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Sam Watson’s journal round-up for 13th 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.

Risky transportation choices and the value of a statistical life. American Economic Journal: Applied Economics [RePEc] Published January 2017

The international airport that serves Freetown, the capital of Sierra Leone, is separated from the city by a body of water. To traverse this channel a number of modes of transportation are available. But, as the British Foreign and Commonwealth Office advises: “Transport infrastructure is poor. None of the options for transferring between the international airport at Lungi and Freetown are risk-free. You should study the transfer options carefully before traveling.” Passengers can travel quickly by helicopter, but this is expensive, and also carries the highest risk of a fatal accident; a slow but cheap ferry is available; water taxis and hovercraft also serve the route. Given this range of choices and differing levels of risk, the authors saw the opportunity to conduct a value of a statistical life (VSL) study by examining the trade-offs people were making between these different choices. The choice people make is a function of their wage, the lowest earners won’t choose the helicopter for example, and then people may be willing to pay more for a safer form of transport, which is the basis of the VLS calculation. African travelers, who were notably wealthier than the average given they were travelling internationally, had an average VSL of $577,000. I have never quite bought into the VSL method and making inferences about the value of infra-marginal changes in health from marginal changes in risk. Chances are no-one would accept $577,000 is exchange for their life. But this is an interesting contribution for a low income settings where studies like this are few and far between.

Spatiotemporal trends in teen birth rates in the USA, 2003-2012. Journal of the Royal Statistical Society: Series A Published 19th January 2017

Empirical economics is more often than not focused on estimation of the causal effects of interventions so that more exploratory analyses are frequently neglected. In order to design an intervention that targets a particular public health issue we need to understand what is driving it and how it has varied over time and space. A great many ‘exploratory’ economic studies, often entitled something beginning ‘The determinants of…’, abuse p-values to determine what’s driving changes to a health outcome of interest. It makes sense therefore to keep abreast of recent studies and up-to-date methods of exploratory data analysis, particularly with regards to health issues, and this article is one such example, which examines teen birth rates across the US. Teen birth rates vary over time and across space, moreover there is potentially an interaction between the two: the authors build a Bayesian hierarchical model using various model checks, including posterior predictive checks. All in all, a good example of this kind of analysis, and full of good maps.

The impact of unanticipated economic shocks on the demand for contraceptives: evidence from Uganda. Health Economics [PubMedPublished 7th February 2017

There has long been an interest in the relationship between household wealth or income and health. It is hard to distinguish whether wealthier households make more money or whether income improves health, for example. Questions like these have important implications for health policy, and the valuation of its effects, as well as understanding the effects of economic conditions and inequality. This article is a paper in this tradition, albeit in a low income country setting. Given the aformentioned issue of reverse causality, this article examines the effect of income on household fertility choices and use of contraceptives using rainfall as an instrument for income. The study us based in Uganda where for many households are agriculatural-dependent for food and income so the way in which rainfall works seems obvious. Many studies have used weather patterns and rainfall as instruments for things such as strikes and conflict. However, the justification for doing so can be controversial, as in unobserved factors in times or places with high rainfall may well influence household income. Other queries remain about this study: if contraceptive demand goes up, is that because people are having sex more often, that they have received education regarding contraceptive use, or that they have changed their mind about fertility decisions. The study remains an interesting contribution nonetheless.


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