ECON 343
Economic Development and Growth
Lecture Notes
Francis T. Lui
Department of Economics
Hong Kong University of Science and Technology
(Spring 2008)
Chapter 1
Introduction
Social scientists often classify countries into “developed” and “less
developed” ones. What exactly do we mean by being more developed? A
wide range of criteria have been used, e.g., income level, educational level
or literacy rate, degree of political freedom or democratization, life
expectancy, density of telephone lines, penetration rate of mobile phones or
computers, etc. Among these, income level seems to be most commonly
used to define the developmental stage of a country. It is something that
every country wants to increase. It also shows significant co-movements
with many variables that are regarded as good indicators of the stage of
development.
Quantitatively, we observe great diversity in both income levels and
income growth rates across countries. (See Table 1.1) For example, the per
capita GNI of Malawi in 2006 (using “purchasing power parity,” or PPP,
measurement) was US$720, which was only 1.63% of that of the United
States.
The huge differences in the average long-term growth rates across
countries are often less recognized. From 1978 to 2006, China’s average
growth rate in per capita real GDP was 8.46%, while that for aggregate real
GDP was 9.69%. This means, per capita real GDP in 2006 was 9.73 times
that of 1978 (13.34 times for aggregate GDP). In another period, 185-1994,
growth rate in real GDP per annum in the United States was 1.3%,
Switzerland 0.5%, Hong Kong 5.3% and South Korea 7.8%. Many of the
African countries, however, experienced negative long-term growth.
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Table 1.1: Per Capita GNI in current US$ and PPP estimates (2006)
Countries
Per Capita GNI
Per Capita GNI
PPP estimates as
(in current US$)
(in PPP US$)
% of US
United States
44,970
44,260
100.0
Norway
66,530
43,820
99.0
Hong Kong
28,460
38,200
86.3
United Kingdom
40,180
35,580
80.4
France
36,550
33,740
76.3
Japan
38,410
33,150
74.9
Singapore
29,320
31,170
70.4
China
2,010
7,740
17.5
India
820
3,800
8.6
Malawi
170
720
1.6
Source: World Bank, World Development Report 2008.
Differences in long-term growth could have far-reaching
consequences. If a country today has an income level of $1, but wil grow at
1% a year for 50 years, then its income will be $1.64 after 50 years. If it
grows at 7% a year, it will be $29.46! What is significant is that differences
in long-term growth rates tend to persist. Many poor countries, which have
experienced negative or very slow growth, seem to have fallen into some
“poverty trap.” On the optimistic side, the kind of high growth rates that we
observe today is a modern phenomenon. Take the example of China again.
Table 1.2 presents the estimates by Angus Maddison (1998) for China’s per
capita real GDP in “international dollar” from 50 AD to 1978 AD using
1990 prices. As we can readily see, there had been clear stagnancy for a long
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period of time. Rapid growth only occurred in recent years. Similar
phenomenon can be found in Western countries before and after the
Industrial Revolution. This may hint that if a country followed the right
policy, growth rate could substantially improve.
Table 1.2: China’s per capita GDP in international dollars at 1990 prices
50 AD
960
1280
1820
1952
1978
$450
$450
$600
$600
$537
$979
How do we explain the diversity in long-term growth rates and
income levels? This is the main focus of the course. Presumably, if we can
do it, stagnant economies can learn from fast-growing ones on how they can
do better. The implications for human welfare are immense.
To explain growth, we need the concept of “engine of growth.”
Growth means that the economy keeps on producing more and more. This is
like a car that keeps on running. What drives the car or the economy? We
need to identify the engine.
Even if we have the engine, we need to know how the forces work
inside the engine. We need to understand the “mechanics of growth.” In
other words, we want to understand how the forces are transmitted through
the mechanics.
In addition to the mechanical side, we have to pay attention to the
human side. Given that people are rational, why and when do they have the
motive to go fast or slowly?
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Chapter 2
Neoclassical or Exogenous Growth Models
(2.1) Stylized Facts to be Explained by the Neoclassical Growth Models.
Let Q = output,
L = labor,
K = capital.
Also let the notation X*/X represent the growth rate of X, i.e., (dX/dt)/X.
The following relations are stylized facts that the neoclassical model seeks to
explain.
(1)
Q*/Q > L*/L.
Q*/Q and L*/L are fairly stable.
Define q = Q/L. The above implies that q*/q > 0.
(2)
K*/K is fairly stable.
(3)
K*/K ≈ Q*/Q.
In other words, K/Q is fairly stable.
(4) Profit rate is fairly constant in the long run. (This may have to be
modified by more recent experiences, since the profit rates in some countries
may have changed substantially.)
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(5) The long-run relative distribution between wages and profits is fairly
stable. (This does not seem to fit Hong Kong’s case too well.)
(1), (2) and (3) actually imply that K*/K > L*/L.
(2.2) The Solow Model.
The above are derived mainly from data in the US and other highly
developed countries. We should be careful about their applicability to other
economies. I shall first discuss a version of the Solow model (with technical
change), which is meant to provide a consistent explanation for the stylized
facts above.
Let the aggregate production function be
Q(t) = F(K(t), E(t)),
E(t) = L(t) e
λt
gt λt
= L(0) e e , i.e., E*/E = g + λ.
F is homogeneous of degree one, i.e.,
F(aK, aE) = aF(K, E), for a > 0.
Thus, (1/E) F(K, E) = F(K/E, 1) ≡ f(k), where k ≡ K/E.
Define q = Q/E = f(k). Assume that f’(k) > 0, f”(k) < 0, and f’(0) → ∞, f’(∞)
= 0.
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