Operational-5

MATERI PENUNJANG KULIAH

METODE PENELITIAN KOMUNIKASI I BAGIAN II

OPERASIONALISASI KONSEP DAN PENGUKURAN

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PROGRAM PASCASARJANA KEKHUSUSAN MANAJEMEN KOMUNIKASI POLITIK DEPARTEMEN I. KOMUNIKASI – FISIP-UI SEMESTER GENAP 2006

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CONCEPTUALIZATION - OPERATIONALIZATION - MEASUREMENT • CONCEPTUALIZATIO N

. . . is the refinement and specification of abstract concepts. (Babbie, 1992) . . . is the process of taking a constructs or concept and refining it by giving it a conceptual or theoretical definition (Neuman, 1997; pp. 133-134)

• CONCEPTUAL DEFINITION

. . . is a definition in abstract, theoretical terms

• OPERATIONALIZATIO N

. . . is the development of specific research procedures (operations) that will result in empirical observations representing those concepts in the real world. (Babbie, 1992) . . . is the process of developing an operational definition

(Neuman, 1997; pp. 133-134).

(Neuman, 1997; p.136

• OPERATIONAL DEFINITION

. . . is a definition in terms of specific operations, measurements instruments, or procedures (Neuman, 1997; p.136).

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• MEASUREMENT:

. . . the assignment of numeral symbols to objects or events according to rules. (Stevens, 1987)

HUMAN DEVELOPMENT INDEX UNDP (1996), Human Development Report 1995. New York: Oxford University Press HUMAN DEVELOPMENT a process of enlarging people’s choices . . . to lead a long and healthy life, to acquire knowledge and to have access to the resources needed for a descent standard of living.

LONGEVITY

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EDUCATIONAL ATTAINMENT

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STANDARD OF LIVING

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LIFE EXPECTANCY AT BIRTH INDEX (25-65 YRS)

ADULT LITERACY INDEX - 2/3 weight ( 0% - 100%)

COMBINED ENROLL-MENT RATIO INDEX 1/3 weight (0% 100%)

REAL GDP PER CAPITA (PPP$) $100 - $40.000

Index = Actual X value - Minimum X value Maximum X value - Minimum X value

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POLYARCHY INDEX Indeks Polyarchy dikembangkan sebagai Cummulative Rating Scale (Guttman-type Scale). Mengukur pluralisme politik berdasarkan keberadaan perangkat tatanan kelembagaan yang memungkinkan dan menjamin adanya oposisi publik dan hak untuk berpatisipasi dalam proses-proses politik . . . the set of institutional arrangements that permits public opposition and establishes the right to participate in politics (Coppedge and Reinicke, 1993; p.47).

CONCEPT

POLYARC HY

DIMENSI ONS

INDICATORS

FREE & FAIR ELECTION

1.No meaningful election are held 2.Marred by fraud and coercion 3.Meaningful fair election

FREEDOM OF ORGANIZA TION

1.All organizations are banned or controlled 2.Only nonpolitical organizations are allowed 3. Some independent political organizations are banned 4.Full freedom for political organization

FREEDOM OF EXPRESSIO N

1.All public dissent is suppressed 2.Some public dissent is supressed 3.Full freedom of expression

AVAILABILI TY OF

1.No public alternative to official information

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ALTERNATI VE INFO SOURCES

2.Alternative sources exist only for nonpolitical issues 3.There is preferential presentation of official views in the media 4.No preferential presentation of official views in the media

Disusun berdasarkan: Coppedge and Reinicke (1993) “Measuring Polyarchy”. In Inkeles, Inkeles, Alex (Ed.), On Measuring Democracy: Its Cosequences and Concomitants. New Brunswick, London: Transaction Publishers; pp. 47-68.

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Exposure to Violence Film / Terpaan Film-film Kekerasan CONCEPTUAL DEFINITION Adegan-adegan kekerasan dalam film yang dikonsumsi individu OPERATIONAL DEFINITION

MANIPULATED / EXPERIMENTAL VARIABLE

e.g. RANDOM ASSIGMENTS Penempatan responden secara random kedalam OPERATIONAL98/10/28/2008

MEASURED / OBSERVED VARIABLE

VERBAL REPORTS Pengakuan verbal

OBSERVATIO N Pengamatan terhadap dedy n. hidayat

RECORDS Catatan tentang filmfilm violence 7

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kelompok yang menonton film violence atau kelompok yang menonton film nonviolence

CONCEPT / CONSTRU CT

responden tentang frekuensi ratarata menonton film-film yang dinilai bertema violence selama periode tertentu

individu tentang frekuensi, pola, intensitas dsb menonton film-film yang dinilai bertema violence

yang pernah ditonton selama periode waktu tertentu

ORGANIZATIONAL COMPLEXITY Conceptual definition: the degree of internal differentiation of an organization

DIMENSIO NS

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VERTICAL

HORIZONTAL

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SPATIAL DISPERSION

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INDICATO RS

Number of levels in the deepest single divisions, and the mean number of levels for the organization as a whole (Hall)

Number of specialties or functional areas (Hage)

Number of location of branches and subsidiaries

INTRA-MEDIA OBJECTIVITY - WESTERSTAHL MODEL KONSEP

DIMENSI

SUB-DIMENSI • FACTUALNESS:

TRUTH

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Pemisahan yang jelas antara fakta dan opini • ACCURACY: Kesesuaian antara pemberitaan dan fakta • COMPLETENESS: Kelengkapan relevant information yang diperlukan untuk memahami apa yang diberitakan dedy n. hidayat

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FACTUALITY cognitive

RELEVANCE

•Semua informasi yang diberitakan hanya menyangkut kepentingan untuk memahami fakta peristiwa atau objek yang diberitakan (nonsensationalism)

OBJECTIVIT Y BALANCE NONPARTISANSHIP

•Keberimbangan dalam pemilihan fakta, sumber berita, opini atau perspektif

NEUTRAL PRESENTATIO N

•Ketidakberpihakan dalam penyajian fakta, a.l., pemilihan kata, penempatan dalam struktur berita, tata letak, visualisasi, dsb.

IMPARTIALI TY evaluative

Westerstahl (1983)

CONCEPT

DIMENSIONS

SUB-DIMENSIONS

INDICES •Factuality

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INDICATORS ?

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•Truth (in

presentation)

•Accuracy

?

•Completeness

?

•Normative standards •Journalistic standards

?

•Audience standards •Real-world indicators

?

•Non-evaluative

?

•Non-sensational

?

•Proportional

?

•FACTUALITY (cognitive dimension) ?

•Relevance (in selection)

OBJECTIVIT Y•

•Neutrality (in

?

presentation)

•IMPARTIALITY (evaluative dimension)

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access •Balance (in selection) Disusun berdasarkan Westerstahl (1983) dan McQuail (1992)

•Even-handed evaluation

?

INDEXES vs SCALES •

Both scales and indexes are composite measure of variables: i.e., measurement based on more than one data item(Babbie, 1996; pp. 166-167)

•An index is constructed through the simple accumulation of scores assigned to individuals attributes.

