As of January 2024, the prices of essential goods in the Philippines increased compared to the same month in the previous year. With the exception of rice, most basic goods noted a significant increase in prices. For instance, the price of six kilograms of meat rose from nearly 1,600 Philippine pesos in 2022 to 1,843 Philippine pesos in 2024. In addition, the cost of eight kilograms of vegetables increased from 698 to 857 Philippine pesos.

Cost of food in Philippines increased 0.40 percent in June of 2025 over the same month in the previous year. This dataset provides the latest reported value for - Philippines Food Inflation - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Abstract

The National Statistics Office generates various establishment based price indices and one of these is the Producers Price Index. The 2008 PPI (2000=100) is generated from the results of the Producer Price Survey conducted monthly by the NSO. This is done through the collection of actual producer prices from sample establishments nationwide. The PPS uses a shuttle type questionnaire which provides the respondent establishments with a running account of all monthly responses for the year. For 2008, the survey covered 595 sample products produced by 309 manufacturing establishments.

The Producer Price Index (PPI) for Manufacturing is a composite figure of producers prices of representative commodities included in the market basket. The PPI serves various purposes, the most important of which are the following: a. measures monthly or yearly changes in the producers prices of key commodities in the manufacturing sector b. serves as deflator to Value of Production Index (VAPI) in the estimation of Volume of Production Index (VOPI) c. serves as deflator in the estimation of manufacturing production in real terms (at constant prices) in the system of national accounts.

The PPI is computed using the Paasche-type method of index computation . As such, the weights are continously revised upon availability of the latest data from the annual survey or census. In the case of 2008 PPI, the weights are taken from the 2005 Annual Survey of Philippine Business and Industry (ASPBI). The revision of weights , are however instituted at the beginning of each year and are used for the entire year.

Geographic coverage

The geographic domain is the whole country.

Analysis unit

The unit of analysis for this survey is the establishment. An establishment is defined as an economic unit under a single ownership or control, i.e., under a single legal entity, engaged in one or predominantly one kind of economic activity at a single fixed location.

Universe

Manufacturing establishments with total employment of 20 and over

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2008 PPS is a non-probability sampling survey of the manufacturing sector. Sample establishments and commodities were selected using the following criteria: a. the commodity has a relatively high market share b. the commodity was available in the market in 2000, this being the base year c. the commodity is being produced currently, and d. the market share of the commodity has been stable for the last 3 years

In the same manner, criteria were also set for the selection of establishments, as follows: a. establishment has an ATE of 50 and over b. establishment has relatively high concentration ratio c. establishment is good respondent in past and current surveys of NSO; that is, it submits prompt reports and provides quality data d. preferably, the establishment is a sample of the Monthly Integrated Survey of Selected Industries (MISSI).

The 2008 PPS utilizes the 3-digit and selected 4-digit amended Philippine Standard Industrial Classification (PSIC) as its industry domain which is patterned after ISIC version 3.

Thus, there are 20 major sectors with 10 further categorized into sub-sectors or a total of 37 sub-sectors for the 2008 MISSI. These are:

1. Food Manufacturing
   1.1. Processed meat and fish 1.2. Processed fruits and vegetables 1.3. Vegetable and animal oils and fats 1.4. Milk and dairy products 1.5. Grain mills products 1.6. Animal feeds 1.7. Bakery products 1.8. Milled and refined sugar 1.9. Coconut products 1.10. Miscellaneous foods
2. Beverages
3. Tobacco products
4. Textiles 4.1. Textile products 4.2. Cordage, rope and twine
   1. Footwear and wearing apparel
   2. Leather products
   3. Wood and wood products 7.1. Planning and sawmill 7.2. Veneer and plywood 7.3. Other wood products
   4. Paper and paper products
   5. Publishing and printing
   6. Petroleum products 10.1. Refined petroleum products 10.2. Coke and other fuel products
   7. Chemical products 11.1. Basic Chemicals and industrial gases 11.2. Fertilizers 11.3. Paints 11.4. Drugs and medicines 11.5. Cosmetics and toilet preparations 11.6. Miscellaneous Chemicals
   8. Rubber and plastic products 12.1. Rubber products 12.2. Plastic products
   9. Non-metallic mineral products 13.1. Glass and glass products 13.2. Cement 13.3. Miscellaneous non-metallic mineral products
   10. basic metals 14.1. Iron and steel 14.2. Non-ferrous metals
   11. Fabricated metal products
   12. Machinery except electrical 16.1. Office,accounting and computing machinery 16.2. Machinery and equipment n.e.c.
   13. Electrical machinery 17.1. Electrical appliances 17.2. Wires and wirings 17.3. Batteries 17.4. Lamps and fixtures 17.5. Microcircuits
   14. Transport equipment
   15. Furnitures and fixtures
   16. Miscellaneous Manufactures

