filipinos whose place of employment is outside the Philippines but whose employer is the Philippine government. Examples are Filipinos who worked or are working in Philippine embassies, missions and consulates abroad.

Filipinos who are sent abroad by the Philippine government or by private institutes for training, scholarship or any other similar purpose, even if they are known to be working abroad. Note that students who are sent abroad by private individual who are working or had worked there are excluded in this category.

Filipinos working in other countries who are hired as consultants/advisers of International organization such as the United Nations International Monetary Fund, etc.

Immigrants to other countries even though they are working abroad.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Survey on Overseas Filipinos, as a rider to the Labor Force Survey (LFS), used the sampling design of the 2003 Master Sample (MS) for Household Surveys starting July 2003. The design of the Master Sample is described below:

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

2. Sampling Frame 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.

1. Sample Size The 2003 MS consists of a sample of 2,835 PSUs of which 330 were certainty PSUs and 2,505 were non-certainty PSUs. The entire MS was divided into four sub-samples or independent replicates, such as a quarter sample contains one fourth of the PSUs found in one replicate; a half sample contains one-half of the PSUs in two replicates. The SOF as a rider to the LFS utilizes the full sample.

2. Stratification 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 as stratification factors (PERCAPITA).

PSTRONG is defined to be the percentage of occupied housing units that are classified as made of strong materials in terms of both the roof and outer walls, based on the data from the 2000 CPH. A roof is considered made of strong material if it is made of either galvanized iron, aluminum, concrete/clay tile, half galvanized-half concrete, or asbestos. The outer wall is considered made of strong material if it is made of concrete, brick, stone, wood, half concrete-half wood, galvanized iron, asbestos or glass.

AGRI was determined in the following way: initially, an indicator variable was computed at the barangay level. That variable has the value 1 if more than 50 percent of the households in the barangay were engaged in agriculture or fisheries and 0 otherwise, based on the 2000 CPH Barangay Schedule. To obtain a measure at the PSU level, a weighted average of the barangay indicator variable was computed for all the barangays within the PSU, weighted by the total number of households in the barangay. Thus, the value of AGRI at the PSU level lies between 0 and 1.

PERCAPITA is defined as the total income of the municipality divided by the total population in that municipality. Note that the PERCAPITA value of the PSUs is the same if the PSUs are in the same municipality. The data on municipal income refer to year 2000 and were taken from the Department of Finance. However, if the 2000 municipal income was not reported to the Bureau of Local Government Finance (BLGF), 2001 income was used. If no 2000 or 2001 municipal income was reported, the income classification from the BLGF for this municipality was obtained. Using the data on income, which are presented in income intervals, the average of the lower and the upper values of the income interval for the municipal class to which this municipality belongs were determined.

1. Sample Selection

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 subsamples 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 self-representing (SR) or non-self-representing (NSR). In addition, to facilitate the selection of subsamples, 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

In 2024, preliminary figures recorded about **** million Filipinos leaving the Philippines to work overseas — a number higher than the previous year's estimates. The number of deployed overseas Filipino workers (OFWs) significantly plummeted between 2020 and 2021 due to the COVID-19 pandemic. Leading occupation of deployed OFWs  Among the newly hired land-based overseas Filipino workers in 2023, about ******* of them were domestic cleaners and helpers, followed by domestic housekeepers. Filipino domestic cleaners and housekeepers have been in demand in several countries, particularly in the Middle East and Hong Kong. These countries usually offer higher wages and better employment benefits for such jobs, in comparison to employers in the Philippines. Increasing demand for healthcare workers  Aside from domestic cleaners and housekeepers, recent years reflected a growing demand for healthcare workers, especially since the onset of the COVID-19 pandemic. In 2020, Saudi Arabia was the leading destination of deployed Filipino nurses, followed by the United Kingdom and Germany.

