Trade Indicators Research Articles

Market Openness and Its Relationship to Connecting Markets Due to COVID-19

In this research, statistical models were formulated to study the effect of the health crisis arising from COVID-19 in economic markets. Economic markets experience economic crises irrespective of effects corresponding to financial contagion. This investigation was based on a mixed linear regression model that contains both fixed and random effects for the estimation of parameters and a mixed linear regression model corresponding to the generalisation of a linear model using the incorporation of random deviations and used data on the evolution of the international trade of a group of 42 countries, in order to quantify the effect that COVID-19 has had on their trade relationships and considering the average state of trade relationships before the global pandemic was declared and its subsequent effects. To measure, quantify and model the effect of COVID-19 on trade relationships, three main indicators were used: imports, exports and the sum of imports and exports, using six model specifications for the variation in foreign trade as response variables. The results suggest that trade openness, measured through the trade variable, should be modelled with a mixed model, while imports and exports can be modelled with an ordinary linear regression model. The trade relationship between countries with greater economic openness (using imports and exports as a trade variable) has a higher correlation with the country’s health index and its effect on the financial market through its main trading index; the same is true for country risk. However, regarding the association with OECD membership, the relations are only with imports.

An Examination of Exchange Rates on Foreign Tourist Flows into ASEAN-3

This research aims to analyze the effect of exchange rates on foreign tourist flows in ASEAN-3. A fixed-effect model is used to estimate data from three ASEAN countries, namely: Indonesia, Malaysia, and Thailand from 1995 to 2016. The result shows that the exchange rate has a significant positive effect on foreign tourist flow. In other words, the depreciation of domestic currency increasing foreign tourist flow. Other control variables such as income per capita, HIV prevalence, trade, and consumer price index significantly affect a different sign.

The Impact of COVID-19 Pandemic on Stock Market: Evidence from Romania.

The current health crisis has several socioeconomic influences that could be compared to those experienced during the 2008 economic and financial crisis. Governments around the world are making great efforts to sustain markets as there are signs showing that the health crisis will be followed by an economic crisis. In this study, we aim to investigate the impact of COVID-19 on the Romanian stock market. For this purpose, we considered the influence on the Bucharest Exchange Trading (BET) index of such variables as the number of new cases and the number of new deaths caused by COVID-19, measures taken by authorities, and the international economic context. The collected data covered the period between 11 March 2020 and 30 April 2021. The Autoregressive Distributed Lag (ARDL) Bound cointegration test was used to measure the impact of COVID-19 on the stock market. The results showed a significant long-term negative impact of the pandemic on the BET index for Romania, while the European economic context had a positive influence. Therefore, these results could be used by authorities as a good guideline for the efficient management of measures that aim to reduce the negative effects of the healthcare crisis.

A Study on the Qualitative Trade Competitiveness of China to Japan in Information Technology Industry

Purpose: The purpose of this paper was to estimate the qualitative trade competitiveness of China with Japan relative to the information technology (IT) industry covering the period from 2007 to 2017. Research design, data, and methodology: Revealed Comparative Advantage (RCA), and Market Comparative Advantage (MCA) are used. Further, an Intra-industry Trade (IIT) index is used to analyze qualitative changes in horizontal intra-industry trade and intraindustry trade of high- and low-quality goods. Results: According to a general comparative advantage analysis, the IT industry has remained relatively inferior in trade with Japan. and mainly exports goods of inferior quality and imports goods of superior quality. Broadcasting equipment and information equipment mainly export inferior quality items and export superior quality items. In the case of electronic and semiconductor parts and equipment, inferior quality items are mainly exported, but the quality of export items has improved. As a result, it cannot be overlooked that the proportion of exports of superior quality items has increased. Also, in the case of communication equipment, it was found that items of inferior quality were mainly exported, but the proportion of exports of superior quality increased significantly, which indicates that the quality of export items has improved. Implications: In the trade with Japan, China’s IT industry’s exports and imports have increased. Although the deficit has decreased, it is still at a relatively disadvantage, especially for semiconductors, broadcasting equipment, and flat-panel display manufacturing equipment. In order to solve these problems, it is necessary to increase the production of high value-added products and further improve the technological level. In this regard, the Chinese government should actively formulate development plans and increase policy and capital investment.

