Demographics and Monetary Policy Shocks
Demographics and MonetaryPolicy Shocks
K.A. Berg?
C.C. Curtis†
S. Lugauer±
N.C. Mark⊕
?Miami University†University of Richmond± University of Kentucky
⊕ University of Notre Dame and NBER
February 2019
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Demographics and Monetary Policy Shocks BLCM
Introduction (1)What we do
Compare consumptionresponse to monetarypolicy shocks of young,middle-aged, and oldhouseholds.
Why?Consumption is 70% ofGDPDemographic profile ischanging. Aging society
Figure: U.S. Pop 65+ divided byPop 25-64: 1950-2050
1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 20500.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
Will effectiveness ofmonetary policy change?
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Demographics and Monetary Policy Shocks BLCM
Introduction (1)What we do
Compare consumptionresponse to monetarypolicy shocks of young,middle-aged, and oldhouseholds.
Why?Consumption is 70% ofGDPDemographic profile ischanging. Aging society
Figure: U.S. Pop 65+ divided byPop 25-64: 1950-2050
1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 20500.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
Will effectiveness ofmonetary policy change?
2 / 54
Demographics and Monetary Policy Shocks BLCM
Introduction (1)What we do
Compare consumptionresponse to monetarypolicy shocks of young,middle-aged, and oldhouseholds.
Why?Consumption is 70% ofGDPDemographic profile ischanging. Aging society
Figure: U.S. Pop 65+ divided byPop 25-64: 1950-2050
1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 20500.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
Will effectiveness ofmonetary policy change?
2 / 54
Demographics and Monetary Policy Shocks BLCM
Introduction (1)What we do
Compare consumptionresponse to monetarypolicy shocks of young,middle-aged, and oldhouseholds.
Why?Consumption is 70% ofGDPDemographic profile ischanging. Aging society
Figure: U.S. Pop 65+ divided byPop 25-64: 1950-2050
1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 20500.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
Will effectiveness ofmonetary policy change?
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Demographics and Monetary Policy Shocks BLCM
Introduction (2)
What we do and useConsumption from CEXFour identified monetarypolicy shocks (fromother people)Two methods: StructuralVAR and local projection
What we findHighest response fromold households
Data also showsNet wealth increaseswith ageWorking age live onlabor incomeHigh income old moreresponsiveHigh and low incomeworking aged the same
How to explain?Life-cycle model thataccentuates differences inwealth, labor supply, anddiscounting the future.
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Demographics and Monetary Policy Shocks BLCM
Introduction (2)
What we do and useConsumption from CEXFour identified monetarypolicy shocks (fromother people)Two methods: StructuralVAR and local projection
What we findHighest response fromold households
Data also showsNet wealth increaseswith ageWorking age live onlabor incomeHigh income old moreresponsiveHigh and low incomeworking aged the same
How to explain?Life-cycle model thataccentuates differences inwealth, labor supply, anddiscounting the future.
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Demographics and Monetary Policy Shocks BLCM
Introduction (2)
What we do and useConsumption from CEXFour identified monetarypolicy shocks (fromother people)Two methods: StructuralVAR and local projection
What we findHighest response fromold households
Data also showsNet wealth increaseswith ageWorking age live onlabor incomeHigh income old moreresponsiveHigh and low incomeworking aged the same
How to explain?Life-cycle model thataccentuates differences inwealth, labor supply, anddiscounting the future.
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Demographics and Monetary Policy Shocks BLCM
Introduction (2)
What we do and useConsumption from CEXFour identified monetarypolicy shocks (fromother people)Two methods: StructuralVAR and local projection
What we findHighest response fromold households
Data also showsNet wealth increaseswith ageWorking age live onlabor incomeHigh income old moreresponsiveHigh and low incomeworking aged the same
How to explain?Life-cycle model thataccentuates differences inwealth, labor supply, anddiscounting the future.
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Demographics and Monetary Policy Shocks BLCM
Literature
Monetary policy transmission under heterogeneity:Gornemann et al. (2012), McKay et al. (2016), and Luetticke (2016).
Monetary policy and inequality:Coibion et al.(2017), Bunn et al. (2018)
NK models with life-cycle aspects:Fujiwara and Teranishi (2007), Bielecki et al. (2018), Doepke andSchneider (2006)
Wealth effects of monetary policy:Krueger and Perri (2006), Sterk and Tenreyro (2018), Glover et al. (2017),Auclert (2019), Storesletten et al. (2007)
Monetary policy and mortgage (re)financeCloyne et al. (2018), Di Maggio et al. (2014), Wong (2018), Eichenbaum etal. (2018)
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Demographics and Monetary Policy Shocks BLCM
Consumption DataConsumption data from CEX
1984Q1 to 2007Q419 real expenditure categories CEX Categories
Young (25-34), Middle (35-64), Old (65+)Urban and ruralPer capita
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Demographics and Monetary Policy Shocks BLCM
The Monetary Policy Shocks
1 HFI-TRM: (Barakchian and Crowe (2013)). Factor structure for fed fundsfutures Term-structure for current month and at 1 through 5 months ahead.Shock is change in first factor on the day announcement following FOMCmeeting.
