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.
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.
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
and h = H
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
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))
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
Dominican R. 0.000
Central A. R
T & Tobago
By using the equation and having in mind the various interpolations.
In (yo*) = (" - gt + (2 In (n + g + () + (3In (sk) + (4In (sh)
(3.651) (-4.863) (-1.752)
(7.109) (-2.143) (4.093)
(-5.668) (-2.557) (1.914)
(4) ) Young
5.064 -0. 363
(5.295) (-4.331) ().933)
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…