INFLUENCE OF CORRUPTION AND THE ROLE OF GDP PER CAPITA IN THE WORLD ON ECONOMIC GROWTH.

SUPERVISED BY:

PROF. LUIGI MARIA SOLIVETTI

PREPARED BY:

ALDA MIFTARI

Course of Quantitative Models for International Economic Policy

Academic year 2014/2015

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Table of contents Abstract……………………………………………………………………………………………………………………..3 Motivation…………………………………………………………………………………………………………....……3 1. Introduction……………………………………………………………………………………………………4 2. Definition of corruption and the influence of GDP

per capita of all the

countries in the world…………………………………………………………………………………..…5 3. The impact of Corruption Perceptions Index on two groups of countries with different level of income: OECD countries with a high level of income and Lower middle level income countries for the year 2013……….………….................17 4. Case of study: Angola and Finland 2005-2013. The role of GDP per capita……19 5. Case of study: Greece and Nigeria. Comparing Corruption Perceptions Index and GDP growth (annul %) for each country…………………………………………………20 6. Conclusions………………………………………………………………………………………………...…26 7. References…………………………………………………………………………………………………….27

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Abstract Corruption is described as the use of public power for individual purposes. It is a feature of societies and countries. Recent years it is considered as a phenomenon present and a disease to developed and developing countries. It tends to grow faster than the dynamics implemented to neutralize it and systematically he has caused many problems of concern in all countries of the world. Based on

report: Transparency International, Corruption

Perceptions Index is one of the large challenges of contemporary in the world. It defines good governance leads to an inefficient allocation of resources, disrupting public and private sector and contributes frequently to the poverty. Social factors, political and institutional have a major role in economic development country and economic growth in developing countries. Corruption, is a symptom of deep institutional weaknesses is one of the factors responsible for reducing investment and spending (education and health), increases inequality income, reduces foreign direct investment and resource allocation. Corruption poses a threat to a country’s economic growth after the decrease efficiency in the private sector and the public. He is one of the most important factors that have impact on reducing economic growth in many countries. This is a phenomenon common today in many developing countries and arises as a result of their poverty. This paper analyzes the impact of corruption on economic growth, on developed and developing countries. The purpose of this paper is to contribute to the literature enabling a specific theoretical model on the impact of corruption on economic growth.

Motivation Corruption is a feature of human society since many decades. Corruption scandals occur not only in developing countries like India, Nigeria, China, Albania, Armenia, etc. where corruption is often seen as a rate or fee, but it is present and in developed countries such as France, UK and USA. Corruption in the public sector is considered as a major economic development (Kaufmann, 1997). Facts (eg, Mauro 1995 and World Bank, 1997) show the effects of corruption in other variables such as investment, economic growth and social 3

welfare. A country has a significant impact on the existence of corruption and anticorruption policies. The motivation for this topic comes, because corruption has become a problem for all the countries. Also he is a key factor that affects many indicators that determine the development and performance of the country. What I'm trying to study and empirically analyze is the impact that using a panel data for developing and developed countries, where the analyses of performed concludes that corruption has a significant negative impact on economic growth.

1. Introduction The phenomenon of corruption is very old and is a universal problem. We have an increasingly growing in awareness and recognition of the widespread nature of corruption as it attracted the attention of economists in recent years. He can be seen in every country and nation in various size and shapes. Corruption has existed for a very long time and will continue in the future, only if governments can find effective ways to combat it (Mauro 1997). It will not be easy. Although the study of the causes and consequences of corruption have a long history in economy, most of developed countries can control it, but its effect in developing countries yet. In recent years, the harmful effects of bureaucratic corruption have gained the attention of economists, as well as international financial institutions and policy-making. Current literature on corruption emphasizes its harmful effects on economic growth1. Some studies have been able to determine the factors and causes of corruption. Recent years various economists and researchers have seen an interest in the study of this phenomenon and the impact it has on the economy of a country. There are a range of models that attempt to identify its causes, but its empirical analysis is complicated. These complications are due to the difficulty of obtaining data and also the complexity of assessing the variables involved. Many international organizations have been able to analyze sources and alternatives to resolve this phenomenon. For example, the World Bank claims that, corruption is one of the main obstacles to economic and social development2. The International Monetary Fund (IMF) support the theory that, many of the causes of 1 2

