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May 27, 2020/Greg Evans, PhDAll views expressed are my own, not those of any other organization with which I am associated.

Preparing for the Economic Unknown

Topics

• Past Recessions– GDP and Output– Employment– Prices

• Enduring Effects– Government Intervention– Long-Run Pandemic Effects– Working from Home

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GDP Growth

GDP Growth

• Quite mild since the Great Depression• Recent recoveries have not returned to the

pre-recession rate of growth– Not much “bounce back”

• Will that change this time?– Maybe– From a shutting down and starting back up

perspective, the bounce back could be huge– But reopening appears to be going very slowly

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Unemployment

Unemployment

• Recent recessions have been slow to replace lost jobs

• Job losses generally lag the recession

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Number of Establishments

57,000

58,000

59,000

60,000

61,000

62,000

63,000

64,000

65,000

2001

-Q1

2001

-Q3

2002

-Q1

2002

-Q3

2003

-Q1

2003

-Q3

2004

-Q1

2004

-Q3

2005

-Q1

2005

-Q3

2006

-Q1

2006

-Q3

2007

-Q1

2007

-Q3

2008

-Q1

2008

-Q3

2009

-Q1

2009

-Q3

2010

-Q1

2010

-Q3

2011

-Q1

2011

-Q3

2012

-Q1

2012

-Q3

2013

-Q1

2013

-Q3

2014

-Q1

2014

-Q3

2015

-Q1

2015

-Q3

2016

-Q1

2016

-Q3

2017

-Q1

2017

-Q3

2018

-Q1

2018

-Q3

2019

-Q1

2019

-Q3

Number of Private Firms

Source: U.S. Bureau of Labor Statistics

Number of Establishments

• Steady downward trend that had turned upward recently

• Downward spike in the last recession came toward the end of the recession

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GDP and Fabricated Metal Production

-25

-20

-15

-10

-5

0

5

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Date

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

GDP Growth and Percent Change in Fabricated Metal Output Index

GDP Growth Fabricated Metal Output Index Growth

Source: U.S. Bureau of Labor Statistics and U.S. Bureau of Economic Analysis

GDP and Fabricated Metal Output

• Output in fabricated metal tracks the economy, but with considerably stronger spikes– A 1 percentage point change in GDP leads to a 2.7

percentage point change in the fabricated metal output index

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Prices

Prices

• Prices have tracked prices in Manufacturing, though there appears to be some divergence since the Great Recession

• Fabricated metals is a bit smoother than manufacturing generally

• But the prices track indistinguishably different from 1-for-1

• Prices spiked in the last recession– Suggests more Supply issue than Demand issue

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Prices

• What happened in April?– Fabricated Metals were flat (204.8 in January to

205.3 in April)– Total Manufacturing dropped from (196.8 in

January down to 186.5 in April

• Consumer Price Index has peaked in February• In Illinois, it peaked in January

Prices

• The drops in Consumer Price Index and Producer Price Index suggest either demand is holding in fabricated metals or supply is decreasing– Could be a lag in the data as it is still preliminary

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Export Prices

100

110

120

130

140

150

160

2005

-12

2006

-520

06-1

020

07-3

2007

-820

08-1

2008

-620

08-1

120

09-4

2009

-920

10-2

2010

-720

10-1

220

11-5

2011

-10

2012

-320

12-8

2013

-120

13-6

2013

-11

2014

-420

14-9

2015

-220

15-7

2015

-12

2016

-520

16-1

020

17-3

2017

-820

18-1

2018

-620

18-1

120

19-4

2019

-920

20-2

Export Price Index

Source: U.S. Bureau of Labor Statistics

Export Prices

• Steady incline• Recessions seem to pause the incline, but do

not cause a decline• What happened in April?

– Slight decrease from March (preliminary) from 150.1 down to 149.7

– Import prices are largely flat (an uptick since March, but that saw a decrease from February)

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Average Hourly Earnings

-1.5%

-1.0%

-0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

2006

-420

06-8

2006

-12

2007

-420

07-8

2007

-12

2008

-420

08-8

2008

-12

2009

-420

09-8

2009

-12

2010

-420

10-8

2010

-12

2011

-420

11-8

2011

-12

2012

-420

12-8

2012

-12

2013

-420

13-8

2013

-12

2014

-420

14-8

2014

-12

2015

-420

15-8

2015

-12

2016

-420

16-8

2016

-12

2017

-420

17-8

2017

-12

2018

-420

18-8

2018

-12

2019

-420

19-8

2019

-12

Percentage Change in Hourly Earnings for the Goods Sector and Fabricated Metal

Growth in Goods Earnings Growth in Fabricated Metal Earnings

Source: U.S. Bureau of Labor Statistics

Average Hourly Earnings

• Changes in Hourly Earnings in Fabricated Metals have not been particularly correlated with changes in Hourly Earnings in the Goods producing sector in general– A 1 percentage point increase in wages in the

