Chris Sampson’s journal round-up for 6th January 2020

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.

Child sleep and mother labour market outcomes. Journal of Health Economics [PubMed] [RePEc] Published January 2020

It’s pretty clear that sleep is important to almost all aspects of our lives and our well-being. So it is perhaps surprising that economists have paid relatively little attention to the ways in which the quality of sleep influences the ‘economic’ aspects of our lives. Part of the explanation might be that almost anything that you can imagine having an effect on your sleep is also likely to be affected by your sleep. Identifying causality is a challenge. This paper shows us how it’s done.

The study is focussed on the relationship between sleep and labour market outcomes in new mothers. There’s good reason to care about new mothers’ sleep because many new mothers report that lack of sleep is a problem and many suffer from mental and physical health problems that might relate to this. But the major benefit to this study is that the context provides a very nice instrument to help identify causality – children’s sleep. The study uses data from the Avon Longitudinal Study of Parents and Children (ALSPAC), which seems like an impressive data set. The study recruited 14,541 pregnant women with due dates between 1991 and 1993, collecting data on mothers’ and children’s sleep quality and mothers’ labour market activity. The authors demonstrate that children’s sleep (in terms of duration and disturbances) affects the amount of sleep that mothers get. No surprise there. They then demonstrate that the amount of sleep that mothers get affects their labour market outcomes, in terms of their likelihood of being in employment, the number of hours they work, and household income. The authors also demonstrate that children’s sleep quality does not have a direct impact on mothers’ labour market outcomes except through its effect on mothers’ sleep. The causal mechanism seems difficult to refute.

Using a two-stage least squares model with a child’s sleep as an instrument for their mother’s sleep, the authors estimate the effect of mothers’ sleep on labour market outcomes. On average, a 30-minute increase in a mother’s sleep duration increases the number of hours she works by 8.3% and increases household income by 3.1%. But the study goes further (much further) by identifying the potential mechanisms for this effect, with numerous exploratory analyses. Less sleep makes mothers more likely to self-report having problems at work. It also makes mothers less likely to work full-time. Going even further, the authors test the impact of the UK Employment Rights Act 1996, which gave mothers the right to request flexible working. The effect of the Act was to reduce the impact of mothers’ sleep duration on labour market outcomes, with a 6 percentage points lower probability that mothers drop out of the labour force.

My only criticism of this paper is that the copy-editing is pretty poor! There are so many things in this study that are interesting in their own right but also signal need for further research. Unsurprisingly, the study identifies gender inequalities. No wonder men’s wages increase while women’s plateau. Personally, I don’t much care about labour market outcomes except insofar as they affect individuals’ well-being. Thanks to the impressive data set, the study can also show that the impact on women’s labour market outcomes is not simply a response to changing priorities with respect to work, implying that it is actually a problem. The study provides a lot of food for thought for policy-makers.

Health years in total: a new health objective function for cost-effectiveness analysis. Value in Health Published 23rd December 2019

It’s common for me to complain about papers on this blog, usually in relation to one of my (many) pet peeves. This paper is in a different category. It’s dangerous. I’m angry.

The authors introduce the concept of ‘health years in total’. It’s a simple idea that involves separating the QA and the LY parts of the QALY in order to make quality of life and life years additive instead of multiplicative. This creates the possibility of attaching value to life years over and above their value in terms of the quality of life that is experienced in them. ‘Health years’ can be generated at a rate of two per year because each life year is worth 1 and that 1 is added to what the authors call a ‘modified QALY’. This ‘modified QALY’ is based on the supposition that the number of life years in its estimation corresponds to the maximum number of life years available under any treatment scenario being considered. So, if treatment A provides 2 life years and treatment B provides 3 life years, you multiply the quality of life value of treatment A by 3 years and then add the number of actual life years (i.e. 2). On the face of it, this is as stupid as it sounds.