2 HFI-3MO: (Gertler and Karadi (2015)). Change in 3-month ahead fed fundsfutures within a 30 minute window of FOMC announcement.
3 HFI-CMO: (Gurkaynak et al.(2005) 1990-1993, Gorodnichenko and Weber(2016) 1994-2007) Change in urrent month fed funds futures within 60 minutewindow of FOMC announcement
4 NAR-GBK: (Romer and Romer (2004), Wieland and Yang (2016)) Residualfrom narrative accounts of FOMC meetings regressed on unemployment,Greenbook estimates of past and future inflation and GDP and revisions.
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Demographics and Monetary Policy Shocks BLCM
Time-Series Properties of the Monetary Policy Shocks
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Demographics and Monetary Policy Shocks BLCM
Structural VAR
1 gc,j,t = 100∆ ln(cj,t ) j = {young, middle,old}2 st monetary policy shock3 rt real fed funds rate
1 a12 a130 1 00 a32 1
gc,tstrt
=8
∑p=1
bp,11 bp,12 bp,130 0 0
bp,31 bp,32 bp,33
gc,t−pst−prt−p
+
uc,tus,tur ,t
,
(1)Structural error terms serially uncorrelated, diagonal covariance matrix, E (ut u′t ) = D.
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Demographics and Monetary Policy Shocks BLCM
Cumulated consumption growth impulse response
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Demographics and Monetary Policy Shocks BLCM
VAR Impulse ResponseYoung (24-34) Middle (35-64) Old (65+)
A. HFI-TRM
B. HFI-3MO
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Demographics and Monetary Policy Shocks BLCM
VAR Impulse ResponseYoung (24-34) Middle (35-64) Old (65+)
C. HFI-CMO
D. NAR-GBK
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Demographics and Monetary Policy Shocks BLCM
Old minus Young
Old minus Middle
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Demographics and Monetary Policy Shocks BLCM
OMY and OMM VAR Impulse ResponseOld minus Young Old minus Middle
A. HFI-TRM
B. HFI-3MO
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Demographics and Monetary Policy Shocks BLCM
OMY and OMM VAR Impulse ResponseOld minus Young Old minus Middle
C. HFI-CMO
D. NAR-GBK
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Demographics and Monetary Policy Shocks BLCM
Impulse Response of Aggregate Consumption (NAcA)at Different Points in Time: 1990, 2010, 2030
NA∆ ln (cA,t ) = Nycy
cA∆ ln (cy ,t ) + Nm
cm
cA∆ ln (cm,t ) + No
co
cA∆ ln (co,t ) ,
(2)
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Demographics and Monetary Policy Shocks BLCM
Impulse Response of Aggregate Consumption 2010minus 1990, 2030 minus 1990
Aggregate Response in 2010 minus 1990 and 2030 minus 1990HFI-TRM HFI-3MO HFI-CMO NAR-GBK
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Demographics and Monetary Policy Shocks BLCM
Response of Aggregate Consumption 2010 minus1990, 2030 minus 1990B. Cumulated 20 Quarter Difference in Aggregate Response2010 minus 1990 and between 2030 minus 1990
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Demographics and Monetary Policy Shocks BLCM
Local ProjectionsFor h = 1, . . . ,20, look at (−βh) from
ln
(ct+h
ct
)= βhst + ah,1 ln
(ct
ct−3
)+ ah,2 ln
(ct−4
ct−7
)+
7
∑j=0
bh,j rt−j + ut+h
(3)
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Demographics and Monetary Policy Shocks BLCM
Local ProjectionsYoung (24-34) Middle (35-64) Old (65+)
A. HFI-TRM
B. HFI-3MO
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Demographics and Monetary Policy Shocks BLCM
Local ProjectionsYoung (24-34) Middle (35-64) Old (65+)
C. HFI-CMO
D. NAR-GBK
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Demographics and Monetary Policy Shocks BLCM
Old minus Young
Old minus Middle
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Demographics and Monetary Policy Shocks BLCM
Local Projections OMY and OMMOld minus Young Old minus Middle
A. HFI-TRM
B. HFI-3MO
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Demographics and Monetary Policy Shocks BLCM
Local Projections OMY and OMMOld minus Young Old minus Middle
C. HFI-CMO
D. NAR-GBK
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Demographics and Monetary Policy Shocks BLCM
Nondurable Consumption
Old minus Young
Old minus Middle
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Demographics and Monetary Policy Shocks BLCM
NondurablesOld-Young Old-Middle Old-Young Old-Middle
