Journal of Monetary Economics 22 (1988) 3-42. North-Holland ON THE MECHANICS OF ECONOMIC DEVELOPMENT* Robert E. LUCAS, Jr. University of Chicago, Chicago, 1L 60637, USA Received August 1987, final version received February 1988 This paper considers the prospects for constructing a neoclassical theory of growth and interna- tional trade that is consistent with some of the main features of economic development. Three models are considered and compared to evidence: a model emphasizing physical capital accumula- tion and technological change, a model emphasizing human capital accumulation through school- ing. and a model emphasizing specialized human capital accumulation through learning-by-doing. 1. Introduction By the problem of economic development I mean simply the problem of accounting for the observed pattern, across countries and across time, in levels and rates of growth of per capita income. This may seem too narrow a definition, and perhaps it is, but thinking about income patterns will neces- sarily involve us in thinking about many other aspects of societies too. so I would suggest that we withhold judgment on the scope of this definition until we have a clearer idea of where it leads us. The main features of levels and rates of growth of national incomes are well enough known to all of us, but I want to begin with a few numbers, so as to set a quantitative tone and to keep us from getting mired in the wrong kind of details. Unless I say otherwise, all figures are from the World Bank's World Development Report of 1983. The diversity across countries in measured per capita income levels is literally too great to be believed. Compared to the 1980 average for what the WorId Bank calls the 'industrial market economies' (Ireland up through Switzerland) of U.S. $10,000, India's per capita income is $240, Haiti's is $270, *This paper was originally written for the Marshall Lectures, given at Cambridge University in 1985. ! am very grateful to the Cambridge faculty for this honor, and also for the invitatiou's long lead time, which gave me the opportunity to think through a new topic with the stimulus of so distinguished an audience in prospect. Since then, versions of this lecture have been given as the David Horowitz Lectures in Israel, the W.A. Mackintosh Lecture at Queens University, the Carl Snyder Memorial Lecture at the University of California at Santa Barbara, the Chung-Hua Lecture in Taipei. the Nancy Schwartz Lecture at Northwestern University, and the Lionel McKenzie Lecture at the University of Rochester. I have also based several seminars on various parts of this material. 0304-3932j88j$3.50©1988, Elsevier Science Publishers B.V. (North-Holland) 4 R. E. Lucas, Jr., On the mechanics of economic development and so on for the rest of the very poorest countries. This is a difference of a factor of 40 in living standards! These latter figures are too low to sustain life in, say, England or the United States, so they ca.

1. Journal of Monetary Economics 22 (1988) 3-42. North-Holland
ON THE MECHANICS OF ECONOMIC DEVELOPMENT*
Robert E. LUCAS, Jr.
University of Chicago, Chicago, 1L 60637, USA
Received August 1987, final version received February 1988
This paper considers the prospects for constructing a
neoclassical theory of growth and interna-
tional trade that is consistent with some of the main features of
economic development. Three
models are considered and compared to evidence: a model
emphasizing physical capital accumula-
tion and technological change, a model emphasizing human
capital accumulation through school-
ing. and a model emphasizing specialized human capital
accumulation through learning-by-doing.
1. Introduction
By the problem of economic development I mean simply the
problem of
accounting for the observed pattern, across countries and across
time, in levels
and rates of growth of per capita income. This may seem too
narrow a
definition, and perhaps it is, but thinking about income patterns
will neces-
sarily involve us in thinking about many other aspects of

2. societies too. so I
would suggest that we withhold judgment on the scope of this
definition until
we have a clearer idea of where it leads us.
The main features of levels and rates of growth of national
incomes are well
enough known to all of us, but I want to begin with a few
numbers, so as to
set a quantitative tone and to keep us from getting mired in the
wrong kind of
details. Unless I say otherwise, all figures are from the World
Bank's World
Development Report of 1983.
The diversity across countries in measured per capita income
levels is
literally too great to be believed. Compared to the 1980 average
for what the
WorId Bank calls the 'industrial market economies' (Ireland up
through
Switzerland) of U.S. $10,000, India's per capita income is $240,
Haiti's is $270,
*This paper was originally written for the Marshall Lectures,
given at Cambridge University in
1985. ! am very grateful to the Cambridge faculty for this
honor, and also for the invitatiou's long
lead time, which gave me the opportunity to think through a
new topic with the stimulus of so
distinguished an audience in prospect. Since then, versions of
this lecture have been given as the
David Horowitz Lectures in Israel, the W.A. Mackintosh
Lecture at Queens University, the Carl
Snyder Memorial Lecture at the University of California at
Santa Barbara, the Chung-Hua

3. Lecture in Taipei. the Nancy Schwartz Lecture at Northwestern
University, and the Lionel
McKenzie Lecture at the University of Rochester. I have also
based several seminars on various
parts of this material.
0304-3932j88j$3.50©1988, Elsevier Science Publishers B.V.
(North-Holland)
4 R. E. Lucas, Jr., On the mechanics of economic development
and so on for the rest of the very poorest countries. This is a
difference of a
factor of 40 in living standards! These latter figures are too low
to sustain life
in, say, England or the United States, so they cannot be taken at
face value
and I will avoid hanging too much on their exact magnitudes.
But I do not
think anyone will argue that there is not enormous diversity in
living stan-
dards. I
Rates of growth of real per capita GNP are also diverse, even
over sustained
periods. For 1960-80 we observe, for example: India, 1.4% per
year; Egypt,
3.4%; South Korea, 7.0%; Japan, 7.1 %; the United States,
2.3%; the industrial
economies averaged 3.6%. To obtain from growth rates the
number of years it
takes for incomes to double, divide these numbers into 69 (the
log of 2 times
100). Then Indian incomes will double every 50 years; Korean

4. every 10. An
Indian will, on average, be twice as well off as his grandfather;
a Korean 32
times. These differences are at least as striking as differences in
income levels,
and in some respects more trustworthy, since within-country
income compari-
sons are easier to draw than across-country comparisons.
I have not calculated a correlation across countries between
income levels
and rates of growth, but it would not be far from zero. (The
poorest countries
tend to have the lowest growth; the wealthiest next; the 'middle-
income'
countries highest.) The generalizations that strike the eye have
to do with
variability within these broad groups: the rich countries show
little diversity
(Japan excepted - else it would not have been classed as a rich
country in
1980 at all). Within the poor countries (low and middle income)
there is
enormous variability. 2
Within the advanced countries, growth rates tend to be very
stable over long
periods of time, provided one averages over periods long
enough to eliminate
business-cycle effects (or corrects for short-term fluctuations in
some other
way). For poorer countries, however, there are many examples
of sudden, large
changes in growth rates, both up and down. Some of these
changes are no
doubt due to political or military disruption: Angola's total GDP

5. growth fell
from 4.8 in the 60s to - 9.2 in the 70s; Iran's fell from 11.3 to
2.5, comparing
the same two periods. I do not think we need to look to
economic theory for
an account of either of these declines. There are also some
striking examples
1 The income estimates reported in Summers and Heston (1984)
are more satisfactory than those
in the World Development Reports. In 1975 U.S. dollars, these
authors estimate 1980 U.S. real
GDP per capita at $8000, and for the industrialized economies
as a group, $5900. The comparable
figures for India and Haiti are $460 and $500, respectively.
Income differences of a factor of 16 are
certainly smaJler, and J think more accurate, than a factor of 40,
but I think they are still fairly
described as exhibiting 'enormous diversity'.
2 Baumol (1986) summarizes evidence, mainly from Maddison
(1982) indicating apparent
convergence during this century to a common path of the
income levels of the wealthiest
countries. But De Long (1987) shows that this effect is entirely
due to 'selection bias': If one
examines the countries with the highest income levels at the
beginning of the century (as opposed
to currently, as in Maddison's 'sample') the data show apparent
divergence!
R.E. Lucas. Jr., On the mechanics of economic development 5
of sharp increases in growth rates. The four East Asian

6. 'miracles' of South
Korea, Taiwan, Hong Kong and Singapore are the most familiar:
for the
1960-80 period, per capita income in these economies grew at
rates of 7.0, 6.5,
6.8 and 7.5, respectively, compared to much lower rates in the
1950's and
earlier. 3,4 Between the 60s and the 70s, Indonesia's GDP
growth increased
from 3.9 to 7.5; Syria's from 4.6 to 10.0.
I do not see how one can look at figures like these without
seeing them as
representing possibilities. Is there some action a government of
India could
take that would lead the Indian economy to grow like
Indonesia's I)r Egypt's?
If so, what, exactly? If not, what is it about the' nature of India'
that makes it
so? The consequences for human welfare involved in questions
like these are
simply staggering: Once one starts to think about them, it is
hard to think
about anything else.
This is what we need a theory of economic development for: to
provide
some kind of framework for organizing facts like these, for
judging which
represent opportunities and which necessities. But the term'
theory' is used in
so many different ways, even within economics, that if I do not
clarify what I
mean by it early on, the gap between what I think I am saying
and what you
think you are hearing will grow too wide for us to have a

7. serious discussion. I
prefer to use the term' theory' in a very narrow sense, to refer to
an explicit
dynamic system, something that can be put on a computer and
run. This is
what I mean by the' mechanics' of economic development - the
construction
of a mechanical, artificial world, populated by the interacting
robots that
economics typically studies, that is capable of exhibiting
behavior the gross
features of which resemble those of the actual world that I have
just described.
My lectures will be occupied with one such construction, and it
will take some
work: It is easy to set out models of economic growth based on
reasonable-
looking axioms that predict the cessation of growth in a few
decades, or that
predict the rapid convergence of the living standards of
different economies to
a common level, or that otherwise produce logically possible
outcomes that
bear no resemblance to the outcomes produced by actual
economic systems.
On the other hand, there is no doubt that there must be
mechanics other than
the ones I will describe that would fit the facts about as well as
mine. This is
why I have titled the lectures 'On the Mechanics ... ' rather than
simply 'The
Mechanics of Economic Development'. At some point, then, the
study of
development will need to involve working out the implications
of competing
theories for data other than those they were constructed to fit,

