Central quantile subspace

Quantile regression (QR) is becoming increasingly popular due to its relevance in many scientific investigations. There is a great amount of work about linear and nonlinear QR models. Specifically, nonparametric estimation of the conditional quantiles received particular attention, due to its model flexibility. However, nonparametric QR techniques are limited in the number of covariates. Dimension reduction offers a solution to this problem by considering low-dimensional smoothing without specifying any parametric or nonparametric regression relation. The existing dimension reduction techniques focus on the entire conditional distribution. We, on the other hand, turn our attention to dimension reduction techniques for conditional quantiles and introduce a new method for reducing the dimension of the predictor $$\mathbf {X}$$. The novelty of this paper is threefold. We start by considering a single index quantile regression model, which assumes that the conditional quantile depends on $$\mathbf {X}$$ through a single linear combination of the predictors, then extend to a multi-index quantile regression model, and finally, generalize the proposed methodology to any statistical functional of the conditional distribution. The performance of the methodology is demonstrated through simulation examples and real data applications. Our results suggest that this method has a good finite sample performance and often outperforms the existing methods.     

Drivers of Change in the Democratic Republic of Congo: The Role of China in Re-Shaping the Country

Africa has always been potentially one of the richest continents in the world, but, due to a series of causes (colonization and decolonization process, wars, dictatorships etc.) it has never reached its full potential. The fight against poverty has been carried out by different institutions at the multilateral and bilateral level during the last 30 years, but the route toward economic development seems to be still long for African countries. This paper will focus on the analysis of the new approach to international cooperation introduced by the People’s Republic of China in order to exchange rights of exploitation of Africa’s mining and natural resources with large amounts of capital without any conditionality. The case-study which will be considered is the agreement concluded between the People’s Republic of China and the Democratic Republic of Congo.     

Analysis of bivariate dichotomous data from a stratified two-stage cluster sample

In the health and social sciences, researchers often encounter categorical data for which complexities come from a nested hierarchy and/or cross-classification for the sampling structure. A common feature of these studies is a non-standard data structure with repeated measurements which may have some degree of clustering. In this paper, methodology is presented for the joint estimation of quantities of interest in the context of a stratified two-stage sample with bivariate dichotomous data. These quantities are the mean value π of an observed dichotomous response for a certain condition or time-point and a set of correlation coefficients for intra-cluster association for each condition or time period and for inter-condition correlation within and among clusters. The methodology uses the cluster means and pairwise joint probability parameters from each cluster. They together provide appropriate information across clusters for the estimation of the correlation coefficients.     

An exploratory study of self-esteem and quality of care of 100 children in foster care

This small-scale research study examined children's perceptions of themselves, their situation, career aspirations and hopes for the future. One hundred San Francisco children in foster care were interviewed and filled out a questionnaire. 50 of the children lived in foster family care; 50 in group homes. The Department of Social Services in San Francisco cooperated in executing this study. Children ranged in ages from 8–18. Both male and female children participated. The questionnaire contained two standarized tests, Coopersmith Self-Esteem Inventory and Parks Career Role Inventory. A section was written by the authors to examine how children in care spend their time, and how they feel about where they live and their foster care status. The last part, an open-ended section asks them which foster care setting they liked best, why, and what they would suggest to improve the foster care system. An additional question “Why do you think you are in foster care?” was designed to elicit the children's understanding of why they lived in foster care rather than their biological home.     

Understanding the Relationship Between Direct Experience and Risk Perception of Natural Hazards

Risk perception has been largely examined in studies that have aimed to explain and predict preparedness behavior in the context of natural hazards. Findings from studies on the relationship between previous experience, preparedness, and risk perception in disaster situations have been inconsistent. Hence, the main goal of this work was to explore the influence of physical and emotional experience on risk perception regarding natural hazards. This study was conducted in a statistically representative sample of the city of Iquique, in northern Chile (n = 701), who completed a survey one month after the occurrence of an earthquake and tsunami (8.2 Mw). The survey assessed the experience and preparation actions of survivors in relation to this event. Using a structural equation model, we examined nine proposed relationships, six of which were significant. The final model had an adequate fit (χ² = 752.23, df = 283, comparative fit index [CFI] = 0.90, root mean square error of approximation [RMSEA] = 0.049). Direct experience showed the greatest influence on risk perception: while direct physical experience (i.e., the physical and material consequences associated with the earthquake) maintained a direct positive effect on risk perception, direct emotional experience (i.e., the fear of experiencing an earthquake) produced an indirect positive effect (through worry). Emotional experience, however, did not directly influence current preparedness and risk perception. Implications for understanding the relationship between risk perception and direct experience are discussed.     

Use of visitors’ perception in urban reserves in the Buenos Aires metropolis

Urban nature reserves (UR’s) fulfill unique functions for society and are irreplaceable, satisfying human needs particularly in urban and periurban areas. The aim of this paper was to use a perception based approach to analyze whether the urban nature reserves in the metropolitan area of Buenos Aires, Argentina were principally used by visitors according to their main conservation mission. Five hundred written surveys designed to evaluate users’ profile and their perceptions of the selected reserves were conducted during the summer of 2009 to visitors selected at random. Collected data was analyzed by multivariate analyses. The results discriminated two groups (1 and 2) of reserves showing that people chose to visit a nature reserve for two contrasting motivations: the contemplation of nature (group 1) or active recreation (group 2). Both groups of reserves, the respondents participated in environmental programs. All respondents knew about plants whereas knowledge of the fauna was related to the visitors’ level of education. In all reserves respondents considered that nature enhance the quality of human life in the first place, and valued biodiversity en second place. Visitors in group 1 considered nature as very important, while respondents in group 2 thought that is important as a place for having fun. Our findings can potentially assist administrators to understand better how visitors perceive the reserves.     

Estimation of value-at-risk using single index quantile regression

ABSTRACT

Value-at-Risk (VaR) is one of the best known and most heavily used measures of financial risk. In this paper, we introduce a non-iterative semiparametric model for VaR estimation called the single index quantile regression time series (SIQRTS) model. To test its performance, we give an application to four major US market indices: the S&P 500 Index, the Russell 2000 Index, the Dow Jones Industrial Average, and the NASDAQ Composite Index. Our results suggest that this method has a good finite sample performance and often outperforms a number of commonly used methods.     

Variable selection in heteroscedastic single-index quantile regression

We propose a new algorithm for simultaneous variable selection and parameter estimation for the single-index quantile regression (SIQR) model . The proposed algorithm, which is non iterative , consists of two steps. Step 1 performs an initial variable selection method. Step 2 uses the results of Step 1 to obtain better estimation of the conditional quantiles and , using them, to perform simultaneous variable selection and estimation of the parametric component of the SIQR model. It is shown that the initial variable selection method consistently estimates the relevant variables , and the estimated parametric component derived in Step 2 satisfies the oracle property.     

The effect of working from home on major time allocations with a focus on food-related activities

Review of Economics of the Household - Telecommuting has been on the rise in the U.S. and working from home may affect how workers allocate their time over the course of a day. In this paper, using...