ON THE HILDRETH-HOUCK ESTIMATOR FOR RANDOM COEFFICIENT REGRESSION MODELS

This paper is concerned with the linear regression model in which the coefficients are random variables. The Hildreth-Houck method is considered for estimating the model. Sufficient conditions for the consistency of the Hildreth-Houck estimator are discussed and its asymptotic normality is established.     

ESTIMATION OF SPATIAL ARMA MODELS

Spatial ARMA models are considered using the nonsymmetric half plane ordering on a lattice of data. A method is given for the estimation of the orders and the coefficients of such models under an identifiability condition and the condition that the beat linear predictor is the best predictor in the mean square sense. Under these conditions, the strong consistency of the estimators ia established. The usual methods for ARMA modelling in Time Series Analysis require estimation of the innovations. The method of this paper introduces an inveree model complementary to the original model so that the estimation of the innovations is avoided. This leads to a substantial reduction in the computational complexity in the two-dimensional case.     

Stress and tobacco use among African-American adolescents: the buffering effect of cultural factors

Tobacco is a leading contributor to morbidity and mortality and a primary reason for health disparities among African Americans. In this study we explore the role of stress in smoking and cultural factors that protect against stress among African-American adolescents. Our sample consisted of 239 youth who were recruited into the study while enrolled in 8th and 12th grade. Measures of risk factors (stress, school transition stress, and community disorganization), moderator or protective factors (religious support and intergenerational connections), and 30-day tobacco use were collected. Hierarchical multiple regression analyses were conducted. Intergenerational connections moderated the effect of stress on past 30-day tobacco use. Religious support moderated the effect of neighborhood disorganization on past 30-day tobacco use. Religious support also moderated the effect of stress on past 30-day tobacco use. The findings have implications for prevention efforts to consider religious beliefs and practices and also to link youth with supportive adults in their community.     

Techniques of Death: Buddhist Practice,Femininity and Self-Cultivation at the Last Stage of Life in Vietnam

This article explores how death is conceptualised by elderly lay Buddhist women in H? Chí Minh City (Vietnam). It explores the traits of a ‘good death’ which elderly laywomen wish to experience, and their dedicated practice of Buddhism to prepare themselves for a peaceful end stage of life. This article contends that, in fact, women’s perceptions of death speak to their desires to live a life with dignity and retain their full personhood and nurturing femininity which they have embodied throughout their adult lives even until their last moments. They pursue devotional practices to train their body and mind in order to prepare themselves for the critical moment of dying, believing that these self-cultivating practices will enable them to transcend physical suffering and mental confusion, and immediately move on to the next, better life.     

No-cointegration test based on fractional differencing: Some Monte Carlo results

This paper examines the use of the t-statistic in the Geweke–Porter-Hudak regression for the estimation of the fractional differencing parameter as a test for cointegration. The critical values of the test statistic are estimated using Monte Carlo methods. The results confirm that the test will over-reject the null hypothesis of no cointegration if the standard-normal critical values are used. The estimated critical values are generally robust to the nuisance parameters in the autoregressive or moving average specification of the error process of the component time series. Exceptions occur when the dependent variable in the cointegration regression follows an autoregressive process with a large positive parameter or a moving average process with a large negative parameter.     

Measuring Attitudes About Intimate Partner Violence Against Women: The ATT-IPV Scale

In lower-income settings, women more often than men justify intimate partner violence (IPV). Yet, the role of measurement invariance across gender is unstudied. We developed the ATT-IPV scale to measure attitudes about physical violence against wives in 1,055 married men and women ages 18–50 in My Hao district, Vietnam. Across 10 items about transgressions of the wife, women more often than men agreed that a man had good reason to hit his wife (3 % to 92 %; 0 % to 67 %). In random split-half samples, one-factor exploratory factor analysis (EFA) (N ₁ = 527) and confirmatory factor analysis (CFA) (N ₂ = 528) models for nine items with sufficient variability had significant loadings (0.575–0.883; 0.502–0.897) and good fit (RMSEA = 0.068, 0.048; CFI = 0.951, 0.978, TLI = 0.935, 0.970). Three items had significant uniform differential item functioning (DIF) by gender, and adjustment for DIF revealed that measurement noninvariance was partially masking men’s lower propensity than women to justify IPV. A CFA model for the six items without DIF had excellent fit (RMSEA = 0.019, CFI = 0.994, TLI = 0.991) and an attitudinal gender gap similar to the DIF-adjusted nine-item model, suggesting that the six-item scale reliably measures attitudes about IPV across gender. Researchers should validate the scale in urban Vietnam and elsewhere and decompose DIF-adjusted gender attitudinal gaps.     

Estimation and Simulation of the Riesz-Bessel Distribution

ABSTRACT

In this article, further properties of the Riesz-Bessel distribution are provided. These properties allow for the simulation of random variables from the Riesz-Bessel distribution. Estimation is addressed by nonlinear generalized least squares regression on the empirical characteristic function. The estimator is seen to approximate the maximum likelihood estimator. The distribution is illustrated with financial data.     

Biodiversity,coastal protection and resource endowment: Policy options for improving ocean health

The paper develops a production function for the Global Ocean Health Index (OHI) for 2013. Data from the Ocean Health Statistics, plus from the Human Development Index (HDI) for 151 countries are used. We employ two-stage regression model to conduct this evaluation. The Tobit model, used to obtain the estimated dependent variable, results show Coastal Protection, Livelihoods and Economies, Tourism and Recreation, Iconic Species, Clean Water and Biodiversity, Food Provision, Artisanal Fisheries Opportunities, Natural Products, and Carbon Storage are significant variables. The rank regression in the second stage showed that HDI and Marine Protected Areas (MPAs) significantly influenced the predicted value of the OHI. Policy makers should note that biodiversity increases have the greatest effect on OHI, and its improvement is within reach of even the poorest country. Countries with varying levels of resource endowment may choose different techniques to improve OHI, but the implementation of MPAs should be priority.     

Semiparametric regression under long-range dependent errors

In this paper, we consider a semiparametric regression model under long-range dependent errors. By approximating the nonparametric component by a finite series sum, we construct consistent estimators for both parametric and nonparametric components. Meanwhile, convergence rates for the consistent estimators are also investigated. Additionally, an optimal truncation parameter selection procedure is proposed.     

Estimated Generalized Least Squares for Random Coefficient Regression Models

ABSTRACT. This paper considers a general class of random coefficient regression (RCR) models to represent pooled cross-sectional and time series data. A new method is given to estimate the covariance matrix of the error component in these RCR models. Also, the asymptotic and small sample properties of the estimated generalized least squares estimator of the regression coefficient vector are established. Procedures for testing a linear restriction on the mean vector of the random coefficients are derived. Finally, a test for non-randomness in the RCR model is devised, and the asymptotic distribution of the test statistic is obtained.