8. and testing
these implications against observation. But this is getting far
ahead of the
3The World Bank no longer transmits data for Taiwan. The
figure 6.5 in the text is from
Harberger (1984, table 1, p. 9).
4According to Heston and Summers (1984), Taiwan's per-capita
GDP growth rate in the 1950s
was 3.6. South Korea's was 1.7 from 1953 to 1960.
6 R.E. Lucas. Jr., On the mechanics of economic development
story I have to tell, which will involve leaving many important
questions open
even at the purely theoretical level and will touch upon
questions of empirical
testing hardly at all.
My plan is as follows. I will begin with an application of a now-
standard
neoclassical model to the study of twentieth century U.S.
growth, closely
following the work of Robert Solow, Edward Denison and many
others. I will
then ask, somewhat unfairly, whether this model as it stands is
an adequate
model of economic development, concluding that it is not. Next,
I will
consider two adaptations of this standard model to include the
effects of
human capital accumulation. The first retains the one-sector
character of the

9. original model and focuses on the interaction of physical and
human capital
accumulation. The second examines a two-good system that
admits specialized
human capital of different kinds and offers interesting
possibilities for the
interaction of trade and development. Finally, I will turn to a
discussion of
what has been arrived at and of what is yet to be done.
In general, I will be focusing on various aspects of what
economists, using
the term very broadly, call the' technology'. I will be abstracting
altogether
from the economics of demography, taking population growth as
a given
throughout. This is a serious omission, for which I can only
offer the excuse
that a serious discussion of demographic issues would be at
least as difficult as
the issues I will be discussing and I have neither the time nor
the knowledge to
do both. I hope the interactions between these topics are not
such that they
cannot usefully be considered separately, at least in a
preliminary way. 5
I will also be abstracting from all monetary matters, treating all
exchange as
though it involved goods-for-goods. In general, I believe that
the importance
of financial matters is very badly over-stressed in popular and
even much
professional discussion and so am not inclined to be apologetic
for going to
the other extreme. Yet insofar as the development of financial

10. institutions is a
limiting factor in development more generally conceived I will
be falsifying the
picture, and I have no clear idea as to how badly. But one
cannot theorize
about everything at once. I had better get on with what I do
have to say.
2. Neoclassical growth theory: Review
The example, or model, of a successful theory that I will try to
build on is
the theory of economic growth that Robert Solow and Edward
Denison
developed and applied to twentieth century U.S. experience.
This theory will
serve as a basis for further discussion in three ways: as an
example of the form
that I believe useful aggregative theories must take, as an
opportunity to
5Becker and Barro (1985) is the first attempt known to me to
analyze fertility and capital
accumulation decisions simultaneously within a general
equilibrium framework. Tamura (1986)
contains further results along this line.
R.E. Lucas, Jr., On the mechanics of economic development 7
explain exactly what theories of this form can tell us that other
kinds of
theories cannot, and as a possible theory of economic
development. In this
third capacity, the theory will be seen to fail badly, but also

11. suggestively.
Following up on these suggestions will occupy the remainder of
the lectures.
Both Solow and Denison were attempting to account for the
main features
of U.S. economic growth, not to provide a theory of economic
development,
and their work was directed at a very different set of
observations from the
cross-country comparisons I cited in my introduction. The most
useful
summary is provided in Denison's 1961 monograph, The
Sources of Economic
Growth in the United States. Unless otherwise mentioned, this
is the source for
the figures I will cite next.
During the 1909-57 period covered in Denison's study, U.S. real
output
grew at an annual rate of 2.9%, employed manhours at 1.3%,
and capital stock
at 2.4%. The remarkable feature of these figures, as compared
to those cited
earlier, is their stability over time. Even if one takes as a
starting point the
trough of the Great Depression (1933) output growth to 1957
averages only
5%. If business-cycle effects are removed in any reasonable way
(say, by using
peak-to-peak growth rates) U.S. output growth is within half a
percentage
point of 3% annually for any sizeable subperiod for which we
have data.
Solow (1956) was able to account for this stability, and also for

12. some of the
relative magnitudes of these growth rates, with a very simple
but also easily
refineable model. 6 There are many variations of this model in
print. I will set
out a particularly simple one that is chosen also to serve some
later purposes. I
will do so without much comment on its assumed structure:
There is no point
in arguing over a model's assumptions until one is clear on what
questions it
will be used to answer.
We consider a closed economy with competitive markets, with
identical,
rational agents and a constant returns technology. At date t
there are N( t)
persons or, equivalently, manhours devoted to production. The
exogenously
given rate of growth of N( t) is A. Real, per-capita consumption
is a stream
c(t), t ~ 0, of units of a single good. Preferences over (per-
capita) consumption
streams are given by
i
oo
e-pt_l_[c(t)l-o-I]N(t)dt,
o I-a
(1)
6 Solow's 1956 paper stimulated a vast literature in the 1960s,
exploring many variations on the
original one-sector structure. See Burmeister and Dobell (1970)

13. for an excellent introduction and
survey. By putting a relatively simple version to empirical use,
as I shall shortly do, I do not
intend a negative comment on this body of research. On the
contrary, it is exactly this kind of
theoretical experimentation with alternative assumptions that is
needed to give one the confidence
that working with a particular, simple parameterization may, for
the specific purpose at hand, be
adequate.
8 R.E. Lucas, Jr., On the mechanics of economic development
where the discount rate p and the coefficient of (relative) risk
aversion 0 are
both positive. 7
Production per capita of the one good is divided into
consumption c( t) and
capital accumulation. If we let K(t) denote the total .stock of
cal?ital, and
K(t) its rate of change, then total output is N(t)c(t) + K(t).
[Here K(t) is net
investment and total output N(t)c(t) + K(t) is identified with net
national
product.] Production is assumed to depend on the levels of
capital and labor
inpu ts and on the level A ( t) of the 'technology', according to
(2)
where 0 < f3 < 1 and where the exogenously given rate of
technical change,
A/A, is p. > O.

14. The resource allocation problem faced by this simple economy
is simply to
choose a time path c( t) for per-capita consumption. Given a
path c(t) and an
initial capital stock K(O), the technology (2) then implies a
time path K( t) for
capital. The paths A(t) and N(t) are given exogenously. One
way to think
abou t this allocation problem is to think of choosing c(t) at
each date, given
the values of K(t), A(t) and N(t) that have been attained by that
date.
Evidently, it will not be optimal to choose c( t) to maximize
current-period
utility, N(t)[1j(1 - o)][c(t) - 1]1-0, for the choice that achieves
this is to set
net investment K(t) equal to zero (or, if feasible, negative): One
needs to set
some value or price on increments to capital. A central
construct in the study
of optimal allocations, allocations that maximize utility (1)
subject to the
technology (2), is the current-value Hamiltonian H defined by
N
H(K, 8, c, t) = -1-[c1- O -1] + 8[AK.8N 1-.8 - Nc],
-0
which is just the sum of current-period utility and [from (2)] the
rate of
increase of capital, the latter valued at the' price' 8( t). An
optimal allocation
must maximize the expression H at each date t, provided the
price O( t) is

15. correctly chosen.
The first-order condition for maximizing H with respect to c is
(3)
which is to say that goods must be so allocated at each date as
to be equally
valuable, on the margin, used either as consumption or as
investment. It is
7The inverse a -I of the coefficient of risk aversion is
sometimes called the intertemporal
elasticity of substitution. Since all the models considered in this
paper are deterministic, this latter
terminology may be more suitable.
R.E. Lucas, Jr., On the mechanics 0/ economic development
known that the price 8( t) must satisfy
. a
8(t) = p8(t) - aKH(K(t),8(t),c(t), t)
= [p - f3A ( t ) N ( t )1-f3 K ( t ) f3 - 1] 8 ( t ) ,
9
(4)
at each date t if the solution c(t) to (3) is to yield an optimal
path (c(t»~=o.
Now if (3) is used to express c(t) as a function 8(1), and this
function 8- 1/ 0

16. is substituted in place of c(t) in (2) and (4), these two equations
are a pair of
first-order differential equations in K (t) and its 'price' 8(1).
Solving this
system, there will be a one-parameter family of paths (K (t), 8(
t», satisfying
the given initial condition on K(O). The unique member of this
family that
satisfies the transversality condition:
lim e- pt8(t)K(t) = 0
t-+ 00
(5)
is the optimal path. I am hoping that this application of
Pontryagin's Maxi-
mum Principle, essentially taken from David Cass (1961), is
familiar to most
of you. I will be applying these same ideas repeatedly in what
follows.
For this particular model, with convex preferences and
technology and with
no external effects of any kind, it is also known and not at all
surprising that
the optimal program characterized by (2), (3), (4) and (5) is also
the unique
competitive equilibrium program, provided either that all
trading is consum-
mated in advance, Arrow-Debreu style, or (and this is the
interpretation I
favor) that consumers and firms have rational expectations
about future prices.
In this deterministic context, rational expectations just means

17. perfect fore-
sight. For my purposes, it is this equilibrium interpretation that
is most
interesting: I intend to use the model as a positive theory of
U.S. economic
growth.
In order to do this, we will need to work out the predictions of
the model in
more detail, which involves solving the differential equation
system so we can
see what the equilibrium time paths look like and compare them
to observa-
tions like Denison's. Rather than carry this analysis through to
completion, I
will work out the properties of a particular solution to the
system and then
just indicate briefly how the rest of the answer can be found in
Cass's paper.
Let us construct from (2), (3) and (4) the system's balanced
growth path: the
particular solution (K(t), 8(1), c(t» such that the rates of growth
of each of
these variables is constant. (I have never been sure exactly what
it is that is
'balanced' along such a path, but we need a term for solutions
with this
constant growth rate property and this is as good as any.) Let K
denote the
rate of growth of per-capita consumption, c(t)jc(t), on a
balanced growth
10 R.E. Lucas, Jr., On the mechanics of economic development

18. path. Then from (3), we have 8(t)/8(t) = -al(. Then from (4), we
must have
f3A ( t ) N ( t ) 1 - fJ K ( t ) fJ - 1 = P + aI( . (6)
That is, along the balanced path, the marginal product of capital
must equal
the constant value p + al(. With this Cobb-Douglas technology,
the marginal
product of capital is proportional to the average product, so that
dividing (2)
through by K( t) and applying (6) we obtain
N(t)c(t) K(t) =A( )K( )fJ-11t.T( )l- fJ = p+al(
K(t) + K(t) t t iV t 13' (7)
By definition of a balanced path, K(t)/K(t) is constant so (7)
implies that
N( t )c(t)/K( t) is constant or, differentiating, that
K(t) N(t) c(t)
--=--+--=I(+A
K(t) N(t) c(t) .
(8)
Thus per-capita consumption and per-capita capital grow at the
common
rate 1(. To solve for this common rate, differentiate either (6) or
(7) to obtain
p.
1(= --.
1-13

