Financial economics is a field of study in which economists try to understand how people make their money.
But there’s a big catch: It’s very hard to do.
“You need to know a lot about what people do to make their living,” says Scott Molloy, an economics professor at the University of North Carolina at Charlotte.
“If you want to make sense of why some people earn more than others, you have to know the people who are really rich.”
For Molloys, that meant knowing how much money people earn from their work.
And so, Molloyer and his colleagues started with a simple question: What are the types of jobs people are doing that generate the highest average incomes?
“We looked at the distribution of jobs, and we found that there was a huge concentration of jobs in the service sector,” he says.
“That’s because that’s where most of the people are.
So that was a good place to start.”
They then narrowed down the top three jobs in that sector, based on the amount of time people spent doing them: work in a hospital, teaching or in the health sector, and in a university or business.
So Mollories team looked at these jobs and found that the top earners are doctors and lawyers, who spend about half of their time doing those types of work.
“There’s a pretty clear pattern,” Mollions team says.
And the top four positions were also dominated by white-collar workers, who typically earn about 20% more than people of color.
This was a clear indication that, for the most part, people of colour are better paid than white-collar workers.
Mollys team then compared this data with some other sources of data on income distribution.
For example, they looked at a number of different measures of the amount people make in different industries, such as median hourly wages, average earnings, and the share of their income going to rent and food.
They also looked at median household income, the share people earn per household.
“We saw a pretty big drop off in the top 10 percent, so we started looking at income inequality,” Molls says.
They found that income inequality in the United States has fallen from around 29% in 2007 to just 14% today, a rate that Mollory says is unprecedented in the world.
Molls team then used the data to develop their model, which takes into account both the size of a country and the distribution that different types of workers make.
“The thing that’s really interesting is that this model was actually very similar to what we saw in Europe,” he explains.
“It was a lot like the way people make money in the U.S., which was to make a lot of money in a very small number of companies.”
So the model’s data-driven approach meant it could explain much more about the relationship between income inequality and the health and wealth of a nation.
But it also meant the model was based on an extremely small sample, and so its conclusions could be generalizable to a much wider range of countries.
“This model is a very large sample of data,” Mormays team says, “and it can’t really be generalized to all countries.”
So how do we make sense out of the data?
One of the biggest challenges in developing a predictive model is finding the right way to break it down into individual categories, Molls cautions.
“Most of the information is very general,” he notes.
“So it’s very difficult to make an exact comparison to what other countries are doing.”
So while the models presented here are a good starting point, it’s important to keep in mind that it’s possible to get very different estimates of the level of inequality across a country.
That’s because of differences in data sources and measurement systems, differences in how people are categorized, and differences in the way they measure income.
For instance, the United Kingdom’s National Institute for Economic and Social Research (NIESR) has data for income inequality from 2011, but the data comes from different sources, including the Bureau of Labour Statistics and the British Household Panel Survey.
The authors of a paper published last year in the journal Economic Surveys by researchers at the London School of Economics, however, looked at data from the 2011 National Income Survey and found the UK’s inequality was much higher than the NIESR.
“What we’re trying to do is try to get across the same conclusions as the Niesr and the BLS,” Mowls team says in a statement.
Mouldy’s team looked only at the data from 2011 and found income inequality was very high in the UK.
“People are really unhappy with the way the system is set up,” Mouldys team says about the data.
“For the most important measures of income inequality, like median earnings and median household incomes, the evidence is very mixed.
This shows the level is not uniform across the country