Monday, May 23, 2011
Sunday, May 22, 2011
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
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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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. Edwards | 0.95 | -- |
| 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 Johnson | Comerica Bank | 1.02 | 0.1 |
| 7 | Nicholas S. Perna | Perna Associates | 1.02 | 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 Lonski | Moody'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 |
*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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Saturday, May 21, 2011
Economy Slowing Says Calculated Risk
Great Blogger, Calculated Risk "Clearly the economy is slowing sharply"
Friday, May 20, 2011
Thursday, May 19, 2011
Wednesday, May 18, 2011
Tuesday, May 17, 2011
Nouriel Roubini: "clear by now that a severe U.S. recession is inevitable in next few months."
Nouriel Roubini, a leading economist at New York University, is now saying that a US Recession is almost here:
"It is increasingly clear by now that a severe U.S. recession is inevitable in next few months. Those of us who warned for the last 12 months about a combination of a worsening housing recession, a severe credit crunch and financial meltdown, high oil prices and a saving-less and debt-burdened consumers being on the ropes causing an economy-wide recession were repeatedly rebuffed the consensus view about a soft landing given the presumed resilience of the US consumer."Roubini is a smart economist who often goes against the consensus view."But the evidence is now building that an ugly recession is inevitable."
Monday, May 16, 2011
Sunday, May 15, 2011
Sugar Giants Shove Their Sweetener
by Chris Tenove
Jul/Aug 2003 Issue
What does anybody know about the sugar industry? The people who put the frosting on the frosted flakes keep a low profile and are happy when folks are too busy eating to ask a lot of questions. Now, though, a dust-up with the World Health Organization (WHO) has flushed them into the limelight, where they're pitting profits against public health.
The conflict was inflamed by a new set of dietary guidelines drawn from two years of research by the WHO and the UN Food and Agricultural Organization. The guidelines are part of a worldwide strategy to tame the swelling epidemic of obesity, diabetes, osteoporosis and cardiovascular diseases. One recommendation is that free sugars (i.e. sugar added to foods) should make up no more than 10 percent of our daily caloric intake. The sugar lobby reacted to that suggestion like a toddler asked to hand back his Halloween booty...
'It was particularly stupid for them to put in writing that they're going to try to get Congress to take away WHO's money,' says Michael Jacobsen, executive director of the Center for Science in the Public Interest. 'It gave consumers a chance to see the kind of bullying that is usually done behind closed doors.' [Adbusters]
Saturday, May 14, 2011
A ranking of WSJ forecasters
For a number of years, The Wall Street Journal has been conducting a survey of economic forecasts. The newspaper is kind enough to publish the prediction of each forecaster, so we can entertain ourselves observing how they fare.
I restrict my attention to quarterly forecasts of GDP growth. Between 2004 and 2007, 27% of the predictions were within 0.5 percentage points of the actual outcome (see Table 1), whereas 56% (27% + 29%) were within one percentage point. Or, if you’re a member of the empty-glass club, 44% missed the target by more than one point.
Table 1. Distribution of accuracy of forecasts (2004-2007)
Source: WSJ's survey of forecasters and author's calculations
To pit forecasters against each other I use the Root Mean Squared Error (RMSE), a one-number summary of the deviations of several forecasts. The RMSE punishes both positive and negative deviations equally, but penalizes big errors proportionally more than small ones*. I also can use it to form confidence intervals.
According to the RMSE measure, the most accurate forecaster is Gary Thayer, of the firm A.G. Edwards, although he no longer participates in the survey. The second most-accurate forecaster, and still in the panel, is Gene Huang of FedEx. (See Table 2.) The best forecaster is able to predict GDP growth within 1.67 percentage points, at a 90% level of confidence. (That means that if he posted 100 forecasts, 90 of them would deviate from the actual GDP growth rate by plus or minus 1.67 percentage points.)
