Recently, I coauthored an essay with Grant Casteel that was published by the Show-Me Institute. In that paper, we specified a model of the state economy and conducted a simple experiment. Our ultimate goal was to compare two different tax structures. More succinctly, which tax structure would do the least harm while raising the same level of revenue? Our results are easily summarized: For most cases, the typical Missourian prefers a broad-based sales tax structure to the current structure that relies on income taxes and sales taxes. The reason is also pretty straightforward: In the absence of the income tax, the state’s economic growth rate increases. Our results indicate that the typical person is willing to forgo some consumption today for faster growth and higher consumption tomorrow, both for themselves and their children.

Our analysis compares the state economy under two different tax structures, holding revenue constant. Over time, the ratio of government revenue to state GDP is constant. The state government runs a balanced budget, so government spending is also a constant fraction of state GDP. It follows that future state government spending will be greater in correlation with a faster economic growth rate. Thus, for those who argue that Missouri needs to spend more on state goods and services, the answer is simple: Choose a tax structure that relies on a broad-based sales tax rather than one that combines an income tax and an exemption-filled sales tax.

In the model economy, in order to achieve revenue neutrality in the first year, the sales tax rate is computed to be 11.9 percent, a figure that several articles have cited. Taken in isolation, this may seem like a radical policy, but it’s important to remember that the people populating this model economy prefer the tax structure in which the broad-based sales tax structure is implemented, replacing the tax structure that combines both income taxes and sales taxes. As with most things, context is everything. In the context of the model economy, the sales tax rate is high — but, to be logically consistent, one must also cite the welfare comparisons. Our results indicate that there is a tradeoff between economic growth and the tax structure, and that the average person prefers a policy that increases the growth rate.

Just to answer the critics, let me explain why we calculated the sales tax rate at 11.9 percent in the baseline economy. In the model economy we created for our analysis, the typical person consumes only 48 percent of their income. In the real world, however, the average person consumes about 70 percent of their income — so, those people populating the model economy choose a tax base that does not match well with actual observations of real-world consumers. Because the tax base is so small in the model economy, the revenue-neutral sales tax rate is higher than it would be in our real economy. If, on the other hand, the person living in the model economy consumed the same fraction of their income that we observe in actual consumers, their revenue-neutral sales tax rate would be only 7.6 percent.

To summarize, then, the sales tax rate is higher in our simple model economy because the modeled savings rate is higher than what we observe in the real world. In this economy, and in various permutations, consumers as a group are better off without an income tax, with a higher sales tax instead, and with the resultant higher economic growth.

In a recent Kansas City Star commentary, Saint Louis University economics professors Lisa Gladson and Jack Strauss criticized my Show-Me Institute study of the earnings tax, They claim that there is no statistically significant relationship between earnings taxes and the growth of metropolitan statistical areas (MSAs). They also imply that I made such a claim in my study. In fact, I made no such claim and these authors are mischaracterizing my study. The purpose of this note is to set the record straight on my research. I will here demonstrate that my findings are perfectly consistent with theirs.

Let me briefly review my empirical evidence. I looked at more than 100 MSAs in the United States. The dependent variable I studied was the ratio of aggregate income reported by the U.S. Census for each primary city in that MSA to the aggregate income for the entire MSA. Basically, I measured the size of the city economy relative to the suburban economy. I then estimated a regression in which the city-to-MSA income ratio was the dependent variable and the earnings tax rate was the independent variable. The result was a significant negative correlation; in other words, cities with higher earnings tax rates tend to have smaller economies relative to their suburbs than cities with lower earnings tax rates. This result held both when using the 1990 Census as the data source and the 2000 Census as the data source.

In the article, I argued that this empirical finding was entirely consistent with sophisticated models of business and household locations within local economies. My analysis was grounded in a widely cited paper by Haughwout and Inman (2001). In it, they analyzed a model economy in which people living in a city took the tax structure as given and made consequent location decisions. When dealing with aggregate economic data, even at the city level, economists do not have a laboratory to run their experiments. Facts are extracted from the data — these are the economists’ observations — and economic theory is employed to account for these facts. Other models exist, but the Haughwout and Inman model can account for the many empirical regularities observed in city growth around the country.

