Income inequality has unprecedently grown in the recent past and its pace has further accelerated. This has alarmed many scholars to reexamine both the widely held wisdom of economic theory of inequality and empirical realities with a view to either reconcile or reject theory for an alternative explanation. The present study posits the relationship between innovation and inequality mediated by the human capital.
In this context, it is proposed to examine the long run nexus between income inequality, innovation and human capital for a sample of 15 Asia-Pacific countries. We have employed the ARDL Bounds Co-Integration Approach to estimate the parameters covering the period of hyper-globalization, that is, 1990-2020. To avoid the spurious regression results in time series analysis, the stationarity test was carried out using the Augmented Dickey-Fuller and Phillips-Perron unit root test methods. Indeed, some explanatory variables are stationary at level while others are stationary after first differencing.
The bounds co-integration test revealed a significant long-run equilibrium relationship between income inequality, innovation and human capital variables in all the 15 Asia-Pacific countries. Except Japan and Vietnam, all other countries have a positive relationship between innovation and income inequality. Furthermore, the empirical
evidence indicates that the income inequality-innovation nexus in eleven of the Asia-Pacific economies is subject to the countries’ level of human capital development via the so-called skill premium during the period of study. The human capital coefficient is positive in eight countries but statistically significant in five countries. This implies that innovation and human capital adversely affected income distribution.
The innovation-human capital interaction coefficient implies that technological innovation adversely affects income distribution of an economy through the composition and nature of work reduces the demand for manual work as well as the generation of economic rents and rent-seeking behavior of skill and capital biased technologies.
It is important to note that there is a strong negative relationship between gross national income per capita and income inequality.
This means that the rise in per capita income improves income distribution. However, the six countries have a growth enhancing income inequality in the case a model estimated without interaction term and five countries in a model estimated with interaction term. An important lesson that comes out of the main finding of the impact of innovation on increase in income equality is that the top-down model of science and technology and increasing investment of private sector in technologies have monopolized the innovations for seeking rents. In this process, the market economy-based innovation system tends to exclude the marginalized section of the society. Therefore, it is suggested that there is a dire need to relook at the innovation system that should use both bottom up and top-down mix to have an impact on reduction of income inequality. Based on these findings, it is important to develop affirmative strategies to improve the education and health services system as well as better opportunities for innovation for those who are marginalized and deprived. In this regard, better quality institutions and infrastructure can play an important role in reducing income inequality in the long run.
(Submitted Oct 27 2022, Revised Jan 02 2023, Accepted Jan 11 2023)
Appendix A
-7.78 -7.76 -7.74 -7.72 -7.70 -7.68 -7.66 -7.64