19. (9)
Then (7) may be solved to obtain the constant, balanced
consumption-capital
ratio N(t)c(t)/K(t) or, which is equivalent and slightly easier to
interpret, the
constant, balanced net savings rate s defined by
K(t) f3(I(+A)
s= =---
N(t)c(t)+K(t) p+al('
(10)
Hence along a balanced path, the rate of growth of per-capita
magnitudes is
simply proportional to the given rate of technical change, p.,
where the
constant of proportionality is the inverse of labor's share, 1 -
13. The rate of
time preference p and the degree of risk aversion a have no
bearing on this
long-run growth rate. Low time preference p and low risk
aversion a induce a
high savings rate s, and high savings is, in turn, associated with
relatively high
output levels on a balanced path. A thrifty society will, in the
long run, be
wealthier than an impatient one, but it will not grow faster.
In order that the balanced path characterized by (9) and (10)
satisfy the
transversality condition (5), it is necessary that p + al( > I( + A.
[From (10), one
sees that this is the same as requiring the savings rate to be less
than capital's

20. R.E. Lucas, Jr., On the mechanics of economic development 11
share.] Under this condition, an economy that begins on the
balanced path
will find it optimal to stay there. What of economies that begin
off the
balanced path - surely the normal case? Cass showed - and this
is exactly
why the balanced path is interesting to us - that for any initial
capital
K(O) > 0, the optimal capital-consumption path (K(t), c(t» will
converge to
the balanced path asymptotically. That is, the balanced path will
be a good
approximation to any actual path 'most' of the time.
Now given the taste and technology parameters (p, 0, X, f3 and
JL) (9) and
(10) can be solved for the asymptotic growth rate K of capital,
consumption
and real output, and the savings rate s that they imply.
Moreover, it would be
straightforward to calculate numerically the approach to the
balanced path
from any initial capital level K (0). This is the exercise that an
idealized
planner would go through.
Our interest in the model is positive, not normative, so we want
to go in the
opposite direction and try to infer the underlying preferences
and technology
from what we can observe. I will outline this, taking the

21. balanced path as the
model's prediction for the behavior of the U.S. economy during
the entire
(1909-57) period covered by Denison's study.8 From this point
of view,
Denison's estimates provide a value of 0.013 for X, and two
values, 0.029 and
0.024 for K + X, depending on whether we use output or capital
growth rates
(which the model predicts to be equal). In the tradition of
statistical inference,
let us average to get K + X= 0.027. The theory predicts that 1 -
f3 should
equal labor's share in national income, about 0.75 in the U.S.,
averaging over
the entire 1909-57 period. The savings rate (net investment over
NNP) is
fairly constant at 0.10. Then (9) implies an estimate of 0.0105
for JL. Eq. (10)
implies that the preference parameters p and 0 satisfy
p + (0.014)0 = 0.0675.
(The parameters p and 0 are not separately identified along a
smooth
consumption path, so this is as far as we can go with the sample
averages I
have provided.)
These are the parameter values that give the theoretical model
its best fit to
the U.S. data. How good a fit is it? Either output growth is
underpredicted or
capital growth overpredicted, as remarked earlier (and in the
theory of growth,
a half a percentage point is a large discrepancy). There are

22. interesting secular
changes in manhours per household that the model assumes
away, and labor's
share is secularly rising (in all growing economies), not
constant as assumed.
There is, in short, much room for improvement, even in
accounting for the
secular changes the model was designed to fit, and indeed, a
fuller review of
8With the parameter values described in this paragraph, the
half-life of the approximate linear
system associated with this model is about eleven years.
12 R.E. Lucas, Jr., On the mechanics of economic development
the literature would reveal interesting progress on these and
many other
fronts. 9 A model as explicit as this one, by the very nakedness
of its simplify-
ing assumptions, invites criticism and suggests refinements to
itself. This is
exactly why we prefer explicitness, or why I think we ought to.
Even granted its limitations, the simple neoclassical model has
made basic
contributions to our thinking about economic growth.
Qualitatively, it empha-
sizes a distinction between 'growth effects' - changes in
parameters that alter
growth rates along balanced paths - and 'level effects' - changes
that raise or
lower balanced growth paths without affecting their slope - that
is fundamen-

23. tal in thinking about policy changes. Solow's 1956 conclusion
that changes in
savings rates are level effects (which transposes in the present
context to the
conclusion that changes in the discount rate, P, are level
effects) was startling
at the time, and remains widely and very unfortunately
neglected today. The
influential idea that changes in the tax structure that make
savings more
attractive can have large, sustained effects on an economy's
growth rate
sounds so reasonable, and it may even be true, but it is a clear
implication of
the theory we have that it is not.
Even sophisticated discussions of economic growth can often be
confusing
as to what are thought to be level effects and what growth
effects. Thus
Krueger (1983) and Harberger (1984), in their recent, very
useful surveys of
the growth experiences of poor countries, both identify
inefficient barriers to
trade as a limitation on growth, and their removal as a key
explanation of
several rapid growth episodes. The facts Krueger and Harberger
summarize
are not in dispute, but under the neoclassical model just
reviewed one would
not expect the removal of inefficient trade barriers to induce
sustained
increases in growth rates. Removal of trade barriers is, on this
theory, a level
effect, analogous to the one-time shifting upward in production
possibilities,

24. and not a growth effect. Of course, level effects can be drawn
out through time
through adjustment costs of various kinds, but not so as to
produce increases
in growth rates that are both large and sustained. Thus the
removal of an
inefficiency that reduced output by five percent (an enormous
effect) spread
out over ten years in simply a one-half of one percent annual
growth rate
stimulus. Inefficiencies are important and their removal
certainly desirable, but
the familiar ones are level effects, not growth effects. (This is
exactly why it is
not paradoxical that centrally planned economies, with
allocative inefficiencies
of legendary proportions, grow about as fast as market
economies.) The
empirical connections between trade policies and economic
growth that
9In particular, there is much evidence that capital stock growth,
as measured by Denison,
understates true capital growth due to the failure to correct
price deflators for quality improve-
ments. See, for example, Griliches and Jorgenson (1967) or
Gordon (1971). These errors may well
account for all of the 0.005 discrepancy noted in the text (or
more!).
Boxall (1986) develops a modification of the Solow-Cass model
in which labor supply is
variable, and which has the potential (at least) to account for
long-run changes in manhours.

25. R. E. Lucas, Jr., On the mechanics of economic development 13
Krueger and Harberger document are of evident importance, but
they seem to
me to pose a real paradox to the neoclassical theory we have,
not a confirma-
tion of it.
The main contributions of the neoclassical framework, far more
important
than its contributions to the clarity of purely qualitative
discussions, stem
from its ability to quantify the effects of various influences on
growth.
Denison's monograph lists dozens of policy changes, some
fanciful and many
others seriously proposed at the time he wrote, associating with
each of them
rough upper bounds on their likely effects on U.S. growth. 1o In
the main, the
theory adds little to what common sense would tell us about the
direction of
each effect - it is easy enough to guess which changes stimulate
production,
hence savings, and hence (at least …
The Lahore Journal of Economics
13 : 1 (Summer 2008): pp. 1-27
16
Qaisar Abbas and James Foreman-Peck Human Capital and
Economic Growth: Pakistan, 1960-2003
15Human Capital and Economic Growth:
Pakistan, 1960-2003

26. Qaisar Abbas*, James Foreman-Peck**Abstract
This paper investigates the relationship between human capital
and economic growth in Pakistan with aggregate time series
data. Estimated with the Johansen (1991) approach, the fitted
model indicates a critical role for human capital in boosting the
economy’s capacity to absorb world technical progress. Much
higher returns, including spillovers, to secondary schooling in
Pakistan than in OECD economies is consistent with very
substantial education under-investment in Pakistan. Similarly,
extremely large returns to health spending compare very
favorably with industrial investment. Human capital is
estimated to have accounted for just under one-fifth of the
increase in Pakistan’s GDP per head. Since the 1990s, the
impact of deficient human capital policies is shown by the
negative contribution to economic growth.
JEL Classification: C13, C22, C51, O15, O53
Keywords:Human Capital, Economic Growth, Cointegration,
Pakistan
1. Introduction
Human capital plays a key role in both neoclassical and
endogenous growth models (Mankiw, Romer and Weil, 1992;
Rebelo, 1991; Sianesi and Van Reenen, 2003). The critical
difference is that in the first group, economic growth is
ultimately driven by exogenous technical progress. Diminishing
returns to accumulated factors, including human capital,
eventually halt growth in a neoclassical model, in the absence
of intervention from outside influences. Policy changes can
raise the level of productivity but not the long run growth rate.
Endogenous growth models, on the other hand, need no
additional explanation, for human capital investment propels
knowledge creation without diminishing returns. A permanent
alteration in some policy variable can cause a permanent change
in an economy’s growth rate.

