ORCID Profile
0000-0002-4232-2783
Current Organisation
University of Oxford
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Publisher: Springer Science and Business Media LLC
Date: 12-11-2015
DOI: 10.1038/SREP16509
Abstract: We investigated the role of common genetic variation in educational attainment and household income. We used data from 5,458 participants of the National Child Development Study to estimate: 1) the associations of rs9320913, rs11584700 and rs4851266 and socioeconomic position and educational phenotypes and 2) the univariate chip-heritability of each phenotype and the genetic correlation between each phenotype and educational attainment at age 16. The three SNPs were associated with most measures of educational attainment. Common genetic variation contributed to 6 of 14 socioeconomic background phenotypes and 17 of 29 educational phenotypes. We found evidence of genetic correlations between educational attainment at age 16 and 4 of 14 social background and 8 of 28 educational phenotypes. This suggests common genetic variation contributes both to differences in educational attainment and its relationship with other phenotypes. However, we remain cautious that cryptic population structure, assortative mating and dynastic effects may influence these associations.
Publisher: Elsevier BV
Date: 04-2010
Publisher: Walter de Gruyter GmbH
Date: 13-01-2008
Abstract: Waiting times have been a central concern in the English NHS, where care is provided free at the point of delivery and is rationed by waiting time. Pro-market reforms introduced in the NHS in the 1990s were not accompanied by large drops in waiting times. As a result, the English government in 2000 adopted the use of an aggressive policy of targets coupled with the publication of waiting times data at the hospital level and strong sanctions for poor performing hospital managers. This regime has been dubbed targets and terror. We estimate the effect of the English target regime for waiting times for hospital care after 2001 by a comparative analysis with Scotland, a neighbouring country with the same healthcare system that did not adopt the target regime. We estimate difference-in-differences models of the proportion of people on the waiting list who waited over 6, 9 and 12 months. Comparisons between England and Scotland are sensitive to whether published or unpublished data are used but, regardless of the data source, the targets and terror regime in England lowered the proportion of people waiting for elective treatment relative to Scotland.
Publisher: Royal College of General Practitioners
Date: 04-2013
Publisher: MDPI AG
Date: 13-11-2018
DOI: 10.3390/ECONOMETRICS6040044
Abstract: A standard test for weak instruments compares the first-stage F-statistic to a table of critical values obtained by Stock and Yogo (2005) using simulations. We derive a closed-form solution for the expectation from which these critical values are derived, as well as present some second-order asymptotic approximations that may be of value in the presence of multiple endogenous regressors. Inspection of this new result provides insights not available from simulation, and will allow software implementations to be generalised and improved. Finally, we explore the calculation of p-values for the first-stage F-statistic weak instruments test.
Publisher: Elsevier BV
Date: 05-2014
Publisher: Springer Science and Business Media LLC
Date: 2011
Publisher: Wiley
Date: 2003
DOI: 10.1002/HEC.830
Abstract: Many health-care systems allocate funding according to measures of need. The utilisation approach for measuring need rests on the assumptions that use of health care is determined by demand and supply and that need is an important element of demand. By estimating utilisation models which allow for supply it is possible to isolate the socio-economic and health characteristics which affect demand. A subset of these variables can then be identified by a combination of judgement and further analysis as needs variables to inform funding allocations. We estimate utilisation models using newly assembled data on admissions to acute hospitals, measures of supply, morbidity and socio-economic characteristics for 8414 small geographical areas in England. We make a number of methodological innovations including deriving additional measures of specific morbidities at small area level from in idual level survey data. We compare models with different specifications for the effect of waiting times and provider characteristics, with total, planned and unplanned hospital admissions, and estimated at small area (ward) and primary care organisation (general practice) level. After allowing for waiting times, distance, capacity and the availability of private health care, measures of mortality, self-reported morbidity, low education and low income increase the use of health care. We find evidence of horizontal inequity with respect to ethnicity and employment and suggest a method for reducing its effects when deriving a needs-based allocation formula.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Frank Windmeijer.