GMM inference in spatial autoregressive models

In this study, we investigate the finite sample properties of the optimal generalized method of moments estimator (OGMME) for a spatial econometric model with a first-order spatial autoregressive process in the dependent variable and the disturbance term (for short SARAR(1, 1)). We show that the estimated asymptotic standard errors for spatial autoregressive parameters can be substantially smaller than their empirical counterparts. Hence, we extend the finite sample variance correction methodology of Windmeijer (2005 Windmeijer, F. (2005). A finite sample correction for the variance of linear efficient two-step GMM estimators. Journal of Econometrics 126(1):25–51.[Crossref], [Web of Science ®] , [Google Scholar]) to the OGMME for the SARAR(1, 1) model. Results from simulation studies indicate that the correction method improves the variance estimates in small samples and leads to more accurate inference for the spatial autoregressive parameters. For the same model, we compare the finite sample properties of various test statistics for linear restrictions on autoregressive parameters. These tests include the standard asymptotic Wald test based on various GMMEs, a bootstrapped version of the Wald test, two versions of the C(α) test, the standard Lagrange multiplier (LM) test, the minimum chi-square test (MC), and two versions of the generalized method of moments (GMM) criterion test. Finally, we study the finite sample properties of effects estimators that show how changes in explanatory variables impact the dependent variable.     

Matrix mean squared error comparisons of some biased estimators with two biasing parameters

To deal with multicollinearity problem, the biased estimators with two biasing parameters have recently attracted much research interest. The aim of this article is to compare one of the last proposals given by Yang and Chang (2010 Yang, H., and X. Chang. 2010. A new two-parameter estimator in linear regression. Communications in Statistics: Theory and Methods 39 (6):923–34.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) with Liu-type estimator (Liu 2003 Liu, K. 2003. Using Liu-type estimator to combat collinearity. Communications in Statistics: Theory and Methods 32 (5):1009–20.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) and k ? d class estimator (Sakallioglu and Kaciranlar 2008 Sakallioglu, S., and S. Kaciranlar. 2008. A new biased estimator based on ridge estimation. Statistical Papers 49:669–89.[Crossref], [Web of Science ®] , [Google Scholar]) under the matrix mean squared error criterion. As well as giving these comparisons theoretically, we support the results with the extended simulation studies and real data example, which show the advantages of the proposal given by Yang and Chang (2010 Yang, H., and X. Chang. 2010. A new two-parameter estimator in linear regression. Communications in Statistics: Theory and Methods 39 (6):923–34.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) over the other proposals with increasing multicollinearity level.     

A comparison of different procedures for principal component analysis in the presence of outliers

Principal component analysis (PCA) is a popular technique that is useful for dimensionality reduction but it is affected by the presence of outliers. The outlier sensitivity of classical PCA (CPCA) has caused the development of new approaches. Effects of using estimates obtained by expectation–maximization – EM and multiple imputation – MI instead of outliers were examined on the artificial and a real data set. Furthermore, robust PCA based on minimum covariance determinant (MCD), PCA based on estimates obtained by EM instead of outliers and PCA based on estimates obtained by MI instead of outliers were compared with the results of CPCA. In this study, we tried to show the effects of using estimates obtained by MI and EM instead of outliers, depending on the ratio of outliers in data set. Finally, when the ratio of outliers exceeds 20%, we suggest the use of estimates obtained by MI and EM instead of outliers as an alternative approach.     

Profust reliability of linear and circular type F and G systems having two failure criteria under Markov dependency

In this study, the profust reliabilities of (n, f, k): F(G) and < n, f, k > : F(G) systems for Markov dependent components are investigated. Having two failure criteria are the common features of these four systems. The usage of both fuzzy approach and two failure criteria in the same system provides us more realistic approach to evaluate the reliability of more complex systems. The component configurations are examined for both linear and circular sequences and the working principle of systems are studied for both F and G systems. Under all these assumptions, the profust reliabilities of (n, f, k): F(G) and < n, f, k > : F(G) systems are obtained using the distribution of run statistics. Also a new membership function different from the linear membership function which is generally used in the literature is proposed. Some numerical results which allow the comparison of the systems from various perspectives and various figures for both linear and circular type systems are presented. Some special cases (between Markov – iid assumption, conventional – profust reliability) are also considered.     