ARDL(2, 2, 1, 0, 2, 2, 2, 0) ARDL(2, 2, 1, 0, 1, 2, 2, 0) ARDL(2, 2, 1, 1, 2, 2, 2, 0) ARDL(2, 2, 1, 1, 1, 2, 2, 0) ARDL(2, 2, 2, 0, 2, 2, 2, 0) ARDL(2, 2, 1, 0, 1, 2, 1, 0) ARDL(2, 2, 1, 0, 1, 2, 2, 1) ARDL(2, 2, 2, 0, 1, 2, 2, 0) ARDL(2, 2, 1, 0, 2, 2, 2, 1) ARDL(2, 2, 1, 2, 2, 2, 2, 0) ARDL(2, 2, 1, 0, 2, 2, 1, 0) ARDL(2, 2, 1, 0, 1, 2, 0, 0) ARDL(2, 2, 1, 1, 2, 2, 2, 1) ARDL(2, 2, 2, 1, 2, 2, 2, 0) ARDL(2, 2, 0, 0, 1, 2, 2, 0) ARDL(2, 2, 2, 2, 2, 2, 2, 0) ARDL(2, 2, 1, 0, 1, 0, 1, 2) ARDL(2, 2, 2, 0, 1, 2, 1, 0) ARDL(2, 2, 2, 0, 2, 2, 1, 0) ARDL(2, 2, 1, 0, 1, 2, 1, 1)
Akaike Information Criteria (top 20 models)
-16.35 -16.30 -16.25 -16.20 -16.15 -16.10 -16.05
ARDL(2, 2, 2, 2, 0, 0, 2, 2) ARDL(2, 2, 2, 2, 0, 1, 2, 2) ARDL(2, 2, 2, 2, 1, 1, 2, 2) ARDL(2, 2, 2, 2, 2, 0, 2, 2) ARDL(2, 2, 2, 2, 2, 1, 2, 2) ARDL(2, 2, 2, 2, 1, 0, 2, 2) ARDL(2, 2, 2, 2, 1, 2, 2, 2) ARDL(2, 2, 2, 2, 0, 2, 2, 2) ARDL(2, 2, 2, 2, 2, 2, 2, 2) ARDL(2, 1, 2, 2, 2, 0, 2, 2) ARDL(2, 1, 2, 2, 0, 0, 2, 2) ARDL(2, 1, 2, 2, 2, 1, 2, 2) ARDL(2, 1, 2, 2, 1, 0, 2, 2) ARDL(2, 1, 2, 2, 1, 2, 2, 2) ARDL(2, 1, 2, 2, 1, 1, 2, 2) ARDL(2, 0, 2, 2, 2, 0, 2, 2) ARDL(2, 1, 2, 2, 0, 1, 2, 2) ARDL(2, 1, 2, 2, 2, 2, 2, 2) ARDL(2, 2, 2, 2, 1, 2, 2, 1) ARDL(2, 2, 2, 2, 1, 1, 2, 1)
Akaike Information Criteria (top 20 models)
Figure a1
oPTImal lag selecTIonfor ausTralIa Case I: without interaction term
Akaike Information Criteria (top 20 models) Case II: with interaction term Akaike Information Criteria (top 20 models)
-7.32 -7.30 -7.28 -7.26 -7.24 -7.22 -7.20 -7.18
ARDL(2, 1, 0, 0, 2, 2, 2, 2) ARDL(2, 1, 0, 0, 2, 2, 2, 0) ARDL(2, 1, 0, 0, 2, 2, 2, 1) ARDL(2, 1, 0, 1, 2, 2, 2, 2) ARDL(2, 1, 1, 0, 2, 2, 2, 1) ARDL(2, 2, 0, 0, 2, 2, 2, 1) ARDL(2, 2, 0, 1, 2, 2, 2, 2) ARDL(2, 2, 0, 0, 2, 2, 2, 2) ARDL(2, 1, 1, 0, 2, 2, 2, 0) ARDL(2, 1, 1, 0, 2, 2, 2, 2) ARDL(2, 1, 1, 1, 2, 2, 2, 2) ARDL(2, 1, 0, 2, 2, 2, 0, 1) ARDL(2, 1, 0, 1, 2, 2, 2, 0) ARDL(2, 2, 0, 0, 2, 2, 2, 0) ARDL(2, 1, 0, 1, 2, 2, 2, 1) ARDL(2, 1, 0, 2, 2, 2, 2, 2) ARDL(2, 2, 1, 0, 2, 2, 2, 0) ARDL(2, 1, 2, 0, 2, 2, 2, 2) ARDL(2, 1, 0, 2, 0, 2, 2, 2) ARDL(2, 1, 2, 0, 2, 2, 2, 1)
Akaike Information Criteria (top 20 models)
-7.48 -7.46 -7.44 -7.42 -7.40 -7.38 -7.36 -7.34
ARDL(2, 0, 0, 1, 1, 2, 2, 2) ARDL(2, 2, 2, 1, 0, 2, 2, 0) ARDL(2, 2, 1, 2, 0, 2, 2, 0) ARDL(2, 1, 2, 2, 0, 2, 2, 0) ARDL(2, 0, 0, 1, 2, 2, 2, 2) ARDL(2, 1, 0, 1, 1, 2, 2, 2) ARDL(2, 0, 1, 1, 1, 2, 2, 2) ARDL(2, 2, 0, 2, 0, 2, 2, 0) ARDL(2, 0, 0, 2, 1, 2, 2, 2) ARDL(2, 1, 1, 1, 1, 2, 2, 2) ARDL(2, 1, 2, 2, 1, 2, 2, 0) ARDL(2, 2, 2, 1, 1, 2, 2, 0) ARDL(2, 2, 0, 1, 1, 2, 2, 2) ARDL(2, 1, 0, 1, 2, 2, 2, 2) ARDL(2, 2, 2, 1, 0, 2, 2, 1) ARDL(2, 2, 0, 2, 1, 2, 2, 0) ARDL(2, 2, 1, 2, 1, 2, 2, 0) ARDL(2, 2, 1, 2, 0, 2, 2, 1) ARDL(2, 0, 0, 2, 2, 2, 2, 2) ARDL(2, 0, 1, 1, 2, 2, 2, 2)
Akaike Information Criteria (top 20 models)
Figure a2
oPTImal lag selecTIonfor bangladesh Case I: without interaction term
Akaike Information Criteria (top 20 models) Case II: with interaction term Akaike Information Criteria (top 20 models)
-8.68 -8.66 -8.64 -8.62 -8.60 -8.58 -8.56 -8.54 -8.52
ARDL(2, 1, 2, 2, 2, 2, 1, 2) ARDL(1, 1, 2, 2, 0, 2, 1, 0) ARDL(2, 1, 2, 2, 2, 2, 2, 2) ARDL(2, 2, 2, 2, 2, 2, 1, 2) ARDL(2, 1, 2, 2, 0, 2, 1, 0) ARDL(1, 2, 2, 2, 2, 2, 1, 2) ARDL(2, 1, 2, 2, 0, 2, 1, 2) ARDL(1, 2, 2, 2, 0, 2, 1, 0) ARDL(1, 1, 2, 2, 0, 2, 2, 0) ARDL(1, 1, 2, 2, 2, 2, 2, 0) ARDL(1, 2, 2, 2, 2, 2, 2, 0) ARDL(2, 1, 2, 2, 2, 2, 2, 0) ARDL(1, 1, 2, 2, 1, 2, 1, 0) ARDL(1, 2, 1, 2, 1, 2, 1, 2) ARDL(1, 1, 2, 2, 0, 2, 1, 1) ARDL(2, 1, 2, 2, 0, 2, 1, 1) ARDL(2, 2, 2, 2, 2, 2, 2, 2) ARDL(1, 2, 2, 2, 2, 2, 2, 2) ARDL(2, 1, 2, 2, 1, 2, 2, 2) ARDL(1, 2, 2, 2, 1, 2, 1, 2)
Akaike Information Criteria (top 20 models)
-9.1 -9.0 -8.9 -8.8 -8.7 -8.6 -8.5 -8.4
ARDL(2, 2, 2, 1, 2, 1, 2, 2) ARDL(2, 2, 2, 2, 2, 1, 2, 2) ARDL(2, 1, 1, 2, 2, 2, 2, 2) ARDL(2, 2, 2, 1, 2, 2, 2, 2) ARDL(2, 2, 2, 2, 2, 2, 2, 2) ARDL(2, 2, 1, 2, 2, 2, 2, 2) ARDL(2, 1, 2, 2, 2, 2, 2, 2) ARDL(2, 1, 1, 2, 2, 1, 2, 2) ARDL(2, 2, 1, 2, 2, 1, 2, 2) ARDL(2, 1, 2, 2, 2, 1, 2, 2) ARDL(2, 2, 1, 1, 2, 1, 2, 2) ARDL(2, 2, 1, 1, 2, 2, 2, 2) ARDL(2, 1, 2, 2, 0, 2, 2, 2) ARDL(2, 2, 2, 1, 1, 1, 2, 2) ARDL(2, 2, 1, 2, 0, 2, 2, 2) ARDL(2, 1, 1, 2, 0, 2, 2, 2) ARDL(2, 2, 2, 1, 0, 2, 2, 2) ARDL(2, 1, 2, 1, 2, 1, 2, 2) ARDL(2, 2, 1, 2, 1, 2, 2, 2) ARDL(2, 1, 2, 2, 1, 2, 2, 2)
