the credit-driven household demand channel · the credit-driven household demand channel atif mian...

$: The Credit-Driven Household Demand Channel · The Credit-Driven Household Demand Channel Atif Mian Princeton University Nobel Symposium On \Money and Banking" May 24, 2018 1/22. 2/22$
The Credit-Driven Household Demand Channel

Atif MianPrinceton University

Nobel Symposium On “Money and Banking”

May 24, 2018

1 / 22

2 / 22

AL

AK

AZ

AR

CA

COCT DE

DC

FLGA

HI

ID

IL

IN

IAKS

KYLA

ME

MD

MAMI

MN

MSMO

MT

NE

NV

NH

NJ

NMNY

NC

ND

OH

OK

OR

PA

RISC

SD

TNTX

UT

VT

VA

WAWV

WIWY

0

2

4

6

8

10∆

Une

mpl

oym

ent,

2007

−10

0 10 20 30 40 50 60∆ HH debt to GDP, 2002−07

Source: Mian and Sufi (IMF, 2010).

United States

AUSAUT

BELCAN

CHECZE

DEU

DNK

ESP

FINFRAGBR

GRC

HKG

HUN

IDN

IRL

ITA

JPNKOR

MEXNLDNOR

POL

PRT

SGP

SWE

THA

TUR

USA

−5

0

5

10

15

∆ U

nem

ploy

men

t, 20

07−

10

−20 0 20 40 60∆ HH debt to GDP, 2002−07

Source: Mian, Sufi, and Verner (QJE, 2017).

World

The credit-driven household demand channel

↑ credit supply ⇒ ↑ household aggregate demand ⇒ ↓ future GDP growth.

3 / 22

Outline

• Evidence from business cycles internationally, as well as regional business cycleswithin the U.S., over the last half-century

• International evidence - including a new out of sample test of previous findings

• A natural experiment using the U.S. banking deregulation wave from the 1980s

• U.S. regional evidence from the Great Recession

• Implications of the credit-driven household demand channel for

• Macroeconomic theory and long run fundamentals

• Public policy (monetary policy, macro-prudential policy, and crisis response)

4 / 22

Empirical Challenges

• How to isolate credit supply expansion?

• ↑ in quantity and ↓ in spreads, deregulation/policy experiments, differentialpass-through of global shocks (e.g. oil, securitization, savings glut)

• How to identify change in household aggregate demand?

• Focus on nontradable/tradable sectors, relative size and prices

• Asymmetry between household and non-financial firm credit

• Use of micro data and regional variation

5 / 22

International Evidence

−.8

−.6

−.4

−.2

0

.2

.4

.6

0 2 4 6 8 10Years after Shock

Source: Mian, Sufi, and Verner (QJE, 2017)

GDP Response to HH Debt Shock

−.8

−.6

−.4

−.2

0

.2

.4

.6

0 2 4 6 8 10Years after Shock

Source: Mian, Sufi, and Verner (QJE, 2017)

GDP Response to NF Debt Shock

6 / 22


MSV2017 30 Countries

(1) (2) (3) (4) (5) (6)

∆3CitYit

∆3NXitYit

∆3sMCit ∆3 ln

(LNTitLTit

)∆3 ln

(PNTit

PTit

)∆3yi ,t+4

∆3dHHit 0.058∗ -0.15∗∗ 0.055∗

0.36∗∗ 0.38∗∗ -0.34∗∗

(0.024) (0.051) (0.025)

(0.056) (0.097) (0.089)

∆3dFit 0.038∗∗ -0.00036 -0.012

0.0085 -0.065 -0.032

(0.012) (0.031) (0.021)

(0.064) (0.059) (0.038)

Country fixed effects X X X

X X X

R2 0.087 0.062 0.012

0.17 0.067 0.11

Observations 816 832 858

639 670 840

Standard errors in parentheses

30 countries, 1962-2012. Source: Mian, Sufi, and Verner (QJE, 2017).+ p < 0.1, ∗ p < 0.05, ∗∗ p < 0.01

7 / 22



(1) (2) (3) (4) (5) (6)

∆3CitYit

∆3NXitYit

∆3sMCit ∆3 ln

(LNTitLTit

)∆3 ln

(PNTit

PTit

)∆3yi ,t+4

∆3dHHit 0.058∗ -0.15∗∗ 0.055∗ 0.36∗∗ 0.38∗∗

-0.34∗∗

(0.024) (0.051) (0.025) (0.056) (0.097)