Table 2. Top-20 WSJ forecasters, by Root Mean Squared Error (RMSE)
Source: WSJ's survey of forecasters and author's calculations.
*Not in WSJ group of forecasts anymore, as of November 2007.
It is well known that, over time, a group’s forecast is closer to the mark than almost any particular individual’s. Among the WSJ panel it’s no different: the median forecast is sixth in the ranking, out of 47. The same conclusion applies to the average forecast (average and median are very close to the each other in every release of the WSJ survey).
The top participants in the group hold but a tiny advantage over the rest. Even the 20th most accurate person has a margin of error of just over 2 percentage points, versus 1.67 points for the top forecaster. It’s not surprising then that rankings tend to change frequently. For example, at the end of 2006 the top five forecasters were (latest ranking in parentheses): Thayer (1), Rosenberg (17), Perna (8), Sinai (5) and Lonski (14).
Catching a “hot streak” seems to be exceedingly difficult too. Suppose that we define “winning” as being among the 50% most-accurate accurate forecasts for a given quarter. (A rather modest victory, may I say.) By that measure, only 37% of successes were followed by a second win, 31% of two-in-a-row’s were followed by a third success, and just 17% of those were followed by a fourth one.
Can a simple predictor outperform the pros? Michael Bryan of the Federal Reserve of Cleveland, whose commentary I follow in this post, asks that question. He compares the predictions in the Survey of Professional Forecasters (SPF) with the naïve forecast that next period’s outcome will be the same as the latest observed outcome. In terms of my data, that is the prediction that GDP growth in, say, 2008:Q1 will be the same as in 2007:Q4.
Bryan finds that 53% of economists made worse predictions than the naïve forecast. The WSJ panel shows much better marksmanship. All of them performed better than the naïve forecast, except one. (The exception is James F. Smith of Western Carolina University, and by a long shot. His RMSE is 2.83, whereas that of the naïve forecast is 1.89. Compare with the values in Table 2.)
By Clay Bennett
I restrict my attention to quarterly forecasts of GDP growth. Between 2004 and 2007, 27% of the predictions were within 0.5 percentage points of the actual outcome (see Table 1), whereas 56% (27% + 29%) were within one percentage point. Or, if you’re a member of the empty-glass club, 44% missed the target by more than one point.
Table 1. Distribution of accuracy of forecasts (2004-2007)
| Forecasts within... | Percentage |
| 0.5 percentage points (p.p.) of actual value | 27.2 |
| 0.5 - 1 p.p. | 28.9 |
| 1 - 1.5 p.p. | 22.6 |
| 1.5 - 2 p.p. | 13.7 |
| 2 - 2.5 p.p. | 5.2 |
| over 2.5 p.p. | 2.4 |
| All | 100 |
To pit forecasters against each other I use the Root Mean Squared Error (RMSE), a one-number summary of the deviations of several forecasts. The RMSE punishes both positive and negative deviations equally, but penalizes big errors proportionally more than small ones*. I also can use it to form confidence intervals.
According to the RMSE measure, the most accurate forecaster is Gary Thayer, of the firm A.G. Edwards, although he no longer participates in the survey. The second most-accurate forecaster, and still in the panel, is Gene Huang of FedEx. (See Table 2.) The best forecaster is able to predict GDP growth within 1.67 percentage points, at a 90% level of confidence. (That means that if he posted 100 forecasts, 90 of them would deviate from the actual GDP growth rate by plus or minus 1.67 percentage points.)
