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C LASSIC P OLICY B ENCHMARKS FOR
H ETEROGENEOUS A GENT
E CONOMIES
James Bullard, Federal Reserve Bank of St. Louis
Riccardo DiCecio, Federal Reserve Bank of St. Louis

Monetary Policy and Heterogeneity Conference
Hong Kong Monetary Authority and
Federal Reserve Bank of New York
May 23, 2019
Hong Kong, China
Any opinions expressed here are our own and do not necessarily reflect those of the FOMC.

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C ONCLUSIONS

Introduction

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P OLICY

L ARGE - SCALE HETEROGENEOUS

E QUILIBRIUM

AGENT

I NEQUALITY

C ONCLUSIONS

DSGE

There has been increasing interest in large-scale heterogeneous
agent DSGE models.
These models have realistic degrees of heterogeneity—approaching
observed Gini coefficients in U.S. data.
They more directly address issues around income, financial wealth
and consumption inequality.
What is the role of monetary policy?

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O UTLINE OF THE ARGUMENT
We construct a heterogeneous agent economy featuring:
An aggregate shock to the natural rate of interest
Both permanent and temporary idiosyncratic risk at the household
level
A simple and symmetric structure

We include four policymakers:
A monetary authority
A fiscal authority
A labor market authority
An education authority

We describe a competitive equilibrium in which the four
policymakers act in concert to attain a first-best allocation of
resources.

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CLASSIC VIEW

The policymaker roles are “classic.”
The monetary authority follows a state-contingent policy rule
reacting to the aggregate shock (nominal GDP, or NGDP, targeting).
The fiscal authority raises revenue via a non-state contingent linear
labor income tax on all households.
The labor market authority runs an unemployment insurance
program.
The education authority minimizes the variance of
beginning-of-life human capital endowments.

Hence, the main result is that classic policy prescriptions can achieve
the first-best allocation of resources in this benchmark heterogeneous
agent economy.
This result may be helpful in understanding more complicated
economies that deviate from this benchmark.

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S OME SURPRISING FINDINGS
The proposed classic policies appear broadly similar to actual
policies in place in OECD economies.
Simple linear labor income taxes can be used without distorting
the labor supply.
The fiscal authority does not rely on age-dependent taxation in
this environment.
The best policy combination drives the consumption Gini to zero
but leaves income and financial wealth Ginis close to observed
levels.
This suggests that most observed income and financial wealth
inequality is due to life-cycle effects alone.

The model has a paper-and-pencil solution despite the aggregate
shock.

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S OME RECENT LITERATURE
Kaplan, Moll and Violante (AER, 2018):
NK model with heterogeneous households (HANK); reasonable
Gini coefficients.
The monetary policy transmission mechanism is substantially
altered relative to standard models.

Bhandari, Evans, Golosov and Sargent (Working paper, NBER,
2018):
Incomplete markets, nominal friction, heterogeneous households;
reasonable Gini coefficients.
Ramsey-optimal monetary-fiscal policy is substantially altered
relative to standard models.

Bullard and DiCecio (Unpublished manuscript, 2019):
Incomplete markets, nominal friction, heterogeneous households;
reasonable Gini coefficients.
Optimal monetary-fiscal policy looks like classic prescriptions from
standard models.
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A DDITIONAL RECENT LITERATURE
Heathcote, Storesletten and Violante (Working paper, NBER,
2019):
Incomplete markets, real economy, heterogeneous households.
Optimal fiscal policy: The average marginal tax rate is increasing
and concave in age; tax progressivity is U-shaped in age.

Heathcote and Tsujiyama (Unpublished manuscript, 2017):
Incomplete markets, heterogeneous households.
Optimal Mirrleesian taxation is compared with parametric Ramsey
taxation.

Koenig (IJCB, 2013) and Sheedy (BPEA, 2014):
NGDP targeting in economies with nominal contracting.

Huggett, Ventura and Yaron (AER, 2011) :
The majority of life cycle earnings are attributable to age-23
characteristics as opposed to subsequent shocks.

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Environment

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L IFE - CYCLE MODELS
We construct a general-equilibrium life-cycle economy with
“symmetry assumptions.”
Each period, a new continuum of households enters the economy,
makes economic decisions over the next 241 periods, then exits the
economy. The model is therefore “quarterly.”
All households have log preferences defined over consumption
and leisure—period utility is of the form
η ln c + (1

η ) ln `.

(1)

All households have a discount factor of unity.
The aggregate production technology is linear in the aggregate
effective labor input.
Aggregate shock: The economy grows over time via stochastic
growth in total factor productivity.

