Thesis Thursday: Edward Webb

On the third Thursday of every month, we speak to a recent graduate about their thesis and their studies. This month’s guest is Dr Edward Webb who graduated with a PhD from the University of Copenhagen. If you would like to suggest a candidate for an upcoming Thesis Thursday, get in touch.

Title
Attention and perception in decision-making and interactions
Supervisors
Alexander Sebald, Peter Norman Sørensen
Repository link
http://www.econ.ku.dk/forskning/Publikationer/ph.d_serie_2007-/Ph.D.181.pdf

Attention and perception aren’t things we often talk about in health economics. Why are they important?

There’s been a lot of work done on attention and perception in economics recently, which I think is a great development. They are really vital topics since unless you know how people perceive the information available to them, and what aspects of their environment are most likely to command their attention, it’s difficult to forecast their behaviour.

I think attention and perception will become more widely talked about in health in future, as there’s many cases in which they have a lot of relevance. For example, you might want to know whether rare symptoms grab doctors’ attention because they’re unusual, or whether they don’t notice them because they’re not expecting them. (There’s a great study by Drew, Vo and Wolfe where radiologists looking at CT scans of the chest failed to notice a picture of a gorilla embedded in them by the experimenters.)

Or if you’re planning some dietary intervention, you might want to take into account how unhealthy food such as pizza and chips attracts people’s attention much more than healthy food, and to look at why this is the case.

What can the new theoretical frameworks described in your thesis tell us about individual behaviour?

Most of the literature in psychology is about how individuals behave. I tried a lot in my thesis to move beyond studying individual decision making to look at how the effects of attention and perception change in different economic environments, as this can often be counter-intuitive.

As an example, in one of the chapters of my thesis I explore the effects of individuals having limited ability to tell the quality of different products apart. It turns out that the effects on a market can be radically different depending on whether there are fixed or marginal costs of quality.

I was also very interested in looking at how individuals with limited or biased attention interact with profit maximising firms. There’s an expectation that companies will rip people off and exploit them, and certainly, that can happen, but I was able to show that it’s not necessarily the case. The case of individuals having limited ability to tell products’ quality apart which I mentioned above is a good example. When firms rely on product differentiation to earn profits, they’re actually harmed by people with this limitation, rather than exploiting them.

Did you find yourself reaching beyond the economics literature for guidance, either in the subject matter or the techniques that you used?

Yes, I read quite a lot outside the standard economics literature during my thesis. Behavioural and experimental economics more or less sits on the boundary between economics and psychology, so it felt very natural to seek guidance from other disciplines. This was especially the case for the eye-tracking experiment that I carried out with the help of my co-authors Andreas Gotfredsen, Carsten S. Nielsen and Alexander Sebald. I needed to learn quite a bit about psychological work on visual attention.

I like that economics is as much a set of analytic tools as a subject area, which gives it the advantage of being able to take on nontraditional topics.

You studied in Denmark, yet your thesis is written in English. Did this raise any additional challenges in completing your PhD?

Danish people speak better English than what I can! Language really wasn’t a problem at all at work, since English is very much the language of academia. Seminars were in English, PhD students and a lot of masters students wrote their theses in English and nearly all postgraduate and some undergraduate teaching was in English. I did feel quite privileged to have the advantage of being a native speaker of the language, and appreciative that most of my colleagues were fine with working in a second language. That’s why I was always very willing to help people out with proofreading English. I only hope I didn’t make too many mistakes!

On the social side, you can get away with living in Denmark without speaking Danish, and many people do. Indeed, I probably wouldn’t have made the effort of becoming a (moderate) Danish speaker if my partner wasn’t Danish.

Copenhagen, and Denmark in general, is a fantastic place to live and work, and I’d urge anyone who is thinking about moving there not to be put off by the language barrier.

How did your experiences during your PhD contribute to your decision to work in the field of health economics?

The question makes it sound like I had a coherent plan! In reality, I’m terrible about thinking about the long term. (I must be a natural Keynesian.) I ended up moving back to the UK after I graduated ironically because of my Danish partner, as she had found a job here. She also works in health, as a medical physicist and cancer researcher at Leeds. I applied for economics jobs in the area and was over the moon to secure a place at the Academic Unit of Health Economics at Leeds.

It’s a little more applied and hands-on than what I was working on before, which is great. I came into economics because I was interested in finding out how people act and interact, and so it’s fantastic to have the opportunity now to work principally with discrete choice experiments, trying to work out patients’ and clinicians’ preferences.

Since I started at Leeds a few months ago I’ve really enjoyed my time. The environment is very stimulating and all my colleagues are extremely friendly and easy going and are always willing to help out or discuss an interesting new idea.

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Thesis Thursday: Ayesha Ali

On the third Thursday of every month, we speak to a recent graduate about their thesis and their studies. This month’s guest is Dr Ayesha Ali who graduated with a PhD from Lancaster University. If you would like to suggest a candidate for an upcoming Thesis Thursday, get in touch.