27. Unlike time series evidence for the United States, at first sight
the data for many developing economies could be broadly
consistent with this prediction (Jones, 1995). Since political
independence for these countries after 1945 was accompanied
by major policy changes, the shifts could be responsible for
accelerated growth after this date in an endogenous growth
model
.
However, Parente and Prescott (1999, 2000) point out that the
technical progress in an extended neoclassical model can alter
in response to policy as well. Individual choices determine the
pace of productivity increase, when time is diverted from
normal work to activities that improve technology. These
activities can draw on the world stock of knowledge and borrow
capital on world markets. Policy-induced constraints, such as
taxation, international capital controls, or entry barriers to
industries, create disincentives to do so. They give rise to
international differences in levels and growth of aggregate
productivity, even when the stock of useful knowledge is
potentially common to all countries.
For economies behind the world technological frontier,
productivity growth is likely to depend critically upon the
spread and absorption of technology, rather than upon the
generation of new knowledge (Nelson and Phelps, 1966;
Benhabib and Spiegel, 2002). Absorptive capacity depends on
national institutions and policies; openness to foreign direct
investment, regulation of intellectual property rights, and
exchange rate regimes affect a follower economy’s imports of
technology, as well as the generation of new useful knowledge
(Shapiro, 2005). But the stock of skills, and the education and
training that create them, is likely to be vital to utilizing foreign
know-how, in addition to functioning as a conventional factor
of production (Saggi, 2002).
Human capital is not restricted to knowledge. Health has been

28. found to be a positive and significant contributor to economic
growth in many empirical cross-country models (Bloom and
Canning 2000, 2003). Measured simply as life expectancy,
health human capital can effect economic growth in several
ways. As people live longer, they may save more for old age.
Life expectancy can also serve as proxy for the heath status of
the whole population, because declines in mortality rates are
related to falls in morbidity. Important as this form of human
capital may be, it will not contribute to technology transfer, in
contrast to education and training.
Despite the theoretical significance of knowledge human
capital, the empirical evidence from cross-country studies is
very mixed. Pungo (1996) showed that the Mankiw et al. (1992)
(MRW) human capital-augmented neoclassical specification
exhibits structural breaks, such that the coefficient on human
capital is insignificant for a sample of labor-abundant countries
and if influential observations are excluded. A possible reason
for these last results is that schooling in developing economies
tends to be of low and very variable quality
. In Pakistan, the largest learning gaps are between primary
schools. The divergence in English test scores between
government and private schools is 12 times that between
children from rich and poor families (Das, Pandey and Zajonc,
2006).
Another possible contributor to the lack of impact evidence for
knowledge capital is the central contribution of the state in
schooling. Variations in the effectiveness and magnitude of
state schooling spending, together with the way in which taxes
are levied to pay for it, can even create a negative correlation
with economic growth (Blankenau and Simpson, 2004). Public
spending might crowd out private spending on education.
Moreover, in the short-term, increasing the proportion of the
potential workforce in full time education reduces the
workforce and may be expected to lower per capita output. Not

29. surprisingly then, the macroeconomic evidence is unclear about
the effects of public education expenditures on economic
growth.
National economies are likely to be especially diverse in the
supply and demand for human capital because of distinctive
institutions. Yet most empirical research has been concerned
with cross-sections or panels of large numbers of countries,
thereby ignoring economy-level institutional differences
. National time series studies offer a way of eliminating or
reducing such heterogeneity (Durlauf, Johnson and Temple,
2004). For this reason the present paper tests and estimates a
time series model of human capital and economic growth for
Pakistan over the period 1960-2003. As a low income economy
that has invested relatively little in human capital over the past
40 years, Pakistan is an especially helpful case for
understanding the relationship with economic growth (Husain,
Qasim and Sheikh, 2003)
.
Most econometric research on human capital in Pakistan has
entailed estimating Mincer (1974) earnings functions on micro
data. Nasir and Nazli (2001) find each year of education brings
approximately 7 percent (private gross) return for wage earners.
Another study by Haroon et al. (2003) estimated that the
maximum private gross return (16 percent) is associated with
higher secondary education. Their results also indicate that
private payoffs from primary education declined during the
previous decade, while returns to higher secondary and tertiary
education rose. Recent research on rural Pakistan by Behrman et
al. (2008) shows that ‘social’ and private rates of return to low
quality primary schooling versus no schooling were 18.2
percent and 20.5 percent respectively
. They also estimated that ‘social’ rates of return to high-quality
versus low-quality primary schooling in rural Pakistan were
13.0 percent. Unfortunately, studies of this type are unlikely to

30. capture all indirect benefits of human capital for economic
growth, especially the stimulus to technology development and
adoption. Therefore, there is a strong case for supplementing
them with macroeconomic studies of rates of return, as
attempted here.
The paper models the impact of human capital on Pakistani
economic growth, provides estimates of social rates of return to
human capital in Pakistan, and assesses the policy implications
of the findings. Section I presents the theoretical framework of
the study, setting out the production function and rate of return
approach. Section II outlines the experience of human capital
investment and development of Pakistan since 1960, with some
international comparisons. Section III elaborates the
measurement of variables and estimation procedures, explaining
why the Johansen approach is necessary. Section IV presents the
empirical results and section V discusses the sources of growth
implied by the analysis of the preceding section.
2. Theoretical Framework
One reason for endogenous growth (in Rebelo, 1991) is that
human capital is embodied in labor. This implies that a worker’s
improved human capital boosts their productivity but cannot
benefit another worker in the same way. The total amount of
human capital, H, in an economy is the product of the number of
workers and their average embodied human capital. If L is
number of workers, the total human capital input is the flow of
services from L(H/L) = H. More workers without any human
capital add nothing to output, so a growing workforce in itself
will drive down output per head at the rate at which it grows.
Constant returns to all three factors are equivalent to constant
returns to human and physical capital alone.
It follows that with constant returns, increased investment in
human and physical capital induced by more benign policies,

31. can permanently raise the growth rate of an economy. The
steady state growth of output and the two types of capital are
obtained by substituting both savings/investment rates into the
production function. Ignoring depreciation, if savings and
investment in human and physical capital increase from 5 to 10
percent of output, the steady state growth of output and capital
rises from 5 to 10 percent. The ratio of human to physical
capital in the steady state will not change because their relative
accumulation rates are unaltered.
Human capital in a neoclassical model has less dramatic but
still fundamental effects. A human capital-augmented Cobb-
Douglas production function consistent with the estimates of
MRW has coefficients of one-third on each of the three factor
inputs; a one percent increase in both human and physical
capital increases output by only two thirds of a percent.
Accumulation at a constant proportion of output therefore adds
less and less to output until the steady state is reached, in the
absence of technical progress. Hence the neoclassical model
must include exogenous technical progress if it is to explain
economic growth in the long run.
The disembodied human capital of MRW (equation 8) implies
that a one percent increase in the work force has a greater
positive effect on output than a one percent rise in human
capital per worker. With H unchanged, greater L boosts output
even though H/L falls. Where Y is real output, A the technology
level that shifts exogenously, K physical capital and 0<α, β, γ0
<1 parameters, the neoclassical (Cobb-Douglas) production
function is:
Y = A K( L( H
0
g

32. = A K( L(+
0
g
(H/L)
0
g
(1)
For Pakistan, and many developing countries with high
population and workforce growth, this disembodied model is
more optimistic than an endogenous growth Cobb-Douglas
production function specification, discussed above, of:
Y = A K( H
0
g
= A K( (L (H/L))
0
g
(2)
In a low income open economy, technology transfer is likely to
be a major source of growth. The scope for transfer will depend
on the technological progress of the leaders in the world
economy, below assumed to advance at a rate given by the
technological frontier economy’s Total Factor Productivity

33. index (F). But technology can only be transferred if an economy
has the absorptive capacity.
Benhabib and Spiegel (1994) conclude that international
technology spillover rates depend on levels of education in the
follower countries. So a plausible formulation for a poorer
economy allows greater technical progress the higher is the
human capital that promotes this capacity. The gap between the
follower economy’s technology (A) and the leader’s (F) depends
upon the follower’s average human capital and the level of the
leader’s technology. Taking logs:
ln A- ln F = (γ1ln(H/L)-1)lnF + lnA0
(3)
Technical progress, F, is exogenous (neoclassical) to the
domestic economy, but the impact of the technology is
endogenous. Substituting (3) into the log of (1) shows that there
is a complete offset to the rising human capital elasticity with
world technical progress; the labor elasticity of output falls as
the world technological frontier extends.
LnY = lnA0 + (γ0 +γ1 lnF)lnH + α ln K + (β- γ0- γ1 lnF) lnL
(4)
With the endogenous growth production function, β=0, and the
labor output elasticity is the same as the human capital output
elasticity. An economy with high workforce growth and weak
human capital investment will increasingly miss out as the
world technology frontier advances. If L actually grows faster
than H, output growth on this account is progressively negative.
When, as in (4), human capital supports the absorption of world
technology, as well as being a factor of production, the excess
of social over private returns may be substantial. Regardless, in
a relatively poor economy the returns to factor inputs, including
human capital, should be high because of their scarcity.
Unfortunately poor quality schooling and an inappropriate

34. syllabus may lower the return to education as a social
investment, but as Behrman et al (2008) have shown, even these
returns can be high in Pakistan. However, if education is merely
a signal, rather than an investment in human capital, private
returns may be high although social returns could be low. For
this reason, and because of the technological spillover, macro
estimation of social rates of return provides information not
available from the more common micro studies.
With the production function assumed in the present model,
rates of return to human capital per worker, as measured by the
marginal product, are higher the lower is an economy’s ratio of
human capital per worker to output. The full return to human
capital includes the technology absorption component γ1ln F/
((H/Y).
(∂Y/∂H) = ((0+γ1ln F)/ ((H/Y)
When economic development raises the ratio of human capital
to output, the rate of return will be driven down. But if world
technical progress, F, is faster than the rise in the human capital
output ratio, returns will rise.
Whether optimal investment in human capital is achieved might
be inferred from the principle that in an efficiently functioning
economy, at the margin returns to human and physical assets
will be equalized. With human assets, the inability to
appropriate returns often deters optimal investment, and thereby
allows persistent higher marginal returns, in the absence of
adequate investment by non-profit institutions. If the return on
comparable alternative physical assets, or on comparable human
capital in other economies is known, the measure of
underinvestment, the (excess) marginal rate of return on human
capital, can be found from the human capital stock to output
ratio and ((0+γ1ln F).
3. The Pakistani Economy Since 1960

35. Consistent with the endogenous growth model, in conjunction
with a broad policy or environmental shift, Pakistan’s economy
experienced an apparent permanent increase in the growth rate
by the 1960s. Pakistan’s average annual real GDP growth rate
of 5.3 percent since then has not matched those of the East
Asian miracle countries. Yet, per capita GDP growth surpassed
that of the typical developing country (1.3 percent since the
1960s) with an annual average rate of 2.6 percent.
Three groups of Asian countries, now classified as East Asian
rapid growers, South Asian developing and Asian least
developed, in many respects were at a broadly similar level of
economic development in 1960. But by the end of the
millennium, there were wide gaps in their per capita incomes.
Their human capital endowments, both in terms of education
and health, also were hugely different.
In the early 1960s, Pakistan was seen around the world as a
model of economic development. Many countries sought to
emulate Pakistan’s economic planning strategy and one of them,
South Korea, copied its second Five Year Plan, 1960-65. In the
early 1960s, the per capita income of South Korea was less than
double that of Pakistan (Maddison, 2001). But South Korea
became by far the more developed, with GNI per capita in 2006
of $22990 compared with Pakistan’s $2410, using purchasing
power parity (World Bank, 2007).
A possible reason for the divergence, consistent with the
fundamental contribution of human capital, is that literacy rates
for East Asian developing countries in the early 1960s were as
high as 71 percent for the Republic of Korea, and 68 percent for
Thailand, while Malaysia achieved a rate of over 50 percent. On
the other hand, in all other Asian least developed countries and
South Asian developing countries, the literacy rate was low;
only 9 percent for Nepal and 16 percent for Pakistan (Table 1).