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L IFE - CYCLE PRODUCTIVITY
Each household is randomly assigned a personal productivity
profile e = fe0 , e1 , ..., e240 g when it enters the model.

Profiles are symmetric—they begin low, rise and peak exactly in
the middle of life, then decline symmetrically back to the low level.
Profiles are restricted to be consistent with interior solutions to all
household problems—households will choose to work low hours
but not zero.
Profiles are members of a set E , but in this talk we restrict E to have
just one member.
Households also draw a scaling factor ξ from a lognormal
distribution as they enter the model, i.e., ln ξ N µ, σ2 .

The product of their scaling factor and their assigned productivity
profile permanently determines their life-cycle productivity, that is, ξe.
Accordingly, there will be arbitrarily rich and arbitrarily poor
households in the economy.

For illustrative purposes, ξ is drawn from a uniform distribution
U [a, b] in the figures shown later.

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R ATIONALE FOR

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A PERMANENT PRODUCTIVITY SHOCK

The assignment of productivity profiles is a stand-in for the
human capital development that takes place before age 20 in
actual economies, including schooling, parenting and any job
experience before age 20.
Huggett, Ventura and Yaron (AER, 2011) argue that differences in
initial conditions are more important than subsequent shocks in
explaining lifetime income.

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A DDITIONAL IDIOSYNCRATIC RISK

Households can earn income in a competitive economywide
labor market by supplying hours along with the productivity
they have available at that date.
At the beginning of each period, each household may be
randomly unemployed.
The household earns no income from work on dates of
unemployment.
The unemployment probability is i.i.d. and uncorrelated with the
aggregate shock.

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B ASELINE LIFE - CYCLE PRODUCTIVITY
1.5

1

0.5

0

0

60

120

180

240

Quarters
F IGURE : A baseline personal productivity endowment profile. The profile is
symmetric and peaks in the middle period of the life cycle at a level about
50% greater than at the beginning or end. A full model would include a set of
symmetric profiles with differing shapes.

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OF LIFE - CYCLE PRODUCTIVITY

F IGURE : The mass of endowment profiles with the scaling factor drawn from
a uniform distribution U [0.05, 1.95]. Drawing from a lognormal distribution
is harder to visualize, but such a distribution would include arbitrarily rich
and arbitrarily poor households. The endowment Gini is about 35%.

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C ONCLUSIONS

H OUSEHOLD CREDIT

The overlapping-generations structure creates a large private
credit market essential to good macroeconomic performance.
The key asset is therefore privately issued household debt.
As practical motivation, think of privately issued debt =
“mortgage-backed securities.”
U.S. household debt in the first quarter of 2019 was about $13.5
trillion, which was equal to about two-thirds of GDP.

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N ON - STATE CONTINGENT

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C ONCLUSIONS

NOMINAL CONTRACTING

There is a key friction in the credit market: non-state contingent
nominal contracting.
There are two aspects to this assumption.
The non-state contingent aspect means that real resources are
misallocated via this friction.
The nominal aspect means that the monetary authority may be able
to fix the distortion to the equilibrium through appropriate
monetary policy.

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I NFORMATION ASSUMPTIONS

All households have private information concerning their
scaling factor ξ and their productivity profile drawn from the
(singleton) set E .
Households can choose a level of effort, or intensity of work,
which is linear in the life-cycle productivity profile.
Accordingly, households can potentially pretend to possess lower
productivity profiles than they actually have.

The unemployment draw is public information.

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A DDITIONAL ASSUMPTIONS
There are no borrowing constraints.
See Azariadis et al. (JEDC, 2019) for a version with some
households excluded from credit markets.

There is no population growth in this version.
There is no default.
Prices are flexible.
Capital is fixed.
We ignore the effective lower bound in this version; see
Azariadis et al. (JEDC, 2019).
All policies are set credibly for all time t 2 ( ∞, +∞) .

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C ONCLUSIONS

Four Policymakers

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ENTITIES

There are four policymaking entities.
The monetary authority can observe the aggregate shock at the
beginning of date t and then set the price level P (t) .
The fiscal authority can set taxes on labor or capital income to raise
an exogenously specified fraction of available real output.
The labor market authority observes household-specific
unemployment shocks, sets taxes and provides household-specific
transfers.
The education authority can control the initial dispersion of
life-cycle productivity profiles by controlling the variance of the
scaling factor ξ.

