International migration and the NGOs working in the field of migration in Turkey

This study aims to analyse the activities and discourses of the non-governmental organizations (NGOs) working in the field of migration in Turkey. The research explores how the NGOs frame the issue of migration differently and how they define and comprehend migration, migrants, and refugees. The article discusses whether the NGOs view refugees as subjects needing help, support, and protection or as actors who have rights and must be empowered and argues that there is tension between the two approaches. These points are discussed through a field study, conducted in 2020 (between February and April), comprising in-depth interviews with representatives of 13 NGOs working in the field of migration. The study points to structural, historical, and conjectural causes and aspects of the weakness of rights-based attitudes and activities among the NGOs working in the field of migration in Turkey. The article finds out that the actions of the NGOs working in the field of migration are concentrated on the basic needs of refugees, and structural limitations, such as political pressure, political polarization, and capacity problems, push the NGOs to evaluate the issue of migration within relatively narrow frames. The article also stresses the importance of an enabling political and legal environment and a coherent and structured communication strategy to promote a rights-based migration agenda.     

Dummy variables vs. category-wise models

Empirical research frequently involves regression analysis with binary categorical variables, which are traditionally handled through dummy explanatory variables. This paper argues that separate category-wise models may provide a more logical and comprehensive tool for analysing data with binary categories. Exploring different aspects of both methods, we contrast the two with a Monte Carlo simulation and an empirical example to provide a practical insight.     

A Horvitz-Thompson Estimator of the Population Mean Using Inclusion Probabilities of Ranked Set Sampling

In this study, we define the Horvitz-Thompson estimator of the population mean using the inclusion probabilities of a ranked set sample in a finite population setting. The second-order inclusion probabilities that are required to calculate the variance of the Horvitz-Thompson estimator were obtained. The Horvitz-Thompson estimator, using the inclusion probabilities of ranked set sample, tends to be more efficient than the classical ranked set sampling estimator especially in a positively skewed population with small sizes. Also, we present a real data example with the volatility of gasoline to illustrate the Horvitz-Thompson estimator based on ranked set sampling.     

Leverages and Influential Observations in a Regression Model with Autocorrelated Errors

This article deals with the general form of the hat matrix and the DFBETA measure to detect the influential observations and the leverages in the linear regression model with more than one regressor when the errors are from AR(1) and AR(2) processes. Previous studies dealing with the influential observations and the leverages in the constant mean model and regression through the origin model are obtained as special cases. To demonstrate the utility of the hat matrix and the DFBETA measure, two numerical examples based on the ice cream consumption data with AR(1) errors and the Fox-Hartnagel data with AR(2) errors are analyzed. The results show that the parameter of the autoregressive process affects the influential and leverage points.     

Goodness of fit tests for Nakagami distribution based on smooth tests

ABSTRACT

Nakagami distribution is one of the most common distributions used to model positive valued and right skewed data. In this study, we interest goodness of fit problem for Nakagami distribution. Thus, we propose smooth tests for Nakagami distribution based on orthonormal functions. We also compare these tests with some classical goodness of fit tests such as Cramer–von Mises, Anderson–Darling, and Kolmogorov–Smirnov tests in respect to type-I error rates and powers of tests. Simulation study indicates that smooth tests give better results than these classical tests give in respect to almost all cases considered.     

A framework for comparing social protection in developing and developed countries: The example of child benefits

Abstract   The article outlines a conceptual and theoretical framework for improved comparative analysis of publicly provided social protection in developing countries, drawing on the research tradition of the study of longstanding welfare democracies. An important element of the proposed institutional approach is the establishment of comparable qualitative and quantitative indicators for social protection. The empirical example of child benefits indicates that differences between developed and developing countries should not be exaggerated, and that the prevalence of child benefits in sub-Saharan African and Latin American countries today resembles the inter-war period (1919-1938) situation in developed regions.     

Social policy and health: transition countries in a comparative perspective

T. Ferrarini, O. Sjöberg. Social policy and health: transition countries in a comparative perspective Int J Soc Welfare 2010: ??: ??–??© 2010 The Author(s), Journal compilation © 2010 Blackwell Publishing Ltd and International Journal of Social Welfare. This article analyses the development and design of unemployment insurance and family policy benefits and their links to health outcomes in Estonia, Poland, the Slovak Republic, Slovenia, the Czech Republic and Hungary from the mid‐1990s. Comparing these six transition countries with long‐standing welfare democracies reveals important similarities and differences in policy and health. Unemployment benefit schemes resemble corporatist schemes in important respects, however, with lower coverage and average benefits. Subjective wellbeing is also comparatively low among both employed and unemployed in the transition countries. Several transition countries have mixed family policy strategies that simultaneously support dual‐earner families and traditional gender roles. One clear exception is Slovenia, which has a highly developed dual‐earner support. Family policy generosity is related to lower rates of poverty, infant mortality and child injuries. The article demonstrates the fruitfulness of institutional analyses of the link between social policy and population health in a broader welfare state context.     

Concurrent processing of heteroskedastic vector-valued mixture density models

We introduce a combined two-stage least-squares (2SLS)–expectation maximization (EM) algorithm for estimating vector-valued autoregressive conditional heteroskedasticity models with standardized errors generated by Gaussian mixtures. The procedure incorporates the identification of the parametric settings as well as the estimation of the model parameters. Our approach does not require a priori knowledge of the Gaussian densities. The parametric settings of the 2SLS_EM algorithm are determined by the genetic hybrid algorithm (GHA). We test the GHA-driven 2SLS_EM algorithm on some simulated cases and on international asset pricing data. The statistical properties of the estimated models and the derived mixture densities indicate good performance of the algorithm. We conduct tests on a massively parallel processor supercomputer to cope with situations involving numerous mixtures. We show that the algorithm is scalable.     

A General Statistical Framework for Multistage Designs

Abstract. The efficiency of observational studies may be increased by applying multistage sampling designs. It is, however, not always transparent how to construct such a design to obtain increased efficiency. We here present a general statistical framework for describing and constructing multistage designs. We also provide tools for efficiency and cost‐efficiency comparisons, to facilitate the choice of sampling scheme. The comparisons are based on Fisher information matrices and the results are presented in graphs, where either efficiency or cost‐adjusted efficiency is plotted against a normalized measure of cost. The former curve resides in the unit square and is analogous to the receiver operating characteristic curve used for testing.