Gravity Model Of Trade Research Articles

The impacts of carbon tariffs on international trade flows and carbon emissions: An analysis integrating trade elasticities with an application to US-China trade

Carbon tariffs have been widely studied as a prominent climate policy in terms of their influences on the economy and the environment. However, previous studies of their effectiveness did not incorporate into the analysis of some key factors, including, notably, trade elasticities. This paper aims at reducing the gap between trade economics and environment studies by integrating trade elasticities into the analysis of carbon tariffs' impacts on trade flows and carbon emissions embodied in exports. We start by adopting the gravity trade model and constructing a panel data set of 63 countries from 2005 to 2015 to calculate the trade elasticities across 13 industries. With a simple model that translates carbon tariffs into tariffs, we evaluate the cross-country and cross-industry impacts of carbon tariffs. A model to forecast the effect of carbon tariffs on China-US trade under different scenarios is also provided. We discover that industries' trade elasticities and carbon intensities play an essential role in determining carbon tariffs' impacts. Furthermore, our estimations show the threshold carbon tariffs for the 13 industries with an average of $42/tCO2. We found out that if the U.S. stopped importing from China by replacing all Chinese exports with its domestic productions, it would emit 88.8% fewer carbon emissions than China does, which would contribute to a 0.65% decrease in world carbon emissions. Other scenarios of replacing all Chinese exports with Canadian, Japanese, or Mexican exports show similar results. This paper illuminates the critical importance of incorporating trade elasticities when designing carbon tariffs.

A Machine Learning Approach to Forecast International Trade: The Case of Croatia

Abstract Background: This paper presents a machine learning approach to forecast Croatia’s international bilateral trade. Objectives: The goal of this paper is to evaluate the performance of machine learning algorithms in predicting international bilateral trade flows related to imports and exports in the case of Croatia. Methods/Approach: The dataset on Croatian bilateral trade with over 180 countries worldwide from 2001 to 2019 is assembled using main variables from the gravity trade model. To forecast values of Croatian bilateral exports and imports for a horizon of one year (the year 2020), machine learning algorithms (Gaussian processes, Linear regression, and Multilayer perceptron) have been used. Each forecasting algorithm is evaluated by calculating mean absolute percentage errors (MAPE). Results: It was found that machine learning algorithms have a very good predicting ability in forecasting Croatian bilateral trade, with neural network Multilayer perceptron having the best performance among the other machine learning algorithms. Conclusions Main findings from this paper can be important for economic policymakers and other subjects in this field of research. Timely information about the changes in trends and projections of future trade flows can significantly affect decision-making related to international bilateral trade flows.

Analysing the Flow of Intra-Industry Trade in the Central African Monetary Community

This paper empirically examines the flow of Central African Economic and Monetary Community (CEMAC) intra-industry trade at different sectors and product categories using the Standard International Trade Classification (SITC). An augmented gravity model of trade was adopted to analyse changes in the different sectors and product categories from 1995 to 2015; this is the time span for which consistent and useable time series data is available for CEMAC. A time fixed effects variable and within estimator were included to control for unpredictable changes in exogenous factors and capture the heterogeneity of the sample over time. The results showed that prior to the formation of the CEMAC customs union, the growth in intra-industry trade had been higher than that of the CEMAC customs union with the exception of very few sectors and that since the establishment of the customs union in 1994, IIT trade has remained low and only Cameroon has witnessed an increase in trade with member states, especially in food and live animals. The results also showed that only mineral fuels exports had been significant and positive for Chad and Equatorial Guinea.

