Perspective (Comparing Recessions)

This is quite a long post.  I hope you’ll be patient and read it all – there are plenty of pretty graphs!

I have previously spoken about the need for some perspective when looking at the current recession.  At the time (early Dec 2008), I was upset that every regular media outlet was describing the US net job losses of 533k in November as being unprecedentedly bad when it clearly wasn’t.

About a week ago, the office of Nancy Pelosi (the Speaker of the House of Representatives in the US) released this graph, which makes the current recession look really bad:

Notice that a) the vertical axis lists the number of jobs lost and b) it only includes the last three recessions.  Shortly afterward, Barry Ritholtz posted a graph that still had the total number of jobs lost on the vertical axis, but now included all post-World War Two recessions:

Including all the recessions is an improvement if only for the sake of context, but displaying total job losses paints a false picture for several reasons:

  1. Most importantly, it doesn’t allow for increases in the population.  The US residential population in 1974 was 213 million, while today it is around 306 million.  A loss of 500 thousand jobs in 1974 was therefore a much worse event than it is today.
  2. Until the 1980s, most households only had one source of labour income.  Although the process started slowly much earlier, in the 1980s very large numbers of women began to enter the workforce, meaning that households became more likely to have two sources of labour income.  As a result, one person in a household losing their job is not as catastrophic today as it used to be.
  3. There has also been a general shift away from full-time work and towards part-time work.  Only looking at the number of people employed (or, in this case, fired) means that we miss altogether the impact of people having their hours reduced.
  4. We should also attempt to take into account discouraged workers; i.e. those who were unemployed and give up even looking for a job.

Several people then allowed for the first of those problems by giving graphs of job loses as percentages of the employment level at the peak of economic activity before the recession.  Graphs were produced, at the least, by Justin Fox, William Polley and Calculated Risk.  All of those look quite similar.  Here is Polley’s:

The current recession is shown in orange.  Notice the dramatic difference to the previous two graphs?  The current recession is now shown as being quite typical; painful and worse than the last two recessions, but entirely normal.  However, this graph is still not quite right because it still fails to take into account the other three problems I listed above.

(This is where my own efforts come in)

The obvious way to deal with the rise of part-time work is to graph (changes in) hours worked rather than employment.

The best way to also deal with the entry of women into the workforce is to graph hours worked per member of the workforce or per capita.

The only real way to also (if imperfectly) account for discouraged workers is to just graph hours worked per capita (i.e. to compare it to the population as a whole).

This first graph shows Weekly Hours Worked per capita and per workforce member since January 1964:

In January 1964, the average member of the workforce worked just over 21 hours per week.  In January 2009 they worked just under 20 hours per week.

The convergence between the two lines represents the entry of women into the workforce (the red line is increasing) and the increasing prevalence of part-time work (the blue line is decreasing).  Each of these represented a structural change in the composition of the labour force.  The two processes appear to have petered out by 1989. Since 1989 the two graphs have moved in tandem.

[As a side note: In econometrics it is quite common to look for a structural break in some timeseries data.  I’m sure it exists, but I am yet to come across a way to rigorously handle the situation when the “break” takes decades occur.]

The next graph shows Year-over-Year percentage changes in the number of employed workers, the weekly hours per capita and the weekly hours per workforce member:

Note that changes in the number of workers are consistently higher than the number of hours per workforce member or per capita.  In a recession, people are not just laid off, but the hours that the remaining employees are given also falls, so the average number of hours worked falls much faster.  In a boom, total employment rises faster than the average number of hours, meaning that the new workers are working few hours than the existing employees.

This implies that the employment situation faced by the average individual is consistently worse than we might think if we restrict our attention to just the number of people in any kind of employment.  In particular, it means that from the point of view of the average worker, recessions start earlier, are deeper and last longer than they do for the economy as a whole.

