Developing long- and short-run nexus between industrial growth, economic growth, and trade balance of China

Shahid, Rabia; Li, Shijie; Shah, Aadil Hameed

doi:10.1007/s11356-021-17104-2

Cited by 9 publications

(8 citation statements)

References 58 publications

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“…For avoiding the problem of spurious regression, econometric analysis of panel data relies on the panel unit root test (Levin et al, 2002;Shafique et al, 2021). Various unit root tests are found in the literature (Shafique et al, 2021;Shahid et al, 2021;Shijie et al, 2021) for verifying the stationarity of a series. According to Dickey and Fuller (1979), the stationarity of data series can be checked through ADF unit root analysis.…”

Section: Panel Unit Root Testmentioning

confidence: 99%

“…According to Dickey and Fuller (1979), the stationarity of data series can be checked through ADF unit root analysis. Phillips Peron (PP) tests are also used for testing the stationarity of data (Shahid et al, 2021). Moreover, the optimal lag selection is also a pre-requisite for the ARDL model.…”

Section: Panel Unit Root Testmentioning

confidence: 99%

“…Moreover, the optimal lag selection is also a pre-requisite for the ARDL model. Different criteria are found in the literature for checking the optimal lag for a series such as SBC (Schwarz Bayesian criterion), HQ (Hannan Quinn), and/or AIC (Akaike information criterion) (Shahid et al, 2021). The current study used AIC for selecting the optimal lag length of 2.…”

Section: Panel Unit Root Testmentioning

confidence: 99%

“…The value of the error correction term (ECT) is significant and negative, indicating the convergence of the model over a long period of time. The speed of adjustment from short to long run is highly depicted by ECT (Shahid et al, 2021). The ECT shows that any shock to GTFEP of the Chinese manufacturing industry bears a yearly adjustment capacity of 47%.…”

Section: Panel Co-integration Testmentioning

confidence: 99%

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Pathway to green growth: A panel-ARDL model of environmental upgrading, environmental regulations, and GVC participation for the Chinese manufacturing industry

Shahid

Yifan

et al. 2022

Front. Environ. Sci.

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Since the opening up of China, its manufacturing sector contributed significantly toward economic development on one hand and caused elevated environmental pollution and heavy resource consumption problems on the other hand. Green productivity is an essential means of addressing environmental problems and promoting sustainable environmental performance and long-term economic growth. When the factors affecting the green total factor energy productivity (GTFEP) are studied in recent years, the hitherto literature lacks the relationship between GTFEP, environmental regulations, and global value chain (GVC) participation. Using GTFEP as a proxy of environmental upgrading for the Chinese manufacturing industry, this study investigates the nexus between the GTFEP, environmental regulation index (ERI), and total production length index (TPLI). Based on panel data 18 industries from 2000 to 2014, the current study employed the panel pool mean group estimators for the auto-regressive distributed lag model (ARDL) and estimated the long-run relationship between variables. Findings revealed the positive effect of ERI and GVC participation (TPLI) on the GTFEP of the Chinese manufacturing industry. Furthermore, pairwise panel causativeness analysis indicated unidirectional causality between GTFEP and ERI, running from GTFEP to ERI. Based on research findings, some conclusions and policy implications are derived, such as strict enforcement of environmental regulations, industry-specific policies, promotion of clean energy resources, and acceleration of the country’s further opening-up and reforms. All of these will help promulgate the GTFEP and environmental upgrading of the Chinese manufacturing sector, thus leading to sustainable economic development decoupled from environmental pollution.

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Section: Panel Unit Root Testmentioning

confidence: 99%

Section: Panel Unit Root Testmentioning

confidence: 99%

Section: Panel Unit Root Testmentioning

confidence: 99%

Section: Panel Co-integration Testmentioning

confidence: 99%

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Pathway to green growth: A panel-ARDL model of environmental upgrading, environmental regulations, and GVC participation for the Chinese manufacturing industry

Shahid

Yifan

et al. 2022

Front. Environ. Sci.

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“…Since China's opening-up reforms, a rapid expansion in China's economy has been witnessed, with industrial growth being the most conspicuous element [22]. On the one hand, the expansion of the industrial sector significantly contributes to China's overall economic growth, while on the other hand, it highlights its production and consumption trends and impacts foreign trade [23]. Moreover, China's industrial expansion has entailed a structural change to its economy and boosted exports, but at the same time, industrial expansion has also increased China's oil consumption and domestic GDP.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Asymmetrical Influence of Economic Growth, Oil Price, Consumer Price Index and Industrial Production on the Trade Deficit in China

et al. 2022

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The present study intends to scrutinize the asymmetrical influence of economic growth, industrial production, CPI (consumer price index) and oil price on the trade deficit for the People’s Republic of China’s economy. The Toda–Yamamoto causality, non-linear ARDL method, and quarterly data for 1995Q1 to 2021Q4 have been utilized to investigate the results. The estimated results confirm the uni-directional causality and presence of non-linear co-integration among variables under discussion. However, bound test analysis also reveals the long-run asymmetrical association among TD (trade deficit), IP (industrial production), oil price, and GDP growth, but not the CPI (consumer price index). Further, long-run asymmetrical outcomes highlight that a decrease (increase) in industrial production and an increase (decrease) in oil price and GDP growth rate increase (decrease) the trade deficit. Short-run asymmetrical outcomes reveal a similar trend to the long run, but the impact of all variables in the short run is insignificant, which means that linkages between the trade deficit and the explanatory variables are a long-run phenomenon in People’s Republic of China. Thus, in terms of policy, to reduce the trade deficit, it is necessary to focus on attaining standardized GDP growth, increasing industrial-sector production using advanced technology, and replacing oil-using energy sources with green technology (solar panels, wind farm energy).

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Green growth in belt and road initiative countries: exploring the interplay of agriculture production, technological innovation and environmental pollution

Hong,

Cheng,

Xue

et al. 2024

Clean Techn Environ Policy

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Developing long- and short-run nexus between industrial growth, economic growth, and trade balance of China

Cited by 9 publications

References 58 publications

Pathway to green growth: A panel-ARDL model of environmental upgrading, environmental regulations, and GVC participation for the Chinese manufacturing industry

Pathway to green growth: A panel-ARDL model of environmental upgrading, environmental regulations, and GVC participation for the Chinese manufacturing industry

Exploring the Asymmetrical Influence of Economic Growth, Oil Price, Consumer Price Index and Industrial Production on the Trade Deficit in China

Green growth in belt and road initiative countries: exploring the interplay of agriculture production, technological innovation and environmental pollution

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