Examining the relationship between electricity consumption, financial development and economic growth in ASEAN countries: Evidence from a bayesian analysis

an between 0.7 and 1, electricity consumption 
and financial development exert a powerfully positive effect 
on economic growth. The 95% credible intervals also point to 
similar results. Thus, we can confirm that the value of 0.7951 of 
the coefficient for LnEC belongs to the interval [0.6587, 0.9315] 
with a 95% probability. Similar interpretations can be made for 
the remaining parameters of the model. With a probability of mean 
Table 2: Bayesian information criteria
Model Gaussian distribution DIC log(ML) log(BF)
1 N(0,1) 103.8528 −75.6626
2 N(0,10) 104.0392 −79.5551 -3.8924
3 N(0,100) 104.0978 −85.1067 -9.4441
4 N(0,1000) 104.1043 −90.8425 −15.1799
5 N(0,10000) 104.1050 −96.5969 −20.9342
Table 3: Bayesian model tests
Model Gaussian distribution log(ML) P(M) P(My)
1 N(0,1) −75.6626 0.2000 0.9799
2 N(0,10) −79.5551 0.2000 0.0200
3 N(0,100) −85.1067 0.2000 0.0001
4 N(0,1000) −90.8425 0.2000 0.0000
5 N(0,10000) −96.5969 0.2000 0.0000
Table 4: Gelman-rubin convergence diagnostic
Max gelman-rubin Rc=1.000142 
<Convergence rule (=1.1)
Rc value
Dependent variable: LnGDP 
LnEC 1.000142
LnFI 1.00009
LnECFI 1.000076
UB 1.00008
Intercept 1.00013
var 0.999963
Table 5: FEM, REM and Bayesian simulation results
Variables Coefficient P_value Coefficient P_value
FEM result REM result
LnEC 0.8324 0.000 0.7461 0.000
LnFI 0.5715 0.000 0.6298 0.000
LnECFI −0.0824 0.000 -0.0891 0.000
UB −0.009 0.000 0.0054 0.021
Intercept 2.916 0.000 2.7009 0.000
F-test F-statistic=254.24 (P_value = 0.000)
Hausman test F-statistic=467.59 (P_value = 0.000)
Variables Mean Bayesian result
Std. Dev. MCSE Probability of mean>0 Equal-tailed (95% Cred. Interval)
Dependent variable: LnGDP
LnEC 0.7951 0.0691 0.0004 1 (0.6587, 0.9315)
LnFI 1.0226 0.1652 0.0009 1 (0.6983, 1.3473)
LnECFI -0.1469 0.0230 0.0001 1* (−0.1919, −0.1019)
UB 0.0251 0.0016 0.0000 1 (0.0221, 0.0280)
Intercept 1.3753 0.4849 0.0028 0.99 (0.4216, 2.3275)
* is probability of mean < 0
Hoang: Examining the Relationship between Electricity Consumption, Financial Development and Economic Growth in Asean Countries: Evidence from a Bayesian Analysis
International Journal of Energy Economics and Policy | Vol 11 • Issue 2 • 202154
is one, we can state that urbanization is a good contribution to 
economic growth in examined countries.
4.5. The Causality Test
Finally, the study used Dumitrescu and Hurlin (2012) test to 
examine the causality relationship between energy consumption 
and economic growth. Both the W-bar and Z-bar statistic test 
presented in Table 6 provides evidence in favor of the rejection 
of the null hypothesis (P_value < 0.05). This result implies that 
there is a uni-directional causality running from economic growth 
to energy consumption in examined countries, which supported 
the Conversation hypothesis.
5. DISCUSSION
The empirical result shows that the impact of financial 
development and electricity consumption on economic growth is 
beneficial. These results are in line with the conclusion by Ben 
Jedidia et al. (2014) for Tunisia, Sarkar et al. (2019) for Malaysia, 
Glasure and Lee (1997) for South Korea and Singapore, or Long 
et al. (2018); Ngoc (2019); Nguyen and Ngoc (2020) for Vietnam. 
Physical capital accumulation and a developed financial system 
will enhance economic growth through the process of mobilizing 
and allocating the saving capital flows into projects, which have 
high productivity or output. All six countries in our sample are 
developing or developed countries, so the demand for production, 
distribution, or household consumption is rapid growth. According 
to the forecasting of the International Energy Agency, the energy 
demand is growing by 1.4% per year until 2035. This is valid for 
both emerging or developed countries.
6. CONCLUSION
The study applies the Bayesian approach via the Metropolis-
Hasting and Gibbs samplers as the MCMC methods to investigate 
the impact of financial development and electricity consumption 
on economic growth in ASEAN+6 countries over the period 1980 
to 2016. Five simulations are conducted with Gaussian prior 
distributions ranging from (0,1) to (0,10000). As shown by model 
comparison results via a Bayes factor and a model test, the model 
with a noninformative, namely, N(0,1) prior fits the best. According 
to the estimation results, we claim in view of the probability that 
both electricity consumption and financial development strongly 
and positively affects economic growth.
Based on the empirical results, some policy implications are 
suggested, as detailed:
Firstly, electricity consumption is beneficial for growth, so the 
Government should intend to expand energy supply through the 
development of renewable or green energies, such as solar, wind, 
biofuels, and geothermal power.
Secondly, financial development will drive economic growth if 
the country has a transparent and efficient financial system. Thus, 
the rate of the money supply should be calculated corresponding 
to the rate of growth. A deficiency in the money supply will result 
in a decrease in economic growth, negatively impacting other 
economic activities.
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