The Use and Abuse of Real-Time and
Anecdotal Information in Monetary Policymaking
Evan F. Koenig
Senior Economist and Vice President
Federal Reserve Bank of Dallas
Dallas, Texas
USA
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 1

Main points
• Data revisions complicate policy
• Usually, revisions are not given proper treatment
• Anecdotal/qualitative information potentially valuable
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 2

Example of the revisions problem:
U.S. monetary policy in the 1990s
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 3

Professional forecasters over-predicted inflation during most of the 1990s
2
1
0
Percent/Yr.
7
6
5
4
3
Blue Chip Forecasts
CPI Inflation
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 4

A candidate explanation: profitability
• profitability = (labor productivity)/(real wage)
= price/(labor cost per unit output)
• high profitability ⇒
▪ expand output and employment
▪ raise wages or cut prices
• 1970s: productivity deceleration + sluggish real wage ⇒ low profitability
• 1990s: productivity acceleration + sluggish real wage ⇒ high profitability
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 5

Profitability movements explain much of the NAIRU’s variation
Percent
11
10
9
8
7
6
Inferred NAIRU
5
4
3
Profitability (inverted)
'68 '70 '72 '74 '76 '78 '80 '82 '84 '86 '88 '90 '92 '94 '96 '98
Ratio
0.76
0.74
0.72
0.70
0.68
0.66
0.64
0.62
0.60
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 6

Profitability apparently a powerful long-leading unemployment indicator
Percent
11
10
Unemployment Rate
7
6
5
9
8
4
3
2
Profitability
(inverted, shifted 3 yrs.)
'62 '64 '66 '68 '70 '72 '74 '76 '78 '80 '82 '84 '86 '88 '90 '92 '94 '96 '98 '00 '02 '04 '06
0.67
0.66
0.65
0.64
0.63
0.62
0.61
Ratio
0.72
0.71
0.70
0.69
0.68
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 7

Profitability estimates are subject to large revisions
1.50
1.48
1.46
1.44
Ratio
1.58
1.56
1.54
1.52
Initial Estimate
Today's Estimate
'82 '85 '88 '91
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004
'94 '97 '00 '03
8

Inflation pressures: revised vs. real time
Percent
Recession
11
10
Unemployment Rate
(left axis)
Recession
9
8
Ratio
0.76
0.74
7
6
Real-Time Profitability
(inverted, right axis)
0.72
0.70
0.68
0.66
5
4
3
0.64
Revised Profitability
(inverted, right axis)
'81 '82 '83 '84 '85 '86 '87 '88 '89 '90 '91 '92 '93 '94 '95 '96 '97 '98 '99
0.62
0.60
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 9

Apples and oranges
• Data relevant for policy are 1st release or lightly revised (oranges)
• Forecasting models usually estimated using heavily revised data (apples)
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 10

Correct procedure: estimate using “realtimevintage” data
• “Real-time vintage” = at each point in sample, the 1st release and lightly revised data then available
• Requires short data series of many vintages
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 11

Alternatives to conventional statistics: anecdotal & qualitative data
“Who are you going to believe? Me or your lying eyes?”
–Groucho Marx
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 12

The Federal Reserve collects anecdotal information:
• Through Directors of 12 regional Reserve
Banks and their 25 Branches
• Through calls to business contacts prior to each FOMC meeting
▪ Each Reserve Bank prepares a call summary
▪ Summaries are assembled and released as the “Beige Book”
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 13

How useful is the Beige Book?
• Receives substantial press attention
• Has predictive power for output and employment
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 14

The collapse of high-tech industrial production
Index, 1997 = 100
320
310
300
290
280
270
260
250
240
Current vintage (left axis)
As of 1/17/01 (right axis)
Index, 1992 = 100
1400
1350
1300
1250
1200
1150
1100
1050
1000
950
900
Jan Mar May Jul Sep Nov Jan Mar May Jul Sep Nov
2000 2001
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 15

The collapse of high-tech industrial production
Index, 1997 = 100
320
310
300
290
280
270
260
250
240
Current vintage (left axis)
As of 1/17/01 (right axis)
Index, 1992 = 100
1400
1350
1300
1250
1200
1150
1100
1050
1000
950
900
Jan Mar May Jul Sep Nov Jan Mar May Jul Sep Nov
2000 2001
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 16

“Sales growth weakened sharply for producers of hightech equipment.”
“Businesses have begun to curtail technologyrelated investment.”
“Consumer demand for PCs has been weakening since the Fall of 2000.”
–FRB-Dallas Beige Book report,
January 2001
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 17

ISM Report on Business
• Survey of 400 manufacturing firms, nationwide
• Orders, output, jobs, etc.: expanding, contracting, or unchanged?
• Numerical index = % expanding + 0.5 ×
(% unchanged)
• PMI = weighted average of component numerical scores
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 18

Goldman-Sachs study shows PMI a big market mover
4.5
4.1
Basis-Point Impact on Treasury Notes
3.8
2.0
1.7
1.5
1.0
PMI GDP Payrolls Consumer
Confidence
Retail Sales Industrial
Production
Initial
Claims
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 19

Limitations of PMI/Beige Book
• Sampling not scientific (small, unrepresentative)
• Responses not properly weighted
• Beige Book difficult to interpret
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 20

Advantages of PMI/Beige Book
• Timely
• Little if any revision
• Respondents filter out short-term fluctuations
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 21

The PMI captures trends in factory output growth
-3
-6
-9
-12
9
6
3
0
Index
18
15
12
Factory Output
(annualized 3-mo. Growth)
Percent/Yr.
77
72
67
62
57
52
47
42
37
32
27
'84 '85 '86 '87 '88 '89 '90 '91 '92 '93 '94 '95 '96 '97 '98 '99 '00 '01 '02 '03 '04
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 22

The PMI captures trends in factory output growth
-3
-6
-9
-12
9
6
3
0
Index
18
15
12
Factory Output
(annualized 3-mo. Growth)
Percent/Yr.
77
PMI (3-mo. Avg.)
72
67
62
57
52
47
42
37
32
27
'84 '85 '86 '87 '88 '89 '90 '91 '92 '93 '94 '95 '96 '97 '98 '99 '00 '01 '02 '03 '04
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 23

Summary and Conclusions
• Don’t trust charts/forecasts that mix apples
(heavily revised data) and oranges (lightly revised data)
• Archive statistical releases!
• Anecdotal/qualitative information potentially quite helpful
OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 24

OECD World Forum “Statistics, Knowledge and Policy,” Palermo, 10-13 November 2004 25