Let us make an in-depth study of the Solow’s Model of Economic Growth. After reading this article you will learn about: 1. Prediction of the Solow Model 2. Solow’s Theory and Evidence.
Prediction of the Solow Model:
The Solow model makes the prediction that whether economies converge depends on why they differed in the first place.
On the one hand, if two economies with the same steady state had started off with different stocks of capital then we would expect them to converge.
On the other hand, if two economies have different steady states due to, say, different rates of saving, then no convergence is expected. In such situations each economy would approach its own steady state. A major finding from statistical evidence is that even when growth rates converge as predicted by the theory, this convergence occurs at a much slower rate than the Solow model predicts.
Economists feel uncomfortable with at least three implications of the Solow model. First, there is the question of exogeneity of technological progress. It augments labour productivity but is completely exogenous to the economy. An economy can do nothing to accelerate its long run rate of economic growth.
Secondly, if technical progress occurs automatically in the Solow model there is no reason why firms, governments, universities and research institutions would make investment in R&D (whose outcome, as far as its contribution to technical progress is concerned, is uncertain).
In other words, neither governments nor private agencies have any incentive to add to society’s stock of technical knowledge or foster technical progress. So some sort of free rider problem is encountered in the Solow model.
The third factor affecting the applicability of the Solow model is its predictions about convergence. The Solow model is essentially a closed economy model. But convergence is a natural outcome of the growth process only in a globalised world with perfect capital mobility.
Thus convergence is possible if economies are opened up and there is greater and greater integration of the world’s capital markets. In truth as the world becomes more and more integrated through movements of capital — technologies would converge.
This is likely to lead to a convergence in levels of output per capita — across rich and poor countries. However, data show that there is a tendency towards convergence in per capita output across rich countries but not across rich and poor countries. At the same time there has been divergence across rich and poor countries, i.e., widening income gap.
A related question here is whether greater openness would lead to slower or faster convergence. In the Solow model if capital is free to move across countries then it will flow from countries with low rates of return to capital (rich countries) to countries with higher rates of return (poor countries).
This implies that most capital should move from rich to poor nations. However, the real world experience contradicts this hypothesis. In truth, capital flows are among rich countries at similar stages of development. So convergence is still a distant dream for most LDCs.
Solow’s Theory and Evidence:
Does the Solow model explain the sustained economic growth observed in most parts of the world? Perhaps the most important prediction of the Solow model is that technological progress causes values of y = Y/L and k = K/L to rise together and at the rate of technological progress. This simply implies that capital-output ratio remains constant. This point has already been proved in the text. Here
This has happened in Solow model where Y/L and K/L have both grown at the same rate.
The second important prediction of the Solow model is that there is lack of symmetry in the effect of technological progress on factor prices. This is why we find diverse behaviour of factor prices in steady state. While in the steady state the real wage grows at the rate of technological progress, the real rental price of capital remains constant over time. These predictions have come true in case of USA.
In the USA, since the 1950s, the real wage has increased at almost the same rate at which real GDP per worker has increased (2% per annum). As the same time the real rental price of capital (measured as real capital income divided by the capital stock) has remained more or less constant.
However, the spectacular growth of the Tiger economies at the rate of 1% per annum cannot be properly explained by the Solow model in which technology grows at a constant exogenous rate.
The four countries — Hong Kong, Korea, Taiwan and Singapore — achieved unusually high growth rates due to large increases in measured factor inputs such as (i) increases in labour-force participation, (ii) increases in the capital stock, (iii) increases in educational attainment.
Since growth occurred due to growth in labour force, physical capital, and human capital, none of these four countries experienced unusually high growth in total factor productivity. Indeed, the average growth in TFP in the Asian tigers was exactly the same as that in the USA.
The evidence for conditional convergence, however, is much better. Studies carried out by N. G. Mankiw, David Romer and David Weil showed that the failure of LDCs like India to catch up with the West reflected high rates of population growth and low rates of saving (which also includes resources devoted to education along with accumulation of physical capital.)
After making corrections for differences in national saving rate and population growth rates they found strong tendencies for countries with the same characteristics to converge.
These findings provide some empirical support to the theory that the saving rate (including human capital formation) is important for growth.