## 5 Results and Discussions
### Long-Run Analysis Results  
Long-run analysis results are interpreted in Table 5.  
Focusing on the elasticity of the variables in the long-run analysis, the results revealed that the electricity access to the total population of Pakistan has a positive and significant impact, as the economic growth has a coefficient of 1.310100 with a p-value of 0.6983. Similarly, \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{4}{c}{**Trace Statistic**} \\ \hline
**Hypothesized No. of CE(s)** & **Eigenvalue** & **Trace Statistic** & **0.05 Critical Value** & **Prob.\({}^{**}\)** \\ \hline None * & 0.993717 & 396.7264 & 143.6691 & 0.0000 \\ At most 1 * & 0.976870 & 269.9806 & 111.7805 & 0.0000 \\ At most 2 * & 0.944234 & 175.8151 & 83.93712 & 0.0000 \\ At most 3 * & 0.816141 & 103.6505 & 60.06141 & 0.0000 \\ At most 4 * & 0.738330 & 61.31087 & 40.17493 & 0.0001 \\ At most 5 * & 0.562836 & 27.79407 & 24.27596 & 0.0173 \\ At most 6 & 0.247014 & 7.107881 & 12.32090 & 0.3145 \\ At most 7 & 0.000607 & 0.015170 & 4.129906 & 0.9198 \\ \hline \multicolumn{4}{c}{**Maximum Eigenvalue Statistic**} \\ \hline
**Hypothesized No. of CE(s)** & **Eigenvalue** & **Max-Eigen Statistic** & **0.05 Critical Value** & **Prob.\({}^{**}\)** \\ \hline None * & 0.993717 & 126.7458 & 48.87720 & 0.0000 \\ At most 1 * & 0.976870 & 94.16546 & 42.77219 & 0.0000 \\ At most 2 * & 0.944234 & 72.16461 & 36.63019 & 0.0000 \\ At most 3 * & 0.816141 & 42.33964 & 30.43961 & 0.0011 \\ At most 4 * & 0.738330 & 33.51680 & 24.15921 & 0.0020 \\ At most 5 * & 0.562836 & 20.68619 & 17.79730 & 0.0179 \\ At most 6 & 0.247014 & 7.092710 & 11.22480 & 0.2415 \\ At most 7 & 0.000607 & 0.015170 & 4.129906 & 0.9198 \\ \hline \hline \end{tabular}  
* Denotes rejection of the hypothesis at the 0.05 level, ** MacKinnon–Haug–Michelis (1999) \(p\)-values.  
\end{table} 
Table 4: Results of the Johansen Cointegration test Using Trace Statistic and Maximum Eigenvalues. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{4}{c}{**ARDL Cointegrating and Long-Run Form**} \\ \hline
**Variables** & **Coefficient** & **Std. Error** & **t-Statistic** & **Prob.** \\ \hline D(LINEAR) & \(-1.828790\) & \(1.992169\) & \(-0.917989\) & 0.3783 \\ D(LINEAR) & \(1.179909\) & \(1.159803\) & \(1.017336\) & 0.3308 \\ D(LINEAR) & \(0.184181\) & \(1.907163\) & \(0.096573\) & 0.9248 \\ D(LINEAR) & \(1.549670\) & \(0.727377\) & \(2.130490\) & 0.0565 \\ D(LNPG) & \(6.825561\) & \(3.067669\) & \(2.224999\) & 0.0479 \\ D(LNRFG) & \(-6.964634\) & \(3.127366\) & \(-2.226997\) & 0.0478 \\ D(LNUPG) & \(10.114401\) & \(6.157831\) & \(1.642527\) & 0.1287 \\ Coint. Equation-(1) & \(-1.031504\) & \(0.233261\) & \(-4.422112\) & 0.0010 \\ \hline \multicolumn{4}{c}{**Long-Run Coefficients**} \\ \hline
**Variables** & **Coefficient** & **Std. Error** & **t-Statistic** & **Prob.** \\ \hline LNEAP & \(1.310100\) & \(3.291778\) & \(0.397992\) & 0.6983 \\ LNEARP & \(-0.891821\) & \(1.868824\) & \(-0.477210\) & 0.6426 \\ LNEAUP & \(3.079896\) & \(2.910661\) & \(1.058143\) & 0.3127 \\ LNEN & \(2.288282\) & \(0.548249\) & \(4.173804\) & 0.0016 \\ LNPG & \(6.617094\) & \(2.840778\) & \(2.329324\) & 0.0399 \\ LNRPG & \(-3.988076\) & \(1.257097\) & \(-3.172450\) & 0.0089 \\ LNPPG & \(0.308340\) & \(2.151163\) & \(0.143336\) & 0.8886 \\ C & \(-27.082991\) & \(11.476944\) & \(-2.359774\) & 0.0378 \\ \hline \hline \end{tabular}  
* Denotes rejection of the hypothesis at the 0.05 level, ** [PERSON]–Haug–Michelis (1999) \(p\)-values.  
\end{table} 
Table 5: Long-Run Analysis. the coefficients of electricity access to the urban population, energy usage, population growth, and urban population growth had a positive and significant impact along with economic growth. The coefficients of the electricity access to the urban population, energy usage, population growth, and urban population growth are 3.079896, 2.288282, 6.617094, and 0.308340, with their \(p\)-values of 0.3127, 0.0016, 0.0399, and 0.8886, respectively.