Growth Within a Country
The issue of development and growth within a country or across countries is such that attracts that attention across board. There are screaming headlines of different economic measures taken by economists and financial analysts of countries concerned. Tracking and recording growth in any country or comparing growth amongst country necessitates using diverse measures. Many measures in the name of models have been propounded of which some are accepted without contention. Many however are still undergoing different measures of experimentation. Augmented Solow Model that was developed by Mankiw et al. (1992) is extensively used in this project to measure growth across countries.
The variable of human capital has a general acceptance as a major contributor to economic development. The correlation between the variable, human capital and economic development will be calculated using time series data of 22 countries. Positive relationship that exists between the variable and time series data is further confirmed. A further sensitivity test is performed to verify the correctness and usability of the result obtained. Human capital has health and education as components and these two shall serve as proxies for human capital. Although the different models assume different states of technological advancement with regards to the sampled countries but in this write-up, the emphasis was placed on using different growth rates for the technological advancements as different countries have distinctive growth rates. This tends to give a better regression results in support of the Solowian concept. The final result obtained lay credence to the concept that all sampled countries move from being poor to a steady state which does not contradict the augmented Solowian theory. Effort was also made in using stock performance record to tract the various per capita incomes which also assisted in the final regression results.
INTRODUCTION
Comparative differences in the levels of development amongst nations have brought about some level of concern and this concern gave birth to so many explanations using different models for explanation. Solow model explained that increased development, measured in Gross Domestic Product (GDP) is as a result of increased use of capital and technological change. The former increased by 12.5% while the latter increased by 87.5 per man-hour in GDP, Solow (1956). It was however realized that the huge percentage of technological change which is 87.5% could also be as a result of human capital. In view of this realization, different models sprang up which include the one found in Lucas (2002). One of such models is Augmented Solow Model developed by Mankiw et al. In the year 1992. Some factors used by Mankiw et al. To explain this concept include trade, inequalities and some core values such as labour and capital which are considered variables in nature. These factors are highly debated by analysts. Others variable factors were added, with reasons while others contested the result obtained from these factors and variables. (Mankiw, Romer and Weil, 1992; Ram, 2007) made an inclusion of schooling as a variable while (Knowles and Owen, 1995) believes that health and longetivity must also be a factor.
The Mankiw, Romer and Weil (MRW) are used as a case study here. Two types of technological changes were observed. The types A and B. According to MRW, the countries studied were noticed to approach a steady state from backward position. This is argued by Cho and Graham (1996) that approaching this steady state is as a result of assuming that the various countries have similar rate of technological advancement. However, by applying different rates of technological advancement to the countries, the number of countries that approached steady states from backward reduced.
EMPERICAL EVIDENCE
The additional non-core variable of choice is technological changes. According to Mankiw, Romer and Weil, selected countries attained a steady state due to per capital income levels that are at variance with those countries that have already attained steady states. In view of this, the Mankiw et al. assumes that total factor product is negative for the selected countries. By applying 2% technological advancement to Solow model, a lower steady-state is obtained for a ratio of labour to capital rather than a zero value obtained by Cho and Graham (1996). What this translates to is that for countries to attain a steady state, the value for the ratio of capital to labor must be less. Mankiew et al. augmented the original Solow model by adding human capital variable. This gives the equation a look as presented below in three steps:
Yt = K (t H (t (A t L. t) 1-( – ( – (1)
k t = s k y t — (n + g + () k t – (2)
h = s h y t (n + g + () h t – (3)
The parameters of the equation above are as represented below:
Y represents output
K represents physical capital
H represents human capital
L represents labour
A, technological level attained n and g represent the rates of growth of labour and technology. They are s h and s k represent amounts invested from the outputs of human and physical capital
( represents the depreciation rate for the amounts invested. However, accumulation function can be expressed in units of effective labour which can be expressed as below:
y = Y, k = K
AL AL
and h = H
AL
Mankiw et al. used the equation above to calculate the level of steady rate per capita income. This was based on time t, yt*= Yt
Lt
In (yt*) = In (A () + gt — (( + () In (n + g + () + ( ( ) In (sk) + ( ( ) In (sh) – 4
1 – ( – ( 1 – ( – (
1 – ( – (
In order to calculate steady state making use of Mankiw et al. theory for the year in question, taken that ( = (n + g + ()
(1 – ( – ()
d In (yt) = g + ( (In (yt*) – In (yt))
dt
B: COLLATED DATA
The countries listed below are some of the countries used as sample in calculating relative percentage annual growth productivity.