Akaike Information Criteria (top 20 models)
Figure a3
oPTImal lag selecTIonfor chIna Case I: without interaction term
Akaike Information Criteria (top 20 models) Case II: with interaction term Akaike Information Criteria (top 20 models)
-7.66 -7.64 -7.62 -7.60 -7.58 -7.56 -7.54
ARDL(2, 2, 2, 2, 2, 2, 2, 0) ARDL(1, 2, 2, 2, 2, 2, 2, 1) ARDL(1, 2, 2, 2, 2, 2, 2, 0) ARDL(1, 2, 1, 2, 2, 2, 2, 0) ARDL(2, 2, 1, 2, 2, 2, 2, 0) ARDL(1, 2, 0, 2, 2, 2, 2, 0) ARDL(2, 2, 0, 2, 2, 2, 2, 0) ARDL(1, 2, 0, 2, 2, 2, 2, 1) ARDL(2, 2, 2, 2, 2, 2, 2, 2) ARDL(1, 1, 0, 2, 2, 2, 2, 1) ARDL(1, 2, 1, 2, 2, 2, 2, 1) ARDL(2, 2, 2, 2, 2, 2, 2, 1) ARDL(1, 2, 2, 2, 2, 2, 2, 2) ARDL(2, 1, 0, 2, 2, 2, 2, 0) ARDL(1, 1, 0, 2, 2, 2, 2, 0) ARDL(1, 2, 0, 2, 2, 2, 2, 2) ARDL(2, 1, 2, 2, 2, 2, 2, 0) ARDL(1, 1, 2, 2, 2, 2, 2, 1) ARDL(1, 2, 1, 2, 2, 2, 2, 2) ARDL(2, 2, 0, 2, 2, 2, 2, 2)
Akaike Information Criteria (top 20 models)
-6.9 -6.8 -6.7 -6.6 -6.5 -6.4
ARDL(2, 2, 2, 2, 2, 2, 2, 2) ARDL(2, 1, 2, 2, 2, 2, 2, 2) ARDL(2, 0, 2, 2, 2, 2, 2, 2) ARDL(1, 2, 2, 2, 2, 2, 2, 2) ARDL(2, 2, 1, 1, 2, 2, 2, 2) ARDL(1, 1, 2, 2, 2, 2, 2, 2) ARDL(1, 0, 2, 2, 2, 2, 2, 2) ARDL(2, 2, 1, 2, 2, 2, 2, 2) ARDL(2, 2, 2, 1, 2, 2, 2, 2) ARDL(1, 2, 1, 1, 2, 2, 2, 2) ARDL(1, 2, 1, 2, 2, 2, 2, 2) ARDL(1, 2, 2, 1, 2, 2, 2, 2) ARDL(1, 2, 1, 2, 2, 2, 2, 1) ARDL(1, 2, 2, 1, 2, 2, 2, 1) ARDL(2, 2, 2, 1, 2, 2, 2, 1) ARDL(2, 2, 1, 2, 2, 2, 2, 1) ARDL(1, 1, 2, 2, 2, 2, 2, 1) ARDL(1, 2, 1, 1, 2, 2, 2, 1) ARDL(1, 2, 2, 2, 2, 2, 2, 1) ARDL(2, 2, 2, 2, 2, 2, 2, 1) Akaike Information Criteria (top 20 models)
Figure a4
oPTImal lag selecTIonfor IndIa Case I: without interaction term
Akaike Information Criteria (top 20 models) Case II: with interaction term Akaike Information Criteria (top 20 models)
-7.75 -7.70 -7.65 -7.60 -7.55 -7.50 -7.45 -7.40
ARDL(2, 2, 2, 1, 2, 2, 0, 2) ARDL(2, 2, 2, 2, 2, 2, 0, 2) ARDL(2, 2, 2, 1, 2, 2, 1, 2) ARDL(2, 2, 2, 2, 2, 2, 1, 2) ARDL(2, 2, 2, 1, 2, 2, 2, 2) ARDL(2, 2, 2, 2, 2, 2, 2, 2) ARDL(2, 2, 1, 2, 2, 2, 0, 2) ARDL(2, 2, 1, 1, 2, 2, 2, 2) ARDL(2, 2, 1, 1, 2, 2, 0, 2) ARDL(2, 2, 0, 2, 2, 2, 0, 2) ARDL(2, 2, 0, 1, 2, 2, 0, 2) ARDL(2, 2, 1, 2, 2, 2, 2, 2) ARDL(2, 2, 0, 2, 2, 2, 1, 2) ARDL(2, 2, 1, 2, 2, 2, 1, 2) ARDL(2, 2, 0, 1, 2, 2, 1, 2) ARDL(2, 2, 0, 1, 2, 2, 2, 2) ARDL(2, 2, 1, 1, 2, 2, 1, 2) ARDL(2, 2, 0, 2, 2, 2, 2, 2) ARDL(2, 2, 2, 1, 2, 1, 2, 2) ARDL(2, 2, 2, 1, 2, 1, 0, 2)
Akaike Information Criteria (top 20 models)
-7.45 -7.40 -7.35 -7.30 -7.25 -7.20 -7.15 -7.10
ARDL(2, 2, 1, 2, 2, 2, 2, 2) ARDL(2, 2, 2, 2, 2, 2, 2, 2) ARDL(2, 1, 2, 2, 2, 2, 2, 2) ARDL(2, 2, 2, 1, 2, 2, 2, 2) ARDL(2, 2, 1, 2, 2, 2, 0, 2) ARDL(2, 2, 2, 2, 2, 2, 0, 2) ARDL(2, 1, 2, 2, 2, 2, 0, 2) ARDL(2, 2, 2, 2, 2, 2, 1, 2) ARDL(2, 2, 1, 2, 2, 2, 1, 2) ARDL(2, 2, 2, 1, 2, 2, 0, 2) ARDL(2, 1, 1, 2, 2, 2, 0, 2) ARDL(2, 1, 1, 2, 2, 2, 2, 2) ARDL(2, 1, 2, 2, 2, 2, 1, 2) ARDL(2, 2, 2, 1, 2, 2, 1, 2) ARDL(2, 1, 1, 2, 2, 2, 1, 2) ARDL(2, 1, 1, 2, 2, 1, 2, 2) ARDL(2, 1, 0, 2, 2, 1, 2, 2) ARDL(2, 2, 2, 1, 2, 1, 2, 2) ARDL(2, 2, 2, 2, 2, 1, 2, 2) ARDL(2, 1, 0, 2, 2, 2, 2, 2)
Akaike Information Criteria (top 20 models)
Figure a5
oPTImal lag selecTIonfor IndonesIa Case I: without interaction term
Akaike Information Criteria (top 20 models) Case II: with interaction term Akaike Information Criteria (top 20 models)
-6.90 -6.88 -6.86 -6.84 -6.82 -6.80 -6.78
