White Hills Loan 13minpaydayloans.com White Hills Loan 13minpaydayloans.com

Consistent with findings in Presimetrics, the book I wrote with Michael Kanell which will be released in August, I’ve had some posts whose results contradict standard economic theory. In some cases, readers have insisted that the results must be some sort of anomaly. Perhaps the biggest offender is a graph which appeared in this post. The graph shows growth rates in real GDP per capita by Presidency, where each President is color coded by whether he increased the tax burden (in this case defined as federal government revenues as a share of GDP) or decreased it:

Figure 1

The graph shows that Presidents who cut the tax burden produced slower growth, on average, than Presidents who increased the tax burden. For many people, this doesn’t make sense at all. (An explanation for why these results show up is provided here. Now, I’ve already some of the objections that have been raised to this, mostly in private or in comments at the Angry Bear blog. In fact, the graph above by itself answers one of the objections – I was told many times that FDR only produced faster growth because the economy accelerated during World War 2. Thus, the graph only shows FDR’s results through 1938, which avoids the war, the build-up to the war, and even Lend Lease.

Another criticism is that somehow the fact that I’m assuming that Presidents have an effect on the economy is the problem, and that a better way to do this is to look at the business cycle. But I’ve had posts looking at the business cycle, and increasing tax burdens doesn’t look all that much better as an economic strategy across the business cycle either. For instance, consider the following graph, one of several fairly damning graphs I posted here and here:

Figure 2

If cutting the tax burdens is the right prescription during a recession, it isn’t evident from the above graph.

I’ve also been accused of cherry-picking, though I’ve gone as far back as the data allows, and on most posts on this subject, I’ve actually chucked the WW2 years. In addition, I’ve noted that throwing out outliers doesn’t change results materially. But what if the last eight decades have all been an anomaly? After all, shouldn’t we consider the “Roaring ‘20s,” a period which every textbook tells you was a period of rapid growth. After all, such intellectuals as Glenn Beck, Thomas Woods, and Amity Shlaes are quick to assure that the prosperity of the 1920s was due to tax cuts.

Unfortunately, the NIPA tables don’t go that far back, so we don’t have actual data on real GDP per capita (or the tax burden). But I’ve done my best to examine that claim; the following graph, which first appeared here, shows the top marginal tax rates and the periods (shown in gray) when the economy was in recession.

Figure 3

While the 1920s was, indeed, a period when marginal tax rates were reduced, it was a period of recession followed by recession followed by recession followed by the Great Depression. The longest consecutive months spent outside of recession during the 1920s was 27 months! Two years and a quarter. In fact, the economy was in recession (if not outright Depression) a full 44% of the time during the 1920s. If these were roaring years, those roars were extremely short-lived.
Which moves us to the next issue – I’ve been criticized for focusing on the tax burden rather than the marginal tax rate, the exception being in periods where the tax burden is not available. Frankly, of all the criticisms, that one seems especially weak. For those with enough income, the marginal tax rate is as much a fiction as the MSRP on a car; Warren Buffett’s offer of $1 million dollars to anyone on the Forbes 400 list who could prove they pay a higher share of their income in taxes than their secretary remains untaken.

Moving on to the next criticism… I’ve been told my interpretation of the above graph is wrong – it is not so much that higher tax burdens are correlated with faster economic growth, but rather that administrations that produced rapid economic growth tended to feel they could raise tax burdens, and that administrations suffering from poor growth kept tax burdens low to try to remedy a bad situation.

I dealt with that issue in recent posts by grouping the periods from 1929 to the present into eight year administrations, where possible. Those administrations were made up of the eight year terms of Presidents who served two terms (or in FDR’s case, the first two terms only). Added to those were eight year periods in which a Vice Presidents took over for a President who died or otherwise left office. For each of those eight year terms, I created the following graph . It shows the change in the tax burden in the first two years of each administration along one axis, and economic growth on the other axis:

Figure 4

Clearly, economic growth in years 3 through 8 cannot explain changes in the tax burden in earlier years unless one assumes time travel, clairvoyance, or one heck of a coincidence.

And speaking of coincidence, we arrive at another common complaint: there simply are not enough observations to reach a conclusion of any sort. Left unstated, of course, is that though the tax cutting Presidents had the lousiest economies, and that (as per graph 4) tax cutting led the economic growth, somehow a supposed lack observations validates the idea that lower taxes does produce faster economic growth.