Here is the comparison of recessions since 1964 from the point of view of Weekly Hours Worked per capita, with figures relative to those in the month the NBER determines to be the peak of economic activity:

The labels for each line are the official (NBER-determined) start and end dates for the recession.  There are several points to note in comparing this graph to those above:

  • The magnitudes of the declines are considerably worse than when simply looking at aggregate employment.
  • Declines in weekly hours worked per capita frequently start well before the NBER-determined peak in economic activity.  For the 2001 recession, the decline started 11 months before the official peak.
  • For two recessions out of the last seven – those in 1980 and 2001 – the recovery never fully happened; another recession was deemed to have started before the weekly hours worked climbed back to its previous peak.
  • The 2001 recession was really awful.
  • The current recession would appear to still be typical.

Since so many of the recessions started – from the point of view of the average worker – before the NBER-determined date, it is helpful to rebase that graph against the actual peak in weekly hours per capita:

Now, finally, we have what I believe is an accurate comparison of the employment situation in previous recessions.

Once again, the labels for each line are the official (NBER-determined) start and end dates for the recession.  By this graph, the 2001 recession is a clear stand-out.  It fell the second furthest (and almost the furthest), lasted by far the longest and the recovery never fully happened.

The current recession also stands out as being toward the bad end of the spectrum.  It is the equally worst recession by this point since the peak.  It will need to continue getting a lot worse quite quickly in order to maintain that record, however.

After seeing Calculated Risk’s graph, Barry Ritholtz asked whether it is taking longer over time to recover from a recession recoveries (at least in employment).  This graph quite clearly suggests that the answer is “no.”  While the 2001 and 1990/91 recessions do have the slowest recoveries, the next two longest are the earliest.

Perhaps a better way to characterise it is to compare the slope coming down against the slope coming back up again.  It seems as a rough guess that rapid contractions are followed by just-as-rapid rises.  On that basis, at least, we have some slight cause for optimism.

If anybody is interested, I have also uploaded a copy of the spreadsheet with all the raw data for these graphs.  You can access it here:  US Employment (excel spreadsheet)

For reference, the closest other things that I have seen to this presentation in the blogosphere are this post by Spencer at Angry Bear and this entry by Menzie Chinn at EconBrowser.  He provides this graph of employment versus aggregate hours for the current recession only:

Alex Tabarrok has also been comparing recessions (1, 2, 3).

Individually sub-rational, collectively rational (near equilibrium)

Alex Tabarrok has had an interesting idea.  It’s short enough to quote in its entirety:

Rationality is a property of equilibrium. By this I mean that rationality is habitual and experience-based and it becomes effective as it becomes embedded in the rules of thumb and collective wisdom of market participants. Rules of thumb approximate rational decision rules as market participants become familiar with an economic environment. Individuals per se are not very rational; shift the equilibrium enough so that the old rules of thumb no longer apply and we are likely to see bubbles, manias, panics and crashes. Significant innovation is almost always going to come accompanied with a wave of irrationality. When we shift to a significant, new equilibrium rationality itself is not strong enough to tie down behavior and unmoored by either reason or experience individuals flail about liked naked apes – this is the realm of behavioral economics. Given time, however, new rules of thumb evolve and rationality once again rules but only until the next big innovation arrives.

It seems appealing to me on a first read, but there are plenty of questions to go with it.

There is a language difficulty here.  On one level, an equilibrium is defined by the actions of everybody aggregating to demand and supply in any given instant, so we are always in an equilibrium by definition.  On another level, an equilibrium is a deeper, fundamental attractor that (at least in the short run) exists independently of people’s choices.  In what follows, I will call the first “where we are” and the second “the attractor”.

Why would agents use rules of thumb instead of making decisions on a fully-rational basis?  Is it just because they aren’t entirely rational people (not very satisfying) or are there constraints that induce a fully rational individual to use rules of thumb?

Under what market mechanisms do the individually sub-rational agents aggregate to collectively rational decision-making when we are close to the attractor and – potentially – to collectively irrational decision-making when we are far away from the attractor?

