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Inference Procedures to Quantify the Efficiency–Equality Trade-Off in Health from Stated Preferences: A Case Study in Portugal

Overview of attention for article published in Applied Health Economics and Health Policy, April 2018
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Title
Inference Procedures to Quantify the Efficiency–Equality Trade-Off in Health from Stated Preferences: A Case Study in Portugal
Published in
Applied Health Economics and Health Policy, April 2018
DOI 10.1007/s40258-018-0394-6
Pubmed ID
Authors

Micaela Pinho, Anabela Botelho

Abstract

This article develops two inference procedures to calculate the inequality aversion and alpha parameters of a health-related social welfare function with constant elasticity (CES-HRSWF) using stated preferences. Based on the relative concept of inequality, a range of values were proposed for the trade-offs between improving total population health and reducing health inequalities. A self-administered questionnaire was used to collect data from a sample of 422 college students in Portugal. Respondents faced three hypothetical allocation scenarios where they needed to decide between two health programmes that assign different health gains to two anonymous sub-groups of the population and to two sub-groups identified by socioeconomic class. Combinations of the median response to these three questions were used to estimate the parameters of the CES-HRSWF. Findings suggest that the quantification of the efficiency-equality trade-off is not independent of the inference procedure used. Plausible values for the inequality aversion and for the alpha parameters were obtained ranging from 2.24 to 4.85 and from 0.5 to 0.58, respectively. Respondents revealed some aversion to health inequality. However, the extent of this aversion seems to be sensitive to (1) the identification of the groups by occupation status, (2) the size of the health gain, and (3) the inference procedure used.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 22%
Student > Ph. D. Student 3 13%
Librarian 1 4%
Student > Bachelor 1 4%
Professor 1 4%
Other 2 9%
Unknown 10 43%
Readers by discipline Count As %
Social Sciences 4 17%
Medicine and Dentistry 2 9%
Economics, Econometrics and Finance 2 9%
Biochemistry, Genetics and Molecular Biology 1 4%
Agricultural and Biological Sciences 1 4%
Other 3 13%
Unknown 10 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 20 April 2018.
All research outputs
#18,603,172
of 23,043,346 outputs
Outputs from Applied Health Economics and Health Policy
#616
of 785 outputs
Outputs of similar age
#253,649
of 326,937 outputs
Outputs of similar age from Applied Health Economics and Health Policy
#17
of 20 outputs
Altmetric has tracked 23,043,346 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 785 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.0. This one is in the 6th percentile – i.e., 6% of its peers scored the same or lower than it.
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We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.