Chattin’ more about graphs

MOAR GRAPHCHATZ

This one makes fun of some WaPo map. Here’s the map (click for full size):

At the top link Catherine and I will tell you what’s wrong with it.

Advertisements

Brownback’s Tax Cuts and Migration Claims

Sam Brownback claimed that the tax cuts he passed in 2012 would compel 35,000 people to move to Kansas. This isn’t population growth (aren’t people turned on by high taxes?), but specifically migration.

I don’t think Sam Brownback believes he’s an evil guy who lies about things for fun, so I’ll give him the benefit of the doubt and assume that somewhere in some time series that he has access to he had good reason to believe in his tax cuts. More specifically, that there’s a case in publicly available data in which cutting top marginal income tax rates while doing nothing to offset the cut yields a huge influx of migrants to the low top tax-rate utopia. I don’t know that I’ll find anything, but I’ll do my best. (Also, not bothering with the supposed budget surplus and huge economic growth the tax cut was supposed to produce. That’s been handled in enough places already.)

The short answer turned out to be, if you don’t think too hard at the numbers, there’s a good reason for Brownback to believe that, net, people would move to Kansas more often than move out of Kansas in the years following his tax cut. I looked at each state that had a top marginal income tax rate cut followed by four years without another such cut to see if there was a naive reason to believe in Brownback’s migration story, and the results were sort of mixed. Simply, each state that qualified had positive net migration over the four years after which it passed its tax cut, but the migration patterns start to look pretty strange when you look at geographic variation.

First, the simple news. Here are1 the net migration figures for each state and tax cut year combination:

State Years Net Migration
Vermont 2001 774
Iowa 2008 1,029
Michigan 2005 913
Kansas 2008 1470
Utah 2008 957
Hawaii 2002 807
Rhode Island 2002 700
Nebraska 2008 765
Arkansas 2005 1,634
Massachusetts 2002 409
District of Columbia 2001 1,304
Maryland 2002 & 2006 4,087
Idaho 2001 949

That’s good for our good buddy Sam! Look at all of those positive numbers! But I have to urge caution. First, people move for a lot of reasons. The census question on why people move (2012 to 2013) showed some of the reasons and some of the ways they interact. “Top marginal income tax rate” wasn’t one of them,  but it doesn’t really need to be. Second, if top marginal income tax rate were a strong motivating factor for people to move, there’s a decent-sized cohort of states that have no income tax, which would make marginal reductions in the top income tax rate less appealing. For the tax rate to be the thing that pushed people over the edge, the claim has to be that for 765 people, from 2008 to 2011, holding all other reasons for moving to Nebraska fixed, the 1.61 percentage point decrease in tax rate on the next $1,000 earned over $1,500,000 (based on NBER TAXSIM methodology) swayed their choice. It’s possible to check the income of those who moved to Nebraska in this time period, but I haven’t done so. Regardless, I don’t think they were all millionaires.

Third, keeping in mind the second note of caution, the geographic patterns are sometimes really weird.

Colors here are:

  • Darkest red: at or above 90% of the maximum net migration to the state in question
  • Darkest blue: at or below 90% of the negative of the maximum net migration to the state in question
  • White: within 10% (positive or negative) of the maximum from zero
  • Black: indicates which state is being shown2

It makes sense that a lot of people moved from California, Florida, Texas, and New York to other states when there was positive net migration. Whatever factors were driving that net migration were going to drive more total people from these four very populous states, if only because there were more people possibly to drive. This is reasonable to believe unless you look at Michigan’s 2005 tax cut, which overall preceded positive net migration, but had large negative net migration to both Texas and California, but large positive net migration from Florida. You might claim that these populations are in some way qualitatively different, but then you’d have a lot of similarity to explain in the other maps.

Also, sometimes closeness seems to be the most important factor for where people seem to be moving, in which case we might think that people’s lives wouldn’t be that uprooted if they moved for a better top marginal income tax rate (see Idaho 2001, Kansas 2008, Maryland 2002 and 2006). This isn’t strictly reliable though, as Arkansas’s pattern of states with large in- and out-migrations is all over the place. Additionally, why did so many Kansans who left after the 2008 tax cut bypass Oklahoma for Texas?

Is there anything here? That’s unclear. There are counterexamples to any consistent narrative I’ve thought of lazily to throw at the maps, and I’m sure they’d change slightly with different cutoffs. Additionally, there are further tests I can do: checking net migration to neighboring states in the same periods, checking county-level net migration to and from states after tax cuts (in the spirit of Arin Dube’s minimum wage work), actually doing the data cleaning and lit work to estimate some sort of regression model.

As usual, all code available on github, with one caveat: ACS dataset I started with was 1.7gb, which is larger than github will let me upload. If you want the data, I’ll provide IPUMS instructions and the sql code I used to create the tables.

1On a 1% sample ACS scale, so I think multiply by 100 if you want to compare to a state’s initial population? I’m still unclear on this.
2Except in Michigan’s case, where I think I broke something in the code that handles the polygons that represent the shapes. Probably an upper and lower peninsula problem. Might fix later. I totally fixed Michigan.

 

Also I think I’m obligated to drop these two citations here as a precaution:

Steven Ruggles, J. Trent Alexander, Katie Genadek, Ronald Goeken, Matthew B. Schroeder, and Matthew Sobek. Integrated Public Use Microdata Series: Version 5.0 [Machine-readable database]. Minneapolis: University of Minnesota, 2010.

Feenberg, Daniel Richard, and Elizabeth Coutts, An Introduction to the TAXSIM Model, Journal of Policy Analysis and Management vol 12 no 1, Winter 1993, pages 189-194. http://www.nber.org/~taxsim.