(0.089)

∆3dFit 0.038∗∗ -0.00036 -0.012 0.0085 -0.065

-0.032

(0.012) (0.031) (0.021) (0.064) (0.059)

(0.038)

Country fixed effects X X X X X

X

R2 0.087 0.062 0.012 0.17 0.067

0.11

Observations 816 832 858 639 670

840



7 / 22



(1) (2) (3) (4) (5) (6)

∆3CitYit

∆3NXitYit

∆3sMCit ∆3 ln

(LNTitLTit

)∆3 ln

(PNTit

PTit

)∆3yi ,t+4

∆3dHHit 0.058∗ -0.15∗∗ 0.055∗ 0.36∗∗ 0.38∗∗ -0.34∗∗

(0.024) (0.051) (0.025) (0.056) (0.097) (0.089)

∆3dFit 0.038∗∗ -0.00036 -0.012 0.0085 -0.065 -0.032

(0.012) (0.031) (0.021) (0.064) (0.059) (0.038)

Country fixed effects X X X X X XR2 0.087 0.062 0.012 0.17 0.067 0.11Observations 816 832 858 639 670 840



7 / 22


IMF2018Additional

MSV2017 30 Countries 105 Countries

(1) (2) (3) (4) (5) (6) (7)

∆3CitYit

∆3NXitYit

∆3sMCit ∆3 ln

(LNTitLTit

)∆3 ln

(PNTit

PTit

)∆3yi ,t+4 ∆3yi ,t+4

∆3dHHit 0.058∗ -0.15∗∗ 0.055∗ 0.36∗∗ 0.38∗∗ -0.34∗∗ -0.37∗

(0.024) (0.051) (0.025) (0.056) (0.097) (0.089) (0.17)

∆3dFit 0.038∗∗ -0.00036 -0.012 0.0085 -0.065 -0.032 -0.019∗∗

(0.012) (0.031) (0.021) (0.064) (0.059) (0.038) (0.0072)

Country fixed effects X X X X X X XR2 0.087 0.062 0.012 0.17 0.067 0.11 0.056Observations 816 832 858 639 670 840 964



8 / 22

Rise in household leverage predicts GDP slowdown

−20

0

20

40

GD

P g

row

th, t

to t+

3

−10 0 10 20 30Household Debt to GDP Expansion, t−4 to t−1

MSV2017 30 CountriesIMF2018 Additional 105 Countries

Source: Mian, Sufi, and Verner (QJE, 2017).

9 / 22

Deregulation experiment in the 1980s in U.S.

100

150

200

250

1980 1982 1984 1986 1988 1990 1992

Early DeregulationLate Deregulation

Source: Mian, Sufi, and Verner (WP, 2018).

Total Bank Credit

50

60

70

80

90

100

1980 1982 1984 1986 1988 1990 1992Source: Mian, Sufi, and Verner (WP, 2018).

