Economic Growth and Convergence Analysis: MBAF 504 Term Paper

This report analyzes long-run economic growth and convergence, as per the requirements of MBAF 504: Economics from a Business Perspective. The analysis uses GDP per capita data extracted from the World Bank database for the years 1960, 1990, and 2015. The report investigates both unconditional and conditional convergence by comparing the economic growth of rich and poor countries. The study includes a sample of 10 countries, 5 rich (Australia, United Kingdom, United States, Japan, and Canada) and 5 poor (Uganda, Nepal, Nigeria, Rwanda, and Burkina Faso), to assess their growth trajectories. Statistical methods, including summary statistics, histograms, and box plots, are used to visualize and interpret the data. Regression analyses are conducted to test for both types of convergence, with the results supporting unconditional convergence but not conditional convergence. The findings suggest that while there's evidence of convergence, other factors beyond initial growth rates influence the process. The report concludes by discussing the implications of these findings and the limitations of the study, highlighting the need for more detailed analysis with different variables and samples.

Introduction
The long term economic growth can be defined as the total market value of the total production
by an economy over the long period of time. There is no definitive time period to define the long
period. As famously said by Keyns “we are all dead”. In the long run, one of the most discussed
topic is the convergence of the economies. It is argued that the poor countries will grow faster
than the rich countries as the economic growth of the rich countries will grow at slow pace as
compared to the poor countries. Many scholars have argued that over a period of time, the poor
countries will be able to catch up with the rich countries. However for this to happen there are
certain conditions which needs to be fulfilled(Barro & Sala-i-Martin, 1992).
There are two type of convergence. The first one is the unconditional convergence, which states
that the poor countries will grow at a faster pace and in the long run, the per capita income or the
standard of living will be similar as the now developed countries. The second type of
convergence is the conditional convergence which states that the convergence of the poorer
countries will happen with the countries which have similar characteristics In other words,
convergence will not happen between all the poor and rich countries. There will be more than
one convergence points(Barro & Sala-i-Martin, 1992; Sarkar, 1997).
Background
The secondary data for the analysis has been extracted from the World Bank data base and GDP
per capita was used as the indicator of the growth(The World Bank Group, 2016).
Summary statistics of the all the countries included in the data set is given in the tables below.
Summary Statistics
1960
Summary Statistics, using the observations 1 - 226
for the variable GDP_1960 (107 valid observations)
Mean Median Minimum Maximum
492.51 241.56 40.537 3007.1
Std. Dev. C.V. Skewness Ex. kurtosis
610.40 1.2394 1.9628 3.3347
5% Perc. 95% Perc. IQ range Missing obs.
60.061 1950.8 396.45 119
1990

Summary Statistics, using the observations 1 - 226
for the variable GDP_1990 (187 valid observations)
Mean Median Minimum Maximum
6150.0 1614.6 95.188 84290.
Std. Dev. C.V. Skewness Ex. kurtosis
10400. 1.6911 3.4461 17.750
5% Perc. 95% Perc. IQ range Missing obs.
244.34 26871. 6739.0 39
2015
Summary Statistics, using the observations 1 - 226
for the variable GDP_2015 (213 valid observations)
Mean Median Minimum Maximum
15243. 5733.1 305.55 1.6729e+005
Std. Dev. C.V. Skewness Ex. kurtosis
23540. 1.5444 3.3591 15.601
5% Perc. 95% Perc. IQ range Missing obs.
577.52 56765. 16165. 13
From the data base, a sample of 10 countries was taken into consideration for the analysis. Out of
the selected 10 countries, 5 countries were taken with high GDP per capita and 5 with low per
capita income.
Rich countries includes: Australia, United Kingdom, United states, Japan and Canada
Poor countries includes: Uganda, Nepal, Nigeria , Rwanda and Burkina Faso