ARDL(2, 1, 2, 0, 0, 1, 2, 2) ARDL(1, 1, 2, 1, 0, 1, 2, 2) ARDL(2, 1, 2, 1, 0, 1, 2, 2) ARDL(2, 1, 2, 0, 1, 1, 2, 2) ARDL(2, 2, 2, 0, 0, 1, 2, 2) ARDL(1, 2, 2, 1, 0, 1, 2, 2) ARDL(2, 1, 2, 0, 0, 2, 2, 2) ARDL(1, 1, 2, 1, 0, 2, 2, 2) ARDL(1, 1, 2, 2, 0, 1, 2, 2) ARDL(2, 2, 2, 0, 1, 1, 2, 2) ARDL(2, 1, 2, 1, 1, 1, 2, 2) ARDL(2, 2, 2, 1, 0, 1, 2, 2) ARDL(1, 1, 2, 1, 1, 1, 2, 2) ARDL(2, 1, 2, 1, 0, 2, 2, 2) ARDL(1, 1, 2, 0, 0, 1, 2, 2) ARDL(2, 1, 2, 2, 0, 1, 2, 2) ARDL(2, 1, 2, 0, 1, 2, 2, 2) ARDL(1, 2, 2, 0, 0, 1, 2, 2) ARDL(2, 1, 2, 0, 0, 1, 1, 2) ARDL(2, 1, 2, 0, 2, 1, 2, 2)
Akaike Information Criteria (top 20 models)
-6.84 -6.80 -6.76 -6.72 -6.68 -6.64 -6.60 -6.56 -6.52 -6.48
ARDL(1, 2, 2, 2, 1, 2, 1, 1) ARDL(2, 2, 2, 2, 1, 2, 1, 1) ARDL(2, 2, 2, 2, 1, 2, 2, 2) ARDL(2, 2, 2, 2, 1, 2, 2, 1) ARDL(2, 2, 2, 2, 1, 2, 1, 2) ARDL(2, 2, 2, 2, 2, 2, 1, 1) ARDL(2, 2, 2, 2, 2, 2, 2, 2) ARDL(1, 2, 2, 2, 1, 2, 1, 2) ARDL(1, 2, 2, 2, 1, 2, 2, 1) ARDL(2, 2, 2, 2, 2, 2, 1, 2) ARDL(2, 2, 2, 2, 2, 2, 2, 1) ARDL(1, 2, 2, 2, 1, 2, 2, 2) ARDL(1, 2, 2, 2, 2, 2, 1, 1) ARDL(1, 2, 2, 2, 2, 2, 2, 1) ARDL(1, 2, 2, 2, 2, 2, 1, 2) ARDL(1, 2, 2, 2, 2, 2, 2, 2) ARDL(2, 2, 2, 2, 0, 2, 1, 1) ARDL(2, 2, 2, 2, 1, 1, 1, 1) ARDL(2, 2, 2, 2, 0, 2, 2, 1) ARDL(1, 2, 2, 2, 0, 2, 1, 1)
Akaike Information Criteria (top 20 models)
Figure a6
oPTImal lag selecTIonfor JaPan Case I: without interaction term
Akaike Information Criteria (top 20 models) Case II: with interaction term Akaike Information Criteria (top 20 models)
-6.62 -6.60 -6.58 -6.56 -6.54 -6.52 -6.50
ARDL(2, 2, 2, 2, 1, 0, 0, 0) ARDL(1, 2, 2, 2, 1, 0, 0, 0) ARDL(2, 2, 2, 2, 1, 0, 1, 0) ARDL(2, 2, 2, 2, 2, 0, 0, 0) ARDL(2, 2, 2, 2, 1, 0, 0, 1) ARDL(2, 2, 2, 2, 1, 1, 0, 0) ARDL(1, 2, 2, 2, 1, 1, 0, 0) ARDL(1, 2, 2, 2, 1, 0, 2, 0) ARDL(1, 2, 2, 2, 2, 0, 0, 0) ARDL(1, 2, 2, 2, 1, 0, 0, 1) ARDL(1, 2, 2, 2, 1, 0, 1, 0) ARDL(1, 2, 2, 2, 1, 2, 0, 0) ARDL(1, 2, 0, 2, 2, 1, 0, 0) ARDL(2, 2, 2, 2, 1, 2, 0, 0) ARDL(2, 2, 2, 2, 2, 0, 1, 0) ARDL(1, 2, 2, 2, 2, 1, 0, 0) ARDL(1, 2, 1, 2, 1, 2, 0, 0) ARDL(2, 2, 2, 1, 1, 0, 0, 0) ARDL(2, 2, 2, 2, 1, 0, 2, 0) ARDL(2, 2, 2, 2, 1, 1, 1, 0)
Akaike Information Criteria (top 20 models)
-6.70 -6.69 -6.68 -6.67 -6.66 -6.65 -6.64 -6.63
ARDL(1, 1, 2, 0, 2, 0, 2, 1) ARDL(1, 1, 2, 1, 2, 0, 2, 1) ARDL(1, 2, 2, 0, 1, 0, 0, 1) ARDL(2, 1, 2, 2, 1, 0, 0, 1) ARDL(1, 1, 2, 0, 2, 0, 2, 2) ARDL(2, 2, 2, 1, 1, 0, 0, 1) ARDL(1, 1, 2, 2, 1, 0, 0, 1) ARDL(1, 1, 2, 1, 1, 0, 2, 1) ARDL(1, 2, 0, 2, 1, 0, 0, 1) ARDL(2, 2, 2, 0, 1, 0, 0, 1) ARDL(1, 0, 2, 2, 1, 0, 0, 1) ARDL(2, 2, 0, 2, 1, 0, 0, 1) ARDL(1, 1, 2, 0, 1, 0, 2, 1) ARDL(1, 0, 2, 2, 0, 0, 0, 1) ARDL(1, 2, 2, 1, 1, 0, 0, 1) ARDL(1, 2, 2, 0, 2, 0, 0, 1) ARDL(1, 2, 2, 0, 1, 0, 0, 2) ARDL(1, 1, 2, 0, 2, 1, 2, 1) ARDL(1, 2, 2, 0, 0, 0, 0, 1) ARDL(1, 2, 2, 0, 1, 1, 0, 1)
Akaike Information Criteria (top 20 models)
Figure a7
oPTImal lag selecTIonfor korea Case I: without interaction term
Akaike Information Criteria (top 20 models) Case II: with interaction term Akaike Information Criteria (top 20 models)
-9.00 -8.96 -8.92 -8.88 -8.84 -8.80 -8.76
ARDL(1, 2, 2, 2, 2, 2, 2, 2) ARDL(1, 2, 2, 2, 2, 2, 1, 2) ARDL(2, 2, 2, 2, 2, 2, 2, 2) ARDL(2, 2, 2, 2, 2, 2, 1, 2) ARDL(1, 2, 2, 2, 2, 2, 1, 0) ARDL(1, 2, 2, 2, 2, 2, 1, 1) ARDL(2, 2, 2, 2, 2, 2, 2, 1) ARDL(2, 2, 2, 2, 2, 2, 1, 1) ARDL(1, 2, 2, 2, 2, 2, 2, 0) ARDL(1, 2, 2, 2, 0, 2, 1, 2) ARDL(1, 2, 2, 2, 2, 2, 2, 1) ARDL(2, 2, 2, 2, 1, 2, 2, 2) ARDL(2, 2, 2, 2, 1, 2, 2, 1) ARDL(1, 2, 2, 2, 2, 1, 1, 0) ARDL(1, 2, 2, 2, 1, 2, 2, 2) ARDL(2, 2, 2, 2, 2, 1, 2, 0) ARDL(2, 2, 2, 2, 2, 2, 1, 0) ARDL(2, 2, 2, 2, 2, 2, 2, 0) ARDL(2, 2, 2, 2, 2, 1, 1, 0) ARDL(1, 2, 2, 2, 1, 2, 1, 2)
Akaike Information Criteria (top 20 models)
-7.98 -7.96 -7.94 -7.92 -7.90 -7.88 -7.86
ARDL(2, 2, 1, 2, 2, 1, 2, 2) ARDL(2, 1, 2, 2, 2, 1, 2, 1) ARDL(2, 2, 2, 1, 2, 1, 2, 1) ARDL(2, 2, 2, 1, 2, 1, 1, 1) ARDL(2, 1, 2, 2, 2, 1, 1, 1) ARDL(2, 2, 1, 2, 2, 1, 1, 1) ARDL(2, 2, 2, 1, 2, 1, 2, 2) ARDL(2, 1, 2, 2, 2, 1, 2, 2) ARDL(2, 2, 1, 2, 2, 1, 1, 2) ARDL(2, 2, 2, 2, 2, 1, 2, 2) ARDL(2, 2, 1, 2, 2, 1, 2, 1) ARDL(2, 2, 1, 2, 2, 2, 2, 2) ARDL(2, 1, 2, 2, 2, 2, 2, 1) ARDL(2, 2, 2, 1, 2, 2, 2, 1) ARDL(2, 2, 2, 2, 2, 1, 2, 1) ARDL(2, 2, 2, 1, 2, 2, 1, 1) ARDL(2, 1, 2, 2, 2, 2, 1, 1) ARDL(2, 2, 2, 2, 2, 1, 1, 1) ARDL(2, 2, 1, 2, 2, 2, 1, 1) ARDL(2, 2, 1, 2, 2, 2, 1, 2)