Is dirty trade concentrating in more polluting countries? Evidence from Africa

Among growing concerns about the environmental impact of human activities, international trade is increasingly in the spotlight. However, the role of Africa has been widely disregarded. In this paper, we assess the trade–environment link in African trade patterns by estimating a gravity model for trade with data from 140 countries for the period 2002–2018. Our findings reveal significant insights: first, that dirty trade appears to be increasingly concentrating in African countries. That is, exports of dirty goods seem to have shifted to countries with less stringent environmental regulations. Second, exports from dirty industries tend to concentrate in those countries with higher levels of capital endowments, although this effect appears to be weaker. Third, the results hold when we consider different exporter and importer country scenarios, such as trade flows with Europe (the main African trading regional partner) and intraregional African trade patterns. In addition, they hold especially for more differentiated products, with some particularities in the case of homogeneous ones. These findings have important implications in terms of both trade and environmental policies as well as for building the basis for sustainable development in Africa.

Patterns and drivers of embodied carbon intensity in international exports: The role of trade and environmental policies

International production fragmentation has generated and reallocated value added as well as CO2 emissions across economies. Prior studies have mainly focused on the embodied emissions or value added in trade. The evidence regarding the embodied emission intensity, and particularly the role of policies, however, remains sketchy. This paper investigates the role of trade and environmental policies in embodiment flows by combining input-output analysis and the gravity model of trade, covering 43 economies over 2000–2014. First, we derive the domestic carbon and value-added contents of bilateral exports in an input-output framework, and find a declining trend in emission intensity in exports. Second, we use the gravity model to examine the determinants of trends in both flows, and further infer the combined effects on intensity. The results show that an open trade policy can lower emission intensity in exports by facilitating the selection of products that are higher in value-added but less emission-intensive. Economies with more stringent environmental policies have a lower emission intensity in exports, but a higher emission intensity in their imports, which suggests carbon leakage. Effective global climate mitigation will require a closer look at the emission intensity in exports and collective action to address the detrimental effects of carbon leakage.

The impact and externalities of natural disasters on local tax revenue in Colombia

ABSTRACT This paper studies the impact of natural disasters on tax revenue across Colombian municipalities. We follow a two-step approach to evaluate how a municipality’s tax revenue depends on natural disasters taking place both locally and in its trade partners. In the first step, we estimate a gravity model of bilateral trade and construct a matrix of estimated bilateral trade shares, allowing us to measure the strength of the economic relationships between municipalities. In the second step, our results reveal that natural disasters in the destination municipalities increase the tax revenue in the origin cities.

Effects of Development Aid on Donor’s Exports: A Case of the Czech Republic

Abstract The main goal of foreign aid should be the support of developing regions; however, due to the rising international requirements on the amount of provided aid, donors start to focus on the benefits aid can bring them as well. Both country-specific and general studies have been conducted to evaluate the return of aid from the donor’s perspective, with the majority of them suggesting that provided aid boosts donor’s exports to the developing countries. As no such analysis exists for the Czech Republic, this paper tries to fill this gap and aims to find out whether there is a positive relationship between the Czech aid and Czech exports. While employing the gravity model of international trade, the study, however, suggests that the Czech aid is not statistically significant for the volume of Czech exports. Unlike other donors, the Czech Republic thus leaves a considerable trade potential arising from the foreign aid untapped. The reasons might be other motives behind the Czech aid (both official and unofficial), poor co-operation of aid and trade policies, or changes in trade patterns.

The Influence Factors of China’s Cross-border E-commerce Export Trade Using Gravity Model

