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In the context of MDG 1 (eradicate extreme poverty and hunger), the target set by the international community is to halve, between 1990 and 2015, the percentage of people (i.e., poverty headcount ratio) whose income is less than one US dollar per day (in Purchasing Power Parity, or PPP dollars). This indicator allows for monitoring the proportion of the national population considered poor. However, most poverty studies on individual countries are based on national poverty lines, which vary with the mean level of income of the country. Since Ecuador uses the US dollar as its currency (since 1999), the only adjustment would be for inflation and hence in the declining PPP of the US dollar, since the $1/day criterion was established. Indeed, Ecuador experienced high inflation in the years prior to and immediately following its abandonment of the sucre and conversion to the US dollar. That conversion was used an a patent excuse of many sectors and businesses to increase prices right after the conversion, resulting in the prices of many things rapidly rising close to US levels. PPP-converted incomes facilitate comparisons of income levels between countries. In the context of the project for which this report is written, it facilitates comparison between Armenia, Sri Lanka and Ecuador. The World Bank (2005) noted that the value to use for the extreme poverty threshold by 2004 was $1.08 per day, to take into account an 8% reduction in the purchasing power of the US dollar, since the original $1/day figure was based on purchasing power at 1993 prices. However, this adjustment is so minor that it is not worth taking into account here, especially given the very rough estimates of incomes available from the survey, as is explained below.

In any case, the results presented below should be interpreted with caution for two main reasons. First, the survey did not collect information on actual incomes

of each member of the household. No data were sought on earnings of each household member from work, much less on incomes from other, more complex sources, such as business, farm and rental incomes: it was determined by NIDI at the outset of the project that it would take too much time and effort to collect detailed income data. Thus the only questions asked about income were posed to the household head and were used to establish a category for total household

income per month, in five income categories. These figures were then used to

estimate per capita income per day. Thus, heads of households were asked several questions about total household income in the previous month. The first question was, “On average, is the monthly income of your household, of all members combined, between 100 and 300 dollars, or is it more than that or less than that?” Follow-up questions were then used to establish the income of the household as being in one of five income categories (see Annex III).

The results of this process for the sample population are indicated in table 4.1. This comprehensive table allows us to compare income levels of refugee/asylum seeker households with mixed and non-refugee households, to compare income levels of households with different household sizes and to do both at the same time, that is, to compare incomes of refugee-non-refugee households controlling for household size.

The last line in each of the three panels indicates the overall income distribution of the three types of households and shows that refugee/asylum seeker and mixed households are poorer than non-refugee households overall, with the percentages claiming to have monthly household incomes in the lowest income class under US $100 per month being 65, 56 and 42, respectively. At the other end, those with over $300 per month are 1.6, 3 and 13.3%, for the three types of households. Indeed, the trapezoidal structure of the table shows the expanding income categories for non-refugee households compared to the other two. As for whether household incomes vary much according to household size, it appears that they do not in this study population, that is, households of Colombian migrants with more members do not have higher aggregate household incomes than those with fewer members. Accordingly, controlling for household size does not lead to any appreciably different conclusions, viz., at

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Table 4.1. Income distribution by category of income, refugees/asylum seekers and others, 2006 (US dollars) Refugees/asylum seekers < 100 100-300 301-500 Total Number of members of household % row cases % row cases % row cases % row cases 1 52.9 9 47.1 8 100 17 2 76.2 16 19.0 4 4.8 1 100 21 3 59.1 13 36.4 8 4.5 1 100 22 4 65.0 13 3.05 7 100 20 5 72.7 16 27.3 6 100 22 6 75.0 6 25.0 2 100 8 7 25.0 1 75.0 3 100 4 8 + 66.7 6 33.3 3 100 9 Total 65 80 33.3 41 1.6 2 100 123 Mixed < 100 100-300 301-500 501-1000 Total Number of members of household % row cases % row cases % row cases % row cases % row Cases 1 2 54.5 6 45.5 5 100 11 3 52.9 9 47.1 8 100 17 4 78.3 18 21.7 5 100 23 5 41.2 7 52.9 9 5.9 1 100 17 6 30.0 3 60.0 6 10.0 1 100 10 7 66.7 6 22.2 2 11.1 1 100 9 8 + 50.0 6 50.0 6 100 12 Total 55.6 55 41.4 41 2.0 2 1.0 1 100 99 Other < 100 100-300 301-500 501-1000 > 1000 Total Number of members of household % row cases % row cases % row cases % row cases % row Cases % row cases 1 36.8 14 44.7 17 15.8 6 2.6 1 100 38 2 37.8 17 40.0 18 4.4 2 11.1 5 6.7 3 100 45 3 48.3 28 41.4 24 1.7 1 5.2 3 3.4 2 100 58 4 58.7 27 30.4 14 6.5 3 4.3 2 100 46 5 23.1 9 61.5 24 5.1 2 2.6 1 7.7 3 100 39 6 53.8 14 42.3 11 3.8 1 100 26 7 14.3 1 71.4 5 14.3 1 100 7 8 + 27.8 5 66.7 12 5.6 1 100 18 Total 41.5 115 45.1 125 6.1 17 3.2 9 4.0 11 100 277