Goods Producing Market leads to an about an 0.67 percentage point increase in wages in the Fabricated Metal Sector

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Average Hourly Earnings

• But the spikes in Hourly Earnings in Fabricated Metals are more pronounced– Standard Deviation for Goods Sector is only 0.33

compared to 0.52 for the Fabricated Metal

• What happened in April?– Actually increased (preliminary) from 26.23 to

26.79– Continuing a steady upward trend

Enduring Effects

• GDP is a flow, if the flow can get restarted, there does not need to be lasting damage– Imagine calculating your change in output from

Christmas Eve to Christmas Day, then from Christmas Day to December 26th

– In fact, the quarter-over-quarter numbers could be huge

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Enduring Effects

• Demand Recession versus Supply Recession– Government intervention is almost exclusively

targeted at stimulating demand– If it is a demand recession, normal government

intervention won’t help – you can’t stimulate demand if people can’t leave their house

– But attempts to stimulate demand feedback negatively into supply◦ What happens when you pay people to be unemployed?

– Also, government willingness to close businesses is going to have a hangover effect on business

Enduring Effects

• Past pandemics show effects linger for decades (Jorda, Singh, & Taylor, 2020)– Labor scarcity & increased precautionary savings– That labor scarcity can have a positive effect on

per capita income (Brainerd & Siegler, 2003)– Big difference with current pandemic is the age

group affected

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Enduring Effects

• Other Likely Changes to the Economy/Society– Knowledge spillovers versus decreased commute

time◦ Workers with more education tend to prefer out-of-home

work, while less educated workers prefer working (De Graaff, & Rietveld, 2007)

◦ Working from home results in more productivity (Bloom, Liang, Roberts, & Ying, 2015)

– This study looked at primarily call center style work

Key Takeaways

• Output and earnings in fabricated metal likely to be more volatile than the economy as a whole

• Economic bounce back likely to be tempered by government intervention

• Pandemics tend to increase incomes as labor decreases, but unlikely with present pandemic

• Likely be at least shift involving more remote work

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Appendix – Regressions

GDP and Output Index

Linear regression Number of obs = 31

F( 1, 29) = 10.93

Prob > F = 0.0025

R-squared = 0.5358

Root MSE = 3.9882

------------------------------------------------------------------------------

| Robust

output | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

gdp | 2.712842 .8207401 3.31 0.003 1.03424 4.391444

_cons | -6.098583 2.498368 -2.44 0.021 -11.20832 -.9888464

------------------------------------------------------------------------------

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Average Hourly Earnings

Linear regression Number of obs = 168

F( 1, 166) = 23.56

Prob > F = 0.0000

R-squared = 0.1213

Root MSE = .00451

------------------------------------------------------------------------------

| Robust

fab | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

goods | .6656521 .1371253 4.85 0.000 .3949178 .9363864

_cons | .0005933 .0004517 1.31 0.191 -.0002986 .0014851------------------------------------------------------------------------------

Producer Price Index

Regression of PPI-Manufacturing versus PPI-Fabricated MetalsSource | SS df MS Number of obs = 411

-------------+------------------------------ F( 1, 409) =22306.17Model | 418240.145 1 418240.145 Prob > F = 0.0000

Residual | 7668.73836 409 18.7499715 R-squared = 0.9820-------------+------------------------------ Adj R-squared = 0.9820

Total | 425908.883 410 1038.80215 Root MSE = 4.3301

------------------------------------------------------------------------------ppi_fab | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------ppi_man | .9882401 .0066168 149.35 0.000 .9752329 1.001247_cons | 1.796103 1.003341 1.79 0.074 -.1762464 3.768453

Test of Coefficient Equal to 1F( 1, 409) = 3.16

Prob > F = 0.0763

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References

• Bloom, N., Liang, J., Roberts, J., & Ying, Z. J. (2015). Does working from home work? Evidence from a Chinese experiment. The Quarterly Journal of Economics, 130(1), 165-218.

• Brainerd, E, & Siegler, M. (2003). The Economic Effects of the 1918 Influenza Epidemic. NBER

References

• De Graaff, T., & Rietveld, P. (2007). Substitution between working at home and out-of-home: The role of ICT and commuting costs. Transportation Research Part A: Policy and Practice, 41(2), 142-160.

• Jorda, O., Singh, S., & Taylor, A. (2020). Longer-run economic consequences of pandemics. NBER 2020-09.

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