Trade Patterns Research Articles

Accounting for the Evolution of China's Production and Trade Patterns

Accounting for the Evolution of China's Production and Trade Patterns

Impact of Stock Returns on Trading Volume in Indian Stocks: A Panel ARDL Approach

The purpose of this paper was to analyse the impact of stock returns on trading volume for the companies listed on BSE in India. This article attempted to analyse that whether there had been a significant impact of returns on the trading volume in the short-run and long-run. This study included a sample of 30 companies listed Sensex. To conduct this analysis, a two-stage methodology was employed. In the first stage, a panel autoregressive distributed lag (ARDL) approach was used to investigate the impact of stock returns on trading volume. In the second stage, the focus was on checking the cross-section short-run relationship in the sample by extending the ARDL estimation. The results showed that the short-run co-integration equation, all the variables have shown significant relationship. The returns have shown significant positive impact on trading volume in short-run whereas significant negative impact in the long-run. The lagged trading volume and stock returns have also shown significant positive impact on current trading volume. These findings have significant implications for investors, equity analysts and portfolio management firms for stock selection and trading patterns.

CHANGES IN LOW-INCOME COUNTRIES' WAGES AS A RESULT OF CHINA'S TRADE LIBERALIZATION

The rapid expansion of China's economy and the subsequent liberalization of its commerce have far-reaching implications for the world's LICs. Focusing on the implications for labor markets and income distribution, this research analyzes how China's trade liberalization has affected salaries in LICs. This study aims to shed light on how China's trade policies have affected wage dynamics and societal shifts by reviewing the relevant literature.China's exports have increased as the country liberalized its trade policies and opened up to international markets. The flood of Chinese imports has affected wages in LICs, both positively and negatively. Cheap Chinese imports have especially hard-hit wages in businesses that heavily rely on human labor. Because of this, low-skilled employees in LICs face more competition and less bargaining leverage, both of which contribute to wage stagnation or decline. The rise of China's exports, however, has opened new doorways for economic development and increased employment in LICs. Increased demand from China has fueled employment growth and pay inflation in LICs' comparative advantage sectors, including natural resources and specialized manufacturing. Chinese investment in low- and middle-income countries (LICs) has boosted local economies by creating jobs and raising salaries in the manufacturing and infrastructure sectors. The overall effect of China's trade liberalization on LICs' salaries is nuanced and sector-specific. Economic diversification, trade patterns, and the structure of LIC economies all play a role in determining the size and direction of these impacts.

“What’s in a Name?” Toponyms and Loanwords in European Textile Cultures

Textiles as man-made products have been exchanged over distances for millennia. They can and have been produced almost anywhere; they are also, as a product, highly differentiated and quickly adjustable to changing demands. This brings with it naming practices to communicate about the goods in question. Textiles are labeled so that people can form expectations about them and rely on the reputation tied to the product’s identity. The terminology of textiles and textile items arises and develops in unison with technical innovations, discoveries, fashions, and trade patterns. Although the occurrence of toponyms e.g., in preindustrial trade (10th to 18th century AD) is widely used to study the development of textile trade, there are no studies that look at textile labeling practices across time and space in Europe’s history. This paper explores textile labels from Antiquity up until now, drawing on the expertise of an interdisciplinary group of scholars. Exploring labeling practices is worthwhile, as it allows us to better understand textiles as a phenomenon that has, across time, always connected regions, markets, and, not least, people. The discussion of naming practices of textiles, and especially the use of geographical indications (toponyms), is by no means only relevant to the study of the past as EU regulations show, namely the Geneva Act of the Lisbon Agreement of 2015, that defines appellation of origin as “any denomination protected in the Contracting Party of Origin consisting of or containing the name of a geographical area, or another denomination known as referring to such area, which serves to designate a good as originating in that geographical area, where the quality or characteristics of the good are due exclusively or essentially to the geographical environment, including natural and human factors, and which has given the good its reputation; as well as any indication protected in the Contracting Party of Origin consisting of or containing the name of a geographical area, or another indication known as referring to such area, which identifies a good as originating in that geographical area, where a given quality, reputation or other characteristic of the good is essentially attributable to its geographical origin.”