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T HE PROPOSED POLICY MIX

The proposed policy mix is as follows:
The monetary policymaker follows an NGDP targeting rule similar
to Koenig (IJCB, 2013) and Sheedy (BPEA, 2014).
The fiscal authority sets a linear tax on all labor income earned that
is sufficient to meet its revenue requirement.
The labor market authority sets a linear tax on all labor income
earned that is sufficient to provide appropriate transfers to
unemployed households.
The education authority minimizes the dispersion of life-cycle
productivity profiles by setting ξ = 1.

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T HE W ICKSELLIAN NATURAL REAL RATE OF INTEREST
T HEOREM
Under the proposed policy mix, the real interest rate is exactly equal to the
stochastic aggregate output growth rate at every date, and an
equal-treatment social planner that discounts at this rate will conclude that
this is a social optimum.

C OROLLARY (E QUITY SHARE CONTRACTING )
Any two households that share the same productivity profile consume the
same amount at each date, and consumption growth is equalized for all
households.

C OROLLARY
Desired labor supply over the life cycle depends on the shape of the
productivity profile alone.

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Characterizing the Policies

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C HARACTERIZING

P OLICY

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C ONCLUSIONS

THE POLICIES

We first describe how the monetary policy works.
We then characterize the equilibrium in a series of schematic
graphs representing the cross-sectional distribution of
households at each date.
In the graphs, we will show both the case when ξ = 1, the social
optimum, and also the case where ξ is drawn from a uniform
distribution.
We can interpret this latter case as one where the education
policymaker cannot drive the variance the scaling factor all the
way to zero.

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M ONETARY POLICY
The monetary policymaker controls the price level P (t) directly
and follows an NGDP targeting rule similar to Sheedy (BPEA,
2014), Koenig (IJCB, 2013) and Bullard and DiCecio (Working
paper, St. Louis Fed, 2019):
P (t) =

Rn (t 1, t)
P (t
λ (t 1, t)

1) ,

(2)

where Rn (t 1, t), the gross nominal interest rate, is equal to the
expected gross rate of NGDP growth between dates t 1 and t,
and λ (t 1, t) is the realized gross rate of aggregate productivity
growth between dates t 1 and t.
The NGDP targeting rule works because it provides a form of
insurance for all households against future aggregate shocks.
This policy rule is not unique. See Bullard and Singh (JMCB, 2019
forthcoming).

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E FFECTS

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OF AN AGGREGATE SHOCK
1.06
1.02
1.04
1
1.02
0

5

10

0

quarters

5

10

quarters

1.4

1.06
1.04

1.2

1.02
1
0

5

quarters

10

0

5

10

quarters

F IGURE : Monetary policy responds to a decrease in aggregate productivity
growth by increasing the inflation rate in the period of the shock.
Subsequently, however, inflation converges to its long-run equilibrium value
from below. The nominal interest rate drops in the period after the shock.

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L EISURE CHOICES AND

P OLICY

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C ONCLUSIONS

TAX POLICY

Given the monetary policy, the labor market authority sets a tax
τ u that is linear in labor earnings.
The fiscal authority sets a tax τ f that is also linear in labor
earnings.
The household i first-order condition for leisure can then be
written as

`t,i (t + s) = (1
where ē =

1
T +1

η)

∑Ts=0 es and ēi =

ēi
= (1
es,i

1
T +1

η)

ē
, 8i,
es

(3)

∑Ts=0 es,i .

The scaling factor ξ and the two taxes τ u and τ f are all linear in e
and therefore cancel out in this expression—so taxing in this
manner is nondistortionary.
This result requires that all labor income is taxed at these rates.

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L EISURE CHOICES AND M IRRLEESIAN CONSIDERATIONS

f

Because τ ui = τ u 8i and τ i = τ f 8i, households will not be
incentivized to withhold effort by misrepresenting their type.
Under these policy choices, all households choose the same
leisure and hours worked profile over the life cycle, and
aggregate output is as large as it would be in an economy
without taxation.

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H OURS

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WORKED OVER THE LIFE CYCLE
1

0.5

0
0

60

120

180

240

Quarters
F IGURE : Cross section: Leisure decisions (green), labor supply decisions
(blue) and fraction of work time in U.S. data, 19% (red). The labor/leisure
choice depends on age only. High-income households plan to work the same
hours as low-income households at each age. A certain percentage of the
continuum of households in each cohort is unemployed but insured.

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E DUCATION POLICY
“Education policy” influences the productivity profile dispersion
parameter σ.
One could interpret this as an idealized insurance market that
operates before households enter the economy at age 20.
Limiting case: σ = 0, all households receive the same profile.
This would be a “perfectly equal” economy in that the talent
distribution would collapse to just one life-cycle pattern.
This would drive the consumption Gini to zero.
However, the income and wealth Gini coefficients would remain
close to observed values—these are driven mostly by the life-cycle
structure.