virtually all household sizes, refugee and asylum seeker households have lower per capita incomes than non-refugee households and usually also lower incomes than mixed households. For example, for households of size 3, 59% of refugee households have monthly incomes under $100 compared to 53% among mixed households and 48% for other households. The corresponding figures for households of size 5 are 73, 41 and 23 per cent, respectively.

To convert the data from table 4.1 into estimates of per capita income per day, the following procedure was used. First, for each closed income category (e.g., 100 to 300 dollars per month), the middle value of the income class was assigned as the best estimate of mean household income for all households in that income category, except that 700 was used for the category 500 to 999, reflecting the likely greater concentration at the lower end of that category. For the lowest open-ended class, the income level of all households was set at 80% of the upper class boundary for that category, or $80, while for the highest open- ended class it was set at 160% of the lower class limit, or $1600. Second, for each household, this estimated mean household income was divided by 30 to obtain household income per day and then by the number of persons living in the households at the time of the survey, to estimate income per capita per day in US dollars.

The results are presented in table 4.2. It is evident that refugee and mixed households are poorer than the other households comprising only non-refugees. The percentages living in extreme poverty, with less than $1 per person per day, are 50 and 58 for refugee households and mixed households, compared to 36% for non-refugee households. All these figures are far higher than the estimate provided in the statement of Ecuador’s MDGs, which was 15.5% for 1999. Furthermore, another quarter of all the households in each of the three categories of households declared their household incomes to be the equivalent of one to two dollars per day, resulting in the overall poverty percentages of 75, 84 and 61 percent, respectively, for refugee, mixed and non-refugee households. Only 11 households had incomes over $4 per day per person, according to the survey. The income per capita data were also tabulated for urban and rural areas (not shown here) to determine the extent of poverty and extreme poverty by area and whether the refugee-non-refugee differentials persist in both areas. The data show that, overall for Colombian immigrants, extreme poverty is 51% in rural

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Table 4.2. Income level and poverty status of refugees/asylum seeker, mixed and non- refugee households

Refugees/asylum

seekers Mixed Non-refugees Total Income per

person per day in

US dollars % col. Cases %

col. Cases % col. Cases % col. Cases Less than $1 49.6 61 57.6 57 36.5 101 43.9 219 $ 1-1.99 25.2 31 26.3 26 24.5 68 25.1 125 $ 2-3.99 17.1 21 15.2 15 22.4 62 19.6 98 $4 or more 8.1 10 1.0 1 16.6 46 11.4 57 Total cases 100 123 100 99 100 277 100 499

areas compared to 34% in urban areas, while overall poverty (under $2 per capita per day) is 74% and 61%, respectively. The differences in the levels of poverty of refugees and others observed above are also found in both urban and rural areas. Within urban areas, extreme poverty is 38% among refugee households, 51% among the larger mixed households and only 28% among non- refugee households. Among rural households of Colombian immigrants, extreme poverty is 58% overall, being 61% in refugee and mixed households and 43% for other households. Thus, we conclude that poverty levels are consistently higher for refugee/asylum seeker households than non-refugee households in both urban and rural areas.

The results of the survey indicate that, on the whole, refugees have lower household incomes and higher levels of income poverty than non-refugees. This overall finding regarding poverty differences will also be seen to be generally consistent with other quality of life indicators presented in later chapters of this monograph, providing mutual support for the findings. Although the income data cannot be considered accurate, they do suggest a far higher incidence of poverty among Colombian migrants than to Ecuadorian citizens.5

5

More detailed data were collected in the survey on household expenditures, by type or category, but the results are not presented here due to lack of resources for the analysis.