Indicators generated from 2008 PPS (2000=100) are the following: 1. Producer Price Index (PPI), yearly and monthly growth rates

Imputation methods used for unit and item non-response are as follows: 1. Historical imputation without trend adjustment, or the use of the latest available data of the establishment
2. Imputed values are revised upon receipt of actual data for inclusion in the revised indices

Mode of data collection

Self Administered Questionnaire and/or Face-to-face interview

Research instrument

The Producer Price Survey utilizes a shuttle type questionnaire. This approach reduces cost and enhances consistency and accuracy in reporting since the respondent establishment is provided with a running account of all monthly responses for the year.

Cleaning operations

It is important to verify the reasonableness and reliability of the prices of products included in the market basket for a given month. Data editing consisted of three stages: field editing, office verification and machine validation.

· Field editing of data was done by the provincial staff upon collection of the accomplished questionnaires from the establishments. The objective is to check for completeness and consistency of entries in the questionnaires. Any inconsistent or missing data was corrected at this stage as this can be immediately verified from the respondents.

· Office verification was done by provincial office staff upon receipt of the accomplished questionnaires from the field men. In some instances, callback to the establishments in the form of phone call or email to verify some inconsistent or missing data is done.

· Desk verification was done by the ISD staff to check the consistency and reasonableness of entries in the accomplished questionnaires. This process also validates the status of establishments such as non-responding and reported closed, cannot be located, transferred, and out of scope. The telephone was extensively utilized to verify information from the establishment's contact person. The Internet was also used to obtain information on the contact address and to research for information on the status of the establishment.

.For unit or item non-response, the following are undertaken: 1. Establishments that stopped operation, temporary out of business (TOB), strike, etc., during the year, historical imputation without trend adjustment or the use of the latest available data of the establishment. This method is appropriate for the reason that the prices of a number of products/commodities do not change very much over a short period of time. 2. Imputed values are revised upon receipt of actual data for inclusion in the revised indices.

Response rate

The average monthly response rate is 88.84%, 35 days (preliminary tabulation) after the reference month and 95 % for the final table.

Sampling error estimates

Not applicable.

Data appraisal

The quality of the PPI indicators are measured in terms of the following:

Representativeness of the samples as measured in the CONCENTRATION RATIO- the combined production value of the samples as a percentage to the total industry production value

