Issues in spatial microsimulation estimation: a case study of child poverty

Spatial microsimulation techniques have become an increasingly popular way to fulfil the need for generating small area data estimates. Nevertheless, this technique poses numerous methodological challenges, including those that relate to fundamental differences between the multiple data sources which spatial microsimulation techniques seek to combine. Using two different databases simultaneously to produce estimates of population characteristics may come up against problems related to different distributions of key variables within the two databases. Such differences can make it difficult to adequately validate small area estimates, as it can be hard to assess whether differences between synthetic and original data are due to failures or inaccuracies within the estimation procedure, or simply to the differences within the underlying data. This study presents a case study of this problem using a very important small area estimate – child poverty rates. We compare how income distributions for children are different in two Australian databases being combined within a spatial microsimulation model. We then assess the extent to which this affects our estimates of child poverty, and gauge its impact on the apparent validity of these synthetic small area poverty rates.Microsimulation, Spatial, Inequality

The Welfare Myth: Disentangling the Long-Term Effects of Poverty and Welfare Receipt for Young Single Mothers

This study investigates the effects of receiving welfare as a young woman on long-term economic and marital outcomes. Specifically, we examine if there are differences between young, single mothers who receive welfare and young, single mothers who are poor but do not receive welfare. Using the 1968-1997 Panel Study of Income Dynamics, our findings suggest those who receive welfare for an extended period as young adults have the same pre-transfer income over a 10 to 20 year period as those who are poor but do not receive welfare as young adults. While we found some differences between the two groups in income levels and the likelihood of having relatively low income when control variables were not included in our models, once appropriate controls were used, these differences became statistically insignificant. The only statistically significant difference found between the two groups in our 10, 15, and 20 year models was the likelihood of being married in year 15. Our results indicate that it is income level as a young adult, as well as such factors as the unemployment rate in the area of residence, but not welfare receipt, that affect long-term income and marital outcomes

Work and Economic Outcomes After Welfare

Using data from the 1969 to 1993 Panel Study of Income Dynamics, this article examines a number of models to determine the characteristics of AFDC recipients who fare well economically after they initially leave the welfare system. The study includes analyses of income levels, time spent employed and not employed, and time spent below the poverty line. Hypotheses regarding state welfare payments, area economic conditions, human capital and time spent receiving welfare are examined. The findings indicate that area employment conditions and the ability to quickly find work greatly affect the likelihood of faring well economically after welfare. We found that time spent receiving welfare had some small negative effects on post-welfare economic outcomes. However, former welfare recipients living in states with more generous welfare payments are as likely to work, to not use welfare, and are generally as well off as those living in states with less generous welfare payments. These results indicate that high welfare benefit levels may not be a disincentive to work. The findings also indicate that women who have little job experience, who lack education, and who have many or more children after AFDC, fare economically worse than others

Marketing and Branding Implications of a Corporate Service Program: The Case of Women’s Group Mentoring

Corporate programs are often voluntary and sometimes struggle to attract sufficient participants. Mentoring programs tend to follow a mentor-mentee format. However, one Australian university offers female staff a group-mentoring model. Despite the positive ratings of this mentoring model, there appeared to be negative perceptions of the program. To understand why these perceptions were negative, exploratory research was undertaken. Quantitative and qualitative research was triangulated to improve understanding of the data. Ultimately, recommendations for branding of the product were developed. Numerous incorrect perceptions existed, and one of the biggest hindrances for participation in the program was a perceived lack of time and confusion about the nature of the program

Old, single and poor

This paper uses microdata and NATSEM\u27s microsimulation models to examine the spatial distribution of poverty among older single people and to test the likely impact upon national and small area poverty rates of an increase in the single age pension rate. In recent months in Australia there has been extended debate about whether the age pension is sufficiently high to allow older Australians to attain an acceptable standard of living. This paper uses microdata and NATSEM\u27s microsimulation models to examine the spatial distribution of poverty among older single people and to test the likely impact upon national and small area poverty rates of an increase in the single age pension rate. The paper provides an illustration of the usefulness of microsimulation models to policy makers. Changes in a country\u27s tax and transfer systems can have a large effect on incomes, and can be targeted towards increasing incomes for the poor, thus reducing poverty rates. However, governments need an estimate of the extent to which a proposed policy change is likely to affect poverty rates, in order to be able to compare different proposals. Microsimulation models allow this comparison of proposed policies and can provide governments with an appreciation of how much a new policy is likely to cost; how many and what types of low income people will benefit; and the extent of any consequent reduction in the poverty rate. Until recently, microsimulation models have been able to estimate the effects of such changes only at a national or very broad regional level. NATSEM has now linked its tax/transfer microsimulation model (STINMOD) to spatially disaggregated census data, producing a spatial microsimulation model which can be used to identify the neighbourhood effects of policy changes for small areas

Trematodes of the Great Barrier Reef, Australia: emerging patterns of diversity and richness in coral reef fishes

The Great Barrier Reef holds the richest array of marine life found anywhere in Australia, including a diverse and fascinating parasite fauna. Members of one group, the trematodes, occur as sexually mature adult worms in almost all Great Barrier Reef bony fish species. Although the first reports of these parasites were made 100 years ago, the fauna has been studied systematically for only the last 25 years. When the fauna was last reviewed in 1994 there were 94 species known from the Great Barrier Reef and it was predicted that there might be 2,270 in total. There are now 326 species reported for the region, suggesting that we are in a much improved position to make an accurate prediction of true trematode richness. Here we review the current state of knowledge of the fauna and the ways in which our understanding of this fascinating group is changing. Our best estimate of the true richness is now a range, 1,100–1,800 species. However there remains considerable scope for even these figures to be incorrect given that fewer than one-third of the fish species of the region have been examined for trematodes. Our goal is a comprehensive characterisation of this fauna, and we outline what work needs to be done to achieve this and discuss whether this goal is practically achievable or philosophically justifiable

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570