Use of weighted least squares regression jn simulation studies

When a simulation or Monte Carlo analysis uses the same set of N samples as input for the comparison of the power of tests, the resulting estimates of power are highly correlated. As a result, the statistical analysis of these results should use weighted least squares or other equivalent procedures. A reanalysis of one simulation study (Thode et al., 1983) found that the weighted least squares estimates had much smaller standard errors than the ordinary least squares estimates. The reduction in the standard errors of the parameters was a factor between 4 and 9 for the tests found to be more powerful. The necessary calculations are described.     

Univariate Bayesian nonparametric mixture modeling with unimodal kernels

Within the context of mixture modeling, the normal distribution is typically used as the components distribution. However, if a cluster is skewed or heavy tailed, then the normal distribution will be inefficient and many may be needed to model a single cluster. In this paper, we present an attempt to solve this problem. We define a cluster, in the absence of further information, to be a group of data which can be modeled by a unimodal density function. Hence, our intention is to use a family of univariate distribution functions, to replace the normal, for which the only constraint is unimodality. With this aim, we devise a new family of nonparametric unimodal distributions, which has large support over the space of univariate unimodal distributions. The difficult aspect of the Bayesian model is to construct a suitable MCMC algorithm to sample from the correct posterior distribution. The key will be the introduction of strategic latent variables and the use of the Product Space view of Reversible Jump methodology.     

Using large data sets to forecast sectoral employment

We use several models using classical and Bayesian methods to forecast employment for eight sectors of the US economy. In addition to using standard vector-autoregressive and Bayesian vector autoregressive models, we also augment these models to include the information content of 143 additional monthly series in some models. Several approaches exist for incorporating information from a large number of series. We consider two multivariate approaches—extracting common factors (principal components) and Bayesian shrinkage. After extracting the common factors, we use Bayesian factor-augmented vector autoregressive and vector error-correction models, as well as Bayesian shrinkage in a large-scale Bayesian vector autoregressive models. For an in-sample period of January 1972 to December 1989 and an out-of-sample period of January 1990 to March 2010, we compare the forecast performance of the alternative models. More specifically, we perform ex-post and ex-ante out-of-sample forecasts from January 1990 through March 2009 and from April 2009 through March 2010, respectively. We find that factor augmented models, especially error-correction versions, generally prove the best in out-of-sample forecast performance, implying that in addition to macroeconomic variables, incorporating long-run relationships along with short-run dynamics play an important role in forecasting employment. Forecast combination models, however, based on the simple average forecasts of the various models used, outperform the best performing individual models for six of the eight sectoral employment series.     

Putting the parity into service‐user participation: An integrated model of social justice

Models of service‐user participation have derived from citizenship or consumerist agendas, neither of which has achieved the structural reforms important for the most marginalised social work clients. This article proposes Fraser's model of ‘parity of participation’ as an appropriately multifaceted frame for capturing the social justice aspirations of service‐user participation. A qualitative case study compared the experiences and expectations of people who had used Australian mental health services with a sample who had used Australian homelessness services to examine their expectations of participation at individual and representative levels. The findings reinforce concerns from Fraser's research about the tendency for identity‐based consumerist notions of participation to reify group identity. This leads to tokenistic service‐user involvement strategies that have little impact on participation at a structural level. Fraser's parity of participation is shown to have untested potential to reshape service‐user participation to meet the social justice aspirations of social work clients. Key Practitioner Message: ● Innovative, service‐user driven strategies for collaboration will be those which challenge existing power structures; ● Service users want their contributions to decision making to generate identifiable change in the system of social services; ● The success of service‐user participation strategies might be the extent to which political, economic and cultural opportunities are enhanced.     

Using Critical Realism to Explain Indeterminacy in Role Behaviour Systematically

We demonstrate in this article how critical realism can be used to explain indeterminacy in role behaviour systematically. In so doing, we both rebut various criticisms of critical realism made recently by Kemp and Holmwood and attempt to illustrate the weaknesses and absences of approaches that concentrate unduly on the collection of expectations of (different groups of) actors concerning roles and the behaviour of incumbents. Within a framework that recognises that structure and agency are ontologically distinct but necessarily empirically related entities, we argue that structures should be seen as sources of indeterminacy within role behaviour for at least four reasons: the co‐determination of roles through the intersection of structures; conflicting role expectations caused by contradictions inhering within structures; asymmetries of power within social relations; and asymmetric repetition within structural reproduction/transformation. In light of this discussion of structural sources of indeterminacy, we then go on to demonstrate how critical realism is also able to analyse systematically the agential sources of indeterminacy within role behaviour and expectations through theories of psychobiography and reflexivity. We thus conclude that critical realism contains the conceptual tools required to illuminate the point(s) of intersection between structure, culture and agency which is central to understanding both role behaviour and the plurality of expectations concerning such behaviour.     

