The impact of government expenditure, renewable energy consumption, and CO2 emissions on Lebanese economic sustainability: ARDL approach

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Most of the recent environmental and economic studies focus on the influence of renewable energy consumption and effective government expenditure respecting global climate change in leading sustainable economic growth. The empirical studies showed variation in the relationship between these variables. Based on the Keynesian economic growth framework, this study aims to investigate the impact of government expenditure, renewable energy consumption, and carbon dioxide emissions on the sustainable economic growth of Lebanon. The study used the ordinary least square method to test the short- and long-run relationship between the model variables by employing the Autoregressive Distributed Lag Stationarity estimation. The research data are gathered from the World Development Indicators annually from 1990 to 2022. The empirical findings showed that all variables are stationary at first difference except for carbon dioxide emissions. A long-term relationship between the dependent and independent variables was shown by the model test simulation employing the bound test. The model test for model residuals showed no heteroscedasticity based on the White test. The residuals are normally distributed by applying the Shapiro-Wilk test, and the model is stable with no structural break at the period. According to the study results, government spending has a robust reverse relation with sustainable economic growth and positive significant results for both renewable energy consumption and carbon dioxide emissions. The study findings are consistent with some literature sources and raise attention to monitoring the nature of government spending and boosting green energy sources in an economy.

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    • Figure 1. Conceptual model
    • Figure 2. Variation of variables with time (Gdp per capita, General government final consumption expenditure, CO2 emissions in kt, Renewable energy consumption)
    • Table 1. Unit root tests on the individual series
    • Table 2. Maximum number of lags
    • Table 3. ARDL regression
    • Table 4. ARDL long-run and short-run results
    • Table 5. Bound test
    • Table 6. Heteroscedasticity White’s test
    • Table 7. Normality test
    • Table 8. Cumulative sum test for parameter stability
    • Conceptualization
      Hanadi Taher
    • Formal Analysis
      Hanadi Taher
    • Funding acquisition
      Hanadi Taher
    • Methodology
      Hanadi Taher
    • Resources
      Hanadi Taher
    • Software
      Hanadi Taher
    • Validation
      Hanadi Taher
    • Writing – original draft
      Hanadi Taher
    • Writing – review & editing
      Hanadi Taher