scholarly journals Heterogeneous Effect of Ethnic Networks on International Trade of Thailand: The Role of Family Ties and Ethnic Diversity

2012 ◽  
Author(s):  
Jing-Lin Duanmu ◽  
Yilmaz Guney
REGION ◽  
2016 ◽  
Vol 3 (2) ◽  
pp. 125
Author(s):  
Laura Márquez-Ramos

We move beyond the nation-state as the unit of analysis and use subnational spatial variation to study the effect of the institutional environment on international trade. Additionally, we address the heterogeneous effect of trade agreements on different regions within a country. Employing a gravity model approach, we use a region-to-country dataset to estimate the determinants of Spanish regional exports and we apply quantile regressions for panel data. We find that better institutional quality of trade agreements leads to an increase in both the intensive and the extensive margins of trade. The institutional quality of trade agreements exerts a differential effect on regional exports at different locations within a country, although differences across Spanish regions seem to be larger for the intensive margin than for the extensive margin. We do, however, find a common trend: for the relatively more important exporting regions, the institutional quality of TAs is less relevant for trade margins. Therefore, our results posit that subnational spatial variation should be added to the analysis of the determinants of international trade flows.


2019 ◽  
Author(s):  
Horag Choi ◽  
Julio Mancuso Tradenta ◽  
Christis G. Tombazos
Keyword(s):  

Sociology ◽  
2016 ◽  
Vol 51 (5) ◽  
pp. 1011-1033 ◽  
Author(s):  
James Laurence

Extensive research has demonstrated that neighbourhood ethnic diversity is negatively associated with intra-neighbourhood social capital. This study explores the role of segregation and integration in this relationship. To do so it applies three-level hierarchical linear models to two sets of data from across Great Britain and within London, and examines how segregation across the wider-community in which a neighbourhood is nested impacts trust amongst neighbours. This study replicates the increasingly ubiquitous finding that neighbourhood diversity is negatively associated with neighbour-trust. However, we demonstrate that this relationship is highly dependent on the level of segregation across the wider-community in which a neighbourhood is nested. Increasing neighbourhood diversity only negatively impacts neighbour-trust when nested in more segregated wider-communities. Individuals living in diverse neighbourhoods nested within integrated wider-communities experience no trust-penalty. These findings show that segregation plays a critical role in the neighbourhood diversity/trust relationship, and that its absence from the literature biases our understanding of how ethnic diversity affects social cohesion.


2021 ◽  
pp. 1-14
Author(s):  
Hamed Zargari ◽  
Morteza Zahedi ◽  
Marziea Rahimi

Words are one of the most essential elements of expressing sentiments in context although they are not the only ones. Also, syntactic relationships between words, morphology, punctuation, and linguistic phenomena are influential. Merely considering the concept of words as isolated phenomena causes a lot of mistakes in sentiment analysis systems. So far, a large amount of research has been conducted on generating sentiment dictionaries containing only sentiment words. A number of these dictionaries have addressed the role of combinations of sentiment words, negators, and intensifiers, while almost none of them considered the heterogeneous effect of the occurrence of multiple linguistic phenomena in sentiment compounds. Regarding the weaknesses of the existing sentiment dictionaries, in addressing the heterogeneous effect of the occurrence of multiple intensifiers, this research presents a sentiment dictionary based on the analysis of sentiment compounds including sentiment words, negators, and intensifiers by considering the multiple intensifiers relative to the sentiment word and assigning a location-based coefficient to the intensifier, which increases the covered sentiment phrase in the dictionary, and enhanced efficiency of proposed dictionary-based sentiment analysis methods up to 7% compared to the latest methods.


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