Purpose
The purpose of this paper is to analyze raw materials, labor, capital, demand, related industries, strategies and policies influencing international competitiveness of Chinese textile and clothing industry.
Design/methodology/approach
The analysis is conducted using “Diamond Model”, in which raw materials, labor, capital, demand, related industries, strategies and policies are included as explanatory variables, and the impacts of international competitiveness on market share (MS), trade competitiveness(TC) and revealed comparative advantage(RCA) are examined based on the estimated coefficients of these variables.
Findings
These factors have different effects on TC, MS and RCA. While their effects on TC and MS are similar in sign even though their degree of significance differs, their effects on RCA are opposite to TC and MS except for capital. Raw materials and capital have negative effects on TC and MS, while the other factors have positive ones. Raw materials have positive effects on RCA, but all other factors have negative ones.
Practical/implications
The results from this study imply that it is necessary to increase investment in fixed assets of Chinese textile and clothing industry, speed up the pace of upgrading equipment, improve the level of industrialization, while strengthening the supply of textile raw materials, and lowering raw material prices, thereby reducing the cost of textile and clothing enterprises.
Originality/value
To the best of the authors’ knowledge, this is the first empirical research made using econometric model about the impact of the main factors of trade competitiveness in Chinese textile and clothing industry based on the “Diamond Model”.
In order to deepen the understanding of the impact of major public health emergencies on the oil market and to enhance the risk response capability, this study analyzed the logical relationship between major public health emergencies and international oil price changes, identified the change points, and calculated the probability of abrupt changes to international oil prices. Based on monthly data during six major public health emergencies from 2009 to 2020, this study built a product partition model. The results show that only the influenza A (H1N1) and COVID-19 pandemics were significant reasons for abrupt changes in international oil prices. Furthermore, the wild poliovirus epidemic, the Ebola epidemic, the Zika epidemic, and the Ebola epidemic in the Democratic Republic of the Congo had limited effects. Overall, the outbreak of a Public Health Emergency of International Concern (PHEIC) in major global economies has a more pronounced impact on international oil prices.
It is crucial for China to take the characteristics and development stage of every province in the region into account in order to achieve the “dual carbon” development goal. Using data collected from 2000 to 2019, this study identifies the factors that influence carbon emissions using the logarithmic mean Divisia index (LMDI) method and establishes a revised stochastic impacts by regression on population, affluence, and technology (STIRPAT) model to investigate the effects of four key factors on carbon emissions in Jiangsu province: population size, economic output, energy intensity, and energy structure. The following conclusions were drawn: (1) energy intensity contributes to a slowed rate of carbon emission production in Jiangsu, whereas population size, economic output, and energy structure contribute to a pulling effect; (2) under different scenarios, Jiangsu’s carbon dioxide emissions peak at different times and reach different values; and (3) two low-carbon scenarios are more in line with the current development situation and future policy orientation of Jiangsu Province and are therefore better choices. Our policy recommendations are as follows: (1) the development of economic and social activities should be coordinated and greenhouse gas emissions should be reduced; (2) the province’s energy structure should be transformed and upgraded by taking advantage of the “dual carbon” development model; and (3) regionally-differentiated carbon emission reduction policies should be developed.
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