This file contains the geographic items from Summary Tape File 1, as well as total population, provisional population counts by race and Spanish origin, the number of families, and the number of persons in group quarters.Also included are the number of one-person households, the total number of housing units, the number of occupied housing units, and the number of owner-occupied housing units.MARF provides summaries and codes for States or State equivalents, counties of county e quivalents, minor civil divisions (MCDs) or census county divisions (CCDs), places or place segments within MCDs/CCDs, remainder of MCD/CCD, census tracts or block numbering areas (BNAs), and block groups (BGs) or, for areas that are not block-numbered, enumeration districts (EDs).

"MARF 2 contains the numeric codes and names for census geographic areas plus 100 percent and sample data for selected population and housing items. The file provides 100 percent counts for the total population, five race groups (White, Black, American Indian, Eskimo, and Aleut; Asian and Pacific Islander; and other races), persons of Spanish origin, families, persons in group quarters, one-person households, and total, occupied, and owner-occupied housing units."

In addition, total pop ulation and housing unit estimates and per capita income based on 1980 census sample returns are included. Latitude and longitude coordinates are given for the approximate population centroid of each geographic area down to the level of block group (BG) and enumeration district (ED). Land area in square miles is provided for geographic areas down to the level of places and minor civil divisions (MCDs), with a population of 2,500 or more.

MARF 2 provides summaries and codes for States or State equivalent, counties of county equivalents, minor civil divisions (MCDs) or census county divisions (CCDs), places or place segments within MCDs/CCDs, remainder of MCD/CCD, census tracts or block numbering areas (BNAs), and block groups (BGs) or, for areas that are not block-numbered, enumeration districts (EDs).

Abstract

The main aim for the establishment census 2012 is to enumerate all of the economic establishments operating in Palestine in 2012, except for those establishments engaged in farming activities, and building a new updated a classified establishment register according to the geographical distribution, main economic activity according to international recommendations.

The goals for the Establishment Census could be summarized as follows: 1. Distribution of establishments by various economic activities. 2. Distribution of establishments by the Palestinian governorates. 3. The size of employment in various economic activities and its distribution by sex. 4. Distribution establishments in terms of economic organization, legal status, ownership and operation status. 5. The value of capital invested in establishments. 6. Distribution establishments in terms of registration status with the official authorities. 7. The rate of growth in the number of economic establishments.

Geographic coverage

The Establishment Census 2012 includes all of the establishments in Palestine, whether those of the government or international organizations and institutions, non-profit, and establishments engaged in economic activities in the markets or in factories and companies, or those that exercise an economic activity in houses and have the definition of an establishment, with the exception of those establishments engaged in the agriculture, forestry, fishing and animal husbandry

Analysis unit

Establishment

Universe

The establishment considered the statistical unit that the data collection was upon, which is an institution or part of it, which is located in one place and specializes mainly in one major activity (non Assistant) which will bring most of the added value, classified within the same activity (with probability of production of secondary activities) and for which data are available, allowing for calculating of operating surplus account, which provides data for both: workers, and expenses, production and revenue, and fixed assets. An establishment must provide the following requirements: 1.Participation in an economic activity, any establishment should provide good or service to the market. 2.The presence in a fixed place. 3.A holder of an establishment, whether an individual or a legal entity. 4.The presence of a single management of the establishment

Kind of data

Census/enumeration data [cen]

Sampling procedure

comprehensive census of all economic establishment in palestine

Mode of data collection

Face-to-face [f2f]

Research instrument

The establishment Census form consisted of two sections:

Part one: Identification data, which included basic information about the establishments, governorate, Locality, number of enumeration area, Building No. in the enumeration area, serial number of establishment in the enumeration area, establishment commercial name, name of holder or director, sex of the holder or director, phone number, location and description, including the name of the neighborhood and the street and the name of the building or the owner of the building, and the working status of the establishment.

Part two: data on operating establishments only, which include: (Description of the main economic activity, Ownership, Economic organization, Legal status, Establishment Year, Number of employees, Preparing of accounting records, Licensing and registration, No. workers, present value of capital, owner Identity No. or director of the of establishment).

Special form for Jerusalem Governorate area (J1) Due to the special situation in the Jerusalem governorate, specially J1 area (those parts of Jerusalem which were annexed by Israel in 1967) a short form for census questionnaire has been designed, which include the following questions: (Identification data for the establishment, working status, main economic activity, ownership of establishment, economic organization, establishment year, the number of employees in the establishment (paid, unpaid)).

