Module

code and title: EC904-7-AU (Macroeconomics)

Family

Name: GREENSLADE

Given

Names: LAWRENNCIA

Registration

number: 1706325

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count (to nearest 100 words): 2800

Introduction

The

issue of convergence has been one topic of interest to many economists over the

years. Many have come up with theoretical and empirical analysis both in favour

and against this controversial issue. Convergence is when the per capita income

of poorer economies tends to grow faster than richer economies. It is sometimes

known as the catch-up effect. Convergence in growth theory can be either

conditional or unconditional (absolute convergence). However, in this paper our

focus is on absolute convergence. The main objective of this paper is to

discuss the evidence in favour and against the hypothesis of absolute

convergence based on the literatures of various economists. That is whether the

hypothesis of absolute convergence holds or not.

Absolute

convergence allows us to compare economic growth across countries to determine

if various countries are catching up in terms of their growth rates and level

of income per capita. Thus, absolute convergence implies that countries

converge to a common steady state irrespective of their initial capital stock

or GDP. It again implies that countries with a lower level of initial capital

stock tends to grow faster than those with a higher level.

Many

empirical studies on cross-country regressions have strongly led to the

rejection of the absolute convergence hypothesis. This is because countries

across the world differ in terms of their basic structural characteristics and

initial conditions and hence will usually not have the same level of capital-labour ratio, output per

capita and consumption (k*, y*, c*)

with an equal growth rate of technology (g) in the long run. Even in cases where

countries begin at the same initial level, it is still possible for them to

diverge with time. For instance, Botswana and Nigeria initially had the same

level of GDP per capita in the early 1960s but later, Botswana grew relatively

faster than Nigeria, leading to a huge difference in their level of income per

capita today. From the data bank of the World Bank, the GDP per capita of

Botswana in 2016 is greater than that of Nigeria by an amount of about

4,700(current US $).

Other

studies by economists such as Kaitila (2004) tends to provide evidence that

supports the hypothesis of absolute convergence. Most of such evidence of

convergence holds for countries within the same region or countries with

similar structural characteristics. Thus, I tend to agree with Barro (1993) on

his statement that, “If different economies-say, countries or regions of

countries have the same underlying technology, preferences, and government

policies, then the standard growth model predicts an absolute form of

convergence”.

Absolute

Convergence

Absolute convergence as

mentioned earlier, is when different economies obtain the same level of income

per capita in their steady states with the same rate of technological progress,

despite their initial conditions.

The

graph below can be used to explain the hypothesis of absolute convergence. The graph below can be used to explain the hypothesis of

absolute convergence.

Figure 1: Absolute convergence

Source: The

Convergence Hypotheses, (http://cruel.org/econthought/essays/growth/neoclass/solowconv.html)

Let’s assume that k1 represents the capital per labour of

poor countries and k2 represents the capital per labour of

rich countries. From the graph, both groups of countries converge to a common

steady state irrespective of where they start from. Based on the explanation of

convergence from the Solow growth model, when a country (in this case poor)

starts at the point where capital per worker is equal to k1, it will gradually converge to k*. This is because at k1, actual investment is greater than

breakeven investment and hence, k increases gradually till it reaches

a level of

k*, where actual investment is equal to

breakeven investment. Similarly, if a country (in this case rich) is initially

at the point where its capital per labour is at k2, then break even investment is

greater than actual investment. This means that there are not enough resources

to sustain capital per labour at its high level. As a result, capital per

labour will gradually fall to k* where actual investment is equal to

breakeven investment. Thus, k* is the steady state level of capital

per worker for both rich and poor countries. This could be possible given that

poor countries grow faster than rich countries and eventually catch up with

them.

The implication of poor countries

growing faster than the rich one can be explained by the law of diminishing

marginal return of capital. At a lower level of capital, the marginal product

of capital is high and when the level of capital is high, its marginal product

is low. Since the capital stock of poor countries is quite low, the marginal

product of capital is high, causing poor countries to grow relatively faster

than the rich countries whose level of capital is high and marginal product of

capital is low.

Evidence

in Favour and Against the Absolute Convergence Hypothesis

According to the Solow model,

population growth and accumulation of human and physical capital are

determinants of the steady state of a country and as such different countries

reach different steady states. However, empirical study by Mankiw, Romer, and

Weil (1992) showed that countries converge to a common income per capita once

the population growth and accumulation of human and physical capital are

controlled.

