Everyone “knows” that the corporate income tax is a mess. Ask any company. They pay too much in corporate income tax, face rates higher than in any other OECD country, and are just following the law when they use tax havens to keep profits eternally deferred from taxation and to perform general sleight-of-hand.
Don’t believe a word of it. While some economists believe we shouldn’t tax corporations at all, the corporate income tax (CIT) is a necessary backstop to the personal income tax (PIT). With no CIT or a rate lower than the PIT, individuals have an incentive to incorporate their economic activities so they aren’t taxed on them, or are taxed less. Needless to say, this is something an average wage or salary worker would not have the ability to do. This is another area where we have one tax law for the 1%, and different rules for the rest of us.
I had my hair cut last week. It’s a big event as it happens about twice per year. While there I always get into political conversations with the lady cutting my hair. This time, as often it was the economy. Her position still is that the individual citizens collecting welfare are effecting her income. We’ve discussed this before. So, I used my simple math of $100 dollars and 100 people and 9% to the 1 person and the remaining 99 splitting what remains. I then note the current split of 24% to the 1 and the 99 splitting what is left. Easy?
Unfortunately, it did not resolve the issue. Her question was: You don’t think the welfare people are effecting this? So, I asked her to explain to me just how someone collecting welfare (we are not talking corporate welfare) could be the cause of her lack of share of the overall income? This is not a laughing matter. It shows just how strongly the conflation has been made of associating the indigent population as the cause of ones financial condition, namely the money in their pocket.
This got me thinking. Maybe numbers are just not enough. Maybe using 100 dollars and the fact that after the 1 gets about $9 as of 1978 the other 99 get $0.92. Shift the split and it’s $24 vs $0.77. How is that relative to a median income of today? And here I’ve been thinking I was keeping it simple.
So, I have upped the numbers. $10 million. 100 people. This produces the following:
The 1 Inc.
The 99 Inc.
That is quite the shift of the 1’s income. In fact it is a 166.7% increase simply due to changing how the pie is cut. The rest of the people, the 99 get 16.5% less. No one worked harder, no one worked less. We just cut the pie differently.
Mike’s post here got me thinking. I’ll telegraph my conclusion. He dramatically understated his case.
You can see the long range view of nominal and inflation adjusted GPD growth in Graph 1 of FRED quarterly YoY percent change data.
Graph 1 YoY growth Nominal and Inflation Adjusted GDP
Nominal GDP Growth was in a secular up-trend from 1960 through 1980. However, inflation adjusted GDP growth quickly peaked after the Kennedy-Johnson tax cut, reaching a maximum value of 8.5% in Q4 of ’65 and Q1 of ’66. It then dropped dramatically for the next four years. This peak value has been matched only once since: in 1984, during a sharp rebound from the double dip recession of 1980-82.
Since then, in the wake of numerous tax cuts, the rate of GDP growth has been anemic. To get a look at the rate of growth, I took an 8 year average of the annual percent change data presented above, and then plotted a 5 year rate of change for that data. This is essentially the 2nd derivative of GDP, or GDP acceleration, as shown in Graph 2.
Graph 2 GDP Acceleration
Inflation Adjusted GDP acceleration peaked in Q3, 1966. Fueled by the inflation of the 70’s, NGDP acceleration stayed high until Q1, 1980, then plummeted for 9 years. It has been relentlessly negative since.
Inflation adjusted GDP acceleration has not done quite as badly in this disinflationary era, but has been below zero more than half the time since 1970. This is a little bit worse than coasting.
This all might seem a bit abstract, but the message is clear. If tax cuts were good for the economy, then GDP growth would be increasing. In other words, acceleration would be positive and most especially so after a tax cut. The data is not consistent with this notion.
Clinton’s famous tax increase preceded increased GDP growth by either measure, and an upturn in acceleration. The Bush tax cuts preceded decreasing GDP growth.
I’m not going to get into a correlation vs causation discussion. I’ll simply say that tax cuts over 5+ decades have been an utter failure at stimulating real economic growth in any inflationary environment. Since the real world data correlation is counter to the received conservative wisdom, it might be worth trying an anti-conservative approach.
