Yazar "Chandio, Abbas Ali" seçeneğine göre listele

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    Assessing the long- and short-run asymmetrical effects of climate change on rice production: empirical evidence from India
    (Springer Heidelberg, 2022) Baig, Imran Ali; Chandio, Abbas Ali; Ozturk, Ilhan; Kumar, Pushp; Khan, Zeeshan Anis; Salam, Md Abdus
    In recent years, environmental change has arisen as a ubiquitous problem and gained environmentalist's attention across the globe due to its long-term harmful effects on agricultural production, food supply, water supply, and livelihoods of rural households. The present study aims to explore the asymmetrical dynamic relationship between climate change and rice production with other explanatory variables. Based on the time series data of India, covering the period 1991-2018, the current study applied the nonlinear autoregressive distributed lag (NARDL) model and Granger causality approach. The results of the NARDL reveal that mean temperature negatively affects rice production in the long run while positively affecting it in the short run. Furthermore, positive shocks in rainfall and carbon emission have negative and significant impacts on rice production in the long and short run. In comparison, negative rainfall shocks significantly affect rice production in the long and short run. Wald test confirms the asymmetrical relationship between climate change and rice production. The Granger causality test shows feedback effect among mean temperature, decreasing rainfall, increasing carbon emission, and rice production. While no causal relationship between increasing temperature and decreasing carbon emission. Based on the empirical investigations, some critical policy implications emerged. Toward sustainable rice production in India, there is a need to improve irrigation infrastructure through increasing public investment and to develop climate-resilient seeds varieties to cope with climate change. Along with, at the district level government should provide proper training to farmers regarding the usage of pesticides, the proper amount of fertilizers, and irrigation systems.
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    Empirical analysis of climate change factors affecting cereal yield: evidence from Turkey
    (2020) Öztürk, İlhan; Chandio, Abbas Ali; Akram, Waqar; Ahmad, Fayyaz; Mirani, Aamir Ali
    This research has examined the dynamic linkages among climate change factors, such as CO2 emissions, temperature, rainfall, and cereal yield in Turkey from 1968 to 2014. At first step, we tested stationary properties of the climatic factors and crop yield by using both traditional and breakpoint unit root tests. After the confirmation of given properties, we used the autoregressive distributed lag (ARDL) model to capture the dynamic relationship among the variables in the given span of time. The empirical results show that there is a long-run equilibrium relationship that exists between climate change factors and cereal yield. CO2 emissions and average temperature have a diverse effect on the cereal yield, whereas average rainfall has a positive effect on the cereal yield in both the long run and short run. To check the causality, we use the Granger causality test that reveals a significant effect of climate change variables on the cereal yield. The unidirectional causal link is significant among temperature and rainfall factors. The results show that the cereal yield is affected by more climate factors like rain fall and temperature due to CO2 emissions as compared to land and labor use. Based on the findings of the study, few suggestions have been made to address the climate change factors. Devise agriculture-specific adaptation policy for the farmers to build their capacity and resilience to tackle climate changes, for example, farm practices. Agriculture research and development should work on cereal crop varieties that can tolerate the high temperature and precipitation. These policies could help the agriculture sector to sustain production and allocation efficiency in the long run
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    Examining the effects of climate change on rice production: case study of Pakistan
    (2019) Öztürk, İlhan; Chandio, Abbas Ali; Magsi, Habibullah
    The current empirical study explores the linkage between carbon dioxide (CO2) emissions, average temperature, cultivated area, consumption of fertilizer, and rice production in Pakistan. For this research, the annual time series data from 1968 to 2014 were used to enhance the validity of the empirical outcomes. The cointegration analysis with the auto-regressive distributed lag (ARDL) bounds testing approach is applied to explore the effects of climate change on rice production. Additionally, the estimated long-run outcomes are verified by employing fully modified ordinary least squared (FMOLS) and canonical cointegrating regression (CCR) approaches. The empirical outcomes revealed that the selected important study variables are cointegrated demonstrating the existence of long-run linkages among them. The main fruitful outcomes of this study are that rice production in Pakistan is positively affected by the carbon dioxide (CO2) emissions in both long-run and short-run.
