Final paper

Running head: Migration and Development in Developing Countries
Final Report
Statistical Analysis of Migration in Relation to Country’s Development
Saidasror Kurbanov
Student ID: 5081133
Quantitative Methodology (QM)
By Dr. Kim
December 17, 2013

Migration and Development
Page 2 of 17
Contents
I. Introduction………………………………………………………………………………4
a. Contribution & Motivation……………………………………………………….5
II. Literature Review………………………………………………………………………..5
III. ResearchMethodology………………………………………………………………......5
IV. Hypotheses……………………………………………………………………………….5
V. Objectives………………………………………………………………………………...6
VI. Variables………………………………………………………………………................7
VII. Data collection……………………………………………………………………………8
VIII. Data Analysis…………………………………………………………………………….8
a. Descriptive statistics………………………………………………………………8
b. Regression……………………………………………………………………….11
IX. Conclusion………………………………………………………………………………14
X. Reference………………………………………………………………………………..16

Page 3 of 17
Executive summary
It is not easy to make development happen. There are several intertwined factors which some of
them boost development and some of them knock it. As we know, labor is one of the factors that
greatly contributes to development. Without adequate labor force, states can hardly go further in
this world economy. In addition, poverty is also related to the economic condition. When the
economy is advanced and unemployment rates are low, there will be lesser fractions of
population under the poverty line. Thus, labor emigration in the great scale can harm the
economic growth and at the same time, it can increase poverty. This research closely looked at
the relationship between development (economic growth and poverty) and labor emigration. The
result shows that there’s no potential relationship between the GDP growth rate and labor
migration due the factors increase or decrease the GDP growth. In other words, the impact of
labor migration is insignificant. However, there’s a reasonable relationship between poverty and
labor migration. When education, net migration, and unemployment are controlled, there’s a
strong relationship which can explain 63.4% variation in the model. All in all, the study
statistically proved that there is no causation between labor migration and GDP growth while
there is a negative strong relationship between labor migration and poverty.

Page 4 of 17
Introduction
Migration has become one of the hotly debated phenomena in politics. Many developed states
are concerned with the number of immigrants or foreign workers move to their country. Because
globalization or in other words, treaties between countries let people move freely, a huge portion
of labor which is not satisfied with jobs in their country moves to a better place in seeking new
job opportunities. For instance, the UK has a strong concern that a number of foreign workers
from the EU countries in Britain take jobs away (Swinford & Dominiczak, 2013). They send the
money they earned to their home countries. These became issues of the time.
Figure 1
According to the World Bank and IMF estimation, currently, 205 million people live outside of
their countries (Ratha & Eigen-Zucchi, 2013). 700 million migrate within states. The figure 1
indicates that remittance, the money sent to their home countries, has reached $401 billion with a
5% increase in 2012. The remittance along with FDI and ODA has been increasing rapidly. It’s

Page 5 of 17
the fastest growing transaction between countries. This indicates that it is important to study
labor migration and the benefits from migrating
The main motivation to start researching on this topic was the statistics of countries with a high
portion of economic income from immigrants of the country to another country. According to
World Bank, Tajikistan gets its 47% of GNP from its people in Russia. In addition, Liberia,
Kyrgyzstan, Lesotho, and Moldova hold 31%, 29%, and 27% respectively (Ratha & Eigen-
Zucchi, 2013). Again, some questions arise: why are they dependent on that money? What
change can their money bring to the country?
Literature Review
There are a lot of researches have been done in migration and its effects. Migration is a very
complex issue. It can bring beneficial effects and adverse effects at the same time. Phillip Martin
argues that for some poor countries that have high rates of permanent emigration, especially of
highly skilled people, and thus, migration can be a significant threat (Phillip, 2005). However,
others argue that where these countries have poor economic and financial infrastructure, the
potential for emigrants to contribute to development through remittances, investment, and
return/circulation migration is also hampered (Brown & Sanders, 1981). Overall, it has both
negative and positive effects. It is the matter of the proportion of migration and other
confounding factors affect each other (Newland, 2003).
Although, these fields of research have been studied many times, there have not been any clear
statistical studies of the relationship between the two phenomena. Development and migration is
very complex indeed. Throughout the paper, the main focus will be the effects of labor migration
on development which I define with only two factors here: economic growth and poverty level.
With the motivation I already mentioned, I will try to find causes of migration in relation to

Page 6 of 17
country’s development. If this paper is successful, it will definitely be added asset to our
knowledge.
ResearchMethodology
Hypothesis
• H01 – Labor migration from a country is a factor that increases poverty in that country
• H02 – Labor migration from a country is a factor that decreases the growth of
development in that country
Migration causes labor force to decrease to some level. Since we know from the production
function, labor is one of the most important factor determines economy (Martin, 1992).
• Ha1 – Labor migration from a country can increase the growth of development in the that
country
• Ha2 – Labor migrations from a country can decrease in poverty in the country
Some research studies suggest that workers tend to choose places where they are more
productive in making income (Sriskandarajah, 2005). Workers go abroad to work because either
they can’t support their families or they are not satisfied with their income in their home
countries. Thus, they send money back home. The money sent contributes to economy in some
ways and thus, it decreases the poverty level.
The study tries to understand the relationship between migration and economic growth and
between migration and poverty. If so, how are they related?
Objectives
 To analyze the topic using statistical tests