So why do it? Well, some people don’t like QALYs. A cabal of organisations, supposedly representing patients, has sought to undermine the use of cost-effectiveness analysis. For whatever reason, they have decided to pursue the argument that the QALY discriminates against people with disabilities, or anybody else who happens to be unwell. Depending on the scenario this is either untrue or patently desirable. But the authors of this paper seem happy to entertain the cabal. The foundation for the development of the ‘health years in total’ framework is explicitly based in the equity arguments forwarded by these groups. It’s designed to be a more meaningful alternative to the ‘equal value of life’ measure; a measure that has been used in the US context, which adds a value of 1 to life years regardless of their quality.

The paper does a nice job of illustrating the ‘health years in total’ approach compared with the QALY approach and the ‘equal value of life’ approach. There’s merit in considering alternatives to the QALY model, and there may be value in an ‘additive’ approach that in some way separates the valuation of life years from the valuation of health states. There may even be some ethical justification for the ‘health years in total’ framework. But, if there is, it isn’t provided by this paper. To frame the QALY as discriminatory in the way that the authors do, describing this feature as a ‘limitation’ of the QALY approach, and to present an alternative with no basis in ethics is, at best, foolish. In practice, the ‘health years in total’ calculation would favour life-extending treatments over those that improve health. There are some organisations with vested interests in this. Expect to see ‘health years in total’ obscuring decision-making in the United States in the near future.

The causal effect of education on chronic health conditions in the UK. Journal of Health Economics Published 23rd December 2019

Since the dawn of health economics, researchers have been interested in the ways in which education and health outcomes depend on one another. People with more education tend to be healthier. But identifying causal relationships in this context is almost impossible. Some studies have claimed that education has a positive (causal) effect on both general and specific health outcomes. But there are just as many studies that show no impact. This study attempts to solve the problem by throwing a lot of data at it.

The authors analyse the impact of two sets of reforms in the UK. First, the raising of the school leaving age in 1972, from 15 to 16 years. Second, the broader set of reforms that were implemented in the 1990s that resulted in a major increase in the number of people entering higher education. The study’s weapon is the Quarterly Labour Force Survey (QLFS), which includes over 5 million observations from 1.5 million people. Part of the challenge of identifying the impact of education on health outcomes is that the effects can be expected to be observed over the long-term and can therefore be obscured by other long-term trends. To address this, the authors limit their analyses to people in narrow age ranges in correspondence with the times of the reforms. Thanks to the size of the data set, they still have more than 350,000 observations for each reform. The QLFS asks people to self-report having any of a set of 17 different chronic health conditions. These can be grouped in a variety of ways, or looked at individually. The analysis uses a regression discontinuity framework to test the impact of raising the school leaving age, with birth date acting as an instrument for the number of years spent in education. The analysis of the second reform is less precise, as there is no single discontinuity, so the model identifies variation between the relevant cohorts over the period. The models are used to test a variety of combinations of the chronic condition indicators.

In short, the study finds that education does not seem to have a causal effect on health, in terms of the number of chronic conditions or the probability of having any chronic condition. But, even with their massive data set, the authors cannot exclude the possibility that education does have an effect on health (whether positive or negative). This non-finding is consistent across both reforms and is robust to various specifications. There is one potentially important exception to this. Diabetes. Looking at the school leaving age reform, an additional year of schooling reduces the likelihood of having diabetes by 3.6 percentage points. Given the potential for diabetes to depend heavily on an individual’s behaviour and choices, this seems to make sense. Kids, stay in school. Just don’t do it for the good of your health.

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Chris Sampson’s journal round-up for 27th February 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.

Does it pay to know prices in health care? American Economic Journal: Economic Policy Published February 2017