Deploying Machine Learning Methods to Predict Global Trade Patterns: The Case of Beef

Highlights Machine Learning (ML) methods are offered as an alternative to conventional techniques for understanding global commodity trade. A formal comparison is made between ML results with those from the Poisson Pseudo Maximum Likelihood (PPML) Estimator, which is the most commonly used statistical technique for bilateral trade analysis. PPML takes into account fixed effects and the dynamic nature of panel data to provide a better fit and higher prediction accuracy than ML in the context of in-sample forecasts. ML methods have strengths in feature selection, better validation statistics, and stronger predictive power than PPML, especially with out-of-sample forecasts. Abstract. In international economics, there has been a steady stream of innovations to explain patterns of trade between and among countries with emerging techniques. The most recent - Poisson Pseudo Maximum Likelihood (PPML) estimator – corrects for a potential bias caused by the large proportion of zero observations in bilateral trade data. Alternatively, this study offers Machine Learning (ML) as an option, especially in the presence of finer data on bilateral trade patterns. Using monthly and HS-6-digit (product) level data, the study finds that the main advantage of PPML is its accuracy of forecasts in-sample, but feature selection is somewhat rigid due to the inclusion of a large number of pair-wise fixed effects. ML models have the advantage in selecting features when a long list of explanatory variables is to be considered. Model validation statistics such as MAE and RMSE favor ML methods, but PPML tends to yield higher goodness of fit. In the out-of-sample context, ML has better accuracy than PPML, and a one-step walk-forward ML approach further improves the accuracy of ML forecasts. While PPML has a rich research and application history, emerging ML techniques have sufficient room for improvement in their adaptation to economic analysis. Keywords: Beef, Bilateral Trade, Boosting, Machine learning, ML for Policy

Study on the Influencing Factors of the Competitive Network Pattern of Cobalt Industry Chain Trade in the Context of Big Data Analysis

Abstract The article proposes a time series model to explore the influencing factors of the cobalt industry chain trade competition network pattern. By analyzing the current situation of the evolution of the cobalt industry chain trade network, the relevant variables are selected. The data are described based on the overview of the relevant algorithmic research of the time series model. Finally, the model based on the time series data is empirically tested. The unit root is verified to be in an unsteady state by first-order differencing, and the p-values all have a probability of accepting the original hypothesis greater than 0. After the second-order differencing ADF test, all the series are smooth and all of them are second-order monotonic. After the cointegration test, it was found that the residual series is smooth at the 5% critical level, and there is a cointegration relationship.

The impact of central bank digital currency issuance on the international monetary system - taking China and other countries as examples

As the current international monetary system is increasingly unstable and unbalanced, even more countries have begun to study and implement digital currency and put forward the concept of super-sovereign currency. The inherent defects of the international monetary system dominated by the US dollar provide space for the generation and development of super-sovereign digital currencies. Based on the superficial reasons for the issuance of decentralized digital currencies by various countries and the current policy situation, this paper proposes the impact of future super-sovereign digital currencies on the international monetary system. Taking the issuance of digital currencies by the People’s Bank of China as the starting point, this paper combines the data of the Federal Reserve and the Bureau of Economic Analysis from general to special. It is concluded that the super-sovereign digital currency may fundamentally reshape the international monetary system and the pattern of international trade. Developing countries, such as China, may hold the upper hand of the upcoming changes in the international monetary system by promoting the internationalization of the digital yuan with its leading position in the field of central bank digital currency and its important position in world trade.

Study on the Development Trends and Strategies of International Economy and Trade under the New Situation

Abstract In today’s increasingly globalized world, trade between countries has become more interconnected, and international trade has emerged as the primary driver of economic development for all nations. This paper proposes a standard trade model for the new situation using the Dixit-Stiglitz model. Starting from the consumer’s point of view, the two-stage maximum method is adopted. Using the Lagrange function, the demand utility function of consumer preferences is processed, and the model optimization scheme is deduced. The ARMA model is used to predict the volume of merchandise foreign trade, and the prediction range includes autoregressive and moving average processes. The indicators are used to evaluate the smoothness of the series within the sample period. A suitable sample of international trade data is selected. The results of the analysis are as follows: in the logistic autoregressive analysis test, the significance of all factors, except for the language and religion factors, passes the significance test of 0.001, and at the same time, the model goodness-of-fit is greater than 0.1, ranging from 0.115 to 0.175. In the analysis of the spatial evolution pattern of international economic trade and trade dynamic development, the spatial Gini coefficients of the first category of goods in 2000, 2014, and 2019 and the third category in 2000 are 0.4306, 0.4717, 0.4956, and 0.4673, respectively, which are lower than 0.5, showing a more balanced evolution pattern.

