economic outlook · 10/4/2017 · without hurricanes harvey and irma 3.55 2.81 difference-0.56...
TRANSCRIPT
Economic OutlookNational Conference of State
Legislatures
October 4, 2017
Brent H. Meyer
Policy Advisor and Economist
Federal Reserve Bank of Atlanta
*The views herein are my own and do not necessarily reflect those of the Federal Reserve Bank of Atlanta or
the Federal Reserve System.
2
Summary of economic data and the policy environment
1. Before the recent hurricanes, the incoming economic data pointed to an economy
that was expanding at a 2 percent pace (or maybe a touch above).
2. We think the hurricanes will have a substantial impact on the near-term quarter-to-
quarter swings in output growth, but will dissipate by mid-next year.
3. The economic growth we have enjoyed over the balance of the recovery has been
sufficient to bring the unemployment rate down to levels we saw before the 2007-
09 recession.
4. However, despite significant improvement in labor market conditions, wage growth
has remained muted and inflation has softened since the beginning of the year.
5. Despite uncertainty regarding underlying trend inflation and the amount of slack in
the economy, the median projection from the September FOMC meeting
continued to mark in another rate increase in December.
The available economic data suggest some momentum heading into the second half of
the year. Economists surveyed by the Wall Street Journal see the economy continuing on
around a 2.4 percent trajectory next year (a bit above the median FOMC member’s
forecast (2.1 percent for 2018).
3
-2
-1
0
1
2
3
4
5
2012 2013 2014 2015 2016 2017 2018
Real GDP Growth and Forecastsannualized percent change
Year over year percent change
1-qtr annualizedpercent change
Source: Bureau of Economic Analysis, ; WSJ Forecasting Survey (Sept 2017); Haver Analytics data through Q2-2017
GDPNow
estimate
(2.7%)
WSJ Panel
forecasts
4
0
10
20
30
40
50
60
70
80
2014 2015 2016 2017
Subjective Balance of Risk to Real GDP Growth ProjectionsPercentage of “Upside” Responses Plus Half Percentage of “Balanced” Responses
FOMC SEP Projections
WSJ Forecast Survey (Growth over next 4 quarters)
After the presidential election, the consensus from the Wall Street Journal Forecast Survey changed the balance of risk on
real GDP growth over the next four quarters from “Downside” to “Upside”, likely on expectations of fiscal stimulus and tax
reform. That enthusiasm has since waned, as slightly more panelists view risks tilted to the “Downside”. Over the past
several years, the responses have been highly correlated (r=0.89) with the analogously defined net response on the balance
risk for GDP growth in the SEP.
2016
Presidential
Election
Sources: Federal Reserve Board of Governors Summary of Economic Projections and Wall Street Journal Economic Forecast Survey
Our in-house tracking estimate for Q3 growth was holding up around 3
percent until we started getting data impacted by the recent storms.
5
Evolution of Atlanta Fed GDPNow real
GDP forecast for 2017: Q3quarterly percent change (SAAR)
Note: The top (bottom) 10 forecast is an average of the highest (lowest) 10 forecasts in the Blue Chip survey.
Retail Sales (Aug)
and IP (Aug)
ISM
manu.
(Sept)
GDPNow rebounded to 2.7 percent on the apparent “strength” in the ISM
report, but some of that “strength” likely reflects the impact of the recent
hurricanes.
6Source: Institute for Supply Management; Haver Analytics
40
45
50
55
60
65
70
2007 2009 2011 2013 2015 2017
ISM Manufacturing PMI: Supplier Deliveries Index Diffusion Index (+50 = expansion)
Private forecasters, with a huge degree on uncertainty, have marked a reduction in Q3 growth of roughly ½ - 1
percentage point, offset by a similarly-sized rebound in Q4 due to the recent storms. The table below is an empirical
estimate based on a recent Goldman Sachs study relating monthly changes in economic activity to 43 major natural
disasters. Using 26 of the largest natural disasters since 1980 [excluding droughts] our findings largely resemble their
findings.
