First publication!!!

I just found out that my paper (with co-authors E. Hurst, A. Lusardi, and A. Kennickell) got published!!

Abstract—Not properly accounting for differences between business owners and nonbusiness owners in studies of household wealth can lead to erroneous conclusions about the significance of different saving motives. Using data from the Panel Study of Income Dynamics from the 1980s and 1990s, we show that within samples of both business owners and non–business owners, the amount of precautionary savings with respect to labor income risk is modest and accounts for less than 10% of total household wealth. Previous large estimates of the size of precautionary balances resulted from pooling these two groups together. Such pooling is inappropriate given that business owners face higher labor risk and accumulate more wealth than non–business owners for reasons unrelated to precautionary motives.

GDP growth and the contribution of the change in inventories

The latest figures on economic growth released by the Bureau of Economic Analysis (BEA) are bad. Yes, GDP growth has surged to 5.7% in the fourth quarter of 2009. But the contributions of investment, government expenditures, and net exports are almost nigh. Personal consumption expenditures has added 1.4 percentage points to growth, down from 2 percentage points in the third quarter. (See Chart 1.) The largest contribution (3.4 points out of 5.7) comes from the change in private inventories, i.e. the variation in the stockpiles of goods that businesses store. An increase in inventories adds to GDP, because those are goods that are produced but not sold, and therefore not included in expenditures; a decrease in inventories, on the other hand, must be subtracted from growth, because those goods were already counted in GDP at the time they were produced.


Chart 1 (click to enlarge)


What is wrong with having more than half of our growth coming from inventories?

First of all, in the medium term we are probably going to see inventories decrease more, not less, on average. Current inventory levels, as measured by the sales-to-inventory ratio, are too high relative to their long-term trend. (See Chart 2.) True, inventories plummeted through 2009, but that was just a correction to the excess stockpiles accumulated during 2008. Taking the recent trend of the sales-to-inventory ratio as benchmark, we should now be closer to 1.2 than to the 1.28 where we actually are. In the near term, therefore, and on average, we should expect net declines in inventories.


Chart 2 (click to enlarge)

Secondly, (optimistic) observers may have claimed that the positive contribution of the change in inventories is a sign that businesses anticipate an increase in demand. In fact, the present behavior of inventories is just a reflection of the economic past: businesses are increasing stockpiles, or at least reducing them more slowly, because consumption expenditures have picked up over the past six months. In other words, businesses are best characterized as backward-looking creatures. There is a strong correlation between current changes in private inventories and the past increase in personal consumption expenditures (PCE). (See Chart 3.) In fact, using quarterly data, the correlation coefficient is around 0.7. The correlation between changes in inventories and future PCE growth, on the other hand, is only 0.4. Saying that increases in inventories forebode stronger demand in the near future is almost wishful thinking.

Chart 3 (click to enlarge)
Finally, and this is a lesser point, estimates of changes in inventories are unreliable. Remember, the figures released by the BEA last Thursday are only advance estimates: over the next two months the government will release two revisions: the preliminary estimate and the final estimate. The “final” estimate will be revised again a few months down the road. Based on recent experience, substantially lower or higher revised figures for changes in inventories should not surprise us. Since 2006, for example, the average difference between the advance estimate and the “finally final” estimate has been $13 billion; the average absolute difference has been $4 billion –in the fourth quarter the change in inventories was -33.5 billion.

Did the recession end in May?

It’s looking more and more as if the recession in the U.S. ended in May. To support that claim I have looked at initial unemployment insurance (UI) weekly claims and the pattern that that time series has followed in previous recessions. The four-week moving average of not seasonally adjusted weekly claims has peaked less than eight weeks before the end* of the each recession since 1970 (see chart).

Click on the chart to enlarge.
The lead time was eight weeks in the 1973-75 recession, seven weeks in two recessions (1980 and 1981-82), six in 1970, five in 2001, and zero in 1991. The moving average declined essentially monotonically after each of those identified peaks.

During the current recession, the moving average saw a peak on the week that ended on April 4, 2009. That would put the end of the recession somewhere between April and May (zero to eight weeks later). And if the past is any indication, most likely in May.

The usual caveat applies: the pattern-recognition method is based on only six episodes of recession, and six is a very small number to make any claim on the significance of this finding. Moreover, each episode is spaced by several years from each other, so the hypothetical relationship between UI claims and the business cycle may have changed since last time.

