Comparative advantage, endowment structure, and trade imbalances

Shen, Jim Huangnan; Long, Zhiming; Lee, Chien‐Chiang; Jun, Zhang

doi:10.1016/j.strueco.2021.12.012

Cited by 66 publications

(17 citation statements)

References 42 publications

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“…All the firms including incumbents and new entrants in each production stage have access to the same level of technology in each particular production stage. It should be noted that our assumption on the monopolistic competition market structure of each stage along GSCs is in line with the spirit of Bernard and Dhingra (2015); Shen, Deng, and Tang (2021a);and Shen, Long, Lee, and Zhang (2022).…”

Section: Market Structure Theoriesmentioning

confidence: 70%

Profit sharing, industrial upgrading, and global supply chains: Theory and evidence

Liu

et al. 2022

Review Development Economics

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This research constructs a simple model to illustrate the global supply-chain (GSC) profit sharing and industrial upgrading mechanism, finding that the average profitability distribution in the different supply-chain stages is determined by three main conditions: (1) the average product of the labor in the firms at each production stage; (2) the production complexity level of each production stage in the chain; and (3) the ratio of the output elasticity of capital to the output elasticity of labor in each stage. This study also proposes a new industrial upgrading mechanism, the "smilecurve-driven supply-chain upgrading," for supply-chain firms. Increases in production complexity and level of factor intensity in each production stage are found to be the two essential conditions for the smile-curvedriven supply-chain upgrading. Our static and dynamic panel empirical models, including robustness checks, are both broadly consistent with the theoretical predictions of this paper.

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Section: Market Structure Theoriesmentioning

confidence: 70%

Profit sharing, industrial upgrading, and global supply chains: Theory and evidence

Liu

et al. 2022

Review Development Economics

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“…Before any regression, this paper tests whether or not non-stationarity exists. First, to further confirm spatial dependence exists, we employ the cross-country dependence (CD) test (Pesaran 2021 ; Shen et al 2022 ). From Table 3 , we see that the null hypothesis is obviously rejected, which highlights the importance of considering the spatial dependence among countries in this paper.…”

Section: Resultsmentioning

confidence: 99%

The impact of air quality on international tourism arrivals: a global panel data analysis

2022

Environ Sci Pollut Res

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Using data from World Development Indicators (WDI), this research constructs panel data of 99 countries from 1996 to 2018 and employs a spatial econometric model to analyze the impact of air quality on international tourism arrivals. Evidence shows that Moran’s I values are significantly positive, indicating a strong positive spatial dependence in each country and that poor air quality does have a negative impact on the number of tourist arrivals. The results of grouped data illustrate that middle-income countries, low-income countries, high concentrations of PM 2.5 , and countries with less numbers of tourists have negative effects on tourist arrivals in neighboring countries. The contrary groups, however, have positive effects on tourist arrivals – that is, the influence of air quality on the number of tourist arrivals exhibits heterogeneity. In addition, tests of the interaction term show that countries with higher R&D intensity have better air quality and thus attract more tourists. Therefore, countries with poor air quality should improve the environment through international cooperation and undertake technology transfer, thus ultimately increasing the number of tourists.

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“…Following the opening up of China's economy, particularly since joining the World Trade Organization (WTO) in 2001, the economic and trade cooperation between China and the United States of America (US) under the framework of the global multilateral trading system has greatly expanded such that these countries are now each other's largest trading partner (Cai et al, 2022; Shen et al, 2022; Wu et al, 2022). However, recent trade friction has come to dominate Chinese‐American economic and political relations due to the deepening of the Sino–US economic and trade relationship, especially since the inauguration of President Donald Trump in 2017.…”

Section: Introductionmentioning

confidence: 99%

The impact of Sino–US trade friction on the performance of China's textile and apparel industry

Shen

Golson

et al. 2022

International Finance

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This study applies the event-analysis method and takes three Chinese listed textile and apparel companies that are representative of the upstream, midstream, and downstream of the textile value chain as research objects. By tracking the Baidu index trend of the keyword "trade war" to identify the 'time window' for each iconic event, we apply the autoregressive distributed lag approach to examine the impact of important landmark events on the performance of these companies during the period of Sino-US trade friction in 2018. We find that the impact diminished over time.Additionally, compared with upstream companies, midstream and downstream companies were hurt more. However, the risks were generally controllable.

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Comparative advantage, endowment structure, and trade imbalances

Cited by 66 publications

References 42 publications

Profit sharing, industrial upgrading, and global supply chains: Theory and evidence

Profit sharing, industrial upgrading, and global supply chains: Theory and evidence

The impact of air quality on international tourism arrivals: a global panel data analysis

The impact of Sino–US trade friction on the performance of China's textile and apparel industry

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