# Energy Consumption and Financial Development in NAFTA Countries, 1971-2015
## 5 Conclusions  
From 1970 to the present, the world population has doubled, going from 3686 to 7185 million people by 2017 [2]. Due to the above, it is important to consider that energy is used to produce most of the goods and services that satisfy the wishes and needs of this world population, so it is crucial to know its determinants. This article analyzes the relationship between energy consumption, economic growth, urbanization, prices, and financial development in the member countries of the North American Free Trade Agreement (NAFTA) from 1971-2015. The cross-section dependence test of Pesaran [36], second generation unit root tests, and cointegration tests were applied. The main contribution of this article is to demonstrate how some variables (e.g., economic growth, trade, urbanization, financial development and prices) determine the behavior of energy consumption in the three countries of the region of North America. The results show that the variables have cross-section dependence, are integrated in order one, and that there is an equilibrium or long-term relationship between them. The long-term elasticities show a positive relationship between the GDP and the EC, which implies that greater economic activity generates greater energy consumption. On the other hand, there is a negative relationship between EC and the variables FD, CPI, URB, and TO. The economic growth in the member countries of NAFTA is occurring efficiently, and more efficient trading goods and services in the region also reduces energy consumption. The benefits of urbanization, such as economies of scale in goods and \begin{table}
\begin{tabular}{c c c} \hline \hline
**Null Hypothesis** & **Wald Test** & **Decision** \\ \hline
**FD does not homogeneously cause EC** & 5.61 *** & Reject \\
**EC does not homogeneously cause FD** & 5.71 *** & Reject \\
**CPI does not homogeneously cause EC** & 10.70 *** & Reject \\
**EC does not homogeneously cause CPI** & 8.31 *** & Reject \\
**GDP does not homogeneously cause EC** & 2.78 & Accept \\
**EC does not homogeneously cause GDP** & 3.22 & Accept \\
**URB does not homogeneously cause EC** & 2.45 & Accept \\
**EC does not homogeneously cause URB** & 3.92 & Accept \\
**TO does not homogeneously cause EC** & 7.25 *** & Reject \\
**EC does not homogeneously cause TO** & 3.02 & Accept \\
**CPI does not homogeneously cause FD** & 2.70 & Accept \\ FD does not homogeneously cause CPI** & 1.74 & Accept \\ GDP does not homogeneously cause FD** & 7.69 *** & Reject \\ FD does not homogeneously cause GDP** & 2.79 & Accept \\
**URB does not homogeneously cause FD** & 4.55 * & Reject \\
**FD does not homogeneously cause URB** & 4.46 * & Reject \\
**TO does not homogeneously cause FD** & 3.65 & Accept \\
**FD does not homogeneously cause TO** & 2.55 & Accept \\ GDP does not homogeneously cause CPI** & 9.52 *** & Reject \\
**CPI does not homogeneously cause GDP** & 11.90 *** & Reject \\
**URB does not homogeneously cause CPI** & 4.73 ** & Reject \\
**CPI does not homogeneously cause URB** & 4.82 ** & Reject \\
**TO does not homogeneously cause CPI** & 2.79 & Accept \\
**CPI does not homogeneously cause TO** & 18.30 *** & Reject \\
**URB does not homogeneously cause GDP** & 9.11 *** & Reject \\ GDP does not homogeneously cause URB** & 4.50 * & Reject \\
**TO does not homogeneously cause GDP** & 4.52 * & Reject \\
**GDP does not homogeneously cause TO** & 8.01 *** & Reject \\
**TO does not homogeneously cause URB** & 6.56 *** & Reject \\
**URB does not homogeneously cause TO** & 5.62 *** & Reject \\ \hline \hline \end{tabular} Note: ***, ** and * denote the rejection of the null hypothesis at the 1%, 5% and 10% levels, respectively.  
\end{table} 
Table 7: Results of the heterogeneous causality test. services, help reduce environmental damage. The policies of these countries can help reduce energy consumption and environmental degradation by promoting financial development, urbanization, and trade openness. This study can be improved by including more indicators that measure financial development and non-linear models.