Per Pettersson-Lidbom is presenting a paper (in the Political Economy Seminar) that claims that an increase in size of local-government legislatures decreases the size of local government. First I’ll give his abstract, then my comments. The abstract:

This paper addresses the question of whether the size of the legislature matters for the
size of government. Previous empirical studies have found a positive relationship
between the number of legislators and government spending but those studies do not
adequately address the concerns of endogeneity. In contrast, this paper uses variation in
council size induced by statutory council size laws to estimate the causal effect of
legislature size on government size. These laws create discontinuities in council size at
certain known thresholds of an underlying continuous variable, which make it possible to
generate “near experimental” causal estimates of the effect of council size on government
size. In contrast to previous findings, I [Pettersson-Lidbom] find a negative relationship between council size
and government size: on average, spending and revenues are decreased by roughly 0.5
percent for each additional council member.

It’s cool how he uses a natural experiment based on the laws of Finland and Sweden. As he writes: “In Finland, the council size of local governments is determined solely by population size. For example, if a local government has a population between 4001 and 8,000, the council must consist of 27 members, but if its population is between 8,001 and 15,000 the council must have 35 members. Thus, the law creates a discontinuity in council size at the threshold of 8001 inhabitants.” And regression-discontinuity analysis certainly seems appropriate here.

The actual result is suprising to me–not that I’m any expert on local government, it’s just surprising to see a negative effect here–and so I’d like to see some presentation of the data. If the effect is as clear as is claimed, it should show up in some basic analyses–here I’m thinking of scatterplots and matching analyses. This is somewhat a matter of taste–as a statistician, I like graphs, but economists seem to prefer tables. But I just find it difficult to be convinced by results such as Tables 9-14.

To flip it around: this is a pretty clean dataset, right? You have a natural experiment and some points near the boundary. So a scatterplot, and a simple regression could be pretty convincing. Tables 2 and 3 are promising (well, I’d prefer graphs, but still…) but they only have data on “x”, not on “y”. As things stand, I really just have to take the results on trust. Not that I have any reason to disbelieve them, but I’d like to be a little more confident in the results–especially given that much of the paper discusses why these results differ from the rest of the literature on the topic.