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Socio-economic impact assessment of environmental degradation in Pakistan: fresh evidence from the Markov switching equilibrium correction model

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Abstract

Environmental degradation is a severe problem for all nations, especially for developing ones like Pakistan. For analysis purpose, this study employed two proxies of environmental degradation, i.e., carbon emission and ecological footprint as the explained variables during 1980–2017. In contrast, real GDP per capita, electricity consumption, financial development, urbanization, life expectancy rate, and fertility rate are used as independent variables. For the empirical analysis, Johnson co-integration, Markov switching equilibrium correction model (MS-ECM), and other second-generation econometric models have been used. Granger causality is also used to quantify the causal association among concern variables. MS-ECM results showed that there is U-shaped behaviour that holds for the case of ecological footprint and real GDP; on the other hand, inverted U-shaped behaviour has been seen between CO2 and real GDP. Study found negative association between electricity consumption and environmental degradation to save the environment. Study suggests that electricity production sector should be shifted from non-renewable to renewable energy (solar and wind) sources for sustainable future.

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Abbreviations

ED:

Environmental degradation

CO2 :

Carbon emissions

EFP:

Ecological footprint

GDP:

Per capita economic growth

ELEC:

Electricity consumption

FD:

Financial development

URB:

Urbanization

LEXP:

Life expectancy rate

FR:

Fertility rate

ADF:

Augmented Dickey–Fuller

FMOLS:

Fully modified ordinary least square

MS-ECM:

Markov switching equilibrium correction model

AIC:

Akaike information criteria

EKC:

Environment Kuznets curve

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Authors and Affiliations

  1. School of Economics and Finance, Xi’an Jiaotong University, Xian, 710061, China

    Syed Ale Raza Shah

  2. Department of Economics, Government College University, Faisalabad, 38000, Pakistan

    Syed Asif Ali Naqvi, Sofia Anwar & Abdul Majeed Nadeem

  3. Ministry of Education and Collaborative Innovation Center On Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, China

    Ashfaq Ahmad Shah

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  1. Syed Ale Raza Shah
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Appendix A

Appendix A

1.1 A1: Graphical representation of Granger Causality test

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Fig. 3
figure 3

Graphical representation of causality linkages (model 1 and 2)

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3,

Fig. 4
figure 4

Graphs of the results of the IFR of the emission variable against the selected dependent variables

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4 and

Fig. 5
figure 5

Graphs of the results of the IFR of EFP variable against the selected dependent variables

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5.

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Table 12 Comparison of selected variables with existing research findings
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12.

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Shah, S.A.R., Naqvi, S.A.A., Anwar, S. et al. Socio-economic impact assessment of environmental degradation in Pakistan: fresh evidence from the Markov switching equilibrium correction model. Environ Dev Sustain 24, 13786–13816 (2022). https://doi.org/10.1007/s10668-021-02013-8

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