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This paper examines the cyclicality of remittance inflows to economies in Asia and the Pacific, aiming to identify major factors associated with remittances using gravity models of bilateral remittances. An analysis that assesses correlation coefficients between the cyclical factors of remittances and gross domestic product suggests that remittances tend to be countercyclical, or acyclical, against the business cycle of the remittance-receiving economy relative to the sending economy. This observation is confirmed by the gravity models of bilateral remittances. Furthermore, the estimation results suggest that migrant stock is one of the most significant factors affecting bilateral remittances. The study also shows that an increase in bilateral remittances can be attributed to a higher occurrence of disasters triggered by natural hazards in receiving economies, an appreciation of the receiving economy’s currency value against the sending economy’s, a lower interest rate differential (receiver–sender), greater capital account openness, more political instability, and lower costs of remittances.

Link prediction is a fundamental study with a variety of applications in complex network, which has attracted increased attention. Link prediction often can be used to recommend new friends in social networks, as well as recommend new products based on earlier shopping records in recommender systems, which brings considerable benefits for companies. In this work, we propose a new link prediction algorithm Local Neighbor Gravity Model (LNGM) algorithm, which is based on gravity and neighbors (1-hop and 2-hop), to suggest the formation of new links in complex networks. Extensive experiments on nine real-world datasets validate the superiority of LNGM on eight different benchmark algorithms. The results further validate the improved performance of LNGM.

This paper aims to describe the spatiotemporal transmission of COVID-19 and examine how various factors influence the global spread of COVID-19 using a modified gravity model. Log-linearizing the model, we run a negative binomial regression with observational data from 22 January 2020 to 31 December 2020. In the first model, population size and GDP per capita are positively related to the sum of newly confirmed COVID-19 cases within a 10-day window; the values for both variables are statistically significant throughout the study period. However, the significance of geographic distance varies. When a single geographic source exits in the early stage, the value is statistically significant. In the intermediate stage, when disease transmission is explosive between countries, the distance loses its statistical significance due to the emergence of multiple geographic transmission sources. In the containment stage, when the spread of disease is more likely to occur within a country, distance becomes statistically significant. According to the second model, the government’s internal movement control and nonpharmaceutical intervention policy, percentage of the population over 70 years old, and population-weighted density are statistically significant and are positively related to the incidence of COVID-19. By contrast, average monthly temperature, international travel restriction policies, and political regimes are statistically significant and negatively associated with the dependent variable.

The gravity model is a widely recognized tool for estimating the movement of people and goods. In this study, we introduce two gravitational variables, population size and regional GDP per capita (RGDPPC), to explain the characteristics of population movement between and within cities in South Korea. A log-linearized gravity model is employed to run regression analyses at three spatial levels: the national level (encompassing the entirety of South Korea), the metropolitan level (focusing on the Seoul and Busan Metropolitan Transportation Areas) and the city level (specifically in Seoul and Busan). The study incorporates data on various modes of transportation from 246 of the 250 municipalities in South Korea. Predictive performance of the model is better when utilizing national-level data. However, as spatial area decreases and population density increases, the models explanatory power decreases significantly when relying solely on data related to either population size or RGDPPC. The findings suggest that incorporation of both population size and RGDPPC into the gravity model best captures the dynamics of traffic flow within economically integrated regions. This relationship is analogous to gravitational fields generated by two distinct types of mass. Including both population size and RGDPPC, the gravity model can be leveraged effectively to estimate traffic patterns, particularly within regions characterized by high economic integration.

We study the effects of free trade areas on bilateral trade flows. We review and extend the previous empirical literature by embarking on the modelling of unobserved heterogeneity. We apply our preferred model to the case of the Asean Free Trade Area (AFTA). The estimation results suggest that there has been a positive effect of AFTA. This empirical finding is contrary to earlier estimation results, which are typically not so positive about AFTA. It is our impression that these earlier estimates on AFTA are confounded with the effects of unobserved determinants of trade.

This paper explores various non-tariff measures (NTMs) that co-exist in China and that directly influence imports into the country. Given the intensity and scope of technical measures imposed by China, the directional impacts of technical barriers to trade (TBTs) on bilateral Association of Southeast Asian Nations (ASEAN)-China exports are investigated empirically using an augmented gravity model. The results imply that Chinese TBTs do have some trade depressing effects from the ASEAN perspective. However, sectoral trade effects of TBTs are important as dual effects exist even within some TBT intensive product groups. This informs the policy debate on the effects of NTMs from the ASEAN-China perspective more specifically, and the "South–South" context more generally on two fronts. First, the identification of specific trade restricting measures for the affected sectors will assist in determining policy priorities within the ASEAN-China context. Second, trade facilitation measures that increase the business costs to the ASEAN exporters also warrant attention in addressing the scale of market access issues in China.