Now, those who complain about the lack of observations generally insist that a) I don’t know the first thing about statistics and b) you need 30 or more observations to reach a conclusion. Now that critique dates back at least three years, having been made by an anonymous blogger for the Economist who I understand is now known as Megan McArdle, and my answer (to point b.) back then is as good of an answer as any:

Which is what degrees of freedom are for… Maybe there’s something wrong with the textbooks on my shelf, but the t distribution tables in the back of those textbooks have as few as 1 (one) degree of freedom. When the degrees of freedom are low, the t-statistics has to be really high in order in to reject H0. Or something like that – what do I know?

Allow me to explain. If there are a large enough number of observations to work with, it is possible to find a statistically significant difference between two things (events, peoples, outcomes, whatever) that at first glance or from a distance look very similar to the unaided eye. However, if there are a very small number of observations, then differences have to be larger and more obvious for them to be statistically significant. Consider three medications to extend the lives of patients with a specific type of cancer, where two have obtained FDA certification and the third was cooked up by the creepy guy who lives two houses down and uses cat puke as an active ingredient. It might take hundreds of observations to tell which of the first two medications is more effective, but it shouldn’t take very many to tell how well the third one compares.

And while in the past I sometimes decided to answer this question by running a t-test or some non-parametric test, it always seems to lead to questions about the assumptions by people who clearly never ran a hypothesis test in their lives but have one or another political point to defend to the death. So let me try something else – an argument by analogy. Consider the graph below.

Figure 5

If such a graph came from a study comparing outcomes of medications, where patients were assigned a medication but otherwise told to go about their daily business, there’d be no argument that, at least as a first approximation, there’s no reason whatsoever to assume that Medication 2 was more efficacious than Medication 1. And if the disease in question was a particularly rare one, and the graph above represented the testing performed on every known sufferer since 1929, most of us would be appalled if a doctor decided to treat the next sufferer with Medication 2. At the very least, we would assume that the burden of proof going forward should lie not with the proponents of Medication 1 but rather with the supporters of Medication 2, whether we understood the mechanisms by which either of these pharmaceuticals worked (or purported to work) or not.

And yet, this graph is identical to Figure 1, except that I changed the title and some labeling.

But there is another problem with the small sample objection. See, there are many ways to test whether there has been a negative correlation between tax burdens and economic growth, and looking at the national economy is only one of those ways. I’ve also had a number of posts at the Angry Bear blog looking at how states have fared over the years, and there are 50 of those. In fact, that was the topic of the first post I ever wrote four years ago next month. In that post, a comparison of the states, using data from 1990 to 2005 yielded the following conclusion:

Thus, the data doesn’t seem to support the idea that lower taxes are associated with faster growth rates. In fact, the opposite is true, especially for the fastest growing states. One way to interpret this is to conclude that taxes are actually below their optimal rates, and therefore, at the margin, the government is actually more efficient than individuals at converting its spending into growth. Society needs a certain amount of public goods (infrastructure, public health, confronting the Canadian menace, etc.) for businesses to thrive, and perhaps we currently have too little provision of public goods rather than too much.

And the other posts I’ve had using similar state level data have all led to the same findings.

Another problem frequently brought up is that growth is too complicated to be explained by a single variable. We agree, and in the book, we actually provide a model that uses several variables. But be that as it may, it isn’t reasonable to state that while cutting tax burdens produces faster economic growth, that effect gets swamped by opposing forces when you look at the data systematically, whether you’re looking at the performance of Presidents, at the growth during business cycles, or the performance of states. Clearly, if reducing the amount that people pay in taxes is so beneficial to the economy, somewhere that effect would show up. It shouldn’t be overwhelmed by other variables pushing in the opposite direction every time one tried to test it systematically and consistently.

Moving on, we have another little gem – that the performance of the two regimes (tax cutters and tax hikers) is not independent. The argument is this: tax hikers do well because they follow tax cutters who laid the foundation for growth. Tax cutters do poorly because they have the misfortune of following tax hikers who set up the economy for a fall.

This one is particularly easy to hit out of the park. First, note that there is only one tax hiker that is followed by another tax hiker: LBJ followed JFK. And LBJ produced the second fastest growth in our sample, which is to say that simply following a tax hiker is no guarantee of poor performance.

Now, look what happens when you consider only Presidents that followed their tax burden cutting peers:

Figure 6

Notice that following a tax cutting President doesn’t mean one will turn in a poor performance… unless one is also a tax cutting President. In fact, tax cutting Presidents that followed other tax cutting Presidents did worse than tax cutting Presidents who followed tax hikers. Imagine that. It’s almost as if the longer tax burdens are cut, the worse the outcome.