Purpose - This study examines the influencing factors of China’s cross-border e-commerce exports in the context of the current situation and trends of China’s cross-border e-commerce development. Through an improved trade gravity model, it provides more in-depth research and constructive opinions on the development of cross-border e-commerce in China. In this paper, factors such as consumption gap, volume of trade frictions, number of tourists, Internet usage and trade openness are added to the formula of the traditional trade gravity model in the improved trade gravity model to examine the influencing factors on China’s cross-border e-commerce exports.
 Design/methodology - According to the empirical analysis, China’s cross-border e-commerce exports to ten countries are used as dependent variables, and consumption gap, trade friction volume, trade distance, trade openness and number of Internet users are taken as independent variables. Regression analysis is conducted through a modified gravity model to test whether the hypotheses hold.
 Findings - The analysis shows that the hypothesis that China’s cross-border e-commerce exports are influenced by trade openness, trade distance, consumption gap between trade parties, and the number of Internet users in the importing country is supported by these four hypotheses, but not all independent variables have an impact on them. Specifically, the number of travelers, trade frictions do not have an impact on China’s cross-border e-commerce. That is to say, trade friction between China and the United States and political issues such as China-India and China-Japan territorial disputes that emerged before do not affect the development of cross-border e-commerce in China.
 Originality/value - The analysis shows that the factors influencing China’s cross-border e-commerce exports are the trade openness of the importing country, the trade distance, the number of Internet users in the importing country, and the consumption gap between the two sides of the trade. The trade openness and the number of Internet users positively contribute to China’s cross-border e-commerce, while the consumption gap and trade distance are negatively related to them. And the analysis found that the Sino-US trade war and the Sino-Indian territorial disputes and other trade frictions to China’s cross-border e-commerce exports did not have a substantial impact.

What does the clean energy transition look like for Russian oil exports?

AbstractThe commitment of governments to achieving the goals of the Paris Agreement and the expected decrease in fossil fuel consumption indicate the importance of studying the risks facing the oil exporters and the range of options and responses. This study adopts the Trade Gravity model to examine the effect of clean energy policies on Russian oil exports during the period 1996–2019. Our results based on Cross‐Sectional Autoregressive Distributed Lags modeling suggest that Russian oil exports are negatively affected by the energy transitions. This indicates that investing in cleaner energy technologies as a channel toward reducing fossil fuel demand can reduce the oil trade globally. Policies and strategies to retain and support the financial stability of the Russian government under the current scenario are suggested.

Using the gravitational mixed models to analyze the impact of China's foreign direct investment along with The Belt and Road countries on trade flows.

Since the “The Belt and Road” initiative was put forward in 2013, China's foreign investment growth rate has been greatly accelerated. In The Belt and Road context, many scholars used models to analyze the relationship between foreign direct investment, trade flows, and import and export trade. From literature reviews, it is found that previous scholars do not conform to reality and cannot be studied dynamically. Therefore, this study used the panel data of China's foreign direct investment and import and export trade in 40 countries along “The Belt and Road” from 2010 to 2019 to focuses on the impact of foreign direct investment (FDI) on trade flows, import trade and export trade. Regression analysis was carried out with the trade gravity model and Tinbergen's trade gravity model. In addition to model variables and arguments, the following control variables were adopted: exchange rate, natural resource rents, labor force population, differences in consumer ability, trade openness, and trade agreement signing. The results found that: (1) Foreign direct investment has a positive correlation with trade flow and import and export trade. (2) The labor force population has a negative correlation with trade flow, and import and export trade. (3) The expansion of China's economic scale can increase the scale of China's import and export trade, at the same time, the gap in consumption levels between the two countries will restrict the degree of import and export trade. (4) The possession of natural resources can also promote the development of trade.

Gross Product, Population Distribution and Heterogeneity of Border Effects in Gravity Models of Trade

Gross Product, Population Distribution and Heterogeneity of Border Effects in Gravity Models of Trade

Ukraine war-induced sanctions against Russia: Consequences on transition economies