Using finely disaggregated data at six-digit harmonized code classification level, this paper examines the patterns and determinants of horizontal and vertical intra-industry trade in the automobile and electrical appliances sectors during the past few decades among the six major Southeast Asian countries. It is found from the analysis of the data that intra-industry trade is much higher than the inter-industry trade in each of these two sectors. Further, the determinants of these two types of trade are found to differ somewhat in terms of sign and magnitude across the sectors, implying the importance of sector-specific factors as influences on the pattern of trade.

The “Belt and Road Initiative” (BRI) has been launched by the Chinese government in 2013. The aim was to stimulate cross-border economic development in massive geographical areas covering Asia, Oceania, Europe, Africa, and Latin America which accounts for 80% and 40% of the world population and gross domestic product (GDP), respectively. The BRI has devised an extension of the “going global” strategy to reconfigure China’s overseas sector in order to extend its spillovers, and create more development opportunities for participating countries. In practice, cross-border infrastructure was a comprehensive role to reduce transportation cost; however, the BRI was vast by nature that includes financial support, policy cooperation, investment, trade facilitation, and people-to-people exchanges for the humanitarian strategy. Against this backdrop, the overarching objective of this study was to analyze the impact of the BRI and Chinese outward foreign direct investment (OFDI) on the bilateral trade between China and Sub-Saharan Africa countries. The investigation was carried out using a trade gravity model, balanced panel dataset, and multivariate regression estimation strategy for robustness checks covering 16 years. The result showed that Chinese OFDI, home, and host country’s GDP and GDP per capita income variables have a positive and statistically significant impact on the bilateral trade. Moreover, the BRI has explained positively on the bilateral trade; however, it does not have enough evidence to stimulate significantly, and it usually takes a long time for the effects of the BRI investment on trade and OFDI. The study also found that geographical distance and official exchange rates have explained negatively and statistically significant impact on the bilateral trade.

The identification of influential nodes is one of the most significant and challenging research issues in network science. Many centrality indices have been established starting from topological features of networks. In this work, we propose a novel gravity model based on position and neighborhood (GPN), in which the mass of focal and neighbor nodes is redefined by the extended outspreading capability and modified k-shell iteration index, respectively. This new model comprehensively considers the position, local and path information of nodes to identify influential nodes. To test the effectiveness of GPN, a number of simulation experiments on nine real networks have been conducted with the aid of the susceptible–infected–recovered (SIR) model. The results indicate that GPN has better performance than seven popular methods. Furthermore, the proposed method has near linear time cost and thus it is suitable for large-scale networks.

Researches on the human mobility have made great progress in many aspects, but the long-term and long-distance migration behavior is lack of in-depth and extensive research because of the difficulty in accessing to household data. In this paper, we use the resume data to discover the human migration behavior on the large-scale scope. It is found that the asymmetry in the flow structure which reflects the influence of population competition is caused by the difference of attractiveness among cities. This flow structure can be approximately described by the gravity model of spatial economics. Besides, the value of scaling exponent of distance function in the gravity model is less than the value of short-term travel behavior. It means that, compared with the short-term travel behavior, the long-term human migration behavior is less sensitive. Moreover, the scaling coefficients of each variable in the gravity model are investigated. The result shows that the economic level is the main factor of migration.

Finding important nodes in complex networks is an important topic. However, the location information obtained by many previous studies is not sufficient and effective, and the types of attributes applied also have limitations. Based on K-shell and gravity model, this paper proposes a node importance measurement method based on multi-attribute fusion. In this method, the objective, comprehensive evaluation of multiple attributes is obtained by the entropy weight method. Experiments on real networks show that the proposed algorithm can effectively measure the importance of nodes.

The impact of human mobility on the spreading of disease in a metapopulation is emphasized on interconnecting between patches, whereas the current volume of movement within the local population is usually neglected. Here, the role of internal commuters is taken into account by two means, a local transmission rate and the volume of internal commuters. Dynamic model of human mobility in the metapopulation with gravity coupling is presented. In conjunction with the disease spreading, the impact on invasion threshold and epidemic final size are analyzed. For two-patch model, we show that under fixing parameters in gravity model, the existence of invasion threshold depends on the difference of local transmission rates and the proportion of internal commuters between two patches. For a fully connected network with an identical transmission rate, the difference in patch final sizes is driven by patch distribution of internal commuters. By neglecting the effect of spatial variation in a simple core–satellite model, we show that the heterogeneity of internal commuters and gravity coupling induce a complex pattern of threshold, which depend mostly on the exponent in gravity model, and are responsible for the differences among local epidemic sizes.

This study aims to assess the trade potential of Pakistan in terms of destinations and products against 101 potential trading partners while applying the gravity model and the trade potential index. The findings indicate that Pakistan’s trade/export potential is maximum with the countries which are not its traditional trading partners. On the other hand, “manufactured goods”, “misc manufactured articles” and “food groups” are the products where maximum trade/export potential exists. Results indicate that Pakistan should not only adopt proactive measures to tap non-traditional partners but it is equally important to strengthen the level of trade with its traditional trading partners.