See Klitgaard 1988, Shleifer and Vishny 1993, Mauro 1995, Cheung 1996, and Bardhan 1997 The World Bank http/.worldbank.org/publicsector/anticorrupt/index.cfm

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corruption are economic nature, and so are the consequences of poor governance his- has a clear inhibitory effect of economic activity and welfare3. Transparency International, Corruption Perceptions Index (CPI) ranks countries and territories based on how corrupt the public sector is perceived to be. The (CPI) reflects the views of observes from around the world, including experts living and working in the countries and territories evaluated. This organizations are not only support anti-corruption programs and policy initiatives in over 180 countries worldwide but organize conferences, workshops ect. The impact of corruption on economic growth is widely researched in the past two decades. Most studies have followed the model of Barros (1991) and Levine & Renelt (1992), which are based on estimates of cross-sector corruption in the average level of growth and a number of other control variables. While they did not deny that corruption may have played a positive role in a certain time in many specific areas, and the main findings of the empirical literature claim that corruption is endemic and pervasive and tends to lead to lower economic growth by hampered the performance of private spending and government productive investment and hinders the effectiveness of public services4. The literature remains divided into channels through which corruption is transmitted, the size of the direct and direct impact of corruption on economic growth rate. The work carried out by Mauro (1995) found that most of the growth of corruption comes through its impact on investment, while Pellegrini and Gerlagh (2004) pointed out that indirect effects of corruption on human capital, political stability and trade opening are also important. Corruption can result in reduced economic growth rate through distortions in tax collection, public expenditure level and composition of government spending.

2. Definition of corruption and the influence of GDP per capita of all the countries of the world. Corruption is present and constitute one of the most pressing problems of the past decades, but over the last decade is shown a great interest by the academics and policymakers. He 3 4

The IMF www.imf.org/facts/gov.htm See , for a review , AIDT , 2003, Svensson , 2005

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has been present in all social and political systems, levels and forms. The World Bank study the identifies corruption as one of the key factors impeding the economic and social development. Corruption is a violation of duties by public officials or persons in charge of legal entities and every activity of initiators or beneficiaries of such behavior, in exchange for a service directly or indirectly promised, offered, given, demanded, accepted or expected to get for yourself or for another person. A human activity, whether it is public, private or non-profit, regardless whatever it takes place in America, Italy, Japan, Russia ect , tends to become a corrupt activity if a person (or a group of individuals) have monopolized power over a good or service, enjoys freedom of judgment and action to put the offer and the price of the good or service and the person (or group of individuals) is not accountable to anyone (not responsible) for the activities. Let’s saw that GDP per capita is a measure of total output of a country that takes the gross domestic product and divides it by the number of people in the country. Table 1. Shows the value of Corruption Perceptions Index for 2013 and GDP per capita in the world for 2013. Data from World Bank Database September 2014 and Transparency International Corruption Perceptions Index 2013. Countries

Afghanistan Albania Algeria American Samoa Andean Region Andorra Angola Antigua and Barbuda Arab World Argentina Armenia Aruba Australia Austria Azerbaijan Bahamas, The Bahrain Bangladesh Barbados

Country Code

AFG ALB DZA ASM ANR ADO AGO ATG ARB ARG ARM ABW AUS AUT AZE BHS BHR BGD BRB

CPI 2013 score

GDP 2013

8 31 36

424,37 4.087,08 3.240,83

23

2.668,46 11.461,56 4.613,46

34 36 81 69 28 71 48 27 75

2.309,71 37.492,85 39.978,41 3.252,83 17.495,47 625,34

6

Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia and Herzegovina Botswana Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Cabo Verde Cambodia Cameroon Canada Caribbean small states Cayman Islands Central African Republic Central Europe and the Baltics Chad Channel Islands Chile China Colombia Comoros Congo, Dem. Rep. Congo, Rep. Costa Rica Cote d'Ivoire Croatia Cuba Curacao Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic East Asia & Pacific (all income levels) East Asia & Pacific (developing only)