•A scale is constructed through the assignment of scores to patterns of attributes •A scale . . . captures the intensity, direction, level, or potency of a variable construct. (Neuman, 1997; p.152)

A Case: Measurement INDEX The logic:the different actions represent similar degrees of political activism; we might give people 1 point for each of the actions they’ve taken

of Political Activism SCALE The logic: the different political actions represent different degree of activism, e.g., running for office represents a higher degree of activism than simply

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voting. 1.Wrote a letter to a public official 2.Signed a political petition 3.Gave money to a political candidate 4.Wrote a political letter to the editor 5.Persuaded someone to change their voting plans 6.Gave money to a political cause

1. Run for office 2. Worked on a political campaign 3. Contributed money to a political campaign 4. Voted

TYPES OF SCALE (Isaac and Michael, 1983; Babbie, 1996,)

INDEX •An index is constructed through the simple accumulation of scores assigned to individuals attributes.

SUMMATIVE RATING SCALE (Likert-type Scale) OPERATIONAL98/10/28/2008

SEMANTIC DIFFERENTIAL SCALE

SCALE •A scale is constructed through the assignment of scores to patterns of attributes

EQUALAPPEARING SCALE dedy n. hidayat

CUMMULATIVE RATING SCALE (Guttman-type 13

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Contains a set of items, all of which are considered approximately equal in value loading. The scores for each item are summed to yield individual’s score

Contains a set of bipolar adjectives, all of which are considered approximately equal in value loading. The scores of each bipolar adjective are summed to yield individual’s score

(Thurstone-type Scale)

Scale)

Contains a set of item all of which are assumed to be differentially ordered (Each item is assigned a scale value indicating the value for an agreement response to the item.

Consists of a relatively small set of homogeneous items that are supposedly unidimensional, measuring one attribute (items can be ordered in difficulty, complexity, or value loading)

LIKERT-TYPE - SUMMATED RATING SCALE: MATERIALISM SCALE (Belk, 1985) CONCEPT OPERATIONAL98/10/28/2008

DIMENSIONS

INDICATORS dedy n. hidayat

SD

D

Un

A

SA 14

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1. I would rather buy something I need than borrow it from someone

1

2

3

4

5

2. I worry about people taking my possesions

1

2

3

4

5

3. I enjoy having guests stay in my home

5

4

3

2

1

4. I do not like to lend things, even to my good friends

1

2

3

4

5

5. There certain people I would like to trade places with

5

4

3

2

1

6. When friends do better than me, it usually makes me happy for them SD=strongly disagree D=disagree UN=uncertain A=agree SA=strongly agree

5

4

3

2

1

Possesiveness:

the tendency to retain control of one’s possesions.

MATERIALISM:

Nongenerosity:

the importance a consumer attaches to worldly possesions

unwillingness to give or to share possesions

Envy:

the displeasure at the superiority of another person in happiness, success or the possesion

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GUTTMAN-TYPE - CUMMULATIVE RATING SCALE: BOGARDUS’ SOCIAL-RACIAL DISTANCE SCALE Social distance: . . . the degree of social acceptance that exists between given persons and certain social groups (Miller, 1991; p.378); . . . the grades and degrees of understanding and intimacy which characterize pre-social and social relations generally (Park, 1902; pp. 339-344).

1. Are you willing to permit Albanians to live in your country? 2. Are you willing to permit Albanians to live in your community? 3. Are you willing to permit Albanians to live in your neighbothood? 4. Are you willing to let an live next door to you? 5. Would you let your child marry an Albanian? (Source: Babbie, 1992; p.182)

Mean of Racial Distance Quotients (RDQs) given to racial groups in 1956 by 2.035 white Americans: Racial groups of RDQ 1. Canadians 2. English

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1.16

Mean of RDQ

Racial groups

1.08

7. Filipinos Chinese

8.

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Mean 2.46 2.56

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3.

French

1.47

9.

4. 5. 6.

Irish Igerman Jews

1.56 1.61

10. Black Americans 11. Mexicans 12. Koreans

2.15

Japanese

2.70 2.74 2.79 2.83

(Source: Miller, 1991; p.379)

SEMANTIC DIFFERENTIAL SCALE: CELEBRITY ENDORSER’S CREDIBILITY SCALE concept

dimension

subdimensi on

indicators 1 2 3 4 5 6 7

physical attractiveness of the source

1.unattracti • • •Beauty •Chicness ve • • 2.not •Elegance • • classy • • 3.ugly • • 4.plain 5.not sexy

• TRUSTWOTHIN ESS

•Trust •Accepta nce

• ATTRACTIVENE SS

Celebrity Endorser ’s

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1.undepen dable 2.dishonest 3.unreliabl

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• • • • •

• • • • •

• • • • •

• • • • •

• • • • •

attractive classy beautiful elegant sexy

• • • • • • • dependable • • • • • • • honest • • • • • • • reliable sincere 17

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Credibili ty (Ohanian, 1990)

the degree of confidence in the communicator’s intent to communicate the assertions s/he considers valid

• EXPERTISE the extent to which the communicator is perceived to be a source of valid assertions about the object/message

e 4.insincere 5.untrustw orthy

•Compete 1.not an expert nce •Expertne 2.inexperie nced ss •Qualifica 3.unkowled gea tion 4.unqualifie d 5.unskilled

• • • • • • • trustworthy • • • • • • •

• • • • •

• • • • •

• • • • •

• • • • •

• • • • •

• • • • •

• • • • •

expert experience d knowledge able qualified skilled

EQUAL-APPEARING SCALE: THURSTONE-TYPE RATING SCALE • A group of judges is given a number of items (statements) felt to be indicators of a given variable/concept. • Each judge is then asked to estimate how strong an indicator of a variable each item is -- by assigning scores of perhaps 1 to 10. OPERATIONAL98/10/28/2008

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•

The researcher examines the scores assigned to each item by all the judges to determine which items produced the agreement among the judges. (Babbie, 1992; p.183).

Contoh: Pemberian skor oleh para juri dalam penyusunan skala Sikap Terhadap Aksi Unjuk Rasa Buruh Berikanlah skor dari 1-10 terhadap setiap pernyataan; bila suatu item pernyataan anda nilai semakin mencerminkan sikap positif terhadap aksi unjuk rasa semakin besar skor yang anda berikan. Item Pernyataan

1

1. Aksi unjukrasa buruh merupakan hak azasi para buruh 2. Aksi unjukrasa buruh perlu dinetralisir dari penunggangan politik 3. Unjuk rasa buruh bisa menurunkan arus investasi modal LN 4. Tuntutan unjukrasa buruh sering tak sesuai dengan kaidah bisnis 5. Unjukrasa adalah salah satu mekanisme kontrol terhadap kapitalis 6. Tanpa unjukrasa, pengusaha cenderung semakin OPERATIONAL98/10/28/2008

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2

Juri 3 4

5

6

Skor rata2 9.5 5.2 5.1 5.2 9.0 8.5 19

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eksploitatif

SKALA / TINGKAT PENGUKURAN • X

• Y

• Z KARAKTERISTIK MATEMATIK SKALA PENGUKURAN

KATEGORISASI DATA X≠Y≠Z JENJANG KATEGORI X>Y>Z

NOMINAL

ORDINAL

INTERVAL

RATIO

V

V

V

V

V

V

V

V

V

JARAK INTERVAL (XZ) - (XY) = (YZ)

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PERBANDINGAN X - Z = 2 (XY)

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PENJENJANGAN HIPOTESIS DALAM STRUKTUR SUATU PENELITIAN PERMASALAHAN Faktor-faktor apakah yang mempengaruhi Partisipasi Politik individu?

