Krugman on Fischer and the GOP

Some thoughts here.

Hey, if Hagel doesn't make it through maybe Obama can nominate Stanley Fischer as Defense Secretary!

One talented undergraduate at American University that I TAed for in intermediate micro last semester said that Stanley Fischer was a big influence on his interest in economics. The student was older - he applied to American out of the IDF, and told me that what he read about Fischer's handling of the financial crisis in Israel first attracted him to the field.

Miles Kimball and Mormon Church History

Maybe people knew this, but I didn't. Miles Kimball has some fascinating Mormon church history in his family tree. Also some very thoughtful reactions to the resignation of Pope Benedict.

What was I thinking?

So I'm working through that engineering chapter again before submitting it and updating some analyses with new data that came out this year. I'm looking at a section where I'm discussing the graduate degree wage premium and I do something really weird in my code that I just can't figure out:

bysort year dgrdg: egen w=total(salarp*rweight)
bysort year dgrdg: egen totalr=total(rweight)
gen wrate=w/totalr
tab year dgrdg, sum(wrate) mean
tab year dgrdg [w=rweight] if salarp!=.

dgrdg is the degree variable, salarp is salary. For some reason I'm aggregating it up before tabulating. I get qualitatively similar results when I just do the natural thing of tabulating salaries and weighting the tabulation, but different results... does anyone have any clue what might have driven me to do this the first time (maybe a year ago)? The fact that the results are somewhat different (although like I said, qualitatively similar) makes me wonder if the weights are even frequency weights, which makes me want to stick with more intuitive thing I'm doing today.

Nominate Romer as Fed Chair

Says Brad DeLong.

Sounds great to me.

Don Boudreaux on empirical social science

I don't want to give the impression that this post is one that I largely disagree with. Actually a lot of it is strong, particularly his discussion on the role of theory (I also liked the prior post where there seemed to be some recognition that reductio ad absurdum is often a terrible way to evaluate an economic claim). As Cafe Hayek posts go, this one is quite good. But I did want to highlight this passage, not to trash Don but just to raise concerns about an attitude that bothers me a lot:

"...there is no shortage of empirical studies that document the minimum-wage’s detrimental impact on low-wage workers. There are also, of course, other empirical studies that find the opposite effect, and yet others that find no significant effect.

That’s the way it is with social-science (including economic) data: they almost never speak for themselves clearly and without significant exceptions. Someone can always challenge even the most consensus-supported studies as having left out important variables, gotten causality backwards, employed inappropriate aggregation, examined inappropriate time periods, and on and on."

I don't like this attitude that empirical analysis is all over the map and you can  criticize all studies. Of course as in any science we're faced with a distribution of point estimates, which we usually take to be around a "true" point estimate. We are usually most confident about this if the studies at the center of mass seem to be the best designed and come out as the most precise. If you find some studies with a positive minimum wage effect and some with a negative, and some with no effect there's a good chance that there's actually no effect of the minimum wage.

Here is an excellent graphic from a new CEPR publication on the employment effects of the minimum wage. The estimated elasticities are on the x-axis, but what I really like is that the reciprocal of the standard error is on the y-axis. That means lower variability (not necessarily more accurate - we'll get to that) estimates have a higher value on the y-axis.



This is really not the picture Don is painting of the empirical literature for the economic impact of the minimum wage. This reaffirms my view from early meta-analytical work that the minimum wage essentially has no employment impact. Now there's a substantial cluster of slightly negative results in this graph, which is the origin of the Neumark and Wascher point that we do have a consensus for a slightly negative impact of the minimum wage. I'm actually willing to embrace that "negative but small" conclusion for essentially the same reason that Don points out - it sure has a theoretical basis. But embracing that conclusion as a practical matter doesn't change the fact that the zero-effect findings look very strong , and anyway the empirical evidence is not wishy-washy at all as Don seemed to suggest. You either have a "no effect" option or you have a "maybe a teeny effect" if you're being objective.

Claims like Jeff Tucker's assertion that one's position on the minimum wage is something of an intelligence test (in his case implying that you are not intelligent if you don't oppose it) fares very poorly.

Now I also alluded to the difference between precision and accuracy above - or what econometricians usually refer to as efficiency and bias. Bias - that your point estimate may not be centered on the "true" estimate - is the primary concern.

One of the biggest sources of variability in any set of studies is the inherent bias of a particular identification strategy. Economists almost never have a true experiment, so we have to use a variety of tricks to identify the relations we're interested in in a system that is simultaneously determined. Often these tricks will influence the point estimate itself. In immigration studies, for example, you have a lot of natural experiment studies and a lot of what I guess you'd call "shift-share" studies. The former tends to find positive effects and the latter tends to find negative effects (none substantial unless you're looking at very close labor market competitors).

Presumably there's something systematically different about these approaches. The natural experiment approach usually involves looking at a large influx of immigrants at a single point in time. The problem with that is that there is still a non-random aspect to (1.) which immigrants go, and (2.) where they go. Immigrants are going to be attracted to local economies where they have a shot at succeeding and where they might have a comparative advantage. You're going to naturally pick up lower negative effects or even positive effects as a result. The strategic behavior on the part of immigrants is good to know and may even reassure us, but it does not present an unbiased estimate of the impact of a truly exogenous migration shock. The shift-share analyses associated with Borjas apparently have some negative biases just like the natural experiment studies have some positive biases, although I'm personally less well versed in those criticisms.