Response rate of the survey

Imputation method used for non-responses

Inflation Rate in Philippines increased to 1.40 percent in June from 1.30 percent in May of 2025. This dataset provides the latest reported value for - Philippines Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The real per capita consumer spending on food and non-alcoholic beverages in the Philippines was forecast to continuously increase between 2024 and 2029 by in total 107.1 U.S. dollars (+14.34 percent). After the ninth consecutive increasing year, the real food-related per capita spending is estimated to reach 853.96 U.S. dollars and therefore a new peak in 2029. Consumer spending, in this case food-related spending per capita, refers to the domestic demand of private households and non-profit institutions serving households (NPISHs). Spending by corporations and the state is not included. The forecast has been adjusted for the expected impact of COVID-19.Consumer spending is the biggest component of the gross domestic product as computed on an expenditure basis in the context of national accounts. The other components in this approach are consumption expenditure of the state, gross domestic investment as well as the net exports of goods and services. Consumer spending is broken down according to the United Nations' Classification of Individual Consumption By Purpose (COICOP). The shown data adheres broadly to group 01. As not all countries and regions report data in a harmonized way, all data shown here has been processed by Statista to allow the greatest level of comparability possible. The underlying input data are usually household budget surveys conducted by government agencies that track spending of selected households over a given period.The data has been converted from local currencies to US$ using the average constant exchange rate of the base year 2017. The timelines therefore do not incorporate currency effects. The data is shown in real terms which means that monetary data is valued at constant prices of a given base year (in this case: 2017). To attain constant prices the nominal forecast has been deflated with the projected consumer price index for the respective category.Find more key insights for the real per capita consumer spending on food and non-alcoholic beverages in countries like Laos and Cambodia.

The real total consumer spending on healthcare in the Philippines was forecast to continuously increase between 2024 and 2029 by in total *** billion U.S. dollars (+**** percent). After the ninth consecutive increasing year, the real healthcare-related spending is estimated to reach **** billion U.S. dollars and therefore a new peak in 2029. Consumer spending, in this case healthcare-related spending, refers to the domestic demand of private households and non-profit institutions serving households (NPISHs). Spending by corporations and the state is not included. The forecast has been adjusted for the expected impact of COVID-19.Consumer spending is the biggest component of the gross domestic product as computed on an expenditure basis in the context of national accounts. The other components in this approach are consumption expenditure of the state, gross domestic investment as well as the net exports of goods and services. Consumer spending is broken down according to the United Nations' Classification of Individual Consumption By Purpose (COICOP).The shown data adheres broadly to group **. As not all countries and regions report data in a harmonized way, all data shown here has been processed by Statista to allow the greatest level of comparability possible. The underlying input data are usually household budget surveys conducted by government agencies that track spending of selected households over a given period.The data has been converted from local currencies to US$ using the average constant exchange rate of the base year 2017. The timelines therefore do not incorporate currency effects. The data is shown in real terms which means that monetary data is valued at constant prices of a given base year (in this case: 2017). To attain constant prices the nominal forecast has been deflated with the projected consumer price index for the respective category.Find more key insights for the real total consumer spending on healthcare in countries like Thailand and Myanmar.

Abstract

The Philippine Statistics Authority generates various establishment based price indices and one of these is the Producers Price Index. The 2013 PPI (2000 base year) is generated from the results of the Producer Price Survey conducted monthly by the PSA. This is done through the collection of actual producer prices from sample establishments nationwide. The PPS uses a shuttle type questionnaire which provides the respondent establishments with a running account of all monthly responses for the year. For 2013, the survey covered 595 sample products produced by 309 manufacturing establishments.

The Producer Price Index (PPI) for Manufacturing is a composite figure of producers prices of representative commodities included in the market basket. The PPI serves various purposes, the most important of which are the following: - measures monthly or yearly changes in the producers prices of key commodities in the manufacturing sector; - serves as deflator to Value of Production Index (VAPI) in the estimation of Volume of Production Index (VOPI); - serves as deflator in the estimation of manufacturing production in real terms (at constant prices) in the system of national accounts.

The PPI is computed using the Paasche-type method of index computation. As such, the weights are continously revised upon availability of the latest data from the annual survey or census. In the case of 2013 PPI, the weights are taken from the 2010 Annual Survey of Philippine Business and Industry (ASPBI). The revision of weights , are however instituted at the beginning of each year and are used for the entire year.

Geographic coverage

National

Analysis unit

Establishment - defined as an economic unit under a single ownership or control, i.e., under a single legal entity, engaged in one or predominantly one kind of economic activity at a single fixed location.

