Environmental Sustainability and Social Work: A Rural Australian Evaluation of Incorporating Eco-Social Work in Field Education

Climate change poses significant threat to the wellbeing of global society. Addressing this change has as yet generated no fixed blueprint for social work practice and education. This paper reports on a formative evaluation of one Australian initiative to address this transformative opening in social work field education. Prompted by service users' and workers' experience of the impact of drought, a rurally located social work course team amended the field education curriculum to include a focus on Environment and Sustainability. This learning goal was added to the existing learning goals derived from the Australian Association of Social Workers (AASW) Practice Standards. Students and field supervisors were surveyed on their experience of meeting this new learning goal. While most expressed confidence in understanding the concepts involved, they clearly lacked assurance in interpreting these in practice encounters. Considering their qualitative input suggests that this topic is making a transition from being on the margins of social work to becoming mainstream. Their open-ended responses indicate that the incorporation of environmental sustainability into practice is at a threshold stage of development. Further enactment of eco-social work at the local level is concluded to be supported by using a transformative learning framework in facilitating critical reflection and collaborative dialogue for effective change.     

Finite-sample Resampling-based Combined Hypothesis Tests,with Applications to Serial Correlation and Predictability

This article suggests Monte Carlo multiple test procedures which are provably valid in finite samples. These include combination methods originally proposed for independent statistics and further improvements which formalize statistical practice. We also adopt the Monte Carlo test method to noncontinuous combined statistics. The methods suggested are applied to test serial dependence and predictability. In particular, we introduce and analyze new procedures that account for endogenous lag selection. A simulation study illustrates the properties of the proposed methods. Results show that concrete and nonspurious power gains (over standard combination methods) can be achieved through the combined Monte Carlo test approach, and confirm arguments in favor of variance-ratio type criteria.     

Does digitization lead to the homogenization of cultural content?

Using weekly music charts data in 10 countries over the period 1990–2015, we analyze whether digitization leads to a trend of homogenization of music content or conversely to a greater acoustic disparity. We split the digitization era in four periods that correspond to four new emblematic distribution models (Napster, iTunes, YouTube, Spotify). Our main result is that while acoustic diversity decreased during the iTunes and the YouTube periods, the period that begins with the introduction of audio streaming services, such as Spotify, represents a turning point and is marked by a significant increase in acoustic diversity.     

The impact of risk aversion and ambiguity aversion on annuity and saving choices

Journal of Risk and Uncertainty - We analyze the impact of risk aversion and ambiguity aversion on the competing demands for annuities and bequeathable savings using a lifecycle recursive utility...     

Five legitimate definitions of correlated equilibrium in games with incomplete information

Aumann's (1987) theorem shows that correlated equilibrium is an expression of Bayesian rationality. We extend this result to games with incomplete information.First, we rely on Harsanyi's (1967) model and represent the underlying multiperson decision problem as a fixed game with imperfect information. We survey four definitions of correlated equilibrium which have appeared in the literature. We show that these definitions are not equivalent to each other. We prove that one of them fits Aumann's framework; the agents normal form correlated equilibrium is an expression of Bayesian rationality in games with incomplete information.We also follow a universal Bayesian approach based on Mertens and Zamir's (1985) construction of the universal beliefs space. Hierarchies of beliefs over independent variables (states of nature) and dependent variables (actions) are then constructed simultaneously. We establish that the universal set of Bayesian solutions satisfies another extension of Aumann's theorem.We get the following corollary: once the types of the players are not fixed by the model, the various definitions of correlated equilibrium previously considered are equivalent.     

Conspicuous conservatism in risk choice

We analyze the risk levels chosen by agents who have private information regarding their quality, and whose performance will be judged and rewarded by outsiders. Assume that risk choice is observable. Agents will choose risk strategically to enhance their expected reputations. We show that conspicuous conservatism results: agents of different qualities choose levels below those that would be chosen if quality were observable. This happens because bad agents must cloak their identity by choosing the same risk level as good agents, and good agents are more likely to distinguish themselves if they reduce the risk level. Our results contrast starkly with those for the case when risk choice cannot be observed.

Variance estimation when donor imputation is used to fill in missing values

Donor imputation is frequently used in surveys. However, very few variance estimation methods that take into account donor imputation have been developed in the literature. This is particularly true for surveys with high sampling fractions using nearest donor imputation, often called nearest‐neighbour imputation. In this paper, the authors develop a variance estimator for donor imputation based on the assumption that the imputed estimator of a domain total is approximately unbiased under an imputation model; that is, a model for the variable requiring imputation. Their variance estimator is valid, irrespective of the magnitude of the sampling fractions and the complexity of the donor imputation method, provided that the imputation model mean and variance are accurately estimated. They evaluate its performance in a simulation study and show that nonparametric estimation of the model mean and variance via smoothing splines brings robustness with respect to imputation model misspecifications. They also apply their variance estimator to real survey data when nearest‐neighbour imputation has been used to fill in the missing values. The Canadian Journal of Statistics 37: 400–416; 2009 © 2009 Statistical Society of Canada     

On the almost unbiased generalized liu estimator and unbiased estimation of the bias and mse

In this paper, we derive the almost unbiased generalized Liu estimator and examine an exact unbiased estimator of the bias and mean squared error of the feasible generalized Liu estimator . We compare the almost unbiased generalized Liu estimator (AUGLE) with the generalized Liu estimator (GLE) and with the ordinary least squares estimator (OLSE).