The point is, when you consider these points the meaningful variability between empirical estimates starts to decline a lot. When you really understand why one set of studies is higher and one set of studies is lower - and if the methods of both studies have implicit biases, then you start to see them as upper and lower bounds - not as widely varying estimates of the same underlying parameter.

This is true of fiscal multiplier studies too. War spending studies give low estimators (I have a research note on this that will hopefully see the light of day at some point), studies where there is spill-over produce low multipliers, studies that look at state or county level spending by the federal government produce high multipliers because all jurisdictions pay federal taxes (so the counterfactual gets a negative hit).

A good empirical economists should be able to do what you might call mental meta-analyses like this. To really know an empirical literature you need to have a sense of the different strategies that people use for doing empirical work and the strengths and weaknesses of each strategy because a lot of the variability of the results are baked in by the differences in the strategies. When you start to think of the literature in these terms you realize there really isn't as wide of a range of results as you first thought. Often you have one group of studies using a strategy that introduces a negative bias with lower results and another group of studies using a strategy that introduces a positive bias with higher results. Your reaction to that should not be "wow there's a wide range of results" - it should be "we can be pretty sure that the real answer lies somewhere in between".

Empirical economics is not a free-for-all, but it does require effort. Most questions are actually clearer than they appear at first glance, but you have to really understand what the studies are doing that makes them different.

Yes, a lot of people have a very odd view of the 1970s

Krugman has a great post on the myth of Keynesian excess and the problems of the 1970s:

The truth is that whatever you might say about economic policy in the 1970s, it had nothing to do with Keynesian fiscal policy — and did not involve increasing debt. People on the right tend to use “Keynesian” to mean “liberal stuff I don’t like”, but aside from that definition, the 70s tell us nothing about the issues we’re discussing right now. You can argue that monetary policy was too loose, that the Fed was too expansionary in 1972 (when Arthur Burns was trying to reelect Richard Nixon) and that it failed to tighten in the face of oil-shock-driven inflation. But again, the idea that this experience has any relevance to expansionary fiscal policy in the face of a liquidity trap is totally bogus.

But I guess I should have expected this; after all, it’s also standard to argue that the troubles of the 70s somehow proved that the welfare state is the root of all economic evil, which makes equally little sense.

The 70s were important for economics. They did kill the notion of a stable Phillips curve that doesn’t depend on expected inflation, and convinced Keynesian as well as non-Keynesian economists that there is a minimum level of unemployment that can’t be reduced with demand-side policies (although we learned that lesson too well; recent experience shows that there is a lot of nominal stickiness at low inflation rates).

This chart is also nice:



Now to all this, add this passage from Buchanan's "Democracy in Deficit":

“We are all Keynesians now.” This was a familiar statement in the 1960s, attributed even to the likes of Milton Friedman among the academicians and to Richard Nixon among the politicians. Yet it takes no scientific talent to observe that ours is not an economic paradise. During the post-Keynesian, post-1960 era, we have labored under continuing and increasing budget deficits, a rapidly growing governmental sector, high unemployment, apparently permanent and perhaps increasing inflation, and accompanying disenchantment with the American sociopolitical order. 

This is not as it was supposed to be. After Walter Heller’s finest hours in 1963, fiscal wisdom was to have finally triumphed over fiscal folly. The national economy was to have settled down on or near its steady growth potential, onward and upward toward better things, public and private. The spirit of optimism was indeed contagious, so much so that economic productivity and growth, the announced objectives for the post-Sputnik, post-Eisenhower years, were soon abandoned, to be replaced by the redistributionist zeal of Lyndon Johnson’s “Great Society” and by the no-growth implications of Ralph Nader, the Sierra Club, Common Cause, and Edmund Muskie’s Environmental Protection Agency. Having mastered the management of the national economy, the policy planners were to have moved on to quality-of-life issues. The “Great Society” was to become real. 

What happened? Why does Camelot lie in ruin? Viet Nam and Watergate cannot explain everything forever. Intellectual error of monumental proportion has been made, and not exclusively by the ordinary politicians. Error also lies squarely with the economists.

The academic scribbler of the past who must bear substantial responsibility is Lord Keynes himself, whose ideas were uncritically accepted by American establishment economists. The mounting historical evidence of the effects of these ideas cannot continue to be ignored. Keynesian economics has turned the politicians loose; it has destroyed the effective constraint on politicians’ ordinary appetites. Armed with the Keynesian message, politicians can spend and spend without the apparent necessity to tax. “Democracy in deficit” is descriptive, both of our economic plight and of the subject matter for this book."

Whenever I read from Democracy in Deficit I always have the same reaction that I do reading Hayek on "scientism". I think "how could someone who was otherwise so brilliant go so terribly wrong?". It happens I suppose.

Notice the strange conflation of everything liberal he doesn't like with Keynesianism. Notice the bizarre characterization of fiscal irresponsibility as the origin of the problems of the 1970s (this was written in 1977).

