BufferStockTheory.tex
Theoretical Foundations of
Buffer Stock Saving
August 4, 2017
| Christopher D. Carroll1 |
_____________________________________________________________________________________
Abstract
“Buffer-stock” models of saving are now common in the consumption literature. This paper builds
theoretical foundations for rigorous understanding of the main features of such models, including the
existence of a target wealth ratio and the proposition that aggregate consumption growth equals
aggregate income growth in a small open economy populated by buffer stock savers.
Precautionary saving, buffer stock saving, marginal propensity to consume, permanent income hypothesis
D81, D91, E21
| PDF: | http://econ.jhu.edu/people/ccarroll/papers/BufferStockTheory.pdf |
| Slides: | http://econ.jhu.edu/people/ccarroll/papers/BufferStockTheory-Slides.pdf |
| Web: | http://econ.jhu.edu/people/ccarroll/papers/BufferStockTheory/ |
| Github: | http://github.com/llorracc/BufferStockTheory-Latest |
| (Contains software for solving and simulating the model) |
1Contact: ccarroll@jhu.edu, Department of Economics, 440 Mergenthaler Hall, Johns Hopkins University, Baltimore, MD 21218, http://econ.jhu.edu/people/ccarroll, and National Bureau of Economic Research.
Spurred by the success of Modigliani and Brumberg’s (1954) Life Cycle model and Friedman’s (1957) Permanent Income Hypothesis, a vast literature in the 1960s and 1970s formalized the idea that household spending can be modeled as reflecting optimal intertemporal choice. Famous papers by Schectman and Escudero (1977) and Bewley (1977) capped this literature, providing key building blocks for the ascendancy of dynamic stochastic optimizing models in economics.
Given this pedigree, it is surprising that the now-standard method for analyzing such problems, contraction mapping theory, has not yet established some basic properties of the solution to the benchmark consumption problem with unbounded (e.g. constant relative risk aversion) utility, uncertainty about permanent and transitory income a la Friedman (1957), and no liquidity constraints (nor has any other method established such results). The gap exists because (except in a few special cases) standard theorems from the contraction mapping literature (including those in Stokey et. al. (1989) and up through the recent work of Matkowski and Nowak (2011)) cannot be used for this problem (for reasons explained below).
This paper fills that gap, deriving the conditions that must be satisfied for this standard problem to have a nondegenerate solution.
The reader could be forgiven for not having noticed a gap. A large literature solving precisely such problems has emerged following Zeldes (1989), fueled by advances in numerical solution methods. But numerical solutions are a ‘black box’: They make it possible to use a model without really understanding it. Indeed, without foundational theory, it can be difficult even to be sure that a computational solution is correct, given the notorious difficulty of writing error-free computer code. Furthermore, without theoretical underpinnings, the analyst often has little intuition for how results might change with changes in the structure (or even the calibration) of the model.
For example, numerical solutions typically imply the existence of a target level of nonhuman wealth (‘cash’ for short) such that if cash exceeds the target, the consumer will spend freely and cash will fall (in expectation), while if cash is below the target the consumer will save and cash will rise. Carroll (1992; 1997) showed that target saving behavior arises under plausible parameter values for both infinite and finite horizon models. Gourinchas and Parker (2002) estimate the Carroll (1997) model using household data and conclude that for the mean household the buffer-stock phase of life lasts from age 25 until around age 40-45; using the same model with different data Cagetti (2003) finds target saving behavior into the 50s for the median household. But none of these papers provides a rigorous delineation of the circumstances under which target saving will emerge or an analytical explanation for why such behavior is optimal.
This paper provides the analytical foundations for target saving and many other results that have become familiar from the numerical literature. All theoretical conclusions are paired with numerically computed illustrations (using software available on the author’s website), providing an integrated framework for understanding buffer-stock saving.
The paper proceeds in three parts.
The first part specifies the conditions required for the problem to define a unique limiting consumption function. The conditions turn out to strongly resemble those required for the liquidity constrained perfect foresight model to have a solution; that parallel is explored and explained. Next, some limiting properties are derived for the consumption function as cash approaches infinity and as it approaches its lower bound, and the theorem asserting that the problem defines a contraction mapping is proven. Finally, a related class of commonly-used models (exemplified by Deaton (1991)) is shown to constitute a particular limit of this paper’s more general model.
The next section examines five key properties of the model. First, as cash approaches infinity the expected growth rate of consumption and the marginal propensity to consume (MPC) converge to their values in the perfect foresight case. Second, as cash approaches zero the expected growth rate of consumption approaches infinity, and the MPC approaches a simple analytical limit. Third, if the consumer is sufficiently ‘impatient’ (in a particular sense), a unique target cash-to-permanent-income ratio will exist. Fourth, at the target cash ratio, the expected growth rate of consumption is slightly less than the expected growth rate of permanent noncapital income. Finally, the expected growth rate of consumption is declining in the level of cash. The first four propositions are proven under general assumptions about parameter values; the last is shown to hold if there are no transitory shocks, but may fail in extreme cases if there are both transitory and permanent shocks.
Szeidl (2012) has recently proven that such an economy will be characterized by stable invariant distributions for the consumption ratio, the wealth ratio, and other variables.2 Using Szeidl’s result, the final section shows that even with a fixed aggregate interest rate that differs from the time preference rate, an economy populated by buffer stock consumers converges to a balanced growth equilibrium in which the growth rate of aggregate consumption tends toward the (exogenous) growth rate of aggregate permanent income. A similar proposition holds at the level of individual households.
The consumer solves an optimization problem from the current period
until the end of life
at
defined by the objective
is a constant relative risk aversion utility function with
.3
4
The consumer’s initial condition is defined by market resources
(what Deaton (1991)
calls ‘cash-on-hand’) and permanent noncapital income
. (This will henceforth be called a
‘Friedman/Buffer Stock’ (FBS) income process because its definition corresponds reasonably
well to the descriptions in Friedman (1957) and because such a process has been widely used
in the numerical buffer stock saving literature.)
In the usual treatment, a dynamic budget constraint (DBC) simultaneously incorporates all
of the elements that determine next period’s
given this period’s choices; but for the
detailed analysis here, it will be useful to disarticulate the steps so that individual ingredients
can be separately examined:
indicates the consumer’s assets at the end of period
, which
grow by a fixed interest factor
between periods, so that
is
the consumer’s financial (‘bank’) balances before next period’s consumption
choice;5
(‘market resources’ or ‘money’) is the sum of financial wealth
and noncapital
income
(permanent noncapital income
multiplied by a mean-one iid transitory
income shock factor
; from the perspective of period
, all future transitory shocks are
assumed to satisfy
). Permanent noncapital income in period
is equal to its previous value, multiplied by a growth factor
, modified
by a mean-one iid shock
,
satisfying
for
where
is the degenerate case with no permanent
shocks.6
(Hereafter for brevity we occasionally drop time subscripts, e.g.
signifies
.)
Following Carroll (1992), assume that in future periods
there is a small
probability
that income will be zero (a ‘zero-income event’),
![]() | (3) |
where
is an iid mean-one random variable (
) that has a
distribution satisfying
where
(degenerately
). Call
the cumulative distribution functions
and
(and
is derived trivially from (3) and
). Permanent income and cash start out strictly positive,
and
,
and the consumer cannot die in debt,
The model looks more special than it is. In particular, the assumption of a positive probability
of zero-income events may seem objectionable. However, it is easy to show that a model with a
nonzero minimum value of
(motivated, for example, by the existence of unemployment
insurance) can be redefined by capitalizing the PDV of minimum income into current market
assets,7
analytically transforming that model back into the model analyzed here. Also, the assumption
of a positive point mass (as opposed to positive density) for the worst realization of the
transitory shock is inessential, but simplifies and clarifies the proofs and is a powerful aid to
intuition.
This model differs from Bewley’s (1977) classic formulation in several ways. The CRRA
utility function does not satisfy Bewley’s assumption that
is well defined, or that
is well defined and finite, so neither the value function nor the marginal value function will be
bounded. It differs from Schectman and Escudero (1977) in that they impose liquidity
constraints and positive minimum income. It differs from both of these in that it permits
permanent growth, and also permanent shocks to income, which a large empirical
literature finds are to be quantitatively important in micro data (MaCurdy (1982);
Abowd and Card (1989); Carroll and Samwick (1997); Jappelli and Pistaferri (2000);
Storesletten, Telmer, and Yaron (2004); Blundell, Low, and Preston (2008)) and which the
theory since Friedman (1957) suggests are far more consequential for household
welfare than are transitory fluctuations. (The incorporation of permanent shocks
also rules out application of the tools of Matkowski and Nowak (2011) and the
extensive literature cited therein). It differs from Deaton (1991) because liquidity
constraints are absent; there are separate transitory and permanent shocks (a la
Muth (1960)); and the transitory shocks here can occasionally cause income to reach
zero.8
Finally, it differs from models found in Stokey et. al. (1989) because
neither liquidity constraints nor bounds on utility or marginal utility are
imposed.9
The number of relevant state variables can be reduced from two (
and
) to one
as follows. Defining nonbold variables as the boldface counterpart normalized by
(as with
), assume that value in the last period of life is
, and consider the
problem in the second-to-last period,
Now consider the related problem
where
is a ‘growth-normalized’ return factor, and the problem’s first
order condition is
Since
, defining
from (??) for
, (5) reduces to