Universe

The 2013 PPS covers formal sector manufacturing establishments with total employment of 20 and over.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2013 PPS is a non-probability sampling survey of the manufacturing sector. Sample establishments and commodities were selected using the following criteria: a. the commodity has a relatively high market share b. the commodity was available in the market in 2000, this being the base year c. the commodity is being produced currently, and d. the market share of the commodity has been stable for the last 3 years

In the same manner, criteria were also set for the selection of establishments, as follows: a. establishment has an average total employemeny of 50 and over b. establishment has relatively high concentration ratio c. establishment is good respondent in past and current surveys of PSA; that is, it submits prompt reports and provides quality data d. preferably, the establishment is a sample of the MISSI.

The 2013 PPS utilizes the 3-digit and selected 4-digit ammended PSIC as its industry domain which is patterned after ISIC version 3. Thus, there are 20 major sectors with 10 further categorized into sub-sectors or a total of 37 sub-sectors for the 2013 MISSI/PPS.

Mode of data collection

Face-to-face [f2f]

Research instrument

The PPS went through the clearance process of the National Statistical Coordination Board (NSCB). It utilizes a shuttle type questionnaire with NSCB approval number and expiration date. The field offices distribute the questionnaires at the beginning of the year and collects the data on a monthly basis.

Cleaning operations

It is important to verify the reasonableness and reliability of the prices of products included in the market basket for a given month. Data editing consisted of three stages: field editing, office verification and machine validation.

Field editing of data was done by the provincial staff upon collection of the accomplished questionnaires from the establishments. The objective is to check for completeness and consistency of entries in the questionnaires. Any inconsistent or missing data was corrected at this stage as this can be immediately verified from the respondents.

Office verification was done by provincial office staff upon receipt of the accomplished questionnaires from the field men. In some instances, callback to the establishments in the form of phone call or email to verify some inconsistent or missing data is done.

Desk verification was done by the ISD staff to check the consistency and reasonableness of entries in the accomplished questionnaires. This process also validates the status of establishments such as non-responding and reported closed, cannot be located, transferred, and out of scope. The telephone was extensively utilized to verify information from the establishment's contact person. The Internet was also used to obtain information on the contact address and to research for information on the status of the establishment.

For unit or item non-response, the following are undertaken: - Establishments that stopped operation, temporary out of business, on strike, etc., during the year, historical imputation without trend adjustment or the use of the latest available data of the establishment. This method is appropriate for the reason that the prices of a number of products/commodities do not change very much over a short period of time. - Imputed values are revised upon receipt of actual data for inclusion in the revised indices.

Response rate

The average monthly response rate is 88.84%, 35 days (preliminary tabulation) after the reference month and 95 % for the final table.

Sampling error estimates

Not applicable.

Data appraisal

The quality of the PPI indicators are measured in terms of the following:

• Representativeness of the samples as measured in the Concentration Ratio - the combined production value of the samples as a percentage to the total industry production value;
• Response rate of the survey;
• Imputation method used for non-responses.

Abstract

Farm prices refer to the prices received by the farmers and livestock/poultry raisers for the sale of their produce at the first point of sale, regardless of whether these are sold at the farm or elsewhere. These prices are generated through the monthly Farm Prices Survey (FPS).

The survey on prices of agricultural commodities at the farm level has been a continuing activity of the Bureau of Agricultural Statistics (BAS) and its predecessor, Bureau of Agricultural Economics (BAEcon). It was started with the collection of prices received by farmers in 1957 by the then Division of Agricultural Economics of the Department of Agriculture and Natural Resources (DANR). Conceptually, these prices were deemed to represent the average prices received by farmers for the sale of their products of whatever grade or class at the point of first sale.

To ensure the effectiveness of the system of generating and delivering data on farm prices, the Bureau of Agricultural Statistics has been conducting assessment of the Farm Prices Survey methodology from time to time. The main purpose of the assessment is to improve the quality of the price information gathered at the farm level. The 1998 assessment provided inputs to the design of the current Farm Price Survey methodology.

Geographic coverage

National coverage Regional Provincial

Analysis unit

The survey has individual farmers/producers and agricultural commodites as unit of analysis.

