effect of unconventional fiscal policy on consumption
TRANSCRIPT
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E�ect of Unconventional Fiscal Policy
on Consumption Expenditure
Francesco D'Acunto
University of Maryland
Daniel Hoang
Karlsruhe Institute of Technology
Michael Weber
University of Chicago and NBER
May 31, 2018
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Motivation
�There are forces in the global economy conspiring to hold in�ation down.�
Mario Draghi, February 4 2016
�Fiscal Constraints Await the Next President.�
Wall Street Journal, September 25 2016
Annual in�ation rate Euro area in May 2016: -0.1%
In�ated Central Bank balance sheets and large sovereign debt burdens
Can unconventional �scal policy stimulate in�ation & demand?
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Research Question
Higher in�ation expectations → higher consumption?
Monetary policy constrained when zero lower bound (ZLB) binds
Higher in�ation expectations lower real interest rates with binding ZLB
Fiscal multipliers increase with higher in�ation when ZLB binds
But: precautionary savings channel, preference assumptions, in�ation
tax on liquid asset, income e�ects, etc.
In�ation expectations ⇔ consumption (open) empirical question
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This Paper
In�ation expectations ⇔ willingness to purchase durables
Identi�cation: Di�erence-in-Di�erences
Novel German household data between Jan 2000 to Dec 2013
Unexpected rise in VAT as shock to in�ation expectations
Match German & foreign households in DiD design
Main �nding
Households expecting higher in�ation more likely to purchase durables
E�ect stronger for more educated, high-income, urban households
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Overview of Results: Time-Series Evidence
2005m11
2005m12
2006m1
2006m2
2006m3
2006m4
2006m52006m6
2006m7
2006m8
2006m9 2006m10
2006m11
2006m12
1.6
1.8
22.
22.
4G
ood
time
to b
uy D
urab
les
0 .1 .2 .3 .4 .5Fraction inflation increases
HH with positive in�ation expectations 9% more likely to purchase durables in XS
19% after announcement and before taking e�ect of VAT (11/05 � 12/06): blue dots
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Data
Data Sources
European harmonized survey on consumption climate
2,000 representative German households every months
Questions about aggregate and personal economic expectations
Sample period: January 2000 to December 2013
Rich demographics (age, income, marital status, city size, kids, job)
Macro aggregates (unemployment, uncertainty, Dax, interest rates)
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Data
Survey Questions I
Question 8
Given the current economic situation, do you think it's a good time to buy
larger items such as furniture, electronic items, etc.?
Answer choices: �it's neither good nor bad time,� �it's bad time,� or �it's a good time.�
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Data
Survey Questions II
Question 3
How will consumer prices evolve during the next twelve months compared
to the previous twelve months?
Answer choices: �prices will increase more,� �prices will increase by the same,� �prices
will increase less,� �prices will stay the same,� or �prices will decrease.�
Create a dummy that equals 1 when households answer �prices will increase more.�
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Data
In�ation Expectations over time
0
0.1
0.2
0.3
0.4
0.5
12/0
012
/01
12/0
212
/03
12/0
412
/05
12/0
612
/07
12/0
812
/09
12/1
012
/11
12/1
212
/13
FractionInflationIncreases
In�ation expectation start building up beginning of 2006
Spike in December of 2006
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Data
Durable In�ation and lagged In�ation Expectations
−2
−1
0
1
2
3
4
5
StandardizedInflation
12/0
112
/02
12/0
312
/04
12/0
512
/06
12/0
712
/08
12/0
912
/10
12/1
112
/12
12/1
3
Standardized Lagged Inflation ExpectationsStandardized Durable Inflation
Increase in CPI in�ation in 2007 driven by durable goods in�ation subject to VAT increase
Lagged in�ation expectations and standardized durable in�ation highly correlated
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Data
Readiness to Spend and Real Durable Consumption
−0.1 −0.05 0 0.05 0.1 0.15
−0.1
−0.05
0
0.05
0.1
0.15
Cyclical Purchasing Propensity
CyclicalDurable
Consumption
06Q4
07Q1
y = 0.4152xR2 = 21.46%
Positive correlation between purchasing propensity and actual purchases
Most positive observation in last quarter before VAT increase
Large negative observation in quarter of increase
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Econometric Model
Baseline Speci�cation: Multinomial Logit
Assume survey answer is random variable y
De�ne the response probabilities as P(y = t|X )
Assume the distribution of the response probabilities is
P(y = t|X ) =eXβt
1+∑
z=1,2 eXβz
,
Estimate βt via maximum likelihood
Marginal e�ect: derivative of P(y = t|x) with respect to x
Empirically: de�ne �it's neither good nor bad time� as baseline
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Empirical Results
Baseline Speci�cation
Marginal E�ects:∂P(y = t|x)
∂x= P(y = t|x)
βtx − ∑z=0,1,2
P(y = z|x)βzx
Good time to buy
In�ation Increase 6.24*** 7.49***
(1.62) (1.52)
Past In�ation -3.42***
(0.28)
N. obs 326,011 321,496
Households which expect in�ation to increase
7% more likely to answer �good time to purchase durables�
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Empirical Results
Demographics, Expectations, and Macro Aggregates
HH characteristics shape purchasing propensities (age, income, ...)
