Research on the Influencing Factors of Russian Foreign Trade Based on R Language Regression Analysis

Based on the systematic analysis of the development of Russian foreign trade and the characteristics of the regional distribution structure of trade, this work further studies the influencing factors of Russia’s foreign trade by using the R language regression analysis method and constructs three econometric models from import, export, and total import and export. The real effective exchange rate and various instruments and equipment and accessories are the main factors affecting Russia’s import trade, energy, minerals, timber, and related products are the main factors affecting its export trade, and Russia’s GDP and international oil prices are the major factors affecting the total import and export volume. A correct understanding of the factors affecting Russia’s foreign trade will help to understand Russia’s economic and trade development and its changing trend and provide a reliable reference value for the further expansion and optimization of economic and trade cooperation between other economies and Russia.

China’s Belt and Road Initiative with ASEAN Countries: Examining the Trade Cooperation and Impact of Coronavirus

The rising US–China tension in the global trade war increased the trade cooperation between China and the ASEAN. Consequently, China’s total import and export volume with ASEAN increased tremendously to 684.60 billion USD in 2020, up by 6.7% year on year. This trend is part of the Belt and Road Initiative (BRI) which promotes China’s infrastructure building program in the neighboring ASEAN countries and exports China’s technical know-how and engineering standards. However, the recent coronavirus outbreak that stormed China and the rest of the world caused delays to many BRI projects. Subsequently, this outbreak also hit the ASEAN countries and halted many of their mega-projects under the BRI framework. Thus, this study attempts to highlight the trade cooperation and project developments of BRI in the ASEAN countries. In addition, the study features the landscape of BRI projects that were affected by the coronavirus amongst the ASEAN countries.

Research on Eco-Efficiency of 11 Cities in Zhejiang Province: Based on the Perspective of High Quality Development

Ecological efficiency (Eco-efficiency) index well represents the quality of regional development and measures the extensive or intensive development mode of a region. The traditional concept of Eco-efficiency refers to the maximum economic benefits through the minimum resource cost and environmental load. This paper argues that the goal of Eco-efficiency evaluation is not only to maximize economic benefits, but also to achieve high-quality development in many aspects such as society, science & technology and economy, so that people can enjoy the results of development.In this paper, the Eco-efficiency input indicators comprehensively considers the consumption of manpower, resources, energy and capital, and negative environmental benefits including waste gas, waste water and waste residue. Output indicators comprehensively consider the five high-quality development dimensions----innovation, coordination, green, openness and sharing, which are represented by indicators such as patents, total import and export, the number of patent, regional Theil index, disposable income, three waste emissions et al. .In terms of empirical research, the SBM model of undesirable output super-efficiency under the assumption of variable returns to scale is established to measure the Eco-efficiencies of 11 cities in Zhejiang Province. Secondly, Malmquist index model is estalished to study the temporal and spatial changes of Eco-efficiencies. Finally, the panel Tobit method is used for regression analysis to study the key factors affecting the Eco-efficiency of Zhejiang Province. The results show that the industrialization structure, economic level and export trade significantly positively correlated with Eco-efficiency. Urbanization level is significantly negatively correlated with Eco-efficiency.

Role of Staple Food Production in Ensuring Food Security in Nigeria

The study investigated the role of staple food production in ensuring food security. The study investigated role of staple food production in ensuring food security in Nigeria. The objectives of this study are to: determine the impact of staple food production on gross domestic product of crops in Nigeria, investigate the value of government guaranteed agricultural loan to farmers on agricultural production in Nigeria, and examine the value of food import bill on total value of import of Nigeria. The study employed time series data. Data is generated from the Central Bank of Nigeria and the National Bureau of statistics bulletin. The study employed the ordinary least square (OLS) of simple regression. The study conducted both econometric and statistical tests. The empirical results showed R2 value of 0.24,053 and 0.22 for models 1-3 respectively. The three models are rightly signed. The coefficient (β) of 0.1631 (model 1) showed that 100% increase in staple food production would lead to a 16.31% increase in gross domestic production of crops (GDPC). Since the computed t-value of 3.102765 falls outside the critical region of 0.0042, we reject the null hypothesis and accept the alternate hypothesis at 5% level of significance. The model 3 test showed that the total import bill (TIMB) was significantly sensitive to variation in the food import bill (β=30.7422). The result confirms that 30.7% of the variation in total import bill was accounted for by the food import bill. Based on the results, the study recommended that emphasis should be placed on one hand and ensuring food security (self-sufficiency) in general.

Dynamic Linear Interdependence between International Trade and Macroeconomic Stability in Nigeria: A Vector Error Correction Modelling.