BLR BEL BLZ BEN BMU BTN BOL BIH BWA BRA BRN BGR BFA BDI CPV KHM CMR CAN CSS CYM CAF CEB TCD CHI CHL CHN COL COM ZAR COG CRI CIV HRV CUB CUW CYP CZE DNK DJI DMA DOM EAS EAP

29 75 36

4.915,93 36.410,53 4.084,12 583,87

63 34 42 64 42 60 41 38 21 58 20 25 81

2.037,16 1.323,12 3.375,47 7.028,05 5.823,04 24.184,67 4.692,43 510,21 155,06 2.738,31 709,18 991,65 37.524,32

25

282,57 10.142,61 741,63

19 71 40 36 28 22 22 53 27 48 46

9.728,48 3.583,38 4.376,40 612,47 288,24 1.960,58 5.839,25 1.014,40 10.454,48

63 48 91 36 58 29

20.516,78 14.089,24 46.264,67 1.182,52 6.175,57 5.195,07 6.236,21 3.036,52 7

East Asia and the Pacific (IFC classification) Ecuador Egypt, Arab Rep. El Salvador Equatorial Guinea Eritrea Estonia Ethiopia Euro area Europe & Central Asia (all income levels) Europe & Central Asia (developing only) Europe and Central Asia (IFC classification) European Union Faeroe Islands Fiji Finland Fragile and conflict affected situations France French Polynesia Gabon Gambia, The Georgia Germany Ghana Greece Greenland Grenada Guam Guatemala Guinea Guinea-Bissau Guyana Haiti Heavily indebted poor countries (HIPC) High income High income: non OECD High income: OECD Honduras Hong Kong SAR, China Hungary Iceland India Indonesia

CEA ECU EGY SLV GNQ ERI EST ETH EMU ECS ECA CEU EUU FRO FJI FIN FCS FRA PYF GAB GMB GEO DEU GHA GRC GRL GRD GUM GTM GIN GNB GUY HTI HPC HIC NOC OEC HND HKG HUN ISL IND IDN

35 32 38 19 20 68 33

3.653,00 1.566,44 3.062,97 10.990,45 196,63 12.046,33 289,25 31.809,02 19.496,31 4.878,56 28.906,34

71

3.680,83 37.676,61 798,63 34.140,57

34 28 49 78 46 40

6.937,71 454,77 2.156,94 38.291,62 766,05 18.146,26

89

6.321,95 29 24 19 27 19

26 75 54 78 36 32

2.340,78 308,00 399,98 1.337,70 473,30 520,95 31.792,74 13.269,35 36.231,10 1.577,15 33.534,28 11.128,23 54.570,43 1.165,00 1.810,31 8

Iran, Islamic Rep. Iraq Ireland Isle of Man Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Kiribati Korea, Dem. Rep. Korea, Rep. Kosovo Kuwait Kyrgyz Republic Lao PDR Latin America & Caribbean (all income levels) Latin America & Caribbean (developing only) Latin America and the Caribbean Latin America and the Caribbean (IFC classification) Latvia Least developed countries: UN classification Lebanon Lesotho Liberia Libya Liechtenstein Lithuania Low & middle income Low income Lower middle income Luxembourg Macao SAR, China Macedonia, FYR Madagascar Malawi Malaysia Maldives Mali Malta

IRN IRQ IRL IMY ISR ITA JAM JPN JOR KAZ KEN KIR PRK KOR KSV KWT KGZ LAO LCN LAC LCR CLA LVA LDC LBN LSO LBR LBY LIE LTU LMY LIC LMC LUX MAC MKD MDG MWI MYS MDV MLI MLT

25 16 72

3.131,80 2.505,39 45.119,27

61 43 38 74 45 26 27

23.414,98 28.376,38

8 55 33 43 24 26

53 28 49 38 15 57

80 44 28 37 50 28 56

37.432,84 2.855,14 5.424,63 606,21 1.176,20 23.892,53 2.894,79 625,19 751,03 6.092,76 5.834,63

8.863,16 535,49 7.240,66 978,28 299,45 6.228,97 10.549,18 2.479,26 454,85 1.260,52 77.840,50 54.091,53 3.577,26 265,25 264,25 6.990,25 4.926,05 476,16 16.735,94 9