Measurement errors in index trader positions data: Is the price pressure hypothesis still invalid?

AbstractIn this paper, we examine whether the repeated rejection of Masters's price pressure hypothesis is robust with respect to measurement errors in index trader positions data. We allow for autocorrelated errors and a potential impact of index trader positions on both the level and volatility of commodity returns. The resulting state‐space model is estimated via particle Markov chain Monte Carlo (PMCMC). The empirical investigation relies on weekly data for 12 commodities listed in the SCoT and DCoT reports from 2006 to 2020. Our empirical findings show that the rejection of the price pressure hypothesis is robust concerning the inclusion of measurement errors in index trader positions data.

Financial investments and commodity prices

In this paper, we show that financial investments dilute the relationship between convenience yields (a proxy for fundamentals) and commodity prices. On average, the explanatory power of convenience yields on the movements of commodity prices decreased from 63% to 33% after 2004, when institutional investors rapidly started building their positions in commodity futures. We develop a model of the commodity market with financial investments and test the model predictions using futures prices of 21 US-traded commodities and index traders' positions on 12 agricultural commodities. Because of correlated financial demands for different commodity futures, we identify comovements in spot prices for fundamentally independent commodities.

COVID-19 Pandemic and Romanian Stock Market Volatility: A GARCH Approach

This paper investigates the volatility of daily returns on the Romanian stock market between January 2020 and April 2021. Volatility is analyzed by means of the representative index for Bucharest Stock Exchange (BSE), namely, the Bucharest Exchange Trading (BET) index, along with twelve companies traded on BSE. The quantitative investigation was performed using GARCH approach. In the survey, the GARCH model (1,1) was applied to explore the volatility of the BET and BSE traded shares. Conditional volatility for the daily return series showed noticeable evidence of volatility that shifts over the explored period. In the first quarter of 2020, the Romanian equity market volatility increased to a level very close to that recorded during the global financial crisis of 2007–2009. Over the next two quarters, volatility had a downward trend. Besides, after VAR estimation, no causal connection was found among the COVID-19 variables and the BET index.

A Tale of Two Premiums Revisited

This paper investigates the effect of the “financialization” of commodity markets in terms of pricing. I explore whether the emergence of commodity index traders affects weekly returns and turnover during the roll periods. I split the sample (1994–2017) into the pre-financialization (1994–2003) and the post-financialization (2004–2017). I directly test whether the market share of index traders contributes to commodity returns and whether risk adjustments (based on momentum, basis, basis-momentum, open interest, crowding, and average factors) alter liquidity and insurance premiums documented in Kang, Rouwenhorst, and Tang (2020). I also examine how the financialization affects liquidity and insurance premiums. Finally, since previous results are obtained with Fama-MacBeth regressions, I use an alternative method totest how liquidity and insurance premiums determine commodity returns.

Natural Resources, International Commodity Prices and Economic Performance in Sub-Saharan Africa (1990–2019)

Abstract In this paper, we investigate the link between windfall gains and losses of income associated with commodity exports and economic performance in a panel of 45 sub-Saharan African (SSA) countries over the period from 1990 to 2019. Windfall gains and losses of income are measured in terms of fluctuations in a country-specific commodity terms of trade (CTOT) index in which each commodity is weighted by the ratio of exports of that commodity in the country’s gross domestic product (GDP). The CTOT index therefore reflects the commodity export specialisation for individual countries. The data on CTOT are taken from the International Monetary Fund. Additionally, we use changes in real GDP per capita as our SSA economic performance measure. We employ a random coefficient model that yields individual estimates for each of the countries included in the analysis. Our approach is based on the assumption that the effect of windfall gains and losses on real GDP per capita growth varies across different SSA countries. Our main conclusion can be elaborated as follows: first, natural resources have undoubtedly contributed to higher economic growth in SSA countries since 1990. Second, when SSA countries are analytically divided into two groups depending on their commodity export specialisation, we find that resource-rich countries—in particular oil rich—are the best economic growth performers during the observation period. Finally, we find that windfall gains from commodity exports are not significantly associated with increased real GDP per capita growth in most agriculture-exporting countries.