Akaike Information Criteria (top 20 models)
Figure a8
oPTImal lag selecTIonfor malaysIa Case I: without interaction term
Akaike Information Criteria (top 20 models) Case II: with interaction term Akaike Information Criteria (top 20 models)
-8.84 -8.80 -8.76 -8.72 -8.68 -8.64 -8.60 -8.56 -8.52
ARDL(2, 2, 2, 1, 2, 2, 2, 0) ARDL(2, 2, 2, 1, 2, 2, 2, 1) ARDL(2, 2, 2, 2, 2, 2, 2, 0) ARDL(2, 2, 2, 1, 2, 2, 2, 2) ARDL(2, 2, 2, 0, 2, 2, 2, 0) ARDL(2, 2, 2, 2, 2, 2, 2, 1) ARDL(2, 2, 2, 2, 2, 2, 2, 2) ARDL(2, 2, 2, 0, 2, 2, 2, 1) ARDL(2, 2, 2, 1, 2, 2, 1, 0) ARDL(2, 2, 2, 0, 2, 2, 2, 2) ARDL(2, 2, 2, 1, 2, 2, 0, 0) ARDL(2, 2, 2, 2, 2, 2, 1, 0) ARDL(2, 2, 2, 1, 2, 2, 1, 1) ARDL(2, 1, 2, 1, 2, 2, 2, 0) ARDL(2, 2, 2, 2, 2, 2, 0, 0) ARDL(2, 2, 2, 1, 2, 2, 0, 1) ARDL(2, 1, 2, 1, 2, 2, 0, 0) ARDL(2, 1, 2, 1, 2, 2, 1, 0) ARDL(2, 1, 2, 2, 2, 2, 0, 0) ARDL(2, 1, 2, 2, 2, 2, 2, 0)
Akaike Information Criteria (top 20 models)
-9.66 -9.64 -9.62 -9.60 -9.58 -9.56 -9.54 -9.52 -9.50
ARDL(2, 2, 2, 2, 0, 2, 2, 2) ARDL(2, 2, 2, 2, 2, 2, 1, 2) ARDL(2, 2, 2, 2, 1, 2, 2, 2) ARDL(1, 2, 2, 2, 2, 1, 1, 1) ARDL(2, 2, 2, 2, 1, 0, 1, 2) ARDL(2, 2, 2, 2, 2, 2, 2, 2) ARDL(2, 2, 2, 2, 1, 1, 1, 2) ARDL(1, 2, 2, 2, 1, 0, 1, 2) ARDL(1, 2, 2, 2, 1, 1, 1, 2) ARDL(2, 2, 2, 2, 0, 2, 1, 2) ARDL(2, 2, 2, 2, 1, 0, 2, 2) ARDL(2, 2, 2, 2, 1, 2, 1, 2) ARDL(1, 2, 2, 2, 2, 1, 1, 2) ARDL(1, 2, 2, 2, 1, 0, 2, 2) ARDL(1, 2, 2, 2, 2, 0, 1, 1) ARDL(1, 2, 2, 2, 1, 1, 2, 2) ARDL(2, 2, 2, 2, 1, 1, 2, 2) ARDL(1, 2, 2, 2, 1, 1, 1, 1) ARDL(2, 2, 2, 2, 2, 1, 1, 1) ARDL(1, 2, 2, 2, 1, 2, 1, 1)
Akaike Information Criteria (top 20 models)
Figure a9
oPTImal lag selecTIonfor neW Zealand Case I: without interaction term
Akaike Information Criteria (top 20 models) Case II: with interaction term Akaike Information Criteria (top 20 models)
-10.28 -10.26 -10.24 -10.22 -10.20 -10.18
ARDL(1, 2, 0, 1, 1, 1, 2, 1) ARDL(1, 2, 0, 2, 1, 1, 2, 1) ARDL(1, 2, 0, 2, 1, 2, 2, 1) ARDL(1, 2, 0, 1, 1, 2, 2, 1) ARDL(2, 2, 0, 1, 1, 1, 2, 1) ARDL(2, 2, 0, 1, 1, 2, 2, 1) ARDL(2, 2, 0, 1, 2, 2, 2, 1) ARDL(2, 2, 1, 1, 2, 2, 2, 1) ARDL(1, 2, 0, 1, 2, 1, 2, 1) ARDL(1, 2, 0, 1, 1, 1, 2, 2) ARDL(2, 2, 0, 1, 2, 1, 2, 1) ARDL(1, 2, 0, 2, 2, 1, 2, 1) ARDL(1, 2, 1, 1, 1, 1, 2, 1) ARDL(1, 2, 0, 2, 2, 2, 2, 1) ARDL(1, 2, 0, 2, 1, 1, 2, 2) ARDL(1, 2, 0, 2, 1, 2, 2, 2) ARDL(2, 2, 0, 2, 1, 1, 2, 1) ARDL(1, 2, 1, 2, 1, 1, 2, 1) ARDL(2, 2, 0, 2, 1, 2, 2, 1) ARDL(1, 2, 0, 1, 1, 2, 2, 2)
Akaike Information Criteria (top 20 models)
-10.58 -10.57 -10.56 -10.55 -10.54 -10.53 -10.52 -10.51 -10.50 -10.49
ARDL(1, 1, 2, 1, 2, 2, 2, 0) ARDL(1, 1, 2, 1, 2, 2, 1, 0) ARDL(1, 1, 2, 1, 1, 2, 2, 0) ARDL(1, 1, 2, 1, 1, 2, 1, 0) ARDL(1, 2, 2, 2, 2, 2, 1, 0) ARDL(1, 1, 1, 1, 1, 2, 2, 0) ARDL(1, 2, 1, 2, 2, 2, 2, 0) ARDL(1, 2, 1, 2, 2, 2, 1, 0) ARDL(2, 2, 2, 2, 2, 2, 1, 0) ARDL(1, 1, 2, 1, 2, 2, 2, 1) ARDL(1, 2, 2, 1, 2, 2, 2, 0) ARDL(1, 1, 2, 2, 2, 2, 2, 0) ARDL(2, 1, 2, 1, 2, 2, 2, 0) ARDL(1, 1, 2, 2, 2, 2, 1, 0) ARDL(1, 1, 2, 1, 2, 2, 1, 1) ARDL(2, 1, 2, 1, 2, 2, 1, 0) ARDL(1, 2, 2, 1, 2, 2, 1, 0) ARDL(2, 2, 2, 2, 2, 2, 1, 1) ARDL(2, 1, 2, 1, 1, 2, 2, 0) ARDL(2, 2, 2, 2, 2, 2, 2, 1)
Akaike Information Criteria (top 20 models)
Figure a10
oPTImal lag selecTIonfor PakIsTan Case I: without interaction term
Akaike Information Criteria (top 20 models) Case II: with interaction term Akaike Information Criteria (top 20 models)
-10.28 -10.26 -10.24 -10.22 -10.20 -10.18