It might also give the NGDP targeting enthusiasts something to ponder.
I’ve been writing about the relationship between tax rates and growth since I started blogging in 2006. A lot of those posts have focused on the quadratic relationship between tax rates and growth. That is, it turns out that if you take US data going back to when the BEA started keeping track, 1929, you can easily build a model of the following form:
% change in real GDP from t to t+1 = a + b*Top Marginal Tax Rate at time t + c* Top Marginal Tax Rate squared at time t
I have modestly referred to that as the Kimel curve. Now, it turns out that for most variations on that theme I’ve come up with, b is positive, c is negative, and both are significant at the 5% or 10% level. That allows you to find a top marginal tax rate that maximizes growth… which turns out to be somewhere between 60% and 70% depending on how the model is specified.
In this post I want to address a few criticisms by running two additional regressions with more or less the form. Parts of this may get a bit wonky but I’m going to keep it so that even if you’ve never done any statistical analysis, hopefully you’ll be able to follow the outcomes.
In the first regression, I’m going to account for a few additional facts: 1. By going with every single observation the BEA produces, I’ve been accused of “cherry picking.” So I’m going to throw in a dummy variable for Hoover. 2. I’ve been told the only reason growth was so quick during the New Deal was that there was a bounceback effect from the Great Depression… so I’m throwing in a dummy variable for FDR’s peacetime years (i.e., 33-41). 3. I’ve been told WW2 biases the results…. so there’s a third dummy for 1942-1944, the fast growing years in WW2. 4. I’ve also included two demographic variables: the percentage of Americans 35 to 44 and the percentage of Americans 45 – 54. The latter group tends to be the highest income group these days, but in an earlier era more focused on manual labor, those 35 to 44 might have been higher paid. 5. For grins, I threw in a dummy variable which is equal to 1 if the President is a Republican and 0 otherwise.
So… here’s what it looks like:
So what does it all mean? Well, this set of variables explains about 43% of the observed variation in growth rates over the period for which we have data (see the adjusted R2). There’s obviously room to improve the model, variables I’m not accounting for, etc.
The percentage of Americans 35 to 44 has a positive coefficient and is almost significant at 10%. We’re almost at the point where we’d be comfortable saying as that percentage increases, growth increases. The percentage of Americans 45 – 54 has a negative coefficient, but isn’t close to being significant.
Not surprisingly, the Hoover dummy is associated with economic shrinkage, FDR’s peacetime period is associated with positive growth, and 1942 – 1944 is associated with even faster economic growth.
The Republican dummy is not significant – any difference in the growth rate observed between the two parties can be explained by other factors. Which other factors?
Well, the top marginal tax rate and the top marginal tax rate squared are both significant – the former is positive and the latter is negative, which means they trace out the desired upside-down-U shape.
Oh… and the top of the curve happens when tax rates are at 64%. That is, the fastest growth rates seem to occur when the top marginal tax rate is around 64%. Now, I’ve had post after post on this topic, and the top of the curve always seems to occur in more or less in the same place. It isn’t a coincidence folks.
I’ll post results of the second regression in my next post in the series. That regression will focus on the period since Reagan took office and thus will only include data from 1981 to the present. What does it say? Well, a hint: if you don’t like the results shown in this post, you won’t be happy about that one either. But remember, I’m just the messenger. The data is what the data is, and if it isn’t showing what you think it should, its up to you figure out what’s wrong with the analysis or with the data, to pontificate wisely and inaccurately, to ignore the evidence, or to change your mind.
If anyone has a line on a good inequality series with annual data that goes back to 1929, please let me know. I’d like to drop it into the model. I’d also love a good proxy for regulation. Don’t be afraid to offer other suggestions for data to drop into the mix are welcome too. I’m like a DJ, I take requests, but it helps if you can point to whatever data you want me to use.
As always, if you want my spreadsheets drop me a line at “mike” period “kimel” (note – one m only in my last name!!!!) at gmail.com.
Thanks to Bill McBride for pointing toward the demographic data and m. jed for suggesting its use.