Impact of COVID-19 on Urban Energy Consumption of Commercial Tourism City

In 2020, the COVID-19 pandemic has spread worldwide. To alleviate this spread, various blockade policies have been implemented in many areas. This has led to a sluggish demand in the world's major economies, sharp drop in the trade index, and negative growth in energy consumption. To formulate a better epidemic prevention policy for urban energy consumption of commercial tourism cities, this study summarizes the major statistics of energy supply and demand before and during the epidemic period based on actual data. The characteristics of energy consumption in different sectors, including hotels, transportation, tourism culture, and public utilities, are then analyzed in detail. Finally, the energy consumption features of commercial tourism cities represented by Macao are compared to those of other typical countries (e.g., Italy, United States, Japan, and Brazil). These analyses demonstrate the impact of COVID-19 on the energy consumption in commercial tourism cities, which provides insights for the government or energy providers to formulate policies to adapt to this pandemic.

The EAEU Free Trade Agreements as a New Viable Format for the Russian Trade Policy

The Regional Trade Agreements (RTA) as a legal format of trade between countries has been actively developed within the last decades. Russian involvement in RTAs until recently was modest. However, after the EAEU creation in 2015, trade policies of the member countries have changed. Setting up the RTAs has become an important priority of the EAEU’s common trade policy. In this study, the assessment is made of the significance for the Russian domestic policies of the already signed and planned FTAs. The focus of the methodology of the study lies in computations of three trade indices: export significance index (suggested by authors and based on the revealed comparative advantage index), trade intensity index and symmetric trade introversion index, which were calculated for the totality of trade partners of Russia for 2019 (193 countries) in order to identify the most promising countries to conclude new FTAs. Authors come to a conclusion that the already signed Russian RTAs and newly planned Russian common FTAs on behalf of the EAEU have a potential to generate trade. Another important result of the study is that it provides the list of the first-priority countries for the new-coming FTAs for Russia and the EAEU partners in terms of efficiency in generating trade, that are - Egypt, Turkey, Algeria, Republic of Korea and Mongolia. The authors suggest to make similar calculations for other countries to support the revealed pattern.

Research on Spatial Dependence and Influencing Factors of Korean Intra-Industry Trade of Agricultural Products: From South Korea’s Agricultural Trade Data

Purpose - Intra-industry trade of agricultural products can eliminate the disadvantage of Korea s traditional agriculture and improve its lack of comparative advantage. The main purpose of this paper is to measure the level and index of intra-industry trade of Korean agricultural products and to explore the spatial dependence and spillover effect associated with this type of trade. The main factors influencing intra-agricultural trade are analyzed from two perspectives: the population and the classification of agricultural products. Design/methodology - First, the level of intra-industry trade of Korean agricultural products is measured. Second, to obtain a more accurate estimate of the influence of various factors, and based on two types of weight matrices, a spatial econometric model is constructed from two aspects: population and classification of agricultural products. The status and the factors influencing intra-industry trade are also studied. Findings - It is concluded that there is a positive spatial correlation between Korea’s intra-industry trade in agricultural products and that of its trading partners. The spatial spillover effect of this type of trade is verified by using the spatial autoregressive model (SAR). Labor-intensive agricultural products are found to have a positive spillover effect on intra-industry trade, while land-intensive products do not have a significant effect. Originality/value - In this paper, the two types of agricultural products are meticulously distinguished, and the spatial effect of the intra-industry trade of agricultural products as well as the influence of various factors are analyzed. In addition, the accuracy of the estimation of the coefficients of the factors by using the spatial econometric model is higher than that of the ordinary panel data model.

Environmental Impact of the Shadow Economy, Globalisation, Trade and Market Size: Evidence Using Linear and Non-Linear Methods

The achievement of the Sustainable Development Goals (SDG) related to the environment requires identifying new sources of environmental degradation. In this research, we examine the impact of the underground economy on polluting gas emissions. This relationship was estimated, including the role of globalization, trade, and market size. Using annual data from the World Bank and the International Monetary Fund, we found that, in the short term, the underground economy had a negative effect on global environmental pollution and a long-term negative impact. In the long term, the cointegration results indicate a long-term relationship between the series included in the investigation. The existence of a long-term relationship between the variables implies that as the underground economy increases, the emissions of polluting gases also change. In the long term, policymakers can use the black economy as an instrument to influence environmental pollution. Likewise, we found a threshold effect in the index of globalization, trade, and market size. The existence of a threshold effect implies that from a threshold, the impact of globalization, trade, and the size of the market on polluting emissions is more significant. Therefore, the environmental policy must consider these aspects to achieve greater effectiveness of regulation in favor of the environment. The results were stable, including the dependence of the cross-sections and the heterogeneity in the slope of the panel. Actions to mitigate polluting gas emissions should regulate informal and clandestine activities and take advantage of globalization and trade to improve the practices of companies and individuals.