This logic induces to all earlier periods, so that if we solve the normalized one-state-variable
problem specified in (??) we will have solutions to the original problem for any
from:10

We say that a consumption problem has a nondegenerate solution if it defines a unique
limiting consumption function whose optimal
satisfies

(‘Degenerate’ limits will be cases where the limiting consumption function
is either
or
.)
The analytical solution to the perfect foresight specialization of the model, obtained by setting
and
, provides a useful reference point and defines some remaining
notation.
The dynamic budget constraint, strictly positive marginal utility, and the can’t-die-in-debt condition (4) imply an exactly-holding intertemporal budget constraint (IBC)
where
is ‘human wealth,’ the discounted value of noncapital income, and with a constant
, human wealth will be (9)
makes plain that in order for
to be finite, we must impose the Finite
Human Wealth Condition (‘FHWC’) Intuitively, for human wealth to be finite, the growth rate of noncapital income must be
smaller than the interest rate at which that income is being discounted.
In the absence of a liquidity constraint, the consumption Euler equation holds in every period;
with
, this says
.11
The sense in which
captures patience is that if the ‘absolute impatience condition’ (AIC)
holds, the
consumer will choose to spend an amount too large to sustain (the level of consumption must
fall over time). We say that such a consumer is ‘absolutely impatient’ (this is the key condition
in Bewley (1977)).
We next define a ‘return patience factor’ that relates absolute patience to the return factor:
so that

is the marginal propensity to consume (MPC) because it answers the question ‘if
the consumer had an extra unit of wealth, how much more would he spend.’ Equation (14)
makes plain that for the limiting MPC to be strictly positive as
goes to infinity we
must impose the condition so
that
Equation (16) thus imposes a second kind of ‘impatience:’ The consumer cannot be so
pathologically patient as to wish, in the limit as the horizon approaches infinity, to spend
nothing today out of an increase in current wealth. This is the condition that rules out the
degenerate limiting solution
. Henceforth (16) will be called the ‘return
impatience condition’ or RIC, and a consumer who satisfies the condition is called ‘return
impatient.’
Given that the RIC holds, and defining limiting objects by the absence of a time
subscript (e.g.,
), the limiting consumption function will be
we need
to be finite so we must impose the finite human wealth condition (10).
A final useful point is that since the perfect foresight growth factor for consumption is
,
using
yields the following expression for value:

approaches
if
;
with a bit of algebra, this requirement can be shown to be equivalent to the
RIC.12
Thus, the same conditions that guarantee a nondegenerate limiting consumption function also
guarantee a nondegenerate limiting value function.
If the liquidity constraint is ever to be relevant, it must be relevant at the lowest possible level
of market resources,
, which obtains for a consumer who enters period
with
. The constraint is ‘relevant’ if it prevents the choice that would otherwise be optimal;
at
the constraint is relevant if the marginal utility from spending all of today’s
resources
, exceeds the marginal utility from doing the same thing
next period,
; that is, if such choices would violate the Euler equation (6):
By analogy to the return patience factor, we therefore define a ‘perfect foresight growth patience factor’ as
and define a ‘perfect foresight growth impatience condition’ (PF-GIC) which is equivalent to (19) (exponentiate both sides by
).
If the RIC and the FHWC hold, appendix A shows that an unconstrained consumer
behaving according to (18) would choose
for all
for some
.
The solution to the constrained consumer’s problem in this case is simple: For any
the constraint does not bind (and will never bind in the future) and so the constrained
consumption function is identical to the unconstrained one. In principle, if the consumer were
somehow to arrive at an
the constraint would bind and the consumer would
have to consume
(though such values of
are of questionable relevance because
they could only be obtained by entering the period with
which the constraint
rules out). We use the
accent to designate the limiting constrained consumption
function:
![]() | (22) |
More useful is the case where the PF-GIC
and the RIC
both hold. In
this case appendix A shows that the limiting constrained consumption function is piecewise
linear, with
up to a first ‘kink point’ at
, and with discrete declines in the
MPC at successively increasing kink points
. As
the constrained
consumption function
approaches arbitrarily close to the unconstrained
, and the
marginal propensity to consume function
limits to
. Similarly, the
value function
is nondegenerate and limits into the value function of the
unconstrained consumer. Surprisingly, this logic holds even when the finite human
wealth condition fails (denoted
" class="math" > " class="oalign" >). A solution exists because the constraint
prevents the consumer from borrowing against infinite human wealth to finance
infinite current consumption. Under these circumstances, the consumer who starts
with any amount of resources
will run those resources down over time so
that by some finite number of periods
in the future the consumer will reach
, and thereafter will set
for eternity, a policy that will yield value
of

whenever
" class="math" > " class="oalign" >
holds.
So, if the
" class="math" > " class="oalign" > holds, value for any finite
will be the sum of two finite
numbers: The component due to the unconstrained consumption choice made over
the finite horizon leading up to
, and the finite component due to the
value of consuming all income thereafter. The consumer’s value function is therefore
nondegenerate.
The most peculiar possibility occurs when the RIC fails. Remarkably, the appendix shows
that although under these circumstances the FHWC must also fail, the constrained
consumption function is nondegenerate even in this case. While it is true that
, nevertheless the limiting constrained consumption function
is
strictly positive and strictly increasing in
. This result interestingly reconciles the
conflicting intuitions from the unconstrained case, where
" class="math" > " class="oalign" > would suggest a
dengenerate limit of
while
" class="math" > " class="oalign" > would suggest a degenerate limit of
.
Tables 2 and 3 (and appendix table 4) codify the key points to help the reader keep them straight (and to facilitate upcoming comparisons with the surprisingly parallel results in the presence of uncertainty but the absence of liquidity constraints (also tabulated for comparison)).
When uncertainty is introduced, the expectation of
can be rewritten as:
![´ - 1 -1
ψ ≡ (E[ψ ])](BufferStockTheory171x.png)
13
We refer to this as the ‘return compensated’ permanent shock, because it compensates for the
effect of uncertainty on the expected growth-normalized return (in the sense implicitly defined
in (25)). Note that Jensen’s inequality implies that
for nondegenerate
(since
by assumption).
Using this definition, we can transparently generalize the PF-GIC (21) by defining a ‘compensated growth factor’
and a compensated growth patience factor
![lim Et[mt+1 ∕mt] = ÞÞÞ ´Γ ,
mt→ ∞](BufferStockTheory180x.png)
from heading to infinity (that is, if we want
to be guaranteed to be expected to fall for some large enough value of
) we must impose a
generalized version of (21) which we call simply the ‘growth impatience condition’
(GIC):14
which is stronger than the perfect foresight version (21) because
.
A consumer who spent his permanent income every period would have value
![[ ]
vt = Et u(pppt) + βu(ppptΓ t+1) + ...+ βT -tu(ppptΓ t+1...Γ T)
( 1- ρ T-t 1-ρ 1-ρ)
= u(pppt) 1 + β Et [Γ t+1 ] + ...+ β Et[Γ t+1 ]...Et[Γ T ]
( 1 - (β Γ 1-ρ E[ψ1-ρ])T-t+1)
= u(pppt) ----------1-ρ----1-ρ-----
1 - βΓ E [ψ ]](BufferStockTheory187x.png)
![1-ρ 1∕(1-ρ)
ψ- = (E[ψ ])](BufferStockTheory188x.png)
for
and nondegenerate
(and
for the preferred
(though not required) case of
); defining
we can see that
will be finite as
approaches
if
which we call the ‘finite value of autarky’ condition (FVAC) because it is the value obtained
by always consuming permanent income, and which for nondegenerate
is stronger (harder
to satisfy in the sense of requiring lower
) than the perfect foresight version (23) because
.
Figure 1 depicts the successive consumption rules that apply in the last period of life
(
), the second-to-last period, and various earlier periods under the baseline parameter
values listed in Table 1. (The 45 degree line is labelled as
because in the last
period of life it is optimal to spend all remaining resources.)
| Description | Parameter | Value | Source
| |
| Permanent Income Growth Factor | ![]() | 1.03 | PSID: Carroll (1992)
| |
| Interest Factor | ![]() | 1.04 | Conventional | |
| Time Preference Factor | | 0.96 | Conventional
| |
| Coefficient of Relative Risk Aversion | ![]() | 2 | Conventional
| |
| Probability of Zero Income | ![]() | 0.005 | PSID: Carroll (1992)
| |
| Std Dev of Log Permanent Shock | ![]() | 0.1 | PSID: Carroll (1992)
| |
| Std Dev of Log Transitory Shock | ![]() | 0.1 | PSID: Carroll (1992)
| |
| Approximate | ||||
| Calculated | ||||
| Description | Symbol and Formula | Value | ||
| Finite Human Wealth Measure | | | | 0.990 |
| PF Finite Value of Autarky Measure | | | | 0.932 |
| Growth Compensated Permanent Shock | | | | 0.990 |
| Uncertainty-Adjusted Growth | | | | 1.020 |
| Utility Compensated Permanent Shock | | | | 0.990 |
| Utility Compensated Growth | | | | 1.020 |
| Absolute Patience Factor | | | | 0.999 |
| Return Patience Factor | | | | 0.961 |
| PF Growth Patience Factor | | | | 0.970 |
| Growth Patience Factor | | | | 0.980 |
| Finite Value of Autarky Measure | | | | 0.941 |
In the figure, the consumption rules appear to converge as the horizon recedes (below we show that this appearance is not deceptive); we call the limiting infinite-horizon consumption rule