I can’t help, nonetheless, to find some solace in that chart.

*Here I take the NBER dating of the business cycles. The NBER, however, provides the month in which a business cycle trough occurs, not the week. I take the liberty of dating the end of each recession on the last week of the month when the NBER identifies a business cycle trough.

Recession buzz: April update

Recession talk decreased slightly again in April. According to an index which includes eight newspapers, each publication included an average of 1.96 articles per day using the word “recession,” down from 2.16 in March and significantly below the level of 3.70 in January (see chart 1). The decrease occurred in spite of the continued softening of the job market in March, which was known the first week of April. The release of the first-quarter growth of GDP and the meeting of the FOMC committee, which might have generated some R-talk, occurred on the last days of the month, so their impact on R-word statistics probably straddled April and May.

Chart 1 (click to enlarge)

In spite of the diminishing buzz, the current level of talk is still consistent with an economy in recession, judging from historical trends (see chart 2).

Chart 2 (click to enlarge)


Previous updates: January, February , March



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Ranking of WSJ forecasters: May update

The GDP estimate for the first quarter is out, so it's time to update my ranking of the Wall Street Journal forecasters. (Remember: to pit forecasters against each other I use the Root Mean Squared Error (RMSE) and the most accurate forecaster is the one with the lowest RMSE, among all who have submitted at least ten forecasts since May of 2004. I only include the predictions submitted in the months of February, May, August and November for quarters Q1, Q2, Q3 and Q4, respectively. The Q1 forecast is the one submitted in February, the Q2 forecast is the one posted in May, and so on.)

According to the latest ranking, the most accurate forecaster is Gene Huang of FedEx, pushing Gary Thayer of A.G. Edwards to second place. Resler and Hoffman keep third and fourth place, respectively. The median forecast falls from 6th to 10th. The lanterne rouge continues to be James Smith of the University of North Carolina. At 2.6%, his forecast for 2008:Q1 was as inaccurate as usual.

The naive forecast, which is equal to the growth rate observed during the previous quarter, would have been spot-on this time, since GDP grew by 0.6% in both Q4 and Q1. Historically, however, it has performed worse than any forecaster but one.

Only Edward Leamer of UCLA Anderson Forecast was right on the mark. The predictions of 38 of the 52 forecasters were within one percentage point of the truth.


Top-20 WSJ forecasters, by Root Mean Squared Error (RMSE), as of 2008:Q1


Rank
Forecaster

Firm
RMSE

Absolute deviation for 2008:Q1
1
Gene Huang
FedEx Corp.
0.95
0.4
2
Gary Thayer*A.G. Edwards0.95
--
3
David Resler
Nomura Securities International
1.01
0.8
4
Stuart Hoffman
PNC Financial Services Group
1.01
0.6
5
Allen Sinai
Decision Economics Inc.
1.01
0.1
6
Dana JohnsonComerica Bank1.02
0.1
7
Nicholas S. PernaPerna Associates1.02
0.3
8
Mike Cosgrove
Econoclast
1.02
0.4
9
J. Prakken and C. Varvares
Macroeconomic Advisers
1.03
0.1
--
Median
--
1.05
0.6
10
Scott Anderson
Wells Fargo & Co.1.07
0.4
11
Nairmen Behravesh
Global Insight
1.08
0.9
12
John LonskiMoody's Investors Service
1.08
0.8
13
Edward Leamer
UCLA Anderson Forecast
1.08
0
14
R. Berner and D. Greenlaw
Morgan Stanley
1.08
1.3
15
Douglas Duncan
Mortgage Bankers Association
1.09
0.2
16
Robert DiClemente*
Citibank SSB
1.09
--
17
Diane Swonk
Mesirow Financial
1.09
0.1
18
Neal Soss
Credit Suisse
1.11
0.1
19
Dean Maki
Barclays Capital
1.12
0.4
20
David Rosenberg
Merrill Lynch
1.12
1
Source: WSJ's survey of forecasters and author's calculations.
*Not in WSJ group of forecasters, as of February 2008.

The May forecast for Q2 is also available now. On average, the top five forecasters according to my ranking predict growth of -0.1%. The median of all forecasts is 0.3%.

Previous ranking

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