In the US, people in need of health care have to pay for it – or for insurance to cover it – without knowing in advance how much said health care actually costs. Weird, right? Instinctively, it feels as if people really ought to be able to find out. However, if knowing prices in advance doesn’t actually affect consumption, maybe we can say it really doesn’t matter. Well, we can’t. As this new study shows, having access to price information affects consumer choices. There’s plenty of price dispersion to make this potentially important: in this study’s dataset, a move from the 90th to the 50th percentile is on average associated with a price drop of 35%. The data relate to 387,774 procedures for 6,208 people working for a corporate client of a price information firm. Access to this service was staggered for different employees, creating the potential for experimental investigation. The principal strategy is difference-in-differences regression analysis. Access to the price information service was associated with prices around 1.6% lower on average. For primary care – which might be less price sensitive – and for complex cases where lots of procedures are taking place, the effect is weakened. The results seem robust to matching and other tests. The author is able to provide further insight by showing that access to price information increases the probability of seeing a new doctor by 14%. And when an instrumental variable approach is used to assess the price reduction specifically for people who searched for price information and then received a procedure within 30 days, the reduction in price reaches a whopping 17%. This suggests that the average impact of a 1.6% reduction could be a lot higher if people searched for price information more frequently. The fact that they don’t is likely due to a particular kind of moral hazard being at play. Moral hazard in search occurs when people have no incentive to search for cheaper services. The author goes on to show that in any given week an individual is around 90% less likely to search if they have already met their deductible, and that this translates into an elasticity of search propensity to the proportion out-of-pocket expense of approximately 1.8. We mustn’t forget the other side of the welfare coin here. What if people are choosing lower quality care in order to save money, or foregoing it altogether? Looking at the rate of follow-through after searches and bringing in hospital quality data seems to show that this isn’t a concern here. This group of people aren’t representative of the general population so it may be that access to prices is only valuable to certain groups. Nevertheless, this paper tells us a lot about the importance of price information and in particular the special kind of moral hazard that can arise in the presence of comprehensive insurance coverage.

Mitigating the consequences of a health condition: The role of intra- and interhousehold assistance. Journal of Health Economics Published 20th February 2017

There’s a lot of research around the effect that an individual’s health problem can have on their immediate family, both in terms of the overspill in quality of life impacts and the costs of satisfying need for health care. However, large panel data research can be limited because the data can’t connect non-coresident family members. This study considers informal insurance and consumption smoothing within families beyond the current household. The data come from the Panel Study of Income Dynamics, with 7,578 individuals and around 33,000 household years from 2001-2011. The panel follows offspring after they leave a household, facilitating the identification of genetically linked families. Participants are asked whether they suffer from 11 different health problems and, if they do, the extent to which it limits their daily activities. The data also include information on different categories of spending, including health. The analysis involves regression that accounts for individual fixed effects and looks at the impact of a change in health status on consumption. If a household is fully insured, changes in health status should not affect non-health expenditures. The analysis focuses on the impact of severe limitations, which are reported at some point by 1,321 people. Such a change in health status was associated with a reduction in annual working hours of around 20%, corresponding to $5000 for men and $2800 for women. Additionally, household health expenditures increased by $479 on average. The notion of complete insurance facilitating consumption smoothing appears to fail, with a decline in consumption of around 10%. Partial insurance smoothes roughly half the loss. Households with formal insurance exhibit a much smaller reduction in consumption. A key finding is that being married may facilitate consumption smoothing to the extent of full insurance, while unmarried couples take a bigger hit. Home equity seems to play an important role in this dynamic, with married couples more likely to remortgage in response to a health shock. Married couples also receive more in social security transfers. Unmarried couples, it seems, have to turn to non-coresident family members instead and are 50% more likely to use this channel than married couples. Male children are more likely to use their own home equity to support their parents, while female children tend to reduce their own consumption. This study identifies a lot of interesting relationships and divergent strategies for consumption smoothing that warrant further investigation.

Handling missing data in within-trial cost-effectiveness analysis: a review with future recommendations. PharmacoEconomics – Open Published 9th February 2017

If you conduct trial-based cost-effectiveness analyses then chances are that at some point you’ve had to go and figure out how to deal with all that missing data. There are a handful of quality papers out there that offer guidance. If we all followed their advice then we’d be doing a decent job of it. This new paper demonstrates that we aren’t all doing a good job of it and offers fresh guidance. The paper starts by outlining the ‘principled’ approach to handling missing data. Essentially it means being sensible with the data, considering the most appropriate statistical model and describing assumptions about the missing data mechanism. Imputation methods that can support this principled approach are briefly discussed. The authors present a quality evaluation scheme, which can be used to assess the appropriateness of methods adopted in a study and the completeness of reporting. It makes recommendations with respect to the description of missing data, the methods used to handle it and the limitations associated with the study. The quality evaluation scheme can be used to score and rank papers from A-E. This is what the authors go on to do, with a systematic review including 81 eligible papers. A previous review found complete case analysis to be the most popular base case method adopted. In 2009-2015, multiple imputation became the most frequently used base case method, though complete case analysis remains common and many studies are still unclear about the methods adopted. Most articles did not describe any robustness analysis, reporting only the base case approach to missing data. Many articles were classified as the lowest quality (E), though this has improved over time. The authors demonstrate that their proposed grading system is associated with the strength of the assumptions in the adopted methods. If you’re engaged in trial-based economic evaluation, you ought to read this paper.