Title
Essays on health economics: trans fat policies, commuting, physical activity, and body mass index in the US
Supervisors
Colin Green, Bruce Hollingsworth
Repository link
http://www.research.lancs.ac.uk/portal/en/publications/-(182eadeb-a873-4d45-93bc-a987899c6587).html

What drew you to this particular topic and made you want to dedicate your PhD to it?

I’ve always been very fascinated about how people make decisions when it comes to health-related behaviors. My Mom was a doctor, so health has always been a main driver in what our family ate and what sort of values my parents emphasized. Growing up, I think we were always kind of “the weird family” in the neighborhood and in our extended family, because we often put health before cultural norms (i.e. changing traditional recipes to be healthier, avoiding all of those colorful and fun children’s cereals and candies, etc.), so I’ve been very aware and very curious about what drives health-related choices for different people. I’ve also lived in a number of very different communities, where norms about behaviors related to health varied significantly from place to place, and that variation has always been something that I’ve sort of observed and wondered about as well. So, I think these observations are what drew me to economics, as a way of understanding choices. My thesis work was somewhat of an attempt to crack the surface.

I don’t think I got the chance in my thesis to dig as deeply into the issue where health behaviors and culture meet as I had wanted, but I was lucky to get to use some of the types of data and some of the econometric tools that will come in handy as I continue to explore this area.

Your study focussed on US data, but you studied at a UK university. Was this a help or a hindrance?

I think it was definitely a challenge to work with non-UK data while studying at a UK University; for example, I didn’t find certain types of support (in terms of local workshops or having other colleagues using the same data) or familiarity that was often easily available to someone using UK data. However, my supervisors were very supportive of me and there were students in my cohort using other non-UK data so I was not alone in that regard.

One challenge that I had was that I couldn’t just ask someone who uses the data, but instead had to spend a bit of time trying to understand how other researchers in the literature used the data and then try to figure out whether or not their assumptions and ways of using the data were applicable to my work. I spent a lot of time reading data documentation files — both of my datasets (NHANES and ATUS) have really good online resources that I’m now very familiar with! I think that a lot of this being “on my own” with the data helped me to develop a feeling of confidence that I may not have had otherwise. I’m somewhat prone to second-guessing myself, so being able to learn to have confidence in my work was really valuable.

So, although challenging, overall I would say it was definitely more of a help than a hindrance.

Methodologically, what was the most challenging aspect of the research?

In my third chapter I use time use data, a two-part model, and a recursive bivariate probit model to estimate physical activity participation and duration decisions given an individual’s commuting time, with an instrument for commuting. There are some conflicting ideas on how best to use time-use data in the literature (see: Franzis and Stewart, 2010; Gershuny, 2012; Stewart, 2013) and few examples of instruments for commuting (see: Baum-Snow, 2007; Gimenez-Nadal and Molina, 2011).

I received a lot of different feedback on the best estimation approach to use. I wanted to estimate participation and intensity elasticities for individuals who do physical activity on a given day. There are a number of ways to deal with these two questions separately or simultaneously and also to deal with the large number of zeros in the data (i.e. individuals who did not participate in physical activity). At one point, I remember that I thought I had everything figured out with this chapter; and then following a conference presentation of this work, one commenter was dead set that I should be using a switching model. I hadn’t considered that approach and wasn’t familiar with it at all, so I had to go look it up, figure out what it was and whether or not it worked with what I was doing. So, just figuring out the best way to deal with my data and with the questions I was asking in this third chapter were probably the most challenging part of the thesis for me.

If you could have a decision maker implement one policy change supported by your work, what would it be?

If I could ideally have policy makers do one thing that is supported by my work, I think it would actually be a rather general thing, not related to one specific policy, but sort of related to the entire approach of policy-making. I would want policy makers to consider the groups they are targeting with more care. For example, my third chapter looks at time use among obese individuals and healthier-weight individuals and finds that many decisions, such as the decision of where to live and work, are often driven by different factors in these different groups. In general, my work suggests that different groups may be driven by different motivating factors and if we don’t understand what these are, policies might not successfully reach those who could most benefit. That being said, this probably isn’t as easy as it sounds, as there are a lot of political influences on how policy decisions are made.

If you had to do it all again (perish the thought), is there anything you would have done differently?

I think overall, I’m really happy with my experience; I had some good resources and Lancaster was a great environment for me. My PhD cohort was close-knit and faculty in my department were very approachable and supportive. If anyone is interested, I also found McCloskey’s Economical Writing and Thomson’s Guide for the Young Economist to be really helpful at various stages of the PhD.

If I could have changed one thing though, it was how I dealt with insecurity. Even in such a supportive environment, the competitive nature of academia can contribute to feelings of insecurity; I worked hard to recognize my own insecurities and fight through them, but I didn’t always succeed. So, if I could do something differently, I would like to have been less afraid to own up to not knowing something and to just keep asking questions until I understood.