Marshall Islands Mauritania Mauritius Mexico Mexico and Central America Micronesia, Fed. Sts. Middle East & North Africa (all income levels) Middle East & North Africa (developing only) Middle East and North Africa (IFC classification) Middle income Moldova Monaco Mongolia Montenegro Morocco Mozambique Myanmar Namibia Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria North America Northern Mariana Islands Norway Not classified OECD members Oman Other small states Pacific island small states Pakistan Palau Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal

MHL MRT MUS MEX MCA FSM MEA MNA CME MIC MDA MCO MNG MNE MAR MOZ MMR NAM NPL NLD NCL NZL NIC NER NGA NAC MNP NOR INX OED OMN OSS PSS PAK PLW PAN PNG PRY PER PHL POL PRT

30 52 34

2.933,11 858,96 6.679,21 8.519,00 2.454,83 5.224,83 2.497,21

35 38 44 37 30 21 48 31 83

2.824,51 1.136,23 1.795,53 4.700,55 2.532,18 435,73 4.581,75 409,04 40.187,12

91 28 34 25

29.146,09 1.366,99 289,43 1.055,84 45.033,38

86

65.188,52

47

28 35 25 24 38 36 60 62

31.712,83 13.306,89 3.529,57 2.578,76 806,38 9.558,06 7.740,06 1.110,61 1.917,73 4.066,27 1.581,01 10.752,82 17.761,92 10

Puerto Rico Qatar Romania Russian Federation Rwanda Samoa San Marino Sao Tome and Principe Saudi Arabia Senegal Serbia Seychelles Sierra Leone Singapore Sint Maarten (Dutch part) Slovak Republic Slovenia Small states Solomon Islands Somalia South Africa South Asia South Asia (IFC classification) South Sudan Southern Cone Extended Spain Sri Lanka St. Kitts and Nevis St. Lucia St. Martin (French part) St. Vincent and the Grenadines Sub-Saharan Africa (all income levels) Sub-Saharan Africa (developing only) Sub-Saharan Africa (IFC classification) Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand

PRI QAT ROM RUS RWA WSM SMR STP SAU SEN SRB SYC SLE SGP SXM SVK SVN SST SLB SOM ZAF SAS CSA SSD SCE ESP LKA KNA LCA MAF VCT SSF SSA CAA SDN SUR SWZ SWE CHE SYR TJK TZA THA

62 68 43 28 53

19.695,96 58.406,46 6.072,84 6.923,45 387,66 2.329,43

42 46 41 42 54 30 86

987,64 18.033,69 805,80 3.987,62 14.235,84 513,19 36.897,87

47 57

15.065,31 18.357,46 4.482,49 1.112,85

8 42

5.916,46 1.060,66

14 59 37 71

24.573,06 2.004,26 10.490,99 5.920,26

62

5.613,42 1.008,70 1.000,61

11 36 39 89 85 17 22 33 35

771,08 4.636,69 2.429,75 44.208,40 55.469,27 480,63 502,08 3.437,84 11

Timor-Leste Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Turks and Caicos Islands Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States Upper middle income Uruguay Uzbekistan Vanuatu Venezuela, RB Vietnam Virgin Islands (U.S.) West Bank and Gaza World Yemen, Rep. Zambia Zimbabwe

TMP TGO TON TTO TUN TUR TKM TCA TUV UGA UKR ARE GBR USA UMC URY UZB VUT VEN VNM VIR WBG WLD YEM ZMB ZWE

30 29 38 41 50 17

26 25 69 76 73

816,17 424,35 2.661,74 14.370,22 3.994,89 8.716,68 3.556,98 2.648,45 414,76 2.138,28

20 31

37.985,42 45.863,02 4.487,54 7.808,63 899,38 2.109,95 6.401,91 1.028,63

18 38 21

7.850,17 742,20 821,56 441,15

73 17

Elaborate by Author: Alda Miftari. Matching data from World Bank database September 2014 and Transparency International Corruption Perceptions Index 2013 for all the countries in the world.

