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Kesenjangan ekonomi

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Perbedaan kesetaraan pendapatan nasional di seluruh dunia menurut koefisien Gini nasional. Koefisien Fini adalah angka antara 0 dan 1; 0 berarti kesetaraan sempurna (pendapatan semua orang sama dan 1 berarti kesenjangan absolut (satu orang menguasai seluruh pendapatan, sisanya berpendapatan nol).

Kesenjangan ekonomi, biasa dikenal dengan istilah kesenjangan pendapatan, kesenjangan kekayaan, dan jurang antara kaya dan miskin, mengacu pada persebaran ukuran ekonomi di antara individu dalam kelompok, kelompok dalam populasi, atau antar negara. Para ekonom umumnya mengakui tiga ukuran kesenjangan ekonomi: kekayaan, pendapatan, dan konsumsi.[1] Persoalan kesenjangan ekonomi mencakup kesetaraan ekonomi, kesetaraan pengeluaran, dan kesetaraan kesempatan.[2]

Sejumlah penelitian menyebut bahwa kesenjangan adalah masalah sosial yang semakin berkembang.[3] Kesenjangan yang terlalu besar cenderung merugikan[4][5] karena kesenjangan pendapatan dan pemusatan kekayaan mampu menghambat pertumbuhan jangka panjang.[6][7][8] Penelitian statistik awal yang membandingkan kesenjangan dengan pertumbuhan ekonomi tidak menghasilkan kesimpulan apa-apa.[9] Pada tahun 2011, peneliti Dana Moneter Internasional menunjukkan bahwa kesetaraan pendapatan yang lebih besar—berkurangnya kesenjangan—meningkatkan durasi pertumbuhan ekonomi sebuah negara dengan lebih cepat dibandingkan perdagangan bebas, korupsi pemerintah rendah, investasi asing, atau utang luar negeri rendah.[10]

Kesenjangan ekonomi bervariasi tergantung masyarakat, waktu, struktur ekonomi, dan sistem. Istilah tersebut dapat mengacu pada persebaran pendapatan atau kekayaan lintas lapisan masyarakat pada waktu tertentu, atau pendapatan dan kekayaan seumur hidup dalam jangka panjang.[11] Ada beberapa indeks numerik untuk mengukur kesenjangan ekonomi. Di antara metode pengukuran kesenjagan yang ada, koefisien Gini merupakan indeks yang paling terkenal.

Tabel berikut menampilkan pola kekayaan antarnegara. Informasi di dalam tabel ini berasal dari Credit Suisse, Research Institute's "Global Wealth Databook", terbit tahun 2013.[12]

