259 research outputs found
Remittances and the Brain Drain Revisited: The Microdata Show That More Educated Migrants Remit More
Two of the most salient trends surrounding the issue of migration and development over the last two decades are the large rise in remittances, and an increased flow of skilled migration. However, recent literature based on cross-country regressions has claimed that more educated migrants remit less, leading to concerns that further increases in skilled migration will hamper remittance growth. We revisit the relationship between education and remitting behavior using microdata from surveys of immigrants in eleven major destination countries. The data show a mixed pattern between education and the likelihood of remitting, and a strong positive relationship between education and the amount remitted conditional on remitting. Combining these intensive and extensive margins gives an overall positive effect of education on the amount remitted. The microdata then allow investigation as to why the more educated remit more. We find the higher income earned by migrants, rather than characteristics of their family situations explains much of the higher remittances.remittances, migration, brain drain, education
Remittances and the Brain Drain Revisited: The microdata show that more educated migrants remit more
Two of the most salient trends surrounding the issue of migration and development over the last two decades are the large rise in remittances, and an increased flow of skilled migration. However, recent literature based on cross-country regressions has claimed that more educated migrants remit less, leading to concerns that further increases in skilled migration will hamper remittance growth. We revisit the relationship between education and remitting behavior using microdata from surveys of immigrants in eleven major destination countries. The data show a mixed pattern between education and the likelihood of remitting, and a strong positive relationship between education and the amount remitted conditional on remitting. Combining these intensive and extensive margins gives an overall positive effect of education on the amount remitted. The microdata then allow investigation as to why the more educated remit more. We find the higher income earned by migrants, rather than characteristics of their family situations explains much of the higher remittances.Remittances, Migration, Brain Drain, Education
Remittances and the brain drain revisited : the microdata show that more educated migrants remit more
Two of the most salient trends surrounding the issue of migration and development over the past two decades are the large rise in remittances, and an increased flow of skilled migration. However, recent literature based on cross-country regressions has claimed that more educated migrants remit less, leading to concerns that further increases in skilled migration will hamper remittance growth. This paper revisits the relationship between education and remitting behavior using microdata from surveys of immigrants in 11 major destination countries. The data show a mixed pattern between education and the likelihood of remitting, and a strong positive relationship between education and the amount remitted conditional on remitting. Combining these intensive and extensive margins gives an overall positive effect of education on the amount remitted. The microdata then allow investigation as to why the more educated remit more. The analysis finds that the higher income earned by migrants, rather than characteristics of their family situations, explains much of the higher remittances.Population Policies,Remittances,Debt Markets,International Migration,Access&Equity in Basic Education
Remittances and the Brain Drain Revisited: The Microdata Show That More Educated Migrants Remit More
Two of the most salient trends surrounding the issue of migration and development over the last two decades are the large rise in remittances, and an increased flow of skilled migration. However, recent literature based on cross-country regressions has claimed that more educated migrants remit less, leading to concerns that further increases in skilled migration will hamper remittance growth. We revisit the relationship between education and remitting behavior using microdata from surveys of immigrants in eleven major destination countries. The data show a mixed pattern between education and the likelihood of remitting, and a strong positive relationship between education and the amount remitted conditional on remitting. Combining these intensive and extensive margins gives an overall positive effect of education on the amount remitted. The microdata then allow investigation as to why the more educated remit more. We find the higher income earned by migrants, rather than characteristics of their family situations explains much of the higher remittances.Remittances, Migration, Brain Drain, Education
A stochastic model for the evolution of the Web
Recently several authors have proposed stochastic models of the growth of the Web graph that give rise to power-law distributions. These models are based on the notion of preferential attachment leading to the "rich get richer" phenomenon. However, these models fail to explain several distributions arising from empirical results, due to the fact that the predicted exponent is not consistent with the data. To address this problem, we extend the evolutionary model of the Web graph by including a non-preferential component, and we view the stochastic process in terms of an urn transfer model. By making this extension, we can now explain a wider variety of empirically discovered power-law distributions provided the exponent is greater than two. These include: the distribution of incoming links, the distribution of outgoing links, the distribution of pages in a Web site and the distribution of visitors to a Web site. A by-product of our results is a formal proof of the convergence of the standard stochastic model (first proposed by Simon)
Growing Scale-Free Networks with Tunable Clustering
We extend the standard scale-free network model to include a ``triad
formation step''. We analyze the geometric properties of networks generated by
this algorithm both analytically and by numerical calculations, and find that
our model possesses the same characteristics as the standard scale-free
networks like the power-law degree distribution and the small average geodesic
length, but with the high-clustering at the same time. In our model, the
clustering coefficient is also shown to be tunable simply by changing a control
parameter - the average number of triad formation trials per time step.Comment: Accepted for publication in Phys. Rev.
Scale-free networks without growth
In this letter, we proposed an ungrowing scale-free network model, wherein
the total number of nodes is fixed and the evolution of network structure is
driven by a rewiring process only. In spite of the idiographic form of , by
using a two-order master equation, we obtain the analytic solution of degree
distribution in stable state of the network evolution under the condition that
the selection probability in rewiring process only depends on nodes'
degrees. A particular kind of the present networks with linearly correlated
with degree is studied in detail. The analysis and simulations show that the
degree distributions of these networks can varying from the Possion form to the
power-law form with the decrease of a free parameter , indicating the
growth may not be a necessary condition of the self-organizaton of a network in
a scale-free structure.Comment: 4 pages and 3 figure
Hierarchical characterization of complex networks
While the majority of approaches to the characterization of complex networks
has relied on measurements considering only the immediate neighborhood of each
network node, valuable information about the network topological properties can
be obtained by considering further neighborhoods. The current work discusses on
how the concepts of hierarchical node degree and hierarchical clustering
coefficient (introduced in cond-mat/0408076), complemented by new hierarchical
measurements, can be used in order to obtain a powerful set of topological
features of complex networks. The interpretation of such measurements is
discussed, including an analytical study of the hierarchical node degree for
random networks, and the potential of the suggested measurements for the
characterization of complex networks is illustrated with respect to simulations
of random, scale-free and regular network models as well as real data
(airports, proteins and word associations). The enhanced characterization of
the connectivity provided by the set of hierarchical measurements also allows
the use of agglomerative clustering methods in order to obtain taxonomies of
relationships between nodes in a network, a possibility which is also
illustrated in the current article.Comment: 19 pages, 23 figure
Community structure and ethnic preferences in school friendship networks
Recently developed concepts and techniques of analyzing complex systems
provide new insight into the structure of social networks. Uncovering recurrent
preferences and organizational principles in such networks is a key issue to
characterize them. We investigate school friendship networks from the Add
Health database. Applying threshold analysis, we find that the friendship
networks do not form a single connected component through mutual strong
nominations within a school, while under weaker conditions such
interconnectedness is present. We extract the networks of overlapping
communities at the schools (c-networks) and find that they are scale free and
disassortative in contrast to the direct friendship networks, which have an
exponential degree distribution and are assortative. Based on the network
analysis we study the ethnic preferences in friendship selection. The clique
percolation method we use reveals that when in minority, the students tend to
build more densely interconnected groups of friends. We also find an asymmetry
in the behavior of black minorities in a white majority as compared to that of
white minorities in a black majority.Comment: submitted to Physica
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