Philippines Family Income: Total: One Person data was reported at 141,785,000.000 PHP th in 2015. This records an increase from the previous number of 110,113,000.000 PHP th for 2012. Philippines Family Income: Total: One Person data is updated yearly, averaging 125,949,000.000 PHP th from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 141,785,000.000 PHP th in 2015 and a record low of 110,113,000.000 PHP th in 2012. Philippines Family Income: Total: One Person data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H015: Family Income and Expenditure Survey: Total Annual Income and Expenditure: By Family Size and By Region.

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

Average Family Income: Philippines: One Person data was reported at 128,000.000 PHP in 2015. This records an increase from the previous number of 111,000.000 PHP for 2012. Average Family Income: Philippines: One Person data is updated yearly, averaging 119,500.000 PHP from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 128,000.000 PHP in 2015 and a record low of 111,000.000 PHP in 2012. Average Family Income: Philippines: One Person 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.

Abstract

The 2003 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

National coverage

Analysis unit

Household Consumption expenditure item Income by source

Universe

The 2003 FIES has as its target population, all households and members of households nationwide. A household is defined as an aggregate of persons, generally but not necessarily bound by ties of kinship, who live together under the same roof and eat together or share in common the household food. Household membership comprises the head of the household, relatives living with him such as his/her spouse, children, parent, brother/sister, son-in-law/daughter-in-law, grandson/granddaughter and other relatives. Household membership likewise includes boarders, domestic helpers and non-relatives. A person who lives alone is considered a separate household.

Institutional population is not within the scope of the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2003 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. Below are the 17 administrative regions of the country:

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

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 self-representing (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 2003 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 2003 and January 2004 round of the LFS.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

The 2003 FIES questionnaire contains about 800 data items and a summary for comparing income and expenditures. The questionnaires were subjected to a rigorous manual and machine edit checks for completeness, arithmetic accuracy, range validity and internal consistency.

The major steps in the machine processing are as follows: 1. Data Entry 2. Completeness Check 3. Matching of visit records 4. Consistency and Macro Edit (Big Edit) 5. Generation of the Public Use File 6. Tabulation

Steps 1 to 2 were done right after each visit. The remaining steps were carried out only after the second visit had been completed.

Steps 1 to 4 were done at the Regional Office while Steps 5 and 6 were completed in the Central Office.

After completing Steps 1 to 4, data files were transmitted to the Central Office where a summary file was generated. The summary file was used to produce the consistency tables as well as the preliminary and textual tables.

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

The FAME (FIES computer-Aided Consistency and Macro Editing), an interactive Windows-based application system was used in data processing. This system was used starting with the 2000 FIES round. The interactive module of FAME enabled the following activities to be done simultaneously. a) Matching of visit records b) Consistency and macro edit (big edit) c) Range check

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

Note: For data entry, CSPro Version 2.6 was used.

Response rate

The response rate for this survey is 95.7%. 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 2003 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.

Data appraisal

Refer to the

Philippines Family Expenditure: Total: One Person data was reported at 110,769,000.000 PHP th in 2015. This records an increase from the previous number of 89,307,000.000 PHP th for 2012. Philippines Family Expenditure: Total: One Person data is updated yearly, averaging 100,038,000.000 PHP th from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 110,769,000.000 PHP th in 2015 and a record low of 89,307,000.000 PHP th in 2012. Philippines Family Expenditure: Total: One Person data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H015: Family Income and Expenditure Survey: Total Annual Income and Expenditure: By Family Size and By Region.

Abstract

The 2009 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 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. Below are the 17 administrative regions of the country:

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

Analysis unit

The unit of analysis was the Household

Universe

The 2009 FIES has as its target population, all households and members of households nationwide. A household is defined as an aggregate of persons, generally but not necessarily bound by ties of kinship, who live together under the same roof and eat together or share in common the household food. Household membership comprises the head of the household, relatives living with him such as his/her spouse, children, parent, brother/sister, son-in-law/daughter-in-law, grandson/granddaughter and other relatives. Household membership likewise includes boarders, domestic helpers and non-relatives. A person who lives alone is considered a separate household.

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. Below are the 17 administrative regions of the country:

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

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 self-representing (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.