Unemployment Rate

10 / 22

Local demand and NT / T sector expands

AK

AL

AR

AZ

CA

CO

CT

DC

FL

GA

HI

IAID

IL

IN

KS

KY

LA

MA

MD

ME

MI

MN

MOMS

MT

NC

ND

NE

NH

NJ

NM

NV

NYOH

OK

ORPA

RI

SC

TN

TX

UT

VA

VT

WA

WI

WV

WY−0.10

0.00

0.10

0.20

0.30

0.40

−2 −1 0 1 2Deregulation exposure


Non−Tradable Employment Growth, 82−89

AK

ALAR

AZ

CA

CO

CTDC

FL GA

HI

IA

ID

IL

INKS

KY

LA

MA

MD

ME

MIMN

MO

MS

MT NCND

NENH

NJ

NM

NV

NY

OH

OK

OR

PA

RI

SC

TN

TX

UT

VA

VT

WA

WI

WVWY

−0.30

−0.20

−0.10

0.00

0.10

0.20



Tradable Employment Growth, 82−89

11 / 22

Local demand and NT / T sector expands

AK

AL

AR

AZ

CA

CO

CT

DC

FL

GA

HI

IAID

IL

IN

KS

KY

LA

MA

MD

ME

MI

MN

MOMS

MT

NC

ND

NE

NH

NJ

NM

NV

NYOH

OK

ORPA

RI

SC

TN

TX

UT

VA

VT

WA

WI

WV

WY−0.10

0.00

0.10

0.20

0.30

0.40



Non−Tradable Employment Growth, 82−89AK

ALAR

AZ

CA

CO

CTDC

FL GA

HI

IA

ID

IL

INKS

KY

LA

MA

MD

ME

MIMN

MO

MS

MT NCND

NENH

NJ

NM

NV

NY

OH

OK

OR

PA

RI

SC

TN

TX

UT

VA

VT

WA

WI

WVWY

−0.30

−0.20

−0.10

0.00

0.10

0.20



Tradable Employment Growth, 82−89

11 / 22

Local demand and NT / T price rises

CA

CO

CT

FL

GAHI

ILIN

KS KY

MAMD

ME

MI

MNMO

NH

NJ

NY

OH

OR

PA

TX

WAWI

0.15

0.20

0.25

0.30

0.35


(Alaska excluded)Source: Mian, Sufi, and Verner (WP, 2018).

Non−tradable CPI Inflation, 84−89

CA

CO

CT

FLGA

HI

ILIN

KSKY

MA

MD

MEMI

MN

MONHNJ

NY

OHOR

PATX

WA

WI

0.05

0.10

0.15

0.20

0.25


(Alaska excluded)Source: Mian, Sufi, and Verner (WP, 2018).

Tradable CPI Inflation, 84−89

12 / 22

Rise in household leverage predicts depth of 1990/91 recession

AK

ALAR

AZ

CA

CO

CTDC

FL

GAHI

IA

ID

ILIN

KSKYLA

MA

MDME

MI

MNMO

MSMT

NC

NDNE

NHNJ

NM

NV

NY

OH

OK

OR

PA

RI

SC

TN

TX

UT

VA

VT

WAWI

WV

WY

−2.00

0.00

2.00

4.00

6.00

∆ U

nem

ploy

men

t, 19

89−

92

−2 −1 0 1 2 3∆ HH Leverage, 1982−89


13 / 22

U.S. experience during the 2000’s

• A large expansion in credit supply, Mian and Sufi (2009), (also see [1])

• Credit expansion led to an increase in local demand and the non-tradable sectorexpanded, Di Maggio and Kermani (2017)

• When the music stops, Fisher’s “debt deflation” dynamics take hold (see [2])

• large fall in demand, Mian et al. (2013)

• fall in employment due to demand shortgage, Mian and Sufi (2014)

• foreclosure fire-sale externalities amplify the negative cycle, Mian et al. (2015)

14 / 22

The fall in demand

−.4

−.2

0

.2

∆ E

xpen

ditu

re, 0

6−09

−.3 −.25 −.2 −.15 −.1 −.05 0 .05∆ HH net worth, 06−09

Source: Mian, Rao, and Sufi (QJE, 2013).

15 / 22

Fall in employment in response to demand

−.15

−.1

−.05

0

.05

.1

∆ T

rada

ble

Em

ploy

men

t, 07

−09

−.15

−.1

−.05

0

.05

.1

∆ N

on−

Tra

dabl

e E

mpl

oym

ent,

07−

09

−.3 −.25 −.2 −.15 −.1 −.05 0 .05∆ HH net worth, 06−09

Source: Mian and Sufi (ECMA, 2014).

16 / 22

Fall in employment in response to demand

−.15

−.1

−.05

0

.05

.1

∆ T

rada

ble

Em

ploy

men

t, 07

−09

−.15

−.1

−.05

0

.05

.1

∆ N

on−

Tra

dabl

e E

mpl

oym

ent,

07−

09

−.3 −.25 −.2 −.15 −.1 −.05 0 .05∆ HH net worth, 06−09

Source: Mian and Sufi (ECMA, 2014).

17 / 22

Theoretical implications of credit-driven household demand channel

18 / 22

• Heterogeneity across borrowers and creditors matters as it interacts withfrictions like ZLB & wage rigidity. e.g. Eggertsson and Krugman (2012), Farhi and

Werning (2015), Guerrieri and Lorenzoni (2017), Schmitt-Grohe and Uribe (2016) ([3])

• Ex-ante “over-borrowing” due to AD and pecuniary externalities (see [4])

0

.005

.01

.015

.02

.025

.03

<= 30% 30%−50% 50%−70% 70%−90% > 90%

Source: Mian, Rao, and Sufi (QJE, 2013).