And yes, I included Hoover in the above graph though we don’t have the data to know with certainty that his predecessor, Calvin Coolidge cut the burden since Coolidge is renown as a small government guy. But leave out Hoover, and leave out Obama’s first year, and you still aren’t left with anything other than: In fact, tax cutting Presidents that followed other tax cutting Presidents did worse than tax cutting Presidents who followed tax hikers.
Which leads to the sorriest objection I’ve heard, namely that the American public, the constantly gulled American public, has the ability to reason out the outcome of economic policies on the macroeconomy to near-perfection, at least in 4 year increments. And the way it manifests itself here is this: when the economy is about to sour, we elect tax cutters, who, in turn, manage to limit the scale of the impending disaster.

This, ahem, theory (gurgle, choke) is the efficient market hypothesis on LSD. But it has the advantage of being able to explain pretty much anything. The problem is that it does so by breaking everything down to utter nonsense. For instance, it would indicate that the recent housing bubble and economic meltdown, rather than being a surprise, was actually anticipated on some unconscious level by the American public, and selected for as being much better than the alternative. Ditto the Great Depression. So what was this worse thing that was avoided? Locusts? Famine and pestilence? Billions of furious yetis descending on us from their Himalayan stronghold?

And yet, despite the fact that this story makes a virtue out of nonsense, it still isn’t internally consistent. For instance, if the American public understood that only a series of tax cuts were going to save us from something worse than the Great Recession, then wouldn’t GW have managed to have won the popular vote in 2000 and achieved a landslide in 2004. Conversely, does the fact GW received fewer votes than Al Gore indicate that perhaps the American public did not perceive that really big threat a few years in the future? It’s easy to knock down a story that is built on nonsense.

All of which brings us back to the point of this post. Michael Kanell and I have noted that lower tax burdens are not correlated with more rapid economic growth. In fact, from 1929 to the present (and in the book, we focus on the period from 1952 to the present) administrations that have cut the tax burden have performed worse than administrations that raised the tax burden.

And I think we, together and separately, have answered every reasonable objection that has come up, and even quite a few unreasonable objections to boot. And we’ve done so in a consistent and open manner. In our book and in my posts, we’ve been open and clear about our methods and data sources, and we’ve made an effort to treat the data as consistently and systematically as we were able. At some point, the burden of proof should no longer lie with us, but rather on those who cling to a story that simply is not consistent with the data we have observed in the U.S. over the past few decades. Frankly, I think we’re well past that point.

Tagged with:

23 Responses to “Tax Burdens and Economic Growth – Answering the Objections”

  1. Ryan F. says:

    Wow. Great post. Very thorough. My only concern is that, for a variety of reasons, you may be understating your conclusions.

    • admin says:

      Ryan F,

      Thanks. But getting people to realize that the “truth” they’ve been brought up with isn’t compatible with the facts is a slow process. Most people who have already been through their formative years are not going to accept what we state in the conclusion, and going any further would result in even more resistance.

  2. Casey B. says:

    -Change it.
    -I ain’t changing this. This is the best.
    -Change it.
    -To what? Come on, this is good.

  3. [...] This piece is cross-posted with the Presimetrics Blog. [...]

  4. Ryan F. says:

    Casey B. is absolutely right about what he says in his comment. F people’s resistance. If people are open enough to accept the conclusions you’ve drawn, why would implacable resistance kick in after going a step or two further? Realistically speaking, I fear this kind of book may be a sermon to the choir anyhow.

    I really would LOVE to see something that estimates the long-run return on public infrastructure investment and credits that extra increment of growth back to the President/Congress under which such investments were made. From what I’ve seen, this return may be as high as 30%. Presimetrics 2: Running Up The Score: Calling Time Out With 20 Seconds Left to Go and Possession of The Ball at the Opponent’s 5-Yard Line With A 36 Point Lead!

  5. [...] noted in my last post , one common criticism, that there aren’t enough observations, is mooted by the fact that state [...]

  6. Ben says:

    I know you’ve already done terribly much work, but could you compare across nations? I’d like to see whether the Chicago school Chile outperformed the a comparison nation of the era.

  7. Arne says:

    I find that people prefer peer-reviewed sources over blogs. Can you point me to such a source I can cite for your conclusions.

  8. Zac says:

    You should send this and a copy of the book to the President’s economic advisers.

    I’ve always thought that cutting taxes in a recession or depression doesn’t help at all and now I see, that statistics prove that case.

  9. admin says:


    I’ve been posting for 4 years at Angry Bear and probably half of my posts have come from reader’s suggestions. I’m always happy to follow them, and yours is a good one. However, in this instance, for the near term, I am completely swamped and I have a few other things to work on in the near term so it may be a while before I get to this. My apologies.