Mode of data collection

Face-to-face [f2f]

Research instrument

Refer to the attached 2009 FIES questionnaire in pdf file (External Resources)

Avg Family Exp: Philippines: One Person data was reported at 100,000.000 PHP in 2015. This records an increase from the previous number of 90,000.000 PHP for 2012. Avg Family Exp: Philippines: One Person data is updated yearly, averaging 95,000.000 PHP from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 100,000.000 PHP in 2015 and a record low of 90,000.000 PHP in 2012. Avg Family Exp: Philippines: One Person data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H022: Family Income and Expenditure Survey: Average Annual Expenditure: By Family Size and Income Group.

Abstract

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

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

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

Geographic coverage

National Coverage.

Analysis unit

Households

Universe

The survey covered farm households with farming/fishing operations.

Kind of data

Sample survey data [ssd]

Sampling procedure

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

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

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

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

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

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

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

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

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

Sampling deviation

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

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

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

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

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

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

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

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

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

Response rate

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

Type of patient, treatment phase during interview, and collected information.

In 2024, the real gross domestic product (GDP) in Vietnam grew by approximately **** percent, marking the highest growth rate in Southeast Asia. In comparison, Myanmar's real GDP growth rate dropped by **** percent. Southeast Asia, a tapestry of economic and cultural complexity Historically a critical component of global trade, Southeast Asia is a diverse region with heterogeneous economies. The region comprises ** countries in total. While Singapore is a highly developed country economy and Brunei has a relatively high GDP per capita, the rest of the Southeast Asian countries are characterized by lower GDPs per capita and have yet to overcome the middle-income trap. Malaysia is one of these countries, having reached the middle-income level for many decades but yet to grow incomes proportionally to its economic development. Nevertheless, Southeast Asia’s young population will further drive economic growth across the region’s markets. ASEAN’s economic significance Aiming to promote economic growth, social progress, cultural development, and regional stability, all Southeast Asian countries except for Timor-Leste are part of the political and economic union Association of Southeast Asian Nations (ASEAN). Even though many concerns surround the union, ASEAN has avoided trade conflicts and is one of the largest and most dynamic trade zones globally. Factors such as the growing young population, high GDP growth, a largely positive trade balance, and exemplary regional integration hold great potential for future economic development in Southeast Asia.

Abstract

The LFS aims to provide a quantitative framework for the preparation of plans and formulation of policies affecting the labor market. Specifically, the survey is designed to provide statistics on levels and trends of employment, unemployment and underemployment for the country as a whole, and for each of the administrative regions, including provinces and key cities.

Importance of LFS a. It provides a quantitative framework for the preparation of plans and formulation of policies affecting the labor market towards 1) creation and generation of gainful employment and livelihood opportunities 2) reduction of unemployment and promotion of employment 3) improvement of working conditions 4) enhancement of the welfare of a working man b. It provides statistics on levels and trends of employment and unemployment and underemployment for the country and regions; c. It is used for the projection of future manpower, which when compared with the future manpower requirements, will help identify employment and training needs; d. It helps in the assessment of the potential manpower available for economic development; and e. It identifies the differences in employment, unemployment, and underemployment according to the different economic, social and ethnic groups existing within the population.

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 II - Cagayan Valley Region III - Central Luzon Region IV-A - Calabarzon Region IV-B - Mimaropa Region V - Bicol Region VI - Western Visayas Region VII - Central Visayas Region VIII - Eastern Visayas Region IX - Zamboanga Peninsula Region X - Northern Mindanao Region XI - Davao Region XII - Soccsksargen Region XIII - Caraga Autonomous Region in Muslim Mindanao (ARMM)

Analysis unit

The unit of analysis is the Individual (Household survey).

Universe

The LFS has as its target population, all households and members of households nationwide. A household is defined as an aggregate of persons, generally but not necessarily bound by ties of kinship, who live together under the same roof and eat together or share in common the household food. Household membership comprises the head of the household, relatives living with him such as his or her spouse, children, parent, brother or sister, son-in-law or daughter-in-law, grandson or granddaughter, and other relatives. Household membership likewise includes boarders, domestic helpers and non-relatives. A person who lives alone is considered a separate household.

