Estimation of parameterized spatio-temporal dynamic models

Spatio-temporal processes are often high-dimensional, exhibiting complicated variability across space and time. Traditional state-space model approaches to such processes in the presence of uncertain data have been shown to be useful. However, estimation of state-space models in this context is often problematic since parameter vectors and matrices are of high dimension and can have complicated dependence structures. We propose a spatio-temporal dynamic model formulation with parameter matrices restricted based on prior scientific knowledge and/or common spatial models. Estimation is carried out via the expectation–maximization (EM) algorithm or general EM algorithm. Several parameterization strategies are proposed and analytical or computational closed form EM update equations are derived for each. We apply the methodology to a model based on an advection–diffusion partial differential equation in a simulation study and also to a dimension-reduced model for a Palmer Drought Severity Index (PDSI) data set.     

The Federal Aviation Administration Airport Improvement Program: Who Benefits?

Public Organization Review - The objective of the (U.S.) Federal Aviation Administration Airport Improvement Program (AIP) is “to help in developing a nationwide system of public-use airports...     

The impact of tax rates, political partisanship and economic variables on the distribution of state and local tax burdens

This study finds that the effective state and local tax rate for the top 1% of income households as a percentage of the effective state and local tax rate for the bottom 20% of income households in 2002 is significantly influenced by whether a state has a multi-rate income tax, right-to-work laws, the liberalism of a state's electorate, the average tax burden in a state and past tax policy. Democratic Party strength in state government, Republican or Democratic Party institutional control of state government, change in real per capita income, a Democratic Governor and the change in the share of income going to the top 1% of income households are not significant predictors. The empirical results are identical for the top 2-5% of income households to the bottom 20% of income households.     

Polarization or “Squeezed Middle” in the Great Recession?: A Comparative European Analysis of the Distribution of Economic Stress

This paper analyses variation in the impact of the Great Recession on economic stress across income classes for a range of advanced European countries. Our analysis shows Iceland, Ireland and Greece to be quite distinctive in terms of increases in their multidimensional income, material deprivation and economic stress profiles. Between 2008 and 2012 these countries moved from being predictably located within anticipated welfare regimes to becoming clear outliers. For this set of counties, each of which was exposed to different but severe forms of economic shock, trends in income class polarisation versus middle class squeeze were variable. Each exhibited substantial increases in levels of economic stress. However, changes in the pattern of income class differentiation were somewhat different. In Iceland a form of middle class squeeze was observed. For Ireland income class polarization did not exclude middle class squeeze. Greece came closest to fitting the polarization profile. Changes in the distribution of household equivalent income had no effect on stress levels once the impact of material deprivation was taken into account. Changes in levels of material deprivation played a significant role in accounting for changing stress levels but only for the three lowest income classes. These findings bring out the extent to which the impact of the Great Recession on the distribution of economic stress across classes varied even among the hardest-hit countries. They also serve to highlight the advantages of a multidimensional approach that goes beyond reliance on income in seeking to understand the impact of such shocks.     

Spiritual Struggles and Psychological Distress: Is There a Dark Side of Religion?

A growing literature examines the correlates and sequelae of spiritual struggles. Particular attention has been focused on three specific types of such struggles: (a) divine, or troubled relationships with God; (b) interpersonal, or negative social encounters in religious settings; and (c) intrapsychic, or chronic religious doubting. To date, however, this literature has focused primarily on one or another type, leaving open the possibility that these are highly correlated and may tap a single, underlying dimension. Further, because studies have relied mostly on small, specialized samples, it is not clear whether the associations between spiritual struggles and psychological functioning vary across key subgroups in the US population. Using data from the 1998 NORC General Social Survey we address these issues. Findings reveal strong and independent associations between each type of spiritual struggle and psychological distress, and they also show that these patterns are robust across most population subgroups, except for variations by age and marital status. Implications, study limitations, and directions for further research are identified.     

To Join or Not to Join: Gay-Straight Student Alliances and the High School Experiences of Lesbian,Gay, Bisexual,and Transgender Youths

This retrospective study investigates 79 lesbian, gay, bisexual, and transgender (LGBT) college students’ experiences attending high schools with gay-straight student alliances (GSAs). Responses to two, open-ended survey questions were analyzed thematically to identify reasons that underlie GSA non-membership and to model facets of GSAs that may impact the GSA-related experiences of LGBT youths. Three frames of reference for understanding GSA non-membership and perceptions of GSAs emerged. Implications for predicting GSA membership and identifying protective mechanisms of GSAs are outlined. Suggestions to help GSA leaders and advisors enhance specific aspects of GSAs that appear to be associated with positive perceptions of GSAs are also provided.     

Confidence intervals for lognormal regression and a non-parametric alternative

Approximate confidence intervals are given for the lognormal regression problem. The error in the nominal level can be reduced to O(n ^?2), where n is the sample size. An alternative procedure is given which avoids the non-robust assumption of lognormality. This amounts to finding a confidence interval based on M-estimates for a general smooth function of both ? and F, where ? are the parameters of the general (possibly nonlinear) regression problem and F is the unknown distribution function of the residuals. The derived intervals are compared using theory, simulation and real data sets.