Analyzing Data: Is possible to individually the group of countries where is concentrated the majority of corruption in the world related to GDP per capita on this year. In this table we show all the data about Corruption Perceptions Index for 2013 and the GDP per capita 2013 for all the countries that we extract from database of World Bank and Corruption Perceptions Index and matched them. Generically speaking the result is very dependent between two variables so that mean that we have a good association of this two variables. The independent variable in this study is the GDP per capita and the dependent variable is Corruption Index. The table shows us the percentage of corruption about the countries. For 12

analyzing that we know that the threshold of 100 is about countries with a very low Corruption and for the Country about 0 we have a high corruption, but there is no any data with this indicator. For example start from 8 that is Afghanistan the country with higher corruption on the world for 2013 and the country with low corruption for 2013 is Denmark. Let’s say that is not the same for the GDP per capita, so doesn’t mean that the same country with the indicator of high Corruption have low Income. So for this we see the scatter chart Figure1 to create an clear idea.

Table 2. Shows the Correlation between Corruption Perceptions Index 2013 and GDP per capita 2013 in all the countries in the world.

Correlation: CPI 2013 score GDP.PC

CPI 2013 score

GDP.PC

1 0,801720081

1

The table 2 is showing as an strong correlation between the level of Corruption Perceptions Index 2013 and the GDP per capita (constant 2005 US$) on the year 2013. From the table you can see that the correlation value equal 0.8001720081 that is very high. So countries with High GDP per capita have an low corruption and the countries with a low GDP per capita have a high corruption.

Table 3. Shows the Regression Statistics for Corruption Perceptions Index (CPI) 2013. February 4, 2015 9:34 PM regressit Model 1 Model: Dependent Variable:

Model 1 CPI_2013_score

Regression Statistics:

Summary Table: Variable

Model 1 for CPI_2013_score

(1 variable, n=164)

R-Squared

Adj. RSqr

Std.Err.Reg.

# Cases

# Missing

t(2.50%,162)

Conf. level

0,643

0,641

11,740

164

94

1,975

95,0%

Model 1 for CPI_2013_score

(1 variable, n=164)

Coefficient

Std. Err.

t-Stat.

P-value

Lower95%

Upper95%

32,224 0,001039

1,112 0,000061

28,988 17,073

0,000 0,000

30,029 0,000919

34,419 0,001159

Intercept GDP_.PC 2013 Analysis of Variance:

Model 1 for CPI_2013_score

(1 variable, n=164)

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We have R-Squared (0.643). For the independent variable that is GDP per capita for the year 2013 we have a t-Stat (17.073) that is great than 2 and in this case we have a P-value (4.80E-38) that is less than (0.05) like 5%. The main objective of this study is to test the hypothesis that there is strong impact of Corruption Index on the GDP per capita. Chart 1. The Scatter Chart shows all the countries in the world related to Corruption Perceptions Index (PCI) for the year 2013 and the GDP per capita (constant 2005 US$) for 2013. 120

C o r r u p t i o n p . i n d e x

100

NZL

80

URY LCA CHL EST BWA BTNVCT CYPISR PRI POL PRT BRN ESP CPV DMALTU SVN KOR MLT 60RWA CRI HUN SYC LVA MUS MYS TUR LSO GEO NAM HRV CZE BHR OMN SVK GHA SAU JOR MKD MNE ROM ITA STP BIH SRB BRA ZAF SEN TUN BGR CHN GRC SWZ LBR ZMB BFA MNG SLV PER TTO MWI MAR LKA BEN IND PHL DJI ARM DZA COL SUR MDA THA ECU PAN 40 NER BOL GAB MEX ETH TZA KSV EGY IDN VNM NPL ALB MOZ TMP MRT SLE TGO GTM DOM BLR MDG GMB COM MLI PAK NIC AZE RUS LBN BGD KEN GUY CIV UGA LAO HND KAZ CAF CMR NGA PNG UKR IRN GIN KGZ PRY AGO ZAR TJK COG ZWE BDI KHM ERI VEN GNB TCD HTI YEM UZB TKM GNQ 20 IRQLBY SDN AFG

DNK FIN SWE SGP NLD CAN AUS DEU GBR HKG BEL JPN USA FRA AUT IRL

NOR

CHE ISL

LUX

QAT

0 0

10

20

30

40

50

60

70

80

90

GDP per capita

Author: Alda Miftari. Representation in a scatter chart of all the countries of two variables that is Corruption Perceptions Index (PCI) for the year 2013 and the GDP per capita (constant 2005 US$) for the 2013 .

