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This study aims to define a “technological statecraft” concept to distinguish tech-based measures/sanctions from an array of economic measures ranging from restrictions of rare earth elements and natural gas supplies to asset freezes under the wider portfolio of economic statecraft. This concept is practically intended to reveal the USA’s “logic of choice” in its employment of technology as an efficient instrument to deal with China in the context of the great power rivalry.

This study follows David A. Baldwin’s statecraft definition and conceptualization methodology, which relies on “means” rather than “ends.” In addition to Baldwin and as an incremental contribution to his economic statecraft analysis, this study also combines national political economy with statecraft analysis with a particular focus on the utilization of technological measures against China during the Trump administration.

The US rationale for choosing technology, namely, emerging and foundational technologies, in its rivalry against China is caused at least by two factors: the nature of the external challenge and the characteristics of the US innovation model based largely on radical innovations. To deal with China, the USA practically distinguished the role of advanced technology and followed a grammer of technological statecraft as depicted in the promulgated legal texts during the Trump administration.

Despite a growing volume of literature on economic statecraft and technological competition, studies focusing on countries’ “logic of choice” with regard to why and under what conditions they choose financial, technological or commodity-based sanctions/measures/controls are lacking. Inspired from Baldwin’s account on the “logic of choice” from among alternative statecrafts (i.e. diplomacy, military, economic statecraft, and propaganda). This study will contribute to the literature with a clear lens to demonstrate the “logic of choice” from among a variety of economic statecraft measures in the case of the US technological statecraft toward China.

The debate to find a solution for domestic price support under the WTO Agreement on Agriculture (AOA) has been a long one. The stance of India is critical to determine due to its large population. This paper aims to analyse the benefits or demerits of minimum price support and what approach could be adopted by India.

The paper is a mix of both analytical and theoretical research. The paper first provides a background on the issues related to public stockholding and further analyses some data at which India procures wheat and rice from the farmers and then compares it with retail market prices in India.

The paper finds that the difference in price between minimum price support and retail market prices in India for wheat and rice is minimal. Therefore, the concern that India might be taking advantage of the minimum price is uncalled for. India also needs to balance its own interests as well as abide by its WTO obligations. The paper finds that cooperation among countries or regional blocks might help to address the problem of food insecurity.

The paper portrays India’s stance with regard to WTO AOA as well as studies the Indian market for wheat and rice.

The regional comprehensive economic partnership (RCEP) is promising as per the claims and can be revolutionary for the Asia–Pacific Region. The member countries will get a boost in the post-pandemic world due to the RCEP. According to Brookings, the RCEP is going to be an agreement reshaping the global economics. This study aims to clarify the aspects related to the RCEP and how it can boost global economics.

The study employs qualitative descriptive analysis to address the status of RCEP in the region and the consequences of such main transnational partnership. The study is based on economic reports, official documents and data directly related to the subject of the study.

Findings show that the RCEP will be a significant driver of regional trade despite its faults. The RCEP's tariff benefits and rules of origin, notwithstanding their relatively restricted scope, will encourage enterprises to source products and services from RCEP members, and in combination, RCEP and Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) are anticipated to replace at least some competing US commodities, services and farm exports. For items that integrate parts and components from inside the area, such as from China, the RCEP is projected to reduce tax and trade facilitation costs, allowing enterprises to avoid US Section 301 tariffs.

By examining how the RCEP operates within the framework of domestic and international trade, this study contributes to a deeper understanding of RCEP and analyses its nature based on data and official reports.

This paper aims to investigate whether the practice of self-designation of developing country status in the World Trade Organization (WTO) risks irrelevance of the institution, having regard to legitimacy concerns and evolving trade policy considerations.

The methodology of this paper involves the application of critical analysis to assess the utility of regime overhaul vis-à-vis a detailed recalibration of the status quo; included in this are key examinations of whether the introduction of a definitive classification criteria will alleviate present challenges as well as critiques of alternative target-specific schemes.

This paper suggests that an ideal approach to the controversies surrounding self-designation steers away from pure income-based indicators to arrive at targeted special and differentiated treatment allocation. Such a framework anchors itself on principles of nuanced differentiation that support depoliticization and facilitate capacity building in developing countries.

To the best of the author’s knowledge, this paper represents an original evaluation of the possible reforms available to the WTO concerning the present status and functionality of the mechanism underpinning the practice of self-designation of developing country status.

The purpose of this paper to examine how global economic policy uncertainty (GEPU) affects export flows of emerging market economies.