Relative % annual growth, Total Growth Productivity 1970-1985, Young
Egypt
3.500
Turkey
0.900
Morocco
0.000
Pakistan
3.000
Netherlands
0.800
Nigeria
0.000
Botswana
2.980
Ethopia
0.700
Haiti
0.000
Congo
2.800
Austra
0.700
Benin
0.000
Syria
2.500
Australia
0.700
Madagascar
0.000
Hong Kong
2.500
Kenya
0.600
Sudan
0.000
Cameroun
2.400
Spain
0.600
Ivory Coast
0.000
Zimbabwe
2.400
France
0.500
Senegal
0.000
Tunisia
2.400
Liberia
0.400
Zambia
0.000
Uganda
2.100
Honduras
0.400
Mozambique
0.000
Bangladesh
1.900
Paraguay
0.400
Angola
0.000
Thailand
1.900
Portugal
0.400
Bolivia
0.000
Italy
1.800
Belgium
0.400
Philippines
0.000
Norway
1.700
U.S. A
0.400
Papua N.G
0.000
Finland
1.500
Algeria
0.300
Dominican R. 0.000
Burma
1.400
Canada
0.300
El. Salvador
0.000
Korea. R
1.400
Central A. R
0.200
Jordan
0.000
Ecuador
1.400
India
0.100
Guatemala
0.000
Mauritius
1.300
Sri Lanka
0.100
Jamaica
0.000
Denmark
1.300
Singapore
0.100
Nicaragua
0.000
Greece
1.200
Rwanda
0.000
Peru
0.000
Japan
1.200
Sierra Leon
0.000
Costa Rica
0.000
Israel
1.200
Burkina F.
0.000
Mexico
0.000
Tanzania
1.100
Niger
0.000
Ireland
0.000
Columbia
1.100
Zaire
0.000
S. Africa
0.000
Malawi
1.000
Burundi
0.000
Argentina
0.000
Brazil
1.000
Mauritania
0.000
Uruguay
0.000
Malaysia
1.000
Togo
0.000
Chile
0.000
Sweden
1.000
Nepal
0.000
T & Tobago
0.000
Panama
0.900
Indonesia
0.000
New Zealand
0.000
U. K
0.900
Somalia
0.000
Switzerland
0.000
Germany
0.900
Chad
0.000
Venezuela
0.000
0.800
Ghana
0.000
By using the equation and having in mind the various interpolations.
In (yo*) = (” – gt + (2 In (n + g + () + (3In (sk) + (4In (sh)
(1
(0
(1
(2
(3
(4
R-2
Non-Oil
(1) MRW-CG
3.022 -0.288
-0.506
0.524
0.231
0.463 49(98)
(3.651) (-4.863) (-1.752)
(6.029)
(3.887)
(2) Young
3.991 -0143
0.419
0.474
0.139
0.530 43(98)
(7.109) (-2.143) (4.093)
(5.749)
(2.408)
OECD
(3) MRW-CG
2.755 -0.398
-0.863
0.332
0.228
0.651 4(22)
(2.294)
(-5.668) (-2.557) (1.914)
(1.570)
(4) ) Young
5.064 -0. 363
0. 157
0.327
0.126
0.541 7(22)
(5.295) (-4.331) ().933)
(1.583)
(0.517)
By having a closer look at the analysis presented above, Cho and Graham reached a conclusion that rich and poor countries are not at par. There is a difference. It was estimated that comparatively poor countries attained their steady state positions from above as opposed to the rich countries that attained theirs from below.