Cleaning operations

The data processing stage includes editing, coding, data entry, reviewing lists and checking all previous operations of data entry for all enumeration areas. All procedures and instructions were conducted to check the consistency of the data and coding fields and ensure the entry of all enumeration areas and booklets and questionnaires, with their content of establishment data. As booklets and questionnaires required checking and moving from one operation site to another, a store was prepared for all the documents to be indexed and categorized and the store keeper controlled the flow of documents.

Coding manuals were prepared and examined beforehand, as well as the instructions for editing and coding procedures to check the consistency of the data and how to detect and correct errors. All editing and coding employees were selected from among the best fieldworkers who collected the data from establishments owners or manager. Training was conducted centrally to ensure uniform concepts and to eliminate disparities in fieldwork in all governorates. Editing, coding and testing the consistency of 100% of the questionnaires was conducted, in addition to desk reviewing, editing and coding (100%) in order to eliminate differences between individual editors and to discover and correct errors and circulate them daily.

Tests were held for all applicants for data entry and those who performed best were trained centrally in a uniform procedure of data entry. During the first three days, all date entered were deleted and re-entered again to correct errors and inform employees so as to avoid such errors in the future. Certain procedures were adopted to ensure correct data entry: in the first stage a unique separate file was prepared for each enumeration area that included identification data (to ensure coverage), the number of establishments and the total number of booklets to ensure that all booklets and all households had been entered. Upon data entry, a thorough examination of the identification data and the range of each digital key question was conducted so that the computer did not accept any figure outside this range. For example, the operation status, sex and all the pre-coded questions in the establishment questionnaire, and the type of building in the buildings questionnaire. The remaining questions were exposed to a comprehensive re-examination of the range of each question after data entry and the extraction of error lists resulting from data inconsistency.

After data entry, certain lists were extracted to ensure the coverage of all enumeration areas, and establishments, and to examine the internal consistency of the data of each unit. The procedures used were to extract error lists that must be corrected or questioned These lists were submitted to the best reviewers under full supervision of the technical operations in the census directorate.

Specific programs previously prepared were used to detect errors according to the following procedures: 1. An instruction manual was prepared for desk editing and procedures for the establishments' questionnaire. A set of desk editing instructions were printed and the procedures for the questionnaire containing tests designed to ensure the coverage of data entry, to detect inconsistencies or to detect abnormal and rare cases. These were reviewed and printed with a name and number given to every error in the manual. 2. A list was extracted for each enumeration area, including the identification data of each establishment message (type of check) and the number printed in the manual. The auditor could then recognize the message name and type of error, location and procedures of editing and audit procedures patch, which consists of several checks on several stages. 3. Lists were submitted to the reviewers to return to the original booklets. If the error was caused by data entry, it would be corrected on the list. If the error was due to fieldwork, all associated questions should be considered for correction. For example, if the operation status of the establishment was closed, it must be no answers on the questions after it. The first check would be conducted through manual editing, then extracting the electronic lists after data entry for such types of tests, then they would be corrected manually on the original booklets and data re-entered correctly. As for the coverage test, there is a key reference that contains all enumeration areas and shows the number of booklets and establishments in the enumeration area to be entered on the computer. At this point, if there was a variation between the number of booklets and establishments actually entered and the total number of establishments in the file of each area, an error message appears to request correction. Through this method, we ensured that 100% of the establishments were entered.

All lists for the enumeration areas were extracted in this way and all kinds of tests. 1. Amended lists were sent back to data entry to be entered and corrected and a copy of the daily entered data was kept in several different places. 2. Previous stages were conducted twice or more until the data of each enumeration area became clean. 3. All files were compiled for enumeration areas for each locality and governorate. Then, all tables and any additional tests were conducted to test the data before the final tabulation in order to correct errors according to the aforementioned procedures.

Sampling error estimates

-

Data appraisal

There are two types of error that can occur: statistical errors and

This data collection contains the MEDList file, the geographic reference file for the 1970 Census containing records for states, counties, minor civil divisions (MCD) or census county divisions (CCD)s, place segments, enumeration districts, and block groups. Items include state code, county code, MCD/CCD code, place code, place type, standard consolidated area code, standard metropolitan statistical area (SMSA) code, urbanized area code, tracted area code, state economic area code, economic subregion code, central business district code, area name, tract code, block group code, enumeration district code, urban/rural classification, ward code, congressional district code, housing count, and population count.

Abstract

The 2012 Family Income and Expenditure Survey (FIES) is a nationwide survey of households undertaken every three years by the National Statistics Office (NSO). It is the main source of data on family income and expenditure, which include among others, levels of consumption by item of expenditure as well as sources of income in cash and in kind.