In this paper, we study trade imbalances between world countries in the period 1960–2011 using a complex-network approach. We show that trade imbalances in absolute value are characterized by a hierarchical arrangement wherein a few developed economies display high clustering and carry an important amount of global-trade imbalances. In contrast, trade imbalances in relative terms show a more fragmented topology, with less concentrated clustering which is particularly high for developing countries. In addition, we find that traditional null random-network models and the gravity model poorly predict the topology of trade imbalance networks. Our main finding is that the evolution of international trade has caused very heterogeneous imbalances in world economies, which may have important consequences for global instability and development.

This paper is focused on the in/stability of a collapsing anisotropic self-gravitating spherically symmetric compact fluid under the influence of non-minimally coupled f(R, T) gravitational theory, where R and T are traces of Ricci tensor and stress-energy tensor, respectively. We explore the f(R, T) equations of motion as well as conservation equations. We utilize the perturbation technique on dynamical equations, and physical quantities to get the collapse equation in a similar scenario. In the presence of considered f(R, T)-function (i.e. $f(R,T)=R-\zeta R_{c}tanh(\frac{R}{R_c})+\lambda RT$), to explain the dynamical behavior of the considered anisotropic relativistic fluid system. Furthermore, to address the issue of in/stability, the conditions on adiabatic index $\mathrm{\Gamma }$ i.e. stiffness parameter of fluid, are developed for Newtonian $(\mathrm{\text{N}})$-$epoch$ and post-Newtonian ($p\mathrm{\text{N}})$-$epoch$. Several physical constraints are imposed to maintain the un/stable fluid structure.

This paper investigates the determinants of foreign direct investment (FDI) flows to developing Asia using bilateral FDI flows for the period 1990 to 2005. We pay particular attention to possible differences in the determinants of FDI flows to developing Asian economies from the rest of the Asia-Pacific region compared to those from nonregional OECD economies, with an emphasis on the role of distance and time zone. We find that the elasticity of distance is much greater for FDI from the non–Asia-Pacific OECD economies than intraregional Asian flows. However, this difference disappears when one accounts for differences in time zones. The world is not flat; differences in time zones appear to act as a hindrance to FDI.

This paper examines the impact of improved trade facilitation measures and institutional capacity in a set of economies in transition Europe. Our results suggest that behind-the-border barriers play an important role in determining bilateral trade flows (controlling for the effects of tariffs, development levels, distance, and regional characteristics of exporters and importers, among other factors). For European Union (EU) members that joined the Union in 2004 and less developed and candidate members raising capacity in port efficiency and information technology infrastructures halfway to the EU-15 average, trade could expand by US$49 billion and US$62 billion respectively. In the context of the economic crisis and fragile recovery, as well as efforts to strengthen Europe integration, efforts to facilitate trade with investments to raise capacity in trade facilitation should be considered as part of policy steps going forward.

In this study, we investigate the potential effects of the Regional Comprehensive Economic Partnership (RCEP) agreement on Vietnam’s rice exports from 2000 to 2016. For this analysis, we employ the panel data augmented gravity model with some modifications. The estimated results suggest a positive relationship between Vietnam’s per capita export and the capita real gross domestic product (GDP) of the importer, Vietnam’s rice production, export price, and ASEAN dummy. We confirm that there is a negative relationship between Vietnam’s per capita rice export value and import country agricultural land and import tariffs. Additionally, this paper forecasts Vietnam’s rice export value per capita at each market in RCEP partners by using the autoregressive model. Our forecast results show that among RCEP members, Vietnam has potential markets if import tariff reductions are lowered in Singapore, Brunei, Korea, Japan, and Malaysia. To reap the benefits of rice exports’ potential, Vietnam must move from low-grade and cheap rice to high-quality rice production instead of expanding rice production and exports with the following implications: changing its present rice trading partners to potential markets and adopting market-oriented policies to meet the international demand and to increase the export elasticity of rice.

Due to the geographic location of Australia and New Zealand, air transport is the dominant mode of travel between the two nations and to and from the rest of the world. While the trans- Tasman air passenger market between the two countries has grown over the last 20 years, direct air routes to Australian destinations from New Zealand’s regional cities of Dunedin, Hamilton and Palmerston North have seen a major decline and, in most cases, the complete closure of those routes. This study uses the two-stage least squares (2SLS) gravity model to investigate the determinants of air passenger numbers on eight sampled city-pair routes. Empirical results show that for these trans-Tasman markets, expanded seat capacity has a strong positive impact on air passenger numbers. A longer driving time to travel to the nearest alternative international airport, the 2008/09 GFC and the winter season in New Zealand are also associated with an increase in air passenger numbers. In contrast, the presence of full-service network carriers has a negative impact on air passenger numbers.

This paper theoretically modifies the Anderson and Wincoop (2003) model on international trade to explain international tourism flows. In addition, this modified model can measure the effect of the Internet penetration at origin and destination countries through misinformation. The theoretical model implies that potential tourists use the Internet to gather information on their destination country through its websites. Through gravity model estimation, results show the significance of the Internet in the origin country as well as destination country.