Immigration politics by proxy: state agency in an era of national reluctance

ABSTRACT

While attempts to reform immigration policy have stalled in the U.S. Congress, statehouses across the country are responsible for an explosion in immigration lawmaking. This study uses an intergovernmental relations framework to identify shifting allocations of authority and contested scales of jurisdiction that now characterise the U.S. immigration policy. It presents an analysis of more than 2200 state bills passed over eight years (2006–2013), and supplements this with a case study of drivers’ licence and identification laws. The study is unique in its consideration of the ways that dispersed authority in multi-level systems may amplify rather than defuse contentious immigration politics.     

A Bootstrap Approach for Testing Marginal Independence Between Two Categorical Variables When Subjects Have Repeated Responses

To assess independence in two-way contingency tables, the Pearson chi-square test or Fisher’s exact test are typically used. These tests assume that each subject contributes at most one count to only one table cell (e.g., sex versus blood type). In other situations, each subject may have more than one count contributing to the table and these counts may occur in different cells of the table. One may wish to test independence, adjusting for the within-subject correlation. We provide a simple nonparametric bootstrap approach and assess its performance through simulation studies. The method is illustrated on subjects with multiple mental health presentations to Emergency Departments.     

Insurance Policies for Monetary Policy in the Euro Area

In this paper, we aim to design a monetary policy for the euro area that is robust to the high degree of model uncertainty at the start of monetary union and allows for learning about model probabilities. To this end, we compare and ultimately combine Bayesian and worst‐case analysis using four reference models estimated with pre–European Monetary Union (EMU) synthetic data. We start by computing the cost of insurance against model uncertainty, that is, the relative performance of worst‐case or minimax policy versus Bayesian policy. While maximum insurance comes at moderate costs, we highlight three shortcomings of this worst‐case insurance policy: (i) prior beliefs that would rationalize it from a Bayesian perspective indicate that such insurance is strongly oriented towards the model with highest baseline losses; (ii) the minimax policy is not as tolerant towards small perturbations of policy parameters as the Bayesian policy; and (iii) the minimax policy offers no avenue for incorporating posterior model probabilities derived from data available since monetary union. Thus, we propose preferences for robust policy design that reflect a mixture of the Bayesian and minimax approaches. We show how the incoming EMU data may then be used to update model probabilities, and investigate the implications for policy. (JEL: E52, E58, E61)     

After the wave-the Centrelink Social Work response offshore

Communities worldwide were affected by the tsunamis that struck a dozen Indian Ocean nations on 26 December 2004. More than 300,000 people were killed or left missing as a result of the tragedy. The Australian Government played a key role in the disaster response overseas and in Australia. As part of a whole-of-government response to the crisis, eight Centrelink Social Workers were deployed to tsunami-affected areas for two weeks after the initial disaster to provide personal support to Australian victims and their families. This paper presents the service delivery framework adopted offshore and delineates the role undertaken by the social workers. Drawing on their practice experience, the paper examines some of the challenges, dilemmas, learnings and implications for future service delivery.     

The distribution of cook's d statistic

Cook (1977) proposed a diagnostic to quantify the impact of deleting an observation on the estimated regression coefficients of a General Linear Univariate Model (GLUM). Simulations of models with Gaussian response and predictors demonstrate that his suggestion of comparing the diagnostic to the median of the F for overall regression captures an erratically varying proportion of the values.

We describe the exact distribution of Cook's statistic for a GLUM with Gaussian predictors and response. We also present computational forms, simple approximations, and asymptotic results. A simulation supports the accuracy of the results. The methods allow accurate evaluation of a single value or the maximum value from a regression analysis. The approximations work well for a single value, but less well for the maximum. In contrast, the cut-point suggested by Cook provides widely varying tail probabilities. As with all diagnostics, the data analyst must use scientific judgment in deciding how to treat highlighted observations.     

Acquisitions: A directional policy matrix approach

There are few techniques available to aid corporate planners with strategic evaluation of potential acquisitions in a comprehensive and consistent manner. A substantial amount has been written about the general philosophy of acquisitions and, at the other end of the scale, about the detailed analysis of an individual company when it has been pulled under the financial microscope. This paper describes a technique that has been developed to systematically evaluate potential acquisitions with regard to their strategic qualitative considerations.     

Quasiextinction Probabilities as a Measure of Impact on Population Growth

A probabilistic language based on stochastic models of population growth is proposed for a standard language to be used in environmental assessment. Environmental impact on a population is measured by the probability of quasiextinction. Density-dependent and independent models are discussed. A review of one-dimensional stochastic population growth models, the implications of environmental autocorrelation, finite versus "infinite" time results, age-structured models, and Monte Carlo simulations are included. The finite time probability of quasiextinction is presented for the logistic model. The sensitivity of the result with respect to the mean growth rate and the amplitude of environmental fluctuations are examined. Stochastic models of population growth form a basis for formulating reasonable criteria for environmental impact estimates.