How Much Damage Did the Great Recession Inflict on the Productive - - PowerPoint PPT Presentation

How Much Damage Did the Great Recession Inflict

• n the Productive Capacity of the US Economy?

David W. Wilcox Federal Reserve Board

Presented at the

Stanford Institute for Economic Policy Research

Stanford University May 12, 2015

This presentation is based on “Aggregate Supply in the United States: Recent Developments and Implications for the Conduct of Monetary Policy” by Reifschneider, Wascher and Wilcox. The opinions expressed are those of the authors and do not necessarily reflect the views of anyone else in the Federal Reserve System.

Lots of interesting questions about the macro effects of the Great Recession:

• 1. How much damage did it cause to the productive

capacity of the economy?

• 2. How much unused productive capacity remains?
• 3. How much damage might be reversible?
• 4. What are the implications for monetary policy?

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Plan for Today

• Address some of these questions based on work with

Dave Reifschneider and Bill Wascher:

• What happened?
• When could it have been known?
• In what aspects of the economy did it occur?
• What might be implications for monetary policy?
• Results here are taken from the published version of

the paper, based on data through 2014:Q3

• My views only, not an official statement of the FRB or

FOMC; views may not be shared by anyone else

3

Main Takeaways

• Impossible to know with precision how much damage

the Great Recession inflicted

• Uncertainty is pervasive; confidence intervals wide; we’re working

with just one model—other models would give different answers

• But the one model we worked with suggests the Great

Recession inflicted considerable damage

• Importantly through loss of capital investment
• MFP may have been affected if R&D was depressed or business

formation was limited by credit constraints

• Evidence on labor market mixed to encouraging
• Whether our results have important implications for

monetary policy depends on the details

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The basic approach: Following Fleischman and Roberts (2011)…

• We posit a model of the economy:

– A description of how key elements of the economy evolve

• A “trend” piece and a “cyclical” piece

– A description of how inflation evolves

• Inflation is a function of the cycle and other factors
• … and estimate it using conventional statistical

techniques borrowed from engineering

– Generate estimates of key variables and measures

• f uncertainty

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A key feature of the model

• A single “business cycle” drives the behavior
• f many different variables

– Possibly with different timing

• Fleischman/Roberts provide a framework for

using multiple indicators to sharpen inference about the cycle

– The most obvious indicators to use are GDP, GDI – But also useful are unemployment and inflation – Haven’t yet tried indicators built from “big data”

• r other new sources of info; mixed frequencies?

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Plan for presenting model results: According to the model…

• What happened?
• When could the extent of the damage

have been known?

• In what aspects of the economy did the

damage occur?

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What happened to the productive capacity of the economy?

11,000 12,000 13,000 14,000 15,000 16,000 17,000 18,000 11,000 12,000 13,000 14,000 15,000 16,000 17,000 18,000 1998 2000 2002 2004 2006 2008 2010 2012 2014 pre-crisis trend actual GDP current estimate billions of chain-weighted 2009 dollars shaded region denotes 95 percent confidence interval

8

What do these results imply about resource slack?

(estimated percent difference between actual and potential GDP)

• 10
• 8
• 6
• 4
• 2

2 4

• 10
• 8
• 6
• 4
• 2

2 4

1998 2000 2002 2004 2006 2008 2010 2012 2014

percent shaded region denotes 95 percent confidence interval

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When could the extent of the damage have been known?

(estimates of potential GDP derived from successive vintages of data)

13,500 14,000 14,500 15,000 15,500 16,000 16,500 17,000 17,500 18,000 13,500 14,000 14,500 15,000 15,500 16,000 16,500 17,000 17,500 18,000 2006 2008 2010 2012 2014 2016 2018 2008 data 2009 data 2010 data 2011 data 2012 data 2013 data 2014 data billions of chain-weighted 2009 dollars

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In what aspects of the economy did the damage occur?

Unemployment

3 4 5 6 7 8 9 10 3 4 5 6 7 8 9 10 1998 2000 2002 2004 2006 2008 2010 2012 2014 actual unemployment rate natural rate percent

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In what aspects of the economy did the damage occur?

Labor force participation

62.5 63.0 63.5 64.0 64.5 65.0 65.5 66.0 66.5 67.0 67.5 68.0 62.5 63.0 63.5 64.0 64.5 65.0 65.5 66.0 66.5 67.0 67.5 68.0

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014

actual trend

percent

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In what aspects of the economy did the damage occur?

Contribution of Capital to the Growth of Potential Output

• 0.2

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8

• 0.2

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014

percentage points

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Implications for monetary policy? It depends…

• Important to underscore that the stakes for

monetary policy are diminished by the following:

– Uncertainty is pervasive

• The structure of the economy is perpetually evolving
• New shocks are always hitting the economy
• No single model is ever “right”

– Accordingly, mid-course corrections are part of standard operating procedure

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Implications for monetary policy? It depends… In an artificial model environment, circumstances that might rationalize an “aggressive” response to cyclical weakness:

• Situation #1:

– Damage from a cyclical weakening hasn’t happened yet; – But would happen if cyclical weakness is left unchecked; – And would be irreversible once it had occurred

• Situation #2:

– Damage from a cyclical weakening has already happened – But is known to be at least partly reversible

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Implications for monetary policy? It depends…

In an artificial model environment, circumstances that might rationalize a “normal” response:

• Situation #3:

– The productive capacity of the economy does not depend on the conduct of monetary policy, perhaps because:

• Damage has already happened and is irreversible;
• Or because supply conditions never depend on demand

In an artificial model environment, circumstances that might rationalize a “cautious” response:

• Situation #4:

– An aggressive policy response would have negative ancillary effects, e.g.,

• Fostering threats to financial stability, or
• Undermining the anchoring of inflation expectations

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