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November 20, 2017,
Christopher D. Carroll
LucasGrowth
The Lucas Growth Model
Lucas
(
1988
) presents a growth model in which output is generated via a production
function of the form
Y = AK
α
( hL)
1−α
(1)
where Y, A, and K are as usually defined and 0 < α < 1, where
is defined as the
proportion of total labor time spent working, and h is what Lucas calls the stock of
‘human capital.’
The production function can be rewritten in per-capita terms as
y = Ak
α
( h)
1−α
(2)
which is a constant returns to scale production function in k and h.
Capital accumulation proceeds via the usual differential equation,
˙k = y − c − (ξ + δ)k,
(3)
while h accumulates according to
˙h = φh(1 − )
(4)
˙h/h = φ(1 − ).
(5)
1 Discussion
Before analyzing the model, an aside.
Mankiw
(
1995
) has persuasively argued for
defining ‘knowledge’ as the sum total of technological and scientific discoveries (what
is written in textbooks, scholarly journals, websites, and the like), and defining
‘human capital’ as the stock of knowledge that has been transmitted from those
sources into human brains via studying.
Recall
Rebelo
(
1991
)’s key insight about endogenous growth models: In order to
produce perpetual growth, there must be a factor or a combination of factors that
can be accumulated indefinitely without diminishing returns. Mankiw points out
that since lifetimes are finite, there is a maximum limit to the amount of human
capital that an individual can accumulate. Thus, while increasing human capital
(with more years of schooling, for example) may be able to extend the length of
the transition period in a growth model, human capital accumulation cannot be the
source of perpetual growth. It is more plausible to think that scientific knowledge
can be accumulated indefinitely (though presumably there is some limit even to the
accumulation of knowledge). These considerations suggest that models of endogenous
growth should focus more on understanding the process of fundamental research and
technological development than on human capital accumulation as Mankiw defines
it.
With this distinction in mind, there are (at least) two interpretations of the Lucas
model. One is at the aggregate level. Here we can think of
as the fraction of the
population engaged in useful work to produce goods and services, while proportion
1− is not working in conventional boring jobs that require asking customers questions
like “Would you like fries with that?”
but instead is producing ‘knowledge’ by
conducting scientific and technological research.
The other interpretation is at the level of an individual agent. Such an agent can
be thought of as operating his or her own production function of the form in (
2
),
where (1 − ) is now interpreted as the proportion of the time this individual spends
studying and
is the time spent working.
From the point of view of Mankiw’s distinction, it is hard to interpret Lucas’s model
as being either about human capital accumulation or about knowledge. It can’t be
about human capital because h can be accumulated without bound, and without
diminishing returns, neither of which makes sense for an individual. It can’t be about
generalized knowledge, because the optimization problem reflects the return for an
individual, while only a trivial proportion of total knowledge (in Mankiw’s sense) is
contributed by any single individual.
Given these considerations, it probably makes more sense to think of the model as
a tool for normative than for positive analysis.
2 The Solow Version
We analyze first the ‘Solow’ version of the model, in which the saving rate is exoge-
nously fixed at s. Thus the capital accumulation equation becomes
˙k = sy − (ξ + δ)k
(6)
˙k/k = s(y/k) − (ξ + δ)
(7)
= sk
α−1
( h)
1−α
− (ξ + δ)
(8)
= s(k/h)
α−1 1−α
− (ξ + δ).
(9)
This equation tells us that the steady-state growth rate in this model (if one exists)
requires a constant ratio of k to h. Thus, k and h must be growing at the same rate
in equilibrium.
Further insight can be obtained by defining ˆ
A = A
1−α
and rewriting the per-capita
production function as
y =
ˆ
Ak
α
h
1−α
.
(10)
If we define a measure of ‘broad capital’ as the combination of physical capital and
2
human capital,
κ ≡ k
α
h
1−α
,
(11)
the model becomes
y = ˆ
Aκ.
(12)
So if
is constant and if k and h are growing at the same rate, then the exponent
on ‘broad capital’ is 1, and we are effectively back at the usual Rebelo AK model.
The key assumption that permits this to work is the accumulation equation for
human capital, which is itself like an AK model, in the sense that the exponent on
human capital in the accumulation equation for human capital is one. Human capital
can be accumulated without bound and without diminishing returns.
3 The Ramsey/Cass-Koopmans Version
Lucas does not examine the Solow version of the model with a constant saving rate,
but instead the version in which a social planner solves for the optimal perfect foresight
paths of the two state variables k and h. It’s not worth going through the math here;
I’ll just present the conclusion, which is that the steady-state growth rate is
˙c/c = ρ
−1
(φ − θ).
(13)
Note that this confirms the crucial role of the CRS accumulation equation for
human capital: The key parameter that corresponds to the interest rate is φ, the
parameter that determines the efficiency of human capital accumulation in equation
(
4
).
Lucas also solves a version of the model in which there is an externality to human
capital. The idea here is that each person is more productive if they are surrounded
by other people with high levels of human capital. Specifically, in this version of the
model the individual’s production function is
y
i
= Ak
α
i
(
i
h
i
)
1−α
¯
h
ψ
(14)
where ¯
h is average human wealth in the population (and the other variables reflect
the values for the individual).
Working through the decentralized solution, Lucas shows that the steady-state
growth rate of human capital for an individual consumer will be
γ
h
=
ρ
−1
(φ − θ)
1 + ψ(1 − 1/ρ)/(1 − α)
.
(15)
Since every individual is assumed to be identical, the growth rate of aggregate
human capital (and everything else) is the same as the rate for this individual.
3
It is easy to see that if there is no externality to human capital accumulation (that
is, if ψ = 0), this solution is identical to (
13
). If there is an externality, its effect
depends on whether 1/ρ is greater than, equal to, or less than 1. This is because
the effect depends on whether the externality causes the saving rate to rise or to
fall (since in endogenous growth models, saving is the source of all growth). The ¯
h
externality is like an increase in the interest rate, and thus its effect will be determined
by the balance between the income and substitution effects. We know that for ρ = 1
the income and substitution effects exactly offset each other, leaving consumption
unchanged in response to an increase in the interest rate, which is why (
15
) collapses
to (
13
) for ρ = 1.
If consumers are very willing to cut current consumption in
exchange for higher future consumption (that is, if the intertemporal elasticity of
substitution (1/ρ) is greater than 1), then the externality boosts saving and therefore
growth. If consumers have an intertemporal elasticity of less than one, the income
effect outweighs the substitution effect, saving falls, and growth is slower.
Lucas also shows that this decentralized solution is suboptimal, because individual
consumers do not obtain the full benefits to society of increasing their own stock of
knowledge. Devoting more time to h
i
accumulation they increase ¯
h, which benefits all
others in the economy in addition to themselves. Lucas shows, unsurprisingly, that the
socially optimal solution requires greater investment in human capital accumulation
than is obtained in the decentralized model. He also derives an optimal subsidy to
human capital accumulation that corrects the externality and induces households to
invest the socially optimal amount in human capital.
4
References
Lucas, Robert E. (1988): “On the Mechanics of Economic Development,” Journal
of Monetary Economics, 22, 3–42.
Mankiw, N. Gregory (1995): “The Growth of Nations,” Brookings Papers on
Economic Activity, 1995(1), 275–326.
Rebelo, Sergio T. (1991): “Long-Run Policy Analysis and Long-Run Growth,”
Journal of Political Economy, 99(3), 500–521.
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