A Note on Whittle's Likelihood

The approximate likelihood function introduced by Whittle has been used to estimate the spectral density and certain parameters of a variety of time series models. In this note we attempt to empirically quantify the loss of efficiency of Whittle's method in nonstandard settings. A recently developed representation of some first-order non-Gaussian stationary autoregressive process allows a direct comparison of the true likelihood function with that of Whittle. The conclusion is that Whittle's likelihood can produce unreliable estimates in the non-Gaussian case, even for moderate sample sizes. Moreover, for small samples, and if the autocorrelation of the process is high, Whittle's approximation is not efficient even in the Gaussian case. While these facts are known to some extent, the present study sheds more light on the degree of efficiency loss incurred by using Whittle's likelihood, in both Gaussian and non-Gaussian cases.     

Posterior Sampling When the Normalizing Constant is Unknown

This article describes a means by which to undertake Bayesian posterior inference via sampling techniques when the normalizing constant is not computable and hence unavailable. The strategy relies on the introduction of latent variables which removes any integrals associated with the inaccessibility of the normalizing constant.     

Testing for Unit Roots and the Impact of Quadratic Trends,with an Application to Relative Primary Commodity Prices

In practice a degree of uncertainty will always exist concerning what specification to adopt for the deterministic trend function when running unit root tests. While most macroeconomic time series appear to display an underlying trend, it is often far from clear whether this component is best modeled as a simple linear trend (so that long-run growth rates are constant) or by a more complicated nonlinear trend function which may, for instance, allow the deterministic trend component to evolve gradually over time. In this article, we consider the effects on unit root testing of allowing for a local quadratic trend, a simple yet very flexible example of the latter. Where a local quadratic trend is present but not modeled, we show that the quasi-differenced detrended Dickey–Fuller-type test of Elliott et al. (1996 Elliott , G. , Rothenberg , T. J. , Stock , J. H. ( 1996 ). Efficient tests for an autoregressive unit root . Econometrica 64 : 813 – 836 .[Crossref], [Web of Science ®] , [Google Scholar]) has both size and power which tend to zero asymptotically. An extension of the Elliott et al. (1996 Elliott , G. , Rothenberg , T. J. , Stock , J. H. ( 1996 ). Efficient tests for an autoregressive unit root . Econometrica 64 : 813 – 836 .[Crossref], [Web of Science ®] , [Google Scholar]) approach to allow for a quadratic trend resolves this problem but is shown to result in large power losses relative to the standard detrended test when no quadratic trend is present. We consequently propose a simple and practical approach to dealing with this form of uncertainty based on a union of rejections-based decision rule whereby the unit root is rejected whenever either of the detrended or quadratic detrended unit root tests rejects. A modification of this basic strategy is also suggested which further improves on the properties of the procedure. An application to relative primary commodity price data highlights the empirical relevance of the methods outlined in this article. A by-product of our analysis is the development of a test for the presence of a quadratic trend which is robust to whether the data admit a unit root.     

CRIME AND POLICE RESOURCES: THE STREET CRIME INITIATIVE

In this paper we look at the connection between police resources and crime by focussing on a large‐scale policy intervention—the Street Crime Initiative—that was introduced in England and Wales in 2002. This allocated additional resources to some police force areas to specifically target street crime, whereas other forces did not receive any additional funding. Estimates derived from several empirical strategies show that robberies fell significantly in SCI police forces relative to non‐SCI forces after the initiative was introduced. Moreover, the policy seems to have been a cost effective one, even after extensively testing for possible displacement or diffusion effects onto other crimes and into adjacent areas. Overall, we reach the conclusion that increased police resources can be used to generate falls in crime, at least in the context of the SCI program we study. (JEL: H00, H5, K42)     

Understanding and informing policy implementation: a case study of the domestic violence provisions of the Maryland Gun Violence Act

The Maryland Gun Violence Act, enacted into law in 1996, explicitly authorized courts to order batterers to surrender their firearms through civil protective orders. It also vested law enforcement with the explicit authority to remove guns when responding to a domestic violence complaint. In order to assess how these laws were implemented, we designed a case study and collected data from in-depth, key informant interviews, court observations, and relevant documents. We present findings from this study and recommend how to increase the likelihood that policies designed to separate batterers and guns are implemented in a way that will result in greater protections for victims of domestic violence.