This scatter chart shows us a stronger correlation(0.801720) between the Corruption Perceptions Index and GDP per capita. So if we have a lower GDP per capita (constant 2005 US$). we will have an higher Corruption for the country. This mean that Corruption is a quite significant related to GDP per capita and let’s focus that country with middle GDP per capita (constant 2005 US$) so most of developing countries have a high level of Corruption.

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Chart 2. The Scatter Chart for all the countries in the world related to Corruption Perceptions Index (PCI) for the year 2013 and GDP per capita (constant 2005 US$) for 2013 (value in logarithmical with labels for only the countries outliners).

Distribution of countries with outliers for Ln Corruption Perceptions Index (CPI) for the year 2013 and the Ln.GDP per capita (constant 2015 US $) for the year 2013 5,5

Ln. Corruption P. Index 2013

5,0 4,5 4,0 3,5 3,0 2,5 2,0 1,5 5

6

7

8

9

10

11

12

Ln. GDP per capita 2013

Distribution of countries with outliers for Ln Corruption Perceptions Index (CPI) for the year 2013 and the Ln GDP per capita (constant 2015 US $) for the year 2013. This representation is only for a better understand of the role of outliners and for the strong relationship between the Corruption Perceptions Index and the GDP per capita.

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Chart 3. The Scatter Chart for all the countries in the world related to Corruption Perceptions Index (PCI) for the year 2013 and GDP per capita (constant 2005 US$) for 2013 (value in logarithmical with labels for only the countries outliners). 5,0 C o r r u p t i o n

4,5

RWA 4,0

3,5

VEN IRQ TKM

3,0 P . i n d e x

GNQ

LBY

SDN

2,5

AFG 2,0

1,5 5

6

7

8

9

10

11

12

GDP per capita income Author: Alda Miftari. This is a representation for a scatter chart with logarithmic value and with labels for only the countries outliners for a better analyses.

Our study highlight the countries with a very strong correlation between the two variables that we are evaluating. So the most corrupt country in the world for the year 2013 according to Transparency International Corruption Perceptions Index and the World Bank Index in a relationship between the level of Corruption Index and GDP per capita is Afghanistan followed by Sudan, Lybia ect.

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3. The impact of Corruption on two groups of country with different level of income: OECD countries and Lower middle income countries on 2013.

Corruption is a crime danger to society and the state. The phenomenon of corruption, if it is not under control when he born he can be very dangerous for the society. In transition countries, corruption is rife in all items of life and thus becoming not only a serious obstacle to the development of the country but also a source of crime organized. From 1998 to present 31 countries have ratified the OECD Anti-Bribery Convention. At the end of 2005 the UN convention against corruption, the most comprehensive corruption convention to date, entered into force. In 2007 The World Bank launched its Strengthening World Bank Group Engagement on Governance and Anticorruption (GAC) strategy. Most estimates of corruption were based on surveys of perception. These perception surveys have the advantage of good coverage it is much easier to ask someone’s perceptions of corruption than to actually measure corruption directly. As such, they still form the basis of most cross-country corruption indices, such as Transparency International’s Annual Corruption Perception Index (CPI) and the World Bank’s Control of Corruption Index5. Perception-based measures were also used in some of the first empirical work in economics on corruption, such as Mauro’s (1995) cross-country study of the relationship between corruption and growth. Now let’s show two groups of countries with different income for each other.

5

The latter incorporates a variety of different aspects of corruption, ranging from the frequency with which firms make ―additional payments to get things done,‖ to the effects of corruption on the business environment, to measuring ―grand corruption‖ in the political arena.

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Table 4. Showing the difference in Mean (average) t-Test: Two-Sample Assuming Unequal Variances for the Corruption Perceptions Index for the countries with High income (OECD) and countries with Lower middle income for the year 2013.

t-Test: Two-Sample Assuming Unequal Variances

Mean Variance Observations Hypothesized Mean Difference Df t Stat P(T