Professor Strauss took an alternative approach and asked a different question. He estimated a regression in which the dependent variable is the growth rate of income in an MSA. The growth rate was computed for the period 1969 through 2007. His regression uses at least two independent variables. One is a dummy variable set equal to one for an MSA in which the primary city has an earnings tax, and set equal to zero otherwise. The other independent variable is the income level for the MSA in 1969, the so-called initial income level. The basis for Prof Strauss’ inquiry was the notion of economic convergence. If the coefficient on the initial income level is negative and statistically significant, the evidence indicates that cities with higher initial income levels tend to grow slower than cities with lower initial income levels. The convergence hypothesis follows, because the evidence suggests that cities starting off poor tend to catch up to the initially richer cities. The convergence hypothesis has been applied to cross-country datasets, and is useful for explaining why Japan and Korea — and, more recently, China — grow so fast. The return to capital is higher in these poor countries, and provides an opportunity for them to catch up to those already-rich countries. The convergence hypothesis cannot explain why Sub-Saharan Africa remains so poor. For our purposes, it is not obvious why convergence should apply to MSAs, but I will blog about this lesson more fully in the future.

In Prof. Strauss’ results, the coefficient on the earnings tax dummy is not significantly different from zero after one includes the MSA’s initial income level as an explanatory variable. He concludes that the earnings tax does not explain economic growth. He interprets these findings as indicating that cities across the United States are catching up and not affected by earnings taxes. I would proffer a slightly different interpretation. Metro areas that started off with lower incomes in 1969 are, on average, catching up to cities that started off with higher incomes. His unit of measurement is the MSA, not the city. This is kind of interesting. At first pass, convergence can characterize MSAs across the United States. The more difficult part is why rural areas are not catching up. If convergence can be attributed to low capital in the low-income metro areas, then it seems that rural areas — ones with low capital accumulation — would catch up to high-income urban areas. For me, the nagging problem about the convergence hypothesis is that Rocheport should start looking like Columbia in terms of capital. But Rocheport’s economy does not look like the Columbia economy. Agglomeration, or increasing returns, probably has something to do with this. As I said, I will save this digression for a future blog.

I do not dispute Strauss’s findings; however, he did mischaracterize my research. He asked a different question than I did. I contend that my question is more relevant for the question of earnings taxes. People can avoid the earnings tax by eschewing the political jurisdiction in which the tax is implemented. Insofar as the suburban area is not a perfect substitute for the city area, economic efficiency is lost and the earnings tax is distorting people’s behavior.

Consider the following situation for illustrative purposes. Suppose there are two cities. In City A, the metro area’s income increased at a 1-percent annual rate between 1969 and 2007. However, all the businesses moved out of a city and into the suburbs in 2000. In City B, the metro area’s income increased at a 1-percent annual rate between 1969 and 2007. In both City A and City B, Prof. Strauss’ measure of income growth would be 1 percent. If I further told you that City A had a 1-percent earnings tax and City B had no earnings tax, then according to Prof. Strauss’ unit of measure — the growth rate of income in the MSA — would indicate no statistical relationship between the earnings tax dummy and the growth rate of MSA income.

In contrast, I estimate the regression for city income to MSA income in 2000 and find a negative relationship between the earnings tax rate and the city-to-MSA income. The purpose of this illustration is to point out that his results do not contradict mine. His findings do not render my interpretation of the evidence as faulty. He asked a different question and got a different answer. Thus, a reasonable person could walk away believing both results are accurately depicted. Because we have different units of measurement for the city economy, we are clearly asking (and answering) different questions.

My results were mischaracterized in the Kansas City Star’s recent op-ed by Prof. Strauss. My goal is to properly characterize both sets of results. I am sure that more “teachable” moments will be forthcoming. Let’s proceed with skepticism before we accept any economic interpretation of the results.

On October 17, Judge Richard G. Callahan rendered a decision in the case brought by many of Missouri’s school districts alleging that the State of Missouri does not adequately fund public education. Judge Callahan concluded that the state is meeting its constitutional obligation to spend 25 percent of the state budget on K-12 public education.