БРИКС и партнерство в интересах устойчивого развития: перспективы расширения торговли с наименее развитыми странами

The informal BRICS group (Brazil, Russia, India, China and South Africa) is actively working to solve the most acute global problems. This is why opportunities for implementing the sustainable development goals (SDGs) at BRICS summits is a topic for urgent research. This article discusses the prospects for achieving SDG 17.11 by the least developed countries (LDCs) in the framework of mutual trade with BRICS. SDG 17.11, unlike other goals, was expected to be achieved in 2020, but World Trade Organization (WTO) estimates for 2018 showed that progress was too slow. Against the sharp drop in international trade in 2020 due to economic shutdowns, the implementation of this goal is especially high on the agenda. This article describes the current implementation of the SDG by BRICS. A general analysis of mutual trade between LDCs and BRICS shows the low involvement of least developed countries in trade with BRICS. The methodology for the study involves computations of two trade indices and the identification of new clusters of LDCs. The export propensity index and trade intensity index are calculated in order to identify the countries with the most promise to increase exports to BRICS. The authors selected 13 LDCs with prospects for trade development with BRICS—Angola, Democratic Republic of the Congo, Mozambique, Bangladesh, Guinea, Mauritania, Nepal, Tanzania, Zambia, Bhutan, Lesotho, Malawi and Solomon Islands. Among 34 other LDCs, the authors identify five clusters based on their economic structure, including the role played in their economies by official development assistance (ODA) and personal remittances. Clustering allows BRICS to provide targeted support to LDCs in order to increase their export potential through the most effective mechanisms for each economy.

The Construction of Illicit Tobacco Trade Index

Background: We constructed a composite index, which measures the enabling factors of illicit tobacco trade for 160 countries. Data and Methods: We collected the most recent and best available data for various variables on general governance, tobacco control policies, trade and customs practices. These factors are known determinants of illicit tobacco trade. We used geometric aggregation method to calculate the score for each country. The higher the score the lower vulnerability of a country to illicit tobacco trade. Results: The ITT index scores of 160 countries ranged from 0.1 to 0.69. We observed a strong positive relationship between ITT index scores and GNI per capita and negative relationship with the share of illicit tobacco trade to total tobacco consumption. Several high-income countries have notably lower ITT scores. Conclusion: The ITT index could be used to track the enabling factors of illicit tobacco trade. Low and middle-income countries are more vulnerable to illicit tobacco trade as suggested by the lower ITT score. The lower ITT score in LMICs was largely driven by the relatively low scores in tobacco control policies and trade and custom practices and conditions.

The Dynamics of Cointegration Between Economic Growth and Financial Development in Emerging Asian Economy: Evidence from India

The present article examines the relationship between economic growth and financial development in the context of Indian economy over the period of 15 years from June 2003 to February 2018. The study employs cointegration test, involving Johansen Juselius Cointegration and autoregressive distributed lag (ARDL) Bounds test approach to ascertain the long-run relationship between financial development and economic growth. The study further employs fully modified ordinary least squares—OLS—(FMOLS), dynamic OLS (DOLS) and canonical cointegration regression (CCR) models to ascertain the sensitivity and robustness of the estimates derived from ARDL Bounds test approach. The stability of the models employed in the study are further confirmed by rolling window analysis and the cumulative sum (CUSUM) and cumulative sum of squares (CUSUMSQ) tests. The outcome of the article reports the existence of long-run equilibrium relationship between economic growth represented by Index of Industrial Production and Financial Development represented by the Bombay Stock Exchange (BSE) Index and BSE Volume of Trade. The article also involves consumer price index as proxy for inflation, exchange rate, ratio of export to import and weighted average call rate as control variable to also examine their impact on the Indian economic growth. The study confirms the existence of Supply Leading Hypothesis, that is, existence of unidirectional causality running from financial development to economic growth in the Indian economic scenario. The outcome of the article indicates the positive and significant influence of development of financial markets represented by stock market on the economic growth.

