Credit card debt? It's in the genes

debt genes

PEOPLE with a particular variant of a much studied gene are significantly more likely to have credit card debt, a forthcoming study says.

The monoamine oxidase A, or MAO-A, gene makes an enzyme that, among other things, breaks down serotonin and dopamine, chemicals associated with impulse control and mood.

This raises serious policy questions because it would be possible to do a simple genetic test - on hair or saliva - to see if someone has a higher risk of getting into debt.
Dr Jan-Emmanuel De Neve, associate professor at UCL

Previous studies have found that people with low efficiency alleles (versions) of the MAOA are more likely to exhibit impulsive or less conscientious behaviour.

This paper, soon to be published in the Journal of Economic Behaviour and Organisation, found a link with one impulsive behaviour in particular: credit card debt.

The finding could have real, and unsettling, consequences, the authors say.

Although there's isn't one "credit card debt" gene, the link between a gene allele and real behaviour means that lenders could start factoring genetics into their lending decisions.

Is debt in your genes?

To find the link two researchers, Dr Jan-Emmanuel De Neve, an associate professor at UCL and James Fowler, a professor at the University of California, looked at 12,000 people in a huge, nationally representative US data set, the National Longitudinal Study of Adolescent Health.

Participants were asked a simple question, "do you have any credit card debt?", and their responses were compared with their MAO-A alleles.

SOURCE: Youtube/LSE. MAO-A discussion begins at 7.30.

We all have two alleles of MAO-A and each one will be either high or low efficiency, so you could have two high, two low or one of each.

"Varying the MAO-A genotype of all subjects from high to low would increase the reporting of credit card debt in this population from 40.5% to 42.2%," the study says.

Having one or two low efficiency MAO-A alleles increases the likelihood of holding credit card debt by 4%.

That might not sound like much, and, actually, it's a much less strong link that preliminary findings published in 2010, which found a 15.9% increase in likelihood with two low alleles, but it's still a significant correlation and one that lenders could use in the future.

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"About half the people in our sample carried this debt correlated gene and because it was representative that suggests half the population does. This raises serious policy questions because it would be possible to do a simple genetic test - on hair or saliva - to see if someone has a higher risk of getting into debt," De Neve said when his findings were first published.

"A bank or credit leader could use that information to decipher your genetic information before deciding whether to lend to you or to charge you an extra premium," he added.

Other studies on similar topics - for example, Kuhnen et al 2013 found that 5-HTTLPR short allele carriers avoid risky and complex financial choices due to negative emotional reactions - make this even more likely.

The US already has a law banning health insurance discrimination on the basis of genetics but there's, over there or here in the UK, there's nothing stopping private companies from discriminating on the basis of genes.

Legislation might be jumping the gun, though. Lenders already have plenty of predictive information: from past borrowing behaviour to social media profiles to draw on and, as the authors admit, the correlation between the gene and debt is fairly weak.

A few questions...

The chances of getting legislation passed is, in any case, the least of the problems with these kinds of studies.

For one thing, the debt is self reported, which is always unreliable, and we have no sense of how much debt the participants actually have or why.

Another issue is that all the participants are young adults, 18-26 years old, when they were questioned about their debt. Older people carrying credit card balances might have had very different reasons for borrowing that could well affect the results.

Finally, although the researchers go to some lengths to account for environmental and other confounding variables in their analysis, there are obviously far more factors than they could account for.

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