ARDL(1, 2, 0, 1, 1, 1, 2, 1) ARDL(1, 2, 0, 2, 1, 1, 2, 1) ARDL(1, 2, 0, 2, 1, 2, 2, 1) ARDL(1, 2, 0, 1, 1, 2, 2, 1) ARDL(2, 2, 0, 1, 1, 1, 2, 1) ARDL(2, 2, 0, 1, 1, 2, 2, 1) ARDL(2, 2, 0, 1, 2, 2, 2, 1) ARDL(2, 2, 1, 1, 2, 2, 2, 1) ARDL(1, 2, 0, 1, 2, 1, 2, 1) ARDL(1, 2, 0, 1, 1, 1, 2, 2) ARDL(2, 2, 0, 1, 2, 1, 2, 1) ARDL(1, 2, 0, 2, 2, 1, 2, 1) ARDL(1, 2, 1, 1, 1, 1, 2, 1) ARDL(1, 2, 0, 2, 2, 2, 2, 1) ARDL(1, 2, 0, 2, 1, 1, 2, 2) ARDL(1, 2, 0, 2, 1, 2, 2, 2) ARDL(2, 2, 0, 2, 1, 1, 2, 1) ARDL(1, 2, 1, 2, 1, 1, 2, 1) ARDL(2, 2, 0, 2, 1, 2, 2, 1) ARDL(1, 2, 0, 1, 1, 2, 2, 2)
Akaike Information Criteria (top 20 models)
-10.58 -10.57 -10.56 -10.55 -10.54 -10.53 -10.52 -10.51 -10.50 -10.49
ARDL(1, 1, 2, 1, 2, 2, 2, 0) ARDL(1, 1, 2, 1, 2, 2, 1, 0) ARDL(1, 1, 2, 1, 1, 2, 2, 0) ARDL(1, 1, 2, 1, 1, 2, 1, 0) ARDL(1, 2, 2, 2, 2, 2, 1, 0) ARDL(1, 1, 1, 1, 1, 2, 2, 0) ARDL(1, 2, 1, 2, 2, 2, 2, 0) ARDL(1, 2, 1, 2, 2, 2, 1, 0) ARDL(2, 2, 2, 2, 2, 2, 1, 0) ARDL(1, 1, 2, 1, 2, 2, 2, 1) ARDL(1, 2, 2, 1, 2, 2, 2, 0) ARDL(1, 1, 2, 2, 2, 2, 2, 0) ARDL(2, 1, 2, 1, 2, 2, 2, 0) ARDL(1, 1, 2, 2, 2, 2, 1, 0) ARDL(1, 1, 2, 1, 2, 2, 1, 1) ARDL(2, 1, 2, 1, 2, 2, 1, 0) ARDL(1, 2, 2, 1, 2, 2, 1, 0) ARDL(2, 2, 2, 2, 2, 2, 1, 1) ARDL(2, 1, 2, 1, 1, 2, 2, 0) ARDL(2, 2, 2, 2, 2, 2, 2, 1)
Akaike Information Criteria (top 20 models)
Figure a11
oPTImal lag selecTIonfor PhIlIPPInes Case I: without interaction term
Akaike Information Criteria (top 20 models) Case II: with interaction term Akaike Information Criteria (top 20 models)
-11.80 -11.78 -11.76 -11.74 -11.72 -11.70 -11.68 -11.66 -11.64
ARDL(1, 1, 2, 2, 2, 2, 1, 2) ARDL(2, 1, 2, 2, 2, 2, 1, 2) ARDL(2, 1, 2, 2, 2, 2, 2, 2) ARDL(1, 1, 2, 2, 2, 2, 2, 2) ARDL(1, 2, 2, 2, 2, 2, 1, 2) ARDL(1, 1, 2, 2, 0, 2, 2, 2) ARDL(1, 2, 2, 2, 2, 2, 2, 2) ARDL(2, 2, 2, 2, 2, 2, 1, 2) ARDL(1, 1, 2, 2, 2, 2, 2, 1) ARDL(2, 1, 2, 2, 2, 2, 0, 2) ARDL(2, 2, 2, 2, 2, 2, 2, 2) ARDL(1, 2, 2, 2, 2, 2, 2, 1) ARDL(2, 1, 2, 2, 0, 2, 2, 2) ARDL(2, 1, 2, 2, 2, 2, 2, 1) ARDL(1, 1, 2, 2, 2, 2, 1, 1) ARDL(1, 2, 2, 2, 0, 2, 2, 2) ARDL(1, 1, 2, 2, 1, 2, 2, 2) ARDL(2, 2, 2, 2, 2, 2, 0, 2) ARDL(1, 2, 2, 2, 2, 2, 2, 0) ARDL(1, 1, 2, 2, 0, 2, 1, 2)
Akaike Information Criteria (top 20 models)
-11.02 -11.00 -10.98 -10.96 -10.94 -10.92 -10.90 -10.88
ARDL(2, 2, 2, 2, 0, 2, 0, 2) ARDL(1, 2, 2, 2, 2, 2, 2, 2) ARDL(2, 2, 2, 2, 2, 2, 2, 2) ARDL(2, 2, 2, 2, 0, 2, 1, 2) ARDL(2, 2, 2, 2, 1, 2, 0, 2) ARDL(1, 2, 2, 2, 2, 2, 0, 2) ARDL(2, 2, 2, 2, 2, 2, 0, 2) ARDL(1, 2, 2, 2, 0, 2, 0, 2) ARDL(2, 2, 2, 2, 1, 2, 1, 2) ARDL(1, 1, 1, 1, 2, 2, 0, 2) ARDL(2, 1, 1, 1, 2, 2, 0, 2) ARDL(2, 2, 2, 2, 0, 2, 2, 2) ARDL(1, 1, 2, 1, 2, 2, 0, 0) ARDL(1, 1, 0, 1, 2, 2, 0, 2) ARDL(1, 1, 2, 1, 2, 2, 0, 2) ARDL(1, 1, 2, 2, 2, 2, 0, 0) ARDL(1, 2, 2, 2, 2, 2, 1, 2) ARDL(1, 2, 2, 1, 2, 2, 0, 0) ARDL(2, 2, 2, 2, 2, 2, 1, 2) ARDL(2, 1, 1, 1, 0, 2, 0, 2)
Akaike Information Criteria (top 20 models)
Figure a12
oPTImal lag selecTIonfor sIngaPore Case I: without interaction term
Akaike Information Criteria (top 20 models) Case II: with interaction term Akaike Information Criteria (top 20 models)
-8.9 -8.8 -8.7 -8.6 -8.5 -8.4 -8.3
ARDL(2, 2, 0, 0, 2, 2, 2, 2) ARDL(2, 2, 0, 1, 2, 2, 2, 2) ARDL(2, 2, 2, 0, 2, 2, 2, 2) ARDL(2, 2, 1, 0, 2, 2, 2, 2) ARDL(2, 2, 2, 1, 2, 2, 2, 2) ARDL(2, 2, 1, 1, 2, 2, 2, 2) ARDL(2, 2, 0, 2, 2, 2, 2, 2) ARDL(2, 2, 2, 2, 2, 2, 2, 2) ARDL(2, 2, 1, 2, 2, 2, 2, 2) ARDL(1, 2, 0, 0, 2, 2, 2, 2) ARDL(1, 2, 0, 1, 2, 2, 2, 2) ARDL(2, 1, 2, 1, 2, 2, 2, 2) ARDL(1, 2, 1, 0, 2, 2, 2, 2) ARDL(1, 2, 1, 1, 2, 2, 2, 2) ARDL(1, 2, 2, 0, 2, 2, 2, 2) ARDL(1, 2, 0, 2, 2, 2, 2, 2) ARDL(2, 1, 0, 1, 2, 2, 2, 2) ARDL(1, 2, 1, 2, 2, 2, 2, 2) ARDL(2, 1, 2, 2, 2, 2, 2, 2) ARDL(1, 2, 2, 1, 2, 2, 2, 2) Akaike Information Criteria (top 20 models)
-9.00 -8.95 -8.90 -8.85 -8.80 -8.75 -8.70
