Filipino families earned 206 thousand pesos yearly, on the average, according to the 2009 Family Income and Expenditure Survey (FIES). Families in the bottom 30 percent income group, which may be considered as poor families, had much smaller yearly earnings at an average of 62 thousand pesos. In comparison, families in the upper 70 percent income group earned an average of 268 thousand pesos a year. On a monthly basis, the reported average income of the families in the bottom 30 percent income group was 5,200 pesos in 2009 while it was 22,300 pesos in the upper 70 percent income group (Table 2c).
The 2009 FIES also reveals that poor families spent 64 thousand pesos annually, on the average, which is two thousand pesos more than their average annual income. In contrast, families in the upper 70 percent income group spent 224 thousand pesos a year, on the average, hence, could generate savings of 44 thousand pesos in a year, on the average (Table 2c).
Adjusting for the inflation between 2006 and 2009, at 2000 prices, the average annual family income in 2009 would be valued at P129 thousand. The average annual family expenditure in 2009 would be valued at P110 thousand at 2000 prices (Table 2d).
The annual income of families in the bottom 30 percent income group increased, from an average of 49 thousand pesos in 2006 to 62 thousand pesos in 2009. Annual income of non-poor families, on the other hand, increased from an average of 226 thousand pesos in 2006 to 268 thousand pesos in 2009. The income gap between families in the bottom 30 percent income group and families in the upper 70 percent income group barely changed. The average annual income of families in the upper 70 percent income group was four times that of the families in the bottom 30 percent income group.
Across regions, families in National Capital Region had the highest average annual family income at 356 thousand pesos. Families in Autonomous Region in Muslim Mindanao (ARMM) had the lowest average annual family income at 113 thousand pesos (Table 4a).
The Gini coefficient of the income of families in the Philippines was estimated at 0.4484 in 2009 (Table 5). Among regions, Eastern Visayas registered the highest Gini coefficient at 0.4841. The Gini coefficient is a measure of income inequality within a population which ranges from 0 to 1, with 0 indicating perfect income equality among families, and 1 indicating absolute income inequality.
In 2009, about 42.6 percent of the expenditures of an average Filipino family were on food. For families in the bottom 30 percent income group, the percentage was much higher at 60 percent, while for families in the upper 70 percent income group, it was 40.5 percent (Table 7).
| (Sgd.) CARMELITA N. ERICTA Administrator |
TECHNICAL NOTES
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The 2009 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 results of FIES provide information on the levels of living and disparities in income of Filipino families, as well as their spending patterns.
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The 2009 FIES is a sample survey designed to provide income and expenditure data that are representative of the country and its 17 regions. It used four replicates of the 2003 Master Sample (MS) created for household surveys on the basis of the 2000 Census of Population and Housing. The 2003 MS has been designed to produce the sample size needed for large surveys, like the FIES. To facilitate subsampling, the 2003 MS has been designed to readily produce four replicate samples from the full set of sampled PSUs.
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In the 2003 MS, a stratified, three-stage sampling design was employed: the selection of Primary Sampling Units (PSUs) for the first stage, sample enumeration areas (EAs) for the second stage, and sampling units for the third stage. The domains are the regions which were stratified by province, highly urbanized city (HUC), independent component city (ICC), and other factors within the geographical strata. The overall sampling fractions vary across regions to generate adequate sample size for each region. Survey weights are used in order to produce valid estimates of the population parameter. Base weights are computed to compensate for the unequal selection probabilities in the sample design. These were adjusted to account for unit nonresponse and to conform to known population distributions (eg. projected population counts).
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The 2009 FIES enumeration was conducted twice - the first visit was done in July 2009 with the first semester January to June as the reference period; the second visit was made in January 2010 with the second semester of 2009, that is, July to December 2009 as reference period. The same set of questions is asked for both visits.
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The number of households/families for the 2009 FIES was estimated using the 2000 Census of Population and Housing (CPH)-based population projections and information from the 2000 CPH on the average household size by province.
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The set of samples selected for the 2009 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 measured in terms of the standard errors for a particular statistic.
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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.
Source: 2006 Family Income and Expenditure Survey (Final Results)
Income and Employment Statistics Division
National Statistics Office
Republic of the Philippines
