Sam Watson’s journal round-up for 9th 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.

Non-separable time preferences, novelty consumption and body weight: Theory and evidence from the East German transition to capitalism. Journal of Health Economics [PubMed] [RePEc] Published January 2017

Obesity is an ever growing (excuse the pun) problem associated with numerous health risks including diabetes and hypertension. It was recently reported that eight in ten middle-aged Britons are overweight or exercise too little. A strong correlation between economic development and obesity rates has been widely observed both over time within the same countries and between countries across the world. One potential explanation for this correlation is innovation of novel food products that are often energy dense and of little nutritional benefit. However, exploring this hypothesis is difficult as over the long time horizons associated with changing consumer habits and economic development, a multitude of confounding factors also change. This paper attempts to delve into this question making use of the natural experiment of German reunification in 1989. After the fall of the Berlin Wall a wave of products previously available in West Germany became available to East Germans, almost overnight. The paper provides a nice in depth theoretical model, which is then linked to data and an empirical analysis to provide a comprehensive study of the effect of novel food products in both the short and medium terms. At first glance the effect of reunification on diet habits and weight gain appear fairly substantial both in absolute and relative terms, and these results appear robust and well-founded, theoretically speaking. A question that remains in my mind are whether preferences in this case are endogenous or state dependent, a question that has important implications for policy. Similarly, did reunification reveal East German preferences for fast food and the like, or were those preferences changed as a result of the significant cultural shift? Sadly, this last question is unanswerable, but affects whether we can interpret these results as causal – a thought I shall expand upon in an upcoming blog post.

Ontology, methodological individualism, and the foundations of the social sciences. Journal of Economic Literature [RePEc] Published December 2016

It is not often that we feature philosophically themed papers. But, I am a keen proponent of keeping abreast of advances in our understanding of what exactly it is we are doing day to day. Are we actually producing knowledge of the real world? This review essay discusses the book The Ant Trap by Brian Epstein. Epstein argues that social scientists must get the social ontology right in order to generate knowledge of the social world. A view I think it would be hard to disagree with. But, he argues, economists have not got the social ontology right. In particular, economists are of the belief that social facts are built out of individual people, much like an ant colony is built of ants (hence the title), when in fact a less anthropocentric view should be adopted. In this essay, Robert Sugden argues that Epstein’s arguments against ontological individualism – that social facts are reducible to the actions of individuals – are unconvincing, particularly given Epstein’s apparent lack of insight into what social scientists actually do. Epstein also developed an ontological model for social facts on the basis of work by John Searle, a model which Sugden finds to be overly ambitious and ultimately unsuccessful. There is not enough space here to flesh out any of the arguments, needless to say it is an interesting debate, and one which may or may not make a difference to the methods we use, depending on who you agree with.

Heterogeneity in smokers’ responses to tobacco control policies. Health Economics [PubMedPublished 4th January 2016

In an ideal world, public health policy with regards to drugs and alcohol would be designed to minimise harm. However, it is often the case that policy is concerned with reducing the prevalence of use, rather than harm. Prevalence reducing policies, such as a Pigouvian tax, reduce overall use but only among those with the most elastic demand, who are also likely to be those whose use leads to the least harm. In this light, this study assesses the heterogeneity of tobacco users’ responses to tobacco control policies. Using quantile regression techniques, Erik Nesson finds that the effects of tobacco taxes are most pronounced in those who consume lower numbers of cigarettes, as we might expect. This is certainly not the first study to look at this (e.g. here and here), but reproduction of research findings is an essential part of the scientific process, and this study certainly provides further robust evidence to show that taxes alone may not be the optimum harm reduction strategy.

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Alastair Canaway’s journal round-up for 31st October 2016

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.

