Modeling U.S. Inflation Dynamics: A Bayesian Nonparametric Approach

This paper uses an infinite hidden Markov model (IIHMM) to analyze U.S. inflation dynamics with a particular focus on the persistence of inflation. The IHMM is a Bayesian nonparametric approach to modeling structural breaks. It allows for an unknown number of breakpoints and is a flexible and attractive alternative to existing methods. We found a clear structural break during the recent financial crisis. Prior to that, inflation persistence was high and fairly constant.

Evaluating sampling strategies and logistic regression methods for modelling complex land cover changes

The role of land cover change as a significant component of global change has become increasingly recognized in recent decades. Large databases measuring land cover change, and the data which can potentially be used to explain the observed changes, are also becoming more commonly available. When developing statistical models to investigate observed changes, it is important to be aware that the chosen sampling strategy and modelling techniques can influence results. We present a comparison of three sampling strategies and two forms of grouped logistic regression models (multinomial and ordinal) in the investigation of patterns of successional change after agricultural land abandonment in Switzerland. Results indicated that both ordinal and nominal transitional change occurs in the landscape and that the use of different sampling regimes and modelling techniques as investigative tools yield different results. Synthesis and applications. Our multimodel inference identified successfully a set of consistently selected indicators of land cover change, which can be used to predict further change, including annual average temperature, the number of already overgrown neighbouring areas of land and distance to historically destructive avalanche sites. This allows for more reliable decision making and planning with respect to landscape management. Although both model approaches gave similar results, ordinal regression yielded more parsimonious models that identified the important predictors of land cover change more efficiently. Thus, this approach is favourable where land cover change pattern can be interpreted as an ordinal process. Otherwise, multinomial logistic regression is a viable alternative.

Bayesian forecasting with highly correlated predictors

This paper considers Bayesian variable selection in regressions with a large number of possibly highly correlated macroeconomic predictors. I show that by acknowledging the correlation structure in the predictors can improve forecasts over existing popular Bayesian variable selection algorithms.

The Effects of Experience on Preference Uncertainty: Theory and Empirics for Public and Quasi-Public Environmental Goods

This paper develop and estimates a model of demand estimation for environmental public goods which allows for consumers to learn about their preferences through consumption experiences. We develop a theoretical model of Bayesian updating, perform comparative statics over the model, and show how the theoretical model can be consistently incorporated into a reduced form econometric model. We then estimate the model using data collected for two environmental goods. We find that the predictions of the theoretical exercise that additional experience makes consumers more certain over their preferences in both mean and variance are supported in each case.

Positive solutions of nonlinear problems involving the square root of the Laplacian

We consider nonlinear elliptic problems involving a nonlocal operator: the square root of the Laplacian in a bounded domain with zero Dirichlet boundary conditions. For positive solutions to problems with power nonlinearities, we establish existence and regularity results, as well as a priori estimates of Gidas-Spruck type. In addition, among other results, we prove a symmetry theorem of Gidas-Ni-Nirenberg type.

The Brezis-Nirenberg type problem involving the square root of the Laplacian

We establish existence and non-existence results to the Brezis-Nirenberg type problem involving the square root of the Laplacian in a bounded domain with zero Dirichlet boundary condition.

Inversion of analytic characteristic functions and infinite convolutions of exponential and Laplace densities

This paper shows that certain quotients of entire functions are characteristic functions. Under some conditions, we provide expressions for the densities of such characteristic functions which turn out to be generalized Dirichlet series which in turn can be expressed as an infinite linear combination of exponential or Laplace densities. We apply these results to several examples.

Suicidal expression among school-attending adolescents in a middle-income sub-Saharan country.