GDP for Poor Countries
The GDP of the poor countries is shown in the figure below, it shows that the GDP of Nigeria
has declined after 1990 which was increasing before that period. For all other countries that there
has been increase in the GDP with decline in 1990. This may be because of the recession in 1990
(Kannan, Scott, & Terrones, 2009; Unctad, 2008).
GDP_1960 GDP_1990 GDP_2015
0
100
200
300
400
500
600
700
800
900
Chart Title
Uganda Nepal Rwanda Niger Burkina Faso
GDP for Rich countries

GDP_1960 GDP_1990 GDP_2015
0
10000
20000
30000
40000
50000
60000
Chart Title
Australia United Kingdom Japan
United States Canada
For Rich countries also the graph shows that there has been increase in the GDP. The period
between the 1960 to early 1980 is considered as the Golden age of industrialization, where the
growh rate of these countries were very high. However in 1990 with the start of the Vietnam war
and the recession the GDP declined for majority of the economies.
Hilstogram
The results from the histograms are shown in the graph below.

0
0.0002
0.0004
0.0006
0.0008
0.001
0.0012
0.0014
0.0016
0.0018
0.002
-1500 -1000 -500 0 500 1000 1500 2000 2500 3000
Density
GDP_1960
relative frequency
N(492.51,610.4)
Test statistic for normality:
Chi-square(2) = 169.167 [0.0000]
Histogram of GDP 1960 indicates that most of the countries, the GDP per capita was very low,
except of some countries which are in the right hand side of the curve.

0
2e-005
4e-005
6e-005
8e-005
0.0001
0.00012
-20000 0 20000 40000 60000 80000
Density
GDP_1990
relative frequency
N(6150,10400)
Test statistic for normality:
Chi-square(2) = 388.730 [0.0000]
In 1990 the number of countries have increased, who have higher GDP, in this case also there are
some outliers such as the Luxemburg which has very high GDP per capita. Overall there has
been improvement in the GDP per capita.

0
1e-005
2e-005
3e-005
4e-005
5e-005
6e-005
-50000 0 50000 100000 150000
Density
GDP_2015
relative frequency
N(15243,23540)
Test statistic for normality:
Chi-square(2) = 530.831 [0.0000]
The increase in GDP per capita continue to increase in 2015. More countries are included in the
middle income group in this time period as compared to the previous period.
Box Plot
Results from the box plot are shown in the figures below.

-20
-10
0
10
20
Growth_rate_1960

-200
-100
0
100
200
300
Growth_rate_1990

-400
-200
0
200
400
600
Growhtrate_2015
Box plot of rich countries
Separate box plot for the rich countries are shown in the figures below.

7.5
8
8.5
9
9.5
10
10.5
11
l_Australia

7.5
8
8.5
9
9.5
10
10.5
l_UnitedKingdom

8
8.5
9
9.5
10
10.5
11
l_UnitedStates

8
8.5
9
9.5
10
10.5
11
l_Canada

6
6.5
7
7.5
8
8.5
9
9.5
10
10.5
l_Japan
The results from the box plots indicates that the growth rate of the poor countries have increased
over the period of time, however they are still far from catching up with the rich countries. Only
a certain countries are on the path to converge.
4. The results for the conditional and unconditional convergence are shown in the table below.
Unconditional Convergence
The conditional convergence argues that all the poor countries and rich countries will have
similar growth in the long run, irrespective of the characteristics of the countries. To test the
same, the regression was conducted and the results are shown below.
Model 1: OLS, using observations 1-52
Dependent variable: Avg_GDP_2015_90
Coefficient Std. Error t-ratio p-value
const 6.62590 5.33408 1.242 0.2200