Impact of Financial Inclusion in Line with Mobile Money on Currency in Circulation

Trade initially started from Barter System and progressing through time, money has become the most used commodity as a medium of exchange. Notes and Coins have outlived the longest till our current 4th Generation era where technology has improved the efficiency and effective means of trade with the use of electronic payment system. Despite electronic payment systems being implemented to a very large scale in Zambia, Bank of Zambia statistics showed an increase in Currency in Circulation over the past 10 years from K3.4 billion (FY12) to K13.5 billion (FY21). Pandemics such as Covid-19 have really shown us that doing business electronically is more steady, efficient, and effective than when doing it the traditional way. This study investigated the impact of financial inclusion in line with mobile money on currency in circulation in Zambia. The study found that Mobile Money agents increased by 21.16% to 156,040 in 2021 from 128,789 in 2020. This was explained by a very strong positive relationship (r= .934; p<.000) between Mobile Money use and Currency in Circulation. This was against a theoretical understanding whereby CIC was supposed to show a steady decrease as more money is being used electronically. The study also found poor full transition to electronic transactions and demand for cash. The strategies for reducing currency in circulation found included education of the general public on financial inclusion and promotion of cashless transactions in shopping malls. The study concluded that mobile money did not reduce currency in circulation but increased the currency in circulation as cash was still needed in the current trading pattern in Zambia. More awareness needs to be done for more people to embrace mobile transactions.

Intra-Regional and Global Competitive Dynamics of African Sugar Industries

Recent dynamics in the sugar industry, including price fluctuations in the global market, reforms in the European sugar sector, and changes in intra-regional trade patterns, underscore the need to understand changes in the competitiveness of African sugar exports. This paper, therefore, uses the Normalized Revealed Comparative Advantage (NRCA) index and the Harris-Tzavalis panel-data unit-root test to conduct a comprehensive analysis of the dynamics in both inter and intra-regional competitiveness of sugar exports across 34 African countries using panel data that spans from 2001-2021. The NRCA indices reveal notable shifts and patterns in the competitive landscape of African sugar exporters. As of 2021, half of the countries under scrutiny demonstrated a competitive edge in sugar exports, representing a slight uptick from the fourteen (14) observed in 2021. Nonetheless, only eight (8) African countries, predominantly from southern Africa, have sustained their competitiveness both globally and intra-regionally over the entire analysis period. The majority of African sugar exports have struggled to maintain competitiveness on the global market, with some alternating between periods of comparative advantage and comparative disadvantage. However, three North African countries, particularly Algeria, Egypt and Morrocco gained comparative advantage during this timeframe. The sustained competitiveness of Southern African countries and the gain in competitiveness of some North African countries highlights the importance and growing influence of Foreign Direct Investment (FDI) in shaping the developmental trajectory of African sugar industries.

An analysis of Agarwood trade patterns, historical perspectives, and species identification challenges: repercussions for importing nations

An analysis of Agarwood trade patterns, historical perspectives, and species identification challenges: repercussions for importing nations

Exploring the Trading Patterns and Regulatory Implications in Cryptocurrency Market

Exploring the Trading Patterns and Regulatory Implications in Cryptocurrency Market

Assessment of the current state of economic integration of the member-states of the Eurasian economic union under food security

This paper conducts a comprehensive examination of the current state of economic integration among the member-states of the Eurasian Economic Union with a specific focus on its implications for food security. Established in 2015, the EAEU comprises Armenia, Belarus, Kazakhstan, Kyrgyzstan, and Russia, and endeavors to create a common economic space to foster mutual cooperation. Against the backdrop of global challenges, the nexus between economic integration and food security within the EAEU emerges as a critical aspect warranting careful scrutiny. The study employs a multidimensional approach, analyzing trade patterns, agricultural policies, and collaborative initiatives among member-states to elucidate the existing dynamics of economic integration and their impact on the food security landscape. By examining the interplay between the free movement of goods, services, capital, and labor, the research aims to identify strengths, weaknesses, opportunities, and threats in achieving a resilient and sustainable food supply for the union’s populations. The findings of this study contribute to the understanding of the intricate relationship between economic integration and food security, offering insights that can inform policy decisions within the EAEU. In unraveling the complexities of this multifaceted nexus, the research seeks to guide the union toward a more secure and prosperous future, emphasizing the importance of nuanced strategies to address evolving global challenges. This paper serves as a valuable resource for policymakers, researchers, and stakeholders interested in the intersection of economic integration and food security within regional economic unions.