A. SVAR HFI-TRM LP HFI-TRM
B. SVAR HFI-3MO LP HFI-3MO
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Demographics and Monetary Policy Shocks BLCM
NondurablesOld-Young Old-Middle Old-Young Old-Middle
C. SVAR HFI-CMO LP HFI-CMO
D. SVAR NAR-GBK LP NAR-GBK
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Demographics and Monetary Policy Shocks BLCM
Robustness
Six age groupsDurable goodsConsumption minushousingCEX weights in agegroupVAR in levels
Six lags in VARLocal projectionswithout controlling forlagged consumptionRegressions with microdata Micro Data Regressions
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Demographics and Monetary Policy Shocks BLCM
Looking for Evidence on a Mechanism
Motivating(i) Heterogeneous Wealth Effects
(ii) Heterogenous Funding for Consumption
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Demographics and Monetary Policy Shocks BLCM
Income, Wealth, Portfolio Composition by AgeThe next three slides show,
1 Most people ‘retire’ before 65.Therefore, old eat mostly from non-labor income
2 Old people’s portfolios tilted towards long-term assetsPortfolio value more sensitive to interest rates.
3 Working age people eat mainly from labor income.They look like they hand-to-mouth
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Demographics and Monetary Policy Shocks BLCM
Income, Wealth, Portfolio Composition by Age
Figure: Median and Mean Wage Income as a Share of Total Income by Age:1989, 1998, and 2007
25 30 35 40 45 50 55 60 65 70 75 80+
Age
0
0.2
0.4
0.6
0.8
1
198919982007
25 30 35 40 45 50 55 60 65 70 75 80+
Age
0
0.2
0.4
0.6
0.8
1
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Demographics and Monetary Policy Shocks BLCM
Measures of Net Worth
1 Net Worth is total assets as stated by the SCF minus total debts.2 Net Long Term 1, is the sum of net property equity (value of
properties, including own residence, less outstanding debt on theproperties), stock holdings, stock mutual funds, and annuities - ameasure of long term, interest sensitive assets.
3 Net Long Term 2 is Net Long Term 1 plus non-stock mutual funds(but not money market funds) plus directly held bonds of alltypes.
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Demographics and Monetary Policy Shocks BLCM
Measures of Net Worth
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Demographics and Monetary Policy Shocks BLCM
Wealth and Income1 I want to run VARs with wealth, but I only have household
income data.2 Income and wealth are positively correlated.
Figure: Log Net Wealth and Log Income in 1989, 1998, and 2007
0
5
10
15
20
Log
Net
Wor
th
5 10 15 20
Log Income
1989
0
5
10
15
20
Log
Net
Wor
th
5 10 15 20
Log Income
1998
0
5
10
15
20
Log
Net
Wor
th5 10 15 20
Log Income
2007
Notes: Data is from the Survey of Consumer Finances.33 / 54
Demographics and Monetary Policy Shocks BLCM
VAR High minus Low IncomeYoung (24-34) Middle (35-64) Old (65+)
A. HFI-TRM
B. HFI-3MO
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Demographics and Monetary Policy Shocks BLCM
VAR High minus Low IncomeYoung (24-34) Middle (35-64) Old (65+)
C. HFI-CMO
D. NAR-GBK
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Demographics and Monetary Policy Shocks BLCM
Local Projections High minus Low IncomeYoung (24-34) Middle (35-64) Old (65+)
A. HFI-TRM
B. HFI-3MO
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Demographics and Monetary Policy Shocks BLCM
Local Projections High minus Low IncomeYoung (24-34) Middle (35-64) Old (65+)
C. HFI-CMO
D. NAR-GBK
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Demographics and Monetary Policy Shocks BLCM
Modelling the Mechanism
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Demographics and Monetary Policy Shocks BLCM
ModelWhat is a model that explains
1 Old consumption responds the most to monetary policy shock?2 Young consuumption more responsive than middle but less than
old?3 Emphasize wealth effect for old people, labor-leisure choice for
young people.
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Demographics and Monetary Policy Shocks BLCM
A ModelMain Properties
1 Quarterly OLG model.2 Idiosyncratic income risk3 People can live 86 years4 Age 25-64
WorkUse labor income to eat and buy long-term bond.
