of 2017, which is about 27% of the total employed and the public sector does not hire any foreigner. As a result, the 6.7% increase in the working age population led to an increase in unemployment among females by about 22%. Employment among females also decrease by about 12%, suggesting that females are suffering more from the displacement crisis. This finding are in line with findings discussed in Bedaso (2021) and many others who find women, specially women refugees are disadvantaged in the labor market, and native women are more likely to bear the adverse effects of refugee influx. Another group that is also suffering disproportionately is the low skilled or those with an education below college degree. Employment among those with an education below college degree plummeted down by about 5%. On the positive side, there is an increase in monthly income among the males and the college educated, suggesting that complementarity of native’s skills with the Venezuelan forcibly displaced is improving the productivity of the high skilled male workers.

Table 9 and table 10 explore the effects on monthly income by different industries, gender and education and this paper find that there are some sectors, which experienced loss in earnings while others that experienced gain in earnings in response to the influx of displaced Venezuelans. For example, male and female earnings went up in the IT and real estate sector while the increase is concentrated among the high skilled. It should be reiterated here that the data does not disaggregate by nationality and consequently all the results are on the overall labor market. The female earnings declined in the construction and trade sector, while the changes in male earnings in these sectors were statistically insignificant. Earnings in the construction sector seemed to have gone down among the low skilled, but increased among the high skilled, while earnings among the low skilled increased in the education and health sector while it decreased among the college educated. The results point to the fact that the displaced Venezuelans may be complementing the high skilled workers in the host community in construction and information technology increasing their productivity while they are partially substituting the low skilled workers and leading to a fall in their earnings, suggesting that some groups gain while others lose in a displacement crisis in the short-run.

Table 9: The effect on gross income in Roraima by sex and industry

||||||**Ma**<br>|**le**<br>||||
|---|---|---|---|---|---|---|---|---|---|
||Agriculture|Industry|Construction|Trade|Transport|Hospitality|IT& Real Estate|Public|Education & Health|
|Conventional|0.0466<sup>_∗_</sup><br>(0.0117)|-0.214<sup>_∗_</sup><br>(0.0437)|0.234<sup>+</sup><br>(0.126)|-0.0000765<br>(0.0118)|0.149<br>(0.113)|0.000552<br>(0.0100)|0.0705<sup>_∗_</sup><br>(0.0263)|-0.0134<br>(0.0570)|-0.0488<sup>_∗_</sup><br>(0.0189)|
|Bias-corrected|0.0264<sup>_∗_</sup>|-0.219<sup>_∗_</sup>|-0.365<sup>_∗_</sup>|0.0101|0.0354|-0.00591|0.0858<sup>_∗_</sup>|0.00180|-0.171<sup>_∗_</sup>|
||(0.0117)|(0.0437)|(0.126)|(0.0118)|(0.113)|(0.0100)|(0.0263)|(0.0570)|(0.0189)|
|Robust|0.0264|-0.219<sup>_∗_</sup>|-0.365|0.0101|0.0354|-0.00591|0.0858<sup>+</sup>|0.00180|-0.171<sup>_∗_</sup>|
||(0.0187)|(0.0798)|(0.627)|(0.0193)|(0.0999)|(0.0125)|(0.0520)|(0.143)|(0.0497)|
||||||**Fem**<br>|**ale**<br>||||
|Conventional|0.00407|-0.0552<sup>_∗_</sup>|-0.0517<sup>_∗_</sup>|-0.0414<sup>_∗_</sup>|0.0232<sup>+</sup>|0.0262|0.0259<sup>_∗_</sup>|-0.0343|0.0412|
||(0.0134)|(0.0223)|(0.00900)|(0.00728)|(0.0127)|(0.0195)|(0.00691)|(0.0438)|(0.0648)|
|Bias-corrected|-0.0549<sup>_∗_</sup>|-0.0543<sup>_∗_</sup>|-0.0643<sup>_∗_</sup>|-0.0497<sup>_∗_</sup>|-0.00177|0.00805|0.0926<sup>_∗_</sup>|0.00721|-0.380<sup>_∗_</sup>|
||(0.0134)|(0.0223)|(0.00900)|(0.00728)|(0.0127)|(0.0195)|(0.00691)|(0.0438)|(0.0648)|
|Robust|-0.0549|-0.0543|-0.0643<sup>_∗_</sup>|-0.0497<sup>_∗_</sup>|-0.00177|0.00805|0.0926<sup>_∗_</sup>|0.00721|-0.380|
||(0.0343)|(0.0450)|(0.0148)|(0.0106)|(0.0119)|(0.0394)|(0.0366)|(0.0790)|(0.337)|

The standard errors are given in parentheses.<sup>+</sup> _p <_ 0 _._ 10,<sup>_∗_</sup> _p <_ 0 _._ 05. The bandwidths and the estimates are calculated using the regression discontinuity model proposed by Calonico et al. (2020) and Calonico et al. (2014). All standard errors are clustered at score variable. The data is segregated by gender and industry.The monthly income is in Brazilian reais adjusted for inflation by IPCA.The covariates included are quarterly dummies and previous quarter’s value of the outcome variables.

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