MPC out of Housing Wealth by HH Leverage, ’06−09

0

.05

.1

.15

.2

.25

< 700 700 − 799 800 − 899 900 − 999

Source: Mian and Sufi (AER, 2011).

MPB out of Housing Wealth by Credit Score, ’02−06

19 / 22

• Systematic forecasting errors suggests departure from rational expectationswith common beliefs (See [5])

• Important to model heterogeneous beliefs and behavioral biases, e.g.Geanakoplos (2010), Gennaioli et al. (2012), Lopez-Salido et al. (2017) ([6])

THA2002

HUN1993

NOR1994

THA2001FIN1996

HUN1994

FIN1997

CHE2009

SGP2007

NOR1996

DEU2009

SWE1996

NOR1995

HKG2007

NOR1993

DEU2008

SGP2008

FIN1998

FIN1995SWE1997

SWE1992

SWE1993

HKG2008NOR1997

NOR1992

THA2003

HKG2006

FIN1999SWE1995

DEU2007

SWE1994NOR1998

HUN1997

JPN2005HUN1998

HKG2009

CHE2008CZE1999

HUN1996JPN2003JPN2004

JPN2007

HKG2005

JPN2009SWE1998GBR1997

JPN2006

MEX1999

MEX2000

GBR1996

FRA1997

DEU1991

JPN2008

HUN1995

HUN1999

DEU2006

MEX2001

ITA1996

KOR2000

KOR2001ITA1997

CAN1996

DEU1992

DEU2005

SGP2009

GBR1995

MEX2002

CAN2002BEL2003NOR2001DEU1993

BEL2002

FRA1998

TUR2004

DEU1990

JPN2002ITA1998DEU2004

HKG1995

FIN1994

MEX1998TUR1997

THA2009

TUR1991FIN2000

DEU2003

CAN2001

ITA1992

CZE2000

TUR1990FRA1996GBR1998

TUR2003

ESP1993

NOR2002

CZE2001ITA1995HUN2000

BEL1996

TUR2002

FRA1999

TUR1992

THA2000CHE2007TUR1993

IDN2009

ESP1995

ESP1996

THA2008

JPN1999

GBR1994

CHE2003MEX2003

TUR2000

JPN1994

AUT2009

PRT1991

JPN1998FRA2001

BEL2004

ITA1991FRA2000

SGP2006

CAN1997

KOR2006

ESP1997

IDN2008

ESP1994BEL2001

AUS1993

TUR1995

TUR1999

KOR1999

PRT1992

ITA1990

NOR1999

TUR1996

BEL1997

USA1995

JPN1993ITA1994

NOR1991

CAN2003

CZE2002

FRA1995JPN2001ITA1999

AUS1991

TUR2001

USA1994

CAN1995SWE1999AUT1999HUN2001

MEX2004

FRA2002

JPN2000

AUT2004

FIN2001GBR1999USA1999

TUR1998

BEL2005BEL1995ITA1993

USA1998

MEX2005FRA2003

USA2000

HKG2004

JPN1995

FIN1993

ESP1992

CAN1998AUS1992

PRT1993AUS1990

SGP2001

MEX2006

AUT2003USA1993

IDN2007

POL2006

JPN1997

TUR1994

SWE1991NOR2000

MEX2009

THA2007

BEL1998

HKG1996

HKG2003

AUT2001THA2004

POL2002

POL2000MEX2007

POL2001

KOR1996

USA1996

PRT1990

AUT2000SWE2000

GRC1998

TUR2005FRA1993

FRA2004

USA1997

FIN2002CAN2000NOR2009BEL1994USA1992

BEL2000AUT2008

AUS1994

FIN2003

FRA1994

AUT2005ESP1998

USA1991

JPN1996

USA1990DEU1994

NOR2007

GRC1999

BEL1992

GBR1993

FRA1992

FIN1992

DEU2002

SGP2000

MEX2008

BEL1993

CZE2003

AUT2002

ITA2000

SWE2001USA2001BEL1999

KOR1997

GRC2000

SGP2005

POL1999

FRA1991

CZE2004

BEL1991BEL2006

HUN2002

KOR1998

FRA1990

CAN1994

HKG1997ESP1991

HKG2002

CAN1999