    FWIW – one of my advisors, and in my opinion, the finest economist I’ve ever met, was Arnold Harberger. The notion of finding a simple way to get at what happened is a Harberger-ism I’ve been trying to imitate for years.

    But the few facts I’ve seen don’t quite back up what is often said about Chile. Krugman put up a graph (http://krugman.blogs.nytimes.com/2010/03/03/fantasies-of-the-chicago-boys/). And here’s the Marginal Revolution critique of Krugman’s post (http://www.marginalrevolution.com/marginalrevolution/2010/03/krugman-on-chile.html).

    My view… from growing up in South America during that time period (despite having been born in Michigan)… compared to the crazy quilt of policies that the other right wing dictatorships in the region suffered under, Chile’s policies under Pinochet may well have been more rational. But, perhaps because the US’ involvement in Pinochet’s coming to power was a bit more obvious than it was in the arrival of the other military dictatorships in the region, we (the US) had more at stake in its success.

    Just as important, Pinochet’s Chile wasn’t exactly a model of what is now called Chicago style econ, as much as both the left and the right like to claim. Nowhere in Chicago doctrine do you find the government owning the key piece of the economy (copper). And its telling that while the economic face of Pinochet’s Chile Friedman, boots on the ground was Harberger, which means more Project Evaluation and less laissez faire monetarism.

    I didn’t spend much time there, and I was just a kid, but I imagine the closest thing to Friedman’s world (and thus what we would call the Chicago approach today) in South America at the time was Paraguay, which made a living as a smuggler’s paradise from where electronic items went into Brazil and Argentina, and stolen cars came out. Its also just about the last place I would have wished on anyone in South America at the time.

  10. admin says:


    I am not an academic, haven’t had access to the standard academic databases since leaving grad school 15 years ago, and I don’t keep up with recent publications except on a very hit or miss basis as a result.

    Thus, I can’t point you to anything. But that said, I haven’t seen much evidence that anyone is doing what you request. In fact, many of the results we show in the book (and that appear here at this blog) do not in way intersect with what I was taught in grad school.

    We’ve made a point of showing the data in the simplest possible way, and making it easy and accessible for other people to replicate what we’ve done, precisely because the facts don’t always match what is taught to economists and has made its way into public knowledge.

    And yes… we recognize what that sounds like. But unlike the typical crackpot railing against something, we can point to the data.

  11. admin says:


    The problem is that a zillion people try to contact the President’s advisors. The only way they’ll end up seeing this is if the book becomes really successful.

    We did this out of a labor of love – no matter how well the book does, we’re not exactly going to get rich out of this. And our publisher put a lot of work into this too – hiring a graphic artist, and the shear amount of editing they did is very costly. But success will help us spread this message, and each of us have other things we want to get across too. For instance, I have in mind a few other ways to look at data that are also not being used and which can explain a lot. Success at book 1 might buy us the ability to get across some of these other ideas as well.

    All of which is to say – consider this an appeal. If you value these ideas, if you want to see them spread and/or debated, help us spread the word for this book. Tell people you know. Let them download the first chapter.

  12. David Silva says:

    Curious…it is “Common Knowledge” that many of the Carter years were extremely difficult with a high unemployment. What does it mean to have Economic Growth (per your graph), but have high unemployment?

    • admin says:

      David Silva,

      Working off memory, unemployment was high throughout the Carter years, but it was much lower at the end of his term than at the start, though his last year went the other way. The job creation that occurred during his term came in part at the cost real wages – his policy of freezing government wages and encouraging the private sector to follow the same policy was a stupid way to fight inflation, and resulted in the typical wage earner losing a lot of ground.

      As we discuss in the book, the gains in real GDP per capita growth that occurred in the Carter years went disproportionately to those with relatively high incomes – in particular folks for whom (as we phrase it in the book) other people’s wages qualify as an expense. However, unlike Reagan, Carter didn’t have the communication skills necessary to make the folks who were losing ground appreciate that they were getting smaller and smaller pieces of the pie.

  13. Jack says:

    Real GDP per Capita is a meaningless statistic in a mixed economy with huge government intervention. GDP is a good stat for a free market economy, but with big government, GDP is artificial, as it includes government spending.

    This whole post was a useless exercise, I could sum it up like this: GDP includes government spending, so when governments spend, GDP goes up. Congratulations, you found that out.

    But the free-market critique indicts this artificial expansion of GDP. The malinvestment needed to liquidate, not be propped up.

    If an activity only delivers $100 of wealth, but takes $200 to accomplish, it will add to GDP, but it is a wealth loser. And that’s what the stimulus plans are – they will prop up unprofitable activities that add to GDP, and you can trumpet that, but it by no means is economically beneficial.