36. After three decades, during which this group of Asian countries
somewhat improved their human capital, literacy rates are still
below 50 percent. By contrast, literacy in South Korea reached
98 percent and Malaysia managed a rate of about 90 percent
(World Bank, 1982; UNESCO, 1999).
Table-1: Human Capital Measures for Pakistan, 1960-2005
Years Indicator
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
Primary Schooling Enrollment (% of Age Group)
20.4
27.4
30.3
38.2
32.1
35.8
47.5
57.3
60.5
68.1
Secondary Schooling Enrollment (% of Age Group)
3.4
4.6
5.7
7.0
6.4

37. 7.3
9.6
12.2
11.6
12.0
Literacy Rate
16.7
16.8
20.9
24.3
26.1
28.8
33.8
39.6
47.1
52.5
Public Spending on Education (% of GDP)
0.9
1.8
2.5
2.2
2.0
2.7
2.7
2.2
2.0
2.5
Public spending on health (% of GDP)
0.4
0.6
0.5
0.6
0.6
0.8
1.0
0.7

38. 0.7
0.6
Life Expectancy
43.9
46.7
49.4
52.3
55.1
57.4
59.1
60.9
63.0
66.0
Source: State Bank of Pakistan (2006), UNESCO Yearbooks
(Various Issues), World Bank (Various Issues).
Another potential contributor to the divergence is health.
Measured by life expectancy at birth across the three groups of
countries in the Asian region, health shows a similar pattern to
literacy. In the 1960s, life expectancy at birth was below 45
years in all Asian least developed countries and South Asian
developing countries. On the other hand, the East Asian
developing countries had life expectancies well over 50 years,
with the Republic of Korea achieving a figure of over 54 years,
followed by the 53 years of Malaysia and 51 years for Thailand
(World Bank, 1984). In the late 1990s, the Asian least
developed countries and South Asian developing countries
enhanced their life expectancy to more than 60 years, at least in
the case of Pakistan, India, Bangladesh and Bhutan. Yet the life
expectancy rate in both Malaysia and Korea is remains much
higher; of the order of more than 72 years, with Thailand
reaching a figure of 69 years.
Nonetheless human capital has grown in Pakistan. Table-1
shows that primary and secondary schooling enrolment in
Pakistan increased substantially in the years after 1960.
However public spending on education as a proportion of GDP

39. stopped rising on trend after 1970, while public spending on
health peaked as a proportion of GDP in 1990. Human capital
per head, as measured by the secondary schooling stock per
worker (lnsstpw, Figure-1), increased strongly in the 1960s and
in the second half of the 1980s. During the later 1990s the stock
fell; the endogenous growth model of the previous section
predicts adverse output consequences, for in 2005 the stock was
lower than in 1995.
Schooling, particularly in rural areas, remained problematic
despite land and other reforms during the 1960s. In 1962, four
tiers of government were introduced and each was assigned
responsibilities in both rural and urban areas, such as
maintenance of primary schools, public roads, and bridges.
Much military and economic aid was received and the capital-
labor ratio (lnkspw, figure 1) rose most rapidly in this decade.
But aid was reduced in 1965, when another war with India over
Kashmir broke out. Later the Tashkent agreement of 1966
mediated the conflict. The longer term impact of the war on the
economy though was severe, ultimately triggering a downturn in
real GDP per worker (lnrgdppw) and the employed labor force
(lnelf) between 1967 and 1968 (figure 1).
The 1970s were a difficult decade for some forms of human
capital accumulation and economic growth. A third war between
India and Pakistan in 1971, the upheaval associated with the
establishment of Bangladesh in January 1972, the first oil crisis
in 1974 and the populist and restrictive economic policies of
new political regime of 1971-77, all adversely affected the
economy. After 1973, Prime Minister Zulfikar Bhutto
nationalized basic industries, insurance companies,
domestically-owned banks, and schools and colleges. The
proportion of the workforce with secondary schooling fell in the
first half of the decade. Table 1 shows that school enrolments as
a proportion of the relevant age group were lower in 1980 than
in 1975 and figure 1 reveals a stagnation of the secondary

40. schooling stock per worker (lnsstpw) in the 1970s.
Some incomplete structural reform efforts were implemented in
the 1990s. Output and employment fell between 1990 and 1991
but recovered the following year. The second half of the decade
was marked by economic uncertainty associated with heightened
domestic and regional political tensions. The 1998 nuclear
explosions and consequent sanctions, coupled with drought and
unsustainable debt, gave rise to macroeconomic instability.
Interest payments and military spending by the government
exceeded 50 percent of consolidated government spending,
shrinking the relative size of public sector development
spending, and leaving only limited resources for state-funded
education, health and physical infrastructure. External balances
deteriorated significantly and foreign reserves fell to
dangerously low levels (World Bank, 2002). Health spending as
a proportion of GDP (lnhegdp, figure 1) declined. According to
the model of the previous section, returns to human capital
should be very high because investment has been so low. But
resource misallocation could hold down returns in practice.
Figure-1: Pakistani Growth Variables 1960-2005 (Logarithmic)
7.6
7.8
8.0
8.2
8.4
8.6
8.8
9.0
60
65
70
75

41. 80
85
90
95
00
05
LNRGDPPW
6.5
7.0
7.5
8.0
8.5
9.0
9.5
60
65
70
75
80
85
90
95
00
05
LNKSPW1
2.4
2.6
2.8
3.0
3.2
3.4
3.6
3.8
60
65
70

42. 75
80
85
90
95
00
05
LNELF
-3.5
-3.0
-2.5
-2.0
-1.5
-1.0
60
65
70
75
80
85
90
95
00
05
LNSSTPW
-1.2
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
0.2
60
65
70

43. 75
80
85
90
95
00
05
LNHEGDP
-16
-14
-12
-10
-8
-6
-4
60
65
70
75
80
85
90
95
00
05
SSMFP
7.6
7.8
8.0
8.2
8.4
8.6
8.8
9.0
60657075808590950005
LNRGDPPW

44. 6.5
7.0
7.5
8.0
8.5
9.0
9.5
60657075808590950005
LNKSPW1
2.4
2.6
2.8
3.0
3.2
3.4
3.6
3.8
60657075808590950005
LNELF
-3.5
-3.0
-2.5
-2.0
-1.5
-1.0
60657075808590950005
LNSSTPW
-1.2
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
0.2
60657075808590950005

45. LNHEGDP
-16
-14
-12
-10
-8
-6
-4
60657075808590950005
SSMFP
Since 1999, the government committed itself to reversing
Pakistan’s poor economic performance with a major
macroeconomic stabilization effort and structural reforms aimed
at strengthening microeconomic fundamentals. Employment
(lnelf) growth faltered between 1999 and 2000 but quickly
resumed. Real output (lnrgdppw) fell for two consecutive years
but in 2002 jumped to a previously unattained height (figure 1).
Fiscal measures included the privatization of state-owned banks
and strengthening the role of State Bank of Pakistan, together
with reform of telecoms and trade policy. Expansion of the U.S.
and E.U. textile quotas further helped to stabilize and revive the
economy. Economic growth exceeded the 5 percent mark in
2003 for the first time since the mid 1990s, and reached 6
percent in 2004 (World Bank, 2006).
In the modeling below we assess what difference these changes
have made.
4. Measurement, Specification and Estimation
Assessing how policy shifts influenced the formation of
knowledge human capital first requires definition and
measurement. Only proxies, such as the number of graduates,
average years of education, literacy rates, school enrolment
ratios or proportion of the population that has completed

46. schooling at different levels of education, are available. They
do not fully match the concept of knowledge capital.
The production function model postulates a flow of productive
services from the human capital stock. More output is generated
by an increase in the human capital, so long as the service flow
is proportional to the stock. The increase in the stock is gross
investment minus depreciation. So for example, considering the
stock of workers with secondary education, more secondary
educated young people may enter the workforce every year, but
both secondary educated and uneducated people leave each year
as well. It is the difference between these two magnitudes that
is relevant for economic growth, though for the level of gross
income, simply the flow generated by the stock of secondary
educated workers is pertinent.
When considering year to year variations in human capital,
these measurement issues matter particularly. In the case of an
increase in the proportion of the relevant age group attending
school from one year to the next, while the eventual effect may
be to increase human capital services, the immediate effect is to
reduce the supply of unskilled labor. If they would have been
productive, this will have a negative impact on output, even
though eventually there will be a greater positive effect.
Given the limited availability of the data, the proxies for human
capital here considered are as follows.
· The stock of human capital at the secondary level of education
is defined as the percentage of the workforce that has completed
secondary education (H). Estimates are constructed from
benchmark figures based on Barro and Lee (2000). Following
the perpetual inventory method, net flows of graduates with
secondary education are added to benchmark stocks to generate
an annual series.

47. · Health expenditure as a percentage of GDP is the measure of
health capital services (HE).
The U.S. (Bureau of Labor Statistics, 2007) multi-factor
productivity index is taken to measure the shift in the world
technological frontier. Data are annual and cover the period
1960-2003. Sources of data and a description of variables are
given in the appendix.
The demand for human capital is derived from the production
function and profit-maximizing behavior, but the supply of
human capital is typically dominated by non-profit
organizations, especially the state. With forward-looking
behavior, the supply of human capital might be expected to
respond to future demands (derived from GDP), as well as GDP
depending upon human capital. Although interest centers on
measuring the contribution of inputs to output, output may have
a causal effect on inputs as well. For example, output growth
may stimulate investments in physical capital and may also
augment human capital by facilitating increased schooling and
income (see for example Bils and Klenow (2000)). This bi-
directional causality creates a correlation between the
independent variables and the equation error term that renders
OLS estimates of the production function coefficients
inconsistent, an important reason for using the Johansen
approach below.
The parameters of the production function measure a long run
relationship, and the time series from which the function is to
be estimated are likely to be non-stationary. Regression models
using such series may give rise to ‘spurious regressions’, even
when the series are integrated of the same order. A necessary
condition for a regression estimate to be a genuine economic
relationship is that the variables are cointegrated, in which case
the residuals will be stationary.