Characteristics might be systematically related to in�ation expectations
Economic outlook can a�ect cross-sectional relationship
Optimistic households might expect high growth and low in�ation
Household might be bullish or bearish about the economy
w/ Philips curve in mind: answer high growth and high in�ation
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Empirical Results
Control for Demographics, Outlook, and Macro�aggregates
Marginal E�ects:∂P(y = t|x)
∂x= P(y = t|x)
βtx − ∑z=0,1,2
P(y = z|x)βzx
Good time Good time Good time
In�ation increase 7.55*** 8.88*** 8.75***(1.56) (1.60) (1.16)
Past In�ation −3.00*** -2.00*** −1.14***(0.30) (0.35) (0.23)
Demographics X X XIndividual expectations X XMacro Aggregates XNobs 244,497 219,799 219,799
8% more likely to answer �good time to purchase�
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Empirical Results
Control for Demographics, Outlook, and Macro�aggregates
Marginal E�ects:∂P(y = t|x)
∂x= P(y = t|x)
βtx − ∑z=0,1,2
P(y = z|x)βzx
Good time Good time Good time
In�ation increase 7.55*** 8.88*** 8.75***(1.56) (1.60) (1.16)
Past In�ation −3.00*** -2.00*** −1.14***(0.30) (0.35) (0.23)
Demographics X X XIndividual expectations X XMacro Aggregates XPseudo R2 0.0292 0.0654 0.0762Nobs 244,497 219,799 219,799
9% more likely to answer �good time to purchase�
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Empirical Results
Control for Demographics, Outlook, and Macro�aggregates
Marginal E�ects:∂P(y = t|x)
∂x= P(y = t|x)
βtx − ∑z=0,1,2
P(y = z|x)βzx
Good time Good time Good time
In�ation increase 7.55*** 8.88*** 8.75***(1.56) (1.60) (1.16)
Past In�ation −3.00*** -2.00*** −1.14***(0.30) (0.35) (0.23)
Demographics X X XIndividual expectations X XMacro Aggregates XNobs 244,497 219,799 219,799
9% more likely to answer �good time to purchase�
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Empirical Results
Household Heterogeneity
E�ect of in�ation expectations on willingness to spend higher for
More educated households by Education
High income households by Income
Urban households by City Size
Unconstrained households by Financial Constraints
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Empirical Results
Exogenous Shock to In�ation Expectations
Still cannot rule out movements along the supply curve
Ideal experiment: shock to in�ation expectations that does not a�ect
households' willingness to purchase durables through channels
di�erent from expectations of rising prices
Follow narrative approach of Romer & Romer (2010), Ramey (2011)
⇒ Unexpected increase in value-added tax (VAT)
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Empirical Results
VAT Experiment of 2007 I
Pre-election 2005: promise not to increase VAT
Nov 2005: new government announces increase in VAT by 3%
Jan 2007: entry into force of VAT increase
VAT increase legislated to consolidate budget
Not related to prospective economic conditions
Exogenous tax change acc to Romer and Romer nomenclature
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Empirical Results
VAT Experiment of 2007 II
In�ation expectations build up during 2006
Germany part of Euro zone and no independent monetary policy
Nominal rate did not increase to o�set in�ation expectations
Experiment resembles unconventional �scal policy described in
Correira, Fahri, Nicolini, Teles (2013)
Feldstein (2002) proposition for Japan: Pre-announced VAT increases
Stimulate in�ation expectations & private spending
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Empirical Results
VAT as Shock to In�ation Expectations
12/0
012
/01
12/0
212
/03
12/0
412
/05
12/0
612
/07
12/0
812
/09
12/1
012
/11
12/1
212
/13
Fra
ctio
nIn.ati
on
Incr
ease
s
0
0.1
0.2
0.3
0.4
0.5
Announcement Increase
In�ation expectation start building up beginning of 2006
Spike in December of 2006