One

of the studies in support of the absolute convergence hypothesis which I will

like to consider is a study done by Mathur (2005). In this paper, he tested for

the absolute convergence hypothesis using sixteen European Union countries(

Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy,

Luxembourg, Netherlands, Portugal, Spain, Sweden, Norway and the United

Kingdom), five South Asian countries(Bangladesh, India, Nepal, Pakistan and Sri

Lanka), eight East Asian countries(China, Hong Kong, Japan, Malaysia,

Singapore, Thailand, Philippines, Indonesia) and fifteen countries(Azerbaijan,

Belarus, Estonia, Latvia, Lithuania, Moldova, Russia, Tajikistan, Turkmenistan,

Ukraine, Uzbekistan, Kazakistan, Krygistan, Armenia and Georgia) from the

Commonwealth of Independent States(CIS) for the periods 1961-2001, 1970-2001,

1980-2001 and 1990-2001. The test was to determine whether there is evidence of

absolute convergence among countries within each region and among all the 44

countries together. Using the per capita average annual growth rate and initial level of per

capita GDP of these countries, he estimated the equation;

Yit,t+T = a +

blogyit + eit, where

Yit,t+T = country i’s average of yearly annual growth rates of GDP time t and t+T

log yit =

the natural log of country i’s GDP per capita at time t

After running a regression, a

negative value was obtained for b, the coefficient of log yit, for

countries in the European Union for each period tested. This value was

statistically significant as well. Therefore, there is generally evidence of

absolute convergence for countries in the European Union. The evidence of

absolute convergence among these countries could be accounted for by the fact

that all these countries are industrialized economies. As such, they have

similar structural characteristics in terms of technological level, population

growth rate and investment rates. For instance, from the graph of annual

population growth rate of the sixteen European Union countries below, these

annual rates are relatively equal for most of the countries with the curves

following a similar trend. Given that population growth is one of the

demographic trends that influence economic growth (Kelly, Schmidt, 2000), it is possible that these countries’ convergence

was partly due to the similarity in their population growth rates. Also, the

population growth rates for these countries are generally low which has a

positive effect on economic growth.

Figure 2: A graph of the annual population growth

rates of the sixteen European Union countries between 1961 to 2001.

Source: Self, using data from World

Development Indicators, World Bank

The regression result for the

European Union and East Asian countries together yielded a negative value of

-0.44 for b which is statistically significant. Therefore, the absolute

convergence hypothesis was not rejected. The evidence of absolute convergence

means that these East Asian countries who were poor some decades ago are

gradually catching up with the industrialized countries. East Asia happens to

be the only region among developing economies catching up with industrialized

countries with countries such as China, Malaysia, Singapore, Thailand,

Philippines and Indonesia recording a high average of 4 percent growth of per

capita GDP between 1960 and 1994(Collins and Bosworth, 1996). During this same

period, the industrialized economies recorded an average GDP per capita of

about 2.6 percent. With the East Asian countries growing at a higher rate than

the industrialized countries, there has been a catching up of the East Asian

countries with the European Union countries. Hong Kong and Singapore are now

part of the 39 countries classified as advanced economies by the International

Monetary Fund. This could explain why the absolute convergence hypothesis holds

for the European Union region and the East Asia region in the above test. The

cause of the tremendous rise in the growth of these East Asian countries is one

question most economies have tried to answer. According to Collins and Bosworth

(1996), increases in physical capital per worker, education per worker and

total factor productivity were the major contributions to this tremendous

growth. Despite the evidence of East Asian countries catching up with the

industrialized economies, the same cannot be said of other developing

countries. Most developing countries seem to be getting poorer if not growing

slower and hence diverging from the rich countries rather than converging. This

is due to factors such as low level of technology, low stock of capital, high

population growth rate with high dependency ratio, low level of foreign direct

investment and others in the developing and undeveloped countries. The rapid

growth in countries such as Hong Kong and Singapore after 1960 should serve as

a source of hope to poor countries today, that it is possible for them to

become rich one day.

The regression result for countries

in all the regions together rejects the absolute convergence hypothesis. This

is because these countries together have different structural characteristics

which determine their steady states. Factors such as demographic trends,

foreign direct investments, political situations, natural resources, trade and

others which affects economic growth, are virtually different for countries in

the world. All countries converging to a common income per capita with the same

growth rate is therefore very difficult to attain, if not impossible.

Timakova

(2011) is another economist who undertook a research on both absolute and

conditional convergence using the Solow model. He extended the study done by

Mankiw, Romer and Weil (1992) by using 87 of the countries they studied, for

the periods 1960 to 2005. He used the following equation in an empirical

analysis, to test for the presence of absolute convergence among different

classifications of countries; Non-oil, Intermediate, Organisation for Economic Co-operation and Development(OECD), Low income and High income

Where, ln (

? = the rate or speed

of convergence

SH = the fraction invested

into human capital, H

n = population growth rate

g = technological progress

With the

data on the 87 countries, he obtained the following results from his regression

of the growth rate of GDP per worker on the initial level of GDP.

Unconditional (absolute) convergence

Regression

Full sample

Non-oil

Intermediate

OECD

Low income

High income

Number of observations

86

78

62

22

43

43

Constant

-0.012

(0.008)

-0.376

(0.376)

-0.404

(0.484)

0.366

(0.805)

-0.674

(0.417)

-0.328

(0.630)

Ln(GDP1960)

0.003***

(0.001)

0.136***

(0.045)

0.133**

(0.057)

0.043

(0.096)

0.189***

(0.049)

0.114

(0.075)

Adj. R-squared

0.083

0.062

0.041

-0.041

0.157

0.021

S.E.E.

