Search results

The proposed Regional Comprehensive Economic Partnership (RCEP) will become a large trade agreement in Asia, which has brought together the ten members of Association of Southeast Asian Nations (ASEAN) and five of the neighbors’ countries. Under the trend of globalization, the progress of the transportation industry and regional integration will increase the volume of trade, therefore maritime performance is intrinsically linked to trade. In fact, few studies have examined regional integration in the context of seaborne. This paper aims to use the cluster analysis and Poisson quasi-maximum likelihood (PQML) gravity model to investigate the trading bloc phenomenon and relation between trade and marine transportation.

In this paper, hierarchical clustering analysis and tree diagrams are used to identify functional areas characterized by bilateral trade intensity and bilateral liner shipping connectivity indices. Regional reorganizations that have occurred within Asian countries were studied. This study illustrates that these trading blocs have a positive impact on trade when maritime transport, production and trading networks have developed between regions. A gravity model was constructed using worldwide trade data for 2007, 2010 and 2015. The study considered free trade agreement (FTA)/common market (CM) of EU, RCEP and North American Free Trade Agreement (NAFTA) as regional dummies and designed a real trade bloc induction variable. In addition, the study did not use the commonly adopted ordinary least squares (OLS) estimation but used the PQML method to estimate the gravity equation to overcome the problem of a large number of zero trade observations. Preliminary results show that regional integration cannot guarantee the establishment of intraregional trade but depends on the stage of economic development and regional industrial characteristics.

The major findings are summarized as follows. Both liner shipping connectivity and logistics performance have significant advantages with positive coefficients in each regression results. The creation of intraregional trade is not guaranteed, depending on the characteristics of the trade and the stage of economic development of the region. For RCEP, the effect created by intra-regional trade is better than the EU. Instead, the “nominal” intra-RCEP trade was significantly below the “real” trading blocs. For RCEP, the effect created by intra-regional trade is better than that of the EU. Instead, “nominal” intra-RCEP trade is much lower than “real” trading blocs. The real trading bloc between East Asia and Taiwan clearly exists, and the bloc phenomenon is becoming more and more significant. This result shows that Taiwan’s trade flow with East Asia is higher than the normal level relationship implied by its corresponding economic and geographical conditions.

This paper focuses on new empirical work done for this study is on the potential impact on trade. Earlier studies that have discussed and/or provided estimates of the benefits to the RCEP plan from improved transport and supply chain connectivity are cited. Marine transportation performance inherently links to economies of commerce. Few studies have examined regional integration in the context of maritime transportation, which reflects the lack of a mix of trade economists and maritime logistics research in the existing literature. This paper attempts to investigate the trading bloc phenomenon formed by regional integration (such as RCEP) and the relation between trade and marine transportation. With the official entry into force of the RCEP in 2020, it will promote increased trade and demand for logistics and maritime transport services in East Asia.

Building on network theory, this study aims to examine how network resources and network knowledge utilization influence mobility within networks of knowledge workers. Specifically, it examines how the availability of resources in a network and knowledge utilization, in a period impacts the structure of the focal network in the following period.

The study uses data from the National Basketball Association to depict the mobility of knowledge workers in a network. Because of the nature of the dependent variable, the study used a conditional fixed-effects quasi-maximum-likelihood Poisson regression as an analytical methodology.

The study finds that network resources are partially significant in predicting knowledge workers’ mobility and that knowledge utilization of networks of knowledge workers in one period negatively affects networks’ structure in the following period.

The study advances our understanding of the knowledge workers’ mobility phenomenon by examining network-level factors that influence the mobility of knowledge workers. It addresses the issue from a different theoretical perspective that is rarely used in studies of knowledge workers, which mostly draw from the traditional human resource literature. Additionally, it contributes to the emerging literature of network dynamics by studying factors that affect network changes. The study also responds to the calls that advocate using sports data to examine organizational phenomena.

At the heart of the African Growth and Opportunity Act (AGOA) are substantial trade preferences, which coupled with the Generalised System of Preferences (GSP) grant a wide range of goods produced in qualified African countries duty-free access to the USA. To be AGOA-eligible, countries are assessed annually on their progress in undertaking appropriate economic, institutional and human rights reforms. This paper seeks to cover new grounds by exploring whether exports of apparel to US crowds out EU-15's imports from Africa.

This paper employs the gravity model to gauge trade displacement effects from the EU to the US due to AGOA, and whether the more relaxed special waiver embodied in AGOA's apparel provision causes non-knitted exports to EU-15 to be crowded out. The basic gravity model, which posits that trade between two countries is positively influenced by the economic size and negatively affected by the distance between them, is augmented with other trade inhibiting and trade facilitating variables.

The gravity model provides no evidence of trade displacement but, instead, provides support for the hypothesis of complementarity of African exports to the two key markets. A strong positive impact of the bilateral trade between the US and Africa on the EU–African trade is evident mainly before the phasing out of the Agreement on Textiles and Clothing (ATC). This paper finds that Special Rule beneficiaries' exports to the two markets still complement each other, but for every percentage increase in exports to the USA, there is a less than proportionate increase in exports to EU-15 indicating a higher utilisation of the special waiver. This paper also provides evidence for complementary apparel exports to both LDCs (least developing countries) and non-LDCs, with stronger effects on non-LDCs and the non-knitted sector.