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Empirical Results
Di�erence-in-Di�erences Matching Estimator
All Germans treated by VAT shocks
Micro data for France, UK, Sweden from EU harmonized survey
Match German & foreign households with nearest-neighbor algorithm
Matching categories: gender, age, education, income, social status
Estimate Average Treatment E�ect of VAT shock:
(DurGerman,post − DurGerman,pre)− (Dur foreign,post − Dur foreign,pre)
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Empirical Results
Parallel-Trends Identifying Assumption I
Control group behaves similarly to Germans before VAT shock
Behavior of control group after shock how Germans behaved absent of it
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Empirical Results
Parallel-Trends Identifying Assumption II
03/0
406
/04
09/0
412
/04
03/0
506
/05
09/0
512
/05
03/0
606
/06
09/0
6
Fra
ctio
nIn.ati
on
Incr
ease
s
0
0.1
0.2
0.3
0.4
0.5
0.6
AnnouncementGermanyEuropean Countries
Parallel trends in in�ation expectations before the announcement of the VAT increase
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Empirical Results
Parallel-Trends Identifying Assumption III
03/0
406
/04
09/0
412
/04
03/0
506
/05
09/0
512
/05
03/0
606
/06
09/0
6
Good
Tim
eto
Buy
Dura
ble
s
1
1.5
2
2.5
3
AnnouncementGermanyEuropean Countries
Parallel trends in durable propensity before the announcement of the VAT increase
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Empirical Results
Further Identifying Assumptions
Balanced households' characteristics after matching (√)
Treated and control households distributed across full distribution (√)
Positive e�ect of in�ation expectations on consumption expenditure at
micro level for all countries (√)
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Empirical Results
Further Identifying Assumptions
Balanced households' characteristics after matching (√)
Balance
Treated and control households distributed across full distribution (√)
Positive e�ect of in�ation expectations on consumption expenditure at
micro level for all countries (√)
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Empirical Results
Further Identifying Assumptions
Balanced households' characteristics after matching (√)
Balance
Treated and control households distributed across full distribution (√)
Support
Positive e�ect of in�ation expectations on consumption expenditure at
micro level for all countries (√)
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Empirical Results
Further Identifying Assumptions
Balanced households' characteristics after matching (√)
Balance
Treated and control households distributed across full distribution (√)
Support
Positive e�ect of in�ation expectations on consumption expenditure at
micro level for all countries (√)
Foreign Baseline
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Empirical Results
Average Treatment E�ect of VAT shock
(DurGerman,post − DurGerman,pre)− (Dur foreign,post − Dur foreign,pre)
09/0
512
/05
03/0
606
/06
09/0
612
/06
03/0
706
/07
09/0
7
Avera
ge
Tre
atm
ent
E,ect
-0.1
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
Average Treatment Effect Over TimeTwo-Standard Error Bounds
German and foreign households behave similarly before shock
Immediate increase of purchasing behavior of Germans after shock
E�ect builds up during 2006
Reversion to normal after actual VAT increase
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Empirical Results
Matched Sample: Robustness
France, UK, Sweden all part of Europe
Larger set of households guarantees better balancing
But UK and Sweden not part of European Monetary Union
Replicate results for French households only
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Empirical Results
Parallel-Trends Identifying Assumption: France I