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    Modeling the impact of climatic and non-climatic factors on cereal production: evidence from Indian agricultural sector
    (Springer Heidelberg, 2022) Chandio, Abbas Ali; Jiang, Yuansheg; Amin, Asad; Akram, Waqar; Ozturk, Ilhan; Sinha, Avik; Ahmad, Fayyaz
    The underpinned study examines the effects of climatic and non-climatic factors on Indian agriculture, cereal production, and yield using the country-level time series data of 1965-2015. With the autoregressive distributed lag (ARDL) bounds testing approach, the long-term equilibrium association among the variables has been explored. The results reveal that climatic factors like CO2 emissions and temperature adversely affect agricultural output, while rainfall positively affects it. Likewise, non-climatic factors, including energy used, financial development, and labor force, affect agricultural production positively in the long run. The estimated long-run results further demonstrate that CO2 emissions and rainfall positively affect both cereal production and yield, while temperature adversely affects them. The results exhibit that the cereal cropped area, energy used, financial development, and labor force significantly and positively impact the long-run cereal production and yield. Finally, pairwise Granger causality test confirmed that both climatic and non-climatic factors are significantly influencing agriculture and cereal production in India. Based on these results, policymakers and governmental institutions should formulate coherent adaptation measures and mitigation policies to tackle the adverse climate change effects on agriculture and its production of cereals.
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    The case of China's fiscal decentralization and eco-efficiency: is it worthwhile or just a bootless errand? (vol 26, pg 89, 2021)
    (Elsevier, 2022) Ahmad, Fayyaz; Xu, Hui; Draz, Muhammad Umar; Ozturk, Ilhan; Chandio, Abbas Ali; Wang, Yanping; Zhang, Dawei
    [Abstract Not Available]
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    The case of China’s fiscal decentralization and eco-efficiency: is it worthwhile or just a bootless errand?
    (2020) Öztürk, İlhan; Ahmad, Fayyaz; Xua, Hui; Draz, Muhammad Umar; Chandio, Abbas Ali; Wang, Yanping; Zhang, Dawei
    During the last two decades, China has made commendable efforts to control environmental pollution and promote sustainable development. Empowering local governments regarding their budgets is an example of such efforts. Although China’s fiscal decentralization (FD) stimulated inter-regional economic competition, environmental pollution also came along as a byproduct. Considering these dynamics, this study aims to investigate the association between the FD and the eco-efficiency of 99 prefecture-level cities from China’s top ten urban agglomerations from 2003 to 2016. We investigated the issue of crosssectional dependence among the panel variables and, to check the stationary properties of our data, applied the second generation Pesaran and Cross-sectional augmented Im, Pesaran, and Shin unit root tests. Subsequently, to check the possible impact of FD on eco-efficiency, we applied both Difference Generalized Method of Moments (GMM) and System GMM with the help of several control variables. The results indicated that FD improved eco-efficiency for the overall sample cities; however, this impact varied among different regions of China. The regional analyses confirmed that FD improved eco-efficiency in the eastern and central parts of China, whereas the relationship was negative in the western region. Our results also confirm that irrational use of resources for economic development reduces eco-efficiency. However, sustainable economic development has a positive and significant impact on eco-efficiency. The negative impact of foreign direct investment and secondary industry was also more significant than was that of population density. Our study presents important policy implications for both central and local governments in China, which include an increase in decentralization and eco-efficiency practices and control over foreign investments, lead towards environmental pollution
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    Towards long-term sustainable environment: does agriculture and renewable energy consumption matter?
    (Springer Heidelberg, 2021) Chandio, Abbas Ali; Akram, Waqar; Ozturk, Ilhan; Ahmad, Munir; Ahmad, Fayyaz
    This work analyzed the long-run (LR) and short-run (SR) effects of renewable and non-renewable energy (RE and NRE) usage, economic development (ED), agricultural value-added (AVA), and forestry area (FA) on the environmental quality (EQ) in China spanning from 1990 to 2015. The autoregressive distributed lags (ARDL) bounds testing method and the Johansen cointegration approach are applied to produce empirical estimates. The empirical results of the ARDL and the fully modified ordinary least square (FMOLS) estimators established that renewable energy usage and forest area reduce CO2 emissions and improve the environmental quality, while non-renewable energy consumption, economic development, and agricultural output increase the level of CO2 emissions in China. The robustness of outcomes is checked through the Granger causality test, impulse response function (IRF), and variance decomposition method (VDM) suggesting that fossil fuel usage in the agriculture production process is mainly accountable for China's CO2 emissions. These findings have inherent policy implications for the central and local Chinese government, which are exhibited in the Conclusions section.