# Energy Consumption and Financial Development in NAFTA Countries, 1971-2015
## 4 Data and Analysis of Results
\begin{table}
\begin{tabular}{c c} \hline \hline
**Test** & **_t_-Statistic \\ \hline ADF & \(-\)3.021 *** \\ _p_-value & (0.000) \\ \hline \hline \end{tabular} Notes: *** denotes the rejection of the null hypothesis at the 1% level.  
\end{table} 
Table 3: Results of the Kao cointegration test. produce estimators of coefficients that are asymptotically unbiased and normally distributed [32; 33]. The FMOLS estimator behaves relatively well and even in small samples, it generates consistent estimates and allows controlling the endogeneity of its regressors and the serial correlation [32]. Due to the above, this research will use both FMOLS and DOLS estimators for cointegrated heterogeneous panels. According to Table 5, with the FMOLS and DOLS estimators, all the variables are statistically significant at the 1% and 5% levels of significance. The long-term elasticities show a positive relationship between the GDP and the EC, which implies that greater economic activity generates a greater energy consumption, as expected. On the other hand, there is a negative relationship between FD, CPI, URB, and TO with respect to EC, which implies that any increase in these variables reduces EC and, therefore, decreases of the environmental degradation in the member countries of NAFTA (Figure 2). The economic growth in the member countries of NAFTA is occurring efficiently; that is, less energy is consumed to increase or maintain production levels. More efficient traded goods and services in terms of their energy consumption in the region also improves environmental conditions. The benefits of urbanization, such as economies of scale in services of public transportation, water, electricity, education, and health [38], help reduce environmental damage in the member countries of NAFTA. Then, the results of this paper show that there is a negative relationship between energy consumption and financial development in the case of NAFTA countries. In relation to other studies, a negative relationship between these variables is also found in [PERSON] and [PERSON] [16] for the United States; [PERSON] and [PERSON] [22] in the case of China. A positive relationship is found in [PERSON] and Topcu [15] for the countries of the European Union (EU) when only old members are included; [PERSON] and [PERSON] [10] for Pakistan; [PERSON] et al. [18] for Saudi Arabia; [PERSON] [3] when stock market variables are used in 22 emerging countries; [PERSON] and [PERSON] [23] for the Gulf Cooperation Council countries; [PERSON] [4] for a sample of 9 Central and Eastern European frontier economies. Therefore, the member countries of NAFTA should encourage economic policies that promote trade openness, urbanization, and financial development, which will reduce the demand for energy and pollutant emissions. There must be a causal relationship in at least one direction after confirming the existence of a long-term relationship between the variables [34]. \begin{table}
\begin{tabular}{c c c} \hline
**Null Hypothesis** & **Trace Test** & **Max-Eigen Test** \\ \hline \(R=0\) & 61.34 *** & 27.76 *** \\ \(R\leq 1\) & 36.65 *** & 17.77 *** \\ \(R\leq 2\) & 22.68 *** & 9.54 \\ \(R\leq 3\) & 17.23 *** & 9.79 \\ \hline \end{tabular}  
* Notes: *** denotes the rejection of the null hypothesis at the 1% level.  
\end{table} 
Table 4: Results of the Fisher-Johansen cointegration test. \begin{table}
\begin{tabular}{c c c} \hline
**Variable** & **DOLS Coefficients** & **FMOLS Coefficients** \\ \hline FD & \(-\)0.156 *** & \(-\)0.193 *** \\ CPI & \(-\)0.100 *** & \(-\)0.112 *** \\ GDP & 1.281 *** & 1.353 *** \\ URB & \(-\)0.838 *** & \(-\)0.959 *** \\ TO & \(-\)0.286 *** & \(-\)0.300 *** \\ \hline \end{tabular}  
* Note: *** and ** denote statistical significance at the 1% and 5% levels, respectively.  
\end{table} 
Table 5: Estimation of long-term coefficients.