Universe

All prices received by farmers for agricultural commodities including crops, livestock, poultry and prices paid for farm chemicals

Kind of data

Sample survey data [ssd]

Sampling procedure

Commodities to be monitored by province are pre-determined based on four (4) criteria, namely: major produce of the province in terms of volume of production; priority crop of the province; national commodity and with the province being one of the major producers; and one of the commodities monitored for the Producers' Price Index (PPI). Determination of the agricultural commodities to be monitored for farm prices shall be done at the Provincial Operations Centers (POCs) and shall be submitted to the Central Office for information and approval.

For crops and backyard livestock and poultry, the farm prices survey utilizes a two-stage sampling procedure with the province as the domain.

The first stage sampling unit is the municipality. It consists of the top five (5) producing municipalities per commodity per province. Selection of these municipalities is done monthly on the assumption that they could change every month for each crop.

The second stage sampling unit is the farmer or livestock/poultry raiser who traded the commodities during the reference period. In each sample municipality, at least five (5) sample farmers or raisers are chosen purposively and interviewed. This two-stage procedure gives the total number of respondents for farm prices survey at 25 per commodity per province.

When less than five (5) municipalities are identified for farm prices survey during the month, the number of samples per municipality is increased to get a provincial total of 25. In the allocation of the number of samples in the municipalities selected, the volume of production and trading during the reference period is considered.

For livestock and poultry commercial farms, the samples are randomly selected from the Commercial Livestock and Poultry Survey (CLPS) master list of establishments for each animal type. Samples are stratified according to the maximum capacity of the farm. Four (4) strata are required to give a total of eight (8) samples for the province. If there are less than four (4) strata in the province, the number of samples per stratum are increased proportionately to get a provincial total of eight (8). In case the total number of farms for each poultry item is less than eight (8), complete enumeration is done.

Respondents for Farm Prices Survey component on pesticides are the dealers of agricultural inputs in the five major crop producing municipalities and in the provincial capital or trading center. Sample dealers of inputs are those most patronized by farmers. One dealer per municipality will be interviewed. In addition, the three (3) major pesticide dealers in the provincial capital or trading center shall be considered as samples. The maximum number of samples per province is eight (8).

Mode of data collection

Face-to-face [f2f]

Research instrument

There are seven (7) forms to be used in the Farm Prices Survey, namely:

FPS Form 1 - Collection Form for Farm Prices Received by Farmers for Crops FPS Form 2 - Collection Form for Farm Prices Received by Backyard Raisers of Cattle and Carabaos FPS Form 3 - Collection Form for Farm Prices Received by Backyard Raisers of Hogs (upgraded) FPS Form 4 - Collection Form for Farm Prices Received by Backyard Raisers of Goats FPS Form 5 - Collection Form for Farm Prices Received by Backyard and Commercial Raisers of Chicken and Chicken Eggs FPS Form 6 - Collection Form for Farm Prices Received by Backyard and Commercial Raisers of Ducks and Duck Eggs FPS Form 8 - Collection Form for Farm Prices Paid by Farmers for Pesticides

FPS Form 1-6 and 8 are survey questionnaires. These have been approved by the National Statistical Coordination Board (NSCB) with the corresponding approval numbers indicated on the right side of the upper portions of the questionnaires.

Cleaning operations

Accomplished Farm Prices Survey questionnaires are subjected to manual editing and coding by Operations Centers staff as data collector and Provincial Agricultural Statistics Officer as supervisor.

Editing, encoding and generation of monthly provincial reports are done in the Provincial Operations Centers (POCs). Prior to encoding, the accomplished questionnaires are manually edited for validity and consistency. The data files undergo validation using an editing program based on pre-set validation criteria such as consistency check, range check and acceptability and validity of data.

Sampling error estimates

Not applicable for crops and livestock and poultry backyard farms. Not computed for livestock and poultry commercial farms, and pesticides.