People always talk about the Laffer curve, but have you ever seen it estimated? Have you ever wondered why you don’t? If you’re a quant guy, you know the answer to that. Because if you’re a quant guy, at some point curiosity must have gotten the best of you. That means you pulled out some data and you plugged it into whatever piece of software happened to be handy. What happened next depends on what sort of a quant guy you are. If you’re the sort that let’s the numbers do the talking, you spotted the joke and probably left it at that. If you have a strong ideological leaning in a certain direction, on the other hand, you might have tried to “fix” it. You tried a few times, failed, and kind of just left it there as something to get back to some time, but no hurry because your ideology tells you what the answer should be.
Today, by coincidence, I got two e-mails asking me about the Laffer curve. And it occurred to me… maybe someone should let non-quant people into the joke. Because the only people really discussing it are those who are driven by ideology, whereas it should be afforded the Hauser’s law treatment.
So here’s how it works. Putting numbers to the Laffer curve pretty much comes down to estimating:
(1) tax collections / GDP = A + B*tax rate + C*tax rate squared + some other stuff if desired
A, B, and C are estimated statistically using a tool such as regression analysis.
If you plug in numbers, and find that B is positive and statistically significant and C is negative and statistically significant, then it turns out that you can trace out a quadratic relationship between tax collections / GDP and tax rates. i.e., tax collections / GDP is a function of tax rates that looks like an upside down U. If you increase tax rates when tax rates are “low,” growth will increase. On the other hand, to increase growth when tax rates are “high”, you have to decrease tax rates.
When you have such a shape, you look for the top of the upside down U and there’s your maximum.
So I started with the obvious:
(2) tax collections / GDP = A + B*tax rate + C*tax rate squared
In other words, the simplest version of (1) possible. I plugged in data. That would be current federal tax receipts, line 2 from NIPA table 3.2, divided by GDP, from the BEA, and the top marginal tax rate from IRS’ historical table 23. You can go all the back to 1929—that’s when the GDP and current federal tax receipts begin.
The problem is… the data isn’t quite amenable to shoehorning into the desired shape. The fit of the model sucks, B is negative, C is positive, and neither coefficient is significant at the ten percent level.But they aren’t so far off either.
All that together means that maybe, just maybe, a slightly better specified model might do the trick. The simplest solution… find another variable that has some explanatory power and throw it in. Well, I’m supposed to be on a hiatus from blogging, so I don’t want to spend a huge amount of time at this, but it occurs to me that year is probably such a variable. There’s a good chance that over time, tax collection has become a bit more efficient.
So I reran (2) as follows:
(3) tax collections / GDP = A + B*tax rate + C*tax rate squared + D*Year
Here’s what the results look like:
B and C have the wrong sign. That means you don’t get an upside down U, you get a U. Here’s what it looks like when graphed:
The low point in tax collections happens to be about 32%. In other words… if the top marginal tax rate is below 32%, cutting it further will raise tax revenues. On the other hand, if the top marginal tax rate is above 32%, to boost revenues you have to raise tax rates.
Now this is quick and dirty, and it has boundary issues (i.e., 100% tax rate collects more than 99% tax rate – would it really? well, the model is extrapolating because its never observed tax rates of 99% or 100% in the wild). I should also throw in a few more variables to improve the fit. Worse, there’s autocorrelation. That means the error terms are correlated. The correlation between the residuals at time and the residuals at time t+1 is 75%. That in turn violates one of the assumptions of OLS regression analysis. Its fixable, but its also ignorable for our purposes since what it means is that the coefficient estimates are probably “correct” but merely less significant than they appear. Regardless, you won’t get anything that bears even a remote resemblance to what you hear from the crowd who perennially cites the Laffer curve so authoritatively.
Which brings up another piece of the joke. In the end, tax collections don’t matter. Its nobody’s goal to maximize tax collections. Taxes only matter because they pay for certain government services. They also take money out of our pockets. So there’s a tradeoff. But we’re made better off if the government services taxes pay for generate more value than they cost us. And at least to some extent, you can measure that by whether they generate more growth than they cost us.