Table 2. Top-20 WSJ forecasters, by Root Mean Squared Error (RMSE)
Rank | Forecaster | Firm | RMSE | Forecasts' 90% confidence margin (p.p.) |
| 1 | Gary Thayer* | A.G. Edwards | 0.95 | 1.67 |
| 2 | Gene Huang | FedEx Corp. | 0.98 | 1.72 |
| 3 | David Resler | Nomura Securities International | 1.02 | 1.79 |
| 4 | Stuart Hoffman* | PNC Financial Services Group | 1.03 | 1.82 |
| 5 | Allen Sinai | Decision Economics Inc. | 1.05 | 1.83 |
| -- | Median forecast | -- | 1.05 | 1.83 |
| 6 | Mike Cosgrove | Econoclast | 1.05 | 1.84 |
| 7 | Nicholas S. Perna | Perna Associates | 1.05 | 1.85 |
| 8 | Dana Johnson | Comerica Bank | 1.06 | 1.88 |
| 9 | J. Prakken and C. Varvares | Macroeconomic Advisers | 1.06 | 1.86 |
| 10 | R. Berner and D. Greenlaw* | Morgan Stanley | 1.07 | 1.87 |
| 11 | Nairmen Behravesh | Global Insight | 1.09 | 1.90 |
| 12 | Robert DiClemente* | Citibank SSB | 1.09 | 1.92 |
| 13 | John Lonski | Moody's Investors Service | 1.09 | 1.91 |
| 14 | Scott Anderson | Wells Fargo & Co. | 1.11 | 1.97 |
| 15 | Douglas Duncan | Mortgage Bankers Association | 1.12 | 1.97 |
| 16 | David Rosenberg | Merrill Lynch | 1.13 | 1.97 |
| 17 | Diane Swonk | Mesirow Financial | 1.13 | 1.99 |
| 18 | David Lereah* | National Association of Realtors | 1.13 | 1.99 |
| 19 | Neal Soss | CSFB | 1.15 | 2.01 |
| 20 | Paul Kasriel | The Northern Trust | 1.15 | 2.02 |
*Not in WSJ group of forecasts anymore, as of November 2007.
It is well known that, over time, a group’s forecast is closer to the mark than almost any particular individual’s. Among the WSJ panel it’s no different: the median forecast is sixth in the ranking, out of 47. The same conclusion applies to the average forecast (average and median are very close to the each other in every release of the WSJ survey).
The top participants in the group hold but a tiny advantage over the rest. Even the 20th most accurate person has a margin of error of just over 2 percentage points, versus 1.67 points for the top forecaster. It’s not surprising then that rankings tend to change frequently. For example, at the end of 2006 the top five forecasters were (latest ranking in parentheses): Thayer (1), Rosenberg (17), Perna (8), Sinai (5) and Lonski (14).
Catching a “hot streak” seems to be exceedingly difficult too. Suppose that we define “winning” as being among the 50% most-accurate accurate forecasts for a given quarter. (A rather modest victory, may I say.) By that measure, only 37% of successes were followed by a second win, 31% of two-in-a-row’s were followed by a third success, and just 17% of those were followed by a fourth one.
Can a simple predictor outperform the pros? Michael Bryan of the Federal Reserve of Cleveland, whose commentary I follow in this post, asks that question. He compares the predictions in the Survey of Professional Forecasters (SPF) with the naïve forecast that next period’s outcome will be the same as the latest observed outcome. In terms of my data, that is the prediction that GDP growth in, say, 2008:Q1 will be the same as in 2007:Q4.
Bryan finds that 53% of economists made worse predictions than the naïve forecast. The WSJ panel shows much better marksmanship. All of them performed better than the naïve forecast, except one. (The exception is James F. Smith of Western Carolina University, and by a long shot. His RMSE is 2.83, whereas that of the naïve forecast is 1.89. Compare with the values in Table 2.)
By Clay Bennett
Friday, May 13, 2011
Wednesday, May 11, 2011
Tuesday, May 10, 2011
Alien arguments
It’s again that time of the year when some people fill out a lot of forms and everyone gets mad at the government. No, it’s not taxes; it’s the visa program for skilled workers.
April 1st marks the beginning of the annual application period. The government sets a general quota of 65,000 H-1B visas, plus 20,000 for people with a graduate degree from a U.S. institution. Last year over 100,000 applications swamped the immigration service on the very first day. This year people are expecting an even bigger excess demand. A lottery will decide who gets to live and work in the U.S.
