Dr Giuseppe Moscelli
Giuseppe received both his undergraduate degree in Economics and Management of Institutions and Financial Markets (in 2004) and also his Master of Science in Finance (in 2007) from Luigi Bocconi University (Milan, Italy). He has worked in the investment banking industry as a front-office risk management analyst in the Capital Markets division of Lehman Brothers (London) in 2007-08, and then in 2009 he moved on to enrol into a PhD program in Econometrics and Empirical Economics at University of Rome Tor Vergata (second years classes and exams at EIEF in Rome). From October 2012 to December 2017, he has worked as a research fellow in the Health Policy team of the Centre for Health Economics of the University of York. Giuseppe was awarded his PhD in June 2015 from University of Rome Tor Vergata. In December 2017, he has joined the University of Surrey as a Lecturer in Economics.
I am an empirical economist, and my main areas of interest are health economics, labour economics, applied microeconometrics and causal inference. My research is focused on robust data analysis and estimation to provide policy makers the tools to decide which interventions can be beneficial to patients, workers and/or the general public. So far, my works have been published in the Journal of Health Economics, Regional Science & Urban Economics, and Social Science and Medicine. In health economics, I have investigated and I am interested in: the determinants of choice of provider of care, and in particular the effect of hospital quality on the choice of provider; the effect of patient choice and competition on healthcare outcomes; the effect of socio-economic status on access to healthcare, in particular waiting times; the effect of waiting times on patient's outcomes (e.g. mortality, readmissions). My research in this area has focused primarily on the English National Health Service case, but its results can be extended to a large part of mixed or Beveridge healthcare systems. In labour economics, I am interested in the effect of education on health, for parents and their children. In causal inference, I am particularly interested in the literature tackling endogeneity bias due to selection or self-selection mechanisms, including bias due to post-treatment selection. Some of the methodologies that I have used in my research include: instrumental variables, difference-in-difference designs, matching, principal stratification, choice models estimation based on revealed preferences, principal stratification, Monte Carlo simulations.
Some of my ongoing works-in-progress include:
- the association between objective hospital quality indicators, subjective quality indicators, and the choice of maternity clinics (joint with D. Avdic, I. Sriubaite, A. Pilny at the Monash Centre for Health Economics and the University of Duisburg-Essen); working paper is out!: https://cinch.uni-due.de/fileadmin/content/research/workingpaper/1803_CINCH_Series_Avdic.pdf
- the effect of Accident & Emergency departments' waiting times on patients' outcomes in the English NHS (work in progress, joint with L. Anselmi, M. Sutton, Y.S. Lau, A. Turner at the University of Manchester);
- the effect of hospital closures for elective patients' outcomes (work in progress, joint with H. Gravelle and L. Siciliani at the University of York);
- the association between the utilization of contraceptive methods and family planning (work in progress, joint with A. Mirelman and M. Suhrcke at the University of York).
Quantitative Methods (ECO1015) - 1st year UG module;
Labour Economics (ECO3016) - 3rd year UG module
and waiting times, (b) differences in choices between patients in urban and rural locations, (c) the relationship
between hospitals' elasticities of demand to quality and the number of local rivals, and how these changed
after relaxation of constraints on hospital choice in England in 2006. Using a data set on over 500,000 elective
hip replacement patients over the period 2002 to 2013 we find that patients became more likely to travel to a
provider with higher quality or lower waiting times, the proportion of patients bypassing their nearest provider
increased from 25% to almost 50%, and hospital elasticity of demand with respect to own quality increased.
By 2013 average hospital demand elasticity with respect to readmission rates and waiting times were ?0.2
and ?0.04. Providers facing more rivals had demand that was more elastic with respect to quality and waiting
times. Patients from rural areas have smaller disutility from distance.
Previous studies of quality and choice of hospitals have used crude measures of quality such as
mortality and readmission rates rather than measures of the health gain from specific treatments. We
estimate multinomial logit models of hospital choice by patients undergoing hip replacement surgery
in the English NHS to test whether hospital demand responds to quality as measured by detailed patient
reports of health before and after hip replacement. We find that a one standard deviation increase in
average health gain increases demand by up to 10%. The more traditional measures of hospital quality
are less important in determining hospital choice.
bypass, Social Science and Medicine 161 pp. 151-159 Elsevier
key policy concern is that long waiting times may worsen health outcomes: when patients receive
treatment, their health condition may have deteriorated and health gains reduced. This study investigates
whether patients in need of coronary bypass with longer waiting times are associated with
poorer health outcomes in the English National Health Service over 2000e2010. Exploiting information
from the Hospital Episode Statistics (HES), we measure health outcomes with in-hospital mortality and
28-day emergency readmission following discharge. Our results, obtained combining hospital fixed effects
and instrumental variable methods, find no evidence of waiting times being associated with higher
in-hospital mortality and weak association between waiting times and emergency readmission following
a surgery. The results inform the debate on the relative merits of different types of rationing in healthcare
systems. They are to some extent supportive of waiting times as an acceptable rationing mechanism,
although further research is required to explore whether long waiting times affect other aspects of individuals?
investigate the effect of hospital competition on dimensions of efficiency including indicators of
resource management (admissions per bed, bed occupancy rate, proportion of day cases, cancelled
elective operations, proportion of untouched meals) and costs (cleaning services costs, laundry and
linen costs, reference cost index for overall and elective activity). We employ a quasi difference-indifference
approach and estimate seemingly unrelated regressions and unconditional quantile
regressions with data on hospital trusts from 2002/03 to 2010/11. Our findings suggest that
increased competition had mixed effects on efficiency. An additional equivalent rival increased
admissions per bed and the proportion of day cases by 1.1 and 3.8 percentage points, and reduced
the proportion of untouched meals by 3.5 percentage points, but it also increased the number of
cancelled elective operations by 2.6%. Unconditional quantile regression results indicate that
hospitals with low efficiency, as measured by fewer admissions per bed and a smaller proportion of
day cases, are more responsive to competition.