KERANGKA TEORI THEORETIC HYPOTHESIS CONCEPTUAL DEFINITIONS Status Sosial-Ekonomi individu mempengaruhi Partisipasi Politik

X

Y

• Status Sosial-Ekonomi: Kedudukan individu dalam suatu stratifikasi sosial yang didasarkan atas kemampuan ekonomi, tingkat pendidikan, dan pekerjaan • Partisipasi Politik: Keikutsertaan individu dalam aktivitas mempengaruhi input serta proses suatu sistem politik

METODOLOGI RESEARCH HYPOTHESIS OPERATIONAL DEFINITIONS Variabel Tingkat SosialEkonomi berhubungan positif dengan Tingkat Partisipasi Politik: semakin tinggi Status SosialEkonomi semakin tinggi pula Variabel Tingkat Partisipasi Politik

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• Status Sosial-Ekonomi: skor yang diberikan terhadap pengakuan verbal individu tentang penghasilan, penmdidikan dan jabatan pekerjaannya • Partisipasi Politik: skor yang diberikan terhadap pengakuan verbal dedy n. hidayat 22

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X

Y

individu tentang frekuensi dan posisi keikutsertaan dalam kampanye pemilu, aktivitas orpol, demo, donasi, pemberian suara.

STATISTICAL HYPOTHESIS

STATISTICAL DEFINITIONS

rXY >0

Variabel Status SosialEkonomi dan variabel Tingkat Partisipasi Politik diukur sebagai variabel interval

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Metodologi Penelitian – Program Pascasarjana Dept. I. Komunikasi FISIP-UI

HUMAN DEVELOPMENT INDEX •

A long and healthy life, as measured by life expectancy at birth.

•

Knowledge, as measured by the adult literacy rate (with two-thirds weight) and the combined primary, secondary, and tertiary gross enrollment ratio (with one-third weight).

•

A decent standard of living, as measured by gross domestic product (GDP) per capita at purchasing power parity (PPP) in USD.

Each year, UN member states are listed and ranked according to these measures. Those high on the list often advertise it, as a means of attracting talented immigrants (economically, individual capital) or discouraging emigration.

Method used to calculate the Human Development Index The Human Development Index (HDI) represents the average of the following three indices:

•

Life Expectancy Index =

•

Education Index =

•

•

Adult Literacy Index (ALI) =

•

Gross Enrollment Index (GEI) =

GDP Index =

LE: Life expectancy ALR: Adult literacy rate CGER: Combined gross enrollment ratio GDPpc: GDP per capita at PPP in USD

http://en.wikipedia.org/wiki/Gini_coefficient

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Metodologi Penelitian – Program Pascasarjana Dept. I. Komunikasi FISIP-UI

GINI COEFFICIENT The Gini coefficient is a measure of inequality developed by the Italian statistician Corrado Gini and published in his 1912 paper "Variabilità e mutabilità". It is usually used to measure income inequality, but can be used to measure any form of uneven distribution. The Gini coefficient is a number between 0 and 1, where 0 corresponds with perfect equality (where everyone has the same income) and 1 corresponds with perfect inequality (where one person has all the income, and everyone else has zero income). The Gini index is the Gini coefficient expressed in percentage form, and is equal to the Gini coefficient multiplied by 100. While the Gini coefficient is mostly used to measure income inequality, it can also be used to measure wealth inequality. This use requires that no one has a negative net wealth.

Calculation Graphical representation of the Gini coefficient

The Gini coefficient is calculated as a ratio of the areas on the Lorenz curve diagram. If the area between the line of perfect equality and Lorenz curve is A, and the area underneath the Lorenz curve is B, then the Gini coefficient is A/(A+B). This ratio is expressed as a percentage or as the numerical equivalent of that percentage, which is always a number between 0 and 1. The Gini coefficient is often calculated with the more practical Brown Formula shown below:

G: Gini coefficient Xk: cumulated proportion of the population variable, for k = 0,...,n, with X0 = 0, Xn = 1 Yk: cumulated proportion of the income variable, for k = 0,...,n, with Y0 = 0, Yn = 1

The small sample variance properties of G are not known, and large sample approximations to the variance of G are poor. In order for G to be an unbiased estimate of the true population value, it should be multiplied by n/(n-1). Advantages of the Gini coefficient as a measure of inequality •

The Gini coefficient's main advantage is that it is a measure of inequality, not a measure of average income or some other variable which is unrepresentative of most of the population, such as gross domestic product.

http://en.wikipedia.org/wiki/Gini_coefficient

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Metodologi Penelitian – Program Pascasarjana Dept. I. Komunikasi FISIP-UI •

Gini coefficients can be used to compare income distributions across different population sectors as well as countries, for example the Gini coefficient for urban areas differs from that of rural areas in many countries (though the United States' urban and rural Gini coefficients are nearly identical).

•

The Gini coefficient is sufficiently simple that it can be compared across countries and be easily interpreted. GDP statistics are often criticised as they do not represent changes for the whole population, the Gini coefficient demonstrates how income has changed for poor and rich. If the Gini coefficient is rising as well as GDP, poverty may not be improving for the vast majority of the population.

•

The Gini coefficient can be used to indicate how the distribution of income has changed within a country over a period of time, thus it is possible to see if inequality is increasing or decreasing.

•

The Gini coefficient satisfies four important principles: o

Anonymity: it doesn’t matter who the high and low earners are.

o

Scale independence: the Gini coefficient does not consider the size of the economy, the way it is measured, or whether it is a rich or poor country on average.

o

Population independence: it does not matter how large the population of the country is.

o

Transfer principle: if income (less than the difference), is transferred from a rich person to a poor person the resulting distribution is more equal.

Disadvantages of the Gini coefficient as a measure of inequality •

The Gini coefficient measured for a large geographically diverse country will generally result in a much higher coefficient than each of its regions has individually. For this reason the scores calculated for individual countries within the E.U. are difficult to compare with the score of the entire U.S.

•

Comparing income distributions among countries may be difficult because benefits systems may differ. For example, some countries give benefits in the form of money while others use food stamps, which may not be counted as income in the Lorenz curve and therefore not taken into account in the Gini coefficient.

•

The measure will give different results when applied to individuals instead of households. When different populations are not measured with consistent definitions, comparison is not meaningful.

•

The Lorenz curve may understate the actual amount of inequality if richer households are able to use income more efficiently than lower income households. From another point of view, measured inequality may be the result of more or less efficient use of household incomes.

•

As for all statistics, there will be systematic and random errors in the data. The meaning of the Gini coefficient decreases as the data become less accurate. Also, countries may collect data differently, making it difficult to compare statistics between countries.

•

Economies with similar incomes and Gini coefficients can still have very different income distributions. This is because the Lorenz curves can have different shapes and yet still yield the same Gini coefficient. As an extreme example, an economy where half the households have no income, and the other half share income equally has a Gini coefficient of ½; but an economy with complete income equality, except for one wealthy household that has half the total income, also has a Gini coefficient of ½.

•

It is claimed that the Gini coefficient is more sensitive to the income of the middle classes than to that of the extremes.

