Both have to be "handled with care".

Revisions

We're all tempted to make predictions on the basis of the last data point. And even more difficult to resist is the temptation to make definitive statements on the basis of data that are sure to be revised. For instance, we see this question from Casey Mulligan, "Where's the GDP Disaster?".

Last October, when we were told that spending and incomes were about to collapse, I predicted that "real GDP will not drop below $11 trillion (chained 2000 $)."

Professor Mulligan provides this graph.

Figure from Mulligan, "Where's the GDP Disaster?"

I think this is an excellent time to recapitulate the hazards of making definitive assessments on the basis of data that are sure to be revised [0] [1]. To illustrate this point, I go back to the last recession, which according to the NBER extended from

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In a recent Economix post, Casey Mulligan asserts that aid to the states and localities is unwarranted given that state and local government employment is doing just fine. His graph highlighting cumulative gains/losses ends in January 2009, to show what had transpired by the time the stimulus bill was being debated. How do things look if one extends the sample to August 2009? And what about spending as opposed to employment?

Figure 1 depicts the level state and local employment. The two dashed lines indicate the reference dates in Professor Mulligan's comparison.

Figure 1: State and local government employment, in thousands, seasonally adjusted. Dashed lines refer to begin-end dates used in Mulligan's graph. Gray shading denotes NBER defined recession dates assuming trough at June 2009. Source: BLS, Employment Situation August release and NBER.

Using those two reference dates, state and local employment has indeed increased. And in

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Casey Mulligan rebuts my post asserting slack in the economy by posing the scenario "Construction Workers Teaching Kindergarten". He writes:

Econbrowser now claims* that the stimulus bill can be effective, because unemployment rates are high (whatever that means) in health care and education. Let's take a look at employment changes Dec 2007 - June 2009 (millions) by industry:

Total nonfarm payrolls: -6.5

Construction: -1.3

Manufacturering: -1.9

Education and Health: +0.7

How exactly is fiscal policy going to create 3.5 million jobs by primarily hiring people in education and health? I see only two scenarios, both absurd and/or dishonest:

He argues these two scenarios are: (1) "The construction workers become kindergarten teachers" or (2) "The people in construction and manufacturing stay unemployed."

Are Unemployment Statistics Meaningless?

Professor Mulligan apparently disbelieves unemployment rates, preferring to ascribe greater importance to employment figures. I think I understand why he does, given the optimizing theoretical framework he works with (see

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In today's Economix post, Casey Mulligan argues that the greater than predicted unemployment numbers should not be ascribed to the negative effect of the stimulus, but rather to bigger than anticipated negative shocks.

We cannot blame the Obama administration for failing to predict June's 9.5 percent unemployment rate. That result just shows the size of the shocks hitting the economy: Even the best forecasters can miss the unemployment rate by almost two percentage points, even when forecasting fewer than six months ahead.

That makes sense, and is in line with my previous post. But he then argues that since we’ve seen little stimulus effect so far, we should cancel the stimulus, since it'd be costly on a per-job basis (and in any case, he believes the effect on GDP to be small [1]). These are interesting assertions meriting further analysis.

Stock-Flow Mismatch

We're all free to use whatever multipliers we

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In today's NYT, Casey Mulligan presents an interesting picture of GDP during the "1980-82 recession" -- the conjoining of the two NBER defined recessions in 1980 and 1981-82. Based on the comparison with the current recession, he concludes:

While the job losses, foreclosures, stock declines and other casualties of the current recession have been very painful, substantially more bad economic news is needed to make this recession worse than the downturns of 1980-'82, at least in G.D.P. terms.

Here is Professor Mulligan's graph.

Figure from C. Mulligan, "Worse than 1982?" Economix (June 3, 2009).

Here, without comment, are three graphs of employment and industrial production, but normalizing the start date instead of the end date. Why one would want to normalize on the trough especially when the trough date is unknown, I'm not certain, but there's nothing to stop one from doing so. But, as I say, I'll

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It has been interesting to me how much excited commentary has been elicited by my posts on output gaps. [0],
[1], [2], [3] I had thought the subject fairly uncontroversial, especially my reliance upon the CBO measure, which is calculated in a conventional manner, and is an object well-understood in mainstream macroeconomics (take your pick — from Hall and Papell to Mankiw). However, it’s clear that there is no such agreement in the blogosphere (which can be taken as an indicator of how dispersed beliefs are in that world). In any case, the reaction tells me that one’s belief in what determines potential GDP defines in large part how one thinks about the workings of the economy, and so I thought it useful to discuss alternative measures coming out of current academic work.

Recap

As I’ve discussed earlier (see this post), in some incarnations actual output is

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