FRA2005

POL2005

IDN2006

SGP1999

NLD1994

ITA2003

USA2009

BEL1990ITA2001

TUR2009

IDN2005NLD2009GBR2000

ITA2004

SGP2003

KOR1994

CZE2006

KOR1995

JPN1992

HKG1994

ITA2002

CZE2005

POL2007

FIN1991

THA2006

DNK2002GBR2001

TUR2006

CAN2004

BEL2007

AUS2009

AUT2007

POL2004

AUT2006NOR2008

GRC2001

SWE2002

ITA2005

AUS1995SWE2003

FRA2006

KOR2007DEU2001

ITA2009

NOR2006

NOR2003SGP2002

FIN2009SGP1998

DEU1995

TUR2007

TUR2008GBR1992BEL2009POL2003

DNK2001THA2005BEL2008

SGP1995

PRT1994

FIN2004

CHE2006

KOR2005

USA2002ESP1999

SWE2004

HKG2001

HUN2003

DEU1998

NLD1995

GBR2008

CZE2007

FRA2009

KOR1993

FRA2007ESP1990

ITA2006

SWE2005

DEU1999

SWE1990

DEU1997CAN2005CAN1993THA1999

AUS1996CHE2005

FRA2008

CHE2004

DEU2000CAN2006

KOR2002

DEU1996GBR2009

JPN1991

CAN1992

AUS1998

SWE2008

NLD1996

DNK2000

CAN2007

CAN1991

AUS1997SWE2009

ITA2007

ITA2008

GBR2002

PRT1995

NOR1990

FIN1990

GRC2002

CAN1990

FIN2008

KOR2009

SGP1996

ESP2003

POL2008

HUN2007

SWE2006

AUS1999ESP2002

USA2008

SWE2007

CZE2008

CZE2009

FIN2005

SGP1997GBR1991

DNK2003

ESP2000

PRT2009CAN2008KOR1990

HUN2008

NLD1997

USA2007

USA2003

PRT1997

CAN2009

DNK1999

PRT1996

KOR2008

DNK1998KOR1992

HUN2004

GBR2007

NLD2008

KOR1991

ESP2004

ESP2001

SGP2004

FIN2007

NOR2005

AUS2001

GBR1990

ESP2009

GRC2003

NLD2003

GBR2006

AUS2000

HUN2005

AUS2002

HKG1998

HUN2006

THA1998

PRT1998

GBR2003

FIN2006

DNK2004

PRT2008

USA2006

NLD1998

GRC2004

JPN1990

THA1997

PRT2005

NLD2002

AUS2008

THA1996

HUN2009

PRT2007HKG2000

PRT2004

USA2005

DNK2005AUS2003

PRT2006

GRC2005NOR2004

THA1995

HKG1999

USA2004

POL2009

PRT2003

GBR2004KOR2004

NLD2007

NLD2004

PRT1999

ESP2005

AUS2007

GRC2009

NLD1999

DNK2006

GBR2005

GRC2006NLD2001

NLD2005

DNK2009

NLD2000

ESP2008

KOR2003AUS2004

GRC2007

PRT2002ESP2006PRT2000

NLD2006

GRC2008

AUS2006

DNK2008

DNK2007

ESP2007

PRT2001

AUS2005IRL2009

IRL2008

IRL2006

IRL2007

−30

−20

−10

0

10

20

IMF

WE

O t

to t+

3 G

DP

For

ecas

t Err

or

−10 0 10 20 30 40Household Debt to GDP Expansion, t−4 to t−1

Source: Mian, Sufi, and Verner (QJE, 2017)20 / 22

• Is there a link between secular rise in household credit, Jorda et al. (2016),falling interest rate and rising inequality and savings glut? (see [7])

0

.5

1

1.5

2

Deb

t to

Inco

me

1960 1970 1980 1990 2000 2010Year

bot 99%top 1%

Source: Mian and Sufi (WP, 2018).

21 / 22

Public policy implications of credit-driven household demand channel

• Post-2007 policy should have focused on reducing household debt servicepayments and preventing foreclosures (see [8]).

