Post on 06-Aug-2020
The Long-Term Impacts of COVID-19
Structural Economic and Demographic Changes
June 9, 2020 and June 11, 2020
FTI Consulting
2
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Disclaimer
The views in this presentation do not reflect the views of FTI Consulting.
Long-term economic effects
Long-term economic effects1
Long-term demographic effects2
Methodology and approach3
4
Economic and demographic impacts4
Two-factor growth model (inputs)“A beginning is a very delicate time.”
5
Labor Force Growth Rate (2021-2050)
Productivity Growth Rate (2021-2050)
Economic Growth Rate (2021-2050)
0.5%
1.0%
0.0%
-0.5%
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
4.0%
Scen
ario
1
Scen
ario
2
Scen
ario
3
1.5%
2.0%
1.0%
-0.5%
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
4.0%
Scen
ario
1
Scen
ario
2
Scen
ario
3
2.2%
3.7%
1.0%
-0.5%
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
4.0%
Scen
ario
1
Scen
ario
2
Scen
ario
3
Two-factor growth model (results)“Compound interest is the eighth wonder of the world.”
6
U.S. GDP in 2050 (2020 $ trillions)(assumes $21.0 trillion starting point)
$30.4
$36.6
$25.2
$0
$10
$20
$30
$40
$50
$60
Scen
ario
1
Scen
ario
2
Scen
ario
3
U.S. GDP per capita in 2050 (2020 $)
(assumes $63,500 starting point)
$95,300
$109,900
$82,600
$0
$20,000
$40,000
$60,000
$80,000
$100,000
$120,000
Scen
ario
1
Scen
ario
2
Scen
ario
3
U.S. average tariff rates (1821-2016)“The chief business of the American people is business.”
7
0%
10%
20%
30%
40%
50%
60%
70%
18
21
18
26
18
31
18
36
18
41
18
46
18
51
18
56
18
61
18
66
18
71
18
76
18
81
18
86
18
91
18
96
19
01
19
06
19
11
19
16
19
21
19
26
19
31
19
36
19
41
19
46
19
51
19
56
19
61
19
66
19
71
19
76
19
81
19
86
19
91
19
96
20
01
20
06
20
11
20
16
Tariff Rate on Total Imports Tariff Rate on Dutiable Imports
Yankee Trading (1934)
Hawley-Smoot (1930)
NAFTA (1994)
Tariff of Abominations (1828)
Underwood (1913)
Fordney-McCumber (1922)
Morrill (1861)
GATT (1947)Dingley (1897)
Kennedy Round (1967)
Developing fiscal pressures on the federal government“Flaws in the system will now become severe.”
8
0%
5%
10%
15%
20%
25%
30%
35%
40%
0%
5%
10%
15%
20%
25%
30%
35%
40%
19
62
19
66
19
70
19
74
19
78
19
82
19
86
19
90
19
94
19
98
20
02
20
06
20
10
20
14
20
18
20
22
20
26
20
30
20
34
20
38
20
42
20
46
20
50
Net
Inte
rest
/ F
eder
al R
even
ues
% o
f G
DP
Net Interest
Other Discretionary
Defense
Other Mandatory
Income Security
Medicaid et al.
Net Medicare
Social Security
Federal Revenues
Interest / Revenues
Historical Data CBO Projections
Long-term demographic effects
Long-term economic effects1
Long-term demographic effects2
Methodology and approach3
9
Economic and demographic impacts4
Baseline birth rates projected to decline only slowly“Sweet child in time, you’ll see the line.”
1. Slight drop in U.S. fertility rate associated with the “dot com” recession of the early 2000s
2. Peak prior to the Great Recession in 2007 at 2.84%
3. Roughly 2.75% would be the rate of population replacement
4. Rapid decline during the depths of the Great Recession
5. Continued rapid decline through the second half of the 2010s
6. No effect from the present recession and pandemic
7. Slow long-term decline in U.S. fertility rates projected
10
1.9%
2.0%
2.1%
2.2%
2.3%
2.4%
2.5%
2.6%
2.7%
2.8%
2.9%2
00
1
20
03
20
05
20
07
20
09
20
11
20
13
20
15
20
17
20
19
20
21
20
23
20
25
20
27
20
29
20
31
20
33
20
35
20
37
20
39
20
41
20
43
20
45
20
47
20
49
% o
f U
.S. w
om
en g
ivin
g b
irth
(ag
e 1
0 t
o a
ge 4
9)
1 2
5
4
6
7
3
U.S. Census Regions“No, it ain’t, but you gotta know the territory.”