For the countries analyzed which are oil producing countries and some others that have attained the steady state level, the various data collated for the is used in calculating per capita income.
In (yt) – In (yo) = (o + (1 In (yo) + (2In (n + g + () + (3In (sk) + (4In (sh)
By making use of the data of the oil producing countries of Makiw et al., Cho and Graham calculated that about half of all the country sampled assumed tha steady state from above. That is assuming that technological changes made a growth rate of 2%. In order to make a precise calculation of the per capita income for the year in question, it is necessary to interpolate the alpha parameters: (o, (1, (2 and (3
It is taken that (o = gt + (1 — e-(t) In (Ao),
(1 = – (1 — e-(t)
(2 = – (1 — e-(t)(( + ()
C: With regards to the regression result obtained above and with the assumption that the growth rate of 2% is assigned to technological changes, Cho and Graham estimated that for all the countries in the sample, about half of them attained a steady state from the top. The regression result also made it clear that for the second sample of 22 countries, the result obtained are very close to those countries that are non-oil producers when the same procedure is utilized. It is noticed that MRW-CG shows a result that is not in agreement with a general concept that countries attained their steady state from below. This could as well be explained in the sense that the same rate of technological advancement was ascribed to all the countries.
D: The main problem faced in conducting a regression analysis, OECD countries are expected to attain steady state from the top but due to small disparate growth performance, only few attained this level. According to Young, ascribing different levels of technological advancements goes a long way at correcting the anomaly. Another problem faced is that making use of the result obtained from Total Factor Production to calculate the 1960 steady state income per capital, there could be an issue of under or over estimation.
E: The variable in my model suffer from non-stationary. The implication for non-stationary is that the approaches of attaining a steady state which is a mirror of advancement in the sampled countries will read different results. The augmented Makiw Solow model that technology variable must be negative. However, the regression result obtained shows otherwise. In order to get this right, the same rate of technological advancement will be ascribed to all samples countries and the stock record for that period is used. For this, perpetual inventory method is used in calculating the capital stock record.
Kt = (1 -()Kt — 1 + It
It is taken that K. represents the capital stock while I stands for the follow of investment. The following regression result is obtained
F: in view of the result gotten from E. above, there is improvement in the number of countries that attained the steady state from above. There are some levels of reliability in the result obtained. If countries attain a steady state from above, allocating different values for technological changes, the disparity in the growth of countries could be explained and analyzed for possible solution.
CONCLUSION
After the various analyses making use of different models and views from different economists and financial analysts, the Solowian model that countries tend to gravitate from being poorer to a steady state and not vice versa. This is reinforced by ascribing that there are different rates of technological advancements to different countries. Different countries have specifics as to technological advancement peculiar to their respective countries. This assumption gives a better result.
Reference
Cho, D., and S. Graham, 1996, The Other Side of Conditional Convergence, Economics Letters, Vol. 50, pp. 285-290.
Mankiw .N, D. Romer, and Weil D, (1992). A contribution to the empirics of economic growth, Quarterly Journal of Economics 107, 407{437.
Lucas, Jr., Lectures on Economic Growth, Harvard University Press The Harvard University Press is a publishing house, a division of Harvard University, that is highly respected in academic publishing. It was established on January 13, 1913. In 2005, it published 220 new titles.
.Click the link for more information., (2002).
Knowles, S. And P.D. Owen, 1995. Health capital and cross-country variation in income per capital in the Mankiw{Romer{Weil model. Economics Letters 48, 99{106.
Ram, R., (2007). IQ and economic growth: further augmentation of Mankiw-Romer-Weil model, Economics Letters 94, 7{11}
Solow, R (1956)., A Contribution to the Theory of Economic Growth, Quarterly Journal of Economics, 50, 65-94,
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