We investigated correlates for suicidal expression among adolescents in the Seychelles. Data on 1,432 students (52% females) were derived from the Global School-based Health Survey. Participants were divided into three groups: those with no suicidal behavior (N = 1,199); those with suicide ideation/SI (N = 89); and those reporting SI with a plan to carry out a suicide attempt/SISP (N = 139), each within a 12-month recall period. Using multinomial logistic regression, we examined the strength of associations with social, behavioral and economic indicators while adjusting for covariates. Sixteen percent of school-attending adolescents reported a suicidal expression (10% with a plan/6.2% without). Those reporting SI were younger (relative risk ratio RRR = 0.81; CI = 0.68-0.96), indicated signs of depression (RRR = 1.69; CI = 1.05-2.72) and loneliness (RRR=3.36; CI =1.93-5.84). Tobacco use (RRR = 2.34; CI = 1.32-4.12) and not having close friends (RRR = 3.32; CI = 1.54-7.15) were significantly associated with SI. Those with SISP were more likely to be female (RRR = 0.47; 0.30-0.74), anxious (RRR = 3.04; CI = 1.89-4.88) and lonely (RRR = 1.74; CI = 1.07-2.84). Having no close friends (RRR = 2.98; 1.56-5.69) and using tobacco (RRR = 2.41; 1.48-3.91) were also strongly associated. Having parents who were understanding was protective (RRR = 0.50; CI = 0.31-0.82). Our results suggest that school health promotion programs may benefit from targeting multiple factors associated with suicidal expression. More research, particularly multilevel designs are needed to identify peer and family influences which may modify associations with suicidality.

Stability and change in party preferences.

This article analyses stability and volatility of party preferences using data from the Swiss Household-Panel (SHP), which, for the first time, allow studying transitions and stability of voters over several years in Switzerland. Analyses cover the years 1999- 2007 and systematically distinguish changes between party blocks and changes within party blocks. The first part looks at different patterns of change, which show relatively high volatility. The second part tests several theories on causes of such changes applying a multinomial random-effects model. Results show that party preferences stabilise with their duration and with age and that the electoral cycle, political sophistication, socio-structural predispositions, the household-context as well as party size and the number of parties each explain part of electoral volatility. Different results for withinand between party-block changes underlie the importance of that differentiation.

Deux extensions de Théorèmes de Hamburger (portant sur l'équation fonctionnelle de la fonction dzêta)

We propose two types of extensions to Hamburger’s theorems on the Dirichlet series with functional equation like the one of the Riemann zeta function, under weaker hypotheses. This builds upon the dictionary betweeen the moderate meromorphic functions with functional equation and the tempered distributions with extended S-support condition.

Alcohol and nonlethal injuries: a Swiss emergency department study on the risk relationship between acute alcohol consumption and type of injury.

BACKGROUND: Acute alcohol consumption has been reported to be an important risk factor for injury, but clear scientific evidence on issues such as injury type is not available. The present study aims to improve the knowledge of the importance of alcohol consumption as an injury determinant with regards to two dimensions of the type of injury, namely the nature and the body region involved. METHODS: Risk relationships between two injury type components and acute alcohol use were estimated through multinomial and logistic regression models based on data from 7,529 patients-among whom 3,682 had injury diagnoses-gathered in a Swiss emergency department. RESULTS: Depending on the type of injury, between 31.1% and 48.7% of casualties report alcohol use before emergency department attendance. The multinomial regression models show that even low alcohol levels are consistently associated with nearly all natures of injury and body regions. A persistent dose-response effect between alcohol levels and risk associations was observed for almost all injury types. CONCLUSIONS: The results highlight the importance and consistency of the risk association between low and moderate levels of acute alcohol consumption and all types of injury. None of the body regions and natures of injury could pride on absence of association between alcohol and injury. Public health, prevention, and care implications are considered.

The European Respiratory Society spirometry tent: a unique form of screening for airway obstruction.

