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Kling writes:

Early in 2007, the price of oil was $60 a barrel. Recently, it has been above $130 a barrel. Which of the following does Paul Krugman believe:

(a) market fundamentals justified $60 a barrel then, and they justify $130 a barrel now; or

(b) market fundamentals justified a much higher price in 2007?

...We know that Krugman does not believe that today's oil price is out of line with fundamentals. Krugman's view, in effect, is that if speculators artificially boost the price of oil, then supply will exceed demand, and the excess has to go somewhere. Where are the inventories?

This view ought to hold in reverse. If speculators artificially kept the price of oil too low early in 2007, then demand should have exceeded supply and inventories should have vanished. Yet they did not. So is Krugman forced by his model to conclude that the price of oil of $60 also reflected fundamentals?

The "fundamentals" price of oil depends on a number of factors that cannot be perfectly foreseen. Among these are (1) will the world enter a deep and prolonged recession in 2007, and (2) will global oil production in 2007 be higher than it was in 2006? Today, we know that the answer to both questions is no, and conditional on knowing that answer, we can see that $60/barrel was too low a price. But a year ago, no one knew those answers.

Likewise, the price of oil today is very much dependent on the answer to questions such as (1) will the world enter a deep and prolonged recession in 2008, and (2) will global oil production in 2008 be higher than it was in 2007? Today, we do not know the answer to these questions. If the answer is yes, the price of oil today is much too high. If the answer is no, the price could still be too low.

As for the specific question of "where are the inventories", let's be a little more precise about the question being asked. The correct question is, Did the movement along the demand curve that resulted from the increased price show up as an increase in inventories? The correct answer is, no, it was offset by a shift in the demand curve for newly industrialized countries and the oil producing countries. For example, China may have consumed a half million more barrels of oil per day in 2007 compared with 2006.

Where are the inventories? China already burned them.

Technorati Tags: oil, oil prices, oil bubble, oil price bubble, oil speculation

The easiest thing to do is to pull down the CBO's measure (interpolated to quarterly frequency). This yields the following picture (in logs):

Two observations: (i) recessions do not necessarily coincide with negative output gaps (although they do seem to coincide with the beginning of periods of negative output gaps); and (ii) recoveries do not always coincide with positive output gaps.

This is obvious when one thinks about it, given the NBER BCDC definition of a recession as the following:

A recession is a significant decline in economic activity spread across the economy, lasting more than a few months, normally visible in real GDP, real income, employment, industrial production, and wholesale-retail sales. A recession begins just after the economy reaches a peak of activity and ends as the economy reaches its trough. Between trough and peak, the economy is in an expansion. Expansion is the normal state of the economy; most recessions are brief and they have been rare in recent decades.

That is a recession is the description of the first derivative of output taking on a negative value, while an output gap is a description of output relative to the output level consistent with the "normal" utilization of factors of production (also "full-employment"). For details of how CBO calculates potential GDP, see this document.

Looking at the last ten years provides another insight.

The US economy only barely made it close to full-employment in the expansion of 2001-2007/8/?, and is now declining again. I think I had realized this (especially in the course of various past debates over the surge in tax receipts, which I think has now been resolved -- see [1], [2] for a recollection.)

As I noted in the beginning of this post, I was finding it difficult to discern the most appropriate measure, so I will share the other measures I have investigated as indicators of potential (or "trend") GDP (which can then be used to calculate corresponding measures of the output gap): (1) the Hodrick-Prescott filter; (2) the Band Pass filter; and the quadratic time trend.

The Hodrick-Prescott filter is a ubiquitous two-sided filter used in time series macroeconometrics and elsewhere (I've even seen it used in the analysis of temperature data! [3]). Essentially, the HP filter calculates a trend that minimizes the weighted sum of squared deviations from trend, and squared changes in the the growth rate of the trend. This weighting is controlled by a parameter which is usually set at 1600 for quarterly data. As a public service, I'll note there are serious hazards associated with this filter, especially when trying to correlate various macro series that have been put through the same filter [4].