• Mortgage design matters, more equity-like contracts that promote risk-sharinghave benefits at the macro level

• Monetary policy pass-through depends on the credit-driven household demandchannel, e.g. Di Maggio et al. (2017)

• UK and many other countries have since adopted macro-prudential regulationsthat impose constraints based on loan to value or debt service to income

22 / 22

Notes

1. Adelino et al. (2014), Demyanyk and Van Hemert (2011), Favara and Imbs(2015), Justiniano et al. (2015, 2017), Keys et al. (2010), Levitin and Wachter(2012), Mian and Sufi (2009, 2017)

2. Andersen et al. (2014), Bahadir and Gumus (2016), Bunn and Rostom (2015),Drehmann et al. (2017), Giroud and Mueller (2017), Glick and Lansing (2010),IMF (2012, 2017), Di Maggio and Kermani (2017), Martin and Philippon (2014),Mian and Sufi (2010, 2011, 2014), Mian et al. (2013, 2017a,b), Verner andGyongyosi (2017)

3. Eggertsson and Krugman (2012), Farhi and Werning (2015), Guerrieri andLorenzoni (2017), Huo and Rıos-Rull (2016), Korinek and Simsek (2016),Lorenzoni (2008), Schmitt-Grohe and Uribe (2016)

1 / 10

Notes

4. Agarwal et al. (2017, 2018), Aladangady (2014), Baker (2018), Cloyne et al.(2017), Di Maggio et al. (2017), Ganong and Noel (2017a,b), Jorda et al. (2014),Liu et al. (2018), Mian and Sufi (2018b, Forthcoming)

5. Mian et al. (2017b), Baron and Xiong (2016)

6. Baron and Xiong (2016), Bordalo et al. (2017), Burnside et al. (2017),Geanakoplos (2010), Gennaioli et al. (2012), Kindleberger (1978), Kindelbergerand Aliber (2005), Krishnamurthy and Muir (2016), Lopez-Salido et al. (2017),Mian and Sufi (2018a), Minsky (2008), Nathanson and Zwick (2017)

7. Favilukis et al. (2012), Jorda et al. (2016), Kumhof et al. (2015)

8. Agarwal et al. (2018), Aladangady (2014), Cloyne et al. (2017), Di Maggio et al.(2017), Jorda et al. (2014, 2013), Ganong and Noel (2017b), Mian and Sufi(2015)

2 / 10

References I

Adelino, Manuel, Antoinette Schoar, and Felipe Severino, “Credit supply and house prices:Evidence from mortgage market segmentation,” Available at SSRN 1787252, 2014.

Agarwal, Sumit, Gene Amromin, Itzhak Ben-David, Souphala Chomsisengphet, TomaszPiskorski, and Amit Seru, “Policy Intervention in Debt Renegotiation: Evidence from the HomeAffordable Modification Program,” Journal of Political Economy, 2017, 125 (3).

, Souphala Chomsisengphet, Neale Mahoney, and Johannes Stroebel, “Do Banks Pass ThroughCredit Expansions to Consumers Who Want to Borrow? Evidence from Credit Cards,” QuarterlyJournal of Economics, 2018, 133 (1), 129–90.

Aladangady, Aditya, “Homeowner Balance Sheets and Monetary Policy,” FEDS Working Paper,Federal Reserve Board 2014.

Andersen, Asger L., Charlotte Duus, and Thais L. Jensen, “Household Debt and ConsumptionDuring the Financial Crisis: Evidence from Danish Micro Data,” 2014. Working Paper.

Bahadir, Berrak and Inci Gumus, “Credit decomposition and business cycles in emerging marketeconomies,” Journal of International Economics, 2016, 103, 250–262.

Baker, Scott R, “Debt and the Response to Household Income Shocks: Validation and Application ofLinked Financial Account Data,” Journal of Political Economy, 2018.

3 / 10

References IIBaron, Matthew and Wei Xiong, “Credit expansion and neglected crash risk,” National Bureau ofEconomic Research, 2016.

Bordalo, Pedro, Nicola Gennaioli, and Andrei Shleifer, “Diagnostic Expectations and CreditCycles,” Journal of Finance, 2017.

Bunn, Philip and May Rostom, “Household Debt and Spending in the United Kingdom,” 2015. Bankof England Working Paper.

Burnside, Craig, Martin Eichenbaum, and Sergio Rebelo, “Understanding Booms and Busts inHousing Markets,” Journal of Political Economy, 2017, 124, 1088–1147.

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