Artikel
Financial development - economic growth nexus in Pakistan: New evidence from the Markov switching model
This paper investigates the impact of financial development on economic growth in Pakistan using the Markov Switching Model over the period 1980-2017. The results based on two-state Markov switching model confirm the Schumpeter's view that finance spurs growth. The result reveals that financial development augments economic growth in both high and low economic growth regimes in Pakistan. However, the impact of financial development on economic growth is found to be relatively higher in the high-growth regime. This implies that economic growth responds differently to financial development in low-growth and high-growth regimes. Among the control variables, trade openness and government expenditures impact economic growth positively, while labour force exerts a negative impact on economic growth.
- Language
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Englisch
- Bibliographic citation
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Journal: Cogent Economics & Finance ; ISSN: 2332-2039 ; Volume: 8 ; Year: 2020 ; Issue: 1 ; Pages: 1-15 ; Abingdon: Taylor & Francis
- Classification
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Wirtschaft
Single Equation Models; Single Variables: Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
Economic Growth of Open Economies
Institutions and Growth
- Subject
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Financial development
economic growth
regime switching model
high- and low-growth regime
Pakistan
- Event
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Geistige Schöpfung
- (who)
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Rahman, Abdul
Khan, Muhammad Arshad
Charfeddine, Lanouar
- Event
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Veröffentlichung
- (who)
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Taylor & Francis
- (where)
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Abingdon
- (when)
-
2020
- DOI
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doi:10.1080/23322039.2020.1716446
- Handle
- Last update
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10.03.2025, 11:44 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Rahman, Abdul
- Khan, Muhammad Arshad
- Charfeddine, Lanouar
- Taylor & Francis
Time of origin
- 2020
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