Philippines OFWs: Africa data was reported at 28.295 Number th in 2023. This records an increase from the previous number of 20.243 Number th for 2022. Philippines OFWs: Africa data is updated yearly, averaging 24.725 Number th from Dec 1999 (Median) to 2023, with 24 observations. The data reached an all-time high of 38.845 Number th in 2013 and a record low of 6.000 Number th in 2001. Philippines OFWs: Africa data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.G044: Overseas Filipino Workers.

Nearly half of all remittances sent towards Southeast Asia went towards the Philippines as of 2021, probably because of overseas Filipino workers (OFW). This is according to a database that tries to model money sent internationally from one party to another. Remittances typically refer to money sent from migrant workers back home to family and friends, although there are other forms of this. Remittances can, for example, include pensioners who have a second home in foreign country. The Philippines received most of its remittances from four countries in particular: The United States, Saudi Arabia, Canada, and the United Arab Emirates.

The value of remittances to the Philippines outweighed the value sent to other countries about ** times in 2021, according to a ranking that maps the flow of such money transfers. Remittances refer to cross-border payments to family or friends and are often associated with migrant workers sending money back home to friends or relatives back in their communities of origin. It is estimated that about one in seven people worldwide are involved with remittances - substantially impacting payment behavior in, especially, Asia and Latin America. For the Philippines, the top five recipient countries for remittances in 2021 included China, Japan, the United States, India, and South Korea. The Philippines' main sources for remittances were the United States, Saudi Arabia, Canada, the United Arab Emirates, and Australia.

Philippines Overseas Workers: Annual: Deployed: LB: Africa: Angola data was reported at 2,940.000 Person in 2016. This records a decrease from the previous number of 3,843.000 Person for 2015. Philippines Overseas Workers: Annual: Deployed: LB: Africa: Angola data is updated yearly, averaging 2,940.000 Person from Dec 2000 (Median) to 2016, with 17 observations. The data reached an all-time high of 6,255.000 Person in 2010 and a record low of 788.000 Person in 2000. Philippines Overseas Workers: Annual: Deployed: LB: Africa: Angola data remains active status in CEIC and is reported by Philippine Overseas Employment Administration. The data is categorized under Global Database’s Philippines – Table PH.G023: Overseas Contract Workers: Processed and Deployed.

Between January and October 2020, ***** newly hired nursing professionals from the Philippines were deployed to Saudi Arabia, making it the country with the highest demand for this type of worker. This was followed by the United Kingdom, Germany, and Singapore. The demand for nursing professionals from the country increased during the COVID-19 pandemic.

Philippines OFWs: Europe data was reported at 182.191 Number th in 2023. This records an increase from the previous number of 176.844 Number th for 2022. Philippines OFWs: Europe data is updated yearly, averaging 162.722 Number th from Dec 1999 (Median) to 2023, with 24 observations. The data reached an all-time high of 193.140 Number th in 2012 and a record low of 89.000 Number th in 1999. Philippines OFWs: Europe data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.G044: Overseas Filipino Workers.

Philippines' total Imports in 2024 were valued at US$134.88 Billion, according to the United Nations COMTRADE database on international trade. Philippines' main import partners were: China, Indonesia and Japan. The top three import commodities were: Electrical, electronic equipment; Mineral fuels, oils, distillation products and Machinery, nuclear reactors, boilers. Total Exports were valued at US$72.98 Billion. In 2024, Philippines had a trade deficit of US$61.90 Billion.

Overseas Filipino Workers (OFWs) are considered bagong bayani, or modern-day heroes, as their remittances have a positive long-term impact on the Philippines economy. The Philippines ranked 10th worldwide in terms of net emigration from 2010 to 2020. The deployment of OFWs declined during the pandemic, and this was estimated to have adverse effects on remittances. As a migrant-sending country, the Philippine government had to deal with the mass of unemployed OFWs stranded in their host countries and organize large-scale repatriation of OFWs. This scoping review aims to assess the existing literature, identify research gaps, and propose future research directions concerning the socio-economic impact of the COVID-19 pandemic on OFWs and their left-behind families. The results indicate that the impact of the pandemic on OFWs was not uniform. It is evident that OFWs in precarious situations beforehand have become even more vulnerable. The loss of their source of income in the host country and the restrictions on international mobility during the pandemic had significant detrimental effects on their wellbeing and their families left behind, regardless of their income level or type of job. Upon returning to their home country, they often experienced anxiety, depression, discrimination, and difficulty in finding a job. Overall, this scoping review highlights the urgent need for greater recognition and protection of OFWs in times of crisis. It is crucial to address the systemic issues that contribute to their vulnerability and to ensure that they receive adequate support and protection in host countries and the Philippines.