Ethical hurdles in the prioritization of oncology care. Applied Health Economics and Health Policy [PubMedPublished 21st October 2016

Recently between health economists, there has been significant scrutiny and disquiet directed towards the Cancer Drugs Fund with Professor Karl Claxton describing it as “an appalling, unfair use of NHS resources”. With the latest reorganization of the Cancer Drugs Fund in mind, this article examining the ethical issues surrounding prioritisation of cancer care was of particular interest. As all health economists will tell you, there is an opportunity cost with any allocation of scarce resources. Likewise, with prioritisation of specific disease groups, there may be equity issues with specific patients’ lives essentially being valued more greatly than those suffering other conditions. This article conducts a systematic review of the oncology literature to examine the ethical issues surrounding inequity in healthcare. The review found that public and political attention often focuses on ‘availability’ of pharmacological treatment in addition to factors that lead to good outcomes. The public and political focus on availability can have perverse consequences as highlighted by the Cancer Drugs Fund: resources are diverted towards availability and away from other more cost-effective areas, and in turn this may have had a detrimental effect on care for non-cancer patients. Additionally, by approving high cost, less cost-effective agents, strain will be placed upon health budgets and causing problems for existing cost-effectiveness thresholds. If prioritisation for cancer drugs is to be pursued then the authors suggest that the question of how to fund new therapies equitably will need to be addressed. Although the above issues will not be new to most, the paper is still worth reading as it: i) gives an overview of the different prioritisation frameworks used across Europe, ii) provides several suggestions for how, if prioritization is to be pursued, it can be done in a fairer manner rather than simply overriding typical HTA decision processes, iii) considers the potential legal consequences of prioritisation and iv) the impact of prioritisation on the sustainability of healthcare funding.

Doctor-patient differences in risk and time preferences: a field experiment. Journal of Health Economics Published 19th October 2016

The patient-doctor agency interaction, and associated issues due to asymmetrical information is something that was discussed often during my health economics MSc, but rarely during my day to day work. Despite being very familiar with supplier induced demand, differences in risk and time preferences in the patient-doctor dyad wasn’t something I’d considered in recent times. Upon reading, immediately, it is clear that if risk and time preferences do differ, then what is seen as the optimal treatment for the patient may be very different to that of the doctor. This may lead to poorer adherence to treatments and worse outcomes. This paper sought to investigate whether patients and their doctors had similar time and risk preferences using a framed field experiment with 300 patients and 67 doctors in Athens, Greece in a natural clinical setting. The authors claim to be the first to attempt this, and have three main findings: i) there were significant time preference differences between the patients and doctors – doctors discounted future health gains and financial outcomes less heavily than patients; ii) there were no significant differences in risk preferences for health with both doctors and patients being mildly risk averse; iii) there were however risk preference differences for financial impacts with doctors being more risk averse than patients. The implication of this paper is that there is potential for improvements in doctor-patient communication for treatments, and as agents for patients, doctors should attempts to gauge their patient’s preferences and attitudes before recommending treatment. For those who heavily discount the future it may be preferable to provide care that increases the short term benefits.

Hospital productivity growth in the English NHS 2008/09 to 2013/14 [PDF]. Centre for Health Economics Research Paper [RePEcPublished 21st October 2016

Although this is technically a ‘journal round-up’, this week I’ve chosen to include the latest CHE report as I think it is something which may be of wider interest to the AHEBlog community. Given limited resources, there is an unerring call for both productivity and efficiency gains within the NHS. The CHE report examines the extent to which NHS hospitals have improved productivity: have they made better use of their resources by increasing the number of patients they treat and the services they deliver for the same or fewer inputs. To assess productivity, the report uses established methods: Total Factor Productivity (TFP) which is the ratio of all outputs to all inputs. Growth in TFP is seen as being key to improving patient care with limited resources. The primary report finding was that TFP growth at the trust level exhibits ‘extraordinary volatility’. For example one year there maybe TFP growth followed by negative growth the next year, and then positive growth. The authors assert that much of the TFP growth measured is in fact implausible, and much of the changes are driven largely by nominal effects alongside some real changes. These nominal effects may be data entry errors or changes in accounting practices and data recording processes which results in changes to the timing of the recording of outputs and inputs. This is an important finding for research assessing productivity growth within the NHS. The TFP approach is an established methodology, yet as this research demonstrates, such methods do not provide credible measures of productivity at the hospital level. If hospital level productivity growth is to be measured credibly, then a new methodology will be required.

