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1 – 10 of 14Xinyang Liu, Anyu Liu, Xiaoying Jiao and Zhen Liu
The purpose of the study is to investigate the impact of implementing anti-dumping duties on imported Australian wine to China in the short- and long-run, respectively.
Abstract
Purpose
The purpose of the study is to investigate the impact of implementing anti-dumping duties on imported Australian wine to China in the short- and long-run, respectively.
Design/methodology/approach
First, the Difference-in-Differences (DID) method is used in this study to evaluate the short-run causal effect of implementing anti-dumping duties on imported Australian wine to China. Second, a Bayesian ensemble method is used to predict 2023–2025 wine exports from Australia to China. The disparity between the forecasts and counterfactual prediction which assumes no anti-dumping duties represents the accumulated impact of the anti-dumping duties in the long run.
Findings
The anti-dumping duties resulted in a significant decline in red and rose, white and sparkling wine exports to China by 92.59%, 99.06% and 90.06%, respectively, in 2021. In the long run, wine exports to China are projected to continue this downward trend, with an average annual growth rate of −21.92%, −38.90% and −9.54% for the three types of wine, respectively. In contrast, the counterfactual prediction indicates an increase of 3.20%, 20.37% and 4.55% for the respective categories. Consequently, the policy intervention is expected to result in a decrease of 96.11%, 93.15% and 84.11% in red and rose, white and sparkling wine exports to China from 2021 to 2025.
Originality/value
The originality of this study lies in the creation of an economic paradigm for assessing policy impacts within the realm of wine economics. Methodologically, it also represents the pioneering application of the DID and Bayesian ensemble forecasting methods within the field of wine economics.
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Mohd Nayyer Rahman, Badar Alam Iqbal and Nida Rahman
This study aims to find the impact of the trade war between the USA and China on Asian economies. Apart from macroeconomic variables associated with trade, this study explicitly…
Abstract
Purpose
This study aims to find the impact of the trade war between the USA and China on Asian economies. Apart from macroeconomic variables associated with trade, this study explicitly creates a trade war scenario and trade war participant dummies. Using the neural network multilayer perceptron, this study checks for the causal linkages between the predictors and target output for the panel of Asian economies and the USA.
Design/methodology/approach
A conceptual model of the after effects of trade war in a quadrant is developed. Variables related to trade and tariffs are included in the study for a panel of 19 Asian economies. The feedforward structure of neural network analysis is used to identify strong and weak predictors of trade war.
Findings
The hidden layers of the multilayer perceptron reveal the inconsistency in linkages for the predictors’ services exports, tariff measures, anti-dumping measures, trade war scenario dummy with gross domestic product. The findings suggest that to curtail the impact of the trade war on Asian economies, predictors with neural evidence must be paid due weightage in policy determination and trade agreements.
Originality/value
The study applies a novel and little explored AI/ML technique of Neural Network analysis with training of 70% observations. The paper will provide opportunity for other researchers to explore techniques of AI/ML in trade studies.
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Shuchuan Hu, Qinghua Xia and Yi Xie
This study investigates firms' innovation behaviour under environmental change. Therefore, it examines the effect of trade disputes on corporate technological innovation and how…
Abstract
Purpose
This study investigates firms' innovation behaviour under environmental change. Therefore, it examines the effect of trade disputes on corporate technological innovation and how product market competition moderates this relationship.
Design/methodology/approach
This research tests the hypotheses using the fixed effects model based on panel data of publicly listed enterprises in China from 2007–2020.
Findings
The empirical results validate the positive association between trade disputes and corporate research and development (R&D) intensity as well as the U-shaped relationship between trade disputes and radical innovation. Additionally, the moderating effect of product market competition is verified: a concentrated market with less competition flattens the U-shaped curve of radical innovation induced by trade disputes; as the market becomes more concentrated and less competitive, the U-shaped relationship eventually turns into an inverted U.
Originality/value
First, this study contributes to the corporate innovation and trade dispute literature by expanding the environmental antecedents of technological innovation and the firm-level consequences of trade disputes. Second, this study enriches the theoretical framework of the environment–innovation link through an integrated perspective of contingency theory and dynamic capabilities view. Third, instead of the traditional linear mindset which had led to contradictory results, this study explores a curvilinear effect in the environment–innovation relationship.
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South-east Asia maintained its position as the largest recipient (40%) of China’s total Asia-Pacific engagement, which was valued at USD14.8bn, up USD12.4bn from 2022. In recent…
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DOI: 10.1108/OXAN-DB286688
ISSN: 2633-304X
Keywords
Geographic
Topical
EU/UK: Delay to EV tariffs is likely
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DOI: 10.1108/OXAN-ES282415
ISSN: 2633-304X
Keywords
Geographic
Topical
Tai will continue to make the Biden administration’s case that the WTO needs reform to make it fit for purpose in the 21st century. Opposition to reform will come from India and…
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DOI: 10.1108/OXAN-DB285432
ISSN: 2633-304X
Keywords
Geographic
Topical
Slovakia’s first EV battery plant aims to support the nascent EV industry and underlying supply chains. Foreign capital and technological innovations are key for Central European…
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DOI: 10.1108/OXAN-DB284377
ISSN: 2633-304X
Keywords
Geographic
Topical
German manufacturers face a multi-faceted competitiveness challenge. Domestic output almost halved from 2016 to 2021. The failure to match rivals in the development of electric…
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DOI: 10.1108/OXAN-DB282476
ISSN: 2633-304X
Keywords
Geographic
Topical
Himanshu Seth, Deepak Deepak, Namita Ruparel, Saurabh Chadha and Shivi Agarwal
This study aims to assess the efficiency of managing working capital in 1,388 Indian manufacturing firms from 2008 to 2019 and investigate the effects of firm-specific and…
Abstract
Purpose
This study aims to assess the efficiency of managing working capital in 1,388 Indian manufacturing firms from 2008 to 2019 and investigate the effects of firm-specific and macro-level determinants on working capital management (WCM) efficiency.
Design/methodology/approach
The current study accommodates a slack-based measure (SBM) in data envelopment analysis (DEA) for computing WCM efficiency. Further, we implement a panel data fixed-effects model that controls for heterogeneity across firms in determining the relationships of selected variables with WCM efficiency.
Findings
The results highlight that manufacturing firms operate at around 50 percent efficiency, which is constant throughout the study period. Furthermore, among the selected variables, yield, earnings, age, size, ability to create internal resources, interest rate and gross domestic product (GDP) significantly affect WCM efficiency.
Originality/value
Instead of the traditional models used for assessing efficiency, the SBM-DEA model is unit-invariant and monotone for slacks, implying that it can handle zero and negative data, which overcomes the incapability of prior DEA models. Hence, this provides accurate efficiency scores for robust analysis. Additionally, this paper provides a holistic working capital model recognizing firm-specific and macro-level determinants for a more explicit estimation of the relationship between WCM efficiency and the selected determinants.
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