•

Too often only the Gini coefficient is quoted without describing the proportions of the quantiles used for measurement. As with other inequality coefficients, the Gini coefficient is influenced by the granularity of the measurements. For example, five 20% quantiles (low granularity) will yield a lower Gini coefficient than twenty 5% quantiles (high granularity) taken from the same distribution.

http://en.wikipedia.org/wiki/Gini_coefficient

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Metodologi Penelitian – Program Pascasarjana Dept. I. Komunikasi FISIP-UI

As one result of this criticism, additionally to or in competition with the Gini coefficient entropy measures are frequently used (e.g. the Atkinson and Theil indices). These measures attempt to compare the distribution of resources by intelligent players in the market with a maximum entropy random distribution, which would occur if these players acted like nonintelligent particles in a closed system following the laws of statistical physics

MISERY INDEX During the Presidential campaign of 1976 campaign, Democratic candidate Jimmy Carter made frequent references to the Misery Index. The term -- coined by Chicago Economist Robert Barro in the 1970s -- simply adds together the rates of inflation and unemployment, and by the summer of 1976 the Misery Index was 13.57%. Carter stated that no man responsible for giving the country a misery index that high had a right to even ask to be President. Carter, of course, won the 1976 election. However, by 1980, when President Carter was running for re-election against Ronald Reagan, the Misery Index had reached an all-time high of 21.98%. Carter lost the election to Reagan. The lowest index since 1948 was 2.97%, in August 2001. Jimmy Carter offers insights into topics in American history including the Great Depression, sharecropping, segregation, the economic and political rise of the South, presidential campaigns and elections, the presidency, presidential speeches, energy policy, inflation, unemployment, international diplomacy, peace and war in the Middle East, the Iranian hostage crisis, terrorism, foreign relations with fundamentalist Muslim countries, the role of ex-presidents, and the fight to eradicate disease. Use part or all of the film, or delve into the rich resources available on this Web site to learn more, either in a classroom or on your own. The following activities are grouped into 4 categories: history, economics, geography, and culture. You can also read a few helpful hints for completing the activities. 1. The poor economic record of the Carter years -- and in particular, the unusual combination of high inflation and high unemployment -- was an important reason for Carter's loss of popularity and his 1980 defeat. Using the data in the table below, draw a graph with two lines: one representing the change in inflation between 1973 and 1980, and the other representing the change in unemployment during that period. Be sure to label both lines. Then draw another graph representing the change in the "misery index" for the period. (The misery index is the sum of the inflation rate and unemployment rate for a given year.) What do these graphs suggest about the success of Carter's economic policies? Is there any information in these graphs that Carter could have used to defend those policies? Year

Inflation Rate (percent)

Unemployment Rate (percent)

1973

6.2

4.8

1974

11.0

5.5

1975

9.1

8.3

1976

5.8

7.6

1977

6.5

6.9

1978

7.7

6.0

1979

11.3

5.8

1980

13.5

7.0

Source: Statistical Abstract of the United States

http://en.wikipedia.org/wiki/Gini_coefficient

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Metodologi Penelitian – Program Pascasarjana Dept. I. Komunikasi FISIP-UI

CORRUPTION PERCEPTIONS INDEX Since 1995, Transparency International has published an annual Index of perception of corruption ordering the countries of the world according to "the degree to which corruption is perceived to exist among public officials and politicians."[1] The organization defines corruption as "the abuse of public office for private gain".[2] The 2003 poll covered 133 countries; the 2005 survey, 159. The results show seven out of every ten countries (and nine out of every ten developing countries) with an index of less than 5 points out of 10.

Methods and interpretation TI claims that the CPI 2005 draws on "16 different polls and surveys from 10 independent institutions… The institutions who provided data for the CPI 2005 are: Columbia University, Economist Intelligence Unit, Freedom House, Information International, International Institute for Management Development, Merchant International Group, Political and Economic Risk Consultancy, United Nations Economic Commission for Africa, World Economic Forum and World Markets Research Centre." Early CPIs used public opinion surveys, but now only "experts" are used. TI requires at least three sources to be available in order to rank a country in the CPI. [3] TI writes in their FAQ on the CPI that "residents' viewpoints correlate well with those of experts abroad. In the past, the experts surveyed in the CPI sources were often business people from industrialised countries; the viewpoint of less developed countries was underrepresented. This has changed over time, giving increasingly voice to respondents from emerging market economies."[4] As this index is based on polls, the results are subjective and are less reliable for countries with fewer sources. Also, what is legally defined, or perceived, to be corruption differs between jurisdictions: a political donation legal in some jurisdiction may be illegal in another; a matter viewed as acceptable tipping in one country may be viewed as bribery in another. Thus the poll results must be understood quite specifically as measuring public perception rather than being an objective measure of corruption. Statistics like this are necessarily imprecise; statistics from different years are not necessarily comparable. The ICCR itself explains, "…year-to-year changes in a country's score result not only from a changing perception of a country's performance but also from a changing sample and methodology. Each year, some sources are not updated and must be dropped from the CPI, while new, reliable sources are added. With differing respondents and slightly differing methodologies, a change in a country's score may also relate to the fact that different viewpoints have been collected and different questions been asked… [despite] anti-corruption reform… [or] recent exposure of corruption scandals… [i]t is often difficult to improve a CPI score over a short time period, such as one or two years. The CPI is based on data from the past three years (for more on this, see the question on the sources of data, below). This means that a change in perceptions of corruption would only emerge in the index over longer periods of time."[5]

http://en.wikipedia.org/wiki/Gini_coefficient

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Metodologi Penelitian – Program Pascasarjana Dept. I. Komunikasi FISIP-UI

INDEX OF ECONOMIC FREEDOM The Indexes of Economic Freedom are several similar indexes released annually. One is published by The Wall Street Journal and conservative think-tank the Heritage Foundation. Another by the Fraser Institute.

Methodology The Heritage index measures how countries score on a list of 50 independent variables. They include: •

Corruption in the judiciary, customs service, and government bureaucracy;

•

Non-tariff barriers to trade, such as import bans and quotas as well as strict labeling and licensing requirements;

•

The fiscal burden of government, which encompasses income tax rates, corporate tax rates, and trends in government expenditures as a percent of output;

•

The rule of law, efficiency within the judiciary, and the ability to enforce contracts;

•

Regulatory burdens on business, including health, safety, and environmental regulation;

•

Restrictions on banks regarding financial services, such as selling securities and insurance;

•

Labor market regulations, such as established work weeks and mandatory separation pay; and

•

Informal market activities, including corruption, smuggling, piracy of intellectual property rights, and the underground provision of labor and other services.

These are divided into 10 broad factors of economic freedom: •

Trade policy,

•

Fiscal burden of government,

•

Government intervention in the economy,

•

Monetary policy,

•

Capital flows and foreign investment, •

Banking and finance,

•

Wages and prices,

•

Property rights,

•

Regulation, and

•

Informal market activity

Research Economic Freedom, as defined by the Heritage Foundation, is statistically correlated with a higher GDP/Capita. http://en.wikipedia.org/wiki/Gini_coefficient

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Metodologi Penelitian – Program Pascasarjana Dept. I. Komunikasi FISIP-UI

Many peer-reviewed articles have used these indices. [1] [2] One question has The higher a country's score on a factor the less economic freedom there is. The 10 factors are given equal weight in determining the final score. Depending on their score, countries are then separated into four categories: Free, Mostly Free, Mostly Unfree, and Repressed. been what subcomponents are responsible for economic growth. Strong property rights and low inflation may be particularly important. Regarding the size of government and free trade there is much conflicting evidence. More economic freedom correlates strongly with higher average income per person, higher income of the poorest 10%, higher life-expectancy, higher literacy, lower infant mortality, higher access to water sources and less corruption. The share of income in percent going to the poorest 10% is the same for both more and less capitalistic countries. [3]. An overview of research can be found here [4], including studies showing that more economic freedom is the cause of beneficial effects.

