1.13 -0.95 0.14 0.18 Estimated result from logit regression and marginal effects.

Education and Leadership in Glocalization : What does “think globally, act locally” mean for education around the world? 21-24 2014 96 4 Table 2 Logit Estimation Plan to leave Overall Coefficient Boarding Coefficient Non-Boarding Coefficient School- Type+ 0.23 0.05 ….. ….. Gender+ -0.86 -0.20 -0.44 -0.10 -1.75 -0.40 EduMaster+ 0.41 0.09 -0.26 -0.06 1.18 0.25 EduPgDE+ 0.65

0.14 1.13

0.22 -0.95

-0.23 EduPgCE+

0.65 0.14

0.97 0.18

0.11 0.03 Years of Experience -0.10 -0.02 -0.08 -0.02 -0.14 -0.03 Incentives -0.71 -0.16 -0.48 -0.10 -1.36 -0.32 Workload -0.22 -0.05 -0.61 -0.13 0.34 -0.05 Working Conditions -0.34 -0.09 -0.41 -0.09 -0.22 0.36 Attitude 0.06 0.01 0.30 0.07 -0.56 -0.13 Constant 4.57 0.30 7.47 Pseudo R2 0.21 0.20 0.34 Count R2 0.76 0.75 0.79 + is Binary dummy variable , , indicates significance level at 99, 95 and 90 confidence level respectively The values in the parenthesis are the Marginal effects at mean The table describes the estimated results of the teacher’s retention in Bhutanese educational system. Gender is negatively significantly related to the teachers’ decision to leave the job. This means, the probability of female teachers leaving the teaching job is 20 percent less than the male teacher in Bhutan. EduPgDE and EduPgCE both have the positive and significant relationship with the teachers’ decision to leave the job. It indicates that the teachers with an additional qualification are more likely to leave the profession. Both PgDE and PgCE teachers with one year of additional qualification are more likely to leave the teaching job by 14 percent compared to base teachers with Bachelor in education. The effect of years of experience to teachers’ decision to leave the job is negative and significant. This means that, with an increase in year of teaching experience will reduce the probability of leaving the profession by 2 percent. The empirical analysis on teachers monetary incentives are negatively significantly related to teachers’ decision to leave the job. This implies that the monetary incentives structure for teachers in Bhutan is not satisfactory. If the overall monetary incentives for teachers in Bhutan are increased, the likelihood of teachers leaving the job will be decrease by 16 percent. The relationship between working conditions and intended leavers are significantly negatively related. It implies that the working conditions in Bhutan are a clear predictor of teachers leaving the job. If working conditions in the school is improved, the likelihood of teachers leaving their job decreases by 8 percent. Workload does not predict the likelihood of teachers’ turnover as the result is insignificant. However, the negative coefficient indicates that teachers’ with more workload are more likely to leave their profession. In boarding schools, teachers with PgDE and PgCE are more likely to leave the job comparing to others type of teachers. Apart from years of experience and monetary incentives, workload is significantly negative in boarding school. Teachers in boarding schools are 13 percent more likely to leave the job, if workload is not reduced. In non-boarding schools, gender is negatively significant. It indicates that male teachers are 40 percent more likely to leave the current job than female teachers. Teachers with master degree are positively significant. They are more likely to leave the job in non-boarding school compared to others type of teachers in Bhutan. The logit model correctly predicts 76 percent of the values and the rest are misclassified. The McFadden’s pseudo R2 is 0.21. R2 indicates how well the regression line fits the data and how well the future outcomes can be predicted by the model. The result shows that the explanatory variables are explaining 21 percent of the variations in the dependent variable. The overall significance test Probchi2 is significant 0.000.

4. Conclusion