Legal proceedings are not cheap. According to an Associated Press article written by David Lieb, two organizing bodies of Missouri’s school districts — The Committee for Educational Equality and the Coalition to Fund Excellent Schools — have spent $1.9 million and $700,000 respectively. In addition, the St. Louis School District spent $600,000. Overall, plaintiffs have spent $3.2 million in trying this case.

At the time the case started, the school districts would have thought of this as an investment. In this context, the return is abysmal. After spending $3.2 million, the additional funding — after enforcing Judge Callahan’s ruling — will be zero. So, from the school district’s perspective, the return is negative-100 percent, so far. Perhaps it is too early to measure the returns. Often, it takes time to realize the gains from such an investment. I cannot accurately forecast how this trial will affect Missouri’s legislature. Hence, it is possible that the school districts will realize significant gains in the future.

What is the likelihood that Missouri’s General Assembly will feel compelled to increase their contribution to K-12 education? In my view, the answer is that they will not. For the sake of disclosure, I should mention that I computed the Legislature’s obligation for this trial, presenting evidence that the state was more-than-meeting its constitutional minimum. Indeed, my independent calculations indicated that the state spent more than 35 percent of its discretionary budget on K-12 education in each of the last three years. Based on my calculations, it is difficult to imagine that the Legislature will feel compelled to increase its contribution to elementary and secondary education, given that it is spending more than one-third of its discretionary budget on this activity. By this reasoning, the most likely event is that K-12 education will receive the same funding, as a percentage of the state’s general revenue, as it did last year.

Thus, unless Missourians want to specify an even larger fraction of state resources to funding elementary and secondary education, the return to this trial investment will not improve much from this year’s utter failure during the next few years. In economics, the question starts with the opportunity cost of the resources spent on this trial. Even if the per-district expenditures are a small fraction, the relevant question is whether the school districts would have had a higher return by spending those resources on producing education. It is hard to imagine that the return would be negative-100 percent if spent on books, teachers, science equipment, etc. Elementary economics tells us that resources should flow to their highest valued use. It is time for school districts to apply this logic.

World-class cycling came to Missouri. For one week in mid-September, Missourians were offered an intimate look at the sport. Judging by the crowds and the enthusiastic press, the state embraced the Tour of Missouri and consumed the product of watching cyclists whizz by at 30 miles per hour.

There has been some criticism of state officials, including in this blog, arguing that the state’s return on its investment is negative. I have not seen the final tally, but suppose that Missouri State Government paid $1 million to sponsor the Tour. On average, between 3 and 4 cents of every dollar of Gross State Product (GSP) is received by Missouri’s General Revenue Fund. Thus, the break-even point is somewhere between $25 million and $33 million in additional GSP that would have to be generated by the Tour of Missouri. I have seen the estimated economic impact from the Tour de Georgia and am skeptical. The bottom line is that it is unlikely that the Tour of Missouri created enough new jobs or new physical capital to generate an additional $25 million of GSP. Nor were there enough idle resources — such as empty hotel rooms — used by out-of-state fans and participants to add that much to the Missouri economy. Rather, what we saw was people substituting the goods and services associated with the Tour of Missouri, displacing other forms of entertainment. As such, I would agree with the narrow economic calculation of the rate of return; it was probably negative.

Does this mean that the State of Missouri should not have sponsored the event with any funding? That answer is yet to be determined. Economic theory indicates that governments do improve welfare when they use resources to overcome coordination failures in the market. In this case, can one imagine that the Tour of Missouri would have been an entertainment offering without the state government’s sponsorship? No. It is difficult to coordinate the numerous activities necessary to put on such a cycling festival; profit-motivated entrepreneurs are probably incapable of solving the coordination problem. Hence, there is a role for government to solve these issues and provide its citizens with this form of entertainment.

The rate-of-return argument notwithstanding, stewards of the state resources must be vigilant. Over time, the justifiable size of state sponsorship will decline as the coordinating problems decline. There will always be issues with state roads and protection that require some state intervention. However, the initial mobilizing services will disappear in several years. If the Tour of Missouri is valuable enough to Missouri citizens, it will survive declining state sponsorship. Ultimately, market forces will determine the value to this enterprise just as it vets all goods and services that consumers choose from. It will take several years to assess the outcome, though there are hints from the revealed preferences of the thousands of people lining the Tour route.