    Start at the individual level, not with aggregates. Learn Austrian Economics.

    • Mike Kimel says:

      I was wondering how long it would take for someone to bring up Austrian Economics on this blog. But I knew it would take the usual form – an admonition that I should learn something about it.

      Now the issue you raise about GDP is one I’ve had many posts on at Angry Bear, and to which Michael Kanell and I devote a whole chapter in Presimetrics. We point out – for the reason you identified – that we prefer other measures. For instance, real GDP per capita less the change in real debt per capita. Given how infrequently this topic ever comes up, and how many times I mention it, I wouldn’t be surprised if the first time you heard of it came indirectly from me.

      Now, I still use the measure, and we do in Presimetrics, because its so commonly accepted. But because it has problems, we also look at other measures. For instance, this post (http://www.presimetrics.com/blog/?p=105) looks at changes in state & local tax burdens and how they affect the growth of real per capita income. Results are precisely the opposite of what Austrian economists would expect.

      We also dedicate a whole chapter in Presimetrics to the issue of how changes in the tax burden over the length of Presidential administrations correlate with changes in a range of issues, from real median incomes to unemployment. We then lather, rinse, and repeat with a look at how the average tax burden over the length of each Presidential administration correlated with changes in those same issues. In just about every case, there either was no correlation (which would be completely unexpected in Austrian econ theory), or the correlation was precisely the opposite of what would be predicted by Austrian econ theory.

      I’ve also had a myriad of posts (two recent ones – http://www.angrybearblog.com/2010/04/1920s-depression-glenn-beck-thomas.html and http://www.angrybearblog.com/2010/04/1920s-depression-glenn-beck-thomas_19.html) on how the Austrian story doesn’t hold up, even on set pieces like the 1920s.

      In sum – I know what Austrian economic theory says. I also know it is contradicted by the available facts much more so than just about any other school of economic theory out there.

  14. Ryan F. says:

    Start in Outer Space, not on the Surface of the Planet Earth. Learn UFO Economics.

    Most of us ignore Austrian Economics because it is fundamentally wrong (to the point of being silly), both conceptually and empirically. Not because it’s somehow something we haven’t been exposed to.

  15. Ryan F. says:

    As a measure of living standards, GDP/hour worked should be given more emphasis. GDP/capita ascribes no value to leisure.

    Also, Net Domestic Product makes more sense to me than GDP. Economic activity devoted to maintaining the current capital stock doesn’t provide any improvement in living standards. The “bottom line” in financial accounting subtracts out depreciation/amortization. Why shouldn’t we do the same here?

    See http://www.csls.ca/ipm/7/spant-e.pdf

    Also see http://www.cepr.net/documents/publications/productivity_2007_06.pdf for other interesting potential adjustments.

    • Mike Kimel says:


      Sorry not to answer in more detail, but I’m swamped right now. There are a lot of measures of well-being; all have advantages and disadvantages. I’m not a big fan of real GDP per capita, to be honest, but I use it because its the most I can push GDP (which most people buy into) into something semi-reasonable without getting pushback. I can see using GDP/hour for some purposes (e.g., for some comparisons with Europe), but for most purposes I imagine the amount of explaining you’d have to do might overwhelm your gains to using a more nuanced measure.

      Its not enough to do the work – you have to be able to get people to accept what you’re doing.

  16. Steve Roth says:

    For those who are interested, I’ve pulled quite a lot of cross-country comparison, concentrating on advanced, prosperous countries to make for a more apples-to-apples approach.

    Instead of giving a bunch of URLs, start with this post and follow the “related posts” at the bottom.

    Europe vs. US: Who’s Winning?

    Conclusion is the same as Mike’s: lower tax burdens are not correlated with faster growth. It’s a myth.


  17. Ryan F. says:

    “This whole post was a useless exercise, I could sum it up like this: GDP includes government spending, so when governments spend, GDP goes up. Congratulations, you found that out.”

    I know this thread is stale, but if I correctly recall intro macro from 9 years ago:

    GDP = C + I + G + (X-N)

    To the extent that government spending increases by virtue of a tax increase, the increase in G will simply result in an equivalent decrease in C and/or I. So there’s no “artificial expansion” in GDP. Same is roughly true for a government increase in spending by virtue of borrowing. The increase should just move some consumption over to saving (cause the increase in the return to saving private saving will induce a substitution effect in favor of saving) and therefore move some I over to G (crowding out). So again, there’s no artificial expansion. I think.. am I missing something here?

Leave a Reply

7 - six =