Discrimination of AR,MA and ARMA time series models

The problem of discrimination between two stationary ARMA time series models is considered, and in particular AR(p), MA(p), ARMA(1,1) models. The discriminant based on the likelihood ration leads to a quadratic form that is generally too complicated to evaluated explicitly. The discriminant can be expressed approximately as a linear combination of independent chi–squared random varianles each with one degree of freedom, the coefficients, of which are eigenvalues of cumbersome matrices. An analytical solution which gives the coefficients approximately is suggested.     

Darling–Erdős limit results for change-point detection in panel data

We wish to test the null hypothesis if the means of N panels remain the same during the observation period of length T. A quasi-likelihood argument leads to self-normalized statistics whose limit distribution under the null hypothesis is double exponential. The main results are derived assuming that the each panel is based on independent observations and then extended to linear processes. The proofs are based on an approximation of the sum of squared CUSUM processes using the Skorokhod embedding scheme. A simulation study illustrates that our results can be used in case of small and moderate N and T. We apply our results to detect change in the “corruption index”.     

Comment

We propose a sequential test for predictive ability for recursively assessing whether some economic variables have explanatory content for another variable. In the forecasting literature it is common to assess predictive ability by using “one-shot” tests at each estimation period. We show that this practice leads to size distortions, selects overfitted models and provides spurious evidence of in-sample predictive ability, and may lower the forecast accuracy of the model selected by the test. The usefulness of the proposed test is shown in well-known empirical applications to the real-time predictive content of money for output and the selection between linear and nonlinear models.     

Long memory stochastic volatility : A bayesian approach

We propose a simulation-based Bayesian approach to the analysis of long memory stochastic volatility models, stationary and nonstationary. The main tool used to reduce the likelihood function to a tractable form is an approximate state-space representation of the model, A data set of stock market returns is analyzed with the proposed method. The approach taken here allows a quantitative assessment of the empirical evidence in favor of the stationarity, or nonstationarity, of the instantaneous volatility of the data.     

Optimal designs for experiments with mixtures: a survey

This is a survey article on known results about analytic solutions and numerical solutions of optimal designs for various regression models for experiments with mixtures. The regression models include polynomial models, models containing homogeneous functions, models containing inverse terms and ratios, log contrast models, models with quantitative variables, and mod els containing the amount of mixture, Optimality criteria considered include D-, A-, E-,φ_p- and I_λ-Optimalities. Uniform design and uniform optimal design for mixture components, and efficiencies of the {q,2} simplex-controid design are briefly discussed.     

Generational conflict and provisions for the elderly in Hong Kong: The relevance of position‐based interest and values

Respect for the elderly and hence the associated rights support a generational contract. Nevertheless, the case of the recent debate on the universal retirement scheme in Hong Kong has raised concerns about its strength. We identify relevant items from the sixth wave of the World Values Survey to explore the orientations of different generations toward others. The analysis shows differences between younger and older generations. Regression analyses show that values are not significant in explaining the differences, but various positions, including sex, marital status, and education, and perceptions of the elderly are relevant. Such differences across generations might weaken the generational contract and potentially engender conflicts as shown in the recent debate about the retirement scheme. We suggest short‐ and long‐term interest calculations, informed by their positions, play a more significant role in policy discussions and decisions, rather than simply appealing to values.     

Examining risk and protective factors on progression of romantic relational aggression among young adults: Parental control,parental care,and peer social support

Abstract

Romantic relational aggression is related to numerous mental health consequences but risk and protective factors of perpetrating this type of aggression, historically, have been unclear. This study fills in the research gap by evaluating the impact of parental control, parental care, and peer social support on later perpetration in romantic relational aggression among 84 predominately Chinese college students. Results revealed the positive association between parental control and perpetration in romantic relational aggression, however, this association diminished in the presence of high peer social support (HSS). Despite insignificance in the main effect, parental care was negatively correlated with later perpetration in romantic relationship in the HSS group while a positive association was found in the low peer social support (LSS) group. These highlights provided evidences how parental control and parental care during childhood could be risk factors for later romantic relational aggression as well as how current social support from peer could serve as a protective factor on the negative influence from parent–child relationships.