Negara Dewasa
(Ribu)
Kekayaan
rerata per
dewasa
(USD)
Kekayaan
median per
dewasa
(USD)
Persebaran dewasa (%) menurut kekayaan (USD) Gini
 %
di bawah 10rb 10rb – 100rb 100rb – 1jt > 1jt Total
Denmark4,190255,06657,67539.51737.85.7100107.7
Russian Federation110,36510,97687193.75.60.60.110093.1
Ukraine35,9123,41341997.42.30.2010090
Kazakhstan10,9587,1611,17693.16.30.60.110086.7
Lebanon2,95330,8686,07666.829.83.20.310086.3
United States of America239,279301,14044,91130.73330.75.510085.1
Zimbabwe6,6902,91347993.95.80.3010083.8
Turkey51,68725,9095,3266730.32.50.210083.7
South Africa31,03419,6133,05172.324.92.60.110083.6
Hong Kong, China6,052153,31232,38430.349.718.31.710083.1
Philippines56,7308,7991,84988.111.10.80.110082.9
Indonesia157,86911,8392,39381.117.61.30.110082.8
Thailand49,6427,7721,85590.58.80.6010082.6
Venezuela18,9916,9001,50590.98.50.6010082.5
Brazil135,38523,2785,11766.630.52.70.210082.1
Malaysia18,38227,0075,83161.435.33.10.210081.5
Chile12,46149,03211,74245486.60.410081.4
India767,6124,7061,04094.45.20.3010081.3
Switzerland6,101512,56295,9165.24638.81010080.6
Sweden7,299299,44152,67715.648.329.26.910080.3
Egypt52,7107,2851,85290.490.6010080.3
Nigeria80,4623,62089494.94.90.3010080
Colombia30,46426,2226,22860.235.83.90.210079.7
Seychelles5460,00314,61740509.20.810079.6
Argentina28,26515,6384,03272.126.11.70.110079.6
Saudi Arabia16,69437,3469,77253.341.15.30.310079.3
Namibia1,25619,8994,53167.528.34.20.110078.7
Israel4,947137,35138,1643044.823.71.510078.7
Comoros3882,87267093.86.10.2010078.7
Cyprus694119,56834,87423.856.318.61.410078.3
Mexico73,38035,8729,71853.540.65.70.310078
Norway3,733380,47392,85919.432.540.67.510077.8
Austria6,761203,93157,45028.231.837310077.8
Libya4,29128,3976,56358.135.760.110077.7
Botswana1,18110,3482,6498117.61.4010077.2
Germany67,068192,23249,3702933.335.12.610077.1
Haiti5,8133,53296092.37.50.2010076.1
Angola9,27314,7083,93469.128.82.1010075.6
Central African Republic2,37080024199.10.90010074.8
Bolivia5,8004,6041,36889.310.40.3010074.4
Zambia6,1511,81754896.83.20010074.1
Czech Republic8,43744,97515,5414053.26.40.310074
Singapore3,955281,76490,4662034.241.44.410073.9
Kuwait2,291119,10142,89721.855.521.51.210073.8
Poland30,25526,0569,1095541.53.30.110073.7
Taiwan18,359151,75253,33622.545.130.81.710073.6
Netherlands12,914185,58883,63123.330.943.62.210073.2
Belize1889,9983,13076.322.61.1010073.1
Suriname34414,2504,54468.829.61.6010073
Nicaragua3,4243,4321,14792.57.30.1010073
Romania16,69214,0445,13769.329.21.40.110073
Lesotho1,0793,4571,10592.47.50.1010072.9
Paraguay3,91010,9343,72673.225.61.3010072.8
Swaziland6284,3601,393909.80.2010072.7
Panama2,32222,2927,50957.338.54.2010072.7
Rwanda5,30672324599.30.70010072.7
Sao Tome and Principe862,72195994.35.70.1010072.7
Canada27,173251,03490,2523021.544.93.710072.7
Korea38,35079,47530,93825.359.514.50.710072.6
Papua New Guinea3,7528,4702,82181.1180.8010072.4
Cape Verde29516,3135,4786532.52.5010072.3
Antigua and Barbuda6319,0116,28158.838.33010072.2
Costa Rica3,24628,1249,53254.140.25.70.110072.2
Dominica5024,0868,3495540.34.70.110072
St. Kitts and Nevis3423,6138,18556.339.14.60.110071.9
St. Vincent and the Grenadines7110,1963,49273.825.11.1010071.9
Grenada6714,4735,01767.530.71.7010071.9
New Zealand3,234182,54876,60725.634.138.12.310071.8
Ecuador8,72312,3504,40369.828.81.4010071.4
El Salvador3,73812,0394,4837028.71.3010071
Ireland3,488183,80475,57320.936.540.42.210070.9
Kenya20,7572,8431,04994.25.70.1010070.9
Oman1,87248,41518,1524047.8120.210070.8
Peru18,86518,2276,70558.538.92.6010070.8
Gambia90886432499.20.80010070.8
Congo-Brazzaville2,0243,8921,42091.28.60.1010070.8
United Arab Emirates3,777126,79151,8822050.628.21.310070.5
Qatar1,278153,29458,2372538.3351.710070.5
Portugal8,61489,07438,84625.854.818.70.810070.1
Mozambique11,44181131399.30.70010070
Jamaica1,71911,4014,3937028.81.2010069.9
