Assignment be it in the form of rural

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Assignment be it in the form of rural

Assignment
4

 

To
critically evaluate this question, a clear understanding of the terms economic
growth and urbanization must be present. Urbanization can be defined in simpler
terms as the shift in residents from rural settlements to urban areas for
various reasons.

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“The process of urbanisation, or “urban transition”, describes a shift
in a population from one that is dispersed across small rural settlements in
which agriculture is the dominant economic activity towards one where the
population is concentrated in larger, dense urban settlements characterised by
industrial and service activities (Montgomery et al., 2004, United Nations,
2015).”

On
the other hand, economic growth can be referred to as how much more the country
produces than it did in the previous year, eventually making businesses more
profitable and rising stock prices allowing the companies to invest and hire
more workers consequently producing more jobs for people giving rise to income.

An
analysis of the interconnection between the above mentioned broad terms made by
Bloom et al challenges the question if there is a strong link or the connection
is a mere causality. “Urbanization is
closely associated with economic growth” (Todaro, M and Smith, S. 2012). Population
in the urban areas is highly corelated to its level of income as urban area is
a magnet for more opportunities attracting rural populations to migrate and
apply for a job. However, urbanization has many negative effects which cannot
be overlooked. The process of urbanization, be it in the form of rural to
urban, natural population growth or due to refugees, creates a pressure on the
urban areas to supply everyone with services. Although the agglomeration
increases the output per capita, the negative effects like squatter
settlements, environmental degradation or high level of unemployment are born.

The
indicator of economic growth is GDP does not consider many factors like illegal
transactions, black money or the most primary factor of informal income which
is basically the income generated by informal methods of earning and not
recorded in the GDP of the country. This informal sector is born out of less
jobs in formal sector for rural unskilled people giving rise to unemployment
and housing challenges, making more than 1 billion people, 14% of global
population living in slum areas. This is a clear sign of no economic well-being.
 

Figure
1 below shows a stark correlation between both phenomenon where both are moving
in the same direction. But, in this case many other factors influencing
economic growth have not been taken into consideration like literacy rate,
human capital, discovery of natural resources, law, technology, or physical capital
or infrastructure. The variety of other factors that are indicators of economic
growth are overlooked which may confer that this movement in the same direction
can be merely a coincidence. A causality which shows that “urbanisation is an indicator in economic growth but not necessarily
and instrument in this process (Bloom, D.E., Canning, D. and G. Fink. 2008)”.

 

Figure 1.

The
scatter plot in Fig. 1. shows a noteworthy relation between economic growth and
urban population share in different countries. The question arises if there is
an increase in economic well-being in a country defined by growth and high
level of income. This relationship could be due to a common factor or a driving
force affecting both the concepts rather than each influencing the other. An
investigation was carried out in a much deeper sense to evaluate further the link
between the two by Bloom et al in 2008. First method was to measure the
definite effects of population share on economic growth from 1960 to 2000
across different countries. The Granger causality test was applied between
urban popularity share and economic growth. The Granger causality was developed
in 1960s by C. W. J. GRANGER. Granger causality is a
statistical concept of causality that is based on prediction. “According to Granger causality, if a signal X1 “Granger-causes” (or
“G-causes”) a signal X2,
then past values of X1 should
contain information that helps predict X2 above and beyond the information contained in
past values of X2 alone.
Its mathematical formulation is based on linear regression modelling of
stochastic processes (Granger 1969)”. Therefore, Urban population
share is said to “Granger-cause” income if, controlling for past income levels,
past values of urban population share are predictive of future values of income
based on the test conducted by Bloom et al. It was concluded that a range of
variables are ignored while conducting this test as well as 10 years being a
short duration of time to calculate the economic growth of any country.

To
attend to the above situation a modified test was carried out where in 67 other
possible variables that boost economic growth were taken into consideration.
The population share of only the year 1970 was considered to predict the
economic growth in the following years of 1970 to 2000 based on the other variables.
A negative correlation was found again which showed no direct influence of
urban population share on the growth of the economy of the country. The result
was indeed same when carried out on developing or poorer countries to consider
other factors.

Hence,
it was concluded that the population in the urban areas has no link with the
economic growth of any country, developed or developing. Policies that are constructed
keeping this correlation in mind should be discarded as it urbanisation comes
with a range of negative impacts simultaneously with the benefits which do not
necessarily enhance the economic well-being of a country. Bloom et al conferred
that policies that are aimed at accelerating urbanisation to strengthen the economy
of the country fail for the same cause.

 

 

References:

1.    
Bloom, D.E., Canning, D. and G. Fink.
2008. Urbanization and the Wealth of Nations, Science, 319, pp. 772-775.

2.    
Todaro, M. and Smith, S. 2012.
Economic Development. 11th ed.

3.    
C. W. J. Granger, Econometrica 37,
424 (1969).

4.    
United Nations, World Population
Prospects: The 2004 Revision. CD-ROM Edition – Extended Dataset (United
Nations, New York, 2005).

 

 

 

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