Political participation beyond borders: a comparative analysis of Turkish youth living in home country,Germany and Belgium

Drawing on data from a large-scale international study [PIDOP – Processes Influencing Democratic Ownership and Participation. 2009–2012. Accessed August 10. http://www.fahs.surrey.ac.uk/pidop/index.htm], the present research examined psychological and demographic factors related to civic and political participation among adolescents and young adults (from 16 to 26 years of age) with a Turkish origin and residing in Belgium (n?=?153), Germany (n?=?204) and Turkey (n?=?253). MANCOVA and one-way ANOVA were employed to address how types of civic, direct and online participation differ by socio-demographic variables. The results indicate that citizenship status was not related with the types of participation, while age, gender and country were significantly related with the type of participation in various degrees. Interaction between all the variables showed that older (20–26), foreign national, male Turkish German sample is significantly more involved in civic participation activities. Results are discussed in light of the naturalization processes of migrant groups abroad and extensive religious involvement of Turkish German sample.     

Concurrent generation of binary and nonnormal continuous data through fifth-order power polynomials

Data collection process in most observational and experimental studies yield different types of variables, leading to the use of joint models that are capable of handling multiple data types. Evaluation of various statistical techniques that have been developed for mixed data in simulated environments requires concurrent generation of multiple variables. In this article, I present an important augmentation to a unified framework proposed in our previously published work for simultaneously generating binary and nonnormal continuous data given the marginal characteristics and correlation structure, via fifth-order power polynomials that are known to extend the area covered in the skewness-elongation plane and to provide a better approximation to the probability density function of the continuous variables. I evaluate how well the improved methodology performs in comparison to the original one, in a simulated setting with illustrations of algorithmic steps. Although the relative gains for the associational quantities are not substantial, the augmented version appears to better capture the marginal quantities that are pertinent to the higher-order moments, as indicated by very close resemblance between the specified and empirically computed quantities on average.     

PoisNor: An R package for generation of multivariate data with Poisson and normal marginals

In this article, the operational details of the R package PoisNor that is designed for simulating multivariate data with count and continuous variables with a prespecified correlation matrix are described, and examples of some important functions are given. The data-generation mechanism is a combination of the “NORmal To Anything” principle and a recently established connection between Poisson and normal correlations. The package provides a unique and useful tool that has been lacking for generating multivariate mixed data with Poisson and normal components.     

An Overview of a Hospital-Based Child Advocacy Center’s Experience from Turkey

The purpose of the present study was to investigate sociodemographic variables, features of sexual abuse (SA), and first psychiatric evaluation results of abused children, and to analyze the relation of the psychiatric evaluation results to the children’s age and gender, type and duration of abuse, abuser–child relationship, and marital status of the children’s parents, at one of the most experienced Child Advocacy Centers (CACs) in Turkey. All data were obtained from reports prepared by child and adolescent psychiatrists. The sample of this study consists of 436 child sexual abuse (CSA) cases who admitted ?zmir CAC between April 2014 and November 2015. The statistical analyses yielded significant relations between psychiatric symptoms and chronic abuse, the gender of the children, and type of abuse. Suicidal ideation and behaviors due to sexual abuse (SA) were also examined. According to our results, it is fair to say that children exposed to SA benefit from immediate psychiatric help because of their vulnerability for psychiatric disorders due to abuse. In this context, CACs are very important multidisciplinary establishments to determine children’s multiple needs to ease their trauma with collaborative teamwork. Psychiatric evaluation should be part of this multidisciplinary context.     

Socio-Economic Disparities in the Development of the Romania’s Border Areas

The Romanian border areas include 898 Local Administrative Units 2 (LAU2), of which 88 are urban and 810 rural. Romania has borderline with the following countries: Bulgaria, Republic of Moldova, Serbia, Ukraine, Hungary, of which 63.5 % is Non-European Union boundary. According to the population structure, 51.6 % of the total population is urban and the rest of 48.4 % is rural. In order to assess the socio-economic territorial disparities in the development of the urban space of Romanian border areas, several research stages were carried out: selecting 22 relevant statistical indicators, analyzing territorial disparities, standardizing the absolute values of the indicators, grouping the elementary indicators by 7 multiple indicator clusters (secondary indexes) in order to reflect the main socio-economic development aspects: (1) housing, (2) public utilities infrastructure and green areas, (3) health, (4) labour market, (5) demography, (6) education and (7) local economy. Finally, the authors were able to compute secondary indexes and the Index of Socio-Economic Development as Hull Score with a mean of 50 and a standard deviation of 14, revealing the levels of socio-economic development (high, average and low). Generally, the outcomes of the current study are in line with Romania’s complex socio-economic disparities, rooted in the historic background of the country. Spatially, the economic development follows a West–East direction, the less developed areas being concentrated in the Eastern and Southern part of the country.