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    Carbon emissions and the rising effect of trade openness and foreign direct investment: Evidence from a threshold regression model
    (Cell Press, 2023) Derindag, Omer Faruk; Maydybura, Alina; Kalra, Akash; Wong, Wing-Keung; Chang, Bisharat Hussain
    The relationship between carbon emissions, foreign trade openness, and FDI has been studied in prior studies. The previous studies, however, did not examine the link by focusing on carbon emissions in India's industrial sectors. Using carbon emission intensity as a threshold variable and a threshold regression model, we add to the existing studies by assessing the influence of India's industrial sector on carbon emissions. According to the study's findings, there are three threshold effects of foreign direct investment and foreign trade openness on industrial carbon emissions. FDI harms industrial carbon emissions, as it has a characteristically declining and then rising effect coefficient on industrial carbon emissions. Foreign trade openness, however, affects carbon emissions both positively and negatively. Foreign trade openness encourages carbon emission in sectors of the economy with lower carbon emission intensity. However, it also partially constrains it for sectors with high carbon emission intensity. The number of employees, technological innovation, GDP per capita, and economic activity intensity significantly influence carbon emissions in India's industrial sector. This study can extend further in other countries using the recent innovative methodologies.
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    Food prices response to global and national factors: Evidence beyond asymmetry
    (Taylor & Francis As, 2023) Derindag, Omer Faruk; Chang, Bisharat Hussain; Gohar, Raheel; Wong, Wing-Keung; Bhutto, Niaz Ahmed
    The current series of studies examine how local food prices are affected by domestic and international factors. This research advances the existing body of knowledge by examining this effect at different quantiles, frequencies, and times. We use research data from January 1999 to August 2022 using three local and six global variables as independent variables. Additionally, our study uses recent econometric methods, including Wavelet Coherence, Quantile-on-Quantile Regression (QQR), and Granger Causality in Quantiles (GCQ). Moreover, this research uses the Quantile Regression (QR) approach to determine how reliable the findings are. Based on the GCQ approach, the results demonstrate that the correlation persists at most of the quantiles. Moreover, the WC results demonstrate a substantial association between local prices of food and the independent factors across various frequencies and times. Additionally, QQR estimates demonstrate that the impact of exogenous variables on food prices vary among quantiles. These findings are also supported by the QR method. Last but not least, our study offers policy suggestions obtained based on the results of this study.