AGRICULTURAL INTRA-INDUSTRY TRADE IN SERBIA

Intra-industrial trade is the exchange of products between countries in the same sector of the economy. A significant part of export and import in goods takes place within the same sector of the economy. This paper analyzes the intra-industrial trade in agricultural products of Serbia and its foreign trade partners from 2004 to 2018. The Grubel-Lloyd intra-industrial trade index was used as a measure. The value of GLI in agricultural products increased over the observed period, ranging from 0.485 to 0.590 as in 2018, while the number of IIT-dominated groups ranged from 26 to 35. The results obtained indicate that vertical IIT is more prevalent than horizontal IIT and that the export of products with lower prices dominates, i. e. those that are, according to the assumptions of the model, of lower quality than the imported products. Dynamic change analysis shows that certain changes in the IIT pattern occur over time, but that changes are gradual without sudden peaks in the IIT structure.

BARTER TERMS OF TRADE IN LATVIAN TRADE IN AGRICULTURAL COMMODITIES AND PROCESSED FOOD PRODUCTS

Since early nineties, Latvia has remained a net importer of agri-food products. At the same time, both exports and imports of agricultural commodities and processed food products has consistently grown, with total trade turnover increasing. The objective of the study is to determine the trends in development of barter terms of trade in Latvian agricultural commodities and food products. To reach the research objective, barter terms of trade indices were compiled with various levels of data aggregation over the period from 2002 to 2012. The research results in general show consistently higher terms of trade in agricultural commodities in comparison with terms of trade in processed food products. The differences exist between the terms of trade for the same products or product groups depending upon the level of aggregation. Trends in development of barter terms of trade indices for agricultural commodities and processed food products are different. In general, barter terms of trade for whole agri-food sector is not deteriorating. Key words: international trade, barter terms of trade, agricultural commodities, processed food products. JEL CODES: F60, Q17 DOI: http://dx.doi.org/10.15181/rfds.v14i3.865

Measuring and forecasting retail trade in real time using card transactional data

We build big data retail trade indicators for Spain using high-dimensional card transaction data from one of the country’s biggest banks. The resulting indicators replicate the dynamics of the Spanish retail trade indices (RTI), regional RTIs (Spain’s autonomous regions), and RTI by retailer type (distribution classes) released by the Spanish National Statistics Institute. The new indicators not only have a higher frequency (daily data) and higher geographical and sectorial breakdown but are also shown to improve nowcasting and forecasting power for the official RTI, making them key variables to monitor consumption.

The forecasting of consumer exchange-traded funds (ETFs) via grey relational analysis (GRA) and artificial neural network (ANN)

Our study uses the grey relational analysis (GRA) and artificial neural network (ANN) models for the prediction of consumer exchange-traded funds (ETFs). We apply eight variables, including the put/call ratio, the EUR/USD exchange rate, the volatility index, the Commodity Research Bureau Index (CRB), the short-term trading index, the New York Stock Exchange Composite Index, inflation, and the interest rate. The GRA model results showed that the NYSE, CRB, EUR/USD, and PCR were the four main variables influencing consumer ETFs. The GRA test results of all the ANN models' data showed that the back propagation neural network (BPN) was the best predictive model. Based on the classification of different percentages of training data, the results of GRA revealed that the radial basis function neural network and the time-delay recurrent neural network exhibited consistent results, compared to BPN and the recurrent neural network. The results also pointed out that different percentages of training data were suitable for predicting consumer ETFs' performance based on high and low grey relationship grade variables. Evidence has shown that the ETFs in Brazil and China are more predictable than those in other countries. All ANN models' results indicated that the use of 10% testing data could predict consumer ETFs better, particularly the ETFs of the United States (US) and those excluding the United States (EX-US). The Diebold–Mariano (DM) test results suggest that the best predictability model for consumer ETFs is BPN, which is significantly superior to other models.