| Title |
Constrained Mortality Extrapolation to Old Age: An Empirical Assessment
|
|---|---|
| Published in |
European Journal of Population, July 2017
|
| DOI | 10.1007/s10680-017-9434-4 |
| Pubmed ID | |
| Authors |
Dalkhat M. Ediev |
| Abstract |
This paper aims to improve the accuracy of parametric extrapolations of the death rates into old age by constraining the extrapolation model on presumed life expectancy at old age. Such a task is particularly important in cases where the data quality at old age, in particular the age exaggeration, is not sufficient for reliable mortality estimates. Our tests are based on period data from the Human Mortality Database and the use of the Horiuchi-Coale and Mitra formulas for reducing the bias of life expectancy in the open age interval. We show that extrapolation accuracy is substantially improved when the extrapolation is constrained by either the empirical life expectancy or the Horiuchi-Coale or Mitra estimates. Unconstrained extrapolations and those constrained by conventional life table estimates of life expectancy in the open age interval show substantial biases and should be avoided. Combining extrapolation with life expectancy estimates which are robust to the effects of age exaggeration appears to be a valuable way of improving mortality estimation. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 25% |
| Germany | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 14 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 3 | 21% |
| Researcher | 3 | 21% |
| Lecturer | 1 | 7% |
| Student > Ph. D. Student | 1 | 7% |
| Student > Doctoral Student | 1 | 7% |
| Other | 2 | 14% |
| Unknown | 3 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Social Sciences | 6 | 43% |
| Mathematics | 2 | 14% |
| Agricultural and Biological Sciences | 1 | 7% |
| Business, Management and Accounting | 1 | 7% |
| Unknown | 4 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 July 2017.
All research outputs
#14,279,971
of 23,999,200 outputs
Outputs from European Journal of Population
#285
of 358 outputs
Outputs of similar age
#164,553
of 319,452 outputs
Outputs of similar age from European Journal of Population
#6
of 10 outputs
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