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Sam Watson’s journal round-up for 18th July 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.

Mortality inequality: the good news from a county-level approach. Journal of Economic Perspectives [RePEcPublished Spring 2016

Research on mortality trends always focuses on the bad news. For example, in a well publicized article Anne Case and Angus Deaton report on finding significant increases in mortality for middle-aged white non-Hispanic men and women in the US.  (Although this article did attract some criticism for bias due to aggregation of age groups.) This essay by Janet Currie and Hannes Schwandt takes an altogether different line: it suggests that there is good news on the whole. Examining life expectancy at birth it is shown that mortality inequality between rich and poor counties declined significantly between 1990 and 2010. However, mortality rates and inequality in life expectancy have shifted a lot less for older age groups – a factor many previous ‘bad news’ type studies have focussed on. One explanation for such a trend is that there has been more smoking cessation in wealthier areas.The authors conclude then that for the youngest people, inequality is likely to remain low, while for older generations positive health behaviours such as smoking cessation are also likely to spread, improving inequality in mortality. However, one might suggest such conclusions are overly optimistic. Poverty and low socio-economic status have a complex relationship with health; reductions in mortality at lower ages may create a survivor bias so that the overall cohort has worse health on average now as those in poor health who may have died a number of years ago now survive to older ages. Nevertheless, Currie and Schwandt are right to suggest that policy makers should be made aware that improvements in mortality are possible and that evidence such as this should be used to mobilise efforts to improve the health of high risk groups.

The tax-free year in Iceland: A natural experiment to explore the impact of a short-term increase in labor supply on the risk of heart attacks. Journal of Health Economics [PubMedPublished 23rd June 2016

In 1987, owing to a change in the tax system in Iceland, no-one had to pay income tax. As a result labour supply increased substantially, which provides a neat natural experiment. In this study, the authors aim to examine whether increased labour market participation increases the risk of acute myocardial infarction (AMI). There is a growing literature of the relationship between macroeconomic conditions and health; a seminal article was Christopher Ruhm’s 2000 study that showed that economic downturns are associated with decreases in the overall mortality rate. However, the mechanisms that mediate such an effect remain elusive. Using panel data on individuals from 1982-92 linked to data on coronary events the authors show an increase in the risk of AMI in both 1987 and 1988 among men. However, some of the results seem improbably large, e.g. a 149% increase in the probability of AMI among self-employed men aged 45-64. While taken as a whole I think the evidence does suggest an increase in AMI risk in 1987, I was left with a number of questions: why no individual effect in the specification?; could the errors be serially correlated?; why wasn’t an instrumental variable approach used if the motivation is that the 1987 policy exogenously shifted labour market participation?; aside from having lower average risk, is there any reason to separately analyse men and women? These results also contradict an earlier study, also from Christopher Ruhm, that showed unemployment was associated with increases in deaths from coronary heart disease. At the very least, this study shows us that we just don’t really understand the complex interplay between economy, society, and health.

Gender roles and medical progress. Journal of Political Economy [RePEcPublished 3rd May 2016

Over the past century female labour market participation has improved as restrictive female gender roles have shifted and technological innovations have reduced the burden of many tasks traditionally assigned to women. Ha-Joon Chang posits that the invention of the washing machine was a more important invention than the internet in the way it revolutionised the labour market. This paper argues that the reduction in maternity conditions as a result of medical progress over the 20th century had a significant impact on female labour market participation. Indeed, they estimate that medical progress can account for 50% of the rise in female labour market participation between 1930 and 1960.

Photo credit: Antony Theobald (CC BY-NC-ND 2.0)