Quantifying the economic impact of disease

This 2015 review article by Marcello Basili (University of Siena) and Filippo Belloc (University “G. d’Annunzio” of Chieti-Pescara), published in the Journal of Economic Surveys (and appears to be open access), has been sitting in my to-be-read pile for too long. Given that I've seen a few mentions recently of the economic costs of the coronavirus outbreak (e.g. see here and here for two examples), it seemed timely to read it now. And timely to write about it on my blog, as some enterprising research students might be tempted to investigate this topic.

The Basili and Belloc article is focused on reviewing the literature on measuring the economic impact of vector-borne disease. Incidentally, the coronavirus is not a vector-borne disease. Vector-borne diseases required a vector for transmission, like a mosquito or flea, which separates them from water-borne diseases, or non-vector-borne diseases, where transmission is directly between infected and uninfected individuals (which appears to include coronavirus). [*] The differences are important for the measurement of impact, but only in the sense that there are a broader range of options that are suitable for an acute disease outbreak like coronavirus than there are for chronic vector-borne diseases like malaria or dengue.

Having said that, the overall points raised in the Basili and Belloc article apply in both cases. There are two general approaches to measuring this impact:

The methods proposed by the literature can be roughly classified in two categories: macroeconomic and micro-based approaches. Macroeconomic approaches follow a traditional cross-country perspective, in which variations in economic outcome variables at country level are explained as a function of variations in population health regressors... At the opposite end of the spectrum, micro-based methods are bottom-up, since they are based on individual- or household-specific measures of the economic effects of a disease, which are then aggregated at the national level...

Basili and Belloc usefully present examples of both macroeconomic and microeconomic approaches, and usefully they present the limitations of each:

Both methods present several weaknesses. On the one hand, the main limit of macroeconomic analyses is that these suffer from endogeneity problems, due to the two-way causality between economic outcomes and VBDs’ incidence; on the other hand, micro-based measures tend to underestimate the true economic impact of VBDs, because they do not capture a number of macroeconomic factors and externality effects.

It seems somewhat obvious to point out that measuring impacts using macroeconomic models (of GDP or the growth rate) will be difficult, because you have to be able to account for all of the factors that contribute to GDP (or growth), or you face a potential omitted variable bias. This is particularly challenging to do well. On the other hand, working up from the microeconomic impacts on individuals or households can lead you to miss important macro-level impacts or spillovers between individuals, households, or regions. So while in some sense the microeconomic approach is simpler (though it often requires a number of heroic assumptions), it can lead to underestimates of overall impact.

For anyone thinking about attempting to measure the economic impact of coronavirus (or any other disease), then thinking through the available research methods is particularly important. In addition to the approaches that Basili and Belloc highlight, the impact of an acute disease like coronavirus could be measured using time series analysis (e.g. an event study), or through modelling (using an input-output model or a computable general equilibrium model). In making the choice of suitable methods, this article would be a good one to read (but not the only one, of course!).

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[*] This categorisation of infectious diseases into three types is necessarily a simplification.