Page 7 of 17
 To find the relationship between migration and development
 To statistically prove the hypothesis
 To provide meaningful conclusions
Variables – definitions
In this research, there are two types of variables: Independent and dependent. Since the argument
is migration impacts development, migration here is the independent and development and
poverty are the dependent variables. There is more than one factor in each category. The
following list of variables is the probable set of variables for the study.
Labor Migration - Independent
▫ Remittance – money sent by workers
▫ Remittance as a percentage of GNP – remittance’s share in the domestic economy
▫ Net Migration – net migration, immigrants – emigrants
▫ Unemployment rate – the portion of population who are jobless
• Development - Dependent
▫ Economic growth – the growth rate of the domestic economy
▫ Poverty headcount – the percentage of the population who live under $2 a day
• Controlling variable
▫ Compulsory education – the length of mandatory education

Page 8 of 17
Data Collection
The World Bank was chosen as the only source to prevent the confusion in the data. All the data
for each variable are for year of 2011. Some countries were excluded due to the lack of data.
There was not enough information for some countries. The key variable in the study is
remittance. The reason is all the assumptions rest on this factor. Since it is hard to generalize
results without remittance, the countries without the remittance data were excluded. The total
number of countries used was 139 out of 193.
The data were input into SPSS and analyzed. The types of analyses used were descriptive
statistics, graphs, scatter plots, and regressions.
Analysis
The figure below is the remittance share in 139 countries. As it is mentioned above, Tajikistan is
the leader of this chart with 48%.
Figure 2

Page 9 of 17
Similarly, the figure 3 shows the mean and the range for the variables. A conclusion from the
table can be that a lot of countries are experiencing high GDP growth rates which make the
overall mean as 4%. However, the economic conditions, in general, are not that much good: the
unemployment in the countries is 8% and the remittance’s share in the economies is 4.6%.
Figure 3
By using the SPSS function, the remittance variable was categorized into three categories: low,
medium, and high remittance. This made analysis much easier and convenient. The graph on the
right is the line graph between the GDP growth rate and the remittance. The figure 4 suggests
Minimum Maximum Mean
Remittance in $ billion 0 67 3.62
Remittance in percent .00 47.97 4.6633
GDP growth %
Unemployed %
Net Migration, million
Mandatory education,years
-7.10
.20
-22.94
5
18.65
31.40
50
14
4.1820
8.7286
-.0507
9.04
Figure 4

Page 10 of 17
that when the amount of remittance goes up, the GDP growth goes down. In other words, there’s
a negative relationship between them. However, there might other confounding factors which
might be involved in this case. This idea can be testified later on in the regression analysis using
controlling variables.
As it is mentioned, the second null hypothesis states that there’s a negative relationship between
the poverty and the remittance. In the figure 5, we can see there’s an interesting association
between these two variables. When the remittance is low, the fraction of the population living
under $2 is high – against the null. However, when the remittance goes up from medium to high,
the association becomes negative which is the null hypothesis. Again, there might be some kinds
of confounding factors. The figure 6 in the next page, as it is expected, shows that the net
migration goes down when the remittance goes up. The reason is the net migration is the number
difference between immigrants and emigrants
Figure 4

Page 11 of 17
.
When people to choose to work abroad and send money, the net migration decreases or even
becomes negative. For the countries like the U.S., it is positive and for the states like Vietnam it
is negative.
RegressionAnalysis
Regression analyses are one of the best approaches to see the relationship and causation between
dependent and independent variables. There is no need to use the correlation analysis since the
both hypotheses are not to test the association but causation. The figure 7 is the regression
analysis for the relationship between the remittance and the GDP growth. The R square here is
0.03 which is very low – all of the variation in the GDP growth 3% is explained by the
remittance. The significance is also low. Basically, there’s no direct relationship.
R Square Significance
0.03 0.493
GDP growth %=4.12+0.025xRemittance in $ billion
Figure 5
Figure 7

Page 12 of 17
The result is not satisfactory: the R square is too weak and the significance level is too low in the
model. Therefore, the first null hypothesis is true. The study fails to reject the null.
Result: H01 is true
The next step is to see the relationship between the poverty and the remittance – to test the
second null hypothesis. In the regression analysis, the remittance is as an independent variable
and the poverty indicator is as a dependent variable. The figure 8 is the summary of the analysis.
The model indicates that all of the variation in the poverty level 12.4% is
explained by the remittance.
The figure 9 is the illustration of
this regression. The line on the
scatter plot is the regression line
and the equation is the same
equation given in the figure 7. On
the whole, with 95% confidence
interval, the regression estimates
that $1 billion increase in the
remittance is associated with 79.7%
R Square Significance
0.124 **
Poverty %=19.75+0.797xRemittance in $ billion
Figure 8
Figure 9
** - 95% confidence