We will show both the idealized case and cases where σ > 0.

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Characterizing the Equilibrium

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L ABOR INCOME

Households want to work more when they are in their peak
earning years in the middle of the life cycle.
This creates substantial labor income inequality.

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L ABOR INCOME MASS

F IGURE : Cross section: Labor income profiles with unemployment insurance.
Personal productivity peaks at the middle of the life cycle, and households
work more at that time as well, making income even more concentrated in
the peak earning years. The blue line depicts conditions of the theorem with
ξ = 1.
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C ONSUMPTION MASS

F IGURE : Cross section: Schematic consumption mass (red) and labor income
mass (blue). Under optimal monetary policy, the private credit market
reallocates uneven labor income into perfectly equal consumption along each
productivity profile. The consumption Gini is 31.7%, similar to values
calculated from U.S. data. The blue line depicts conditions of the theorem
with ξ = 1.
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C ONSUMPTION EVOLUTION

F IGURE : Time series: Evolution of the distribution of log consumption
(shaded area) and examples of individual log consumption profiles (colored
lines). Under optimal monetary policy, individual consumption profiles
share the same stochastic trend as aggregate consumption.
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ASSET HOLDING MASS

F IGURE : Cross section: Schematic net asset holding mass relative to GDP by
cohort. Borrowing, the negative values to the left, peaks at stage 60 of the life
cycle (age ~35), while positive assets peak at stage 180 of life (age ~65). The
financial wealth Gini is 72.7%, similar to values calculated in U.S. data. The
blue line depicts conditions of the theorem with ξ = 1.
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T HREE NOTIONS

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OF INCOME

Three notions of income:
Pretax labor income, Y1 .
Pretax labor income plus non-negative capital income, Y2 .
The non-negative component of total income, Y3 .

Gini coefficients of income distributions: GY1 = 56.1%,
GY2 = 51.5%, GY3 = 59.5%.

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L ABOR INCOME + NON - NEGATIVE CAPITAL INCOME

F IGURE : Cross section: Profiles of labor income and non-negative capital
income. The blue line depicts conditions of the theorem with ξ = 1.

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N ON - NEGATIVE TOTAL INCOME

F IGURE : Cross section: Profiles of non-negative total income. The blue line
depicts conditions of the theorem with ξ = 1.

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Inequality

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D ATA ON INEQUALITY IN THE U.S.

Consumption (Heathcote, Perri and Violante, RED, 2010):
GC,U.S. = 32%.
Income (CBO, 2016): pre-taxes/transfers GY,U.S. = 51%;
post-taxes/transfers GY,U.S. = 43%.
Financial wealth (Davies, Sandström, Shorrocks and Wolff, EJ,
2011): GW,U.S. = 80%.

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G INI COEFFICIENTS

Y1

Income
Y2
51%

Y3

U.S. data

Wealth
W
80%

Consumption
C
32%

Uniform

72.7%

56.1%

51.5%

59.5%

31.7%

Lognormal

72.4%

55.7%

51.1%

59.0%

32%

TABLE : Gini coefficients in the U.S. data and in the model with uniform and
lognormal productivity.

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P RODUCTIVITY DISPERSION AND G INI COEFFICIENTS
1

0.653
0.5
0.443

0
0

0.5

1

1.5

2

2.5

3

3.5

F IGURE : As the dispersion of productivity profiles, σ, increases, the Gini
coefficients increase. The ordering GW > GY > GC is preserved. The case
where σ = 0 is the social optimum and has GC = 0 but GW = 65.3% and
GY = 44.3%. The model can match the wealth Gini in the data with a
sufficiently large choice of σ.

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Conclusions

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S UMMARY
A classic combination of policies, which looks like those of many
OECD countries, can deliver a first-best allocation of resources in
this environment.
A monetary policymaker pursues NGDP targeting, providing a
type of insurance against the aggregate shock.
This leaves labor supply as a function of relative life-cycle
productivity alone. Therefore, this enables non-distortionary linear
labor income taxes to fund government expenditures as well as an
unemployment insurance program.
Education policy can mitigate the effects of the permanent shock to
household productivity as households enter the model without
impacting the other policy settings.
A perfect education policy could drive the consumption Gini to
zero but would leave income and wealth Ginis near their observed
values.
These classic benchmarks may be useful in understanding the
effects of monetary policy for models in this class going forward.

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