Table 5. Multinomial Logit Model using Data for Argentina and Brazil , Men, 15 to 18 y.o

||_BRAZIL -_|_Males 15-18 (4fir_|_st interviews)_||_ARG_|_ENTINA - Males_|_15-18_|
|---|---|---|---|---|---|---|---|
|_Variables_|_Nini_|_Study Only_|_Work only_|_Variables_|_Nini_|_Study Only_|_Work only_|
|Index Study Only|-0.007|0.032***|-0.025***|Index Study Only|-0.038|0.134***|-0.096***|
||(0.009)|(0.009)|(0.003)||(0.033)|(0.036)|(0.011)|
|Index Nini|0.171***<br>|-0.171***<br>|0.001<br>|Index Nini|0.250***<br>|-0.259***<br>|0.009<br>|
||(0.014)|(0.014)|(0.001)||(0.037)|(0.040)|(0.008)|
|Index Work Only|0.140***<br>(0.016)|-0.165***<br>(0.017)|0.025***<br>(0.004)|Index Work Only|0.296***<br>(0.045)|-0.378***<br>(0.050)|0.082***<br>(0.014)|
|Quintil 2|-0.005|0.002|0.003***|Quintil 2|-0.044***|0.035***|0.010**|
||(0.005)|(0.006)|(0.001)||(0.012)|(0.013)|(0.004)|
|Quintil 3|-0.008|0.000|0.008***|Quintil 3|-0.033**|0.003|0.029***|
||(0.006)|(0.006)|(0.002)||(0.016)|(0.020)|(0.009)|
|Quintil 4|-0.015**|0.004|0.010***|Quintil 4|-0.049***|0.045**|0.004|
||(0.006)|(0.007)|(0.002)||(0.016)|(0.019)|(0.007)|
|Quintil 5|-0.032***|0.030***|0.003**|Quintil 5|-0.031|-0.013|0.043**|
||(0.006)|(0.006)|(0.001)||(0.028)|(0.037)|(0.021)|
|Complete primary|-0.010***|0.014***|-0.003***|Complete primary|-0.066***|0.086***|-0.020*|
||(0.003)|(0.003)|(0.001)||(0.026)|(0.031)|(0.011)|
|Complete secondary +|0.436***|-0.490***|0.055***|Complete secondary +|0.142***|-0.162***|0.020|
||(0.036)|(0.038)|(0.010)||(0.044)|(0.051)|(0.017)|
|||||Household head: Incomplete primary|-0.008|0.032|-0.024|
||||||(0.052)|(0.062)|(0.037)|
|Household head: Complete primary|-0.008|0.011*|-0.003**|Household head: Complete primary|-0.058|0.107*|-0.050|
||(0.005)|(0.006)|(0.001)||(0.051)|(0.059)|(0.036)|
|Household head: Complete secondary|-0.021***|0.027***|-0.007***|Household head: Complete secondary|-0.071|0.138**|-0.066*|
||(0.005)|(0.005)|(0.001)||(0.052)|(0.061)|(0.036)|
|Household head: Tertiary|-0.037***|0.046***|-0.010***|Household head: Tertiary|-0.101**|0.173***|-0.072**|
||(0.005)|(0.006)|(0.002)||(0.051)|(0.060)|(0.036)|
|Household head is female|0.011***|-0.014***|0.004***|Household head is female|0.012|-0.019|0.008*|
||(0.004)|(0.004)|(0.001)||(0.010)|(0.012)|(0.004)|
|Married|0006|-0014|0008*|Married|0007|-0006|-0001|
||.<br>(0.012)|.<br>(0.013)|.<br>(0.005)||.<br>(0.039)|.<br>(0.044)|.<br>(0.014)|
|Age|0.008***|-0.009***|0.002***|Age|0.028***|-0.039***|0.011***|
||(0.002)|(0.002)|(0.000)||(0.005)|(0.006)|(0.002)|
|_Obs._|17585|||10645||||
|_Pseudo R-squared_|0.6797|||0.4258||||

_Note_ s: Results are marginal effects evaluated at means of covariates. Standard errors, robust to heteroskedasticity, are in parentheses. The underlined multinomial logit models are estimated with a pooled sample of people who had complete information on the variables of interest for four consecutive quarters and months in Argentina and Brazil, respectively. The dependent variable is a categorical variable which outcomes are represented by the columns of each country in the table. Sample weights are used in estimation. A person is considered _Nini_ when she/he is not working nor studying. In the models for both countries the base group for comparison is given by people who were not Nini, in income quintile one, with no education or incomplete primary and who were not married. Each model includes controls for year and quarter (for Argentina) and month (for Brazil), and state fixed effects (32 dummy variables for Argentina and 5 dummy variables for Brazil). ***,**, and * denotes statistical significance at 1, 5, and 10 percent levels, respectively. _Source_ : Authors' calculations based on _Encuesta Permanente de Hogares,_ 2003:Q1 – 2013:Q _; and Pesquisa Mensal de Emprego,_ 2007:M1-2012:M8.