Criticism Some economists and commentators have criticized the Index on several grounds—asking, for instance, if Canada's slightly higher income tax rates make it a less economically free country than the United States. Critics of the index's methodology most commonly take issue with its equation of regressive taxation, low tax rates generally, and weak worker protection regulations with economic freedom. Some critics go further, saying that the index judges countries against a specious list of 'ideal' economic and fiscal policies, which reflect the Heritage Foundation and Wall Street Journal 's own laissez-faire economic and fiscal policy ideas more than they do a substantive concept of economic freedom. For such critics, the list is simply a promotional tool for laissez-faire policy, rather than a meaningful index of economically free countries. In response, proponents point out that the indexes and their subcomponents have been used in much research, independent of the creators of the indices, published in numerous peerreviewed papers. Such peer-review includes the methodology used in creating the indices. That the creators of the indexes support laissez-faire capitalism does not invalidate the empirical research. Also, this independent research do not necessarily support the ideals of laissez-faire. For example, when examining the effects of subcomponents of the index, any positive effect a low level of taxes is much more disputed than the importance of rule of law and functioning property rights.

QUALITY OF LIFE INDEX The well-being or quality of life of a population is an important concern in economics and political science. There are many components to well-being. A large part is standard of living, the amount of money and access to goods and services that a person has; these numbers are fairly easily measured. Others like freedom, happiness, art, environmental health, and innovation are far harder to measure. This has created an inevitable imbalance as programs and policies are created to fit the easily available economic numbers while ignoring the other measures, that are very difficult to plan for or assess. Debate on quality of life is millennia-old, with Aristotle giving it much thought in his Nicomachean Ethics and eventually settling on the notion of eudaimonia, a Greek term often http://en.wikipedia.org/wiki/Gini_coefficient

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Metodologi Penelitian – Program Pascasarjana Dept. I. Komunikasi FISIP-UI

translated as happiness, as central. The neologism liveability (commonly but less correctly livability), from the adjective liveable, is an abstract noun now often applied to the built environment or a town or city, meaning its overall contribution to the quality of life of inhabitants. Understanding quality of life is today particularly important in health care, where monetary measures do not readily apply. Decisions on what research or treatments to invest the most in are closely related to their effect of a patient's quality of life. Quality of Life also refers to the first White House regulatory review program started in the Nixon Adminstration. See quality of life in (5)"See Also" below.

Measuring quality of life The measures often used in the study of health care are 'quality-adjusted life years' (QALYs) and the related 'disability-adjusted life years' (DALYs); both equal 1 for each year of full-health life, and less than 1 for various degrees of illness or disability. Thus the cost-effectiveness of a treatment can be assessed by the cost per QALY or DALY it produces; for example, a cancer treatment which costs $10,000 and on average gives the patient 2 extra years of full health costs $5000 per QALY. Assessing treatments in this way avoids the much greater problems associated with putting a monetary value on life, as required in other areas of economics; saying that a treatment costs $5000 per QALY (i.e. per year of life) does not say or assume anything about the monetary value of a year of life. Another method of measuring quality of life is by subtracting the "standard of living", according to the technical definition of the term. For example, people in rural areas and small towns are generally reluctant to move to cities, even if it would mean a substantial increase in their standard of living. One can thus see that the quality of life of living in a rural area is of enough value to offset a higher standard of living. Similarly people must be paid more to accept jobs that will lower their quality of life, night jobs, ones with extensive travel all pay more and the difference in salaries can also give a measure of the value of quality of life. There is a growing field of research concerned with developing, evaluating and applying quality of life measures within health related research (eg within randomised controlled trials). Many of these focus on the measurement of health related quality of life (HRQoL), rather than a more global conceptualisation of quality of life. They also focus on measuring HRQoL from the perspective of the patient and thus take the form of self completed questionnaires. The International Society for Quality of Life was founded in response to this research and is a useful source of information on this topic.

Gap Between Rich and Poor: World Income Inequality

http://en.wikipedia.org/wiki/Gini_coefficient

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Metodologi Penelitian – Program Pascasarjana Dept. I. Komunikasi FISIP-UI

Percentage share of income (poorest and richest 20% of population) To understand how many inhabitants of a country are poor, it is not enough to know a country's per capita income. The number of poor people in a country and the average quality of life depend on how equally or unequally income is distributed across the population. In Brazil and Hungary, for example, per capita income levels are quite comparable, but the incidence of poverty in Brazil is much higher. In Hungary the richest 20% of the population receives about four times more income than the poorest 20%, whereas in Brazil the richest 20% receives 30 times more than the poorest 20%.  

Countries with 

Lowest 

greatest inequality

Gini  index

 1.

Sierra Leone

62.9

1.1%

63.4%

 2.

Central African Republic

61.3

2.0

65.0

 3.

Swaziland

60.9

2.7

64.4

 4.

Brazil

60.7

2.2

64.1

 5.

Nicaragua

60.3

2.3

63.6

 6.

South Africa

59.3

2.9

64.8

 7.

Paraguay

57.7

1.9

60.7

 8.

Colombia

57.1

3.0

60.9

 9.

Chile

56.7

3.3

61.0

10.

Honduras

56.3

2.2

59.4

11.

Guinea­Bissau

56.2

2.1

58.9

12.

Lesotho

56.0

2.8

60.1

13.

Guatemala

55.8

3.8

60.6

14.

Burkina Faso

55.1

4.6

60.4

15.

Mexico

53.1

3.5

57.4

16.

Zambia

52.6

3.3

56.6

17.

Hong Kong, China

52.2

4.4

57.1

17.

El Salvador

52.2

3.3

56.4

19.

Papua New Guinea

50.9

4.5

56.5

20.

Nigeria

50.6

4.4

55.7

21.

Mali

50.5

4.6

56.2

21.

Niger

50.5

2.6

53.3

http://en.wikipedia.org/wiki/Gini_coefficient

20%

Highest  20%

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Metodologi Penelitian – Program Pascasarjana Dept. I. Komunikasi FISIP-UI

23.

Gambia

50.2

4.0

55.3

24.

Zimbabwe

50.1

4.7

55.7

25.

Venezuela

49.5

3.0

53.2

26.

Malaysia

49.2

4.4

54.3

27.

Russia

48.7

4.4

53.7

28.

Panama

48.5

3.6

52.8

29.

Cameroon

47.7

4.6

53.1

30.

Dominican Republic

47.4

5.1

53.3

 

Countries with  greatest equality

Gini  Index

 1.

Slovakia

19.5

11.9%

31.4%

 2.

Belarus

21.7

11.4

33.3

 3.

Hungary

24.4

10.0

34.4

 4.

Denmark

24.7

9.6

34.5

 5.

Japan

24.9

10.6

35.7

 6.

