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“Masking and Aggregate Employment Changes: Housing Booms and Manufacturing Decline During the 2000s” “Housing Booms, Labor Market Outcomes and Educational Attainment” Kerwin Charles Erik Hurst Matt Notowidigdo
34

Research Design

Jan 03, 2016

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“Masking and Aggregate Employment Changes: Housing Booms and Manufacturing Decline During the 2000s” “Housing Booms, Labor Market Outcomes and Educational Attainment”. Research Design. A local labor market approach oIdentify a “manufacturing” labor demand shifter - PowerPoint PPT Presentation
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Page 1: Research  Design

“Masking and Aggregate Employment Changes: Housing Booms and Manufacturing Decline During the 2000s”

“Housing Booms, Labor Market Outcomes and Educational Attainment”

Kerwin CharlesErik Hurst

Matt Notowidigdo

Page 2: Research  Design

Research Design

• A local labor market approach

o Identify a “manufacturing” labor demand shifter

o Identify a “housing boom” labor demand shifter

• Some towns experienced larger manufacturing declines than others

o Detroit vs. Orlando

• Some towns experienced larger “housing” demand shocks than others

o Las Vegas vs. Dallas

• Adjust for migration responses

Page 3: Research  Design

Simple Labor Market Model

ln

ln

D D Dkt kt l kt

S S Skt kt l kt

N w

N w

D M M H H O O Xkt kt kt kt ktX

Page 4: Research  Design

Estimating Equation

0 1 2

1

2

N N M N H N Nkt kt kt kt kt

SN Ml

D Sl l

SN Hl

D Sl l

S DN O O Sl lkt ktD S D S

l l l l

N X

Page 5: Research  Design

The Manufacturing “Instrument”: Shift Share (Bartik)

• Identifying Assumption:

o Manufacturing composition in location k in period t is orthogonal to local supply shocks and local changes in demand of other sectors.

• Highly Predictive “First Stage”:

o Shift share measure strongly predicts actual manufacturing employment changes within the MSA.

,~ , 1 ,~ ,( )Mkt ikt i k t i k t

i

s m m

Page 6: Research  Design

Predicted vs. Actual Change in Manufacturing

Page 7: Research  Design

Inferring Housing Demand Changes

,

,

log log

log log

D H D Hk k k k

S H S Hk k k k

H P

H P

, , ,H D H S D H S Hk k k k k k kP H P

• Assuming no local housing supply shocks

• Housing demand changes are potentially correlated with other labor demandchanges and labor supply changes.

• Need an instrument.

Page 8: Research  Design

Estimating Equations

Effects of interest:

o β1 + δ1β2 (Total effect of predicted manufacturing decline)

o β2 (Effect of predicted housing demand change)

Key Assumption: Housing demand change does not affect predicted manufacturing decline in location

(Data strongly support this assumption)

0 1 2

0 1

(1)

( ) (2)

N N M N H N Nkt kt kt kt kt

H M H Okt kt kt kt kt kt kt

N X

f Z X D

Page 9: Research  Design

Estimating Equations

• Motivation for using an instrument for housing demand change:

o Housing demand change measured with error (e.g., housing supply shocks are possible, measurement error in supply elasticity estimate).

o Housing demand change may be result of other labor demand shocks or labor supply shocks (omitted variables bias)

• Instrument using sharp, structural break in quarterly house price series that occurred in some MSAs during mid-2000s.

o Isolate the “Bubble” component of housing demand change (wish test)o Look for “structural breaks” in housing demand series.

0 1 2

0 1

(1)

( ) (2)

N N M N H N Nkt kt kt kt kt

H M H Okt kt kt kt kt kt kt

N X

f Z X D

Page 10: Research  Design

Identifying Assumptions

Trying to capture housing markets during the 2000s.

Evidence that national/local house prices changed in part because of speculative behavior and changes in lending technology

o As opposed to traditional housing demand factors (e.g., income growth, population growth, etc.)

o Speculative behavior may differ spatially.

o Lending technology changes may not differ spatially.

Our structural break measure is uncorrelated with all traditional labor market variables (lagged population growth, lagged employment growth, composition of workforce, etc.).

Our structural break measure is highly correlated with changes in Price-to-Rent ratios and share of out-of-town home owners in MSA.

Page 11: Research  Design

Our New Housing “Instrument”: Structural Breaks

Page 12: Research  Design

Relationship Between Instrument and Housing Demand Change

Page 13: Research  Design

Relationship Between Instrument and Lagged Housing Change

Page 14: Research  Design

Relationship Between Instrument and Supply Elasticity

Page 15: Research  Design

Relationship Between Instrument and Lagged Non-Employment

Page 16: Research  Design

Relationship Between Instrument and Lagged Wages

Page 17: Research  Design

Instrument vs. “Out of Town” Buyers (21 MSAs)

Page 18: Research  Design

Instrument vs. “Out of Town” Buyers (21 MSAs)

Page 19: Research  Design

Effects on Employment: Manufacturing Decline

Manufacturing declines depress employment

o A one standard deviation manufacturing decline reduced employment by 0.7 percentage points between 2000 and 2007.

o A one standard deviation manufacturing decline between 2000 and 2007 reduced employment by 1.1 percentage points between 2000 and 2011 (suggesting persistence in manufacturing declines).