7
2017:q3 growth
(SAAR)
2017:q4 growth
(SAAR)
Real GDP Growth
With Hurricanes Harvey and Irma 2.99 3.32
Without Hurricanes Harvey and Irma 3.55 2.81
Difference -0.56 0.52
Industrial Production Growth
With Hurricanes Harvey and Irma 1.86 4.38
Without Hurricanes Harvey and Irma 2.76 2.60
Difference -0.90 1.77
Real PCE Growth (using 5 lags of PCE growth)
With Hurricanes Harvey and Irma 2.45 2.81
Without Hurricanes Harvey and Irma 2.94 2.97
Difference -0.49 -0.17
Sources: Goldman Sachs, Hurricane Handbook: Natural Disasters and Economic Data 9 September 2017 and US Daily: Hurricanes Irma and Harvey to Delay but Not Derail US
Growth 11 September 2017; Bureau of Economic Analysis; Federal Reserve Board and National Oceanic And Atmospheric Administration
In a survey that was in the field shortly after Hurricane Irma showed
that the majority of the district experienced little-to-moderate disruption
of operations and sales.
8Source: FRBA Business Inflation Expectations Survey, September 2017
9Source: FRBA Business Inflation Expectations Survey, September 2017
Perhaps a sign of resilience, nearly 60 percent of our panel members
expect normal operations to resume within a week, while just over 10
percent expect operations to be impacted for longer than a quarter.
Consumer attitudes appear to be unfazed by the
recent storms (or anything else for that matter).
10
20
40
60
80
100
120
140
2007 2009 2011 2013 2015 2017
Consumer AttitudesIndex (Nov. 2016 = 100)
Consumer confidence (Conf. Board) Consumer Sentiment (U of M)
Sources: University of Michigan Survey of Consumers; Conference Board; Haver Analytics data through September 2017
Rising household net worth, typically associated with declines in the
saving rate, should provide ongoing support for consumer spending.
11
1.0
2.5
4.0
5.5
7.0
8.5
10.0
400
450
500
550
600
650
700
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Household Net Worth and Personal Savingspercent of disposable income, quarterly
Household Net Worth
Personal Saving Rate
Sources: U.S Bureau of Economic Analysis, Federal Reserve Board; Haver Analytics
Personal savings data through Q2-2017,
Household net worth data through Q1-2017
Note: Saving rate adjusted for effects of tax changes in 2012
Since the beginning of the year the dollar has depreciated by roughly 7 percent, undoing
some of its run-up over the past two years. Amid the depreciation, export activity has
increased and prospects for the manufacturing sector have brightened considerably.
12
100
105
110
115
120
125
130
Jan-14 Jul-14 Jan-15 Jul-15 Jan-16 Jul-16 Jan-17 Jul-17
Nominal Broad Trade-Weighted Exchange Value of the US Dollar
Jan-97=100
Source: Federal Reserve Board; Haver Analytics
27%
Jan-14 Jul-14 Jan-15 Jul-15 Jan-16 Jul-16 Jan-17 Jul-17
45
50
55
60
65
ISM Manufacturing IndexesSA, 50+=expansion
ISM Manufacturing: PMI Composite Index
ISM Manufacturing: New Export Orders
Source: Institute for Supply Management; Haver Analytics data through Sept 2017data through Sept 29, 2017
-7.0%
0
50
100
150
200
250
300
350
400
11 12 13 14 15 16 17
Payroll Employment Growththousands of jobs, SA
Sources: Bureau of Labor Statistics, staff calculations; Haver Analytics data through August 2017
12-month average
Monthly change
Nonfarm payrolls continue to trend at a pace much higher than what’s needed to sustain
the current (already low) unemployment rate. Based on the initial claims for unemployment
insurance in hurricane-impacted areas, we’ll probably see a weak print in September.
13
113k jobs needed to maintain
current unemployment rate if
labor force participation rate
stays constant
Avg. monthly change in nonfarm payrolls over the last:
1 mo. 3 mo. 6 mo. 9 mo. 12 mo. 24 mo.
156,000 185,000 160,000 173,000 175,000 191,000
Both the narrow (U3) unemployment rate and the broader (U6)
underemployment rate suggest that labor utilization is about “normal.”
