The Impact of Changes to the Unemployment Rate on Australian Disability Income Insurance Claim Incidence

Khemka, Gaurav; Roberts, Steven O.; Higgins, Timothy

doi:10.3390/risks5010017

Cited by 5 publications

(2 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A hurdle model was applied because (1) there were no truck accidents (i.e., outcomes) in a large proportion of the grids resulting in an outcome value of zero, and (2) the zero outcomes have exactly one source (a zero indicates that there were no trucks accidents) [ 21 , 22 ]. The hurdle model employed a logistic regression model for the incidence process, and a zero-truncated negative binomial regression model (with log link) for the prevalence process.…”

Section: Methodsmentioning

confidence: 99%

Truck and Multivehicle Truck Accidents with Injuries Near Colorado Oil and Gas Operations

Blair

Hughes

Allshouse

et al. 2018

IJERPH

View full text Add to dashboard Cite

Unconventional and conventional oil and gas (O&G) operations raise public health concerns, such as the potential impacts from trucking activity in communities that host these operations. In this work, we used two approaches to evaluate accidents in relation to O&G activities in the State of Colorado. First, we calculated the rate of truck accidents by computing the ratio of accident count and county population. When comparing counties with increased O&G operations to counties with less activity, we found that counties with more activity have greater rates of truck traffic accidents per capita (Rate Ratio = 1.07, p < 0.05, 95% CI: 1.01–1.13). Second, we laid a grid over the eleven counties of interest and counted, for each cell, the number of truck accidents, the number of multivehicle accidents with injuries, the number of homes, and the number of O&G wells. We then applied hurdle count models, using the accident counts as the outcomes and the number of homes and number of wells as independent variables. We found that both independent variables are significant predictors of truck accidents and multivehicle truck accidents. These accidents are of concern since they can have an impact on the people who live near O&G operations.

show abstract

Section: Methodsmentioning

confidence: 99%

Truck and Multivehicle Truck Accidents with Injuries Near Colorado Oil and Gas Operations

Blair

Hughes

Allshouse

et al. 2018

IJERPH

View full text Add to dashboard Cite

show abstract

“…The forecasting models and their extensions have been applied in the real world to overcome the complexity and uncertainty [36][37][38][39]. Grey theory is primarily concerned with ambiguous system models in which there is inadequate information to perform system link analysis, model creation, predictions, and judgments.…”

Section: Literature Reviewmentioning

confidence: 99%

Unemployment Rates Forecasting with Grey-Based Models in the Post-COVID-19 Period: A Case Study from Vietnam

et al. 2021

View full text Add to dashboard Cite

The Coronavirus (COVID-19) pandemic has had a significant impact on most countries’ social and economic perspectives worldwide. Unemployment has become a vital challenge for policymakers as a result of COVID-19′s negative impact. Because of the nonstationary and nonlinear nature of the dataset, researchers applied various time series models to forecast the unemployment rate. This study aims to ensure a better forecasting approach for predicting the unemployment rates with an uncertainty of insufficient knowledge and tiny data throughout Vietnam. The study proposes the Grey theory system-based GM (1,1), the Grey Verhulst Model (GVM), and the Autoregressive Integrated Moving Average (ARIMA) model that can more precisely predict unemployment rates. The model’s applications are shown using the Vietnamese unemployment rate at six different rural and urban areas with data sets from 2014–2019. The results indicate that the lower Mean Average Percentage Error (MAPE) values obtained with the GM (1,1) model at all regions for rural and urban areas (excluding Highlands Region in urban area) are extremely encouraging in comparison to other traditional methods. The accurate level of the ARIMA and GVM models follows the GM (1,1) model. The findings of this study show that the effects of the modeling assist policymakers in shaping future labor and economic policies. Furthermore, this study can contribute to the unemployment literature, providing future research directions in the unemployment problems.

show abstract

COVID-19 and Mental Health: Should We Expect an Increase in Disability?

Meagher¹

2021

Journal of Insurance Medicine

View full text Add to dashboard Cite

Disability due to mental health disorders has been increasing in many countries over the past years. The COVID-19 pandemic may worsen this trend because of 3 different, and at times overlapping, pathways. This article describes each pathway, and by drawing on the experience of previous coronavirus epidemics and recent recessions, attempts to estimate the likelihood that claims due to mental health disorders will increase.

show abstract

The Impact of Changes to the Unemployment Rate on Australian Disability Income Insurance Claim Incidence

Cited by 5 publications

References 11 publications

Truck and Multivehicle Truck Accidents with Injuries Near Colorado Oil and Gas Operations

Truck and Multivehicle Truck Accidents with Injuries Near Colorado Oil and Gas Operations

Unemployment Rates Forecasting with Grey-Based Models in the Post-COVID-19 Period: A Case Study from Vietnam

COVID-19 and Mental Health: Should We Expect an Increase in Disability?

Contact Info

Product

Resources

About