ARDL(2, 0, 2, 2, 2, 2, 2, 2) ARDL(2, 2, 2, 0, 2, 2, 2, 2) ARDL(2, 2, 1, 0, 2, 2, 2, 2) ARDL(2, 1, 2, 2, 2, 2, 2, 2) ARDL(2, 2, 2, 1, 2, 2, 2, 2) ARDL(2, 0, 1, 2, 2, 2, 2, 2) ARDL(2, 2, 1, 1, 2, 2, 2, 2) ARDL(2, 2, 1, 2, 2, 2, 2, 2) ARDL(2, 1, 1, 2, 2, 2, 2, 2) ARDL(2, 2, 0, 2, 2, 2, 2, 2) ARDL(2, 2, 2, 2, 2, 2, 2, 2) ARDL(2, 2, 0, 0, 2, 2, 2, 2) ARDL(1, 2, 1, 1, 2, 2, 2, 2) ARDL(2, 0, 0, 2, 2, 2, 2, 2) ARDL(1, 1, 1, 2, 2, 2, 2, 2) ARDL(2, 2, 0, 1, 2, 2, 2, 2) ARDL(1, 2, 1, 2, 2, 2, 2, 2) ARDL(2, 1, 0, 2, 2, 2, 2, 2) ARDL(1, 2, 2, 1, 2, 2, 2, 2) ARDL(1, 1, 2, 2, 2, 2, 2, 2)
Akaike Information Criteria (top 20 models)
Figure a13
oPTImal lag selecTIonfor srI lanka Case I: without interaction term
Akaike Information Criteria (top 20 models) Case II: with interaction term Akaike Information Criteria (top 20 models)
-7.88 -7.86 -7.84 -7.82 -7.80 -7.78 -7.76 -7.74 -7.72
ARDL(2, 2, 1, 2, 2, 2, 2, 0) ARDL(2, 2, 2, 2, 2, 2, 2, 0) ARDL(1, 2, 1, 2, 2, 1, 2, 2) ARDL(1, 2, 1, 2, 1, 2, 2, 2) ARDL(2, 2, 1, 2, 2, 1, 2, 2) ARDL(2, 2, 1, 2, 2, 2, 2, 1) ARDL(1, 2, 1, 2, 2, 2, 2, 0) ARDL(2, 2, 1, 2, 2, 1, 2, 0) ARDL(1, 2, 1, 2, 1, 1, 2, 2) ARDL(2, 2, 2, 2, 2, 2, 2, 1) ARDL(2, 2, 1, 2, 1, 2, 2, 2) ARDL(2, 2, 2, 2, 2, 1, 2, 2) ARDL(1, 2, 2, 2, 2, 1, 2, 2) ARDL(1, 2, 1, 2, 2, 2, 2, 2) ARDL(2, 2, 1, 2, 2, 2, 2, 2) ARDL(2, 2, 1, 2, 2, 1, 2, 1) ARDL(1, 2, 2, 2, 1, 2, 2, 2) ARDL(2, 2, 1, 2, 1, 1, 2, 2) ARDL(2, 2, 2, 2, 2, 1, 2, 0) ARDL(1, 2, 2, 2, 1, 1, 2, 2)
Akaike Information Criteria (top 20 models)
-9.04 -9.00 -8.96 -8.92 -8.88 -8.84 -8.80
ARDL(2, 2, 2, 2, 0, 1, 1, 0) ARDL(2, 2, 2, 2, 0, 2, 1, 0) ARDL(2, 2, 2, 2, 0, 1, 1, 1) ARDL(2, 2, 2, 2, 0, 1, 2, 0) ARDL(2, 2, 2, 2, 1, 1, 1, 0) ARDL(2, 2, 2, 2, 0, 2, 1, 1) ARDL(2, 2, 2, 2, 0, 1, 1, 2) ARDL(2, 2, 2, 2, 1, 2, 1, 0) ARDL(2, 2, 2, 2, 0, 2, 2, 0) ARDL(2, 2, 2, 2, 1, 1, 1, 1) ARDL(2, 2, 2, 2, 0, 1, 2, 1) ARDL(2, 2, 2, 2, 2, 1, 1, 0) ARDL(2, 2, 2, 2, 1, 1, 2, 0) ARDL(2, 2, 2, 2, 0, 2, 1, 2) ARDL(2, 2, 2, 2, 2, 2, 1, 0) ARDL(2, 2, 2, 2, 0, 2, 2, 1) ARDL(2, 2, 2, 2, 1, 2, 1, 1) ARDL(2, 2, 2, 2, 0, 1, 2, 2) ARDL(2, 2, 2, 2, 1, 1, 1, 2) ARDL(2, 2, 2, 2, 2, 1, 1, 1)
Akaike Information Criteria (top 20 models)
Figure a14
oPTImal lag selecTIonfor ThaIland Case I: without interaction term
Akaike Information Criteria (top 20 models) Case II: with interaction term Akaike Information Criteria (top 20 models)
-10.82 -10.80 -10.78 -10.76 -10.74 -10.72 -10.70 -10.68
ARDL(2, 1, 1, 2, 2, 2, 1, 1) ARDL(2, 0, 1, 2, 2, 2, 1, 1) ARDL(2, 1, 1, 2, 2, 2, 1, 2) ARDL(2, 0, 0, 2, 2, 2, 1, 2) ARDL(2, 1, 2, 2, 2, 2, 1, 1) ARDL(2, 1, 1, 2, 2, 2, 2, 1) ARDL(2, 2, 1, 2, 2, 2, 1, 1) ARDL(2, 0, 0, 2, 2, 2, 1, 1) ARDL(2, 1, 0, 2, 2, 2, 1, 2) ARDL(2, 2, 0, 2, 2, 2, 1, 2) ARDL(2, 0, 0, 2, 2, 2, 1, 0) ARDL(2, 2, 1, 2, 2, 2, 1, 0) ARDL(2, 2, 0, 2, 2, 2, 1, 0) ARDL(2, 0, 1, 2, 2, 2, 1, 2) ARDL(2, 0, 1, 2, 2, 2, 2, 1) ARDL(2, 2, 0, 2, 2, 0, 1, 2) ARDL(2, 1, 0, 2, 2, 2, 1, 1) ARDL(2, 0, 0, 2, 2, 2, 2, 2) ARDL(2, 0, 2, 2, 2, 2, 1, 1) ARDL(2, 2, 1, 2, 2, 0, 1, 2)
Akaike Information Criteria (top 20 models)
-11.1 -11.0 -10.9 -10.8 -10.7 -10.6 -10.5 -10.4
ARDL(2, 2, 2, 2, 2, 2, 2, 2) ARDL(2, 2, 2, 2, 2, 2, 1, 2) ARDL(2, 1, 2, 2, 2, 2, 2, 2) ARDL(2, 2, 2, 2, 1, 2, 1, 2) ARDL(2, 1, 2, 2, 2, 2, 1, 2) ARDL(2, 2, 2, 2, 1, 2, 2, 2) ARDL(2, 2, 2, 1, 2, 2, 2, 2) ARDL(2, 2, 1, 2, 2, 2, 2, 2) ARDL(2, 2, 1, 1, 2, 2, 2, 2) ARDL(1, 2, 2, 2, 1, 2, 1, 2) ARDL(1, 2, 2, 2, 2, 2, 1, 2) ARDL(2, 2, 2, 1, 2, 2, 1, 2) ARDL(1, 2, 2, 2, 1, 2, 2, 2) ARDL(1, 2, 2, 2, 2, 2, 2, 2) ARDL(2, 2, 1, 2, 2, 2, 1, 2) ARDL(2, 2, 1, 1, 2, 2, 1, 2) ARDL(1, 2, 2, 2, 2, 2, 0, 2) ARDL(1, 2, 2, 2, 1, 2, 0, 2) ARDL(1, 1, 2, 2, 2, 2, 0, 1) ARDL(1, 2, 2, 2, 0, 2, 1, 2)
Akaike Information Criteria (top 20 models)
Figure a15
oPTImal lag selecTIonfor vIeTnam Case I: without interaction term
Akaike Information Criteria (top 20 models) Case II: with interaction term Akaike Information Criteria (top 20 models)
Appendix B
-10.0 -7.5 -5.0 -2.5 0.0 2.5 5.0 7.5 10.0
2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 CUSUM 5% Significance
-0.4 0.0 0.4 0.8 1.2 1.6