Uruguay2,40047,00217,99839.648.311.90.210069.8
Uganda15,10775029499.40.60010069.6
DR Congo31,85432112499.90.10010069.6
China998,25422,2308,02358.439.12.40.110069.5
Madagascar10,35944817799.80.20010069.4
Guyana4743,8011,50691.68.30.1010069.2
Fiji5236,4732,6308514.60.4010069
France48,124295,933141,85021.722.950.84.610069
Barbados20022,2898,1085541.53.5010069
Eritrea2,7812,12587596.33.70010068.9
Macedonia, FYR1,56111,5434,74369.329.61.1010068.8
Sierra Leone2,89768127399.60.40010068.8
Ghana13,5011,81174397.72.30010068.6
St. Lucia11913,0875,29666.332.51.2010068.5
Tunisia7,45221,0848,8235541.53.5010068.2
Gabon86921,8609,2405541.33.7010068.2
Solomon Islands2989,8684,26173.825.31010068.1
Morocco21,35511,3984,7507028.91.1010068.1
Côte d'Ivoire11,5012,6401,104954.90.1010068.1
Sri Lanka14,3265,0332,10187.911.90.2010068
Turkmenistan3,35236,57015,3054052.17.80.110068
Georgia3,17221,6409,17854.741.83.5010068
Togo3,6932,4501,04995.64.30010067.9
United Kingdom48,220243,570111,5241828.8503.210067.7
Mauritania1,8321,9678659730010067.7
Burkina Faso7,7211,27354398.71.30010067.7
Djibouti5083,4651,48892.87.20.1010067.5
Chad5,4851,1314839910010067.5
Trinidad and Tobago98715,0886,4596038.51.5010067.4
Malawi7,4172078910000010067.3
Guinea5,30188238099.40.60010067.3
Iceland253211,592104,733203047.32.710067.3
Tonga5415,9057,21758.839.81.5010067.2
Senegal6,4232,5971,12595.34.70010067.2
Cameroon10,4592,6031,11595.24.80010067.2
Vanuatu1386,0682,7538514.70.3010067.1
Benin4,7333,1871,39893.66.30.1010067.1
Samoa9234,53715,13240536.90.110067
Cambodia9,1512,6441,155954.90010067
Yemen12,1924,9512,19388.311.60.2010066.8
Iran53,2708,7273,8467524.40.6010066.8
Liberia2,1182,17398796.53.50010066.7
Tanzania22,03895142399.30.70010066.6
Laos3,6185,3932,41186.713.10.2010066.5
Lithuania2,53723,41110,63547.548.53.9010066.5
Myanmar34,1802,2149419730010066.4
Finland4,195171,82195,0952922.347.21.610066.4
Maldives2105,5562,4808514.80.2010066.3
Bahamas24241,10617,8423555.990.110066.2
Spain37,206123,99763,30617.452.4291.110066.1
Mongolia1,85514,2146,43361.137.61.3010066.1
Syrian Arab Republic13,3527,0733,19882.716.90.4010066
Latvia1,78724,28511,3384550.94010066
Greece9,105102,97153,93720.453.725.10.810065.9
Jordan3,85814,3646,58960.338.31.4010065.9
Kyrgyz Republic3,5685,3852,43285.913.90.2010065.9
Viet Nam61,7654,8572,21587.8120.2010065.8
West Bank and Gaza1,7398,9794,20073.126.30.6010065.8
Equatorial Guinea36519,5259,1305542.62.4010065.8
Bosnia and Herzegovina2,98511,1735,13968.230.90.9010065.8
Luxembourg390315,240182,7681522.5575.510065.7
Estonia1,05533,70115,7244053.36.60.110065.7
Guinea-Bissau83642419999.90.10010065.7
Albania2,2379,4504,45172.726.60.7010065.6
Niger7,01493743499.30.70010065.5
Algeria23,98210,1004,6737029.20.7010065.5
Sudan23,8111,29159598.91.10010065.4
Burundi4,72929313799.90.10010065.2
Azerbaijan6,27616,3447,72157.141.41.5010065.1
Croatia3,49826,55112,63941.254.14.7010065.1
Italy49,117241,383138,6532020.556.5310065
Mali6,46495545599.40.60010064.7
Moldova2,6923,8541,87491.88.10.1010064.7
Nepal17,2731,99895197.72.30010064.7
Bangladesh104,1351,89490897.92.10010064.6
Mauritius93537,30819,2474052.57.40.110064.5
Hungary7,91528,37914,06840554.9010064
Armenia2,2635,6132,79385.514.30.2010063.9
Tajikistan4,0223,1681,58194.35.70.1010063.8
Pakistan106,3654,2482,10690.890.1010063.8
Ethiopia42,75041120799.90.10010063.6
Australia16,617402,578219,5056.923.762.66.810063.6
Japan104,315216,694110,2949.237.750.62.510063.5
Montenegro46721,34010,9294552.62.4010063.4
Belgium8,387255,573148,14117.422.157.33.210062.6
Serbia7,52715,1757,97856.8421.3010062.5
Bulgaria5,99116,8188,82555.243.41.4010062.5
Belarus7,5432,4071,27196.83.10010062.2
Malta33071,44842,89818.86515.90.310059.5
Bahrain57144,82226,67528.76011.2010058.5
Brunei Darussalam28651,37331,52726.258.715010058.5
Slovenia1,65564,06744,93219.460.619.90.110053.5
Slowakia4,30327,22420,74019.877.82.4010044.7

