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

er

pe

rce

nt

ch

an

ge

in

Em

plo

ym

en

t C

os

t In

de

x f

or

wa

ge

s a

nd

sa

lari

es

le

ss

me

dia

n 1

0-y

ea

r C

PI in

fla

tio

n e

xp

ec

tati

on

s f

rom

Su

rve

y o

f P

rofe

ss

ion

al F

ore

ca

ste

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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