Tariff rate, most favored nation, simple mean, all products (%) in Philippines was reported at 6.15 % in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Philippines - Tariff rate, most favored nation, simple mean, all products - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Philippines PH: Tariff Rate: Most Favored Nation: Weighted Mean: All Products data was reported at 6.080 % in 2016. This records a decrease from the previous number of 6.510 % for 2015. Philippines PH: Tariff Rate: Most Favored Nation: Weighted Mean: All Products data is updated yearly, averaging 5.900 % from Dec 1988 (Median) to 2016, with 27 observations. The data reached an all-time high of 22.510 % in 1989 and a record low of 2.440 % in 2003. Philippines PH: Tariff Rate: Most Favored Nation: Weighted Mean: All Products data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Philippines – Table PH.World Bank: Trade Tariffs. Weighted mean most favored nations tariff is the average of most favored nation rates weighted by the product import shares corresponding to each partner country. Data are classified using the Harmonized System of trade at the six- or eight-digit level. Tariff line data were matched to Standard International Trade Classification (SITC) revision 3 codes to define commodity groups and import weights. Import weights were calculated using the United Nations Statistics Division's Commodity Trade (Comtrade) database.; ; World Bank staff estimates using the World Integrated Trade Solution system, based on data from United Nations Conference on Trade and Development's Trade Analysis and Information System (TRAINS) database and the World Trade Organization’s (WTO) Integrated Data Base (IDB) and Consolidated Tariff Schedules (CTS) database.; ;

Statistics illustrates most promising supplying countries of manostats in the Philippines from 2007 to 2024.

Philippines PH: Income Share Held by Highest 20% data was reported at 47.300 % in 2015. This records a decrease from the previous number of 49.100 % for 2012. Philippines PH: Income Share Held by Highest 20% data is updated yearly, averaging 49.100 % from Dec 1985 (Median) to 2015, with 11 observations. The data reached an all-time high of 52.100 % in 1997 and a record low of 47.300 % in 2015. Philippines PH: Income Share Held by Highest 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Philippines – Table PH.World Bank.WDI: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

As of the third quarter of 2024, internet users in the Philippines spent an average of **** hours accessing the internet on various devices, according to a global survey. In terms of devices, most Filipinos have used their mobile phones to surf the web. Internet usage of Filipinos Being the population with the most time spent using the internet in the region, Filipino internet users have been taking advantage of the ease of communication and access to information and entertainment that the internet offers. Aside from just browsing the web, accessing social media has been popular among a large share of the Filipino population. As of the third quarter of 2023, Meta platforms such as Facebook and Instagram, along with TikTok, were the most used social media platforms in the country. These platforms were used to connect with friends and family, and to access news and information, stream video content, and find products and services to purchase. Level of internet security in the Philippines Since most activities have been digitalized, cybersecurity threats and online fraud have been a growing concern among internet users. In the Philippines, over ** million web threats have been detected in 2022. Among those who shop on social media, product fraud was identified as the most common fraud type, along with non-delivery of products or services and payment fraud. To address this, the national government amended its cybersecurity laws to ensure better security of internet users in the Philippines.

Tariff rate, most favored nation, simple mean, primary products (%) in Philippines was reported at 7.54 % in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Philippines - Tariff rate, most favored nation, simple mean, primary products - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Tariff rate, most favored nation, simple mean, manufactured products (%) in Philippines was reported at 5.66 % in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Philippines - Tariff rate, most favored nation, simple mean, manufactured products - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.