48. Parameter estimates of a cointegrating equation are
‘superconsistent’; the distributions are asymptotically invariant
to measurement error and simultaneous equation bias. However
they may be also subject to small sample bias and have non-
standard distributions. This last characteristic means the usual
tests of significance do not apply. Moreover there are possibly a
number of different cointegrating relations among a group of
cointegrated variables. For reasons already stated, all the inputs
into the production function can be endogenous, in which case
there may be a cointegrating equation and an error correction
model for each input, in addition to the production function.
For such circumstances, Johansen (1991, 1995) proposed a
maximum likelihood method for estimating and testing for the
number of cointegrating equations, as well as their speeds of
adjustments. The approach is to test the restrictions imposed by
cointegration on the Vector Error Correction model involving
all the series under consideration. In this system, the dependent
column vector is the first difference of output and all the inputs
of the production function (∆Zt). On the right hand side is the
column vector of these variables lagged (here we consider only
one lag, ∆Zt-1) and the associated coefficients (Γ). Also there is
a column vector of the lagged levels of the production function
variables (Zt-1). Matrices of adjustment coefficients (a) and of
cointegrating coefficients (b) premultiply this vector. The
standard errors of the coefficients in the cointegrating equations
of the Johansen method have conventional distributions and so
may be used for the usual significance tests.
With a one period lag the system is:
∆Zt = Γ∆Zt-1 + abZt-1+ et
where et is a vector of error terms.
5. Empirical Results
The elements of the Z vector are obtained from (4) in section I,
modified to include two human capital variables, secondary

49. education (H) and health spending (HE):
Y/L = A0 F
)
/
ln(
1
L
H
g
(K/L)( L
1
0
-
+
+
g
b
a
(H/L)
0
g
(HE/Y) φ
(5)
The production function (5a) shows how the parameters of (5)
are related to the output elasticities:
LnY = lnA0 + ((γ0 +γ1 lnF)/(1+ φ))lnH + (α/(1+ φ))ln K + ((β-
γ0- γ1 lnF)/(1+ φ)) lnL + (φ /(1+ φ)) ln HE

50. (5a)
When γ1>0, the growth of the technological frontier F increases
the human capital elasticity, but reduces the labor elasticity, of
output. The education human capital measure influences
absorptive capacity, and therefore interacts with the
technological frontier. The health human capital variable only
affects productivity directly.
Testing for Unit Roots
The degree of integration of each series in (5) is determined
with Augmented Dickey Fuller (ADF) tests statistics, reported
in table 2. Trend and additional lags were included when they
were statistically significant. The ADFs show that all the
variables considered are integrated of order one at the one
percent level except Lnsstpw, which is significant at the 5%
level. We cannot reject the hypotheses that all the variables are
stationary in the first difference, and integrated of order I(1). So
the series may be used to estimate co-integration regressions.
Co-Integrating Equations
The next stage is the estimation of the long-run relationship.
The lag length for the Johnansen VAR is chosen to maximise
the AIC. With one lag on the first differenced variables, AIC is
-21.3 and with two lags it is -22.4. With increased lag length
the AIC becomes smaller, indicating that one lag is the
preferred specification.
The cointegrating model specification that fits the data and the
theoretical constraints is one with a linear deterministic trend in
the data, and an intercept, but no trend in the cointegrating
equation(s). The trace and max-eigen tests for numbers of
cointegrating vectors reject the hypothesis of none, but not at
most one (Table 3). So the data are consistent with one
cointegrating vector.
Table-2: Augmented Dickey Fuller (ADF) Tests

51. Variable
Model
Adf Stat
Lags
Levels
Lnrgdppw
C and tr
-0.766
2
Lnkspw
C and tr
-2.137
2
Lnsstpw
C no tr
-1.801
1
Ssmfp
C and tr
-3.460
2
Lnhegdp
C no tr
-2.213
1
Lnelf
C and tr
-4.02
1
First Differences
Lnrgdppw
C and tr
-4.634
1
Lnkspw

52. C no tr
-3.968
2
Lnsstpw
C and tr
-3.823
2
Ssmfp
C and tr
-4.083
2
Lnhegdp
C no tr
-5.157
1
Lnelf
C no tr
-6.048
1
Lnrgdppw: Log of real GDP per worker, ln (Y/L)
Lnkspw:
Log of real capital stock per worker, ln(K/L)
Lnelf:
Log of employed labor force, ln L
Lnsstpw:
Log of human capital stock at the secondary level of
education per worker, ln(H/L)
Lnhegdp:
Log of government expenditure on health as
percentage of GDP, ln(HE/Y)

53. Ssmfp:
ln(H/L)*lnF (where F is U.S. multifactor productivity)
C:
Constant
tr:
Time trend
Table-3: Unrestricted Cointegration Rank Test
Sample: 1960 2005
Included observations: 42
Test assumption: Linear deterministic trend in the data
Series: LNRGDPPW LNKSPW1 LNSSTPW LNHEGDP SSMFP
LNELF
Lags interval: 1 to 1
Hypothesized
No. of CE(s)
Eigenvalue
Trace Statistic
5 Percent
Critical Value
Max-Eigen
Statistic
5 Percent
Critical Value
None **
0.658140
104.1756
94.15
45.08086
40.07757

54. At most 1
0.471896
59.09474
68.52
26.81542
33.87687
** denotes rejection of the hypothesis at the 0.05 level by both
Trace and Max-Eigen Statistics.
The normalized cointegrating vector (equation 6) is
theoretically consistent with an aggregate production function
including human capital, although the coefficient on physical
capital/labor ratio is small, and on the margins of statistical
significance. The other coefficients are more than three times
their standard errors (in parentheses).
ln (Y/L) = 0.175 ln(K/L) + 0.310 ln (HE/Y) + (0.447 ln MFP -
1.767) ln(H/L)
(0.092) (0.038)
(0.110) (0.498)
+ 0.357 ln L - 6.226
(6)
(0.095)
Log likelihood
518.3626
The adjustment coefficients, (a), of the right hand side variables
of (6) are not significantly different from zero (not reported),
consistent with these variables being weakly exogenous.
Advances of the world technological frontier (F), measured by

55. the coefficient (γ1) (on Ssmfp or ln (H/L)lnMFP in equation 6),
raise the output elasticity of secondary schooling human capital
variable from 0.08 in 1960 to 0.25 in 2005
. Health expenditure has an elasticity (φ) of 0.24 and the capital
elasticity (() is 0.13. The total human and physical capital
elasticity of 0.62 is therefore well below unity in 2005. The
labor elasticity is large, at 0.82 in 1960, falling to 0.65 in 2005
. Adding all the input elasticities implies increasing returns to
scale for all factors together throughout the period.
Implied Rates of Return
The return to educated workers in 2005 can be compared with
that discussed by Bassanini and Scarpetta (2001) and by Sianesi
and Van Reenen (2003); that is, increasing average education in
the population by one year raises output per head by between 3
and 6 percent, and returns are higher for LDCs than for OECD
economies. To do so, it is necessary to assume that a rise in the
proportion of the workforce having attained a certain level of
education can be directly translated into an increase in the
average number of years of education in the workforce. Since
there is no control for primary education in the model, the
secondary education impact must be assumed to include years of
primary education as well, that is, a total of ten years of
education. For the comparison, the 2005 value of the proportion
of the workforce with secondary education of 0.195 is
considered. One extra year of education for the whole workforce
translates into 10 years of education for one tenth of the
workforce. Ten percent amounts to a (10/19.5 =) 0.513 increase
in the workforce with secondary education. With an elasticity of
0.25, a 51.3 percent increase in the workforce with secondary
education raises output per head by nearly 13 percent. This falls
well outside the Sianesi and Van Reenan range for the OECD,
indicating substantial under-investment in education in
Pakistan.
To compare with returns to primary education excluding

56. spillovers reported earlier, secondary education must be
assigned a financial cost. From section 1, (∂Y/∂H) = ((0+γ1ln
F)/ ((H/Y), and ((0+γ1ln F) has been estimated at 0.25 for 2005.
If the secondary education financial returns, including
spillovers, are equal to the Behrman et al (2008) estimated
returns to poor quality primary education (20 percent), the
secondary educated human capital stock to income ratio in 2005
was (0.25/0.2=) 1.25.
Turning to the second human capital measure, a rate of return
from health investment may be obtained directly. Total health
spending can be considered as the flow of services from a health
human capital stock. A health investment ratio (0.6%) in the
year 2005 (Table 1), and the coefficient of (0.31/1.31=) 0.24
implies an even higher return than for education, of
(0.24*0.006-1 =) 39 percent
. As with secondary education, this not only constitutes a very
high return to an investment judged by commercial standards,
but also indicates an enormous unmet requirement for health
spending.
6. Sources of Growth
Proximate sources of Pakistani economic growth can be
obtained from a decomposition of the production function (6).
Table 4 gives the decadal average annual growth rates of inputs
and output. The variation between decades has already been
noted, but the decline in human capital inputs in more recent
decades is very obvious in the table and remarkable. Both health
and schooling input growth rates become negative from the
1990s, and, as a consequence, so to does the absorption of
technology variable (technology frontier shift*human capital).
Yet the foreign (U.S.) technology frontier shifted faster, and
therefore the possibilities for absorption were greater, in most
recent years.
Table-4: Pakistani Economic Growth Data 1961-2005
Actual Annual Average Growth Rates

57. Real GDP / Worker
Real Capital / Worker
Secondary Schooling Stock / Worker
Health Expenditure / GDP
Technology Frontier Shift* Human Capital
Labour Force
Tech Frontier
1961-70
3.73
7.42
7.79
2.19
17.15
2.61
1.53
1971-80
2.29
2.97
0.88
3.08
2.45
2.42
0.62
1981-1990
2.63
3.09
5.82
1.91
14.93
1.95
0.57
1991-2000
0.76
1.89
-0.52

58. -1.79
-4.08
2.19
0.87
2001-5
-0.38
-3.24
-4.16
2.36
1.65
The following growth attribution (Table-5) is derived from the
production function estimate, equation 3.
Table-5: Human Capital and Pakistani Economic Growth 1961-
2000
Actual / Worker Real GDP Annual Average Percentage Growth
Model Predicted
Model Predicted due to Human Capital
1961-2003
2.73
2.34
0.41
1961-70
3.73
3.42
0.57
1971-80
2.29
2.32
0.74
1981-1990
2.63
3.53