14
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
05 06 07 08 09 10 11 12 13 14 15 16 17
Unemployment (U-3) and Underemployment (U-6) Rates percent
(U6) 2005-2007 average
Un(under)employment
rate (U6). Includes
PTER and marginally
attached workers
Unemployment rate (U3)
FOMC participants’ median unemployment
rate estimate (from June ’17 SEPs)
data through August 2017Sources: Bureau of Labor Statistics; FOMC, Jun. 2017 Summary Economic Projections; Haver Analytics
2
4
6
8
10
01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17
Available persons per job openingPeople per job opening
15
One alternative way to measure labor market slack is to look at how many potential
applicants a firm has to choose from when attempting to fill a vacancy. This measure
adds up the total number of unemployed persons plus the number of people not in the LF
but want a job and divides that by the number of job openings.
Sources: Bureau of Labor Statistics; author’s calculations
Pre-crisis average (3.3)
Through August 2017 (job opening data was projected for August)
16
Despite the apparent pressure, various measures of wage
and labor compensation growth still remain below their pre-
recession levels.
Sources: Bureau of Labor Statistics; Atlanta Fed; Haver AnalyticsECI data through Q2-2017, Wage growth tracker data and
AHE through August 2017
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
5.5
07 08 09 10 11 12 13 14 15 16 17
Measures of wage, earnings and compensation growth4-quarter or 12-month percent change
Employment Cost Index: Total Compensation
Payroll survey: Average hourly earnings
Atlanta Fed Wage Growth Tracker
One simple model for nominal wage growth is to adding together productivity growth—
how rapidly the output generated by each hour of labor is increasing—and inflation. What
the picture shows is that relative to the drop off in inflation and productivity growth,
wage growth looks good right now.
17
0
2
4
6
8
10
12
1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005 2009 2013 2017
Nominal Wage Growth, Inflation, and Productivitypercent change, annual rate over past three years
Productivity + Inflation
Compensation per hour
Notes: Productivity is nonfarm business sector output per hour worked. Inflation is the PCE price index. Compensation per hour (from BLS) includes wages and salaries of
employees plus employers’ contributions for social insurance and private benefit plans.
Sources: Bureau of Labor Statistics; Bureau of Economic Analysis
18Sources: Bureau of Economic Analysis; FRB Dallas; Haver Analytics data through August 2017
1.0
1.2
1.4
1.6
1.8
2.0
2.2
2.4
13 14 15 16 17
FRB Dallas trimmed-mean PCE Inflationannualized percent change
FOMC’s inflation target
The most puzzling aspect of our current economic situation is that, despite what
looks like solid output growth and (apparently) tight labor markets, inflation has
softened and wage growth has flattened out.
12-month
6-month (a.r.)
5-year (a.r.)
Chair Yellen, in a speech on September 26th, argued that a lot of the estimated
shortfall this year is due to “other” (i.e. things our basic models can’t explain).
19
-15
-10
-5
0
5
10
15
20
99 01 03 05 07 09 11 13 15 17
Lodging Away From Home CPIPercent change, SAAR
5-month 12-month
20
These are a couple of the categories that analysts are pointing to as evidence of
“idiosyncratic noise” that has impacted inflation since early this year. But,
remember back to two slides ago?
Source: Bureau of Labor Statistics
-12
-10
-8
-6
-4
-2
0
2
4
6
8
99 01 03 05 07 09 11 13 15 17
Communication CPIPercent change, SAAR
5-month 12-month
21Sources: Bureau of Economic Analysis; FRB Dallas; Haver Analytics data through August 2017
1.0
1.2
1.4
1.6
1.8
2.0
2.2
2.4
13 14 15 16 17
FRB Dallas trimmed-mean PCE Inflationannualized percent change
FOMC’s inflation target
This measure of underlying inflation minimizes distortions from large price
swings by “trimming-out” the largest price increases and decreases each month.
12-month
6-month (a.r.)
5-year (a.r.)
-2
-1
0
1
2
3
4
5
6
2005 2007 2009 2011 2013 2015 2017
Global Core InflationYear-over-year percent change
Euro Area Germany Canada UK Japan MA: Broad foreign CPI
A potential explanation is that some sort of global
phenomenon is driving domestic inflation rates lower.
22
Note: MA’s Core CPI series is a weighted average of these countries: Canada, Germany, France, Italy, Netherlands, Belgium, Spain, Ireland, Austria, Finland, Portugal, Greece, Japan, Mexico, China,
UK, Taiwan, Korea, Singapore, Hong Kong, Malaysia, Brazil, Switzerland, Thailand, Australia, Indonesia, Philippines, Russia, India, Sweden, Saudi Arabia, Israel, Argentina, Venezuela, Chile, and
Colombia.