03/0
4
06/0
4
09/0
4
12/0
4
03/0
5
06/0
5
09/0
5
12/0
5
03/0
6
06/0
6
09/0
6
Fra
cti
on
In.ati
on
Incre
ase
s
0
0.1
0.2
0.3
0.4
0.5
0.6
AnnouncementGermanyFrance
Parallel trends in in�ation expectations before the announcement of the VAT increase
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Empirical Results
Parallel-Trends Identifying Assumption: France II
03/0
4
06/0
4
09/0
4
12/0
4
03/0
5
06/0
5
09/0
5
12/0
5
03/0
6
06/0
6
09/0
6
Good
Tim
eto
Buy
Dura
ble
s
1
1.5
2
2.5
3
AnnouncementGermanyFrance
Parallel trends in durable propensity before the announcement of the VAT increase
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Empirical Results
General Equilibrium E�ects
VAT change could a�ect purchasing decision through other channels
Consumer con�dence
Crowding out
Redistribution channel
Financial constraints
Home-equity extration
Political uncertainty
But: tax increase regressive
Other channels should operate via income perception or expectations
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Empirical Results
Other Household Expectations
03/0
4
06/0
4
09/0
4
12/0
4
03/0
5
06/0
5
09/0
5
12/0
5
03/0
6
06/0
6
09/0
6
House
hold
Expecta
tions
0
0.1
0.2
0.3
0.4
0.5
0.6
Announcement
Inflation ExpectationsIncome PerceptionIncome Expectations
Income perceptions and expectations do not change after the announcement
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Empirical Results
Intratemporal Substitution
Policy makers concerned with stimulating overall consumption
Survey only asks about purchasing intentions of larger items
VAT mainly a�ects durable goods
Households might substitute from non-durables to durables
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Empirical Results
Real Aggregate Consumption Growth
−15%
0%
15%RealDurable
Consum
ptio
nG
rowth
Announcement Increase
−5%
0%
5%
00Q1
01Q1
02Q1
03Q1
04Q1
05Q1
06Q1
07Q1
08Q1
09Q1
10Q1
11Q1
12Q1
13Q1
RealN
on-Durable
Consum
ptio
nG
rowth
Durable ConsumptionNon−durable Consumption
Both real nondurable and durable consumption growth increase
Average savings propensity decreases
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Empirical Results
Taking Stock
Unconventional �scal policy is salient, easy to understand
Reaction across cuts of the data by income, education, age, etc
But: low reaction to �complex� policies: e.g., forward guidance puzzle
Do cognitive abilities limit the e�ectiveness of economic policies?
D'Acunto, Hoang, Paloviita, Weber (2018):
Human Frictions to the Transmission of Economic Policies
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Empirical Results
Mean Absolute Forecast Error by IQ
22.
53
3.5
44.
55
Mea
n Ab
solu
te F
orec
ast E
rror
0 2 4 6 8 10Normalized IQ
Absolute forecast errors twice as large for low IQ men than for high IQ men
Monotonic relationship btw absolute forecast error and IQ
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Empirical Results
ECB Deposit Facility Rate: Beginning of Quarter
12
34
Dep
osit
Faci
lity
Rat
e
2.4
2.6
2.8
33.
2
01jan2001 01jul2002 01jan2004 01jul2005 01jan2007
Until end of 2001: rate falls from 3.75% to 2.25%
Trough of 1% in June 2003
December 2005 rates start to increase; 2.5% end of 2006
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Empirical Results
Propensity to take out Loan: High IQ
12
34
Dep
osit
Faci
lity
Rat
e
2.4
2.6
2.8
33.
2Av
erag
e Pr
open
sity
Loa
n
01jan2001 01jul2002 01jan2004 01jul2005 01jan2007
Early 2001: average propensity to take out loans is about 2.5
2001-2003: rates fall and propensities increase to more than 3
Until mid-2005: rates and propensities �at
2005-2007: rates increase, propensities fall
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Empirical Results
Propensity to take out Loan: Low IQ
12
34
Dep
osit
Faci
lity
Rat
e
2.4
2.6
2.8
33.
