Detecting structural change with heteroskedasticity

The hypothesis of structural stability that the regression coefficients do not change over time is central to all applications of linear regression models. It is rather surprising that existing theory as well as practice focus on testing for structural change under homoskedasticity – that is, regression coefficients may change, but the variances remain the same. Since structural change can, and often does, involve changes in variances, this is a puzzling gap in the literature. Our main focus in this paper is to utilize a newly developed test (MZ) by Maasoumi et al. (2010 Maasoumi, E., Zaman, A., Ahmed, M. (2010). Tests for structural change, aggregation, and homogeneity. Econ Model. 27(6):1382–1391.[Crossref], [Web of Science ®] , [Google Scholar]) that tests simultaneously for break in regression coefficients as well as in variance. Currently, the sup F test is most widely used for structural change. This has certain optimality properties shown by Andrews (1993 Andrews, D.W.K. (1993). Test for parameter instability and structural change with unknown change point. Econometrica. 61(4):821–856.[Crossref], [Web of Science ®] , [Google Scholar]). However, this test assumes homoskedasticity across the structural change. We introduce the sup MZ test which caters to unknown breakpoints, and also compare it to the sup F. Our Monte Carlo results show that sup MZ test incurs only a low cost in case of homoskedasticity while having hugely better performance in case of heteroskedasticity. The simulation results are further supported by providing a real-world application. In real-world datasets, we find that structural change often involves heteroskedasticity. In such cases, the sup F test can fail to detect structural breaks and give misleading results, while the sup MZ test works well. We conclude that the sup MZ test is superior to current methodology for detecting structural change.     

A KNOWLEDGE-BASED DSS FOR MANAGERIAL PROBLEM DIAGNOSIS

A knowledge-based system supporting managerial problem diagnosis is described. The system provides the capability to monitor values of selected variables for problem situations. When problems are located, a list of problem symptoms is delivered to a problem processor for structuring and diagnosis. Problem structuring is based on a combination of concepts from expert systems and structural modeling. User assertions about cause-effect relationships between pairs of variables are maintained in a semantic network. Problem diagnosis uses the relationships in the semantic network to construct causation trees, the branches of which represent potential explanations of the problem symptoms. Mathematical models are constructed based on causation-tree branches, and values from the data base are used to test whether the model confirms the diagnosis. If so, the source of the problem has been located and it is then up to the user to resolve the problem. If the model fails to explain the problem, the model apparently is deficient and the user may perform “what if…” type scenarios in attempts to improve the model and search for problem causes. Realistic applications in the accounting and health care areas are discussed.     

Markov bridges and enlarged filtrations

The semimartingale decomposition of a Markov chain, whose value at some future time is known, is obtained by considering an enlarged filtration.     

Pre-War and Post-War Lebanese Immigrants in Melbourne

The following paper forms part of a thesis on the Lebanese community in Melbourne. The Lebanese community in Australia has not been the subject of any systematic study and thus the author attempted to investigate as many facets as possible of the life style of Melbourne's Lebanese immigrants. The purpose of this paper is to examine the causes and characteristics of immigration from Lebanon to Melbourne before and after the Second World War.     

Moslem Arab Portrayal in the Australian Press and in School Textbooks

This paper surveys the overall characterization of Moslem Arabs and their culture as reflected by the press and in social science textbooks. Four widely circulated Melbourne newspapers and 15 of the most commonly used social science school textbooks formed the basis of content analysis. It has been found that the portrayal of Moslem Arabs was predominantly negative, involving overstatements, baseless charges and evaluative perceptions.     

Observing Different Faiths,Learning About Ourselves: Practice with Inter-married Muslims and Christians

Abstract

Advanced care planning and end-of-life decision making are part of contemporary debates about death and dying. A data-mining study reviewing medical records of patient deaths in hospital investigated these issues and the utilisation of social work services. Findings indicated that the majority of records included some form of documentation about end-of-life care, including cardio pulmonary resuscitation (CPR) orders and that family members and surrogate decision makers were more likely to be consulted than patients about these plans. The incidence of referrals to social workers was found to be highest “out-of-hours”. Key social work interventions were identified, including establishing the reliability of surrogates' decisions through social work assessment. This paper discusses elements that contribute to a supportive environment for patients and family members to facilitate the decision making process, including the need for a broader ethical discourse to accommodate the increasing complexity of end-of-life decision making in hospital settings.     

An EOQ model with partial delayed payment and partial backordering

In many transactions concerning selling and buying, a specified delay of payment is offered or accepted by the seller. This can be regarded as a kind of discount and has potential consequences for the order size. These kinds of effects are not explicitly incorporated in the classical formulas for economic order quantities (EOQ). In this research we consider an EOQ problem under partial delayed payment. A fraction of the purchasing cost must be paid at the beginning of the period and the remaining amount can be paid later. Shortages are permitted and occur as a combination of backorders and lost sales. The aim of this paper is to determine the order and shortage quantities.     

Non-parametric detection of meaningless distances in high dimensional data

Distance concentration is the phenomenon that, in certain conditions, the contrast between the nearest and the farthest neighbouring points vanishes as the data dimensionality increases. It affects high dimensional data processing, analysis, retrieval, and indexing, which all rely on some notion of distance or dissimilarity. Previous work has characterised this phenomenon in the limit of infinite dimensions. However, real data is finite dimensional, and hence the infinite-dimensional characterisation is insufficient. Here we quantify the phenomenon more precisely, for the possibly high but finite dimensional case in a distribution-free manner, by bounding the tails of the probability that distances become meaningless. As an application, we show how this can be used to assess the concentration of a given distance function in some unknown data distribution solely on the basis of an available data sample from it. This can be used to test and detect problematic cases more rigorously than it is currently possible, and we demonstrate the working of this approach on both synthetic data and ten real-world data sets from different domains.     

Why bother to ‘downshift’? The characteristics and satisfaction of downshifters in the Brisbane-South East Queensland region,Australia

Using the data collected as part of a Quality of Life (QoL) survey in the Brisbane-South East Queensland region (SEQ) of Australia, this paper examines differences in satisfaction levels between downshifters and non-downshifters, and identifies socio-economic predictors of the downshifting phenomenon. Almost 30% of survey respondents are classified as downshifters. Multivariate Analysis of Covariance reveals significant differences between downshifters and non-downshifters in a number of life-satisfaction domains, although the degree to which they were satisfied with their life before downshifting is unknown. Analysis of Covariance shows that downshifters reported a significantly lower level of satisfaction than non-downshifters, especially with respect to satisfaction with the amount of money available to them, independence or freedom, and employment. Multivariate logistic regression analysis reveals that post-secondary education and employment were positively associated with downshifting, while age was significantly associated with downshifting. It is argued that if downshifting is associated with lower levels of satisfaction, intervention may be required to initiate programs to engage downshifters more fully in the workforce by facilitating more flexible work arrangements and an improved working environment.     

On the impossibility of events of zero probability

A logically consistent way of maintaining the events of probability zero are actually impossible is presented.