Analysis of the influence of foreign direct investment on the international trade pattern of host countries

This paper aims to explore the impact of foreign direct investment (FDI) on the international trade patterns of host countries. Based on a comprehensive analysis of relevant domestic and foreign literature, this study sorted out the basic theoretical framework of the interaction between FDI and international trade. On this basis, using the latest panel data and econometric methods, this study conducted an empirical analysis of how FDI affects the export structure, import structure and trade balance of host countries. The findings indicate that foreign direct investment (FDI) plays a crucial role in enhancing the technological advancement of host nations, boosting the sophistication and value of exported goods, and aiding in the diversification of imported products while decreasing reliance on specific raw materials and technologies. In addition, the study also found that FDI can help the host country to improve its trade deficit and enhance its position in the global value chain. Finally, this paper further verifies the above conclusions through case analysis, and puts forward some policy suggestions for the government, including optimizing the foreign investment introduction policy, strengthening the cooperation between local enterprises and foreign enterprises, so as to make better use of FDI to promote the sustainable and healthy economic development of the host country. This study offers a new perspective for understanding the dynamic relationship between FDI and international trade, but also provides an empirical basis for formulating more effective foreign investment policies.

Trade pattern evolution and risk propagation modeling of wind power industrial chains worldwide

Trade pattern evolution and risk propagation modeling of wind power industrial chains worldwide

Evolution and vulnerability analysis of the global trade pattern in the lithium industry chain

Evolution and vulnerability analysis of the global trade pattern in the lithium industry chain

Evolution of global phosphorus products trade pattern and China’s phosphorus import and export security

Evolution of global phosphorus products trade pattern and China’s phosphorus import and export security

Climate Cha(lle)nges in global wine production and trade patterns

The global wine trade is interested by significant changes since a few decades, due to new productive scenarios induced by climate change and to (rapidly) evolving trade and policy regimes. We investigate how these changes are altering trade dynamics. Following a gravity-type approach, we find that higher temperatures are beneficial for the terms of trade, and are boosting trade values. As for policy interventions, the impact of technical measures on trade values is heterogeneous across objectives: While technical measures tend to friction trade, the environment-related policies show pro-trade effects.

Do Geopolitical Risks Impact Trade Patterns in Latin America?

ABSTRACT The rapid rise of China as a major economic power, characterized by its expanding global trade and financial connections, has significantly heightened geopolitical tensions, particularly with the US. The primary objective of this study is to examine the ramifications of such geopolitical risks (GPR) on trading patterns within Latin America, employing a gravity model. The selection of Latin America stems from its ongoing transformation in power dynamics, with China emerging as the second largest partner, posing substantial competition to the US, which has historically been the region’s primary trading partner. This region has also emerged as an attractive investment and trade destination with abundant natural resources and a growing middle class. By focusing on seven of the largest economies in Latin America – Argentina, Brazil, Chile, Colombia, Mexico, Peru, and Venezuela – from 2000 to 2020, our study yields valuable insights into the influence of GPR on trade dynamics. The findings underscore the overall detrimental impact of GPR on trade, with a disproportionately adverse effect on imports. This study represents a significant contribution by bridging existing gaps in the literature, particularly within the underexplored context of Latin America, while providing crucial guidance for policy formulation and informing future research endeavours.

Supply Chain Interconnectedness in Times of Crises: A Gravity Model with DiD Analysis of COVID-19 Effects on Central and Eastern European Trade

This paper explores the impact of COVID-19-induced disruptions on supply chains, specifically focusing on the interconnectedness of supply chains and the transmission effects they cause. The gravity model framework, together with difference-in-differences analysis, is employed to analyze monthly trade patterns among Central and Eastern European (CEE) countries, Western European countries, and other trading partner countries. The model presented accounts for the country’s roles in global value chains (GVCs) by incorporating data related to exports, imports of intermediate and capital goods, and imports of final consumption goods. CEE countries have demonstrated a certain resilience during the COVID-19 pandemic. Yet, they were not immune to adverse consequences due to disrupted supply chains, primarily in the imports of intermediate and capital goods. We find that the countries that suffered from the COVID-19 pandemic the least demonstrated remarkable resilience against disrupted GVCs. The findings of our study enrich the literature on the effects of the COVID-19 pandemic, specifically for the CEE region, by providing a framework for understanding the pandemic’s impact on international trade. The results show that supply shock might be greater than demand shocks on production and trade dynamics. Furthermore, our results suggest that policymakers seek adaptability to changing supply and demand patterns, while enterprises should consider broader diversification both within the region and locally.