from The Academic Health Economists’ Blo… at http://bit.ly/2ICWRFX on February 25, 2019 at 11:15AM
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Citizens of a country with a democratic system of government are able to affect change in its governors and influence policy. This threat of voting out the poorly performing from power provides an incentive for the government to legislate in a way that benefits the population. However, democracy is certainly no guarantee of good governance, economic growth, or population health as many events in the last ten years will testify. Similarly, non-democracies can also enact policy that benefits the people. A benevolent dictator is not faced with the same need to satisfy voters and can enact politically challenging but beneficial policies. People often point to China as a key example of this. So there remains the question as to whether democracy per se has any tangible economic or health benefits.
In a past discussion of an article on democratic reform and child health, I concluded that “Democratic reform is neither a sufficient nor necessary condition for improvements in child mortality.” Nevertheless democracy may still be beneficial, on average, given the in-built safeguards against poor leaders. This paper, which has been doing the rounds for years as a working paper, is another examination of the question of the impact of becoming democratic. Principally the article is focused on economic growth, but health and education outcomes feature (very) briefly. The concern I have with the article mentioned at the beginning of this paragraph and with this newly published article are that they do not consider in great detail why democratisation occurred. As much political science work points out, democratic reform can be demanded in poor economic conditions due to poor governance. For these endogenous changes economic growth causes democracy. Whereas in other countries democracy could come about in a more exogenous manner. Lumping them all in together may be misleading.
While the authors of this paper provide pages after pages of different regression specifications, including auto-regressive models and instrumental variables models, I remain unconvinced. For example, the instrument relies on ‘waves’ of transitions: a country is more likely to shift politically if its regional neighbours do, like the Arab Spring. But neither economic nor political conditions in a given country are independent of its neighbours. In somewhat of a rebuttal, Ruiz Pozuelo and other authors conducted a survey to try to identify and separate out those countries which transitioned to democracy endogenously and exogenously (from economic conditions). Their work suggests the countries that transitioned exogenously did not experience growth benefits. Taken together this shows the importance of theory to guide empirical work, and not the other way round.
Effect of Novartis Access on availability and price of non-communicable disease medicines in Kenya: a cluster-randomised controlled trial. Lancet: Global Health. Published February 2019
Access to medicines is one of the key barriers to achieving universal health care. The cost-effectiveness threshold for many low income countries rules out many potentially beneficial medicines. This is in part driven though by the high prices charged by pharmaceutical countries to purchase medicine, which often do not discriminate between purchasers with high and low abilities to pay. Novartis launched a scheme – Novartis Access – to provide access to medicines to low and middle income countries at a price of US$1 per treatment per month. This article presents a cluster randomised trial of this scheme in eight counties of Kenya.
The trial provided access to four treatment counties and used four counties as controls. Individuals selected at random within the counties with non-communicable diseases and pharmacies were the principle units within the counties at which outcomes were analysed. Given the small number of clusters, a covariate-constrained randomisation procedure was used, which generates a randomisation that ensures a decent balance of covariates between arms. However, the analysis does not control for the covariates used in the constrained randomisation, which can lead to lower power and incorrect type one error rates. This problem is emphasized by the use of statistical significance to decide on what was and was not affected by the Novartis Access program. While practically all the drugs investigated show an improved availability, only the two with p<0.05 are reported to have improved. Given the very small sample of clusters this is a tricky distinction to make! Significance aside, the program appears to have had some success in improving access to diabetes and asthma medication, but not quite as much as hoped. Introductory microeconomics though would show how savings are not all passed on to the consumer.