Estimation of Disability Transition Probabilities in Australia II: Implementation

Hariyanto, Evan A.; Dickson, David; Pitt, David

doi:10.1017/s174849951300016x

Cited by 19 publications

(29 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We should bear in mind that quantifying the value of change in biometric assumptions is no easy task, given that obtaining timely and accurate estimates of mortality, transition and incidence rates is highly complex for technical reasons [84][85][86][87][88]. In many countries, the lack of biometric data could make it impossible to obtain regular representative estimates of functional status transition rates.…”

Section: The Income Statement: Exploring the Reasons For The Change Imentioning

confidence: 99%

“…To give a couple of examples, data obtained from [94] for the US indicate that the amount of life expectancy likely to be spent in states of dependence will average 3.22 years, i.e., 21.11% of remaining life expectancy (15.26 years at Age 65). If we use data from [85,86] for Australia, the figures would be different: for pensioners at Age 65, the percentage of life expectancy likely to be spent in states of dependence would average 8.17 years, i.e., 42.99% of remaining life expectancy (18.99 years). Table 3 also shows that the expected number of years allocated to the possible range of health states depends on the starting status by age.…”

Section: The Swedish Abs For An Ndc Scheme Combining Retirement and Lmentioning

confidence: 99%

See 1 more Smart Citation

Social Insurance Accounting for a Notional Defined Contribution Scheme Combining Retirement and Long-Term Care Benefits

2018

View full text Add to dashboard Cite

This paper develops a social insurance accounting model for a notional defined contribution (NDC) scheme combining retirement and long-term care (LTC) contingencies. The procedure relies on standard double-entry bookkeeping and enables us to compile a "Swedish" type actuarial balance sheet (ABS) following a framework equivalent to an open group approach. This methodology is suitable for reporting the system's solvency status and can show periodical changes in the system's financial position by means of an income statement. The information underpinning the actuarial valuation is based on events and transactions that are verifiable at the valuation date, without considering expected future trends. The paper also contains an illustrative example to make it easier for policymakers to understand the main advantages and difficulties of our proposal. The policy conclusions stress the need to properly report social insurance benefits to enhance transparency and sustainability and to improve decision-making because it is in the public interest to do so.

show abstract

Section: The Income Statement: Exploring the Reasons For The Change Imentioning

confidence: 99%

Section: The Swedish Abs For An Ndc Scheme Combining Retirement and Lmentioning

confidence: 99%

Social Insurance Accounting for a Notional Defined Contribution Scheme Combining Retirement and Long-Term Care Benefits

2018

View full text Add to dashboard Cite

show abstract

“…(a) Scenario 1 comprises a numerical example performed using data from Hariyanto et al (2014aHariyanto et al ( , 2014b for Australia. Given that their papers do not provide all the probabilities by age that we need to perform our numerical example, a cubic smoothing spline 14 using R software has been fitted to the data in order to obtain them.…”

Section: Numerical Illustration Based On Data From Australia and The Usmentioning

confidence: 99%

“…The data used to perform this numerical example were obtained from the papers by Hariyanto et al (2014aHariyanto et al ( , 2014b. Their model provides five health statuses as shown in Figure 1: one healthy and four dependent (with core activity limitation in their terminology).…”

Section: ) Scenario 1 Based On Biometric Assumptions For Australiamentioning

confidence: 99%

“…Section 3 shows the results obtained for two numerical examples representative of the methodology seen in the previous section. It is divided into two parts: (a) the numerical outcomes for Australia resulting from using data from Hariyanto et al (2014aHariyanto et al ( , 2014b, and (b) the numerical results for the US using data obtained from Robinson's (1996) care transition model (CTM). In both parts we also look at what might happen if the annuitant's initial heath state is not able when they become entitled to benefits.…”

Section: -Introductionmentioning

confidence: 99%

See 1 more Smart Citation

How Do Unisex Life Care Annuities Embedded in a Pay-As-You-Go Retirement System Affect Gender Redistribution?

Vidal‐Meliá

Ventura-Marco

Pla-Porcel³

2017

SSRN Journal

View full text Add to dashboard Cite

This paper aims to assess gender redistribution when using unisex conversion factors to compute the initial benefit of life care annuities (LCAs) embedded in a pay-as-you-go (PAYG) pension system. We use a method based on actuarial factors to disentangle the hidden redistribution of LCAs with graded benefits. The value of the actuarial factor relies on a multistate framework in which transitions are modeled from the initial health state to the absorbing state. According to our calculations for Australia and the US, the amount of gender redistribution is by no means irrelevant. In spite of the very different biometric data, the results are surprisingly similar for both countries. Risk equalization based on the "equal treatment" of men and women may not be fair, given that age, gender and health state are very significant risk factors in computing the initial benefit in a system covering retirement and long-term care.

show abstract

Analyzing the demographic coherence of selected US, Australian and Chinese biometric data sets used to price long-term care insurance and life care annuities

Vidal-Meliá,

Ventura-Marco,

Garvey

2023

Qual Quant

View full text Add to dashboard Cite

This paper examines the implicit healthy life expectancy used for actuarial calculations in some selected biometric data sets from the US, Australia and China. We are interested in checking the demographic/epidemiological coherence of these data sets because this health indicator is rarely presented when authors build their biometric data sets, nor when they are used to calculate long-term care insurance (LTCI) and life care annuity (LCAs) premiums, nor when they are employed in research articles to estimate the future demand for LTC services. We follow a methodology based on multistate life table methods that enables us to obtain a life expectancy matrix for individuals on the basis of their initial health state. We also present some additional indicators of longevity, mortality and morbidity, these being the median age at death, the interquartile range, the weighted modal age at death, the mortality ratio and the implicit LTC prevalence rates broken down by health state. We find several weaknesses that highlight the difficulty involved in building the biometric data sets needed to make an actuarially fair valuation of the premiums for LTCI and LCAs. We also verify the existence of the so-called “male–female health-survival paradox”. From the perspective of a potential purchaser of this type of insurance products, disclosing and explaining the summary measures of health and longevity would make it easier for them to understand the need to protect themselves against the cost of possible LTC services and also make the computation of the premiums more transparent.

show abstract

Estimation of Disability Transition Probabilities in Australia II: Implementation

Cited by 19 publications

References 13 publications

Social Insurance Accounting for a Notional Defined Contribution Scheme Combining Retirement and Long-Term Care Benefits

Social Insurance Accounting for a Notional Defined Contribution Scheme Combining Retirement and Long-Term Care Benefits

How Do Unisex Life Care Annuities Embedded in a Pay-As-You-Go Retirement System Affect Gender Redistribution?

Analyzing the demographic coherence of selected US, Australian and Chinese biometric data sets used to price long-term care insurance and life care annuities

Contact Info

Product

Resources

About