Data appraisal

Data review for farm prices is undertaken at the POCs every month and at the regional and national level every quarter. Since 2001, the review of farm prices had been included in the regional quarterly data reviews alongside with production statistics. Farm price data are reviewed against consistency with basket and trading matrix, consistency with trends, abrupt changes and trends/levels relative to wholesale and retail prices.

The Philippines has seen high levels of meat consumption in 2024, with pork leading the way at ***** kilograms per person. This underscores the nation's growing appetite for meat products, particularly pork and poultry. Poultry production and pricing Chicken remains a popular meat choice in the Philippines, with approximately **** billion chickens slaughtered for meat production in 2023. Central Luzon emerged as the top producer, followed by CALABARZON. Interestingly, native or improved chicken commanded the highest average farmgate price among poultry animals in 2023, which was significantly higher than broiler chicken. Meat imports and consumption patterns To meet the growing demand, the Philippines imported over a million metric tons of meat in 2023. Across the different meat types, pork registered the highest volume of meat imports in comparison to poultry. Imported pork meat significantly contributes to current supply, as domestic pork meat production has stagnated since 2021.

The Measurable AI GrabFood and GrabExpress Restaurant & Food Delivery Transaction datasets are leading sources of email receipts and transaction data, offering data collected directly from users via Proprietary Consumer Apps, with millions of opt-in users.

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Abstract

The viability of any agricultural endeavor is one of the main concerns of planners and policy makers in the agricultural and fishery sector. In support of this concern, goals and strategies are geared towards increasing productivity and profitability. Thus, there is a need for adequate and relevant marketing information which would include marketing structure, cost and margins, prices and other marketing-related information.

The Bureau of Agricultural Statistics (BAS) recognizes the need for such marketing information and has incorporated the generation of such in its data system. While data on prices has been regularly-generated, the other marketing information are collected periodically. These are limited to selected types of crop, livestock and fishery commodities.

The main objective of the study is to determine the marketing structure of milkfish. Specifically, it aims to: 1) Identify the key players in the milkfish industry, 2) Determine the components of marketing costs of milkfish by type of marketing participants, 3) Determine the marketing practices of milkfish operators and traders, 4) Determine the flow of commodities and channels of distribution; and 5) Compare marketing costs across trading centers.

Geographic coverage

Regional Coverage

Analysis unit

Individuals

Universe

All marketing costs of milkfish farm operators and traders.

Kind of data

Sample survey data [ssd]

Sampling procedure

The study covered four (4) major milkfish supply areas and five (5) demand areas. For supply areas, the provinces covered were Pangasinan, Bulacan, Capiz and Iloilo, while demand areas included Baguio City, Isabela, Pampanga, Aklan, and Metro Manila. Supply provinces were chosen based on their significant contribution to the total milkfish production in the country. On the average, these provinces accounted for 44% of the country's milkfish production during the last five (5) years. Demand provinces, however, were identified as the distribution and consumption areas of milkfish produced from the supply provinces. These provinces were identified during the interview phase in the supply areas.

The selection of sample milkfish farm operators and traders was guided by the following procedures:

a) Milkfish Farm Operators: From the identified milkfish farm operators taken from the Costs and Returns Survey (CRS), the research team purposively selected 20 sample farm operators who have undertaken pre-marketing activities prior to the marketing of milkfish. These pre-marketing activities include hauling, sorting, chilling, packing, etc. that were done by the operator before selling the commodity. Selection of the 20 sample farm operators was done either by equally distributing the samples among the sample producing barangays or by distributing the samples among the top producing barangays only.

However, if the sample respondents from the CRS have not identified milkfish farm operators who had undertaken pre-marketing activities, the 20 sample farm operators were chosen from the top two (2) producing barangays within the top two (2) producing municipalities identified by the traders in each province. Five (5) respondents were chosen in each barangay or a total of 20 respondents.

b) Traders: Adopting the snowball sampling techniques, the team interviewed traders identified by sample farm operators as buyers of milkfish. The traders interviewed were asked to whom and where they sell the milkfish they procured so that the interviewee has the information for the next traders to be interviewed or the destination of the commodity. This approach accumulates the data gathered from one trader respondent to other respondents at different levels of commodity marketing system.