What form of decision rules do the sub-rational (rule of thumb) agents use?  Could we say that agents use taylor-series approximations around the point they believe to be the attractor, with the exact location of the attractor being uncertain?  If so, would it be interesting to imagine that simple agents use first-order (i.e. linear) approximations and sophisticated agents use second-order (quadratic) approximations?

What is the source of uncertainty?  With my example in the previous paragraph, why doesn’t everybody instantly know the new location of the attractor and adjust their rules of thumb accordingly?

How do agents learn?  Could we bypass this question by proposing that agents update their understanding of where the attractor is in a manner analogous to firms setting prices in the Calvo pricing (i.e. a fixed percentage of agents discover the truth in any given period)?

Paul Krugman wins the Nobel (updated)

There is no doubt in my mind that Professor Krugman deserves this, but who doesn’t think that this is just a little bit of an “I told you so” from Sweden to the USA?

Update: Alex Tabarrok gives a simple summary of New Trade Theory.  Do read Tyler Cowen for a summary of Paul Krugman’s work, his more esoteric writing and some analysis of the award itself.

I have to say I did not expect him to win until Bush left office, as I thought the Swedes wanted the resulting discussion to focus on Paul’s academic work rather than on issues of politics. So I am surprised by the timing but not by the choice.

This was definitely a “real world” pick and a nod in the direction of economists who are engaged in policy analysis and writing for the broader public. Krugman is a solo winner and solo winners are becoming increasingly rare. That is the real statement here, namely that Krugman deserves his own prize, all to himself. This could easily have been a joint prize, given to other trade figures as well, but in handing it out solo I believe the committee is a) stressing Krugman’s work in economic geography, and b) stressing the importance of relevance for economics

Justifying my continued existance

… as a blogger [*], that is.

Via Alex Tabarrok (with two r’s), I note that the National Library of Medicine (part of the NIH) is now providing guidelines on how to cite a blog.

There are the ongoing calls for more academic bloggers and, while there are certainly questions over incentives and the impact on research productivity, academia continues to dip the odd toe in the water. Justin Wolfers just did a week of it at Marginal Revolution and now I see this brief post by Joshua Gans:

As more evidence that blogging is going mainstream, a bunch of faculty at Harvard Business School are now in on the act (including economist Pankaj Ghemawat)

[*] I didn’t think it was possible for me to dislike any word more than I do “blog,” but it turns out that I do. To call myself “blogger” required a supression of my own gag reflex.

Orthodoxy, trade and the developmental state

I love the internet. I love what it’s becoming, what it’s capable of becoming. A few years ago, the blogosphere (I hate that word) was dominated by enthusiastic amateurs. That is, it was filled with people who, in so far as they had any speciality, had it in entirely separate fields, but were interested in the topics they wrote about. It still is, and that’s great. Public debate is always good.

But now we are seeing professional thinkers stepping into the arena. University professors are emerging from their ivory towers and using the web to debate each other in the public sphere. That is freakin’ awesome. Here’s a recent example …

Patricia Cohen, of the New York Times, wrote this piece: In Economics Departments, a Growing Will to Debate Fundamental Assumptions. In it she quoted the views of, among others, Alan Blinder (Princeton), David Card (U.C. Berkley) and Dani Rodrik (Harvard).

It elicited quite a response in the various academic blogs. Three of them that are worth checking out:

It’s that last one by Don Boudreaux that I want to focus on. In it, he criticised the views of Dani Rodrik in particular and issued Dani a challenge.

Dani Rodrik replied: What’s different about international trade?

Brad DeLong (U.C. Berkley) was watching and gave his opinion: Don Boudreaux vs. Dani Rodrik on Industrial Policy: I Call This One for Don–I Think It’s a Knockout

Dani Rodrik then updated his original post with a rebuff to Brad DeLong.

Brad DeLong stepped up with a more lengthy post: DeLong Smackdown Watch: Dani Rodrik Strikes Back