Now, it turns out that the optimal tax rate for growth is easy to calculate. The data cooperates very nicely. There is a relationship, an easy to estimate curve which I’ve modestly called the “Kimel curve.” And the high point in the Kimel curve is somewhere around 65%. Now, the Laffer curve analysis shows us that getting to the level of taxation that produces the fastest economic growth rates would also increase our tax collections… not a bad thing at all in an era of rapidly rising national debts.
Which brings us to the biggest Laffer curve joke of them all: ain’t no way the folks who like to talk about the Laffer curve would support that.
As always, if you want my spreadsheet drop me a line. I’m at my first name (“mike”) period my last name (“kimel” – that’s with one m only!!!) at gmail.
[UPDATE: Graphic title corrected below. h/t Eric Whitaker]
This post is the seventh in a series that looks at the relationship between real economic growth and the top individual marginal tax rate. The first looked at the period from 1901 to 1928, the second from 1929 to 1940, the third from 1940 to 1950, the fourthh looked at 1950 – 1968, and the fifth from 1968 to 1988. Because the Reagan era is so pivotal in the American psyche, it was also covered again in the sixth post, which looked at the period from 1981 to 1993. This post will look at the period from 1988 to the present.
Before I begin, a quick recap… both the 1901 – 1928 period and the 1929 – 1940 failed to show the textbook relationship between taxes and growth. In fact, it seems that for both those periods, there was at least a bit of support for the notion that growth was faster in periods of rising tax rates than in periods when tax rates were coming down. It is worth noting that growth from 1933 to 1940 was generally quite a bit faster than at any other peacetime period since data has been available, both on average and for individual years. Not remotely what people believe, but that’s what it is.
In the 1940 – 1950 period, we did observe slower economic growth following a tax hike and faster economic growth followed a tax reduction. However, that happened when the top marginal tax rate was boosted above 90%.
Interestingly enough, though the so-called “Kennedy Tax Cuts” are often used as one of the prime exhibits on the benefits of cutting taxes, a look at the 1950 – 1968 period yields no such conclusion. Growth rates were already rising before the tax cuts occurred in 1964 and 1965, reached a peak when the tax cuts took place, and started shrinking immediately afterwards. The other period that is always pointed to as evidence that tax cuts spur growth is the Reagan years, which showed up in the 1968 – 1988 and the 1981-1993 posts. It turns out that put into context, the Reagan years produced one year of rapid but not particularly extraordinary growth a few years after tax cuts began. That’s it. In fact, its worse than that… during the Reagan Bush 1 years, aside from that one good year, growth tended to shrink as tax rates were slashed.
Real GDP figures used in this post come from Bureau of Economic Analysis. Top individual marginal tax rate figures used in this post come from the IRS. As in previous posts, I’m using growth rate from one year to the next (e.g., the 1980 figure shows growth from 1980 to 1981) to avoid “what leads what” questions. If there is a causal relationship between the tax rate and the growth rate, the growth rate from 1980 to 1981 cannot be causing the 1980 tax rate. Let me stress this point again as I’ve been getting people e-mailing me to tell me I’ve got the growth rates shifted a year. That is correct, and is being done on purpose (and is shown on the graph labels). To avoid questions of causality, the growth rate in year X used in this post is the growth rate from year X to year X+1. And when I say “to avoid questions of causality” – you’d be amazed at how many people write me when I don’t do this and insist that sure, higher tax rates seem to be correlated with faster growth, but that’s because when growth is faster governments feel more willing to charge higher tax rates.
So here’s what the period from 1988 to the present looks like [update: Graphic Title Corrected; h/t Eric Whitaker)
Once again, the data fails to show anything resembling the old “lower taxes = faster growth” story. In fact, once again, it kind of looks like things go the other way. The two biggest dips in the graph occur when tax rates are at low points (28% and 35%). The highest tax rates also coincide with the fastest overall growth. But no doubt next week’s post looking at the next period will be the one that finally shows what everyone believes is there. Oh wait, we’ve run out of years.