A precondition for the main proof is that the maximization problem (??)
defines a sequence of continuously differentiable strictly increasing strictly
concave15 functions
.16
The proof of this precondition is straightforward but tedious, and so is relegated to
appendix B. For present purposes, the most important point is the following intuition:
for all periods
because if the consumer spent all available resources, he
would arrive in period
with balances
of zero, then might earn zero noncapital
income for the rest of his life (an unbroken series of zero-income events is unlikely but
possible). In such a case, the budget constraint and the can’t-die-in-debt condition
mean that the consumer would be forced to spend zero, incurring negative infinite
utility. To avoid this disaster, the consumer never spends everything. (This is an
example of the ‘natural borrowing constraint’ induced by a precautionary motive
(Zeldes (1989)).)17
The consumption functions depicted in Figure 1 appear to have limiting slopes as
and
as
. This section confirms that impression and derives those slopes, which also turn
out to be useful in the contraction mapping proof.
Assume (as discussed above) that a continuously differentiable concave consumption
function exists in period
, with an origin at
, a minimal MPC
,
and maximal MPC
. (If
these will be
; for earlier periods
they will exist by recursion from the following arguments.)
For
we can define
and
and the Euler
equation (6) can be rewritten
Consider the first conditional expectation in (32), recalling that if
then
. Since
,
is contained
within bounds defined by
and
both of which are
finite numbers, implying that the whole term multiplied by
goes to zero as
goes to
zero. As
the expectation in the other term goes to
(This follows from
the strict concavity and differentiability of the consumption function.) It follows
that the limiting
satisfies
We can conclude that
Then
is a decreasing convergent sequence if
it will hold more easily (for a larger set of parameter values) than the RIC
(
).
Since
, iterating (34) backward to infinity (because we are interested in the limiting
consumption function) we obtain:
the ‘limiting maximal MPC.’
The minimal MPC’s are obtained by considering the case where
. If the FHWC
holds, then as
the proportion of current and future consumption that will be
financed out of capital approaches 1. Thus, the terms involving
in (31) can be neglected,
leading to a revised limiting Euler equation
![(m e (m ))-ρ = βR E [(e (a (m )R )(Ra (m )))- ρ]
t t t t t+1 t t t+1 t t](BufferStockTheory288x.png)
, and
so
a further limit of the Euler equation is 
holds, then a recursive formula for the minimal marginal propensity to consume is given by
so
that
is also an increasing convergent sequence, with
being the ‘limiting
minimal MPC.’ If the RIC does not hold, then
and so the limiting MPC
is
We are now in position to observe that the optimal consumption function must satisfy
because consumption starts at zero and is continuously differentiable (as argued above), is strictly concave (Carroll and Kimball (1996)), and always exhibits a slope between
and
(the formal proof is provided in appendix D).
To prove that the consumption rules converge, we need to show that the problem defines a
contraction mapping. This cannot be proven using the standard theorems in, say, Stokey
et. al. (1989), which require marginal utility to be bounded over the space of possible values
of
, because the possibility (however unlikely) of an unbroken string of zero-income events
for the remainder of life means that as
approaches zero
must approach zero (see the
discussion in 2.7); thus, marginal utility is unbounded. Although a recent literature
examines the existence and uniqueness of solutions to Bellman equations in the
presence of ‘unbounded returns’ (see Matkowski and Nowak (2011) for a recent
contribution), the techniques in that literature cannot be used to solve the problem here
because the required conditions are violated by a problem that involves permanent
shocks.18
Fortunately, Boyd (1990) provides a weighted contraction mapping theorem that can be used. To use Boyd’s theorem we need
Definition 1. Consider any function
where
is the space of continuous
functions from
to
. Suppose
with
and
. Then
is
-bounded if the
-norm of
,
![]() | (39) |
is finite.
For
defined as the set of functions in
that are
-bounded;
,
,
, and
as examples of
-bounded functions; and using
to
indicate the function that returns zero for any argument, Boyd (1990) proves the
following.
Boyd’s Weighted Contraction Mapping Theorem. Let
such
that19
20

defines a contraction with a unique fixed point.
For our problem, take
as
and
as
, and define
![[ ]
{Ez}(at) = Et Γ 1-t+1ρz(atRt+1 + ξt+1) .](BufferStockTheory340x.png)
Using this, we introduce the mapping
,21
We can show that our operator
satisfies the conditions that Boyd requires of his
operator
, if we impose two restrictions on parameter values. The first restriction is the
WRIC necessary for convergence of the maximal MPC, equation (35) above. A more serious
restriction is the utility-compensated Finite Value of Autarky condition, equation (29).
(We discuss the interpretation of these restrictions in detail in section 2.11 below.)
Imposing these restrictions, we are now in position to state the central theorem of the
paper.
The proof is cumbersome, and therefore relegated to appendix D. Given that the value function converges, appendix D.3 shows that the consumption functions converge.
This section shows that a related problem commonly considered in the literature (e.g. with a
simpler income process by Deaton (1991)), with a liquidity constraint and a positive minimum
value of income, is the limit of the problem considered here as the probability
of the
zero-income event approaches zero.
Formally, suppose we change the description of the problem by making the following two assumptions:
and we designate the solution to this consumer’s problem
. We will henceforth refer to this
as the problem of the ‘restrained’ consumer (and, to avoid a common confusion, we will refer
to the consumer as ‘constrained’ only in circumstances when the constraint is actually
binding).
Redesignate the consumption function that emerges from our original problem for a given
fixed
as
where we separate the arguments by a semicolon to distinguish between
, which is a state variable, and
, which is not. The proposition we wish to demonstrate
is

We will first examine the problem in period
, then argue that the desired result
propagates to earlier periods. For simplicity, suppose that the interest, growth, and
time-preference factors are
and there are no permanent shocks,
; the results below are easily generalized to the full-fledged version of the
problem.
The solution to the restrained consumer’s optimization problem can be obtained as
follows. Assuming that the consumer’s behavior in period
is given by
(in
practice, this will be
), consider the unrestrained optimization problem

As usual, the envelope theorem tells us that
so the expected marginal
value of ending period
with assets
can be defined as

therefore answers the question “With what level of assets would the restrained
consumer like to end period
if the constraint
did not exist?” (Note that
the restrained consumer’s income process remains different from the process for the
unrestrained consumer so long as
.) The restrained consumer’s actual asset position
will be
![*
`aT-1(m ) = max [0,`aT- 1(m )],](BufferStockTheory374x.png)

at which the constraint makes the transition between binding and
non-binding in period
.
Analogously to (42), defining
the Euler equation for the original consumer’s problem implies with solution
. Now note that for any fixed
,
. Since
the LHS of (42) and (44) are identical, this means that
. That
is, for any fixed value of
such that the consumer subject to the restraint would
voluntarily choose to end the period with positive assets, the level of end-of-period assets for
the unrestrained consumer approaches the level for the restrained consumer as
. With
the same
and the same
, the consumers must have the same
, so the consumption
functions are identical in the limit.
Now consider values
for which the restrained consumer is constrained. It is
obvious that the baseline consumer will never choose
because the first term in (43) is
, while
is finite (the marginal value of end-of-period assets
approaches infinity as assets approach zero, but the marginal utility of consumption has a
finite limit for
). The subtler question is whether it is possible to rule out strictly
positive
for the unrestrained consumer.
The answer is yes. Suppose, for some
that the unrestrained consumer is
considering ending the period with any positive amount of assets
. For
any such
we have that
. But by assumption we are
considering a set of circumstances in which
, and we showed earlier that
. So, having assumed
, we have proven that the
consumer would optimally choose
, which is a contradiction. A similar argument holds
for
.
These arguments demonstrate that for any
,
which is the period
version of (41). But given equality of the period
consumption functions, backwards recursion of the same arguments demonstrates that the
limiting consumption functions in previous periods are also identical to the constrained
function.
Note finally that another intuitive confirmation of the equivalence between the two problems is that our formula (36) for the maximal marginal propensity to consume satisfies