This study examines the effect of GEPU on 28 emerging markets' export performance. GEPU variable used in the authors’ empirical analysis is measured by partial least square (PLS) factor loading model with the help of 24 countries' economic policy uncertainty index. A panel vector autoregression (VAR) model is employed for the estimations and monthly data over the 2006:01–2019:12 period are used.

The empirical findings show that while the real external income is the main factor that affects export flows, the real exchange rate is the least effective variable with regard to the variance decomposition, which is not expected by the related economic theory. Panel VAR estimations results confirm the previous studies and find that GEPU affects export flows negatively and significantly.

To the best of the authors’ knowledge, this is the sole study in terms of focusing on the impacts of GEPU on the export volume of emerging markets. The contribution of this paper is twofold. Firstly, a large set of countries with monthly frequented data that assist to capture uncertainties better is used. Secondly, the global economic policy index is obtained by employing the PLS method, which provides more robust results that are calculated with respect to the dependent variable.

Most economic growth is concentrated in the eastern and coastal provinces of China, while the western and central provinces have not yet experienced the expected economic growth. This study aims to address the following crucial research questions: Do the central and western provinces achieved potential efficiency in economic growth? Have China’s provinces used their resources effectively in implementing economic growth strategies?

The research design concerns the use of a panel dataset on province-specific economic growth in China over the years to 2000–2020. The methodology used was a stochastic frontier gross domestic product (GDP) model with time-varying technical efficiency over time. The approach uses the existing literature to identify the important variables influencing economic growth at the provincial level to model the stochastic frontier GDP model for empirical analysis.

This study concludes that the central provinces show the highest rate of efficiency in economic growth, though not 100%, followed by the Eastern and Western provinces. By increasing and improving skilled education institutes and intensifying supply chain opportunities through foreign direct investment (FDI), the central provinces achieving 100% growth efficiency may not be ruled out.

The modes of economic governance and policies to improve GDP growth have been rapidly changing from increasing incentives to improving competition. Thus, more unique avenues and expansion of the horizon for impending research on provincial, national and international macroeconomics would emerge that would make current methodologies of the growth analysis outdated.

The empirical analysis highlights the importance of improving skilled education institutes and intensifying supply chain opportunities through FDI for achieving sustained economic growth.

The empirical analysis facilitates finding ways to reduce income inequality across provinces in China.

To the authors' knowledge empirical analysis examining the Chinese province-specific economic growth efficiency explicitly has not been carried out using the recent Chinese panel dataset.

Drawing upon resource-based view (RBV) and attribution theoretical lenses, this chapter provides a paradigm for examining the interplay among environmental investment towards green innovation, environmental disclosure as well as firm performance using the structural equation modelling (SEM) methodology. This chapter demonstrate a growing environmental awareness among stakeholders of the relevance of environmental performance to share value. It is also suggested that the mediating power of environmental disclosure between environmental investment and firm value as well as incremental goodwill is crucial. The findings of this chapter provide critical implications for several stakeholders that if environmental performance is hypothesised to affect the firm's value, companies may take proactive measures to avert potential environmental-related violations. Besides, investors may trade based on the evidence as to how firm value and its goodwill from acquisition will be affected by news of its environmental performance.

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.

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.

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.

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.

The author attempts to examine the existence and pattern of coalitions in international relations across countries, and investigates whether international relations of coalition partners influence a country's enaction of agricultural non-tariff measures (NTMs).

The author adopts a machine learning technique to identify international relation coalition partnerships and use network analysis to characterize the clustering pattern of coalitions with high-frequent records of global event data. The author then constructs a monthly dataset of agricultural NTMs against China and international relations with China of each importer and its coalition partners, and designs a panel structural vector autoregressive (PSVAR) model to estimate impulse response functions of agricultural NTMs with regard to international relation shocks.

The author finds countries to establish coalition partnerships. Two major clusters of coalitions are noted, with one composed of coalitions primarily among “North” countries and the other of coalitions among “South” countries. The United States is found to play a pivotal role by connecting the two clusters. The PSVAR estimation reveals reductions of NTMs against China following improved international relations with China of both the importer and its coalition partners. NTM responses are more substantial for measures that are trade restrictive. These results confirm that coalitions in international relations lead to coordination of agricultural NTMs.

The author provides international political insights into agricultural trade policymaking by showing interactions of NTM enaction across countries in the same coalition of international relations. These insights offer useful policy implications to predict and cope with hidden barriers to agricultural trade.