Page 13 of 17
increase in the fraction of the people living under $2 a day. In other words, there’s a positive
relationship between these two variables. It means the study fails to reject the null hypothesis.
However, this is not the end. There might be some confounding factors.
For now, the result: H02 is true
What can be the confounding factors? The following variables were decided to be controlled:
 Education – there are several types of workers such as 3D (Dirty, Difficult, and
Demanding) and highly skilled (Debrah, 2010). Because the 3D workers are different
than the highly skilled ones, the mandatory education can distinguish them in the type.
 Unemployment – some people choose to leave their country because they are not
satisfied with their jobs (low payment) or some people choose to leave because there’s
no job available for them in their country. There’s a difference here. Therefore,
unemployment should be controlled.
 Net migration – in some countries like the U.S., there’s positive net migration. Basically,
there are more people coming to the country compared to the people leaving the country.
This should be controlled because a country with positive net migration is different than
a country with negative migration. The difference might be due to the economy in the
countries or overall living conditions. Since the focus of this study is to get the
relationship between the remittance and development, net migration should be controlled.
The figure 10 on the next page is the summary of the regression between the remittance and
poverty controlling for the mandatory education, unemployment, and net migration. This model
suggests that all of the variation in the poverty headcount 63.1% is explained by the remittance
holding mandatory education, unemployment, and net migration constant. The confidence level

Page 14 of 17
for the variable is highly significant, 99%. Looking at the equation, the remittance decreases the
poverty when the confounding factors are controlled. If we compare this model to the previous
model, the significance increased. The reason is simple: all the confounding factors were
excluded.
The result: H02 is not true. The null has been rejected.
Conclusion
All in all, the deep analysis of this study shows that labor migration is very complex. It is
hard to prove the association between labor migration and development. The reason is they
are a number of variables affect each other. However, it was possible to narrow the topic
down to a specific hypothesis: the causation between remittance and GDP growth and the
causation between remittance and poverty. The results indicate that the money labor migrants
send to their home countries is associated with the poverty level. In other words, the more
Adjusted R Square Significance
0.631
Remittance: ***
Education: ***
Unemployment: 0.948
Net migration: ***
Poverty%=56.67 - 2.097xRemittance($bil.) - 4.215xEducation - 0.023xUnemployment % -
- 4.065xNet migration (million)
Figure 10
** 95% confidence
*** 99% confidence

Page 15 of 17
remittance migrant workers send the less poverty headcount of population in their country
will be. On the other hand, however, the remittance doesn’t contribute to the GDP growth.
The results show it does contribute at a very low proportion, however, with a low
significance level. It means the first alternative hypothesis turned out to be wrong whereas
the second alternative is true. In other words, this study failed to reject the first null
hypothesis but it could reject the second null hypothesis with 99% confidence.

Page 16 of 17
Reference
Brown, L. , & Sanders, R., (1981). Toward a development paradigm of migration, with
particular reference to third world settings, Pergamon, New York.
Debrah, Y. (2010). Introduction: Migrant workers in pacific asia. Asia Pacific Business
Review, Retrieved from
http://www.tandfonline.com/doi/abs/10.1080/713999165?journalCode=apb20
Martin, P., International Migration Review Vol. 26, No. 3 (Autumn, 1992), pp. 1000-1012
The Center for Migration Studies of New York, Inc, Retrieved from
http://www.jstor.org/stable/2546975
Newland, K., (2003). Migration as a factor in development and poverty reduction . Retrieved
from:
http://scholar.googleusercontent.com/scholar?q=cache:5j04Y6eG6q8J:scholar.google.com/
migration and development&hl=en&as_sdt=0,5
Ratha, D., & Eigen-Zucchi, C. The World Bank, (2013).Migration and development brief.
Retrieved from The World Bank website:
http://siteresources.worldbank.org/INTPROSPECTS/Resources/334934-
1288990760745/MigrationandDevelopmentBrief21.pdf
Sriskandarajah, D. Global Commission on International Migration, (2005). Migration and
development . Retrieved from Global commission on international migration website:
http://iom.ch/jahia/webdav/site/myjahiasite/shared/shared/mainsite/policy_and_research/gci
m/tp/TP4.pdf

Page 17 of 17
Swinford, S., & Dominiczak, P. (2013, December 13). Stop unrestricted immigration from poor
eu countries, david cameron suggests. The telegraph. Retrieved from
http://www.telegraph.co.uk/news/uknews/immigration/10517128/Stop-unrestricted-
immigration-from-poor-EU-countries-David-Cameron-suggests.html

Final paper

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Viewers also liked

Viewers also liked (17)

Similar to Final paper

Similar to Final paper (20)

Final paper