59. 2.13
1991-2000
0.76
0.12
-1.12
The results in Table 5 indicate that, over the whole period 1961-
2003, just under one-fifth (0.41/2.34) of (predicted) growth in
output per worker was due to human capital as measured here.
Human capital has been responsible for more economic growth
in successive decades from the 1970s until the 1990s. The 1980s
appears to have experienced the strongest impact of human
capital, accounting for 60 percent of predicted economic
growth. Most extraordinary for a developing country is the
massive negative contribution of human capital to growth in
recent years, because of falling inputs
.
Strong growth during the 1960s was largely due to Pakistan’s
capital accumulation. During the 1980s, economic growth was
almost as high, but based on a greater human capital
contribution. Later, economic mismanagement in general and
fiscally imprudent economic policies in particular, caused a
large increase in the country's public debt and reduced the input
of human capital, leading to slower growth in the 1990s. No
clearer indication of underinvestment in human capital can be
found than the evidence of this decade.
7. Conclusion
Economic growth in Pakistan for practical purposes is
endogenous, influenced by government policy. Technical
progress is driven by the ability to absorb foreign technology
and the rate of absorption depends upon knowledge human
capital. Thus the movement of the foreign technological frontier
and the stock of human capital (secondary school graduates) are
increasingly critical for economic development. Yet the return

60. to years of secondary education indicates substantial
underinvestment in knowledge human capital. The marginal
output generated by secondary education far exceeds the range
calculated for OECD countries. Unlike micro estimates, the
macro estimate of this paper takes into account spillovers; it is
a wider measure of social costs, and therefore is more
appropriate for policy guidance.
The high return is found despite the poor average quality of
education shown by, for instance, large numbers of schools
lacking buildings and widespread teacher absenteeism (Human
Rights Commission, 2005 pp. 243-4). Higher quality education
may be expected to achieve greater returns. The extremely large
rate of return to health spending of 39 percent suggests such
outlays are sound investments, quite independently of their
consumption value. It may also indicate that the quality of
health care needs less of a boost than does the quality of
education.
Compared with the MRW implied production function, the
output elasticity of human capital is low
, and the elasticity of ‘raw’ labor is high. This may reflect
deficiencies in the measurement of human capital. But it may
capture shortcomings in the Pakistani education system as well.
A decomposition of the sources of growth implied by the
estimated cointegrating equation shows that even the incomplete
measures of human capital employed in this study explain just
under 20 percent of the increase in output per head during the
years 1961-2003. The striking feature of this growth analysis is
the impact of human capital policies from the 1990s. Rapid
labor force growth was not matched by expansion of secondary
education, so that the proportion of the educated workforce
declined. As the opportunities for benefiting from world
technology increased, Pakistan’s ability to reap the advantages
deteriorated.

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APPENDIX
Table-A: Description of variables and data sources
Variables
Definition and Unit of Measurement
Data Sources
RGDPPW
Real GDP per worker (In US $ per worker in 2000 Constant
Prices)
Penn World Table 6.2
ELF
Employed labour force (in million)
Handbook of Pakistan Economy by Sate Bank of Pakistan, ILO
yearbook statistics
KSPW
Capital stock per worker (in millions)
Miketa, A., 2004: Technical description on the growth study
datasets. Environmentally Compatible Energy Strategies
Program, International Institute for Applied Systems Analysis
(IIASA), Laxenburg, Austria, October 2004.
http://www.iiasa.ac.at/ECS/data_am/index.html
SST
Secondary Schooling Stock (percentage)
Benchmark figures are taken from Barro and Lee (2000) and
following the perpetual inventory method, we constructed flows
of adult population that are added to bench mark stocks.
LITERACY
Literacy (percentage)

66. Economic Surveys of Pakistan for different years, World tables
by World Bank,
Handbook of Pakistan economy by State Bank of Pakistan, Fifty
year of Pakistan Statistics by Federal Bureau of Statistics (FBS)
Pakistan, and Statistical yearbooks by UNESCO for different
years.
HEGDP
Total health expenditure as % of GDP (HEGDP)
Handbook of Pakistan Economy by State Bank of Pakistan
MFP
Multifactor Productivity
U.S., Bureau of Labor Statistics, Office of Productivity and
Technology (May 2007 publication)
RHE
Real health expenditure (in millions)
Handbook of Pakistan Economy by State Bank of Pakistan
LER
Life Expectancy Rate
Handbook of Pakistan Economy by State Bank of Pakistan and
World Bank
TELE1000
Telephone in use (000 people)
Statistical Yearbooks by United Nation for different years
Education Expenditure
Government Expenditure on Education as % of GDP (GEEGDP)
Economic Surveys of Pakistan for different years, Statistical
Yearbooks by United Nation for different years, Handbook of
Pakistan economy
Table B: Descriptive Statistics
Statistics Variables
Mean
Standard Deviation
LNRGDPPW
8.379

67. 0.382
LNKSPW
8.640
0.645
LNELF
3.212
0.329
LNLITERACY
3.341
0.367
LNSST
1.421
0.667
LNHEGDP
-0.433
0.309
LNMFP
4.471
0.117
Table-C: Partial Correlations
Variables
LNRGDPPW
LNKSPW
LNELF
LNSST
LITERACY
LNHEGDP
LNRGDPPW
1.000
0.981
0.980
0.969
0.961
0.802
LNKSPW

68. 1.000
0.961
0.975
0.936
0.755
LNELF
1.000
0.937
0.981
0.765
LNSST
1.000
0.924
0.713
LITERACY
1.000
0.711
LNHEGDP
1.000
* Comsats Institute of Information Technology, Islamabad,
Pakistan & Cardiff Business School, Cardiff University, UK.

69. ** Cardiff Business School, Cardiff University.
� For instance from 1820 to 1929 Maddison’s (1995) estimates
show that Pakistan’s real GDP per head grew at an average rate
of 0.31 percent. Then incomes doubled in the course of the
1960s, and high growth by historical standards became
sustained in subsequent years, albeit at varying rates.
� Tested at the end of the third grade, only 31 percent of
Pakistani primary school children could correctly form a
sentence with the word “school” in the vernacular (Urdu) (Das,
Pandey and Zajonc, 2006).
� This may be an explanation for Shapiro’s (2005) surprising
finding of a negative international technology diffusion effect
for East Asia.
� A previous time series study of Pakistan industrial’s growth
1973-1995 (Dutta and Ahmed, 2004) investigated the impact of
secondary school enrolment, but there is some question about
the signs of the variables in the cointegrating vector.
� ‘Social’ here does not include spillovers but only the public
(as well as private) financial costs of providing education.
� ((0 + γ1 lnF) / (1 + φ) = ((4.19076 * 0.447) - 1.767) / 1.31 for
1960.

70. � (β - (0 - γ1 lnF) / (1 + φ) = ((1.357 - 0.175) / 1.31) - 0.08 =
0.82 for 1960, to ((1.357 -0.175) / 1.31) - (((4.6923 * 0.447) -
1.767) / 1.31) = 0.65 for 2005
� (∂Y/∂HE)(HE/Y) = 0.31/1.31, (HE/Y)=0.006, so ∂Y/∂HE =
0.236/.006 =39.44.
� There is a substantial error in the decadal predictions for
growth.
� MRW’s implied result is about one third for human capital,
and it should be noted that by excluding technical progress, as
they do, a similar result can be obtained here.
_1274802552.unknown
_1274802757.unknown
_1274802843.unknown
_1274802697.unknown
_1274802511.unknown
Chapter 15 in S Broadberry and K Fukao eds. Cambridge
Economic History of the Modern World (forthcoming)
Underlying sources of growth: institutions and the state
James Foreman-Peck and Leslie
Hannah
Two characteristics differentiate today’s rich
countries from many poor and middle-income ones: they are all

71. market economies run largely by capitalist corporations, and
most are representative democracies (oil-rich economies being
exceptions)[footnoteRef:1]. However, capitalist democracies
have widely differing commitments to tax redistribution, levels
of state ownership, health and welfare policies, or the balance
between protecting established property rights and interventions
to remedy the system’s perceived failings. Autocrats have also
promoted economic growth - President Xi of China follows a
long tradition - and have sometimes succeeded over a lower
range of GDP per head. However, economic growth eventually
seems to expand demands for participation: in the later
twentieth century military dictatorships of Taiwan, South Korea
and Spain liberalized and communist autocrats in eastern
Europe conceded free elections. [1: In 2018 no country that
was an autocracy (Polity IV definition, see note 10, below) had
an income per head of more than $15,000 if it was not heavily
dependent on fossil-fuel exports. Countries that were
autocratically ruled and did not have the option to export fossil
fuels were poor (Roser 2014).]
While democracy, capitalism and wealth are
correlated, the possibility and nature of causation among the
three is much debated. Major themes in the western literature -
pioneered by Nobel-prizewinning economic historian Douglass
North and enriched by many others[footnoteRef:2] - are when
these correlations emerged and how they are structurally
related. We follow this “new institutional economics” approach
here. Wealth-maximizing political institutions are hypothesized
to be inclusively representative, sometimes leading toward full
democracy, combined with respect for minorities. Arguably
political and economic ‘open access’ - representative political
institutions and ready access to incorporation or similar
enterprise forms - are mutually reinforcing and conducive to
high living standards, broadly shared (North Wallis and
Weingast 2009, hereafter NWW). [2: For instance, North and
Thomas 1973; Rosenberg and Birdzell 1986; Ostrom 1990;

72. Engerman and Sokoloff 2012; Acemoglu and Johnson 2005;
Haber North and Weingast 2008; Acemoglu and Robinson 2012;
Lamoreaux and Wallis 2017; Alston et al 2018.]
Institutions are the patterns of interaction that govern
and constrain the relationships of individuals; the ‘rules of the
game’. Relevant rules include written laws, formal social
conventions, informal norms of behaviour and shared beliefs
about the world. This variety ensures that institutions are often
difficult to define precisely. The institutional form of some
states includes the rule of law, in others the rule of arbitrary
terror. Institutions are often hard to create and highly persistent.
Institutional economics attempts to understand why and under
what conditions they emerge.
Institutions facilitating transitionsfrom limited to open access
must allow the circulation of elites. Elites may be elected but in
a low income, feudal society such as contemporary Pakistan
they can still at best be a ‘selectorate’. New people must be
allowed access to power, changing the social structure, but
without too much collateral damage to society. Peaceful
transitions therefore may entail outgoing elites being permitted
to hold on to their wealth, so they abandon power without
violence. The condition of peaceful circulation in turn needs
acceptance of a rule of law for elites that offers them a form of
legal protection. A second condition is that there must be
substantial numbers of independent, perpetually lived
organizations, such as corporations; these can undertake more
economic activities than finite life organizations. Political
control of the military is an essential third condition. The
failure of the military coups in 1981 and 1982 marked the
success of the Spanish transition to open political and economic
access. Control is essential to reduce threats of violence and
trade disruption and cutting the risk of expropriation by the
military increases the benefits of markets. When economies and
societies satisfy these three conditions and become wealthier,
the open access transition and sustained economic growth are