Sweden

25.0

9.6

34.5

 7.

Czech Republic

25.4

10.3

35.9

 8.

Finland

25.6

10.0

35.8

 9.

Norway

25.8

9.7

35.8

10.

Bulgaria

26.4

10.1

36.8

11.

Luxembourg

26.9

9.4

36.5

12.

Italy

27.3

8.7

36.3

13.

Slovenia

28.4

9.1

37.7

14.

Belgium

28.7

8.3

37.3

15.

Egypt

28.9

9.8

39.0

15.

Rwanda

28.9

9.7

39.1

17.

Croatia

29.0

8.8

38.0

17.

Ukraine

29.0

8.8

37.8

19.

Germany

30.0

8.2

38.5

20.

Austria

31.0

6.9

38.0

21.

Romania

31.1

8.0

39.5

http://en.wikipedia.org/wiki/Gini_coefficient

Lowest  20%

Highest  20%

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Metodologi Penelitian – Program Pascasarjana Dept. I. Komunikasi FISIP-UI

22.

Pakistan

31.2

9.5

41.1

23.

Canada

31.5

7.5

39.3

24.

Korea, South

31.6

7.5

39.3

25.

Poland

31.6

7.8

39.7

26.

Indonesia

31.7

9.0

41.1

27.

Latvia

32.4

7.6

40.3

27.

Lithuania

32.4

7.8

40.3

29.

Spain

32.5

7.5

40.3

30.

Netherlands

32.6

7.3

40.1

NOTE: Countries are ranked according to the Gini index (or coefficient), a measure of income inequality within a country.  A country's Gini rating is between 0 and 100, with 0 indicating perfect equality and 100 indicating absolute inequality. (The  U.S. rates 40.8 on the Gini index—the poorest 20% of its population receives 5.2% of income; the richest 20% receives  46.4%.) 

Source: World Development Index 2002, The World Bank

Measuring Global Poverty Traditionally, poverty has been measured by the lack of a minimum income (or consumption level) necessary to meet basic needs. Measuring poverty on a global scale requires establishing a uniform poverty level across extremely divergent economies, which can result in only rough comparisons. The World Bank has defined the international poverty line as U.S. $1 and $2 per day in 1993 Purchasing Power Parity (PPP)1, which adjusts for differences in the prices of goods and services between countries. The $1 per day level is generally used for the least developed countries, primarily African; the $2-per-day level is used for middle income economies such as those of East Asia and Latin America. By this measure, in 2003 there were 1.2 billion out of the developing world's 4.8 billion people living on $1 per day, while another 2.8 billion were living on less than $2 per day2. In 2003, the richest fifth of the world's population received 85% of the total world income, while the poorest fifth received just 1.4% of the global income. The $1- and $2-per-day measures offer a convenient, albeit crude, way to quantify global poverty. In the last several decades, poverty research has adopted a broader, multidimensional approach, taking into account a variety of social indicators in addition to income. The UN's Human Poverty Index, for example, factors in illiteracy, malnutrition among children, early death, poor health care, and poor access to safe water. Vulnerability to famine or flooding, lack of sanitation, exposure to disease, a diet poor in nutrients, and the absence of education are as much the signs of poverty as material deprivation. Providing the poor with basic social services and infrastructure would in many cases alleviate poverty to a greater extent than simply a rise in income level. 1. Purchasing power parity (PPP), as defined by the World Bank, is “a method of measuring the relative purchasing power  of different countries’ currencies over the same types of goods and services. Because goods and services may cost more  in one country than in another, PPP allows us to make more accurate comparisons of standards of living across  countries.” 

http://en.wikipedia.org/wiki/Gini_coefficient

34

Metodologi Penelitian – Program Pascasarjana Dept. I. Komunikasi FISIP-UI 2. The original $1 per day was based on 1985 PPP estimates; currently the poverty line is based on 1993 PPP estimates,  which has raised the amount from $1.00 to $1.08. As a convention, “$1 a day” is still widely used when discussing income  poverty

Most and Least Livable Countries: UN Human Development Index, 2005 The Human Development Index (HDI), published annually by the UN, ranks nations according to their citizens' quality of life rather than strictly by a nation's traditional economic figures. The criteria for calculating rankings include life expectancy, educational attainment, and adjusted real income. The 2005 index is based on 2003 figures. “Most Livable” Countries, 2005 1. Norway

11. Japan

2. Iceland 

12. Netherlands 

3. Australia

13. Finland

4. Luxembourg 

14. Denmark 

5. Canada 

15. United Kingdom

6. Sweden 

16. France

7. Switzerland

17. Austria

8. Ireland 

18. Italy 

9. Belgium 

19. New Zealand 

10. United States

20. Germany

“Least Livable” Countries, 2005 1. Niger

11. Congo, Dem. Rep. of

2. Sierra Leone

12. Zambia 

3. Burkina Faso

13. Malawi 

4. Mali

14. Tanzania 

5. Chad 

15. Côte d’Ivoire

6. Guinea­Bissau

16. Benin

7. Central African Republic 

17. Eritrea

8. Ethiopia 

18. Angola 

9. Burundi 

19. Rwanda

10. Mozambique 

20. Nigeria

Source: Human Development Report, 2005, United Nations. Web: hdr.undp.org .

http://en.wikipedia.org/wiki/Gini_coefficient

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Metodologi Penelitian – Program Pascasarjana Dept. I. Komunikasi FISIP-UI

Freedom in the World, 2005 Since 1978, Freedom House has published Freedom in the World, an annual comparative assessment of the state of political rights and civil liberties around the world. Widely used by policy makers, journalists, and scholars, the 600-page survey is considered the definitive report on freedom around the globe. The 2005 ratings reflect global events from Dec. 1, 2003, through Nov. 30, 2004. According to the survey, 89 countries are free. Their 2.8 billion inhabitants (44% of the world's population) enjoy a broad range of rights. Fifty-four countries representing 1.2 billion people (19%) are considered partly free. Political rights and civil liberties are more limited in these countries, in which corruption, dominant ruling parties, or, in some cases, ethnic or religious strife is often the norm. The survey finds that 49 countries are not free. The 2.4 billion inhabitants (37%) of these countries, nearly three-fifths of whom live in China, are denied most basic political rights and civil liberties. In 2004, Russia was the only country to register a negative category change, moving from partly free to not free. The list below features only independent countries. Freedom House's separate listing of territories reveals that four territories received the lowest possible political rights rating: Chechnya (Russia), Kashmir (Pakistan), Tibet (China), and Western Sahara (Morocco); of those, Chechnya and Tibet also received the lowest possible civil liberties ratings.