Causal relationships are often treated erroneously in isolation as a single equation without the consideration of the endogeneity of right-hand side variables and also without recourse to the presence of coco-integration. This study modelled and estimated the dynamic linear interdependence between international trade and macroeconomic stability in Nigeria. The specific objectives were to, establish the trend of the study variables, model and estimate the interdependence existing among total export, total import, exchange rate, and inflation rate, determine the significant causalities and summarize the causal channels among the study variables. The study used the quasi-experimental design. The study used monthly time series data which span from January, 2000 to June, 2019. The data on all the variables were sourced from the Central Bank of Nigeria Statistical Bulletin. Appropriate models were specified in line with the objectives. The study used the Vector Error Correction Models, the pre and post-diagnostic tests were also conducted. The unit root test results showed that the variables were integrated of order one [I(1)]. The co-integration test results showed 1 co-integrating equation and VAR lag length selection criteria choose lag 2. The Vector Error Correction Result showed that inflation rate was the most explained by variations in the independent variables (R2 =73.4%) while exchange Rate was the least explained (R2 =18.8%), the total export model had R2 =53.8% and total import model had (R2 =59.2%. Significant bi-directional causality was found between total export and inflation rate, and also between total import and inflation rate. There was also significant joint causality on total import and also on exchange rate. The post test showed that the models were stable. It was recommended that the right-hand side variables should be tested for endogeneity before concluding on single or system equation. It was also recommended that policies to check inflation rate should consider possibility of shocks to international trade.

Forecasting algorithm of tourism service trade based on PSO-optimized hybrid RVM model

As a comprehensive form of trade, tourism service trade has had a profound impact on the economies of various countries. This research mainly discusses the tourism service trade forecasting algorithm based on the PSO-optimized hybrid RVM model. This study extracts 8 indicators including gross national product, total fixed asset investment, total import and export, China's import and export tariff rate, the exchange rate of renminbi to the US dollar, and the global economic growth rate. The same as the impact indicators of tourism service trade, but there is a certain degree of redundancy and correlation in these indicators. In order to measure the correlation between the evaluation indicators, the autocorrelation evaluation function in MATLAB is used, and the principal component analysis method is used to extract the principal components that can represent the indicators in a larger percentage. In order to improve the prediction accuracy of the RVM model, based on the adaptive construction model structure and initial model weights, the PSO algorithm is used to optimize the RVM model weights. The optimization process takes the minimum error of the RVM model as the algorithm search target, and each represents the RVM model. The algorithm finds the value and threshold of the optimal RVM model through the particle swarm tracking search algorithm and then uses the original RVM model and the optimized RVM prediction respectively total amount of tourism service trade in City A, and compares the prediction errors of the single RVM method and the PSO-optimized RVM method, and analyzes the degree of model prediction error reduction after the PSO model optimizes the RVM model. According to the forecast result, the relative average error of 2020 is 5.7%, and the forecast result is relatively accurate. This research is helpful to provide scientific reference for my country's tourism service trade.

A Framework for Assessing Import Costs of Medical Supplies and Results for a Tuberculosis Program in Karakalpakstan, Uzbekistan

Background. Import of medical supplies is common, but limited knowledge about import costs and their structure introduces uncertainty to budget planning, cost management, and cost-effectiveness analysis of health programs. We aimed to estimate the import costs of a tuberculosis (TB) program in Uzbekistan, including the import costs of specific imported items. Methods. We developed a framework that applies costing and cost accounting to import costs. First, transport costs, customs-related costs, cargo weight, unit weights, and quantities ordered were gathered for a major shipment of medical supplies from the Médecins Sans Frontières (MSF) Procurement Unit in Amsterdam, the Netherlands, to a TB program in Karakalpakstan, Uzbekistan, in 2016. Second, air freight, land freight, and customs clearance cost totals were estimated. Third, total import costs were allocated to different cargos (standard, cool, and frozen), items (e.g., TB drugs), and units (e.g., one tablet) based on imported weight and quantity. Data sources were order invoices, waybills, the local MSF logistics department, and an MSF standard product list. Results. The shipment contained 1.8 million units of 85 medical items of standard, cool, and frozen cargo. The average import cost for the TB program was 9.0% of the shipment value. Import cost varied substantially between cargos (8.9–28% of the cargo value) and items (interquartile range 4.5–35% of the item value). The largest portion of the total import cost was caused by transport (82–99% of the cargo import cost) and allocated based on imported weight. Ten (14%) of the 69 items imported as standard cargo were associated with 85% of the standard cargo import cost. Standard cargo items could be grouped based on contributing to import costs predominantly through unit weight (e.g., fluids), imported quantity (e.g., tablets), or the combination of unit weight and imported quantity (e.g., items in powder form). Conclusion. The cost of importing medical supplies to a TB program in Karakalpakstan, Uzbekistan, was sizable, variable, and driven by a subset of imported items. The framework used to measure and account import costs can be adapted to other health programs.