Over the next two weeks we shall witness a repetition of last year’s debate. On one side, businesses and pro-immigration groups advocate lifting the cap. Skilled labor, they say, gives the U.S. an edge in high human-capital sectors, particularly science and technology, and contributes to faster growth. The country should, therefore, welcome as much skilled labor as employers will bear. On the other corner, some professionals in the IT industry and protectionists would like to restrict the hiring of foreigners, if not kill the program altogether. Their main complaint is that employers just want to hire foreign computer programmers and engineers on the cheap.
I have been indoctrinated to believe in the virtues of the free movement of goods, capital and labor. But if we’re going to make any progress in this quarrel, both sides should come clean. Free-traders must acknowledge that immigrants will lower wages in some sectors; some Americans will lose their jobs to foreign nationals. And any system is susceptible to abuse from greedy employers. Failing to mention the negatives does little service to the cause. And simply stating that “the country is better off on the whole” won’t cut it.
Protectionists should accept that the job market is not always a zero-sum game. In many instances, a job “lost” to a foreigner generates several other complementary positions, whether horizontally or vertically. Immigration detractors must also admit that, if skilled people don’t move in, capital and entire companies will move out. Don’t forget that Canada and the UK, just to mention two close rivals, have much friendlier immigration policies than the U.S.
Evidence of the effects of immigration is tenuous, which keeps skepticism alive. For example, a 2007 study by Ottaviano and Peri reported that immigrant and native workers are not perfect substitutes within skill groups —their study included all education levels. Their conclusion, another paper discovered, hinges on a disputable assumption, and has been promptly proven wrong. (George Borjas briefs us in his blog. The paper also provides a short review of the literature on the substitutability of immigrants and natives.)
About.com: political humor
April 1st marks the beginning of the annual application period. The government sets a general quota of 65,000 H-1B visas, plus 20,000 for people with a graduate degree from a U.S. institution. Last year over 100,000 applications swamped the immigration service on the very first day. This year people are expecting an even bigger excess demand. A lottery will decide who gets to live and work in the U.S.
Over the next two weeks we shall witness a repetition of last year’s debate. On one side, businesses and pro-immigration groups advocate lifting the cap. Skilled labor, they say, gives the U.S. an edge in high human-capital sectors, particularly science and technology, and contributes to faster growth. The country should, therefore, welcome as much skilled labor as employers will bear. On the other corner, some professionals in the IT industry and protectionists would like to restrict the hiring of foreigners, if not kill the program altogether. Their main complaint is that employers just want to hire foreign computer programmers and engineers on the cheap.
I have been indoctrinated to believe in the virtues of the free movement of goods, capital and labor. But if we’re going to make any progress in this quarrel, both sides should come clean. Free-traders must acknowledge that immigrants will lower wages in some sectors; some Americans will lose their jobs to foreign nationals. And any system is susceptible to abuse from greedy employers. Failing to mention the negatives does little service to the cause. And simply stating that “the country is better off on the whole” won’t cut it.
Protectionists should accept that the job market is not always a zero-sum game. In many instances, a job “lost” to a foreigner generates several other complementary positions, whether horizontally or vertically. Immigration detractors must also admit that, if skilled people don’t move in, capital and entire companies will move out. Don’t forget that Canada and the UK, just to mention two close rivals, have much friendlier immigration policies than the U.S.
Evidence of the effects of immigration is tenuous, which keeps skepticism alive. For example, a 2007 study by Ottaviano and Peri reported that immigrant and native workers are not perfect substitutes within skill groups —their study included all education levels. Their conclusion, another paper discovered, hinges on a disputable assumption, and has been promptly proven wrong. (George Borjas briefs us in his blog. The paper also provides a short review of the literature on the substitutability of immigrants and natives.)
About.com: political humor