In the perfect foresight unconstrained problem (section 2.4.2), the RIC was required for
existence of a nondegenerate solution. It is surprising, therefore, that in the presence of
uncertainty, the RIC is neither necessary nor sufficient for a nondegenerate solution to
exist.
We thus begin our discussion by asking what features the problem must exhibit (given the
FVAC) if the RIC fails (that is,
:
and
(because we have assumed
), this can hold only
if
; that is, given the FVAC, the RIC can fail only if human wealth is
unbounded. Unbounded human wealth is permitted here, as in the perfect foresight
liquidity constrained problem. But, from equation (37), an implication of
" class="math" > " class="oalign" >
is that
. Thus, interestingly, the presence of uncertainty both
permits unlimited human wealth and at the same time prevents that unlimited
wealth from resulting in infinite consumption. That is, in the presence of uncertainty,
pathological patience (which in the perfect foresight model with finite wealth results
in consumption of zero) plus infinite human wealth (which the perfect foresight
model rules out because it leads to infinite consumption) combine here to yield a
unique finite limiting level of consumption for any finite value of
. Note the close
parallel to the conclusion in the perfect foresight liquidity constrained model in the
PF-GIC,
" class="math" > " class="oalign" >
case (for detailed analysis of this case see the appendix).
There, too, the tension between infinite human wealth and pathological patience
was resolved with a nondegenerate consumption function whose limiting MPC was
zero.
The ‘weakness’ of the additional requirement for contraction, the weak RIC, can be seen by asking ‘under what circumstances would the FVAC hold but the WRIC fail?’ Algebraically, the requirement is
If there were no conceivable parameter values that could satisfy both of these inequalities,
the WRIC would have no force; it would be redundant. And if we require
, the WRIC
is indeed redundant because now
, so that the RIC (and WRIC) must
hold.
But neither theory nor evidence demands that we assume
. We can therefore
approach the question of the WRIC’s relevance by asking just how low
must be for the
condition to be relevant. Suppose for illustration that
,
,
and
. In that case (46) reduces to

by assumption, the binding requirement is that 
we would need
(that is, a perpetual riskfree rate of
return of worse than -90 percent a year) in order for the WRIC to bind. Thus, the relevance of
the WRIC is indeed “Weak.”
Perhaps the best way of thinking about this is to note that the space of parameter values for
which the WRIC is relevant shrinks out of existence as
, which section 2.10 showed
was the precise limiting condition under which behavior becomes arbitrarily close to the
liquidity constrained solution (in the absence of other risks). On the other hand, when
,
the consumer has no noncapital income (so that the FHWC holds) and with
the
WRIC is identical to the RIC; but the RIC is the only condition required for a solution to
exist for a perfect foresight consumer with no noncapital income. Thus the WRIC forms a sort
of ‘bridge’ between the liquidity constrained and the unconstrained problems as
moves
from 0 to 1.
If both the GIC and the RIC hold, the arguments above establish that the limiting
consumption function asymptotes to the consumption function for the perfect foresight
unconstrained function. The more interesting case is where the GIC fails.
A solution that satisfies the combination FVAC and
" class="math" > " class="oalign" > is depicted in Figure
2. The consumption function is shown along with the
locus that
identifies the ‘sustainable’ level of spending at which
is expected to remain
unchanged. The diagram suggests a fact that is confirmed by deeper analysis:
Under the depicted configuration of parameter values (see the software archive for
details), the consumption function never reaches the
locus; indeed,
when the RIC holds but the GIC does not, the consumption function’s limiting
slope
is shallower than that of the sustainable consumption locus
,22
so the gap between the two actually increases with
in the limit. That is, although a
nondegenerate consumption function exists, a target level of
does not (or, rather, the
target is
), because no matter how wealthy a consumer becomes, he will always spend
less than the amount that would keep
stable (in expectation).
For the reader’s convenience, Tables 2 and 3 present a summary of the connections between the various conditions in the presence and the absence of uncertainty.
| Perfect Foresight Versions | Uncertainty Versions |
| Finite Human Wealth Condition (FHWC)
| |
| |
|
The
growth
factor
for
permanent
income
must
be
smaller
than
the
discounting
factor
,
for
human
wealth
to
be
finite. |
The
model’s
risks
are
mean-preserving
spreads,
so
the
PDV
of
future
income
is
unchanged
by
their
introduction. |
| Absolute Impatience Condition (AIC)
| |
| |
|
The
unconstrained
consumer
is
sufficiently
impatient
that
the
level
of
consumption
will
be
declining
over
time: |
If
wealth
is
large
enough,
the
expectation
of
consumption
next
period
will
be
smaller
than
this
period’s
consumption: |
| |
| Return Impatience Conditions
| |
| Return Impatience Condition (RIC) | Weak RIC (WRIC)
|
| |
|
The
growth
factor
for
consumption
must
be
smaller
than
the
discounting
factor
,
so
that
the
PDV
of
current
and
future
consumption
will
be
finite: |
If
the
probability
of
the
zero-income
event
is
then
income
is
always
zero
and
the
condition
becomes
identical
to
the
RIC.
Otherwise,
weaker. |
| |
| Growth Impatience Conditions
| |
| PF-GIC | GIC
|
| |
|
Guarantees
that
for
an
unconstrained
consumer,
the
ratio
of
consumption
to
permanent
income
will
fall
over
time.
For
a
constrained
consumer,
guarantees
the
constraint
will
eventually
be
binding. |
By
Jensen’s
inequality,
stronger
than
the
PF-GIC.
Ensures
consumers
will
not
expect
to
accumulate
unboundedly. |
|
|
| Finite Value of Autarky Conditions
| |
| PF-FVAC | FVAC
|
| |
equivalently | |
|
The
discounted
utility
of
constrained
consumers
who
spend
their
permanent
income
each
period
should
be
finite. |
By
Jensen’s
inequality,
stronger
than
the
PF-FVAC
because
for
and
nondegenerate
,
. |
Solution
| Model | Conditions | Comments
|
| PF Unconstrained | RIC, FHWC | RIC ; FHWC |
RIC prevents |
||
FHWC prevents |
||
| PF Constrained | PF-GIC | If RIC, |
If " class="math" > " class="oalign" >, |
||
| Buffer Stock Model | FVAC, WRIC | FHWC ![]() |
" class="math" > " class="oalign" >+RIC |
||
" class="math" > " class="oalign" >+ " class="math" > " class="oalign" > |
||
| GIC guarantees finite target wealth ratio | ||
| FVAC is stronger than PF-FVAC | ||
| WRIC is weaker than RIC | ||
For feasible
, limiting consumption function defines unique value of
satisfying
.
RIC, FHWC are necessary as well as
sufficient.
Solution also exists for
" class="math" > " class="oalign" > and RIC, but is identical to the unconstrained model’s solution for feasible
.
Figures 3 and 4a,b capture the main properties of the converged consumption rule when the RIC, GIC, and
FHWC all hold.23
Figure 3 shows the expected consumption growth factor
for a consumer
behaving according to the converged consumption rule, while Figures 4a,b illustrate
theoretical bounds for the consumption function and the marginal propensity to
consume.
Five features of behavior are captured, or suggested, by the figures. First, as
the expected
consumption growth factor goes to
, indicated by the lower bound in Figure 3, and the marginal
propensity to consume approaches
(Figure 4), the same as the perfect foresight
MPC.24
Second, as
the consumption growth factor approaches
(Figure 3) and the
MPC approaches
(Figure 4). Third (Figure 3), there is a target
cash-on-hand-to-income ratio
such that if
then
, and (as
indicated by the arrows of motion on the
curve), the model’s dynamics are
‘stable’ around the target in the sense that if
then cash-on-hand will rise (in
expectation), while if
, it will fall (in expectation). Fourth (Figure 3), at the
target
, the expected rate of growth of consumption is slightly less than the
expected growth rate of permanent noncapital income. The final proposition suggested
by Figure 3 is that the expected consumption growth factor is declining in the
level of the cash-on-hand ratio
. This turns out to be true in the absence of
permanent shocks, but in extreme cases it can be false if permanent shocks are
present.25