5 Age 65-86Retired,Can die prematurely,Live off of accumlated bonds and pension incomeBequest motive
6 Epstein-Zin recursive utility
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Demographics and Monetary Policy Shocks BLCM
Income Process: individual i cohort zLife-cycle of permanent income
Yi,z,t =
Yi,z−1,t−1MgGzeni,z,t z < z∗
prr Yi,z∗,t−1 z = z∗
Yi,z−1,t−1eni,z,t z > z∗.
Transitory income shock
ui,z,t =
{N(µu, σ2
u)
with probability (1− p)−∞ with probability p
Wage incomeWi,z,t = Yi,z,teui,z,t for z < z∗
Pension income
Si,z,t =
{Yi,z,t z = z∗
Yi,z,teui,z,t z > z∗.
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Demographics and Monetary Policy Shocks BLCM
Income Process Parameter Estimates
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Demographics and Monetary Policy Shocks BLCM
Long-Term Bond and Interest RateBond
1 Bond is real perpetuity (consol)2 Pays 1 unit consumption per bond3 Price Pa
t = 1rt
Interest rate1 AR(1) for Federal funds rate2 Expectations theory plus 1.309% term premium to get 10 year
bond rate.3 Five interest rate states: 3.08, 3.27, 3.44, 3.61, and 3.78 percent per
annum
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Demographics and Monetary Policy Shocks BLCM
Utility and budget constraintsWorking aged
Vi,z,t =
{(1− β)
(Cν
i,z,t (1− Li,z,t )1−ν)(1−ρ)
+ β
[(Et
[V 1−γ
i,z+1,t+1
]) (1−ρ)(1−γ)
]} 1(1−ρ)
Pat Ai,z+1,t+1 = Ai,z,t + Pa
t Ai,z,t + Li,z,tWi,z,t −Ci,z,t ,
Rewrite as
Ai,z+1,t+1 = Ai,z,t + rt (Ai,z,t + Li,z,tWi,z,t −Ci,z,t ) .
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Demographics and Monetary Policy Shocks BLCM
Utility and budget constraintsRetired
Vi,z,t =
(1− βδz,t )(
Cνi,z,t
)(1−ρ)+ β
[δz,t Et
(V 1−γ
i,z+1,t+1
)+
(1− δz,t )
1− γEt
((1b
Ai,z+1,t+1rt
)ν)1−γ] 1−ρ
1−γ
1
1−ρ
,
Ai,z+1,t+1 = Ai,z,t + rt (Ai,z,t + Si,z,t −Ci,z,t )
Last possible period (quarter 344)
Vi,Z ,t =
(Cνi,z,t)(1−ρ)
+ β
[1
1− γEt
((1b
Ai,z+1,t+1rt
)ν)1−γ] 1−ρ
1−γ
1
1−ρ
,
Parameters used
prr = 0.4
β = 0.9962 , ρ = 5
γ = 12, ν = 0.5.
b = 2.5
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Demographics and Monetary Policy Shocks BLCM
Impulse ResponseExperiment Federal Funds Rate Impulse Response
1 Simulate economy until there are 344 cohorts2 10,000 individuals per cohort3 Drop interest rate from 3.44 % to 3.08% and hold for 8 quarters4 Interest rate rises to 3.27% for 7 quarters5 Interest rate resumes stochastic evolution6 Observe consumption response by age groups
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Demographics and Monetary Policy Shocks BLCM
Impulse ResponseA. Log Consumption B. Number of Assets
C. Value of Assets D. Log Labor
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Demographics and Monetary Policy Shocks BLCM
Net Asset HistogramsA. Young (25-34) B. Middle (35-64)
C. Old (65+)
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Demographics and Monetary Policy Shocks BLCM
Impulse Response by Age and WealthA. Young (25-34) B. Middle (35-64)
C. Old (65+)
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Demographics and Monetary Policy Shocks BLCM
Alternative Utility SpecificationsA. No Labor B. ψ = 1.5
C. ψ = 0.1,γ = 2 D. CRRA, γ = 12
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Demographics and Monetary Policy Shocks BLCM
Conclusion
1 Largest response: Old consumption2 Second highest response (it seems): Young consumption3 Weath effect for the old4 Hand-to-mouth consumption of working aged5 Model qualitatively explains (most of) data features
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Demographics and Monetary Policy Shocks BLCM
CEX Categories
Back To Orig
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Demographics and Monetary Policy Shocks BLCM
Federal Funds Rate Impulse Response
Back
A. HFI-TRM B. HFI-3MO
C. HFI-CMO D. NAR-GBK
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Demographics and Monetary Policy Shocks BLCM
Micro Data Regressions
Back
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