October 3, 2013

Income by Select Occupations over Time


A little while  ago I watched a documentary on cable called American Teacher.   The documentary was about teaching in American and was generally pro-teacher.  But the point that I found interesting was a chart they showed in the middle of the film that compared teacher wages to other professions.   They claimed that real estate brokers and lawyers had significantly higher income growth over the period than teachers.   The numbers seemed a bit off to me.

I thought that wage trends over time for different occupations would be an interesting topic to explore.   I know the general income for my occupation where I live has gone up abut 50% in the past 15 years.   On the other hand my fathers occupation has been virtually flat for the past 15 years in his home city (though he's now retired). 

I set out to find income figures per specific occupations over several decade period.  It was pretty hard to find good consistent data breaking down income by occupations.    I looked all over the Census site to find a good list but it seemed the data they collect changes a bit over time.    I was at least able to find a hodge podge of tables that give me numbers for some common occupations.  

I couldn't find consistent data and some of its not really comparing equal information.  But I think its close enough to get an OK idea of wages for the occupations in question.  
Data for 1978, 1983, 1987 and 1992 are from the Census Consumer Income reports.  Annoyingly they seem to only give income for males or females but not the combined population so I'm using the numbers for males.   The 1999 data is from the Census page2005 is from BLS OES and 2012 is the current BLS OES.    For BLS data I and used hourly wage x 2000 wages as an estimate of annual median wages.   For the first few data points the figure for 'lawyer' is actually including judges but the later years is lawyers only, so that means that the income figures for the lawyer category are actually measuring different set of people.    For engineers I first had a general category for all engineers but then they split them up so I picked just electrical engineers which seem to be closer to the middle of income for engineer specialties.   The teacher incomes are annual averages in the later years because they didn't have median hourly rates.   Teachers are almost all paid salary and theres little variation in wages.

So let me be clear, the charts and data are pretty flawed due to my mix matched data sources with inconsistent numbers.  Almost makes this exercise futile.

Here is the income over time from 1978 to 2012 :

(click image for full size)

And here is how the income for each occupation grew from 1983 to 2012:

(click image for full size)


I only had a few data points from 1978 so I didn't include that year in this chart.

It just so happened that the occupations I sampled all grew faster than wages in general.  I suspect thats because many many low skill service jobs make up a larger portion of the employment and those wages haven't grown as fast compared to the jobs I sampled which are mostly skilled professional occupations.

Carpenter, Nurses and teachers grew the fastest.  However part of that may be a fault in my methodology of pulling together miss matched sources.    Both occupations had high jumps from 1999 to 2005 and thats when I went from a census table to the BLS figures.   Median hourly  wages x 2000 may not be very accurate approximation for median annual income for some occupations versus others.   For example carpenters tend to have higher unemployment during economic downturns and may have seasonal unemployment due to weather.   School teacher wages jumped 50% in my chart from 1999 to 2005 and I'm pretty sure thats not right and must be the difference in what I'm reporting from the different sources.   Lawyers didn't grow as fast as other professions but I started out with data for lawyers and judges and then ended up with only lawyers and I'm sure judges pulled up the initial numbers so makes it look like they haven't grown as fast.

Again, I have to point out that the numbers are not very great.   If I can find better data I'll revisit the topic.  For now we've got a set of data with some flaws.



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