An Improved Divergence Information Criterion for the Determination of the Order of an AR Process

In this article we propose a modification of the recently introduced divergence information criterion (DIC, Mattheou et al., 2009 Mattheou , K. , Lee , S. , Karagrigoriou , A. ( 2009 ). A model selection criterion based on the BHHJ measure of divergence . Journal of Statistical Planning and Inference 139 : 128 – 135 .[Crossref], [Web of Science ®] , [Google Scholar]) for the determination of the order of an autoregressive process and show that it is an asymptotically unbiased estimator of the expected overall discrepancy, a nonnegative quantity that measures the distance between the true unknown model and a fitted approximating model. Further, we use Monte Carlo methods and various data generating processes for small, medium, and large sample sizes in order to explore the capabilities of the new criterion in selecting the optimal order in autoregressive processes and in general in a time series context. The new criterion shows remarkably good results by choosing the correct model more frequently than traditional information criteria.     

Variance estimation for integrated population models

State-space models are widely used in ecology. However, it is well known that in practice it can be difficult to estimate both the process and observation variances that occur in such models. We consider this issue for integrated population models, which incorporate state-space models for population dynamics. To some extent, the mechanism of integrated population models protects against this problem, but it can still arise, and two illustrations are provided, in each of which the observation variance is estimated as zero. In the context of an extended case study involving data on British Grey herons, we consider alternative approaches for dealing with the problem when it occurs. In particular, we consider penalised likelihood, a method based on fitting splines and a method of pseudo-replication, which is undertaken via a simple bootstrap procedure. For the case study of the paper, it is shown that when it occurs, an estimate of zero observation variance is unimportant for inference relating to the model parameters of primary interest. This unexpected finding is supported by a simulation study.     

How do Greek banking institutions react after significant events?—A DEA approach

The efficiency of Greek commercial banks is considered through the period 1995–2003 using the data envelopment analysis technique. Two approaches are used to measure efficiency: one using financial ratios as outputs only and the other viewing banks as credit generation and transaction institutions. The empirical results are used to examine the reaction of banking institutions after significant events such as M&As, privatizations and the crisis of the Athens Stock Exchange in 1999. In most cases performance deteriorates for the next 1 to 2 years, while increases thereafter, forming specific patterns of efficiency. In the last part we introduce an index to measure the management's efficiency through a process of change. The results suggest that the Greek banking sector operated efficiently on average during the destabilization periods. The contribution of the article is that it comprises the first study which examines empirically the performance behavior of banking institutions within the scope of change management theory.     

Determinants of Well-being Among Legal and Illegal Immigrants: Evidence from South Italy

The pursuit of happiness and life satisfaction mobilises individuals to create a dynamic, unique, everyday reality for themselves. The literature has placed particular emphasis on the study of immigrants on the basis that migration is triggered by discrepancies between prior expectations and realisations post-migration. However, the relationship between happiness and illegal migration has received little attention. This study contributes to the current literature by analysing a sample of both illegal and legal immigrants to test the established socio-economic drivers of well-being for each group. Additionally, for the first time, the subjective well-being (SWB) of the respondents is measured in a continuous scale utilising the Visual Analogue Scale technique. Our findings demonstrate that illegal immigrants not only experience greater increases in SWB, but they also report higher levels. Finally, the income effect is positively correlated (although weak) with SWB for illegal immigrants only and family size is positively correlated with greater levels of SWB for their legal counterparts.     

GARCH-Type Models and Performance of Information Criteria

This article discusses the ability of information criteria toward the correct selection of different especially higher-order generalized autoregressive conditional heteroscedasticity (GARCH) processes, based on their probability of correct selection as a measure of performance. Each of the considered GARCH processes is further simulated at different parameter combinations to study the possible effect of different volatility structures on these information criteria. We notice an impact from the volatility structure of time series on the performance of these criteria. Moreover, the influence of sample size, having an impact on the performance of these criteria toward correct selection, is observed.     

Does the supplemental nutrition assistance program really increase obesity? The importance of accounting for misclassification errors

The prevalence of obesity among US citizens has grown rapidly over the last few decades, especially among low-income individuals. This has led to questions about the effectiveness of nutritional assistance programs such as the Supplemental Nutrition Assistance Program (SNAP). Previous results on the effect of SNAP participation on obesity are mixed. These findings are however based on the assumption that participation status can be accurately observed, despite significant misclassification errors reported in the literature. Using propensity score matching, we conclude that there seems to be a positive effect of SNAP participation on obesity rates for female participants and no such effect for males, a result that is consistent with several previous studies. However, an extensive sensitivity analysis reveals that the positive effect for females is sensitive to misclassification errors and to the conditional independence assumption. Thus analogous findings should also be used with caution unless examined under the prism of classification errors and of other assumptions used for the identification of causal parameters.     

A Useful Pivotal Quantity

Consider n continuous random variables with joint density f that possibly dependson unknown parameters θ. If the negative of the logarithm of f is a positive homogenous function of degree p taking only positive values, then that function is distributed as a Gamma random variable with shape n/p and scale 2, and thus it is a pivotal quantity for θ. This provides a general method to construct pivotal quantities, which are widely applicable in statistical practice, such as hypothesis testing and confidence intervals. Here, we prove the aforementioned result and illustrate through examples.     

The effect of spillover on the Granger causality test

In this paper, we investigate the properties of the Granger causality test in stationary and stable vector autoregressive models under the presence of spillover effects, that is, causality in variance. The Wald test and the WW test (the Wald test with White's proposed heteroskedasticity-consistent covariance matrix estimator imposed) are analyzed. The investigation is undertaken by using Monte Carlo simulation in which two different sample sizes and six different kinds of data-generating processes are used. The results show that the Wald test over-rejects the null hypothesis both with and without the spillover effect, and that the over-rejection in the latter case is more severe in larger samples. The size properties of the WW test are satisfactory when there is spillover between the variables. Only when there is feedback in the variance is the size of the WW test slightly affected. The Wald test is shown to have higher power than the WW test when the errors follow a GARCH(1,1) process without a spillover effect. When there is a spillover, the power of both tests deteriorates, which implies that the spillover has a negative effect on the causality tests.