FREE1 •

Ranking: 1 

•

Liechtenstein 

•

Ranking: 1.5 

•

Ghana 

•

Andorra 

•

Luxembourg 

•

Belize 

•

Guyana 

•

Australia 

•

Malta 

•

Bulgaria 

•

Israel 

•

Austria 

•

•

Greece 

•

Lithuania 

•

Bahamas 

Marshall  Islands 

Grenada 

•

Mali 

Mauritius 

•

•

Japan 

•

Mexico 

•

Micronesia 

•

Latvia 

•

Mongolia 

•

Nauru 

•

Monaco 

•

Samoa 

•

Netherlands 

•

Panama 

•

New Zealand 

•

•

St. Kitts and Nevis 

•

Norway 

•

Sao Tome and  Principe 

St. Lucia 

•

Vanuatu 

•

Palau 

•

Ranking: 2.5 

•

St. Vincent and  Grenadines 

•

Poland 

•

•

Brazil 

•

Portugal 

•

South Africa 

•

El Salvador 

•

San Marino 

•

South Korea 

•

India 

•

Barbados 

•

Belgium 

•

Canada 

•

Cape Verde 

•

Chile 

•

Costa Rica 

•

Cyprus 

•

Czech  Republic 

•

Denmark 

http://en.wikipedia.org/wiki/Gini_coefficient

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Metodologi Penelitian – Program Pascasarjana Dept. I. Komunikasi FISIP-UI

•

Dominica 

•

Slovakia 

•

Suriname 

•

Jamaica 

•

Estonia 

•

Slovenia 

•

Taiwan 

•

Lesotho 

•

Finland 

•

Spain 

•

Ranking: 2 

•

Namibia 

•

France 

•

Sweden 

•

•

Peru 

•

Germany 

•

Switzerland 

Antigua and  Barbuda 

•

Philippines 

•

Hungary 

•

Tuvalu 

•

Romania 

•

Iceland 

•

•

Senegal 

•

Ireland 

United  Kingdom 

•

Serbia and  Montenegro 

•

Thailand

•

Italy 

•

Kiribati

•

Argentina 

•

Benin 

•

Botswana 

•

United States 

•

Croatia 

•

Uruguay

•

Dominican Republic

PARTLY FREE1 •

Ranking: 3 

•

Sri Lanka 

•

Bangladesh 

•

Gabon 

•

Albania 

•

Trinidad and Tobago 

•

Colombia 

•

Jordan 

•

Bolivia 

•

Turkey 

•

Comoros 

•

Kuwait 

•

East Timor 

•

Ranking: 3.5 

•

The Gambia 

•

Liberia 

•

Ecuador 

•

•

Guatemala 

•

Morocco 

•

Honduras 

Bosnia and  Herzegovina 

•

Guinea­Bissau 

•

Singapore 

•

Fiji 

•

Malawi 

•

Uganda 

•

Georgia 

•

Malaysia 

•

Ranking: 5 

•

Indonesia 

•

Nigeria 

•

Bahrain 

•

Moldova 

•

Tonga 

•

Burundi 

•

Mozambique 

•

Zambia 

•

Djibouti 

•

Sierra Leone 

•

Ranking: 4.5 

•

Ethiopia 

•

Tanzania 

•

Armenia 

•

Nepal 

•

Burkina Faso 

•

Yemen

•

Congo, Rep.  of

•

Kenya 

•

Macedonia 

•

Madagascar 

•

Nicaragua 

• •

Niger  Papua New  Guinea 

•

Paraguay 

•

Ukraine 

•

Seychelles 

•

Venezuela 

•

Solomon Islands

•

Ranking: 4

NOT FREE1 http://en.wikipedia.org/wiki/Gini_coefficient

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Metodologi Penelitian – Program Pascasarjana Dept. I. Komunikasi FISIP-UI

•

Ranking: 5.5 

•

Lebanon 

•

Afghanistan 

•

Maldives 

•

Algeria 

•

Mauritania 

•

Angola 

•

Oman 

•

Azerbaijan 

•

Pakistan 

•

Bhutan 

•

Qatar 

•

Brunei 

•

Russia 

•

Cambodia 

•

Rwanda 

•

Central African  Republic 

•

Tajikistan 

•

Togo 

•

Tunisia 

•

Ranking: 

•

Chad 

•

Egypt 

•

Guinea 

•

Kazakhstan

6  •

Cameroon

•

Congo, Dem.  Rep. of 

•

Cote d'Ivoire 

•

Iran 

•

Iraq 

•

Swaziland 

•

United Arab  Emirates 

•

Ranking: 6.5 

•

Belarus 

•

China 

•

Equatorial Guinea 

•

Eritrea 

•

Haiti 

•

Laos

•

Somalia 

•

Uzbekistan 

•

Vietnam 

•

Zimbabwe 

•

Ranking: 7 

•

Cuba 

•

Libya 

•

Myanmar  (Burma) 

•

North Korea 

•

Saudi Arabia 

•

Sudan 

•

Syria 

•

Turkmenistan

1. Countries are ranked according to political rights and civil liberties on a scale from 1.0 (most free) to 7.0 (least free).  Source: Freedom in the World, 2005, published by Freedom House. www.freedomhouse.org/research/survey2005.htm .

Global Trends in Freedom Year 

Partly 

under 

Free 

free 

Not free 

review

countries

countries

countries

1974

41 (27%)

48 (32%)

63 (41%)

1984

53 (32%)

59 (35%)

55 (33%)

1994

76 (40%)

61 (32%)

54 (28%)

2004

89 (46%)

54 (28%)

49 (26%)

Source: Freedom in the World, an annual comparative assessment of the state of political rights and civil  liberties around the world, published by Freedom House. www.freedomhouse.org/research/survey2005.htm .

The Failed States Index FOREIGN POLICY and the Fund for Peace have ranked 60 troubled countries that are in danger of collapse. The countries are ranked according to twelve social, economic, political, and military indicators, including economic decline and inequality, demographic pressures, war, and corruption. Below are the top 20 most vulnerable countries.

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Metodologi Penelitian – Program Pascasarjana Dept. I. Komunikasi FISIP-UI

•

 1. Côte D'Ivoire 

•

 8. Yemen 

•

15. Zimbabwe 

•

 2. Dem. Rep. of the Congo 

•

 9. Liberia 

•

16. Guinea 

•

 3. Sudan 

•

10. Haiti 

•

17. Bangladesh 

•

 4. Iraq 

•

11. Afghanistan 

•

18. Burundi 

•

 5. Somalia 

•

12. Rwanda 

•

19. Dominican Rep. 

•

 6. Sierra Leone 

•

13. North Korea 

•

20. Central African Rep. 

•

 7. Chad 

•

14. Colombia 

Source: FOREIGN POLICY www.foreignpolicy.com , 2005

The 2005 Transparency International Corruption Perceptions Index According to the annual survey by the Berlin-based organization Transparency International, the world's least corrupt country is seen as being Iceland and the countries perceived as most corrupt are Bangladesh and Chad. The index defines corruption as the abuse of public office for private gain, and measures the degree to which corruption is perceived to exist among a country's public officials and politicians. It is a composite index, drawing on 16 surveys from 10 independent institutions, which gathered the opinions of businesspeople and country analysts. Only 159 of the world's countries are included in the survey, due to an absence of reliable data from the remaining countries. The scores range from ten (squeaky clean) to zero (highly corrupt). A score of 5.0 is the number Transparency International considers the borderline figure distinguishing countries that do and do not have a serious corruption problem. Countries that have improved their rating since the 2004 index were Argentina, Austria, Bolivia, Estonia, France, Guatemala, Honduras, Hong Kong, Japan, Jordan, Kazakhstan, Lebanon, Moldova, Nigeria, Qatar, Slovakia, South Korea, Taiwan, Turkey, Ukraine, and Yemen. Some of the countries that have a worse rating since 2004 include Costa Rica, Gabon, Nepal, Papua New Guinea, Russia, Seychelles, Sri Lanka, Suriname, Trinidad & Tobago, and Uruguay. Country  rank 

2005 Country 

CPI Score

1.