Now, I’m sure someone will bring up the fact that there was a tech boom and the internet in the late 1990s. And no doubt there was some of that. But that doesn’t explain why only once did the graphs appear to show that cutting tax rates correlates with faster economic growth, and that one time occurred in the middle of WW2 during what was essentially a command economy when tax rates were above 90%. Talk about a special case. Conversely, most of the other graphs that we’ve seen in this series have not shown any relationship between tax rates and economic growth. And then there were a few, such as those showing the Reagan era, that seem to at least suggest that faster growth was more likely when tax rates were higher. None of this matches what we hear in the liberal (ha ha) media. None of this matches what I see in econ textbooks. It doesn’t match what I read in economics journals. But anyone, and I mean anyone, can do these graphs. Not sure many people can replicate Barro.
Next post in the series… what it all means.
As always, if you want my spreadsheets, drop me a line. I’m at my first name which is mike and a period and my last name which is kimel (note that I’m not from the wealthy branch of the family that can afford two “m”s – make sure you only put one “m” in there) at gmail period com.
This post is the fourth in a series that looks at the relationship between real economic growth and the top individual marginal tax rate. The first looked at the period from 1901 to 1928, the second from 1929 to 1940, the third from 1940 to 1950. This week we look at 1950 – 1968.
Before I begin, a quick recap… both the 1901 – 1928 period and the 1929 – 1940 failed to show the textbook relationship between taxes and growth. In fact, it seems that for both those periods, there was at least a bit of support for the notion that growth was faster in periods of rising tax rates than in periods when tax rates were coming down. In the 1940 – 1950 period, we did observe slower economic growth following a tax hike and faster economic growth followed a tax reduction. However, that happened when the top marginal tax rate was boosted above 90%.
There were also a few other findings that might be surprising given the poor acquaintance Americans have with data. For example, the so-called Roaring 20s were a period in which the economy was often in recession. The New Deal era, on the other hand, coincided with some of the fastest economic growth rates this country has seen since reliable data has been kept. Additionally, rather than leading to faster economic growth, the economy actually slowed, a lot, during World War 2.
Real GDP figures used in this post come from Bureau of Economic Analysis. Top individual marginal tax rate figures used in this post come from the IRS [link fixed]. As in previous posts, I’m using growth rate from one year to the next (e.g., the 1980 figure shows growth from 1980 to 1981) to avoid “what leads what” questions. If there is a causal relationship between the tax rate and the growth rate, the growth rate from 1980 to 1981 cannot be causing the 1980 tax rate.
Now that the preliminaries are done, if I was following the same pattern I followed in other posts I’d post a graph showing real GDP growth rates and tax rates. But this time I’m going to hold off on that graph for a few more paragraphs. Instead, I want to discuss an extremely pervasive myth about the period, and how that affects our understanding of economic of the era. The myth involves the so-called Kennedy Tax Cuts. Ask most economists and they’ll tell you: the economy was in the doldrums until Kennedy cut taxes from 91% to 70%. After that shot in the arm, growth took off like a shot. There is a second myth, but it is more confused: the myth of the idyllic 1950s. That one says that there was rapid growth in the 1950s because the US had little economic competition, what with the rest of Free World haven’t been destroyed during World War 2. It doesn’t reconcile that well with the Kennedy tax cut myth since, of course, for the Kennedy tax cuts to pull the economy out of the doldrums caused by a 91% tax rate, the economy has to be in the doldrums rather than idyllic when tax rates are 91%.
So let’s look at what happened. The graph below shows growth rates for the period. (I’m not including tax rates quite yet… that comes later.)
Well, growth rates in the 1950s weren’t steady. There were a lot of ups and downs. During three years in the 1950s, growth rates equaled or exceeded those in Reagan’s best year. But it was also a period in which in which there were two recessions (and two more between 1945 and 1950, and another one in 1960) and the economy actually shrunk in two different years. The 1950s can’t be characterized as idyllic nor as the doldrums.