We analyze the spillovers of Western economic sanctions against Russia into twenty-seven transition economies of the former Soviet Union, and Central and Eastern Europe. These spillovers are measured in terms of their impact on bilateral trade and direct investments for the period of 2014–2018. We construct a new dataset to quantify each episode of Western/US sanctions against Russia. The gravity models of bilateral trade and direct investment are used and the data analysis is conducted using Poisson pseudo-maximum likelihood econometric technique. We estimate that the Western and U.S. sanctions against Russia spilled over into third-party small countries. These sanctions resulted in the significant decline of exports from transition economies, Russian imports to transition economies, and Russian direct investments to transition economies. Interestingly, the direct investments to Russia from transition economies sharply increased during the same period. The quantitative estimates of the spillovers suggest the following cumulative changes. Due to an imposed sanction type (e.g., against an individual, entity or sector) each episode of Western/U.S. sanction resulted in the decline of aforementioned indicators in the range of 10.9–30.5-million-dollar/5.6–16.9-million-dollar of exports from transition economies, 6.3–17.7-million-dollar/3.3–9.8-million-dollar of Russian imports to transition economies, and 3.4–9.4-million-dollar/1.7–5.2-million-dollar of Russian direct investments to transition economies. The direct investments to Russia from transition economies increased by 10.9–30.6-million-dollar/5.7–17-million-dollar, respectively.

Challenges for Western Balkan Countries Regional Integration: the Case of North Macedonia

This paper aims to elaborate on the possibilities that increased regional integration initiatives can have in boosting mutual trade among the countries in the Western Balkans region, such as: creating a Regional Economic Area by 2023; the creation of a Common Regional Market based on EU rules in the period 2021-2024 and the initiative “Open Balkan” created between North Macedonia, Serbia, and Albania for enabling free movement of goods and free movement of workers. For our research, the gravity model of trade for North Macedonia covering the period 2005-2020 is applied. The influence of bilateral and regional trade agreements on the country’s trade is analyzed. The results have shown that for North Macedonia, CEFTA-2006 membership has higher significance for increasing trade when compared to the agreement signed with the EU and to the other bilateral free trade agreements signed with EFTA, Turkey, and Ukraine. This paper point out that deepening trade integration through different regional initiatives could have a positive influence on increasing mutual trade.

Eurasian economic integration: impact evaluation using the gravity model and the synthetic control methods

The study examines the impact of Eurasian integration at aggregate country and industry levels using the gravity model of trade and the synthetic control methods. We find that the establishment of the Eurasian Customs Union in 2010 and its further deepening resulted in notable trade creation effects with particularly sizable gains attributed to the commodities and chemicals sectors. The effects on other sectors, including textiles, machinery and transportation, while initially positive and significant, largely dissipated by the year 2015. The analysis also finds that the Eurasian integration, on average, has also facilitated trade with non-bloc trading partners. The results, however, are highly heterogeneous across the members of the bloc. The net impact on trade flows of Eurasian integration was overwhelmingly positive for Belarus, generally positive for Russia and mixed for Kazakhstan.

A calibrated gravity model of interregional trade

ABSTRACT Lack of interregional trade data is often a major obstacle when doing economic analysis at the subnational level. This paper discusses a calibration procedure for estimating bilateral trade between the regions of a country. Our approach can be equivalently characterized as an application of the gravity-RAS or the doubly constrained gravity model method. Either way, a crucial element is represented by the distance elasticity parameter, which the user is expected to provide exogenously. We propose a way of estimating that parameter using standard econometric methods with readily available data and demonstrate our calibration procedure in a case study of Italy.

China's global value chain linkage and logistics performances in emerging ASEAN economies

AbstractThis paper aims to evaluate the extent of China's forward linkage of global value chains (GVCs) with emerging market economies of the Association of Southeast Asian Nations (ASEAN) compared to those with the United States and Japan, and also to examine the nexus of China's forward GVC linkage with logistics performances in emerging ASEAN economies as China's trade partners. This study uses the UNCTAD‐Eora Database and applies a structural gravity trade model for empirical analysis. The statistical observations identified the major position of China's GVC, which has transformed from a backward linkage to a forward linkage since the mid‐2000s. The empirical estimation verified that there is less linkage in China's forward GVC with emerging ASEAN economies than with the United States and Japan, and demonstrated that the lack of logistics performances in emerging ASEAN economies has been a significant factor in explaining the less linkage in China's forward GVC with them.