I really enjoyed having the chance to talk with you about my experiences and motivation. And I hope that if anyone can find my experiences useful to them at their stage of the process, they do. Thanks again for inviting me.

Chris Sampson’s journal round-up for 16th January 2017

Every Monday our authors provide a round-up of some of the most recently published peer reviewed articles from the field. We don’t cover everything, or even what’s most important – just a few papers that have interested the author. Visit our Resources page for links to more journals or follow the HealthEconBot. If you’d like to write one of our weekly journal round-ups, get in touch.

Competition and quality indicators in the health care sector: empirical evidence from the Dutch hospital sector. The European Journal of Health Economics [PubMed] Published 3rd January 2017

In case you weren’t already convinced, this paper presents more evidence to support the notion that (non-price) competition between health care providers is good for quality. The Dutch system is based on compulsory insurance and information on quality of hospital care is made public. One feature of the Dutch health system is that – for many elective hospital services – prices are set following a negotiation between insurers and hospitals. This makes the setting of the study a bit different to some of the European evidence considered to date, because there is scope for competition on price. The study looks at claims data for 3 diagnosis groups – cataract, adenoid/tonsils and bladder tumor – between 2008 and 2011. The authors’ approach to measuring competition is a bit more sophisticated than some other studies’ and is based on actual market share. A variety of quality indicators are used for the 3 diagnosis groups relating mainly to the process of care (rather than health outcomes). Fixed and random effects linear regression models are used to estimate the impact of market share upon quality. Casemix was only controlled for in relation to the proportion of people over 65 and the proportion of women. Where a relationship was found, it tended to be in favour of lower market share (i.e. greater competition) being associated with higher quality. For cataract and for bladder tumor there was a ‘significant’ effect. So in this setting at least, competition seems to be good news for quality. But the effect sizes are neither huge nor certain. A look at each of the quality indicators separately showed plenty of ‘non-significant’ relationships in both directions. While a novelty of this study is the liberalised pricing context, the authors find that there is no relationship between price and quality scores. So even if we believe the competition-favouring results, we needn’t abandon the ‘non-price competition only’ mantra.

Cost-effectiveness thresholds in global health: taking a multisectoral perspective. Value in Health Published 3rd January 2017

We all know health care is not the only – and probably not even the most important – determinant of health. We call ourselves health economists, but most of us are simply health care economists. Rarely do we look beyond the domain of health care. If our goal as researchers is to help improve population health, then we should probably be allocating more of our mental resource beyond health care. The same goes for public spending. Publicly provided education might improve health in a way that the health service would be willing to fund. Likewise, health care might improve educational attainment. This study considers resource allocation decisions using the familiar ‘bookshelf approach’, but goes beyond the unisectoral perspective. The authors discuss a two-sector world of health and education, and demonstrate the ways in which there may be overlaps in costs and outcomes. In short, there are likely to be situations in which the optimal multisectoral decision would be for individual sectors to increase their threshold in order to incorporate the spillover benefits of an intervention in another sector. The authors acknowledge that – in a perfect world – a social-welfare-maximising government would have sufficient information to allocate resources earmarked for specific purposes (e.g. health improvement) across sectors. But this doesn’t happen. Instead the authors propose the use of a cofinancing mechanism, whereby funds would be transferred between sectors as needed. The paper provides an interesting and thought-provoking discussion, and the idea of transferring funds between sectors seems sensible. Personally I think the problem is slightly misspecified. I don’t believe other sectors face thresholds in the same way, because (generally speaking) they do not employ cost-effectiveness analysis. And I’m not sure they should. I’m convinced that for health we need to deviate from welfarism, but I’m not convinced of it for other sectors. So from my perspective it is simply a matter of health vs everything else, and we can incorporate the ‘everything else’ into a cost-effectiveness analysis (with a societal perspective) in monetary terms. Funds can be reallocated as necessary with each budget statement (of which there seem to be a lot nowadays).

Is the Rational Addiction model inherently impossible to estimate? Journal of Health Economics [RePEc] Published 28th December 2016

Saddle point dynamics. Something I’ve never managed to get my head around, but here goes… This paper starts from the problem that empirical tests of the Rational Addiction model serve up wildly variable and often ridiculous (implied) discount rates. That may be part of the reason why economists tend to support the RA model but at the same time believe that it has not been empirically proven. The paper sets out the basis for saddle point dynamics in the context of the RA model, and outlines the nature of the stable and unstable root within the function that determines a person’s consumption over time. The authors employ Monte Carlo estimation of RA-type equations, simulating panel data observations. These simulations demonstrate that the presence of the unstable root may make it very difficult to estimate the coefficients. So even if the RA model can truly represent behaviour, empirical estimation may contradict it. This raises the question of whether the RA model is essentially untestable. A key feature of the argument relates to use of the model where a person’s time horizon is not considered to be infinite. Some non-health economists like to assume it is, which, as the authors wryly note, is not particularly ‘rational’.

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