Parameter estimation for a discrete-response model with double rules of sample selection: A Bayesian approach

We present a Bayesian sampling approach to parameter estimation in a discrete-response model with double rules of selectivity, where the dependent variables contain two layers of binary choices and one ordered response. Our investigation is motivated by an empirical study using such a double-selection rule for three labor-market outcomes, namely labor force participation, employment and occupational skill level. Full information maximum likelihood (FIML) estimation often encounters convergence problems in numerical optimization. The contribution of our investigation is to present a sampling algorithm through a new reparameterization strategy. We conduct Monte Carlo simulation studies and find that the numerical optimization of FIML fails for more than half of the simulated samples. Our Bayesian method performs as well as FIML for the simulated samples where FIML works. Moreover, for the simulated samples where FIML fails, Bayesian works as well as it does for the simulated samples where FIML works. We apply the proposed sampling algorithm to the double-selection model of labor-force participation, employment and occupational skill level. We derive the 95% Bayesian credible intervals for marginal effects of the explanatory variable on the three labor-force outcomes. In particular, the marginal effects of mental health factors on these three outcomes are discussed.Bayesian sampling; conditional posterior; marginal effects; mental illness; reparameterization.

Simultaneity, Rationality and Price Determination in US Live Cattle

This paper develops a simultaneous rational expectations model of the US live cattle spot and futures markets. The issues addressed are first, the scarcity of such models of futures markets for non-storables, and second the semi-strong efficient markets hypothesis (EMH), on which recent research for this market has been inconclusive. The model contains functional relationships for short and long hedgers, net short speculators in futures and consumers. The results suggest first, that there is support for Working's hypotheses of selective and operational hedging, for short and long hedgers respectively, second that speculators may be noise traders or risk-loving, and third that beef is a normal good while corn is a complementary input. Timevarying volatility is represented as an EGARCH (p,q) process. Post-sample, this model does not significantly outperform the futures price in spot price forecasting, implying non-rejection of the EMH

The PULSAR Specialist Care protocol: a stepped-wedge cluster randomized control trial a training intervention for community mental health teams in recovery-oriented practice

Background: Recovery features strongly in Australian mental health policy; however, evidence is limited for the efficacy of recovery-oriented practice at the service level. This paper describes the Principles Unite Local Services Assisting Recovery (PULSAR) Specialist Care trial protocol for a recovery-oriented practice training intervention delivered to specialist mental health services staff. The primary aim is to evaluate whether adult consumers accessing services where staff have received the intervention report superior recovery outcomes compared to adult consumers accessing services where staff have not yet received the intervention. A qualitative sub-study aims to examine staff and consumer views on implementing recovery-oriented practice. A process evaluation sub-study aims to articulate important explanatory variables affecting the interventions rollout and outcomes. Methods: The mixed methods design incorporates a two-step stepped-wedge cluster randomized controlled trial (cRCT) examining cross-sectional data from three phases, and nested qualitative and process evaluation sub-studies. Participating specialist mental health care services in Melbourne, Victoria are divided into 14 clusters with half randomly allocated to receive the staff training in year one and half in year two. Research participants are consumers aged 18-75 years who attended the cluster within a previous three-month period either at baseline, 12 (step 1) or 24 months (step 2). In the two nested sub-studies, participation extends to cluster staff. The primary outcome is the Questionnaire about the Process of Recovery collected from 756 consumers (252 each at baseline, step 1, step 2). Secondary and other outcomes measuring well-being, service satisfaction and health economic impact are collected from a subset of 252 consumers (63 at baseline; 126 at step 1; 63 at step 2) via interviews. Interview based longitudinal data are also collected 12 months apart from 88 consumers with a psychotic disorder diagnosis (44 at baseline, step 1; 44 at step 1, step 2). cRCT data will be analyzed using multilevel mixed-effects modelling to account for clustering and some repeated measures, supplemented by thematic analysis of qualitative interview data. The process evaluation will draw on qualitative, quantitative and documentary data. Discussion: Findings will provide an evidence-base for the continued transformation of Australian mental health service frameworks toward recovery

Economic growth and contraction and their impact on the poor

This paper considers the relationship between growth in real per capita GDP and the growth in real per capita GDP of the poorest 20% of a country. It uses the data set compiled by Dollar and Kraay (2002), but come to very different conclusions. We argue that if the purpose is to answer questions about the impact of growth on the poor, models are best estimated in growth rates. The empirical results show that growth's impact on the poor occurs in two episodes. First, in periods of sustained economic slowdown (negative growth over a period of at least 5 years), the poor clearly suffer more than the average. In contrast, where economies are growing, the poor do not benefit as much as the average. We also find that the poor benefit from growth less in periods of high inflation, and in countries with low average income

Economic Growth and Contraction and Their Impact on the Poor

This paper considers the relationship between growth in real per capita GDP and the growth in real per capita GDP of the poorest 20% of a country. It uses the data set compiled by Dollar and Kraay (2002), but come to very different conclusions. We argue that if the purpose is to answer questions about the impact of growth on the poor, models are best estimated in growth rates. The empirical results show that growth's impact on the poor occurs in two episodes. First, in periods of sustained economic slowdown (negative growth over a period of at least 5 years), the poor clearly suffer more than the average. In contrast, where economies are growing, the poor do not benefit as much as the average. We also find that the poor benefit from growth less in periods of high inflation, and in countries with low average income

Structural Unemployment in Australia

This paper examines whether structural unemployment increased in Australia over the last two decades. A simple regression model has been considered for testing the hypothesis of an increase in unemployment in several segments of the labour force over time. Six dimensions of the labour force namely, age, sex, region, duration of unemployment, occupation and industry have been taken into account. Analysis of the regression results reveals that the structural unemployment problem is substantial with respect to age, sex, duration of unemployment, occupation and industry. Regarding region the evidence for structural unemployment is not very strong