Sources: Macroeconomic Advisers; Haver Analytics’ G10 databases
Using a Phillips curve framework similar to what Chair Yellen put forth, I find that the influence of the
domestic output gap on inflation has diminished relative to the 1975-95 period. However, the trade-
weighted foreign GDP gap is not significant. What is interesting is that domestic inflation appears to
have become more sensitive to the relative price of imports since the early 1990s.
23
-2.5
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
1990 1993 1996 1999 2002 2005 2008 2011 2014 2017
10-year Rolling Window Coefficient Estimates
Coefficient on relative nonoil import prices
95 low
95 high
Sensitivity of Inflation to
Slack and Relative Import Prices
Coefficient
estimates
Domestic
Slack
Foreign
Slack
Relative
Import Prices
Full Sample
(1975-2017) 0.08** -0.04 0.35***
1975-1995 0.14*** 0.34 0.27
1995-2017 0.05 0.03 0.39***
Notes: Estimated from simple Phillips curve (similar to Yellen (2015))
where quarterly core PCE inflation depends on inflation expectations
(the Board’s PTR measure), 2 lags of quarterly core inflation, the
relative price of nonoil imports (index – q4/q4 core inflation), and
activity measures. Domestic slack is the CBO’s output gap. Foreign
slack is the cyclical series from HP filtering Macroadviser’s trade-
weighted foreign GDP index
24Sources: Bureau of Labor Statistics; Bureau of Economic Analysis data through July 2017
-16
-12
-8
-4
0
4
8
12
16
-6
-4
-2
0
2
4
6
12 13 14 15 16 17
Relative Nonoil Import Prices and the Trade weighted $ exchange value year-over-year percent change, monthly
Nonoil import prices - core PCE inflation
Nominal Broad Trade-Weighted ExchangeValue of the US$
Over the past few years, we could point to some downward pressure on
domestic inflation stemming from lower import prices. That no longer
appears to be the case.
An often discussed explanation for the low inflation readings we’ve seen over
the past 5 years is that we’re seeing an increase in competition. However, the
available evidence seems to run counter to this argument.
25
Sources: Federal Reserve Bank of Atlanta, Business Inflation Expectations Survey; Bureau of Labor Statistics; Producer Price Index program staff, “Wholesale and retail Producer
Price Indexes: margin prices,” Beyond the Numbers: Prices & Spending, vol. 1, no. 8 (U.S. Bureau of Labor Statistics, August 2012), https://www.bls.gov/opub/btn/volume-
1/wholesale-and-retail-producer-price-indexes-margin-prices.htm *Mathematically, a “margin price” is the current selling price minus the current acquisition price.
-45
-40
-35
-30
-25
-20
-15
-10
100
102
104
106
108
110
112
114
116
118
2011 2012 2013 2014 2015 2016 2017
PPI: Retail trade margins index* vs the BIE margins indexIndexes
PPI: Retail trade margins (NSA, Jun-09=100)
Current Profit Margins Compared with Normal Times:Diffusion Index (0+=Greater) (RIGHT AXIS)
-10
-5
0
5
10
15
-3
-2
-1
0
1
2
3
4
5
13 14 15 16 17
Year-over-year
A less unconventional argument is that the unemployment rate might not be a sufficient
gauge of slack at the moment. The “prime-age” (25-54 years) employment-to-population
ratio is still below its level heading into the recession.
26
78.4
72
74
76
78
80
82
84
1998 2000 2002 2004 2006 2008 2010 2012 2014 2016
“Prime Age” (25-54 yrs.) Employment-to-Population Ratiopercent
Previous recovery avg. = 79.4
Sources: Bureau of Labor Statistics; staff calculations; Haver Analytics data through August 2017
-6
-5
-4
-3
-2
-1
0
1
2014 2015 2016 2017
Measures of resource slackPercentage points
BIE: Sales GAP CBO Output gap U. Rate gap (SEP median-u.rate, inverse)
One interesting perspective on resource slack comes directly from firms. We ask them, “By roughly
what percent are your firm's sales levels above/below "normal", if at all?” Movements in this alternative
estimate are highly correlated with the others and suggest a bit more slack remains in the economy.