Growth_rate_1960 6.38601 0.627598 10.18 <0.0001 ***
Mean dependent var 3.354825 S.D. dependent var 66.61822
Sum squared resid 73707.62 S.E. of regression 38.39469
R-squared 0.674346 Adjusted R-squared 0.667833
F(1, 50) 103.5373 P-value(F) 8.93e-14
Log-likelihood −262.4569 Akaike criterion 528.9137
Schwarz criterion 532.8162 Hannan-Quinn 530.4099
Conditional Convergence
Findings indicates that the coefficient of growth rate in 1960 is statistically significant which
indicates that the growth rate in 1960 is able to predict the growth in the next period. This
suggest that there is some evidence of convergence .
Conditional convergence
The results from the unconditional convergence indicates that the other factors included in the
regression analysis is not statistically significant. This results do not support the conditional
convergence.
Model 2: OLS, using observations 1-52
Dependent variable: Avg_GDP_2015_90
Coefficient Std. Error t-ratio p-value
const 5.48068 10.7886 0.5080 0.6137
Growth_rate_1960 6.39676 0.639914 9.996 <0.0001 ***
Invet_1960 0.0628722 0.513154 0.1225 0.9030
Mean dependent var 3.354825 S.D. dependent var 66.61822
Sum squared resid 73685.05 S.E. of regression 38.77856
R-squared 0.674446 Adjusted R-squared 0.661158
F(2, 49) 50.75630 P-value(F) 1.15e-12
Log-likelihood −262.4489 Akaike criterion 530.8978
Schwarz criterion 536.7515 Hannan-Quinn 533.1420
5. Explanation of Economic growth and Convergence
The results from the analysis support the unconditional convergence as the other explanatory
factors included in the current study (the investment from the government), do not show
statistically significant results. On the basis of the results it can be suggested that the poor
countries will be able to catch the rich countries in the long run. However, it was predicted a long
time ago and if the convergence theory was correct, most of the countries in the world should

have been on the same GDP level, which is not the case. Only few countries are able to show
some progress on catching up with the rich countries(Cavenaile & Duboi, 2011; Tsanana &
Katrakilidis, 2016). This is may be because the growth rate in the rich countries has not slowed
down as expected due to various factors such as technological advancement and new invention to
boost productivity. Or the poor countries are not able to grow faster as expected. The previous
studies on convergence have also given different results based on the sample selection and also
the selection of the variables to measure growth and standard of living(Cavenaile & Duboi,
2011; Haan & W.J., 1995; Tsanana & Katrakilidis, 2016).
Conclusion
The main aim was to examine the convergence among the selected data set. The data set was
collected from World Bank. The data was divided into two groups, rich and poor for analysis
purpose. Test for both the conditional and unconditional convergence was performed and results
suggest the unconditional convergence. This might be because of the sample selected for this
study and also the time period. The question of convergence require more detailed analysis with
different sets of analysis.
Reference
Barro, R. J., & Sala-i-Martin. (1992). Convergence. Journal of Political Economy, 100(2), 223–
251.
Cavenaile, L., & Duboi, D. (2011). An empirical analysis of income convergence in the
European Union. Applied Economic Letters, 18(17).
Haan, D., & W.J. (1995). Convergence in Stochastic Growth Models: the Importance of
Understanding Why Income Levels Differ. Journal of Monetary Economics`, 35(1), 65–82.
Kannan, P., Scott, A., & Terrones, M. E. (2009). From Recession to Recovery: How Soon and
How Strong. World Economic Outlook, 2.
Sarkar, P. (1997, August). Are Poor Countries Coming Closer to the Rich? Economic and
Political Weekly. Retrieved from https://www.jstor.org/stable/4405709?
seq=1#page_scan_tab_contents
The World Bank Group. (2016). World Data Base. Retrieved October 29, 2017, from
http://www.worldbank.org/en/news/infographic/2016/05/27/india-s-poverty-profile

Tsanana, E., & Katrakilidis, C. (2016). The issue of convergence: New empirical evidence for
the Central Eastern Europe area. Applied Econometrics and International Developmen,
16(1).
Unctad. (2008). Trade and Development Report 2008 - Commodity prices, capital flows and the
financing of investment. Trade and Development Report.