In order to raise public awareness of the importance of early detection of airway obstruction and to enable many people who had not been tested previously to have their lung function measured, the European Lung Foundation and the European Respiratory Society (ERS) organised a spirometry testing tent during the annual ERS Congresses in 2004-2009. Spirometry was performed during the ERS Congresses in volunteers; all participants answered a simple, brief questionnaire on their descriptive characteristics, smoking and asthma. Portable spirometers were freely provided by the manufacturer. Nurses and doctors from pulmonary departments of local hospitals/universities gave their service for free. Lower limit of normal (LLN) and Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria for diagnosing and grading airway obstruction were used. Of 12,448 participants in six congress cities, 10,395 (83.5%) performed acceptable spirometry (mean age 51.0 ± 18.4 yrs; 25.5% smokers; 5.5% asthmatic). Airway obstruction was present in 12.4% of investigated subjects according to LLN criteria and 20.3% according to GOLD criteria. Through multinomial logistic regression analysis, age, smoking habits and asthma were significant risk factors for airway obstruction. Relative risk ratio and 95% confidence interval for LLN stage I, for example, was 2.9 (2.0-4.1) for the youngest age (≤ 19 yrs), 1.9 (1.2-3.0) for the oldest age (≥ 80 yrs), 2.4 (2.0-2.9) for current smokers and 2.8 (2.2-3.6) for reported asthma diagnosis. In addition to being a useful advocacy tool, the spirometry tent represents an unusual occasion for early detection of airway obstruction in large numbers of city residents with an important public health perspective.

A tale of two logits, compositional data analysis and zero observations

The application of compositional data analysis through log ratio trans-formations corresponds to a multinomial logit model for the shares themselves.This model is characterized by the property of Independence of Irrelevant Alter-natives (IIA). IIA states that the odds ratio in this case the ratio of shares is invariant to the addition or deletion of outcomes to the problem. It is exactlythis invariance of the ratio that underlies the commonly used zero replacementprocedure in compositional data analysis. In this paper we investigate using thenested logit model that does not embody IIA and an associated zero replacementprocedure and compare its performance with that of the more usual approach ofusing the multinomial logit model. Our comparisons exploit a data set that com-bines voting data by electoral division with corresponding census data for eachdivision for the 2001 Federal election in Australia

Bayesian tools for zero counts in compositional data

The log-ratio methodology makes available powerful tools for analyzing compositionaldata. Nevertheless, the use of this methodology is only possible for those data setswithout null values. Consequently, in those data sets where the zeros are present, aprevious treatment becomes necessary. Last advances in the treatment of compositionalzeros have been centered especially in the zeros of structural nature and in the roundedzeros. These tools do not contemplate the particular case of count compositional datasets with null values. In this work we deal with \count zeros" and we introduce atreatment based on a mixed Bayesian-multiplicative estimation. We use the Dirichletprobability distribution as a prior and we estimate the posterior probabilities. Then weapply a multiplicative modi¯cation for the non-zero values. We present a case studywhere this new methodology is applied.Key words: count data, multiplicative replacement, composition, log-ratio analysis

CODAMAT: a modern analogue techinque for compositional data

The quantitative estimation of Sea Surface Temperatures from fossils assemblages is afundamental issue in palaeoclimatic and paleooceanographic investigations. TheModern Analogue Technique, a widely adopted method based on direct comparison offossil assemblages with modern coretop samples, was revised with the aim ofconforming it to compositional data analysis. The new CODAMAT method wasdeveloped by adopting the Aitchison metric as distance measure. Modern coretopdatasets are characterised by a large amount of zeros. The zero replacement was carriedout by adopting a Bayesian approach to the zero replacement, based on a posteriorestimation of the parameter of the multinomial distribution. The number of modernanalogues from which reconstructing the SST was determined by means of a multipleapproach by considering the Proxies correlation matrix, Standardized Residual Sum ofSquares and Mean Squared Distance. This new CODAMAT method was applied to theplanktonic foraminiferal assemblages of a core recovered in the Tyrrhenian Sea.Kew words: Modern analogues, Aitchison distance, Proxies correlation matrix,Standardized Residual Sum of Squares