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Global Health Economics and
            Sustainability
                                                                      Energy consumption and life expectancy in West Africa


            for medical services. These results corroborate those of   significant relationship with life expectancy (LEXP).
            Aderinto (2023) and Agbanike  et al. (2019). They also   Although  NREC negatively affects  LEXP, the non-
            confirm the findings of Qiang et al. (2023), who used the   significance of the coefficient in the short run, shown
            same estimation method to find that renewable energy has   in Panel B of Table 3, indicates that this effect does not
            a positive and significant effect on life expectancy in 121   manifest itself immediately. The long-run coefficient of
            countries. In contrast, Noor & Cameron (2014) showed that   NREC is significant, suggesting that its effects manifest
            wind turbines cause noise pollution and wildlife fatalities   themselves  fully  in  the  long  run.  This  explains  why  the
            through collisions and take up a lot of space. Furthermore,   negative effect of non-renewable energy is not taken
            Dunlap (2021, p. 91) observed that wind energy, acclaimed   seriously  and  the sluggishness  in  embracing  renewable
            to be clean energy, “involves socially and ecologically   energy. This finding is in line with that of Nkalu and Edeme
            destructive mining processes that produce large amounts   (2019), who showed that life expectancy decreases due to
            of mining tailings (or waste) containing heavy metals,   the environmental effects of fossil fuels. Therefore, non-
            thorium and radioactive materials that go into the air,   renewable energy consumption (NREC) is detrimental to
            water,  soil,  animals,  and  people’s  bodies.”  This  implies   longevity. The findings of Asgher et al. (2019) support this
            that there are drawbacks of renewable energy use, which   view in that non-renewable energy reduces environmental
            must be guarded against. Even the recommendation of   quality while increasing the mortality rate.
            Weitensfelder et al. (2024), who called for energy efficiency
            and renewability as mitigating measures following a higher   Indeed, increasing income (GDPpc) enhances life
            energy demand for economic growth, should be used with   expectancy (LEXP). A  higher GDP per capita enables
            caution.                                           governments to invest more in healthcare infrastructure,
              The  results  also  revealed  that  the  consumption  of   facilities, and medical technologies. This leads to improved
            non-renewable energy (NREC) has a negative but non-  access to quality healthcare services for citizens, thereby
                                                               improving healthcare outcomes and life expectancy. The
                                                               coefficient of  GDP  was positive and non-significant in
            Table 2. ARDL cointegration test results                          PC
                                                               the short run. Although this conforms with our a priori
            Variable   Coefficient  Std. error  t‑statistic  Prob.  economic expectation, it is rather surprising that this
            COINTE01   −0.310638  0.009827  −3.082517  0.0043  coefficient was not statistically significant. This is mainly
            Source: Authors’ computation, 2024 using Eviews 9.  because while the population of West African countries
            Abbreviation: ARDL: Autoregressive distributed lag.  grows geometrically, their ability to produce output/

            Table 3. ARDL long‑ and short‑run results, dependent variable: LEXP
            Variable                 Coefficient          Std. error             t‑statistic           p‑value
            Panel A: Long-run coefficients
             REC                     0.624657             0.087810               7.113754               0.00002
             NREC                    −0.580912            0.083661               −6.943649              0.00003
             GDP PC                  0.006412             0.000561               11.43314               0.00006
             HEXP                    6.600008             0.596038               11.07313               0.00002
             CPI                     −28.86016            2.135960               −13.51156              0.00001
             FP                      0.002898             0.010621               −0.272894              0.78610
            Panel B: Short-run coefficients
             D (REC[−2])             0.147074             0.074008               1.987288               0.05250
             D (NREC[−1])            −0.091490            0.060392               −1.514943              0.13620
             D (GDP [−1])            0.000230             0.000275               0.837404               0.40640
                   PC
             D (HEXP)                0.032988             0.072610               0.454322               0.65160
             D (CPI[−2])             −0.199786            0.097450               2.050131               0.04570
             D (FP[−2])              0.014632             0.005544               2.639065               0.01110
                                                             2
             ECT = −0.310638         R =0.67833           Ad-R =0.55495          DW=1.932502
                                      2
            Note: ECT: Error correction term; DW: Durbin-Watson; R2: R squared; Ad R2: Adjusted R2. Source: Authors’ computation, 2024 using Eviews 9.
            Abbreviations: ARDL: Autoregressive distributed lag; GDP: Gross domestic product.


            Volume 3 Issue 1 (2025)                         8                        https://doi.org/10.36922/ghes.3518
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