I especially like the line about Camelot in ruins and Vietnam. For international readers that may not know, "Camelot" is a reference to Kennedy. The ironic thing here is that despite the tepid semi-embrace of Keyesian ideas by Roosevelt, Kennedy is usually the president most associated with a deliberate application of Keynesian principles due to his Keynesian advisors, not Johnson - who had other priorities. But apparently the loss of Camelot to the Great Society is some kind of Keynesian problem? The other guy that applied Keynesian principles pretty decently (aside from 2009 Obama) was Bill Clinton, consolidating our fiscal position in the growth years of the 1990s.

Of course, Kennedy, Clinton, and Obama don't fit as nicely into Buchanan's narratives about Keynesians abandoning prudent fiscal policy. To get Buchanan's answer you have to fabricate what went on in the 1970s (like Holtz-Eakin), redefine Keynesianism, and somehow make the argument that politicians who were not Keynesian at all were somehow enabled to do what they did because Keynes was just so awful and killed any sense of fiscal responsibility (as if politicians need an economic theorist to give them license to behave badly, and as if it even makes sense to talk about Keynes as a potential source of such license).

Noah Smith on business "cycles"

Noah Smith shares some information on a point that some of you may already be aware of: modern business cycles aren't really "cycles". Booms don't correlate well with subsequent busts - instead, busts correlate with subsequent booms. Milton Friedman was one of the first to highlight this point - he called it the "plucking model". It's a simple insight, but I personally think it's one of the strongest arguments against Austrian business cycle theory. Indeed, Friedman pointed to Mises as an example of a theory that was rendered problematic by the plucking model. Garrison (and surely others) have arguments against this, but I've never found them all that convincing.

[UPDATE: So as I think about it, Friedman's plucking model point and Noah's trend-stationary point are probably a little different (although someone with more background in time series can expand on this point in the comments). Presumably, subsequent booms correlated with prior busts could be a genuine cycle theory which started with a bust. I think that sort of cycle theory is less natural to think about than a cycle theory that starts with a bust - which is why the plucking model is usually associated with the idea that the economy is growing and occasionally gets hit by shocks that dissipate over time (the line I drew above between Friedman and Noah's points). But I suppose that's not strictly necessary.]

Noah also gets into Minsky, who he talks about as having a more classical cycle theory. My understanding of Minsky (which is admittedly limited), though, is that it's probably more accurate to say that he had a cyclical theory of financial markets - which of course is a little different from having a cyclical business cycle theory. After all, financial crises often provide the shock that might cause a recession in trend-stationary GDP data. So the question for evaluating Minsky is to ask whether financial markets are trend-stationary or not. If they are, then a cycle theory may be less appropriate. I really don't know this literature, but my understanding is that's a disputed point - some early work said it was, but a lot of people are concerned about the robustness of those results.

If you're interested in these sorts of distinctions, you should check out some of Gene Callahan's posts on the subject. He is working on some kind of survey of cycle theories, focusing on those that offer actual cycles of the sort that Noah is describing (not just shocks that are called cycles, such as RBC). I'd just go to Gene's blog and search on "cycle theory".

Anybody catch the Hayek in the xkcd alt-text today?

Assault of thoughts - 2/14/2013

"Words ought to be a little wild, for they are the assault of thoughts on the unthinking" - JMK

- A new book is out from the Upjohn Institute Press that looks very interesting and that I'd like to get my hands on: "Occupational Labor Shortages : Concepts, Causes, Consequences, and Cures". Burt Barnow is a big name in labor market policy evaluation. He was at Hopkins and recently moved to the Urban Institute and GWU. I had the opportunity to work closely with him on the evaluation of the High Growth Job Training Initiative (he taught me regression discontinuity design, along with a lot of other things). This looks like it uses a lot of the material he had presented at the high skill immigration conference I invited to at Georgetown this past summer. Another co-author, John Trutko, is with Capital Research Corporation but he is a familiar face at the Urban Institute too. The third co-author must have met Burt at Hopkins (she has an MPP from there), but she's actually a PhD student in the policy department at American University. So it looks like a good set of authors on an interesting topic.

- Speaking of new books I want: Gavin Wright on the economics of the Civil Rights movement is, of course, self-recommending.

- A Keynesian worrying about supply (apropos of another discussion in an earlier post).

- Unemployment insurance benefit recipiency. The numbers are pre-recessionary, but they put some context to some outlandish claims about the impact of unemployment insurance (also in that earlier post). Since only about a quarter of the unemployed received it (again, pre-recession -maybe different now but its been on a downward trajectory), its impact on their behavior has to be that much bigger to have a net impact of -2.7% points of unemployment (Barro - truly nutty reasoning that didn't even persuade Arnold Kling), or -1% points (Mullins - more solid reasoning). Something like Rothstein's estimate of a -0.1% to -0.5% supply impact plus a 1.6 total multiplier (as the CBO suggests) seems more plausible. I did all the number crunching for the study linked above, but frustratingly that does not appear to be acknowledged.

Jinx cleaning me

It took a second to figure out what he was doing up there...