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Three arguments in favour of a negative social discount rate

In the last journal round up, we featured a paper that found that gains to life were valued higher than gains to consumption under standard assumptions about preferences. This sounds like one of those common sense things that are touted as a ‘finding’ but which most people would have said ‘I don’t need an economics degree to tell you that’. Fair enough. But these results do have consequences for economic methodology. One example of that is the social discount rate that we use for the evaluation of the benefits of medical technologies.

A positive social discount rate is often used so that gains in the future are worth less than gains today. But why? Based on the Ramsey growth model, the discount rate is equal to the sum of two components: a) the time preference rate as applied to cardinal utility, and b) differences in the marginal utility of consumption over time. The latter term is the product of the growth rate and the consumption elasticity of marginal utility, which is the rate at which consumption declines in consumption. Since we are valuing health benefit, we can express the consumption value of health, which is the amount of consumption at time t equivalent to one unit of health. Let’s examine these in more detail (see also Further Reading at the bottom for more in depth analysis).

1. Time preference

The extent to which an individual prefers present benefits to those in the future is known as an individual’s time preference. While an individual may have a positive time preference, whether rational or not, this does not necessarily imply a positive social discount rate. This is most clearly evident when we make inter-generational comparisons and evaluate policies that affect as yet unborn people. Often a positive social time preference for health is taken as given. Yet, while I may prefer to be in better health now rather than later, people who are as yet unborn have no such preference. They are not ‘waiting’ for these benefits to accrue. This is known as the No Waiting Argument, the strongest form of which states that we have zero time preference before birth. It makes little sense to argue that we should discount future benefits for as yet unborn people because they would prefer to receive those benefits now. At the very least, the No Waiting Argument shows that a positive discount rate within a life does not imply a positive discount rate across lives and hence a positive social discount rate.

2. Marginal Utility of Consumption

With regards to consumption goods a positive social discount rate is usually implied. A positive growth rate means future generations will have greater consumption and marginal utility is decreasing in consumption so equivalent goods should be valued more today. This is also a way of smoothing consumption across generations. A positive social discount rate for health effects is therefore implied if the consumption value of health is decreasing. However, the consumption value of health is likely to be increasing. One reason for this is that the marginal utility of consumption is likely to diminish faster than the marginal utility of health. The consumption today that is equivalent to a unit of health in terms of utility may be less than the equivalent. Some studies also suggest that the value of a statistical life increases with income and will therefore increase over time.

3. Uncertainty

There are other reasons given in support of a positive social discount rate. Some authors have suggested that the future should be discounted because it is less certain. Uncertainty has been a key point regarding discounting in the debate about the economics of climate change. More uncertainty may be a reason to discount outcomes to reflect a reasonable risk premium, but while temporal distance may be correlated with higher uncertainty, it is not interchangeable with it. There are different levels of uncertainty attached to present day outcomes, which should attract the same discounting with respect to the uncertainty as any outcomes in the future.

Conclusions

Many of the arguments presented here have been aired in other debates, in particular in climate change economics, where the effects of environmental policies today have effects extending many hundreds of years in the future. A consensus is unlikely to be reached any time soon about the appropriate discount rate and this post is not a comprehensive treatment by any means. The choice of discount rate can have important consequences on our choices about which medical technologies to invest in. Indeed, different rates may have important equity implications. While many evaluations present results for a range of discount rates, these never include negative rates for benefits. Perhaps they should…

Further Reading

Claxton K, Paulden M, Gravelle H, Brouwer W, Culyer AJ. Discounting and decision making in the economic evaluation of health-care technologies. Health Econ 2011; 20: 2–15.

Gravelle H, Smith D. Discounting for health effects in cost-benefit and cost-effectiveness analysis. Health Econ 2001; 10: 587–99.