Define

); clearly
, since allowing the possibility of future noncapital income cannot reduce current
consumption.26
Assuming the FHWC holds, the infinite horizon perfect foresight solution (18) constitutes
an upper bound on consumption in the presence of uncertainty, since Carroll and
Kimball (1996) show that the introduction of uncertainty strictly decreases the level of
consumption at any
.
Thus, we can write
But
, and the continuous differentiability and strict concavity of
therefore implies
![]() |
because any other fixed limit would eventually lead to a level of consumption either exceeding
or lower than
.
Figure 4 confirms these limits visually. The top plot shows the converged consumption function along with its upper and lower bounds, while the lower plot shows the marginal propensity to consume.
Next we establish the limit of the expected consumption growth factor as
:
![lim Et [ct+1∕ct] = lim Et[Γ t+1ct+1∕ct].
mt→∞ mt→ ∞](BufferStockTheory553x.png)
But
![Et [Γ t+1c ∕c¯t] ≤ Et[Γ t+1ct+1∕ct] ≤ Et[Γ t+1¯ct+1∕c-]
t+1 t](BufferStockTheory554x.png)
![]() |
while

27
and
which goes to zero as
goes to infinity.
Hence we have
![]() |
so as cash goes to infinity, consumption growth approaches its value
in the perfect
foresight model.
This argument applies equally well to the problem of the restrained consumer, because as
approaches infinity the constraint becomes irrelevant (assuming the FHWC
holds).

Now consider the limits of behavior as
gets arbitrarily small.
Equation (36) shows that the limiting value of
is

Defining
as before we have

Now using the continuous differentiability of the consumption function along with L’Hôpital’s rule, we have

Figure 4 confirms that the numerical solution method obtains this limit for the MPC as
approaches zero.
For consumption growth, we have
![[ ( ) ] [( ) ]
c(mt+1 ) c(Rt+1a (mt ) + ξt+1)
lim Et -------- Γ t+1 > lim Et -------------------- Γ t+1
mt↓0 c(mt ) mt↓0 [( ¯κmt ) ]
c(Rt+1a-(mt-))
= ℘ lmimt↓0Et ¯κmt Γ t+1
[( ) ]
+ ℘ lim Et c(Rt+1a-(mt-) +-θt+1∕/℘-) Γ t+1
/ mt↓0 κ¯mt
[( c(θ ∕℘ )) ]
> /℘ lim Et ---t+1-/--- Γ t+1
mt↓0 ¯κmt
= ∞](BufferStockTheory572x.png)
is
positive, and the last line follows because the minimum possible realization of
is
so the minimum possible value of expected next-period consumption is
positive.28
Define the target cash-on-hand-to-income ratio
as the value of
such that
![]() | (47) |
where the
accent is meant to invoke the fact that this is the value that other
’s ‘point
to.’
We prove existence by arguing that
is continuous on
, and takes on
values both above and below 1, so that it must equal 1 somewhere by the intermediate value
theorem.
Specifically, the same logic used in section 3.2 shows that
.
The limit as
goes to infinity is
![[ R a (m ) + ξ ]
lim Et[mt+1 ∕mt ] = lim Et --t+1----t-----t+1-
mt→ ∞ mt→ ∞ mt
= Et[(R∕Γ t+1)ÞÞÞR ]
= Et[ÞÞÞ∕ Γ t+1]
< 1](BufferStockTheory586x.png)
Stability means that in a local neighborhood of
, values of
above
will result in a
smaller ratio of
than at
. That is, if
then
. This
will be true if
. But ![( ) [( ) ]
-d-- -d--
dmt Et[mt+1 ∕mt ] = Et dmt [Rt+1(1 - c(mt )∕mt ) + ξt+1∕mt ]
[ ′ ]
= Et Rt+1-(c(mt)---c(mt-)mt)---ξt+1
m2t](BufferStockTheory596x.png)
as the expectation of the
numerator,
![]() | (48) |
The target level of market resources
satisfies
At the target, equation (48) is
Substituting for the first term in this expression using (49) gives
![ζζζ(ˇm ) = 1 + (R¯ - 1)ˇm - ¯Rc ′(ˇm )ˇm - 1
= mˇ (¯R - 1 - R¯c ′(ˇm ))
( ′ )
= mˇ ¯R (1 - c(ˇm )) - 1
< mˇ (¯R (1 - (1 - R -1(Rβ )1∕ρ)) - 1)
( )
= mˇ ¯R ÞÞÞR - 1
( )
| |
= mˇ ( Et[ÞÞÞ∕Γ-t+1]- 1)
◟<1 fr◝o◜m (28◞)
< 0](BufferStockTheory602x.png)
which is an
implication of the concavity of the consumption function.
We have now proven that some target
must exist, and that at any such
the solution
is stable. Nothing so far, however, rules out the possibility that there will be multiple values of
that satisfy the definition (47) of a target.
Multiple targets can be ruled out as follows. Suppose there exist multiple targets; these can
be arranged in ascending order and indexed by an integer superscript, so that the target with
the smallest value is, e.g.,
. The argument just completed implies that since
is continuously differentiable there must exist some small
such that
for
. (Continuous differentiability of
follows from the continuous
differentiability of
.)
Now assume there exists a second value of
satisfying the definition of a target,
.
Since
is continuous, it must be approaching 1 from below as
, since
by the intermediate value theorem it could not have gone above 1 between
and
without passing through 1, and by the definition of
it cannot have passed through 1
before reaching
. But saying that
is approaching 1 from below as
implies that
![( )
-d--
dmt Et[mt+1 ∕mt ] > 0 (50)](BufferStockTheory624x.png)
. However, we just showed above that, under our assumption that the GIC
holds, precisely the opposite of equation (50) must hold for any
that satisfies the
definition of a target. Thus, assuming the existence of more than one target implies a
contradiction.
The foregoing arguments rely on the continuous differentiability of
, so the arguments
do not directly go through for the restrained consumer’s problem in which the existence of
liquidity constraints can lead to discrete changes in the slope
at particular values of
. But we can use the fact that the restrained model is the limit of the baseline model as
to conclude that there is likely a unique target cash level even in the restrained
model.
If consumers are sufficiently impatient, the limiting target level in the restrained model will
be
. That is, if a consumer starting with
will save nothing,
, then the target level of
in the restrained model will be 1; if a consumer with
would choose to save something, then the target level of cash-on-hand will be greater
than the expected level of income.
Is Less than Expected Permanent
Income GrowthIn Figure 3 the intersection of the target cash-on-hand ratio locus at
with the
expected consumption growth curve lies below the intersection with the horizontal line
representing the growth rate of expected permanent income. This can be proven as
follows.
Strict concavity of the consumption function implies that if
then
and
it is clear that cov
which
implies that the entire term added to
in (51) is negative, as required.
(or Is It?)Figure 3 depicts the expected consumption growth factor as a strictly declining function of the cash-on-hand ratio. To investigate this, define

![[ ( )]
c′(mt+1)Rt+1a ′(mt)c(mt ) - c(mt+1 )c′(mt )
Et Γ t+1 -----------------------2----------------- < 0. (52)
c(mt )](BufferStockTheory647x.png)
Henceforth indicating appropriate arguments by the corresponding subscript
(e.g.
), since
, the portion of the LHS of equation (52) in
brackets can be manipulated to yield
Now differentiate the Euler equation with respect to
:
we can see from (54) that (52) is equivalent to 



The latter proposition is obviously true under our assumption
. The former will be
true if

The two shocks cause two kinds of variation in
. Variations due to
satisfy the
proposition, since a higher draw of
both reduces
and reduces the marginal
propensity to consume. However, permanent shocks have conflicting effects. On the one hand,
a higher draw of
will reduce
, thus increasing both
and
. On the
other hand, the
term is multiplied by
, so the effect of a higher
could be
to decrease the first term in the covariance, leading to a negative covariance with the
second term. (Analogously, a lower permanent shock
can also lead a negative
correlation.)
This section examines the behavior of large collections of buffer-stock consumers with identical parameter values. Such a collection can be thought of as either a subset of the population within a single country (say, members of a given education or occupation group), or as the whole population in a small open economy. We will continue to take the aggregate interest rate as exogenous and constant. It is also possible, and only slightly more difficult, to solve for the steady-state of a closed-economy version of the model where the interest rate is endogenous.
Formally, we assume a continuum of ex ante identical households on the unit interval, with constant
total mass normalized to one and indexed by
, all behaving according to the model specified
above.29
Szeidl (2012) proves that such a population will be characterized by an invariant distribution
of
that induces invariant distributions for
and
; designate these
,
, and
.30
Szeidl’s proof, however, does not yield any sense of how quickly convergence occurs, which in principle depends on all of the parameters of the model as well as the initial conditions. To build intuition, Figure 5 supplies an example in which a population begins with a particularly simple distribution that is far from the invariant one:

The figure plots the distributions of
(for technical reasons, this
is slightly better than plotting
) at the ends of 1, 4, 10, and 40
periods.32
The figure illustrates the fact that, under these parameter values, convergence to the invariant distribution has largely been accomplished within 10 periods. By 40 periods, the distribution is indistinguishable from the invariant distribution.
It is useful to define the operator
which yields the mean value of its argument in the
population, as distinct from the expectations operator
which represents beliefs about
the future.
An economist with a microeconomic dataset could calculate the average growth rate of idiosyncratic consumption, and would find
![M [Δ log ct+1] = M [log ct+1pppt+1 - log ctpppt]
= M [log pppt+1 - log pppt + log ct+1 - log ct]
= M [log ppp - log ppp ] + M [log c - logc ]
2 t+1 t t+1 t
= γ - σψ∕2,](BufferStockTheory693x.png)
and the last equality follows because the invariance of
means that
.33
Attanasio and Weber (1995) point out that concavity of the consumption function (or other nonlinearities) can imply that it is quantitatively important to distinguish between the growth rate of average consumption and the average growth rate of consumption.34 We have just examined the average growth rate; we now examine the growth rate of the average.
Using capital letters for aggregate variables, the growth factor for aggregate income is given by:
![Yt+1∕Yt = M [ξt+1Γ ψt+1pppt]∕M [ppptξt]
= Γ](BufferStockTheory697x.png)
and
.
Aggregate assets are:
where
designates the mean level of permanent income across all individuals, and we are
assuming that
was distributed according to the invariant distribution with a mean value
of
Since permanent income grows at mean rate
while the distribution of
is
invariant, if we normalize
to one we will similarly have for any period

Unfortunately, Szeidl (2012)’s proof of the invariance of
does not yield the information
about how the cross-sectional covariance between
and
evolves required to show that the
covariance term grows by a factor smaller than
; if that were true, its relative size would
shrink to zero over time. (A proof that the covariance shrinks fast enough would mean that
the term could be neglected).
The desired result can be proven if there are no permanent shocks; see appendix E for that proof, along with a discussion of the characteristics of a covariance term that prevents proof in the general case with both transitory and permanent shocks.
A wide range of simulation experiments confirms that the role of that covariance term is
more an irritating theoretical curiosum than an important practical consideration. An example
is given in Figure 6, which plots
for the economy whose converging CDFs were
depicted in Figure 5. After the 40 periods of simulation that generated CDFs plotted in 5, we
conduct an experiment designed to flush out the role of the annoying covariance term: We
reset the level of permanent income to be identical for all consumers (‘the revolution’):

that they would have had in the absence of the revolution. This leaves us with
the same distribution of
as before the revolution, but no covariance between
and
.
The effect on aggregate consumption growth of even such an extreme revolution in
covariance is small, and dissipates immediately (no effect is visible after the period of
revolution itself). This experiment is representative of many that suggest that the practical
effects of time-variaton in the covariance between
and
are negligible.
This paper provides theoretical foundations for many characteristics of buffer stock saving models that have heretofore been observed in simulations but not proven. Perhaps the most important such proposition is the existence of a target cash-to-permanent-income ratio toward which actual cash will tend.
Another contribution is provision a set of tools for numerical solution and simulation (available on the author’s web page) that confirm and illustrate the theoretical propositions. These programs demonstrate how the incorporation of the paper’s theoretical results can make numerical solution algorithms more efficient and simpler. A goal of the paper has been to make these tools accessible and easy to use while incorporating the full rigor of the theoretical results in the structure.
This appendix taxonomizes the characteristics of the limiting consumption function
under perfect foresight in the presence of a liquidity constraint requiring
under various
conditions. Results are summarized in table 4.
| Name | Condition | Outcome/Comments | ||
" class="math" > " class="oalign" > | | | | Constraint never binds for |
| RIC | | | | FHWC holds ( ) |
for |
||||
" class="math" > " class="oalign" > | | | | is degenerate |
| PF-GIC | | | | Constraint binds in finite time for any |
| RIC | | | | FHWC may or may not hold |
|
||||
|
||||
" class="math" > " class="oalign" > | | | " class="math" > " class="oalign" > |
|
|
||||
" class="math" > " class="oalign" > and RIC
both hold, while the fourth row indicates that when the PF-GIC and the RIC both fail, the consumption function is degenerate; the next row
indicates that whenever the PF-GIC holds, the constraint will bind in finite time.
A consumer is ‘growth patient’ if the perfect foresight growth impatience condition
fails (
" class="math" > " class="oalign" >,
). Under
" class="math" > " class="oalign" > the constraint does not bind at
the lowest feasible value of
because
implies that spending
everything today (setting
) produces lower marginal utility than is
obtainable by reallocating a marginal unit of resources to the next period at return
:35
Similar logic shows that under these circumstances the constraint will never bind for an
unconstrained consumer with a finite horizon of
periods, so such a consumer’s
consumption function will be the same as for the unconstrained case examined in the main
text.
If the RIC fails (
) while the finite human wealth condition holds, the
limiting value of this consumption function as
is the degenerate function

If the RIC fails and the FHWC fails, human wealth limits to
so the
consumption function limits to either
or
depending on the
relative speeds with which the MPC approaches zero and human wealth approaches
.36
Thus, the requirement that the consumption function be nondegenerate implies that for a
consumer satisfying
" class="math" > " class="oalign" > we must impose the RIC (and the FHWC can be shown to
be a consequence of
" class="math" > " class="oalign" > and RIC). In this case, the consumer’s optimal behavior is
easy to describe. We can calculate the point at which the unconstrained consumer would
choose
from (18):

.37
For
the unconstrained consumer would choose to consume more
than
; for such
, the constrained consumer is obliged to choose
.38
For any
the constraint will never bind and the consumer will choose to spend the
same amount as the unconstrained consumer,
.
Imposition of the PF-GIC reverses the inequality in (55)-(57), and thus reverses
the conclusion: A consumer who starts with
will desire to consume more
than 1. Such a consumer will be constrained, not only in period
, but perpetually
thereafter.
Now define
as the
such that an unconstrained consumer holding
would
behave so as to arrive in period
with
(with
trivially equal to 0); for
example, a consumer with
was on the ‘cusp’ of being constrained in period
:
Had
been infinitesimally smaller, the constraint would have been binding (because the
consumer would have desired, but been unable, to enter period
with negative,
not zero,
). Given the PF-GIC, the constraint certainly binds in period
(and
thereafter) with resources of
: The consumer cannot spend more
(because constrained), and will not choose to spend less (because impatient), than
.
We can construct the entire ‘prehistory’ of this consumer leading up to
as follows.
Maintaining the assumption that the constraint has never bound in the past,
must have
been growing according to
, so consumption
periods in the past must have been
The PDV of consumption from
until
can thus be computed as
and
(the relevant time horizon,
because from
onward the consumer will be constrained and unable to access post-
income) is 

such that the consumer with
would
unconstrainedly plan (in period
) to arrive in period
with
:
Defining
, consider the function
defined by linearly connecting the
points
for integer values of
(and setting
for
). This
function will return, for any value of
, the optimal value of
for a liquidity constrained
consumer with an infinite horizon. The function is piecewise linear with ‘kink points’ where
the slope discretely changes, because for infinitesimal
the MPC of a consumer with assets
is discretely higher than for a consumer with assets
because the
latter consumer will spread a marginal dollar over more periods before exhausting
it.
In order for a unique consumption function to be defined by this sequence (65) for the entire
domain of positive real values of
, we need
to become arbitrarily large with
. That is,
we need
The FHWC requires
, in which case the second term in (65) limits to a constant as
, and (66) reduces to a requirement that

, this will hold iff the RIC holds,
. But given that the
FHWC
holds, the PF-GIC is stronger (harder to satisfy) than the RIC; thus,
FHWC and the PF-GIC together imply the RIC, and so a well-defined solution exists.
Furthermore, in the limit as
approaches infinity, the difference between the limiting
constrained consumption function and the unconstrained consumption function becomes
vanishingly small, because as the date at which the constraint binds becomes arbitrarily
distant, the effect of that constraint on current behavior shrinks to nothing. That is,