Future work could consider the longer lifespan of AGOA following its latest renewal in 2015. This would allow one to also capture the ongoing changes in EU trade arrangements in particular implementation of Economic Partnership Agreements (EPAs). This new agreement comes with more flexible rules of origin requiring single transformation step instead of the double step. As most African nations are still in the process of adopting EPAs, new research can shed more light on complementary or displacement effects once these agreements are adopted.

Since the main intent of AGOA is to enhance Africa's integration into the global economy by encouraging trade and investment, generate employment and increase productivity and per capita income growth, its impact on Special Rule beneficiaries' exports to the US has been extensively examined. However, the indirect effects of this trade agreement on African exports to other key markets providing similar preferences such as the EU has not been fully explored. This study also covers new grounds by examining whether there has been any apparel trade displacement from the EU to the US, as a result of the Act, over 2001–2016 period right from AGOA's inception.

The emergence of China in the international trading system has shifted its gravity center, as the country has become one of the mayor actors in international economic relations. Through the subscription of preferential agreements, China is building a network of strategic partnerships worldwide, including Latin America. The purpose of this paper is to answer the questions: Do free trade agreements (FTAs) between China and Latin American countries contribute to expand trade flows and enhance products diversification?

Three countries have an FTA with China, Chile (2005), Peru (2009) and Costa Rica (2010). Through an econometric estimation based on a gravity model, the authors expect to determine the impact of these agreements over both trade flows and products.

The study shows that FTAs have a positive impact on both bilateral trade flows and on the number of exchanged products. Nevertheless, this impact is positive but diminishes in time. The authors confirm that these agreements allowed for a substantive expansion of trade between Latin American economies and China, becoming relevant for policymakers regarding the bi-regional relation.

The study contributes to the understanding of the bilateral trade relations between China and Latin American countries, giving evidence of the magnitude of the impact of FTAs. Through new data, at a six-digit level of detail, this study improves current knowledge regarding bilateral economic relations.

This chapter proposes M-estimators of a fractional response model with an endogenous count variable under the presence of time-constant unobserved heterogeneity. To address the endogeneity of the right-hand-side count variable, I use instrumental variables and a two-step procedure estimation approach. Two methods of estimation are employed: quasi-maximum likelihood (QML) and nonlinear least squares (NLS). Using these methods, I estimate the average partial effects, which are shown to be comparable across linear and nonlinear models. Monte Carlo simulations verify that the QML and NLS estimators perform better than other standard estimators. For illustration, these estimators are used in a model of female labor supply with an endogenous number of children. The results show that the marginal reduction in women's working hours per week is less as women have one additional kid. In addition, the effect of the number of children on the fraction of hours that a woman spends working per week is statistically significant and more significant than the estimates in all other linear and nonlinear models considered in the chapter.

The variance targeting estimator (VTE) for generalized autoregressive conditionally heteroskedastic (GARCH) processes has been proposed as a computationally simpler and misspecification-robust alternative to the quasi-maximum likelihood estimator (QMLE). In this paper we investigate the asymptotic behavior of the VTE when the stationary distribution of the GARCH process has infinite fourth moment. Existing studies of historical asset returns indicate that this may be a case of empirical relevance. Under suitable technical conditions, we establish a stable limit theory for the VTE, with the rate of convergence determined by the tails of the stationary distribution. This rate is slower than that achieved by the QMLE. The limit distribution of the VTE is nondegenerate but singular. We investigate the use of subsampling techniques for inference, but find that finite sample performance is poor in empirically relevant scenarios.

Can transparency mitigate the trade-distortive effects of nontariff measures (NTMs)? This chapter explores the trade impact associated with promoting greater transparency in NTMs, using a new database of transparency provisions in over 100 Regional Trade Agreements (RTAs). The investigation surveys the incidence and scope of transparency provisions in RTAs, and econometrically assesses the trade effects of these instruments on bilateral agricultural and food trade. The findings demonstrate that transparency provisions in RTAs are associated with greater agricultural trade flows, suggesting that transparency should remain an important element of ongoing policy efforts to make NTMs less onerous for trade in agriculture.

The objective of this chapter is to introduce the reader to Spatial Health Econometrics (SHE). In both micro and macro health economics there are phenomena that are characterised by a strong spatial dimension, from hospitals engaging in local competitions in the delivery of health care services, to the regional concentration of health risk factors and needs. SHE allows health economists to incorporate these spatial effects using simple econometric models that take into account these spillover effects. This improves our understanding of issues such as hospital quality, efficiency and productivity and the sustainability of health expenditure of regional and national health care systems, to mention a few.

We discuss a class of copula-based ordered probit models with endogenous switching. Such models can be useful for the analysis of self-selection in subjective well-being equations in general, and job satisfaction in particular, where assignment of regressors may be endogenous rather than random, resulting from individual maximization of well-being. In an application to public and private sector job satisfaction, and using data on male workers from the German Socio-Economic Panel for 2004, and using two alternative copula functions for dependence, we find consistent evidence for endogenous sector selection.