73. more likely to occur (NWW 2009).
The “Washington consensus” - or the
“Manchester School” as similarly free market
liberal[footnoteRef:3] ideas were known in the nineteenth
century - never goes uncontested (Chang 2002, Stiglitz
2003).[footnoteRef:4] It is now concretely expressed in the
World Bank’s detailed policy prescriptions and “Doing
Business” index (www.worldbank.org). The “good” institutions
it recommends include democracy, an independent judiciary,
uncorrupt and efficient bureaucrats, secure property rights, a
politically-independent central bank, easy and cheap business
registration, transparent and market-orientated corporate
governance, and a responsive legal system (with common law
systems judged to perform well on this dimension). [3: We use
the term “liberal” in its original European - or modern “neo-
liberal” - sense to mean anti-authoritarian supporters of
individual freedom, free markets and a limited state, not in the
modern American English sense (broadly the opposite).] [4:
Before 1914, the Manchester School was similarly contested by
Marxists, American institutionalists, German
Kathedersozialisten, British Fabian socialists and many others.]
A frequent problem in understanding their role today is that
institutions have often existed for decades. They have
sometimes evolved with minimal formal deliberation (the
unwritten British “constitution”) rather than being consciously
constructed (the American constitution, though that too
evolved). It is sometimes difficult to identify origins, causes
and effects separately from those of related institutions, or
cultural background, with which they interact. For example,
Haber, North and Weingast (2008) contend that correlations
between favourable economic outcomes and Anglo-American
common law systems are not causal: both the outcomes and
common law judgments are triggered by third factors,

74. representative political institutions and tolerably equal
economic access.
Some institutions - such as patents, education
and demographic norms - are discussed in other chapters. We
pay special attention here to the development of business
incorporation and its relation to evolving representative
government. The capitalist corporate form - and some state-
owned substitutes - came to dominate enterprise in almost all
post-agrarian societies by the end of the twentieth century and
political institutions played a key role in this development.
NWW (2009) maintain that under the ‘natural state’ (a coalition
of elites), economic growth can take place but will be
eventually choked off as the basis of elite power comes under
threat. The transition to sustained economic growth requires the
transformation of both political and economic institutions, so
that they can become mutually supporting. Traditional - feudal,
monarchical, established religion, class- or caste-bound –
societies usually restrained political and economic open access.
Sometimes the move to more representative government
occurred because incumbent elites made mistakes that weakened
their hold on power (Treisman 2017). For those outside the elite
the overthrow of such systems in the name of “modernity” often
seemed a prerequisite for growth and development. In that
limited sense American and French revolutionaries
overthrowing monarchy and aristocracy, Lenin’s execution of
the Tsar and attacks on the bourgeoisie, and Maoist
revolutionaries undermining Confucianism and the Manchukuo
dynasty were all on the same page. All also seriously risked
oversimplifying (sometimes murderously) the problematic
transition to modernity.
We set the scene with a survey of economic and political
institutions in 1870 and the concentration of wealth in Western
Europe and North America. We go on to consider the experience
and institutional features of the first non-Western moderniser
after 1870, Japan. The third section summarises the non-market
institutions and state development from 1917 of the Communist

75. alternative states. This is followed by a brief account of the key
characteristics of the hybrid state-driven capitalist economies
that begin to appear after 1945. In each section we rely heavily,
but not uncritically, on the NWW framework to interpret the
relationships between economic development and political and
economic institutions.
I Economic and Political Institutions in 1870
In 1870 political economists - as institutional
economists were then called - had strong views on the
characteristics of desirable institutions and were confident they
were the cause, not merely the happy result, of prosperity. They
used Christianity and “civilisation” as synonyms:
“Christendom” meant the developed world (Mulhall 1881). A
leading sociologist, Max Weber, and many historians agreed
that religion - and especially the Protestant variety - had
promoted capitalist prosperity (Weber 1904, Butterfield 1931,
Tawney 1964) and there remain today some exponents of the
view that “good” or “poor” institutions are rooted in deep
national cultural traits such as religion (Landes 1999; Stulz and
Williamson 2003; McCloskey 2010; Djankov and Hauck
2016).[footnoteRef:5] Most Islamic countries have experienced
difficulties in growing rich (except on oil) and generally have
had autocratic governments (Kuran 2011). Yet economic growth
is now more widely shared by non-Protestant countries and rich
countries have become more agnostic. Religious institutions as
causes of national economic growth are accordingly less
prominent in today’s institutional economics than they were in
the past. [5: For a broader discussion of the interactions
between culture (generally learned informally from parents,
civil society or churches) and institutions (which are more
deliberate -and often political – creations), see Alesina and
Giuliano 2015.]
One obvious feature of the world of 1870 was how distant the
bulk of humanity were from the NWW ideal of ‘open access’ or

76. ‘inclusive’ institutions. Living standards were already high in
much of western Europe, north America and Australasia, where
governments fostered widespread (if imperfectly democratic)
participation in both dispersed capitalist corporations and
representative political assemblies. It was still a matter of
heated debate whether some institutions – like limited liability,
patents, or democracy - were aids to, or barriers to, economic
progress. Not until the early twentieth century did three rich
countries – Finland, Australia and New Zealand – introduce a
franchise close to that considered democratic today (including
women). Some, like France and Switzerland, did not do so until
after World War Two. One near approach to a more generous
definition of democracy - universal adult male franchise - in the
French Second Republic only demonstrated its dangers: it had
led in 1852 to the endorseement of the autocratic Napoleon III.
In the richest countries, statesmen either judged a wider
franchise undesirable, or, accepting it was inevitable, fretted
about ensuring broader commitment to the existing polity and
social hierarchy. They pressed for wider education, modest
social protections, or for restricting radicals, labour unions and
(within empires) native independence movements.
Most of the world’s population lived under absolute hereditary
rulers, subject to few formal restraints (Russia, China, Japan,
Brazil, the Ottomans) or direct rule by a controlling power
(British India, French Indo-China, American Alaska). In the
developed world, most states (including the UK, Germany,
Italy) were monarchies, though with some representative
government and serious restraints on the arbitrary exercise of
regal power. Only in America (north and south) did republics
predominate. Nation states were the basic institutional
framework for political and economic development: their
governments were the authors of legislation and incubators of
formal institutions. People, capital, goods and ideas moved
across national borders, but they travelled more easily within
those borders, especially borders that enclosed linguistic or
culturally homogeneous communities. Newspapers, political

77. activities, social interactions, education systems, transport
improvements and laws increasingly reinforced national links.
Mill (1861) argued that representative government “was next to
impossible in a country made up of different nationalities.” The
Hapsburg monarchy, though opting not to merge its nine million
German-speakers into the new German confederation of 1870-
71, did separate the government of its constituent Austrian and
Hungarian kingdoms. Mill’s point was important, as nation
states consolidated, but also raised as many questions as it
answered: were the Irish British? were Poles and Alsatians
German? were Muslims or Buddhists Indian? could one really
create a nation out of US polyglot immigrants, when the north
disagreed with the south on as fundamental an issue as slavery?
The number of sovereigns had declined as states consolidated
and major sovereigns annexed weaker ones and was to decline
further, notably with the European “scramble for Africa,” to 54
by 1914.[footnoteRef:6] European empires, which had
administered a third of the world’s land surface in 1800,
controlled over 84% by 1914 (Fieldhouse 1973). Rich nation
states (excluding their empires) in 1870 were about equal in
size: populations were 40m (US), 39m (Germany), 38m (France)
and 31m (UK). Many more people lived in recognizably poorer
countries with autocratic governments (Russia with 83m, the
Indian subcontinent with 300m and China with 358m together
accounted for 58% of the world’s population). [6: War-induced
break-ups were to increase that to 76 by 1949 and later de-
colonizations resulted in today’s level of around 200 nation
states (Gancia et al 2016, p. 1).
]
International institutions - European empires apart
- were almost non-existent. Bodies such as the International
Commission on the Danube worked well for riparian states, the
International Office of Telegraphy was set up 1869 and the
International Bureau of Weights and Measures in 1870. The
Hague Tribunal (another forerunner of today’s United Nations

78. for resolving international disputes) had to wait until 1899.
Nonetheless international trade (the increasingly protectionist
US excepted) was relatively free, facilitated by tariff reduction
agreements and acceptance of the “most favoured nation”
clause. Communications were improving: the French opened the
Suez Canal (speeding communication between Europe and Asia)
in 1869 and in the same year the US completed north America’s
first transcontinental railway, both expanding trade
opportunities. The Victorian “worldwide web” was almost
complete, with a working cable across the Atlantic by 1866,
India and Singapore connected by 1870 and Australia and major
cities on Asia’s Pacific coastline following in 1871 (Foreman-
Peck 1995). These achievements left sub-Saharan Africa as the
only major region not then linked to rapid telegraphic
communication.
The connection that North et al hypothesised
between open access in the political and economic spheres
might be expected to show up earliest and most clearly in the
US, a self-consciously new and different country whose many
constituent states were experimenting with open access both
politically and economically: extending the franchise and
general incorporation laws. The number of corporations per
capita in the US was already high by European standards by the
middle decades of the nineteenth century (Wright 2014, Hannah
2014). However, there was considerable variation between US
states in allowing incorporation with limited liability by simple
registration and political open access, with long lags both ways;
the changes were slow, difficult and contingent (Hilt 2017).
Few believed that opening access to organizations of all kinds
could both spark sustained economic growth and enhance the
workings of democratic politics (Lamoreaux and Wallis 2017).
A more sharply mixed pattern can be seen globally.
China, Japan, many un-colonized Asian and African states, the
Russian and Ottoman Empires and much of south eastern Europe
lacked general incorporation statutes in 1870 and for several
more decades. On the other hand, most rich countries with some