11
Projected international migration by U.S. Census region“Our forefathers were kicked out of every decent country.”
12
0
200
400
600
800
1,000
1,200
1,4002
00
1
20
03
20
05
20
07
20
09
20
11
20
13
20
15
20
17
20
19
20
21
20
23
20
25
20
27
20
29
20
31
20
33
20
35
20
37
20
39
20
41
20
43
20
45
20
47
20
49
Net
inte
rnat
ion
al m
igra
nts
by
regi
on
(th
ou
san
ds)
Pacific
Mountain
West South Central
East South Central:
South Atlantic
West North Central
East North Central
Mid-Atlantic
New England
Historical Data REMI Projections
Some regions rely more on international migrants“See your future. Be your future.”
1. In the 2000s decade, the Pacific region (e.g., California) was the most dependent on migrants
2. The Midwest (ENC and WNC) along with the ESC (AL, KY, MS, and TN) were the least reliant in the historical data series
3. New England and the South Atlantic (stretching from MD south to Florida) take over the top spots in the late 2010s
4. These regions have the highest reliance in the forecast
5. West South Central (e.g., Texas) and the Pacific region are now projected in the middle, and the lowest regions are unchanged
13
0.0%
0.1%
0.2%
0.3%
0.4%
0.5%
0.6%
0.7%2
00
12
00
4
20
07
20
10
20
13
20
16
20
19
20
22
20
25
20
28
20
31
20
34
20
37
20
40
20
43
20
46
20
49
% o
f p
op
ula
tio
n m
ade
up
of
new
inte
rnat
ion
al m
igra
nts
New England
Mid-Atlantic
East North Central
West North Central
South Atlantic
East South Central
West South Central
Mountain
Pacific
1
2
3
4
5
Historical Data REMI Projections
Methodology and approach
Long-term economic effects1
Long-term demographic effects2
Methodology and approach3
14
Economic and demographic impacts4
REMI model structure“Theory is judged by its predictive power.”
15
REMI model inputs“I think I’m turning Japanese, I really think so.”
•Foreign export costs and foreign import costs increase by 10%
•Only applies to goods – e.g., manufacturing – but not to services
•Roughly symbolic of a partial return to the more protectionist, autarkic world of the 1920s with Fordney-McCumber, though not as extreme as Hawley-Smoot in the 1930s
International Trade
•Normally, a slow economy can depress the fertility rate, but it recovers
•The fertility rate for women of child-bearing age declined from 2.8% to 2.3% in the aftermath of the Great Recession – it never “recovered” after that economic upset
•Assume another permanent impact to the fertility rate (20%) because of COVID-19 and the economic, social, and political disruptions that are coming along with it
Fertility Rates
•Assume the long-term reduction in international migration of 20% compared to baseline
•Roughly the size of the effect during the Great Recession carried forward
•There was some recovery in the rate of international migration after the Great Recession, though the REMI project is for a return to the historic highs of the 1990s
International Migration
16
Potential model inputs not included in this simulation“We also know there are known unknowns.”
• Fears of pandemic could reduced urbanization in the U.S., reducing the productivity benefits of agglomeration (alternatively, more widespread telecommuting and allowing firms to access talent from a wider pool nationally could offset this effect)
• Low interest rates and exhausted federal resources is the justification for using the Keynesian closure in the simulation, but this analysis does not model any specific pullbacks with federal fiscal policy (e.g., defense cuts or entitlement reform) or problems provoked by a debt crisis (e.g., higher capital costs from higher interest rates/inflation)
• The simulation does not try to account for the fiscal pressures on states and localities, which are beset by declining revenues due to decreased economic activities, higher costs to deal with COVID-19, and difficult imbalances in their pension systems
• Did not attempt to model the medium-term or long-term effects of COVID-19 on special or particularly exposed economic sectors, such as commercial air travel, foodservice, hotels and accommodations, and the “live” arts, entertainment, and media sectors
• Did not attempt to integrate the deaths from COVID-19, which peak in the “85 years and over” cohort according to the CDC, into the analysis or results
17
Economic and demographic impacts
Long-term economic effects1
Long-term demographic effects2
Methodology and approach3
18
Economic and demographic impacts4
Economic and demographic summary“He’s King Midas with a curse, he’s King Midas in reverse.”
