methods, particularly the exclusion of children from the LFS data set in 2014, this paper is not able to use the 2014 data set to impute household-level poverty rates.<sup>13</sup> Our analysis is limited to 2013.

Another difference is that this paper’s analysis is conducted at the regional level. Regional aggregation smooths away household differences. Therefore, regressions are run on poverty rates of different subsamples of the host community. Table 13 and Table 14 present results of regressions on sub-samples based on the characteristics of the head of the household. We consider gender, education, and work type. Del Carpio and Wagner (2015) found the impact of SUTPs varies across different groups of the labor force. It is possible that some households are more susceptible or vulnerable than others in managing externalities from large in-flows of SUTPs. However, results from these regressions continue to show that across various groups, the proportion of foreign-born did not have a significant effect on poverty.

A third reason is substitution of labor yielded no net effects at the household level. Not all impacts are negative to the host community. As Del Carpio and Wagner (2015) point out, the influx of refugees also generated better paying jobs that were filled by local Turkish workers. It is possible that at the household level, the net labor market effects from the influx of refugees remained insignificant as some low skilled members lost jobs but then better jobs became available. Summary statistics show that from 2009 to 2013, the share of employed adults in a host community household near the Syrian border actually increased from 24 to 27 percent, and the share of unemployed adults dropped from 5 to 4 percent (Table 10). The share of host community heads of household working in Agriculture, Forestry, Fishing, and Mining also significantly declined near the Syrian border from 2009 to 2013. In 2009, 16 percent of heads of household in this group worked in this sector, and declined to 12 percent in 2013. The share of workers in white collar jobs also significantly increased and blue collar jobs declined during this period. This would result in insignificant impacts from an increasing foreign-born population at the household level.

In the shorter time period, from 2011 to 2013, the characteristics of host communities in near the Syrian border did not regress (Table 16). For example, the proportion of workers in a household working white collar jobs increased from 30.9 percent in 2011 to 34.4 percent in 2013. The share of workers registered with a social security institution also increased from 46.1 to 52.4 percent.

One caveat is that over this period, Turkey experienced healthy growth, and direct impact of these effects whether through displacement effects or increased growth due to the influx of Syrians is not completely obvious. For example, in the rest of the country, which is a less popular destination for migrants, the share of adults employed also increased from 32 to 37 percent from 2009 to 2013. In other words, improved conditions of host community families could be due to a period of healthy growth. Would host community families have stopped working in agriculture anyway even if there were no Syrians or did Syrians start taking these jobs? Whether or not host communities would be better off is not clear, but what can be said is that the poverty rate has not gone up.

While poverty rates in 2014 are not available, a comparison of the host community characteristics in 2013 and 2014 may give insights to trends. Looking at a more compressed period from 2013 to 2014, there is some evidence that host community families changing in their labor market characteristics. For example, the proportion of workers with a permanent contract type declined from 36.2 percent in 2013 to 35.1 percent

> 13 Household size is not reported for the entire household, only the 15+ segment. Dependency ratios and per capita income cannot be computed using the 2014 LFS.

16