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Macropolicy

Autor:   •  April 26, 2015  •  Coursework  •  1,825 Words (8 Pages)  •  633 Views

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Introduction

The hypothesis tested in this assignment is whether developing countries that showed a considerable drop in population growth are richer now than countries that have a prevailing population. Real GDP per capita (adjusted for PPP) , is used in this hypothesis to measure how rich a country is.

Process

For the purpose of testing the hypothesis, a total of 40 countries were selected; which consists of 20 countries that had a high population growth in 1960 which showed a declining trend in 2010 and 20 other countries which had a high population growth in 1960 which raised even further in 2010. Counties which showed a high population growth in 1960 and declined in 2010 are Afghanistan, Comoros, Timor-Leste, Benin, Burkina Faso, Burundi, Cameroon, Chad, Congo Rep, Cyprus, Iraq, Liberia, Mali, Madagascar, Malawi, Nigeria, Oman, Sierra Leone, Togo, Zambia and countries which showed a relatively high population growth in 1960 and increased even further in 2010 are Bahamas, Bangladesh, Belize, Chile, China, Colombia, Cost Rica, Czech Republic, Dominican Republic, Ecuador, Fiji, Honduras, India , Korea Rep, Lesotho, Malaysia, Maldives, Turkey and Uruguay.

For the process of selecting countries for these two criteria’s population growth percentages were compared against 2010 and 1960 and the counties which gave a positive figure was classified as countries that had an increasing population growth and countries which showed a negative figure was classified as counties that had a decline in population growth.

Figure 1 below shows a scatter plot diagram for countries that had a high population growth in 1960 which showed a further increasing trend in 2010.

Figure 1

[pic 1]

The countries and data’s illustrated in figure 1 is showed in the table below.

Table1

Country Name

Country Code

Population growth (annual %)1960

Population growth (annual %)2010

% change in population growth

GDP per capita, PPP (constant 2005 international $)

Afghanistan

AFG

1.958993663

2.458417085

0.499423423

1183.045192

Comoros

COM

1.738612427

2.517814139

0.779201712

1057.709871

Timor-Leste

TMP

1.704726645

2.879661709

1.174935064

1367.256757

Benin

BEN

1.304979864

2.869601321

1.564621457

1321.271334

Burkina Faso

BFA

1.359522204

2.907424319

1.547902115

1204.503648

Burundi

BDI

1.945425218

3.371194115

1.425768897

475.3842531

Cameroon

CMR

2.020835241

2.55560127

0.53476603

1957.219013

Chad

TCD

1.901535214

3.026858444

1.12532323

1822.868995

Congo, Rep.

COG

2.512806973

2.876009218

0.363202245

3748.223075

Cyprus

CYP

1.044306126

1.196967402

0.152661276

25198.03189

Iraq

IRQ

2.44887611

2.649523348

0.200647238

3270.348463

Liberia

LBR

2.151489847

3.510900571

1.359410724

492.5599045

Mali

MLI

1.035537335

3.098167701

2.062630366

1095.119233

Madagascar

MDG

2.373168625

2.80876582

0.435597195

849.1192449

Malawi

MWI

2.24527923

2.976902311

0.73162308

657.7296981

Nigeria

NGA

1.989401905

2.746547633

0.757145727

2170.057238

Oman

OMN

2.274941747

5.107008134

2.832066387

24753.12022

Sierra Leone

SLE

1.27998982

1.944982993

0.664993173

996.548259

Togo

TGO

1.326944703

2.595340664

1.268395961

862.041038

Zambia

ZMB

2.851176681

3.010393667

0.159216986

1370.47282

Source: http://databank.worldbank.org/data/views/variableselection/selectvariables.aspx?source=world-development-indicators

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