Page 11 - Azerbaijan State University of Economics

Rza Mammadov, Erdal Gümüş: Secondary Education, Economic Growth and Finance

Table 5: DOLS and FMOLS findings
Sample Variable Method Model 1 Model 2 Model 3
Group Coef. t-stat. Coef. t-stat Coef. t-stat
1 DOLS -0.16 -8.10*** -0.44 -3.01*** 0.10 1.45
Panel FMOLS -0.16 -9.26*** -0.36 -3.05*** 0.13 2.38**
2 DOLS 0.04 0.61 0.57 3.73*** 0.09 4.31***
FMOLS 0.12 1.75* 0.71 5.77*** 0.10 6.28***
1 DOLS -0.23 -7.82*** -0.47 -2.51** 0.12 1.44
Above FMOLS -0.25 -9.11*** -0.46 -3.02*** 0.18 2.81***
Average 2 DOLS 0.03 0.28 0.65 2.73*** 0.11 3.63***
Perf. FMOLS 0.15 1.36 0.95 5.55*** 0.13 5.36***
1 DOLS -0.07 -2.99*** -0.41 -1.77* 0.07 0.67
Below FMOLS -0.06 -3.06*** -0.27 -1.35 0.08 0.85
Average 2 DOLS 0.05 0.77 0.48 2.63*** 0.06 2.37**
Perf. FMOLS 0.09 1.12 0.44 2.47** 0.08 3.40***
1 DOLS -0.20 -6.95*** -0.30 -1.33 -0.10 -1.17
1998-2007 FMOLS -0.21 -10.68*** -0.30 -1.44 -0.09 -1.73*
2 DOLS 0.05 0.37 0.63 2.41** 0.02 0.58
FMOLS 0.11 0.94 0.61 1.73* 0.02 1.08
1 DOLS -0.05 -1.01 -0.17 -0.39 0.04 0.35
2010-2015 FMOLS -0.05 -1.07 -0.10 -0.24 -0.06 -0.43
2 DOLS -0.00 -0.02 1.17 2.40** 0.12 5.02***
FMOLS -0.02 -0.10 1.32 2.49** 0.13 5.64***

*, **, and *** are respectively 10%, 5% and 1% significance levels. Bartlett Kernel method was used
and Bandwidth width was determined by Newey-West method

The relational direction and value of the variables are presented as a panel to cover 30
countries. In addition, the countries were distinguished as upper and lower from the
OECD average on the PISA exam and analysed. On the other hand, the years 1998-
2007 and 2010-2015 distinctions were made to show the direction of the relationship
between variables pre and post the 2008 crisis. According to the results in Table 4,
financing across the panel affects the education negatively, at a level of 0.16% when
viewed with both the DOLS and FMOLS method. The impact of growth in education is
not statistically significant in the DOLS model. According to the FMOLS method, 10%
significance level, growth leads to a positive change of 0.12 on education. Considering
the model, in which financing is considered as a dependent variable, as the number of
students enrolled in secondary education increases, the expenditure per student
decreases by the public. This decrease is seen as -0,44 in DOLS method and -0,36 in
FMOLS method at 1% significance level. The increase in GDP per capita, which is an
indicator of growth, positively affects public education expenditures per student, which
is an indicator of finance. In other words, 1% significance level, growth affects the
finance 0.57 positively in the DOLLS method and 0.71 in the FMOLS method. When
the model is analysed in three, secondary education affects growth positively. Although
this effect is not statistically significant in DOLS method, it increases 0.13 values with
5% significance level compared to FMOLS method. On the other hand, has a 1%
significance level, financing has a positive effect growth on both models.

11