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    Asymmetric effects of economic growth, fossil fuel consumption, and financial development on carbon emissions in Ghana
    (Shaheed Benazir Bhutto Women University, 2024) Abdul Rahman, Mutawakil; Iftikhar, Sundas; Khan, Asad ul Islam; Yönetim Bilimleri Fakültesi, İktisat Bölümü
    This research analyzes the impact of economic expansion, non-renewable energy consumption (NonREC), financial sector improvement, and carbon releases in Ghana. The study used yearly data from 1971 to 2014 and applied the Nonlinear Autoregressive Distributed Lag (NARDL) method to examine the data. The NARDL approach facilitated the differentiation of variables into favorable and unfavorable adjustments by examining the short-and long-run effects. The results indicated that all the independent variables exhibited short-term asymmetries, while economic growth presented long-term asymmetry. Negative adjustments in economic expansion led to a decline in carbon releases in the long run but an increase in the short run. favorable and unfavorable adjustments in NonREC positively and negatively impact carbon releases in both the short and long term. Additionally, negative adjustments in financial development positively affected carbon releases in the long run. The cumulative dynamic multipliers graphs and impulse response function graphs illustrate the same impact pattern of the independent variables on carbon releases, confirming the findings' robustness. The study suggests implementing environmental policies in Ghana that promote renewable sources of energy and energy-conserving innovations to reduce environmental degradation. The findings recommend that the decision-maker prioritize effective environmental strategies like a green economy, renewable energy use, and energy-saving technologies. By adopting clean energy and implementing advanced technologies, sustainable economic growth can be achieved while preserving the environment and the ecosystem.
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    From earnings to occupations: Understanding intergenerational mobility in Turkey
    (Shaheed Benazir Bhutto Women University, 2024) Iftikhar, Sundas; Vergil, Hasan; Yönetim Bilimleri Fakültesi, İktisat Bölümü
    The studies analyzing intergenerational economic mobility have been rather scarce for developing countries due to unavailability of longitudinal datasets. This study uses data from Survey of Income and Living Condition (SILC) from 2006-2021, obtained from Turkish Statistical Institute to analyze the intergenerational income and occupational mobility in Turkey. Besides measuring the dynamics of income and occupational mobility across generations, we also analyze how does the association of children socioeconomic outcome with their family background vary at different career levels of children. Our findings reveal that the association with parents income is much higher for daughters as compared to sons suggesting daughters outcomes are more explained by their family socioeconomic status. Regarding the association of children’ outcome with family status at different career stage, the relationship is stronger when children are at the mid-career level. The Bayesian methodology and Pseudo-panel fixed effect model has been employed to estimate intergenerational income elasticity and for the rest of the analysis, Bayesian methodology has been utilized. Our finding also reveals higher intergenerational occupational persistence among children in higher income families while children from disadvantaged families have higher probability of switching career upon receiving good education and income perspective.
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    Whether the crypto market is efficient? Evidence from testing the validity of the efficient market hypothesis
    (Bank Indonesia Institute, 2024) Iftikhar, Sundas; Khan, Asad ul Islam; Özcan, Rasim; Yönetim Bilimleri Fakültesi, İktisat Bölümü
    This study examines the validity of the efficient market hypothesis for the cryptocurrency market. We use the Exponential Generalized Autoregressive Conditional Heteroscedastic approach to examine the presence of different calendar anomalies i.e., the Halloween effect, the day-of-the-week (DOW) effect, and the month-of-the-year effect in the case of Bitcoin, Ethereum, XRP, Tether, and USD Coin. The findings show that there is no strong evidence of the Halloween effect. We find only robust Thursday and Saturday effects in the mean equation. In the case of the month-of-the-year effect, there is only a reverse January effect. More specifically, we note that April and February are statistically significant in the case of Bitcoin and Ethereum, respectively. Results obtained from the variance equations imply that September and October are the least risky months for investors.