2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 CUSUM of Squares 5% Significance
Figure b1
sTabIlITy TesTsof ardl modelfor ausTralIa Case I: CUSUM Test Case II: CUSUMSQ Test
-10.0 -7.5 -5.0 -2.5 0.0 2.5 5.0 7.5 10.0
2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 CUSUM 5% Significance
-0.4 0.0 0.4 0.8 1.2 1.6
2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 CUSUM of Squares 5% Significance
Figure b2
sTabIlITy TesTsof ardl modelfor bangladesh
-8 -6 -4 -2 0 2 4 6 8
2015 2016 2017 2018 2019 2020
CUSUM 5% Significance
-0.4 0.0 0.4 0.8 1.2 1.6
2015 2016 2017 2018 2019 2020
CUSUM of Squares 5% Significance
Figure b3
sTabIlITy TesTsof ardl modelfor chIna
-8 -6 -4 -2 0 2 4 6 8
2015 2016 2017 2018 2019 2020
CUSUM 5% Significance
-0.4 0.0 0.4 0.8 1.2 1.6
2015 2016 2017 2018 2019 2020
CUSUM of Squares 5% Significance
Figure b4
sTabIlITy TesTsof ardl modelfor IndIa
-10.0 -7.5 -5.0 -2.5 0.0 2.5 5.0 7.5 10.0
2013 2014 2015 2016 2017 2018 2019 2020
CUSUM 5% Significance
-0.4 0.0 0.4 0.8 1.2 1.6
2013 2014 2015 2016 2017 2018 2019 2020
CUSUM of Squares 5% Significance
Figure b5
sTabIlITy TesTsof ardl modelfor IndonesIa
-10.0 -7.5 -5.0 -2.5 0.0 2.5 5.0 7.5 10.0
10 11 12 13 14 15 16 17 18 19 20
CUSUM 5% Significance
-0.4 0.0 0.4 0.8 1.2 1.6
10 11 12 13 14 15 16 17 18 19 20
CUSUM of Squares 5% Significance
Figure b6
sTabIlITy TesTsof ardl modelfor JaPan
-12 -8 -4 0 4 8 12
09 10 11 12 13 14 15 16 17 18 19 20
CUSUM 5% Significance
-0.4 0.0 0.4 0.8 1.2 1.6
09 10 11 12 13 14 15 16 17 18 19 20
CUSUM of Squares 5% Significance
Figure b7
sTabIlITy TesTsof ardl modelfor korea
-10.0 -7.5 -5.0 -2.5 0.0 2.5 5.0 7.5 10.0
2013 2014 2015 2016 2017 2018 2019 2020
CUSUM 5% Significance
-0.4 0.0 0.4 0.8 1.2 1.6
2013 2014 2015 2016 2017 2018 2019 2020
CUSUM of Squares 5% Significance
Figure b8
sTabIlITy TesTsof ardl modelfor malaysIa
-8 -6 -4 -2 0 2 4 6 8
2016 2017 2018 2019 2020
CUSUM 5% Significance
-0.4 0.0 0.4 0.8 1.2 1.6
2016 2017 2018 2019 2020
CUSUM of Squares 5% Significance
Figure b9
sTabIlITy TesTsof ardl modelfor neW Zealand
-10.0 -7.5 -5.0 -2.5 0.0 2.5 5.0 7.5 10.0
2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 CUSUM 5% Significance
-0.4 0.0 0.4 0.8 1.2 1.6
2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 CUSUM of Squares 5% Significance
Figure b10
sTabIlITy TesTsof ardl modelfor PakIsTan
-10.0 -7.5 -5.0 -2.5 0.0 2.5 5.0 7.5 10.0
2013 2014 2015 2016 2017 2018 2019 2020
CUSUM 5% Significance
-0.4 0.0 0.4 0.8 1.2 1.6
2013 2014 2015 2016 2017 2018 2019 2020
CUSUM of Squares 5% Significance
Figure b11
sTabIlITy TesTsof ardl modelfor PhIlIPPInes
-10.0 -7.5 -5.0 -2.5 0.0 2.5 5.0 7.5 10.0
2012 2013 2014 2015 2016 2017 2018 2019 2020 CUSUM 5% Significance
-0.4 0.0 0.4 0.8 1.2 1.6
2012 2013 2014 2015 2016 2017 2018 2019 2020 CUSUM of Squares 5% Significance
Figure b12
sTabIlITy TesTsof ardl modelfor sIngaPore
-8 -6 -4 -2 0 2 4 6 8
2016 2017 2018 2019 2020
CUSUM 5% Significance
-0.4 0.0 0.4 0.8 1.2 1.6
2016 2017 2018 2019 2020
CUSUM of Squares 5% Significance
Figure b13
sTabIlITy TesTsof ardl modelfor srI lanka
-10.0 -7.5 -5.0 -2.5 0.0 2.5 5.0 7.5 10.0
10 11 12 13 14 15 16 17 18 19 20
CUSUM 5% Significance
-0.4 0.0 0.4 0.8 1.2 1.6
10 11 12 13 14 15 16 17 18 19 20
CUSUM of Squares 5% Significance
Figure b14
sTabIlITy TesTsof ardl modelfor ThaIland
References
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Acemoglu, D., and Autor, D. “Skills, Tasks and technologies: implications for employment and earnings.” in: Ashenfelter, O., and Card, D.
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-10.0 -7.5 -5.0 -2.5 0.0 2.5 5.0 7.5 10.0
2013 2014 2015 2016 2017 2018 2019 2020
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CUSUM of Squares 5% Significance
Figure b15
sTabIlITy TesTsof ardl modelfor vIeTnam
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