0.015

0.644

0.740

0.731

0.571

0.724

Ln(GDP1960) is the log of

the initial level of income per worker. Furthermore, *=10% significance; **=5%

significance; ***=1% significance. Standard errors are in parenthesis below the

estimated coefficients.

Figure 3: A table

of the result obtained from regressing the growth rate of GDP per worker against

the initial level of GDP

Source: Timakova, (2011), “Conditional Convergence and

the Solow Model: an Empirical Study”, Pg. 39

From the table, it can be observed

that the coefficient of the log of GDP for 1960 are positive but close to zero for

all the country classifications. These values are all statistically

significant, except those for OECD and high-income countries. Also, the adjusted R2 values are

very small for most of the regressions. Thus, the hypothesis of absolute

convergence is rejected for this study, which implies that there is not enough

evidence to show that poor countries grow faster than the rich countries.

However, considering the graphs of

GDP per capita growth rates of low income and high-income countries from his

paper, the following observations can be made. The growth rate of GDP per

worker for low income countries is increasing overtime between 1960 and 2010,

showing an upward sloping trend line. The slope of the trend line is steep,

indicating that the increase in the growth rate overtime is quite slow. On the

other hand, the growth rate of GDP per worker for high income countries is

decreasing overtime between these years.

The trend line is steep and downward sloping. Similarly, this gradual

decrease in the growth rate of GDP per worker is slow.

Figure

4: Growth

rate dynamics in time, low income countries

Data source: World Bank, 2010

Source: Timakova, (2011), “Conditional Convergence and

the Solow Model: an Empirical Study”, Pg. 36, Fig. 6.1

Figure 5: Dynamics of economic growth in time for high income economies

Data source: World Bank, 2010

Source: Timakova,

(2011), “Conditional Convergence and the Solow Model: an Empirical Study”, Pg.

37, Fig. 6.2

The gradual movement of the growth

rates of GDP per capita for low income and high-income countries in opposite

direction implies that low-income countries are growing faster than the high-income

countries. This shows some evidence of absolute convergence. Based on the

explanation of convergence by Solow in the neoclassical growth model, could it

be that the gradual decrease in the growth rate of GDP per capita for high

income countries could be due to the possibility that these countries are above

their steady states?

Conclusion

As

discussed in the paper, there have been studies both in favour and against the

hypothesis of absolute convergence across countries. Rejecting or failing to

reject this hypothesis was usually dependent on the factors that influence

economic growth and convergence for the countries under study. Different

economists have come out with many different factors that influence economic

growth and convergence. For instance, the

diffusion of technology, the migration of persons, capital mobility and the

savings rate as mentioned by Barro (1993). The difference in these factors

across countries in the world makes it seem quite impossible to achieve

absolute convergence for the whole world. However, countries within the same

region or income level have shown evidence of absolute convergence due to the

similarities in their structural characteristics and initial conditions. This

is often true for the high-income countries with little evidence on convergence

among low-income countries (Noorbakhsk, 2006). There has also been evidence in

favour of absolute convergence among countries within different regions, such

as the convergence between the European Union countries and East Asian

countries discussed in this paper. If the hypothesis of absolute convergence

holds, then poverty among poor countries should be eradicated with time. Thus,

there will be no need for policies such as foreign aid to low income countries

(Timakova, 2011).

Bibliography

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R. J., 1993. “Economic Growth and Convergence”, An International Centre for Economic Growth Publication. ICS

Press, San Francisco California 1993.

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V., 2004. “Convergence of Real GDP per capita in the EU15: How do the accession

countries fit in?”, European Network of Economic Policy Research Institutes,

25.

3. Kelley,

A., Schmidt, R., 1995. “Aggregate Population and Economic Growth Correlations:

The Role of Components of Demographic Change”, Demography, Vol. 32, pg. 543-555.

4. Mankiw,

N.G., Romer, D., Weil, D.N., 1992. “A Contribution to the Empirics of Economic

Growth”, The Quarterly Journal of

Economics, May 1992, pg. 421-429.

5. Mathur,

S. K., 2005. “Absolute Convergence, Its Speed and Economic Growth for Selected

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2005): pg. 245-273.

6. Collins,

M. S., Bosworth, B. P., 1996. “Economic Growth in East Asia: Accumulation

versus Assimilation”, pg. 135.

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F., 2006. “International Convergence and Inequality of Human Development:

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Economics/University of Glasgow.

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M. V., 2011. ” Conditional Convergence and the Solow Model : An Empirical

study ” , Rotterdam School of Economics, Department of Economics, Erasmus University.

10. World

Bank 2018. “World Development Indicators”, World Bank DataBank, 2018.