The 2012 FIES enumeration was conducted twice – the first visit was done in July 2012 with the first semester January to June as the reference period; the second visit was made in January 2013 with the second semester of 2012, that is, July to December 2012 as reference period. The same set of questions is asked for both visits.

The number of families for the 2012 and 2009 FIES was estimated using the household population estimate, derived by applying the growth rate (PGR) based on the household population counts from the 2000 and 2010 Census of Population and Housing (CPH).

The set of samples selected for the 2012 FIES is only one of the possible sets of samples of equal size that have been selected from the same population using the same sampling design. Estimates derived from each of these sets of samples would differ from one another. Sampling error is a measure of the variability of the estimates among all possible sets of samples. It is usually measures in terms of the standard errors for a particular statistic.

The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of the same size and design.

Geographic coverage

The 2012 FIES is a sample survey designed to provide income and expenditure data that are representative of the country and its 17 regions

Analysis unit

Household and Household member (Individual)

Universe

The 2012 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 FIES used the sampling design of the 2003 Master Sample (MS) for household surveys starting in July 2003.

The 2003 MS considers the country's 17 administrative regions as defined in Executive Orders (EO) 36 and 131 as its sampling domain. A domain is referred to as a subgroups of the population 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 that goes along with it.

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.

To have some control over the subsample 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.

For the updating of the MS in 2012 (using the 2010 Census results), this concern should again be looked into. Meantime, the use of small area estimation can be tapped seriously to answer this data need.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2006 FIES is basically the same as the 2003 FIES in terms of approach in the interview, thus using separate questionnaire for each visit with the same set of questions. Data items specifically, school service (both land and water) and food supplements were added in the questionnaire.

This file 3 contains the geographic items from Summary Tape File 1A (STF1A) and Summary Tape File 3A (STF 3A), as well as total population and housing unit counts. The MARF 4 file contains geographic items from Summary Tape File 1b (STF 1B), as well as total population and housing unit counts.The geographic levels on MARF 3 are sequenced hierarchically as follows: States (including the District of Columbia), counties or county equivalents, minor civil divisions (MCDs) or census county divisions (CCDs), places or place segments within MCDs/CCDs, remainder of MCD/CCD, census tracts or block numbering areas (BNAs), and block groups (BGs) or, for areas that are not block-numbered, enumeration districts (EDs). The geographic levels on MARF 4 are sequenced hierarchically as follows: States (including the District of Columbia), standard metropolitan statistical areas (SMSAs), nonSMSA remainder of State, counties or county equivalents, minor civil divisions (MCDs) within counties (available for 20 specified States), places within MCDs within counties (20 specified states) or places within counties (remaining 31 States), census tracts or block numbering areas (BNAs), and blocks or, for nonblock numbered areas, enumeration districts (EDs). Data for SMSAs which cross State lines are shown only for that portion in the particular State file. Summaries are also provided for partially block- numbered portions of all geographic levels.

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

Abstract

The 2006 Family Income and Expenditure Survey (FIES) had the following primary objectives:

1) to gather data on family income and family expenditure and related information affecting income and expenditure levels and patterns in the Philippines; 2) to determine the sources of income and income distribution, levels of living and spending patterns, and the degree of inequality among families; 3) to provide benchmark information to update weights for the estimation of consumer price index; and 4) to provide information for the estimation of the country's poverty threshold and incidence.

Geographic coverage

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

Analysis unit

The unit of analysis is the family. A family consists of the household head, spouse, unmarried children, ever-married children, son-in-law/daughter-in-law, parents of the head/spouse and other relatives who are members of the household.

In households where there are two or more persons not related to each other by blood, marriage or adoption, only the income and expenditure of the member who is considered as the household head is included.

Institutional population is not within the scope of the survey.

Universe

All households and members of households nationwide

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2003 Master Sample (MS) considers the country's 17 administrative regions as defined in Executive Orders (EO) 36 and 131 as the sampling domains. A domain is referred to as a subdivision of the country for which estimates with adequate level of precision are generated. It must be noted that while there is demand for data at the provincial level (and to some extent municipal and barangay levels), the provinces were not treated as sampling domains because there are more than 80 provinces which would entail a large resource requirement.

As in most household surveys, the 2003 MS made use of an area sample design. For this purpose, the Enumeration Area Reference File (EARF) of the 2000 Census of Population and Housing (CPH) was utilized as sampling frame. The EARF contains the number of households by enumeration area (EA) in each barangay.

This frame was used to form the primary sampling units (PSUs). With consideration of the period for which the 2003 MS will be in use, the PSUs were formed/defined as a barangay or a combination of barangays with at least 500 households.