A minimum of three (3) and maximum of five (5) respondents per type of marketing participants were interviewed per trading site.

For additional information relevant to the study, the research team also interviewed other key players knowledgeable to the marketing structure of milkfish. This is an addition to the information taken from the previous interview.

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

Data editing was done at various stages: a) Right after data collection to check the completeness and consistencies of entries; b) During data processing c) After the consolidation and generation of output tables

The data were processed manually by four (4) staff at the Central Office. The processors were tasked to edit and process all the entries on the questionnaires for the supply and demand areas assigned to them.

Each processor was provided with two separate tabulation worksheets, one for the operators and the other for traders. These tabulation worksheets were designed according to the contents of the questionnaires which include the profile or socio-economic characteristics of the respondents, the production and marketing practices in case of the operators, marketing practices of the traders and the components of marketing costs such as labor, transportation, supplies and materials and other operating expenses.

Frequency counts and percentages were determined for the profile and marketing procatices of the respondents. For marketing costs, average cost per kilogram for each item, per activity and per type of marketing participants were estimated for each supply and demand area.

After all the data were processed, these were consolidated and entered to the output tables in Microsoft Excel formats.

Since data processing was done manually without using any software, microdata are not available for public access.

Data appraisal

The data presented in the output tables were reviewed and compared across areas covered by the study. Data analysis and report preparation were done accordingly.

The Philippines has a steadily growing economy, with a gross domestic product (GDP) that reached over 461.62 billion U.S. dollars in 2024. Gross domestic product (GDP) denotes the aggregate value of all services and goods produced within a country in any given year. GDP is an important indicator of a country's economic power. The GDP of the Philippines is expected to increase substantially to over 757.67 billion U.S. dollars by 2030. The Philippines’ economy GDP of the Philippines has consistently grown at around six percent and is expected to remain constant through 2024. At the same time, the unemployment rate has fallen to about 2.5 percent in 2018, with an increasing amount of employment being within the services sector . Sectors of the economy The services sector is a significant economic sector in the Philippines economy, with a share of almost 60 percent in gross domestic product generation. Usually, a shift of GDP generation from agriculture to services is a sure sign of a growing economy - the same is true for the Philippines: Tourism and IT are industries within the services sector which has substantially contributed to the Philippines’ economic growth. The agriculture sector, although contributing to the Philippines’ export quantity, such as coconut oil and fruits, has declined over recent years, with more and more inhabitants moving to the cities to find work.

Jollibee was the leading limited-service restaurant in the Philippines in terms of sales value in 2023. In that year, the restaurant chain generated sales of approximately **** billion U.S. dollars. Its closest competitor, McDonald's, had total sales of about *** billion U.S. dollars that year. Bringing happiness in the Philippines and abroad  Known for its Jolly Spaghetti and Chickenjoy, Jollibee managed to maintain its position as the country’s largest fast-food chain brand, operating a network of 1,200 stores nationwide and close to a hundred locations abroad. Managed by the Jollibee Foods Corporation, the restaurant chain gradually expanded to various international locations in Southeast Asia, the Middle East, North America, and Europe. Two other limited-service restaurants owned by the Jollibee Foods Corporation made it to the list. The state of the country’s QSR industry As with other food service segments, the quick-service restaurant (QSR) industry in the Philippines recorded massive revenue losses in 2020. The decrease was attributed to the COVID-19 pandemic, which resulted in heightened social distancing measures, causing reluctance to visit restaurants among Filipinos. Limited dining capacity was also imposed to curb the infections, contributing to minimal revenue. The sales value of the QSR industry in the Philippines has shown improvement in 2023, even exceeding pre-pandemic sales.

In 2024, animal or vegetable fats and oils and their cleavage products, prepared edible fats, and animal or vegetable waxes were the leading agricultural commodity export from the Philippines. This type of commodity registered an export value of about **** billion U.S. dollars. This was followed by edible fruits and nuts.