Iceland 

9.7

2.

Finland 

9.6

 

New Zealand 

9.6

4.

Denmark 

9.5

5.

Singapore 

9.4

6.

Sweden 

9.2

7.

Switzerland 

9.1

8.

Norway 

8.9

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Metodologi Penelitian – Program Pascasarjana Dept. I. Komunikasi FISIP-UI

9.

Australia 

8.8

10.

Austria 

8.7

11.

Netherlands 

8.6

 

United Kingdom 

8.6

13.

Luxembourg 

8.5

14.

Canada 

8.4

15.

Hong Kong 

8.3

16.

Germany 

8.2

17.

United States

7.6

18.

France 

7.5

19.

Belgium 

7.4

 

Ireland 

7.4

21.

Chile 

7.3

 

Japan 

7.3

23.

Spain 

7.0

24.

Barbados 

6.9

25.

Malta 

6.6

26.

Portugal 

6.5

27.

Estonia 

6.4

28.

Israel 

6.3

 

Oman 

6.3

30.

United Arab Emirates 

6.2

31.

Slovenia 

6.1

32.

Botswana 

5.9

 

Qatar 

5.9

 

Taiwan 

5.9

 

Uruguay 

5.9

36.

Bahrain 

5.8

37.

Cyprus 

5.7

 

Jordan 

5.7

39.

Malaysia 

5.1

40.

Hungary 

5.0

 

Italy 

5.0

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Metodologi Penelitian – Program Pascasarjana Dept. I. Komunikasi FISIP-UI

 

Korea, South

5.0

43.

Tunisia 

4.9

44.

Lithuania 

4.8

45.

Kuwait 

4.7

46.

South Africa 

4.5

47.

Czech Republic 

4.3

 

Greece 

4.3

 

Namibia 

4.3

 

Slovakia 

4.3

51.

Costa Rica 

4.2

 

El Salvador 

4.2

 

Latvia 

4.2

 

Mauritius 

4.2

55.

Bulgaria 

4.0

 

Colombia 

4.0

 

Fiji 

4.0

 

Seychelles 

4.0

59.

Cuba 

3.8

 

Thailand 

3.8

 

Trinidad and Tobago 

3.8

62.

Belize 

3.7

 

Brazil 

3.7

64.

Jamaica 

3.6

65.

Ghana 

3.5

 

Mexico 

3.5

 

Panama 

3.5

 

Peru 

3.5

 

Turkey 

3.5

70.

Burkina Faso 

3.4

 

Croatia 

3.4

 

Egypt 

3.4

 

Lesotho 

3.4

 

Poland 

3.4

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Metodologi Penelitian – Program Pascasarjana Dept. I. Komunikasi FISIP-UI

 

Saudi Arabia 

3.4

 

Syria 

3.4

77.

Laos 

3.3

78.

China 

3.2

 

Morocco 

3.2

 

Senegal 

3.2

 

Sri Lanka

3.2

 

Suriname 

3.2

83.

Lebanon 

3.1

 

Rwanda 

3.1

85.

Dominican Republic 

3.0

 

Mongolia 

3.0

 

Romania 

3.0

88.

Armenia 

2.9

 

Benin 

2.9

 

Bosnia and Herzegovina

2.9

 

Gabon 

2.9

 

India 

2.9

 

Iran 

2.9

 

Mali 

2.9

 

Moldova 

2.9

 

Tanzania 

2.9

97.

Algeria 

2.8

 

Argentina 

2.8

 

Madagascar 

2.8

 

Malawi 

2.8

 

Mozambique 

2.8

 

Serbia and Montenegro

2.8

103.

Gambia 

2.7

 

Macedonia 

2.7

 

Swaziland 

2.7

 

Yemen 

2.7

107.

Belarus 

2.6

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Metodologi Penelitian – Program Pascasarjana Dept. I. Komunikasi FISIP-UI

 

Eritrea 

2.6

 

Honduras 

2.6

 

Kazakhstan 

2.6

 

Nicaragua 

2.6

 

Palestine 

2.6

 

Ukraine 

2.6

 

Vietnam 

2.6

 

Zambia 

2.6

 

Zimbabwe 

2.6

117.

Afghanistan 

2.5

 

Bolivia 

2.5

 

Ecuador 

2.5

 

Guatemala 

2.5

 

Guyana 

2.5

 

Libya 

2.5

 

Nepal 

2.5

 

Philippines 

2.5

 

Uganda 

2.5

126.

Albania 

2.4

 

Niger 

2.4

 

Russia 

2.4

 

Sierra Leone 

2.4

130.

Burundi 

2.3

 

Cambodia 

2.3

 

Congo, Republic of

2.3

 

Georgia 

2.3

 

Kyrgyzstan 

2.3

 

Papua New Guinea 

2.3

 

Venezuela 

2.3

137.

Azerbaijan 

2.2

 

Cameroon 

2.2

 

Ethiopia 

2.2

 

Indonesia 

2.2

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Metodologi Penelitian – Program Pascasarjana Dept. I. Komunikasi FISIP-UI

 

Iraq 

2.2

 

Liberia 

2.2

 

Uzbekistan 

2.2

144.

Congo, Democratic Republic of the

2.1

 

Kenya 

2.1

 

Pakistan 

2.1

 

Paraguay 

2.1

 

Somalia 

2.1

 

Sudan 

2.1

 

Tajikistan 

2.1

151.

Angola 

2.0

152.

Côte d'Ivoire 

1.9

 

Equatorial Guinea 

1.9

 

Nigeria 

1.9

155.

Haiti 

1.8

 

Myanmar 

1.8

 

Turkmenistan 

1.8

158.

Bangladesh 

1.7

 

Chad 

1.7

Source: Transparency International, 2005. Web: www.transparency.org 

World's Ten Most Corrupt Leaders1 Name

Position

Funds embezzled2

 1. Mohamed Suharto

President of Indonesia (1967–1998)

$15–35 billion

 2. Ferdinand Marcos

President of the Philippines (1972–1986)

5–10 billion

 3. Mobutu Sese Seko

President of Zaire (1965–1997)

5 billion

 4. Sani Abacha

President of Nigeria (1993–1998)

2–5 billion

 5. Slobodan Milosevic

President of Serbia/Yugoslavia (1989–2000) 1 billion

 6. Jean­Claude Duvalier

President of Haiti (1971–1986)

300–800 million

 7. Alberto Fujimori

President of Peru (1990–2000)

600 million

 8. Pavlo Lazarenko

Prime Minister of Ukraine (1996–1997)

114–200 million

 9. Arnoldo Alemán

President of Nicaragua (1997–2002)

100 million

http://en.wikipedia.org/wiki/Gini_coefficient

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Metodologi Penelitian – Program Pascasarjana Dept. I. Komunikasi FISIP-UI

10. Joseph Estrada

President of the Philippines (1998–2001)

78–80 million

1. Defined as former political leaders who have been accused of embezzling the most funds from their countries over the  past two decades. 2. All sums are estimates of alleged embezzlement and appear in U.S. dollars.

Source: Transparency International Global Corruption Report 2004. 

http://en.wikipedia.org/wiki/Gini_coefficient

45