2Av
erag
e Pr
open
sity
Loa
n
01jan2001 01jul2002 01jan2004 01jul2005 01jan2007
Early 2001: average propensity to take out loans of around 2.6
2011-2007: propensities �at, hover around 2.8
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Empirical Results
Conclusion
Households expecting higher in�ation want to purchase more durables
Discretionary �scal policy in recessions: series of pre-announced VAT
increases and a simultaneous reduction in income tax rates
Large e�ect across households
Scope for increased economic literacy, policy transparency, & salience
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Appendix
Balancing of Variables: German and Foreign Households
Variable Mean Control Mean Treated t-stat p-value
Age 2.33 2.30 1.01 0.31
Male 0.47 0.47 0.22 0.82
Education 1.77 1.81 -1.15 0.25
Income 2.31 2.28 0.8 0.42
Social Status 2.60 2.61 -0.37 0.71
Obs in common support 5,108 1,431
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Appendix
Balancing of Variables: German and Foreign Households
0 .2 .4 .6 .8Propensity Score
Untreated Treated
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Appendix
Baseline Speci�cation Foreign Households
France Sweden UK
(1) (2) (3)
In�ation Increase 2.65∗∗∗ 3.81∗∗∗ 4.65∗∗∗(0.37) (0.53) (0.61)
Past In�ation −1.63∗∗∗ −3.15∗∗∗ −0.61(0.15) (0.55) (0.19)
Demographics X X X
Individual expectations X X X
Nobs 163,419 176,829 113,774
Standard errors in parentheses
∗p < 0.10, ∗ ∗ p < 0.05, ∗ ∗ ∗p < 0.01
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Appendix
Baseline Speci�cation by Education
Marginal E�ects:∂P(y = t|x)
∂x= P(y = t|x)
βtx − ∑z=0,1,2
P(y = z|x)βzx
Hauptschule Realschule Gymnasium University
Bad time Good time Bad time Good time Bad time Good time Bad time Good time
(1) (2) (3) (4) (5) (6) (7) (8)
In�ation increase 1.08 6.89∗∗∗ 1.17 9.85∗∗∗ −3.42∗∗∗ 9.79∗∗∗ −3.87∗∗∗ 11.28∗∗∗(1.05) (1.52) (0.80) (1.62) (1.18) (2.25) (0.80) (1.88)
Past In�ation 4.14∗∗∗ −1.94∗∗∗ 3.73∗∗∗ −1.88∗∗∗ 3.19∗∗∗ −2.64∗∗∗ 2.52∗∗∗ −2.14∗∗∗(0.34) (0.32) (0.34) (0.38) (0.47) (0.48) (0.45) (0.57)
Demographics X X X X X X X X
Individual expectations X X X X X X X X
Nobs 89,991 88,315 23,282 18,211
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Appendix
Baseline Speci�cation by Income
Marginal E�ects:∂P(y = t|x)
∂x= P(y = t|x)
βtx − ∑z=0,1,2
P(y = z|x)βzx
Income ≤ 1,000 1,000 < Income ≤ 2,500 2,500 < Income
Bad time Good time Bad time Good time Bad time Good time
(1) (2) (3) (4) (5) (6)
In�ation increase −0.99 8.98∗∗∗ −0.55 8.51∗∗∗ −1.09 10.48∗∗∗(1.05) (1.68) (0.78) (1.51) (0.77) (2.03)
Past In�ation 4.23∗∗∗ −1.94∗∗∗ 3.51∗∗∗ −1.92∗∗∗ 2.77∗∗∗ −2.99∗∗∗(0.36) (0.37) (0.32) (0.36) (0.43) (0.45)
Demographics X X X X X X
Individual expectations X X X X X X
Nobs 96,555 112,710 16,477
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Appendix
Baseline Speci�cation by City Size
Marginal E�ects:∂P(y = t|x)
∂x= P(y = t|x)
βtx − ∑z=0,1,2
P(y = z|x)βzx
City ≤ 2T 2T < City ≤ 20T 20T < City ≤ 100T 100T < City
Bad time Good time Bad time Good time Bad time Good time Bad time Good time
(1) (2) (3) (4) (5) (6) (7) (8)
In�ation increase −1.23 5.81∗∗∗ 0.18 8.47∗∗∗ 0.02 8.54∗∗∗ −2.44∗∗∗ 10.13∗∗∗(1.32) (1.99) (0.86) (1.51) (1.02) (2.17) (0.92) (1.33)
Past In�ation 4.14∗∗∗ −1.96∗∗∗ 2.98∗∗∗ −1.87∗∗∗ 4.14∗∗∗ −2.64∗∗∗ 4.15∗∗∗ −1.77∗∗∗(0.52) (0.55) (0.36) (0.34) (0.37) (0.38) (0.40) (0.42)
Demographics X X X X X X X X
Individual expectations X X X X X X X X
Nobs 17,833 74,937 59,674 67,355
Standard errors in parentheses
∗p < 0.10, ∗ ∗ p < 0.05, ∗ ∗ ∗p < 0.01
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Appendix
Baseline Speci�cation by Financial Constraints
Marginal E�ects:∂P(y = t|x)
∂x= P(y = t|x)
βtx − ∑z=0,1,2
P(y = z|x)βzx
Unconstrained Constrained
Bad time Good time Bad time Good time
(1) (2) (3) (4)
In�ation Increase −0.57 10.42∗∗∗ −1.05 7.47∗∗∗(0.66) (1.80) (1.01) (1.46)
Past In�ation 3.45∗∗∗ −2.50∗∗∗ 3.88∗∗∗ −1.59∗∗∗(0.27) (0.38) (0.40) (0.35)
Nobs 98,344 121,455
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