The 2003 MS considers the 17 regions of the country as the primary strata. Within each region, further stratification was performed using geographic groupings such as provinces, highly urbanized cities (HUCs), and independent component cities (ICCs). Within each of these substrata formed within regions, the PSUs were further stratified, to the extent possible, using the proportion of strong houses (PSTRONG), indicator of engagement in agriculture of the area (AGRI), and a measure of per capita income (PERCAPITA) as stratification factors.

The 2003 MS consists of a sample of 2,835 PSUs. The entire MS was divided into four sub-samples or independent replicates, such as a quarter sample contains one fourth of the total PSUs; a half sample contains one-half of the four sub-samples or equivalent to all PSUs in two replicates. The final number of sample PSUs for each domain was determined by first classifying PSUs as either selfrepresenting (SR) or non-self-representing (NSR). In addition, to facilitate the selection of sub-samples, the total number of NSR PSUs in each region was adjusted to make it a multiple of 4. SR PSUs refers to a very large PSU in the region/domain with a selection probability of approximately 1 or higher and is outright included in the MS; it is properly treated as a stratum; also known as certainty PSU. NSR PSUs refers to a regular too small sized PSU in a region/domain; also known as non certainty PSU. The 2003 MS consists of 330 certainty PSUs and 2,505 non-certainty PSUs. To have some control over the sub-sample size, the PSUs were selected with probability proportional to some estimated measure of size. The size measure refers to the total number of households from the 2000 CPH. Because of the wide variation in PSU sizes, PSUs with selection probabilities greater than 1 were identified and were included in the sample as certainty selections.

At the second stage, enumeration areas (EAs) were selected within sampled PSUs, and at the third stage, housing units were selected within sampled EAs. Generally, all households in sampled housing units were enumerated, except for few cases when the number of households in a housing unit exceeds three. In which case, a sample of three households in a sampled housing unit was selected at random with equal probability.

An EA is defined as an area with discernable boundaries within barangays consisting of about 150 contiguous households. These EAs were identified during the 2000 CPH. A housing unit, on the other hand, is a structurally separate and independent place of abode which, by the way it has been constructed, converted, or arranged, is intended for habitation by a household.

The 2006 FIES involved the interview of a national sample of about 51,000 sample households deemed sufficient to gather data on family income and family expenditure and related information affecting income and expenditure levels and patterns in the Philippines at the national and regional level. The sample households covered in the survey were the same households interviewed in the July 2006 and January 2007 round of the LFS.

Sampling deviation

The estimates from the 2006 FIES include results of the first FIES visit for the NCR based on questionnaires recovered from fire. The fire that hit the NCR’s Statistics Office on October 3, 2006 damaged 58 percent of the total questionnaires for the FIES first visit. Questionnaires that were encoded and processed cover around 42 percent of these questionnaires. In the preliminary results, values for the burned questionnaires were imputed using a ratio which requires data from the recovered questionnaires and data from corresponding questionnaires from the second visit. The ratio was computed by getting the sums of the total income and total expenditure in the recovered questionnaires from the first visit and the sums of the same data from corresponding second visit questionnaires and then by dividing the sums from the second visit by the sums from the first visit. The annual estimates on income and expenditure for NCR were computed by dividing the second visit values by the computed ratio. For the final results, the annual estimates for the NCR were computed by multiplying by 2 the second visit data. This imputation procedure was opted after it has been established that there was no significant difference between using the ratio and the multiplier ‘2’.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2006 FIES adopts a questionnaire design wherein separate questionnaire with the same sets of questions for both visits will be used. The sample household is interviewed in two separate operations each time using the half-year period preceding the interview as reference period. This scheme envisions to improve the quality of data gathered since it minimizes memory bias of respondents and at the same time captures the seasonality of income and expenditure patterns. The use of separate questionnaire with the same set of questions for both visits was used starting 2003 FIES. In previous FIES, the same set of questions for each semester (two enumeration periods) were contained in one questionnaire.

To further reduce memory bias, the concept of "average week" consumption for all food items shall be utilized for the 2006 FIES. Moreover, the reference period for Fuel, Light and Water, Transportation and Communication, Household Operations and Personal Care and Effects is limited to the past month and in some specified cases, the concept of average month consumption shall be used. For all other expenditure groups, the past six months shall be used as reference period.