Trade Development in Pakistan: An Evidence by Gravity Model Approach

This study estimated the trade potential of Pakistan by using the gravity model of trade. In this research, the panel data is used for the time period 1995-2018 for 42 counties under analysis. The country's potential trade is predicted with some specific trading partners as well as globally in the context of coefficients results obtained from the model. The outcomes indicated that Pakistan's potential in terms of trade is at maximum level in (ASEAN), (EU), Middle East, Latin America and North America. The potential for trade is very lower with (SAARC) and (ECO). The key issues analyzed by this study are; political and social barriers with neighboring countries, specifically India and Pakistan, which are the biggest economies of SAARC. The same barriers seemed in the EU and NAFTA. In this situation, the Exports of Pakistan are badly impacted by political crises.

Research on Determinants and Potential of Goods Trade between China and ASEAN Countries under “the Belt and Road” Initiative

The trade between China and ASEAN countries has been very close since ancient times. Taking China and ASEAN countries as research objects, this paper analyzes the current situation and changing trend of China's and ASEAN countries' trade in goods based on the import and export data of both sides from 2001 to 2018. By using the trade gravity model, this paper empirically analyzes the determinants of trade in goods between China and ASEAN countries, and further calculates the trade potential of goods between China and ASEAN countries. The empirical results show that the GDP of China and ASEAN countries has a positive impact on bilateral trade, while the geographical distance between trading countries has a negative impact on bilateral trade. In terms of trade potential, China's trade in goods with more than half of the ASEAN countries still has a huge potential for expansion and a broad prospect for trade in goods.

The role of the One-Belt One-Road initiative in China?s exports and global value chains

Research background: China is regarded as the ?world factor? highly involved in international trade and plays an increasingly important role in the global value chains (GVC). Additionally, the ?One-Belt One-Road? (OBOR) initiative was proposed by the Chinese government to further promote China in the international market. Purpose of the article: The article explores the role of the OBOR in China?s exports and global value chain. It aims at: 1) verifying how OBOR impacts the volume of China's export and value-added export to its partners. 2) checking whether or not OBOR strengthens the industrial connection between China and its participants at the GVC level. 3) examining the different roles of corridors in China's exports and GVC. Methods: The empirical analysis is based on the augmented gravity model of international trade, which comprises China and its 197 partners in the period 2000?2018. The model is estimated for gross export as well GVC measured by domestic value added in export and the value contributed by a partner to China?s exports. Findings & value added: In general, there is a significant positive correlation between OBOR and the volumes of China?s export, domestic value-added trade and the value of partner?s contributed in China?s export. However, some of the results are blurred by OLS and FE methods. The author points out that FE-PPML estimation methods are more adequate. Among the six economic corridors, Bangladesh-China-India-Myanmar (BCIM), China-Pakistan (CP) and China Indochina Peninsula (CIP) were proven to play a prominent role in promoting China?s export, DVA and strengthening the links of global value chains. It is worth noting that the China-Mongolia-Russian Federation (CMRF) corridor harms China's export and DVA trade, and at the same time promotes countries in its region that benefit from trade with China.

Geopolitical Risk and Globalization

In this paper we examine the effect of geopolitical risks on globalization using Pseudo-Poisson Maximum Likelihood (PPML) methodology for gravity trade model. As a measure for globalization, we use bilateral foreign direct investment (FDI) data from 2001 to 2012 and bilateral trade data from 1948 to 2019. Ours is the first paper making use of the recently created geopolitical risk (GPR) dataset using text analysis to test its effect on globalization. For the univariate model, we find a significant decline in FDI by 3.6% and 0.5% in trade for 10% increase in geopolitical riskiness, but for multivariate model we only see a significant increase in trade by 0.04%. We test the robustness of our results by doing more granular analysis by using individual country GPR measures as well as using KOF Globalization Index instead of FDI and Trade flow. Here also we see a significant negative effect of geopolitical risk on globalization.