Migrants’ socio-economic integration is a major theme in migration research, which can provide economic and cultural benefits. And it will contribute to social stability. The investigation from the spatial perspective should also be considered. This paper aims to examine the spatial differentiation of the socio-economic integration of migrants and identify its driving forces to provide crucial evidence and policy recommendations to urban policymakers and further improve migrants’ socio-economic integration. Based on the latest China Migrants Dynamic Survey, this paper uses global Moran’s I index, hot spot analysis and GWR model to explore spatial differentiation and driving forces of the socio-economic integration of 155,789 migrants in 291 cities at prefecture level and above in China. The results show that: (1) The socio-economic integration of migrants consists of five dimensions, which are economic integration, cultural integration, social security, social relation and psychological integration. Among them, psychological integration is the highest (73.16) and economic integration is the lowest (13.38). (2) The socio-economic integration of migrants is mainly influenced by their own characteristics instead of the destination characteristics. Four factors (age, education, length of stay and population growth rate) positively affect migrants’ socio-economic integration, while three factors (inter-provincial mobility, proportion of tertiary industry in GDP, and ratio of teacher to student in middle school) negatively impact the socio-economic integration of migrants. (3) The socio-economic integration of migrants shows the distribution pattern of agglomeration. And the integration also presents a significant spatial heterogeneity. The driving forces of the socio-economic integration exhibit various zonal spatial differentiation patterns, including “E–W”, “SE–NW”, “NE–SW”, and “S–N”. Finally, some useful recommendations are given for improving migrants’ socio-economic integration.
Theory and Decision - We introduce a family of proportional surplus division values for TU-games. Each value first assigns to each player a compromise between her stand-alone worth and the average... 相似文献
In this article, we study global L2 error of non linear wavelet estimator of density in the Besov space Bspq for missing data model when covariables are present and prove that the estimator can achieve the optimal rate of convergence, which is similar to the result studied by Donoho et al. (1996)Donoho, D.L., Johnstone, I.M., Kerkyacharian, G., Picard, D. (1996). Density estimation by wavelet thresholding. Ann. Stat. 24:508–539.[Crossref], [Web of Science ®], [Google Scholar] in complete independent data case with term-by-term thresholding of the empirical wavelet coefficients. Finite-sample behavior of the proposed estimator is explored via simulations. 相似文献
This paper proposes the use of the Bernstein–Dirichlet process prior for a new nonparametric approach to estimating the link function in the single-index model (SIM). The Bernstein–Dirichlet process prior has so far mainly been used for nonparametric density estimation. Here we modify this approach to allow for an approximation of the unknown link function. Instead of the usual Gaussian distribution, the error term is assumed to be asymmetric Laplace distributed which increases the flexibility and robustness of the SIM. To automatically identify truly active predictors, spike-and-slab priors are used for Bayesian variable selection. Posterior computations are performed via a Metropolis-Hastings-within-Gibbs sampler using a truncation-based algorithm for stick-breaking priors. We compare the efficiency of the proposed approach with well-established techniques in an extensive simulation study and illustrate its practical performance by an application to nonparametric modelling of the power consumption in a sewage treatment plant. 相似文献
ABSTRACTCorrelated bilateral data arise from stratified studies involving paired body organs in a subject. When it is desirable to conduct inference on the scale of risk difference, one needs first to assess the assumption of homogeneity in risk differences across strata. For testing homogeneity of risk differences, we herein propose eight methods derived respectively from weighted-least-squares (WLS), the Mantel-Haenszel (MH) estimator, the WLS method in combination with inverse hyperbolic tangent transformation, and the test statistics based on their log-transformation, the modified Score test statistic and Likelihood ratio test statistic. Simulation results showed that four of the tests perform well in general, with the tests based on the WLS method and inverse hyperbolic tangent transformation always performing satisfactorily even under small sample size designs. The methods are illustrated with a dataset. 相似文献