Tag: preference

Behavioural colour schemes

One of the seminal results of behavioural economics (a field I’m having less and less faith in as the days go by, especially once I learnt about ergodicity) is that by adding a choice to an existing list of choices, you can change people’s preferences.

For example, if you give people a choice between vanilla ice cream for ?70 and vanilla ice cream with chocolate sauce for ?110, most people will go for just the vanilla ice cream. However, when you add a third option, let’s say “vanilla ice cream with double chocolate sauce” for ?150, you will see more people choosing the vanilla ice cream with chocolate sauce (?110) over the plain vanilla ice cream (?70).

That example I pulled out of thin air, but trust me, this is the kind of examples you see in behavioural economics literature. In fact, a lot of behavioural economics research is about getting 24 undergrads to participate in an experiment (which undergrad doesn’t love free ice cream?) and giving them options like above. Then based on how their preferences change when the new option is added, a theory is concocted on how people choose.

The existence of “green jelly beans” (or p-value hunting, also called “p-hacking”) cannot be ruled out in such studies.

Anyway, enough bitching about behavioural economics, because while their methods may not be rigorous, and can sometimes be explained using conventional economics, some of their insights do sometimes apply in real life. Like the one where you add a choice and people start seeing the existing choices in a different way.

The other day, Nitin Pai asked me to product a district-wise map of Karnataka colour coded by the prevalence of Covid-19 (or the “Wuhan virus”) in each district. “We can colour them green, yellow, orange and red”, he said, “based on how quickly cases are growing in each district”.

After a few backs and forths, and using data from the excellent covid19india.org  , we agreed on a formula for how to classify districts by colour. And then I started drawing maps (R now has superb methods to draw maps using ggplot2).

For the first version, I took his colour recommendations at face value, and this is what came out. 

While the data is shown easily, there are two problems with this chart. Firstly, as my father might have put it, “the colours hit the eyes”. There are too many bright colours here and it’s hard to stare at the graph for too long. Secondly, the yellow and the orange appear a bit too similar. Not good.

So I started playing around. As a first step, I replaced “green” with “darkgreen”. I think I got lucky. This is what I got. 

Just this one change (OK i made one more change – made the borders black, so that the borders between contiguous dark green districts can be seen more clearly) made so much of a difference.

Firstly, the addition of the sober dark green (rather the bright green) means that the graph looks so much better on the eye now. The same yellow and orange and red don’t “hit the eyes” like they used to in green’s company.

And more importantly (like the behavioural economics theory), the orange and yellow look much more distinct from each other now (my apologies to readers who are colour blind). Rather than trying to change the clashing colours (the other day I’d tried changing yellow to other closer colours but nothing had worked), adding a darker shade alongside meant that the distinctions became much more visible.

Maybe there IS something to behavioural economics, at least when it comes to colour schemes.

Doctors marrying doctors

So I’ve learnt that doctors prefer to marry other doctors. Well, there’s nothing new in this. When I think about my extended families, and doctors there, most of them I realize are married to other doctors. The ostensible reason, I’m told, is that it’s a different lifestyle, and only doctors can understand the lifestyles of other doctors, and hence this preference. It cannot be ruled out, however, that it is a fallout of pretty good gender ratios and long hours at medical colleges, which leads to coupling – with the “understand each other’s professions” only being a fig leaf.

While people in other professions also marry within their profession (again put down to ease of “meeting”), this tendency is especially exaggerated among doctors. The problem with this, though, is that it doesn’t make financial sense.

Now, the deal with doctors is that they don’t earn good money until very late. After you’ve finished your bachelors, you first need to slog it off for a few years before you get a masters seat. And once you’ve finished your masters, you need to slog for a few years at a hospital which will pay you a pittance, until a point comes in life when you become senior enough that you start getting paid well.

Typically, most doctors (in India) don’t make much at all till they are 35, and after that they get flooded with money. Now, if two doctors marry, that means they are starved of cash flow during their prime years – time when their engineer and MBA counterparts will be minting money, traveling the world, having kids and buying houses. By the time the doctor couple makes money, they would probably be well past their youth, and it is only their descendants that will get to really enjoy their cash flows.

If a doctor marries an engineer (or an MBA), though, cash flows are better hedged. While it is true of all professions that salary goes up with years of experience, the curve isn’t as steep for professions apart from doctors. So, a doctor-MBA couple (say) can live a good life on the MBAs salary till they are in their mid-late 30s, by which time the doctor’s career would have begun to take off and the MBA would have begun to burn out. And then the doctor’s enhanced cash flow starts kicking in! Great hedge, I would say!

So dear doctors, unless you have fallen in love with a classmate at medical school (which has effectively locked you in to a lifetime of poor cash flow structures), reconsider. Consider marrying out of your profession. Yes, it might be harder for you to get each others’ professions. But at least your finances are taken care of!

PS: Some other professions such as lawyers and accountants also have a fairly steep salary increase curve – starting off at a pittance and then later making money. But in these professions people end up getting to “partner level” at around 30, which is far superior to doctors. Then again, such professionals don’t inter-marry within profession as much as doctors do.