Table 8

OLS estimates and diagnosis tests

Variables3rd Wave4th Wave5th Wave6th Wave7th Wave
1994–19981999–20042005–20092010–20142017–2021
Constant2.5522.9603.1064.328**6.3224*
Cultural variablesTRUST−2.435*−0.889−0.8104−2.110**−2.3138*
SATISFACTION0.581**0.444**0.5372***0.379**−0.0673
POST_MATERIALIST_INDEX0.1611.516***0.09530.4911.4630***
AUTONOMY _INDEX0.1680.3830.7952**0.1260.5080
Economic variables (Control variables)FDI_TO_GDP0.0060.0360.02030.006−0.0724*
TRADE_TO_GDP0.0060.0030.00050.0020.0069**
SCHOOL_ENROLLMENT_PRIMA0.060*0.0040.0361**0.053***0.0426
N (Countries)5339575956
R-squared0.4590.6570.5890.5900.5932
R-squared (adj.)0.3750.5790.5300.5340.5327
F. Statistics5.4476818.48110.02810.4959.7926
Prob(F-statistic)0.0001420.00000.0000.0000
Diagnosis Tests
Serial Correlation LM Test: Breusch-Godfrey (Chi-squared)
Null Hypothesis (H0): there is no serial correlation
4.103364 (0.1285)4.894958 (0.0865)2.126108 (0.1306)3.343257 (0.1879)1.127863 (0.5690)
Heteroskedasticity Test: Breusch-Pagan-Godfrey (Chi-squared)
Null Hypothesis (H0): Homoscedasticity is present
4.680588 (0.6989)10.43826 (0.1651)7.881646 (0.3431)8.202674 (0.3151)10.34206 (0.1700)

Note(s): (***), (**), and (*) indicate the significance of the estimated coefficients at (1%), (5%), and (10%) levels of significance, respectively Breusch-Godfrey tests for serial correlation, The Breusch-Pagan test is used to determine whether or not heteroscedasticity is present in a regression model

Source(s): Authors' estimation

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