If the FHWC fails, matters are a bit more complex. Given failure of FHWC, (66) requires
If RIC Holds. When the RIC holds, rearranging (68) gives




If RIC Fails. Consider now the
" class="math" > " class="oalign" > case,
. In this case the constant
multiplying
in (68) will be positive if

. The
combined limit will be
if the term involving
goes to
faster than the term
involving
goes to
; that is, if 
" class="math" > " class="oalign" > implies a limiting MPC of zero, 
. (Figure 7 presents an example for
,
,
,
).
" class="math" > " class="oalign" > and
" class="math" > " class="oalign" >
We can summarize as follows. Given that the PF-GIC holds, the interesting question is
whether the FHWC holds. If so, the RIC automatically holds, and the solution limits into the
solution to the unconstrained problem as
. But even if the FHWC fails, the problem
has a well-defined solution, whether or not the RIC holds.
To show that (??) defines a sequence of continuously differentiable strictly increasing concave
functions
, we start with a definition. We will say that a function
is
‘nice’ if it satisfies
is well-defined iff
is strictly increasing
is strictly concave
is
(its first three derivatives exist)
.
(Notice that an implication of niceness is that
)
Assume that some
is nice. Our objective is to show that this implies
is also nice;
this is sufficient to establish that
is nice by induction for all
because
and
is nice by inspection.
Now define an end-of-period value function
as
![]() | (72) |
Since there is a positive probability that
will attain its minimum of zero and since
, it is clear that
and
. So
is
well-defined iff
; it is similarly straightforward to show the other properties required for
to be nice. (See Hiraguchi (2003).)
Next define
as
![]() | (73) |
which is
since
and
are both
and note that our problem’s value function
defined in (??) can be written as

is well-defined if and only if
. Furthermore,
,
,
, and
. It follows that the
defined by

![]() | (76) |
Since both
and
are strictly concave, both
and
are
strictly increasing. Since both
and
are three times continuously differentiable, using
we can conclude that
is continuously differentiable and

Similarly we can easily show that
is twice continuously differentiable (as is
)
(See Appendix C.) This implies that
is nice, since
.
is Twice Continuously DifferentiableFirst we show that
is
Define
as
. Since
and

and
are continuous and increasing,
and
are satisfied. Then
for
sufficiently small
. Hence we obtain a well-defined equation:
![]() |
This implies that the right-derivative,
is well-defined and
![]() |
Similarly we can show that
, which means
exists. Since
is
,
exists and is continuous.
is differentiable because
is
,
is
and
.
is given by
![]() | (78) |
Since
is continuous,
is also continuous.
Is a Contraction MappingWe must show that our operator
satisfies all of Boyd’s conditions.
Boyd’s operator
maps from
to
A preliminary requirement is
therefore that
be continuous for any
bounded
,
. This is not
difficult to show; see Hiraguchi (2003).
Consider condition 1). For this problem,
so
implies
by
inspection.40
Condition 2) requires that
. By definition,
![]() |
the solution to which is patently
. Thus, condition 2) will hold if
is
-bounded. We use the bounding function

whose value will be determined in the course of the proof. Under this
definition of
,
is clearly
-bounded.
Finally, we turn to condition 3),
The
proof will be more compact if we define
and
as the consumption and assets
functions41
associated with
and
and
as the functions associated with
; using this
notation, condition 3) can be rewritten

Now note that if we force the
consumer to consume the amount that is optimal for the
consumer, value for the
consumer must decline (at least weakly). That is,

and defining
, this condition is ![1-ρ 1-ρ 1- ρ 1-ρ
β Et[Γt+1(ˆatRt+1 + ξt+1) ] - m t < η(1 - β◟-Et◝Γ◜-t+1◞)
= ℶ](BufferStockTheory1035x.png)
can be rewritten as: ![[ 1-ρ 1-ρ] 1- ρ
η > β-Et--Γt+1(ˆatRt+1-+-ξt+1)-------m-t--. (80)
1 - ℶ](BufferStockTheory1037x.png)
But since
is an arbitrary constant that we can pick, the proof thus reduces to showing
that the numerator of (80) is bounded from above:
We can thus conclude that equation (80) will certainly hold for any:

The proof that
defines a contraction mapping under the conditions (35) and (29) is now
complete.
and 
In defining our operator
we made the restriction
. However, in
the discussion of the consumption function bounds, we showed only (in (38)) that
. (The difference is in the presence or absence of time subscripts on the
MPC’s.) We have therefore not proven (yet) that the sequence of value functions (??) defines
a contraction mapping.
Fortunately, the proof of that proposition is identical to the proof in 2.9, except that we
must replace
with
and the WRIC must be replaced by a stronger condition. The
place where these conditions have force is in the step at (81). Consideration of the prior two
equations reveals that a sufficient stronger condition is

. For small values of
this expression can be further
simplified using
so that it becomes 
is plainly easy to satisfy.
The upshot is that under these slightly stronger conditions the value functions for the original
problem define a contraction mapping with a unique
. But since
and
, it must be the case that the
toward which these
’s are
converging is the same
that was the endpoint of the contraction defined by our
operator
. Thus, under our slightly stronger (but still quite weak) conditions, not only do
the value functions defined by (??) converge, they converge to the same unique
defined by
.42
in Euclidian SpaceBoyd’s theorem shows that
defines a contraction mapping in a
-bounded space. We now
show that
also defines a contraction mapping in Euclidian space.
Since
,
![]() | (83) |
On the other hand,
and
because
and
are in
. It follows that
![]() | (84) |
Then we obtain
![]() | (85) |
Since
,
. On the other hand,
means
, in other words,
. Inductively one gets
. This means that
is a decreasing sequence,
bounded below by
.

Given the proof that the value functions converge, we now show the pointwise convergence of
consumption functions
.
We start by showing that
![]() | (86) |
is uniquely determined. We show this by contradiction. Suppose there exist
and
that both attain the supremum for some
, with mean
.
satisfies
![]() | (87) |
where
and
.
is concave for concave
. Since
the space of continuous and concave functions is closed,
is also concave and
satisfies
![]() | (88) |
On the other hand,
Then one gets
![]() | (89) |
Since
is a feasible choice for
, the LHS of this equation cannot be a maximum, which
contradicts the definition.
Using uniqueness of
we can now show
![]() | (90) |
Suppose this does not hold for some
. In this case,
has a
subsequence
that satisfies
and
. Now
define
.
because
.
Because
and
there exist
satisfying
and
. It follows that
and the
convergence is uniform on
. (Uniform convergence is obtained from Dini’s
theorem.43 )
Hence for any
, there exists an
such that
![[ 1-ρ | * * * * |]
β ET -n ΓT-n+1 |vT-n+1(mT - n+1(m ,cT-n+1)) - v(mT -n+1(m ,cT-n+1 ))| < δ](BufferStockTheory1128x.png)
. It follows that if we define
![]() | (91) |
then
satisfies
![]() | (92) |
On the other hand, there exists an
such that
![]() | (93) |
because
is uniformly continuous on
.
and
![]() | (94) |
This implies
![]() | (95) |
From (92) and (95), we obtain
and this implies
. This implies that
is not uniquely determined, which is a
contradiction.
Thus, the consumption functions must converge.
The text asserted that in the absence of permanent shocks it is possible to prove that the growth factor for aggregate consumption approaches that for aggregate permanent income. This section establishes that result.
Suppose the population starts in period
with an arbitrary value for
.
Then if
is the invariant mean level of
we can define a ‘mean MPS away from
’
function
,
is a constant at
we can write 

But since
,
![]() |
and for the version of the model with no permanent shocks the GIC says that
which
implies

This means that from any arbitrary starting value, the relative size of the covariance term
shrinks to zero over time (compared to the
term which is growing steadily by the factor
). Thus,
.
This logic unfortunately does not go through when there are permanent shocks, because the
terms are not independent of the permanent income shocks.
To see the problem clearly, define
and consider a first order Taylor
expansion of
around

The problem comes from the
term. The concavity of the consumption function implies
convexity of the
function, so this term is strictly positive but we have no theory to place
bounds on its size as we do for its level
. We cannot rule out by theory that a positive shock
to permanent income (which has a negative effect on
) could have an unboundedly
positive effect on
(as for instance if it pushes the consumer arbitrarily close to the
self-imposed liquidity constraint).
The model is solved using an extension of the method of endogenous gridpoints
(Carroll (2016)): A grid of possible values of end-of-period assets
is defined (aVec in
the software), and at these points, marginal end-of-period-
value is computed as
the discounted next-period expected marginal utility of consumption (which the
Envelope theorem says matches expected marginal value). The results are then
used to identify the corresponding levels of consumption at the beginning of the
period:44
The dynamic budget constraint can then be used to generate the corresponding
’s:

An approximation to the consumption function could be constructed by linear interpolation
between the
points. But a vastly more accurate approximation can be made (for a
given number of gridpoints) if the interpolation is constructed so that it also matches the
marginal propensity to consume at the gridpoints. Differentiating (96) with respect to
(and
dropping policy function arguments for simplicity) yields a marginal propensity to have
consumed
at each gridpoint:
,

, yields the MPC from
and
we call the vector of MPC’s at the
gridpoints
.
For any set of parameter values that satisfy the conditions required for convergence, the
problem can be solved by setting the terminal consumption function to
and
constructing
by time iteration (a method that will converge to
by
standard theorems). But
is very far from the final converged consumption rule
,45
and thus many periods of iteration will likely be required to obtain a candidate rule that even
remotely resembles the converged function.
A natural alternative choice for the terminal consumption rule is the solution to the perfect
foresight liquidity constrained problem, to which the model’s solution converges (under
specified parametric restrictions) as all forms of uncertainty approach zero (as discussed in the
main text). But a difficulty with this idea is that the perfect foresight liquidity constrained
solution is ‘kinked:’ The slope of the consumption function changes discretely at the
points
. This is a practical problem because it rules out the use of
derivatives of the consumption function in the approximate representation of
,
thereby preventing the enormous increase in efficiency obtainable from a higher-order
approximation.
Our solution is simple: The formulae in appendix A that identify kink points on
for
integer values of
(e.g.,
) are continuous functions of
; the conclusion that
is piecewise linear between the kink points does not require that the terminal
consumption rule (from which time iteration proceeds) also be piecewise linear. Thus, for
values
we can construct a smooth function
that matches the true perfect
foresight liquidity constrained consumption function at the set of points corresponding to
integer periods in the future, but satisfies the (continuous, and greater at non-kink points)
consumption rule defined from the appendix’s formulas by noninteger values of
at other
points.46
This strategy generates a smooth limiting consumption function – except at the remaining
kink point defined by
. Below this point, the solution must match
because the constraint is binding. At
the MPC discretely drops (that is,
while
).
Such a kink point causes substantial problems for numerical solution methods (like the one we use, described below) that rely upon the smoothness of the limiting consumption function.
Our solution is to use, as the terminal consumption rule, a function that is identical to the
(smooth) continuous consumption rule
above some
, but to replace
between
and
with the unique polynomial function
that satisfies the
following criteria:

where
is chosen judgmentally in a way calculated to generate a good compromise between
smoothness of the limiting consumption function
and fidelity of that function to the
(see the actual code for details).
We thus define the terminal function as47
![]() | (98) |
Since the precautionary motive implies that in the presence of uncertainty the optimal level
of consumption is below the level that is optimal without uncertainty, and since
, implicitly defining
(so that
), we can construct
and
(since
for
).
This function turns out to be much better behaved (as a numerical observation; no
formal proof is offered) than the level of the optimal consumption rule
. In
particular,
is well approximated by linear functions both as
and as
.
Differentiating with respect to
and dropping consumption function arguments yields
Similarly, we can solve (99) for
Thus, having approximated
, we can recover from it the level and derivative(s) of
.48
abowd, john m., and david card (1989): “On the Covariance Structure of Earnings and Hours Changes,” Econometrica, 57, 411–445.
attanasio, orazio, and guglielmo weber (1995): “Is Consumption Growth Consistent with Intertemporal Optimization? Evidence from the Consumer Expenditure Survey,” Journal of Political Economy, 103(6), 1121–57.
bewley, truman (1977): “The Permanent Income Hypothesis: A Theoretical Formulation,” Journal of Economic Theory, 16, 252–292.
blundell, richard, hamish low, and ian preston (2008): “Decomposing Changes in Income Risk Using Consumption Data,” Manusscript, University College London.
boyd, john h. (1990): “Recursive Utility and the Ramsey Problem,” Journal of Economic Theory, 50(2), 326–345.
cagetti, marco (2003): “Wealth Accumulation Over the Life Cycle and Precautionary Savings,” Journal of Business and Economic Statistics, 21(3), 339–353.
carroll, christopher d. (1992): “The Buffer-Stock Theory of Saving: Some Macroeconomic Evidence,” Brookings Papers on Economic Activity, 1992(2), 61–156, http://econ.jhu.edu/people/ccarroll/BufferStockBPEA.pdf.
__________ (1997): “Buffer Stock Saving and the Life Cycle/Permanent Income Hypothesis,” Quarterly Journal of Economics, CXII(1), 1–56, http://econ.jhu.edu/people/ccarroll/BSLCPIH.zip.
__________ (2016): “Theoretical Foundations of Buffer Stock Saving,” manuscript, Department of Economics, Johns Hopkins University, Available at http://econ.jhu.edu/people/ccarroll/papers/BufferStockTheory.
carroll, christopher d., and miles s. kimball (1996): “On the Concavity of the Consumption Function,” Econometrica, 64(4), 981–992, http://econ.jhu.edu/people/ccarroll/concavity.pdf.
carroll, christopher d., and andrew a. samwick (1997): “The Nature of Precautionary Wealth,” Journal of Monetary Economics, 40(1), 41–71.
carroll, christopher d., jiri slacalek, and kiichi tokuoka (2011): “Digestible Microfoundations: Buffer Stock Saving in a Krusell-Smith World,” Manuscript, Johns Hopkins University, At http://econ.jhu.edu/people/ccarroll/papers/BSinKS.pdf.
clarida, richard h. (1987): “Consumption, Liquidity Constraints, and Asset Accumulation in the Face of Random Fluctuations in Income,” International Economic Review, XXVIII, 339–351.
deaton, angus s. (1991): “Saving and Liquidity Constraints,” Econometrica, 59, 1221–1248, http://www.jstor.org/stable/2938366.
__________ (1992): Understanding Consumption. Oxford University Press, New York.
friedman, milton a. (1957): A Theory of the Consumption Function. Princeton University Press.
gourinchas, pierre-olivier, and jonathan parker (2002): “Consumption Over the Life Cycle,” Econometrica, 70(1), 47–89.
hiraguchi, ryoji (2003): “On the Convergence of Consumption Rules,” Manuscript, Johns Hopkins University.
jappelli, tullio, and luigi pistaferri (2000): “Intertemporal Choice and Consumption Mobility,” Econometric Society World Congress 2000 Contributed Paper Number 0118.
macurdy, thomas (1982): “The Use of Time Series Processes to Model the Error Structure of Earnings in a Longitudinal Data Analysis,” Journal of Econometrics, 18(1), 83–114.
matkowski, janusz, and andrzej s. nowak (2011): “On Discounted Dynamic Programming With Unbounded Returns,” Economic Theory, 46, 455–474.
modigliani, franco, and richard brumberg (1954): “Utility Analysis and the Consumption Function: An Interpretation of Cross-Section Data,” in Post-Keynesian Economics, ed. by Kenneth K. Kurihara, pp. 388–436. Rutgers University Press, New Brunswick, N.J.
muth, john f. (1960): “Optimal Properties of Exponentially Weighted Forecasts,” Journal of the American Statistical Association, 55(290), 299–306.
ramsey, frank (1928): “A Mathematical Theory of Saving,” Economic Journal, 38(152), 543–559.
schechtman, jack, and vera escudero (1977): “Some results on ‘An Income Fluctuation Problem’,” Journal of Economic Theory, 16, 151–166.
scheinkman, josé, and laurence weiss (1986): “Borrowing Constraints and Aggregate Economic Activity,” Econometrica, 54(1), 23–46.
stokey, nancy l., robert e. lucas, and edward c. prescott (1989): Recursive Methods in Economic Dynamics. Harvard University Press.
storesletten, kjetil, chris i. telmer, and amir yaron (2004): “Consumption and Risk Sharing Over the Life Cycle,” Journal of Monetary Economics, 51(3), 609–633.
szeidl, adam (2012): “Stable Invariant Distribution in Buffer-Stock Saving and Stochastic Growth Models,” Manuscript, Central European University.
toche, patrick (2005): “A Tractable Model of Precautionary Saving in Continuous Time,” Economics Letters, 87(2), 267–272, http://ideas.repec.org/a/eee/ecolet/v87y2005i2p267-272.html.
yao, jiaxiong (2012): “The Theoretical Foundations of Buffer Stock Saving: A Note,” Manuscript, Johns Hopkins University.
zeldes, stephen p. (1989): “Optimal Consumption with Stochastic Income: Deviations from Certainty Equivalence,” Quarterly Journal of Economics, 104(2), 275–298.