The questionnaire has four main parts consisting of the following:

Part I. Identification and Other Information (page 1-3) (Geographic Identification, Other Information and Particulars about the Family)

Part II. Expenditures (page 4-45) Section A. Food, Alcoholic Beverages and Tobacco Section B. Fuel, Light and Water, Transportation and Communication, and Household Operations Section C. Personal Care and Effects, Clothing Footwear and Other Wear Section D. Education, Recreation, and Medical Care Section E. Furnishings and Equipment Section F. Taxes Section G. Housing, House Maintenance and Minor Repairs Section H. Miscellaneous Expenditures Section I. Other Disbursements

Part III. Income (page 46-55) Section A. Salaries and Wages from Employment Section B. Net Share of Crops, Fruits and Vegetables Produced and/or Livestock and Poultry Raised by Other Households Section C. Other Sources of Income Section D. Other Receipts Section

Abstract

The Labor Force Survey (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.

Geographic coverage

National

Analysis unit

Individuals

Universe

Individuals 15 years and over.

Kind of data

Sample survey data [ssd]

Sampling procedure

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

Sampling Frame

As in most 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. 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.

Stratification Scheme

Startification involves the division of the entire population into non-overlapping subgroups called starta. Prior to sample selection, the PSUs in each domain were stratified as follows: 1) All large PSUs were treated as separate strata and were referred to as certainty selections (self-representing PSUs). A PSU was considered large if it has a large probability of selection. 2) All other PSUs were then stratified by province, highly urbanized city (HUC) and independent component city (ICC). 3) Within each province/HUC/ICC, the PSUs were further stratified or grouped with respect to some socio-economic variables that were related to poverty incidence. These variables were: (a) the proportion of strongly built houses (PSTRONG); (b) an indication of the proportion of households engaged in agriculture (AGRI); and (c) the per-capita income (PERCAPITA).

Sample Selection

To have some control over the subsample 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 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

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-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. Thus, the survey covers a nationwide sample of about 51,000 households deemed sufficient to measure the levels of employment and unemployment at the national and regional levels.

Strategy for non-response

Replacement of sample households within the sample housing units is allowed only if the listed sample households had moved out of the housing unit. Replacement should be the household currently residing in the sample housing unit previously occupied by the original sample.

Sampling deviation

Starting the July 2003 round of the Labor Force Survey, the generation of the labor force and employment statistics adopted the 2003 Master Sample Design. - Using this new master sample design, the number of samples increased from 41,000 to around 51,000 sample households.

• The province of Basilan is grouped under Autonomous Region in Muslim Mindanao while Isabela City (Basilan) is now grouped under Region IX. This is to adopt the regional grouping under Executive Order No.36.
• The 1992 four-digit code for Philippine Standard Occupational Classification (PSOC) and 1994 Philippine Standard Industry Classification (PSIC) were used in classifying the occupation and industry.

Mode of data collection

Face-to-face [f2f]

Abstract

The Labor Force Survey (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.

Geographic coverage

National

Analysis unit

Individuals

Universe

Individuals 15 years and over.

Kind of data

Sample survey data [ssd]

Sampling procedure

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

Sampling Frame

As in most 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. 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.

Stratification Scheme

Startification involves the division of the entire population into non-overlapping subgroups called starta. Prior to sample selection, the PSUs in each domain were stratified as follows: 1) All large PSUs were treated as separate strata and were referred to as certainty selections (self-representing PSUs). A PSU was considered large if it has a large probability of selection. 2) All other PSUs were then stratified by province, highly urbanized city (HUC) and independent component city (ICC). 3) Within each province/HUC/ICC, the PSUs were further stratified or grouped with respect to some socio-economic variables that were related to poverty incidence. These variables were: (a) the proportion of strongly built houses (PSTRONG); (b) an indication of the proportion of households engaged in agriculture (AGRI); and (c) the per-capita income (PERCAPITA).

Sample Selection

To have some control over the subsample 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 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

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-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. Thus, the survey covers a nationwide sample of about 51,000 households deemed sufficient to measure the levels of employment and unemployment at the national and regional levels.

Strategy for non-response

Replacement of sample households within the sample housing units is allowed only if the listed sample households had moved out of the housing unit. Replacement should be the household currently residing in the sample housing unit previously occupied by the original sample.

Sampling deviation

Starting the July 2003 round of the Labor Force Survey, the generation of the labor force and employment statistics adopted the 2003 Master Sample Design. - Using this new master sample design, the number of samples increased from 41,000 to around 51,000 sample households.

• The province of Basilan is grouped under Autonomous Region in Muslim Mindanao while Isabela City (Basilan) is now grouped under Region IX. This is to adopt the regional grouping under Executive Order No.36.
• The 1992 four-digit code for Philippine Standard Occupational Classification (PSOC) and 1994 Philippine Standard Industry Classification (PSIC) were used in classifying the occupation and industry.

Mode of data collection

Face-to-face [f2f]