Results
Main results
Table 2 presents results for wages of private employees. As can be seen in column 1, and
also in Figure 2, the raw district-level relationship between migrant intensity and wages is
strongly positive. Regression-adjusting for differences in the human capital of Thai
workers in column 2 reduces the strength of the relationship slightly. Adding variables to
control for labor demand in column 3 reduces the strength considerably, though the
relationship remains positive. Column 4 is identical to column 3, except that overall
migrant intensity is replaced by Myanmar-specific migrant intensity. The number of
observations drops by 42, because of districts that do not have any migrants from
Myanmar, and which therefore do not have a defined value for Myanmar migrant
intensity. All four OLS models have negative coefficient estimates for the Myanmar
border dummy, though only the first two have negative estimates for the Lao or
Cambodian border.
[Figure 2 and Table 2 here]
ResultsMain resultsTable 2 presents results for wages of private employees. As can be seen in column 1, andalso in Figure 2, the raw district-level relationship between migrant intensity and wages isstrongly positive. Regression-adjusting for differences in the human capital of Thaiworkers in column 2 reduces the strength of the relationship slightly. Adding variables tocontrol for labor demand in column 3 reduces the strength considerably, though therelationship remains positive. Column 4 is identical to column 3, except that overallmigrant intensity is replaced by Myanmar-specific migrant intensity. The number ofobservations drops by 42, because of districts that do not have any migrants fromMyanmar, and which therefore do not have a defined value for Myanmar migrantintensity. All four OLS models have negative coefficient estimates for the Myanmarborder dummy, though only the first two have negative estimates for the Lao orCambodian border.[Figure 2 and Table 2 here]
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