Manufacturing declines also reduced wage growth 2000-2007 (but not between 2007 and 2011).

Manufacturing declines caused an in migration of workers (but employment propensities of the migrants were similar to natives).

Manufacturing declines hit older workers harder than younger workers (and also resulted in higher disability take ups).

Page 20: Research  Design

Effects on Employment: Housing Boom

Housing boom lifted employment

o A one standard deviation housing demand change increased employment by about 1 percentage points between

2000 and 2007.

o A one standard deviation housing boom between 2000 and 2007 had essentially no effect on employment between 2000 and 2011 (the booms were followed by busts – different interpretation of Mian and Sufi results.)

Housing booms increased wage growth between 2000-2007 and 2000-2011 (wags declines during bust didn’t offset the boom).

Housing boom caused an in migration of workers (but employment propensities of the migrants were similar to natives).

For men, employment response concentrated in construction (90%); For women concentrated in FIRE (about 50%). Housing boom hit younger workers more than older workers.

Page 21: Research  Design

Within Individual Masking: Re-Employment Rate

Page 22: Research  Design

A Simple Counterfactual

Page 23: Research  Design

Estimated Effect of Manufacturing Decline on Non-Employment

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011-0.020

-0.010

0.000

0.010

0.020

0.030

0.040

0.050

0.060

0.070

0.080

Page 24: Research  Design

Estimated Effect of Manufacturing Decline on Non-Employment

~42% Explained

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011-0.020

-0.010

0.000

0.010

0.020

0.030

0.040

0.050

0.060

0.070

0.080

Page 25: Research  Design

Estimated Effect of Housing Cycle on Non-Employment

Housing Cycle (Construction and Other)

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011-0.020

-0.010

0.000

0.010

0.020

0.030

0.040

0.050

0.060

0.070

0.080

Manufacturing Decline

Page 26: Research  Design

The Housing Boom Masked The Manufacturing Decline in 2000s

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011-0.020

-0.010

0.000

0.010

0.020

0.030

0.040

0.050

0.060

0.070

0.080

Manufacturing

Data

Housing + Manufacturing

Page 27: Research  Design

The Housing Boom Masked The Manufacturing Decline in 2000s

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011-0.020

-0.010

0.000

0.010

0.020

0.030

0.040

0.050

0.060

0.070

0.080

Manufacturing

Data

Housing + Manufacturing

34% DuringRecession

Page 28: Research  Design

Housing Boom and Human Capital Attainment

Page 29: Research  Design

Propensity to Have At Least One Year of College (Age: 18-29)

1979 1984 1989 1994 1999 2004 20090.40

0.45

0.50

0.55

0.60

0.65

Page 30: Research  Design

Did Housing Boom Delay College Attendance?

Use same local labor market design to answer this question.

The answer is YES – in both survey and administrative data

Places that had large housing booms had a large reduction in the propensity to attend at least one year of college.

o Nearly all the action was on two year colleges (community colleges, technical schools, trade schools, etc.).

o Found effects for both men and women.

o Effect only present among “lost generation”; those who were young in the early 2000s in boom markets.

For this “lost generation”, the effect was persistent through 2013.

Estimates can explain about 40% of the time series change.

Page 31: Research  Design

Summary: Our Interpretation

Page 32: Research  Design

Interpretation

Housing boom “masked” some of the labor market effects of declining manufacturing during the early 2000s.

o Cross-MSA masking (Detroit vs. Las Vegas)

o Cross individual masking (Old hurt by manufacturing decline while young lifted by housing boom)

o Within individual masking (Displaced manufacturing workers are more likely to be reemployed in a MSA that experienced a housing boom).

Is the 2007 labor market the right benchmark to assess cyclical fluctuations?

o Our results suggest no

o Large temporary housing boom lifted labor markets during early 2000s and then brought them back to trend (particularly for low skilled).

Page 33: Research  Design

Interpretation

We are predicting a period of a “medium run” decline in employment to population decline (relative to pre-recession period)

o Some displaced middle age and older workers in manufacturing decline MSAs have taken up disability (Sloane, 2014).

o Younger workers will slowly adjust to new labor market conditions (process was delayed because of housing boom).

Is this transition from manufacturing (routine) jobs to non-routine services different from the transition from agriculture to manufacturing?

o We think so. We are working on estimating the transition rate across sectors for different types of workers.

Page 34: Research  Design

Policy Thoughts

Temporary policy stimulus (either monetary or fiscal) will:

o Only have temporary effects on labor market outcomes

o Potentially slow down the human capital accumulation process

For example, another temporary housing boom could temporarily improve labor markets and again deter schooling choices.

How do we train workers displaced by manufacturing (routing jobs) to move to non-routine services?.

O Are those workers willing/able to work at service job wages?

O Will those policies only work for younger workers – or can they lift the employment propensities of older workers.

o Not likely something influenced by Fed policy.