after controlling for the bias in the estimates in the conventional way. The difference in row two and three comes from row two reporting the standard errors with out bias correction, while row three controls for the bias in both the standard errors and the RD estimates. All standard errors are clustered at the score variable and all the variables are adjusted for inflation using IPCA and are in millions of Brazilian reais. The covariates that are controlled for in the estimations include dummies for each bimonth to control for seasonality, previous bimonth’s outcome variable to control for unit root, previous month’s changes in service sector volume index to control for economic growth and depreciation rate to control for trade policy. The table reveals that total expenditure fell by about 81 million Brazilian reais in the second bimonth of 2018. This decrease is mainly due to a fall in personnel spending of 129 million Brazilian reais, suggesting that the personnel spending and total expenditure was mainly responding to the economic crisis that Brazil was coming out from and is unrelated to the influx of about 20,000 displaced Venezuelans. Investment rose about 9 million Brazilian reais, as expected from an economy that was coming out from an economic crisis. Looking into expenditure by functions, it seems that both education and health spending fell, while social assistance, social security and expenditure on civil defence increased. Table A5 shows that using uniform kernel and different bandwidths, the results on total expenditure, personnel spending and social assistance remain robust, suggesting that with the advent of forcibly displaced Venezuelans, social assistance spending did cater to the increase in population and its short-run needs, although total expenditure, specially spending in education and health did not adjust for the higher demand. This is not surprising given that personnel spending is the main driver of total expenditure and that education and health spending are tied to revenues and can only increase when revenue increases, which takes time. The 2.1 million Brazilian reais increase that we observe in the second bimonth is due to the influx of displaced Venezuelans as there is universal access to social assistance programs in Brazil, irrespective of immigration status and Cadastro Unico shows that there is jump from 1,100 registered Venezuelans in December 2017 to about 2,800 registered Venezuelans in April 2018, which corresponds to the second bimonth of 2018.

Table 1: Regression discontinuity estimates of expenditure by categories of functions in Roraima

||(1)<br>Total expenditure|(2)<br>Investment|(3)<br>Personnel Spending|(4)<br>Education|(5)<br>Health|(6)<br>Social assistance|(7)<br>Social security|(8)<br>Police|
|---|---|---|---|---|---|---|---|---|
|Conventional|-73.88*|6.689*|-118.4*|-2.397|-12.24*|1.725*|0.457*|1.285*|
||(16.34)|(2.132)|(4.460)|(2.510)|(3.748)|(0.0635)|(0.0726)|(0.413)|
|Bias-corrected|-81.67*|9.082*|-129.1*|-6.347*|-15.60*|2.101*|1.095*|1.539*|
||(16.34)|(2.132)|(4.460)|(2.510)|(3.748)|(0.0635)|(0.0726)|(0.413)|
|Robust|-81.67*|9.082*|-129.1*|-6.347|-15.60*|2.101*|1.095*|1.539*|
||(25.00)|(3.156)|(13.67)|(8.673)|(4.983)|(0.218)|(0.394)|(0.696)|
|Bandwidths|2.857|8.859|7.085|3.267|4.141|17.001|5.841|3.095|
|Mean|127.50|7.49|67.65|22.06|23.60|1.292|1.749|5.676|
|_N_|33|33|33|31|31|30|31|33|

The standard error are in parentheses and are clustered at the score variable. + _p <_ 0 _._ 10, * _p <_ 0 _._ 05. All data is in millions of Brazilian reais and adjusted for inflation by IPCA. The bandwidths and the estimates are calculated using the regression discontinuity model proposed by Calonico et al. (2020) and Calonico et al. (2014). Covariates include dummies for each bimonth, value of the outcome variables in the previous bimonth and depreciation rate.

Table 2 reports the sharp RD estimates of the impact on total revenue and its different sources. The structure of table is same as Table 1 and using the robust estimates, total revenue is found to have jump up by 15 million Brazilian reais, which seems to be mainly driven by jump in indirect 20