27
Correlation with other popular resource gap
measures
CBO’s GDP gap 0.86
CBO’s UR gap (inverse) 0.86
Fed’s UR gap (inverse) 0.88
Capacity Utilization gap 0.78
Source: Atlanta Fed Business Inflation Expectations (BIE) Survey, June 2017; Congressional Budget Office; Fed Board; BLS; BEA; staff calculations
1.8
2
2.2
2.4
2.6
2.8
3
Jan-12 Jan-13 Jan-14 Jan-15 Jan-16 Jan-17
Firm Inflation Uncertainty(mean variance from subjective probability distributions)
5-10 years ahead
Next 12 months
0.5
1
1.5
2
2.5
3
3.5
Jan-12 Jan-13 Jan-14 Jan-15 Jan-16 Jan-17
Year-ahead and Longer-term Inflation Expectations of Firms
(mean expected value from subjective probability distributions)
5-10 years ahead
Next 12 months
Our data indicate that the year-ahead inflation expectations of firms have been at, or
slightly below, 2% over the past 5 years. Longer-term inflation expectations of firms has
been moving lower, gradually, as firms assess the likelihood of a high inflation outcome
has fallen.
28Source: FRBA Business Inflation Expectations Survey
36
38
40
42
44
46
48
2012 2013 2014 2015 2016 2017
Probability unit costs will rise more than 3% over long-term
We asked our Business Inflation Expectations Panel what inflation target (annual rate of inflation) they
believe the Federal Reserve is aiming for in the long run. A follow-up question asked whether they
believed the Federal Reserve was more likely to accept inflation above/below its inflation target. While
the typical respondent said 2% inflation was the target, she also said that target was not symmetric.
29Source: Atlanta Fed Business Inflation Expectations (BIE) Survey, April 2017
5%
0%2% 2%
48%
11%
22%
1%2%
6%
0%
10%
20%
30%
40%
50%
60%
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5 ormore
Inflation target (annual rate of inflation)
Firms' Understanding of the Federal Reserve's Inflation Target
percentage of responses
22%
38%
25%
15%
0%
5%
10%
15%
20%
25%
30%
35%
40%
more likely toaccept inflation
above its inflationtarget
more likely toaccept inflation
below its inflationtarget
equally likely toaccept inflation
above or below itsinflation target
Unsure
Firms' Perception of Federal Reserve's Tolerance for Inflation Above/Below its
Inflation Targetpercentage of responses
The median committee member still sees the
need for another rate hike by the end of the year.
30
FOMC participants’ assessments of appropriate monetary policy
(target range for the fed funds rate)
Source: Federal Open Market Committee, Summary Economic Projections, September 2017
Median
path
0
2
4
6
8
10
12
1960 1964 1968 1972 1976 1980 1984 1988 1992 1996 2000 2004 2008 2012 2016
The unemployment rate vs the CBO’s natural rate of unemployment percent
1987:Q3
1997:Q12005:Q4
1978:Q21971:Q4
1964:Q3
The red-shaded areas denote “high pressure” economies. According to a number of
studies, labor market activity has nonlinear effects on inflation during these periods. It
also happens to be the case that recessions are usually preceded by these “high
pressure” periods.
31Sources: Bureau of Labor Statistics; Congressional Budget Office (CBO); BEA; Federal Reserve Board
One concern that may temper the need for caution is if we slip further
into a “high pressure” period, wage growth and inflation may get away
from us.
32
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 10.5 11.0
Dallas Fed Nonlinear real-wage Phillips curve estimate with Employment
Cost Index and Unemployment Rate
Fo
ur-
qu
art
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nt
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an
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in
Em
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fla
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Su
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ore
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rs
Quarterly unemployment rate lagged four-quarters
Points from 1984:Q1 to 2008:Q2
**Note: Regresses real wage inflation against a constant, the lagged unemployment rate, and the inverse of the lagged unemployment rate.
Points from 2010:Q1 to
2017:Q1
08:Q2
Nonlinear Phillips curve fit to 84:Q1 –
08:Q2 data (black diamonds) using
specification from 2014 Economic Letter
by Richard Fisher and Evan Koenig**
10:Q1
17:Q1
Predicted value for 17:Q1
Forecast error for
2017q1: -0.5
percentage points
Predicted value for 18:Q2, it would require the ECI wage
compensation growth to accelerate 0.9 percentage points
to 3.3 percent (roughly the pre-recession level)
15:Q2
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