There is an additional problem (which is often ignored), namely that the HP filter is two-sided, so that running the filter up to the end point of data will tend to result in the trend being too close to the last data point (in our case, the output gap will be pulled to zero).

There are several band pass filters; the one most commonly used in the macroeconometric literature is the Baxter-King version.

Band pass filters are called this because (in the frequency domain) they pass through any cyclical components within a particular frequency band, and elimates the others. In the time domain, this means fluctuations that are shorter or longer than a specific length are ignored. In the business cycle area, then, in order to use this filter, one would have to have a prior on how long a "typical" business cycle is. More on both the HP and BP filters can be found in Tim Cogley's entry for the New Palgrave Dictionary of Economics [5].

The final means of identifying the output gap is to the simplest (at least in implementation) -- take the deviation from an estimated quadratic trend in time. This is not an uncommon procedure, but if you are pretty confident there is a unit root in log GDP, you might feel a little queasy about doing this [6]. But for completeness' sake, I'll show what happens when you do this as well.

Note that in order to circumvent the two-sided filter aspect of the HP filter, I have done a standard fix, which is to use an ARIMA(1,1,1) on log GDP over the 1980-08q1 period to dynamically forecast out 12 quarters, and then apply the HP filter to this "extended" series. I could have done a similar procedure for the BP filter, but opted to use the Christiano and Fitzgerald (2003) one-sided asymmetric version of the band pass filter to estimate the trend series.

First, the good news. Using the band pass filter, one finds that the output gap is still positive, at less than one percentage point of GDP in 2008q1. The HP filter indicates an essentially zero output gap. The quadratic trend indicates something similar to what the CBO indicates -- something close to a 2 percentage point negative output gap in 2008q1, versus 1.5 percentage points for CBO.

I don't want to say that there is one best version. Variations in the sample period, and the parameters used in each filter, will change the results. And of course, data revisions will mean the real-time output gaps will differ from the final revised output gaps we estimate today using either mechanical or judgmental approaches. For a pessimistic view regarding real time use, see Orphanides and van Norden (2004) [pdf].

Nonetheless, the distinction between the rate of change in economic output, and where output levels will gravitate to (and at what pace) is a useful one. And I think it will become of greater usefulness as the slowdown ends, if and when growth resumes. In particular, I'm thinking of whether the pattern of smaller -- but more persistent -- ups and downs continues (the half life of a deviation from potential has risen from 8 quarters in the 1970-90q1 period to 11.6 quarters in the 1990q2-2008q1 period).

Technorati Tags: potential GDP, recession, output+gap, full employment output, trend.

One point to keep in mind, when comparing against previous downturns: for the last few months, the indicators are either preliminary or once/twice revised, while viewing back in time, one will be looking at final, revised, data. For the issue of vintage data and revisions, see these posts (see Creative Destruction, as well as these posts [3], [4], [5]). To access vintage data, see the St. Louis Fed's ALFRED system.

With that caveat in mind, it looks to me like we've passed at least a local maximum, and indicators are trending down.

As I've remarked before [1], there is likely two way causality between the dollar's value and the price of oil denominated in dollars. One way of taking out some of the numeraire issue is to see how a price of a barrel of oil would be, expressed in other currencies. In the figure below, I compare the dollar price against that in euros, and against that in the Special Drawing Rights (SDR).

The weights for the USD, EUR, JPY and GBP in the SDR are 0.44, 0.34, 0.11 and 0.11, respectively.

What the figure highlights is that while USD weakness is associated with higher dollar prices for oil, upward trends in all prices are evident. The wedge between the dollar increase and the SDR increase since January 2008 to 6/6 is only 2.8% (in log terms; 4.2% in level terms). It's a bit bigger for the dollar/euro comparison, at 6.7% (in log terms; 9.6% in level terms)

So the dollar's exchange rate "matters" (keeping in mind two-way causality), but for the bulk of the movement in oil prices, look here.

Technorati Tags: oil prices, exchange rates .

The story from Bloomberg:

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