Since the reporting unit is the household, the statistics emanating from this survey will refer to the characteristics of the population residing in private households. Persons who reside in the institutions are not within the scope of the survey. Also excluded in the target population are households in the least accessible barangays (LABs). A barangay is classified as LAB if: (a) it requires more than eight hours walk from the last vehicle station; and/or, (b) the frequency of transportation is less than three times a week and the cost of a one-way trip is more than five hundred pesos. A total of 350 barangays were classified as LABs. This number accounts for only 0.83 percent of the total number of barangays in the country. The total number of households in these areas account for only 0.38 percent of the total number of households surveyed.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling design of the LFS uses the sampling design of the 2003 Master Sample (MS) for Household Survey that started July 2003.

Sampling Frame As in previous household surveys, the 2003 MS used an area sample design. 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.

With the conduct of the 2003 Listing of Households, the number of households of the selected sampled EA from the CPH EA lists were updated and the sample sizes that were initially generated where subsequently adjusted.

Stratification Scheme Prior to sample selection, the PSUs in each domain were stratified as follows: a) Proportion of strong houses (PSTRONG) - PSTRONG is defined to be the percentage of housing units occupied by households 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, glass. b) A variable labeled AGRI - An initial variable is an indicator variable computed at the barangay level. That variable has the value 1 if more than 50 percent of the households in the barangay are 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 1 value of AGRI at the PSU level lies between 0 and 1. c) Per capita income (PER CAPITA) - 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 municipal income used was the 2000 municipal income sourced from the De4partment of Finance. 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 median income of the municipal class of the municipality was used.

Sample Selection

The sample design is an epsem in each region (Equal Probability Selection for each Member). Given the overall sample, the number of PSUs, EAs and Housing Units (HUs) were determined so that the epsem property within region was preserved.

The PSUs were selected with probability proportional to some estimated measure of size (PPES). Since PSUs vary considerably in size, PSUs were identified as certainty and non-certainty PSUs. Each PSU which was selected with certainty (selection probability is greater than 1) was treated as a separate stratum. In each certainty selection, sample EAs were selected with PPES in each sampled PSU; and housing units (HU) were selected with equal probability in each sampled EA.

A housing unit is 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. It may contain more than one household. In the 2000 CPH, about two percent of the total household population consist of two or more households.

For non-certainty selection, PSUs were sampled from a set of strata defined for each domain. In each domain, these PSUs were grouped into strata by province, Highy Urbanized Cities (HUC) or Independent Component Cities (ICCs). To further improve on the precision of the estimates, PSUs within province/HU/ICC stratum were further stratified with respect to some socio-economic variables that were associated with poverty.

Within each selected PSUs, EAs were selected with probability proportional to size and households with equal probability within selected EAs.

In each HU, all households were selected. However, for operational considerations, only 3 households will be selected with equal probability in HU consisting of more than 3 households.

Sample Size

The 2003 Master Sample consist of a sample of 2,835 PSUs of which 330 were certainty PSUs and 2,505 were non certainty PSUs. The number of households for the 2000 CPH was used as measure of size. The entire MS was divided into four sub-sample 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.

For the purpose of the master sample, the sample EAs selected with certainty were classified as sub-sample of replicate 0, and all the non-certainty PSUs were classified in any of the sub-samples 1, 2, 3 and 4.

Sampling deviation

Replacement of sample households is allowed only if the respondent to LFS cannot be contracted after 3 callbacks. If the sample household moved out from the sample barangay and can no longer be located then the replacement should be the household currently residing in the housing unit previously occupied by the original sample. If no household currently residing in the aforementioned housing unit then a replacement may be selected from among the neighbors who has the closest socio-economic and demographic characteristics as the original sample household. Household members who are identified as eligible respondents but cannot be interviewed should never be replaced.

Mode of data collection

Face-to-face [f2f]

Research instrument

• ISH FORM 2 is a four-page, forty five-column questionnaire that is being used in the quarterly rounds of the Laor Force Survey nationwide. This questionnaire gathers data on the demographic and economic characteristics of the population.
• On the first page of the questionnaire, the particulars about the geographic location, design codes and household auxiliary information of the sample

Estimated mean total costs incurred by TB-affected households, assessed by output approach in US$.

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