Comparing the two regressions

54

grade average at 2. Having a grade average at 5 is associated with a 41% higher re-enrollment probability compared to having a grade average of 1. Having a grade average at 3 is

associated with a 21.4% higher re-enrollment probability compared to having a grade average of 1. The coefficient on grade average 5 is almost twice as big as the coefficient on grade average of 3, implying that students with grade averages of 5 has a twice as big re-enrollment association as the students with grade average of 3. The interaction between female and grades are not significant for the probability of re-enrolling, and all of the coefficients are negative. This implies that the association between average grades and the probability to re-enroll is not significantly different between males and females.

55 there are significant coefficients on upper secondary, supplementary and both lengths of university of college education. The biggest coefficient being from the level of long university or college, where the associated probability of re-enrolling is increased by 16.1% when

mothers go from primary to supplementary education. All of the education levels for the mothers has a positive association with the probability of the dropout becoming a re-enroller compared to primary education.

Father education coefficients paints a different picture. On the dropout probability no levels of father’s education are significant, and all coefficients are negative except the coefficient on lower secondary education. For all levels above lower secondary education there is associated a lower dropout probability compared to primary education. It is expected that lower levels of education are associated with a higher probability of dropout, and this holds for the coefficients on father’s education. It is however a paradox that it is an increasing probability associated with dropping out when fathers have lower secondary level of

education, compared to primary education. These coefficients are not significant, but either way this is an unexpected result. On re-enrollment probability none of the coefficients for father’s education are significant. Lower secondary and basic upper secondary education has negative coefficients, implying that these levels of education is associated with a reduced probability of re-enrolling compared to primary education. All other coefficients are positive, implying an increased re-enrollment probability for higher levels of education. The highest coefficient is for researcher level, which is associated with a 5.8% higher association on re-enrollment probability. The absolute values of the coefficients are higher in the dropout regression compared to the re-enrollment regression. This indicates that father’s education is not as important for the dropout process as for the re-enrollment process.

For the regressors on school regions are all coefficients positive and significant on the dropout probability, with the highest coefficient being North. Going to school in North is associated with a 11.9% higher dropout probability compared with going to school in the South. This is expected as the northern council municipalities constitutes the ones with the highest dropout rates in the country. On the re-enrollment probability, however, is none of the coefficients significant. There are negative coefficients of schooling in North and East, while there are positive coefficients in Mid and West. It does imply that the schooling region has significant associations with dropping out, but not so much for re-enrollment in this sample.

56

All grade averages have a negative association with dropout probability, and all grades except 2 are significant. The biggest coefficient on dropout probability is having a grade average at 6, which is associated with 82.1% lower dropout probability compared to having a grade average at 1. These findings are not surprising as it is expected that higher grade averages are related to lower dropout probability. On re-enrollment probability all the grade averages are positive, and all grade averages over 2 is significant. The highest coefficient is from having an average of 5, where there is associated a 41% higher probability of

re-enrolling compared to students with a grade average of 1. The absolute value of the estimated coefficients on grades is bigger in the dropout regression compared to the re-enrollment regression. This implies that higher grade averages play a bigger role in reducing the dropout probability than to increase the re-enrollment probability.

The interaction term between grades and gender has different implications for the different regressions. In the dropout regression the coefficients are positive on dropout probability for all levels of grade averages, while for the re-enrollment probability the

coefficients are negative. The interaction coefficients are not significant in either regressions, implying that the associations between average grades and the probability of becoming a dropout or re-enroller does not significantly differ between males and females.

To sum up the regressions show that the same model specification and regressors have different associations for the probability of drop out and the probability of re-enrolling. There is not such that the same level of parental education or the same grade average has the same sign, size of level of significance for the two regressions. It is interesting that some variables, for example school region is more substantial for the dropout process than for the

re-enrollment process.

57