Jatropha Curcas Biodiesel: A Lucrative Recipe for Pakistan’s Energy Sector

One of the greatest challenges of the 21st century is to fulfill the growing energy needs sustainably and cost-effectively. Among the different sources of energy, biodiesel is one of the alternative energy sources that has tremendous potential to become a major mainstream renewable energy mix. Jatropha is an important raw input for biodiesel that provides an ecological and sustainable solution for emerging greenhouse gas emissions over the other biomass feedstock. This paper critically evaluates different factors and presents a SWOT analysis (strengths, weaknesses, opportunities, and threats) and barriers to the adoption of Jatropha biodiesel. In Pakistan, the estimated production of Jatropha biodiesel is expected to be 2.93 million tons, that are calculated from available barren land and possible shortlisted suitable areas for Jatropha plantation. It is ~25% of the total import (11.84 million tons) of petroleum products, which can save ~$2 billion USD reserves of Pakistan. The cultivation of Jatropha on barren land is an environmentally and economically lucrative approach for Pakistan. This study has real implications for developing a policy framework related to the environment and socio-economic feasibility of Jatropha biodiesel production in Pakistan.

India’s Foreign Trade – An Overview

Export-Play, Important Role of any country’s business India is one among these countries that have been exporting a large number of product and raw material to other countries to earn economy wealth. India is 19th largest export economy. India’s overall, export- in 2019-20 was US $ 313138.5 million and total import was US $ 473995.2 million and trade balance was US $ 160856.7 million. The main object of the paper is to analyse the structural change in foreign trade- Under new Exim policy. The period of the study is from 2010-11 to 2019-20. The result shows that USA, UAE, Hongkong, UK, Germany, Saudi Arbia and China accounted from more than 40% of export from India at the world level. India total export which was US $ 330078.1 million in the year 2018-19 decline to US $ 313138.5 million in the year 2019-20. The total export from India decreased by 5.13% from the year 2018-19 to year 2019-20. In the year 2019-20 the share in total export from India to USA is 16.95%, UAE 9.21%, China 5.30%, Hongkong 3.50%, UK 2.79%, Germany 2.64%, and Saudi Arbia 1.99%. India’s total import in the year 2019-20 was US $ 473995.2 million which China contributed by 37.76%, USA 7.52%, Saudi Ariba 3.60%, Hongkong 3.5%, UAE .38% and Germany 2.81%,. The result show that USA is most important trading partner followed by UAE an UK, Hongkong, China and other countries.

Markov-Switching Vector Autoregressive Modelling (Intercept Adjusted); Application to International Trade and Macroeconomic Stability in Nigeria (2000M1–2019M6)

Economic relationships are often modelled without consideration of a possible regime switch, the transmission from one regime to another and the duration of stay in a particular regime which are not captured by linear models. This study aimed to model and estimate the interdependence existing among Nigeria’s International Trade and Macroeconomic Stability. Specifically, this study sought to estimate and compare the estimated Models, select the best Model and determine the probabilities of stay, the expected duration of stay in a particular regime. The study adopted a quasi-experimental design. Time series data on the study variables from January 2000 to June 2019 were obtained from the Statistical Bulletin of the Central Bank of Nigeria. Models were specified accordingly, the statistical analyses were carried out using the Markov Switching Intercept Vector Autoregressive Models, the pre and post-diagnostic tests were also conducted. The unit root test results showed I (1). VAR lag length selection criteria choose lag 2. The MS-VAR analysis identified two regimes (expansion and contraction), the information criteria selected the Markov-Switching Intercept Autoregressive Heteroschedastic 2 Variance Auto-regression 2 [MSIARH (2) - VAR (2)]. The MS-VAR results in regime 1 showed that lags 1 and 2 of total export significantly affected total export and total import, Lags 1 and 2 of total import had significant effects on exchange rate while lags 1 of exchange rate and lags 1 and 2 of exchange rate had significant effects on inflation rate. In Regime 2, lag 1 of total export and lag 2 of exchange rate had significant effects on total export. Only lag 2 of inflation rate had significant effects on exchange rate while lag 2 of total export and lags 1 and 2 of exchange rate had significant effects on the inflation rate. The results also showed an 89% probability of staying in regime 1 for a duration of 8 months 8 days and 57% probability of staying in regime 2 for 2 months 10 days. It was concluded that the MSIARH (2) - VAR (2). It was recommended that the right-hand side variables should be tested for endogeneity before concluding on single or system equation. It was also recommended that the possibility of regimes should be verified before concluding on linear or nonlinear models.