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SPEM SIGNED

Semi-Parametric Econometric Models: Health, Obesity and Patient Expenditures

Total Cost €

EC-Contrib. €

Partnership

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Outcomes and
results

SPEM project word cloud

Explore the words cloud of the SPEM project. It provides you a very rough idea of what is the project "SPEM" about.

australian retransformation gap obtain literature zero records simultaneously semiparametric positive medicare negative government examine framework linked adjustment empirical waves highlight exist preventing serves purposes accommodate longitudinal spem risk decision treating heavy differentiate estimate panel full meet prediction 2014 smoking children accurate informed estimates relationship econometric skewed parametric conditional data healthcare evaluation tailed childhood insurance 2004 mean filling effectiveness distributional obesity flexible

Project "SPEM" data sheet

The following table provides information about the project.

Coordinator	UNIVERSITY OF YORK Organization address address: HESLINGTON city: YORK NORTH YORKSHIRE postcode: YO10 5DD website: http://www.york.ac.uk contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.
Coordinator Country	United Kingdom [UK]
Total cost	183˙454 €
EC max contribution	183˙454 € (100%)
Programme	1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
Code Call	H2020-MSCA-IF-2016
Funding Scheme	MSCA-IF-EF-ST
Starting year	2018
Duration (year-month-day)	from 2018-01-01 to 2019-12-31

Partnership

Take a look of project's partnership.

#	participants	country	role	EC contrib. [€]
1	UNIVERSITY OF YORK UNIVERSITY OF YORK Organization address address: HESLINGTON city: YORK NORTH YORKSHIRE postcode: YO10 5DD website: http://www.york.ac.uk contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	UK (YORK NORTH YORKSHIRE)	coordinator	183˙454.00

Map

Project objective

Econometric modelling of healthcare costs serves many purposes: to obtain key parameters in cost-effectiveness analyses; to implement risk adjustment in insurance systems; and to examine the impact of risk factors such as smoking and obesity. Modelling healthcare costs is challenging because the cost data are typically non-negative, heavy tailed and highly skewed.

Filling the gap in the literature: SPEM will develop an ambitious research programme that simultaneously meet these conditions: (1) no need for retransformation of costs; (2) be able to estimate both the conditional mean and the whole distribution; (3) no need to differentiate zero costs from positive costs; (4) be less parametric and more flexible; and (5) be able to accommodate panel data. Such a method does not exist in the literature. Another highlight of SPEM is that the new method will be used for out-of-sample prediction and full distributional analysis which are typically not considered in the semiparametric framework.

Promoting more informed decision making: SPEM will produce accurate and robust estimates of the relationship between childhood obesity and healthcare costs, which are crucial in the design and evaluation of government programmes aimed at treating and preventing childhood obesity. This will be achieved through an empirical application. The Longitudinal Study of Australian Children (6 waves: 2004-2014) and linked records from Medicare will be used to investigate the relationship between childhood obesity and healthcare costs.

Publications

List of publications.
year	authors and title	journal	last update
2019	Rajan Sharma, Yuanyuan Gu, Kompal Sinha, Mona Aghdaee, Bonny Parkinson Mapping the Strengths and Difficulties Questionnaire onto the Child Health Utility 9D in a large study of children published pages: 2429-2441, ISSN: 0962-9343, DOI: 10.1007/s11136-019-02220-x	Quality of Life Research 28/9	2020-01-29

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The information about "SPEM" are provided by the European Opendata Portal: CORDIS opendata.