Project I: Why do States Spend Money?

I have a file drawer full of research projects that I at some point started and then abandoned. Since I am unlikely to ever get back to them I thought it would be worth describing some here in the hope that someone else, earlier in his career, would be interested in reviving them, perhaps for a PhD thesis or a book. This is the first such post.

At a crude level, there are two theories of government expenditure. One is that it is determined by the need for government services. The other is that it is determined by the ability of the government to get money. It would be interesting to know the relative importance of the two in the real world.

One obvious test is the behavior of government finance before, during, and after a war. The war sharply increases the need for government spending. Its end eliminates most of the need but leaves standing the higher taxes used to pay part of the cost of the war. On a pure need theory, one would expect government expenditure to fall back to something close to its pre-war level. On a pure revenue theory, one would expect expenditure to remain high—not as high as during the war, when it was financed in part by borrowing and/or inflation, but at least as high as the taxes enacted during war time would support.

That is one approach to the question, but I thought of another. Different U.S. states have different sources of revenue, different tax structures. Different taxes respond differently to exogenous changes such as inflation. If a state is financed by a progressive income tax, inflation pushes taxpayers into higher brackets and so raises real revenue; if prices and incomes double, tax revenue should more than double. If, at the other extreme, a state is financed by regressive income taxes or by property taxes in a system where reassessment of property values is infrequent, inflation should reduce real revenue; if prices and incomes double, tax revenue should less than double. Keeping tax laws is easier than expanding them, so, if expenditure is driven by the availability of revenue, we would expect the first sort of states to have real expenditure increased, the second sort to have it decreased, by inflation. One could do a similar analysis for other changes in the economic environment that could be expected to change, in one direction or another, real revenues, and then see how the expenditure of states was affected by those changes.

To test the alternative, need, hypothesis, you need changes that affect needs for revenue. The largest expenditure of state and local governments is schooling. The cost of schooling largely depends on the number of school age children, which changes over time. On a need theory, when the fraction of the state’s population that is school age goes up, as it did for (I think) all states as the baby boom reached school age, state expenditures should go up. When it goes down, as it did in the years when the baby boom was coming out of the schools and onto the labor market, it should go down. While this effect would apply to all states, its strength should depend on how large a fraction of state expenditure goes to schooling. And other changes that affect the need for state expenditure may vary more across states.

For both hypotheses, the best evidence would be differences in what happened in different states, since that eliminates causes you are missing that affect all states equally, such as changes in technology that  make schooling or tax collection more or less costly. But you would also want to look at changes that affected all states similarly, such as demographic changes that affected the fraction of the population of school age.

That’s the project. Calculate, for each state, how real revenue would be expected to respond to changes in its environment. Calculate, for each state, how the demand for government services would be expected to respond to changes in its environment. See which plays how large a role in predicting what actually happened.

I have described the project from a U.S. point of view but it could also be done for Canadian provinces, Indian or Australian or Brazilian states, or as an international comparison—perhaps with the price of oil as an important exogenous variable.