Now, there is a point in the graph that seems consistent with the idea that Kennedy did something that was a game changer. Kennedy took office in January 1961, while the economy was going through the downward part of the cycle we had seen repeated since 1950. And then… instead of the economy continuing on its downward trajectory, growth picked up and accelerated (with one blip), staying (mostly) above 5% through about 1965. LBJ of course, took office when JFK was shot on November 22, 1963 so in this version of history, presumably, the end of the Kennedy boom came about when LBJ started inflicting socialism on us. The only fly in that ointment to that story, of course, is that while hitting the same growth rate as Reagan achieved in his best ever year was not uncommon in the 1950s when the top marginal tax rate was 91%, it stopped happening after JFK.
Which is all well and good, except for one detail apparent in the graph below which shows both the growth rate and the tax rate:
As figure 2 shows, the cut in the top marginal rate occurred in 1964 (91% to 77%) and 1965 (77% to 70%). Yes, the Kennedy tax cuts were pushed through by LBJ after Kennedy was dead, and growth rates had already been fast and getting faster for several years before they occurred. Worse, real growth in the 1960s reached their peak – the acceleration that had begun years earlier all of a sudden came to a halt – when the tax cuts occurred. For the remainder of LBJ’s term, growth remained strong, but not as strong as it had been earlier. For instance, the average of the annual growth rates of the 1961 to 1962, 1962 to 1963, and 1963 to 1964 years when tax rates were 91% was 5.41%. The average from 1966 to 1967, 1967 to 1968, and 1968 to 1969, after the tax rates were dropped was 3.49%. (Yes, I know, in his last year LBJ raised tax rates back to 75.25%, but even then it was well below the 91% before the tax cuts.)
This is not, repeat, remotely consistent with the myth I keep hearing about the Kennedy tax cuts.
So far in this series… it seems the evidence has been at least weakly against the idea that tax cuts lead to faster economic growth in the 1901 – 1928, 1929 – 1940, and 1950 – 1968 periods. The 1940 – 1950 period does seem to behave consistently with that notion, though it is worth noting that it happened when tax rates were above 90%. Next post in the series: 1968 – 1980.
As always, if you want my spreadsheets, drop me a line. I’m at my first name which is mike and a period and my last name which is kimel (note that I’m not from the wealthy branch of the family that can afford two “m”s – make sure you only put one “m” in there) at gmail period com.
The real story of Michelle Bachmann’s “win” in the Iowa straw poll (not to be confused with the Iowa primary) isn’t that she got just over 4,800 votes—it’s that she paid for 6,000, proving at least 1,200 Iowa straw pollers are smarter than most of the reporters covering her “win.”
Late to the party mention: The Kauffman Institute’s Blogger Survey results are here (I hope).
Robert (at least on his FB feed) is trying desperately to be nice to Matt Yglesias. I’m not, since Matt “I’ve never attended a public school so I know what’s wrong with them” Y. continues to fool himself about “the need for education reform” and refuses to pay attention to the research that shows most of those “reforms” his hedge-fund buddies are championing have been tried and failed. Jersey Jazzman does the heavy lifting here and (especially) here, while Bruce Baker notes the core of the Charterist argument.
Want a clear explanation for why people become writers or, if they don’t write well enough, bloggers? Jason Albert in, of course, Slate explains his own ego.
Kevin Drum writes “The GOP leadership has released “Tread Boldly,” a guidebook for Republican members of congress during the summer recess, and it includes a whole section called “Spending Restraint Solutions for Discussion.” Finally, we’ll get some details! So here they are:
‘Canceling unspent “stimulus” funds, saving up to $266 billion …’
Being hep and up to date with the interwebs, the Republicans posted a pdf.
My point is that they just declared their willingness to increase the taxes paid by over 95% of working US families. There is no way they can get “up to $266 billion” by cancelling other parts of the stimulus and not cancelling the tax cuts.
The payments include extended unemployment insurance (I’m not sure that’s the only payment). Total additional government consumption (the standard word for government investment too) was $ 265 billion, so one can’t save $266 billion by cutting the un-contracted funds (about $ 50 billion). http://tinyurl.com/383zez
Of course the Republicans would like nothing less than to have to explain that the ARRA included tax cuts for over 95% of working families in the USA and to explain that they want to eliminate those cuts (as all currently Republican legislators not from Maine voted against those tax cuts).