19
-10%
-8%
-6%
-4%
-2%
0%
2%
4%2
02
0
20
21
20
22
20
23
20
24
20
25
20
26
20
27
20
28
20
29
20
30
20
31
20
32
20
33
20
34
20
35
20
36
20
37
20
38
20
39
20
40
20
41
20
42
20
43
20
44
20
45
20
46
20
47
20
48
20
49
20
50
% d
elta
fro
m R
EMI S
tan
dar
d N
atio
nal
Co
ntr
ol
Total Population Labor Force Gross Domestic Product Price Index
Regional impacts to GDP vary slightly over time“You just stare, you’re such a cold fish.”
1. A region’s relative exposure to exporting goods (not services) is the determining factor for the regional results, and the West South Central region would have the highest risks here
2. The Pacific Region, which includes California, would have the lowest risk because more of its exports are in the service sector
3. Gradual decrease in all regions
4. “Pause” in the long-term impact because of the trade shock would be fully absorbed and before the reduced birth rate “hits” the labor market in the 2040s
5. The reduced birth rate would finally being to affect the labor market in the 2040s
20
-7%
-6%
-5%
-4%
-3%
-2%
-1%
0%
20
20
20
22
20
24
20
26
20
28
20
30
20
32
20
34
20
36
20
38
20
40
20
42
20
44
20
46
20
48
20
50
% d
elta
fro
m R
EMI S
tan
dar
d R
egio
nal
Co
ntr
ol
New England
Mid-Atlantic
East North Central
West North Central
South Atlantic
East South Central
West South Central
Mountain
Pacific1
2
3
4
5
Regional impacts to demographics also vary slightly“Children growing up, old friends growing older.”
1. Shock to immigration rates would affect all regions immediately
2. New England would have the largest impact to its population because it relies the most on immigrants for replenishment
3. The Pacific region would have the smallest impact to its population
4. By 2050, the regions that rely the most on native births to replace their population in the Midwest and the East South Central would start to “bend” downwards relative to the states that rely more on international migrants
21
-12%
-10%
-8%
-6%
-4%
-2%
0%2
02
0
20
22
20
24
20
26
20
28
20
30
20
32
20
34
20
36
20
38
20
40
20
42
20
44
20
46
20
48
20
50
% d
elta
fro
m R
EMI S
tan
dar
d R
egio
nal
Co
ntr
ol
New England
Mid-Atlantic
East North Central
West North Central
South Atlantic
East South Central
West South Central
Mountain
Pacific
1
2
3
4
Four-major age cohorts in the two simulations“Wondering how much I can take, should have tried to do some more.”
22
0
50
100
150
200
250
300
350
400
450
20
01
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04
20
07
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10
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13
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16
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22
20
25
20
28
20
31
20
34
20
37
20
40
20
43
20
46
20
49
Mill
ion
s o
f U
.S. r
esid
ents
by
age
Standard National Control
0 - 17 18-24 25-64 65+
0
50
100
150
200
250
300
350
400
450
20
01
20
04
20
07
20
10
20
13
20
16
20
19
20
22
20
25
20
28
20
31
20
34
20
37
20
40
20
43
20
46
20
49
Mill
ion
s o
f U
.S. r
esid
ents
by
age
COVID-19 Scenario
0 - 17 18-24 25-64 65+
75.0
31.2
191.9
84.7
57.1
24.7
84.6
182.5
# of adults (26-64) to support each retiree (65+)“I’m waiting for my royalty check to come, and it still hasn’t come yet.”
23
2.0
2.5
3.0
3.5
4.0
4.5
Rat
io o
f w
ork
ing
age
adu
lts
to r
etir
emen
t ag
e ad
ult
s
Standard National Control COVID-19 Scenario
Main takeaways“We are all interested in the future for that is where we are going to spend the rest of our lives.”
•Countries are likely to be less welcoming to international trade and the free flow of capital as they were from 1990 to 2019
•Security of medical supply chains added to previous concerns about security of defense, food, and infrastructure supply chains
•Smaller economy and higher cost-of-living in the U.S.
Economic
•U.S. birth rates experienced a sharp decline below the rate of replacement during the Great Recession – and never came back
•A similar drop (modeled here) would lead to a birth rate similar to Japan, and Japan is likely the best case study of these results
• Immigration rates are also unlikely to repeat past highs
Demographic
•The federal government, states, localities, and institutions (e.g., pension funds) faced stark difficulties even before COVID-19
•The virus and economic crisis have exacerbated this situation
•Reduced immigration and population growth implies a smaller tax base and worsening ratio of workers to retirees to support
Fiscal
24
Scott Nystrom
Senior Director
+1 (515) 290-6990
Scott.Nystrom@FTIConsulting.com