Refuting the "iron law of bureaucracy"?

Well, without having read the whole article, it seems to me that the reason they're getting this result is that we're comparing bureaucrats to the general public.

The general public doesn't know how much is actually spent. They vastly overestimate spending on foreign aid, for instance, and welfare. It's plausible that bureaucrats prefer levels of spending that are roughly commensurate with actual operating costs, while ordinary citizens are just mis-estimating.

The fact that the public doesn't know the actual budget explains several strange artifacts in polling. For instance, when you poll people, a large percentage think foreign aid should be cut, but when you ask them what percent of the budget it should be, it's still higher than the actual percent! There's a similar phenomenon with taxes: people tend to think they should be cut, but they also overestimate how high taxes are in the first place, so they sound like they're calling for higher taxes.

Stated preference or revealed preference?

(I know, I could find it out by reading the paper, but I think this is important enough that it should have been in the post. Downvote if you think I'm misbehaving.)

Interesting. How would you explain behavior like NASA management's cooking of shuttle safety numbers before the Challenger explosion, then? Richard Feynman is always a good read. It seems clear that at some level bureaucrats have often tried to optimize the wrong things, in this case "percieved safety," but it seems reasonable that lots of other wrong things will get optimized, including money.

It's also a little problematic because the survey doesn't measure quite what we want to measure. It could be a genuine effect, or it could be something like the difference between believed belief and actions in the real world, with effects not seen in the survey emerging in the workplace? Or maybe, due to the general perception it's simple dishonesty - I looked up the source of the data, and it's a face to face interview survey, which picks up more bias from that kind of thing.

If anything, doesn't the fact that chief bureaucrats see little need for more funding imply that bureaus really are wasteful?

See also: The Case FOR Bureaucracy

That link bothers me immensely. While many of the things they describe are myths (I consider the most important part of politics to be math, and so the "there's always more waste to cut!" guy drew a laugh here), many of the things they describe are strawmen / they handle them wrongly.

For example, consider myth #5. When you compare private industries as a whole to public industries as a whole, the difference is a statistically insignificant .4%. However, what about when you compare apples and apples, not apples and oranges? The U.S. Postal Service gets a rating of 76.1%, private mail carriers get a rating of 84.5%. Public health clinics get a rating of 74.4%, private doctors' offices get a rating of 80.6%. If you average those two actual comparisons together, private industry's edge is 7.3%, almost a full 10% better than the public industry's ratings.

(Also, I would suggest "evidence against" rather than "refuting" when discussing a result, just like "evidence for" is a better description than "proving.")

Interesting. How would you explain behavior like NASA management's cooking of shuttle safety numbers before the Challenger explosion, then? Richard Feynman is always a good read. It seems clear that at some level bureaucrats have often tried to optimize the wrong things, in this case "percieved safety," but it seems reasonable that lots of other wrong things will get optimized, including money.

It's also a little problematic because the survey doesn't measure quite what we want to measure. It could be a genuine effect, or it could be something like the difference between believed belif and actions in the real world, with effects not seen in the survey emerging in the workplace? Or maybe, due to the general perception it's simple dishonesty - I looked up the source of the data, and it's a face to face interview survey, which picks up more bias from that kind of thing.