Lihat pula

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2

Referensi

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  1. ↑ Kesalahan pengutipan: Tanda <ref> tidak sah; tidak ditemukan teks untuk ref bernama "hydra"
  2. ↑ Fletcher, Michael A. (Maret 10, 2013). "Research ties economic inequality to gap in life expectancy". Washington Post. Diakses tanggal Maret 23, 2013.{{cite news}}: Pemeliharaan CS1: Tanggal diterjemahkan otomatis (link)
  3. ↑ Wilkinson, Richard; Pickett, Kate (2009). The Spirit Level: Why More Equal Societies Almost Always Do Better. Allen Lane. hlm. 352. ISBN 978-1-84614-039-6.
  4. ↑ Easterly, W (2007). "Inequality does cause underdevelopment: Insights from a new instrument" (PDF). Journal of Development Economics. 84 (2): 755–776. doi:10.1016/j.jdeveco.2006.11.002. Diarsipkan dari asli (PDF) tanggal 2016-03-04. Diakses tanggal 2015-11-02.
  5. ↑ Castells-Quintana, David; Royuela, Vicente (2012). "Unemployment and long-run economic growth: The role of income inequality and urbanisation" (PDF). Investigaciones Regionales. 12 (24): 153–173. Diakses tanggal 17 Oktober 2013.{{cite journal}}: Pemeliharaan CS1: Tanggal diterjemahkan otomatis (link)
  6. ↑ Stiglitz, J (2009). "The global crisis, social protection and jobs" (PDF). International Labour Review. 148: 1–2. doi:10.1111/j.1564-913x.2009.00046.x.
  7. ↑ Temple, J (1999). "The New Growth Evidence" (PDF). Journal of Economic Literature. 37 (1): 112–156. doi:10.1257/jel.37.1.112. Diarsipkan dari asli (PDF) tanggal 2015-10-18. Diakses tanggal 2015-11-02.
  8. ↑ Clarke, G (1995). "More evidence on income distribution and growth" (PDF). Journal of Development Economics. 47: 403–427. doi:10.1016/0304-3878(94)00069-o.
  9. ↑ Kesalahan pengutipan: Tanda <ref> tidak sah; tidak ditemukan teks untuk ref bernama "BanerjeeDuflo"
  10. ↑ Kesalahan pengutipan: Tanda <ref> tidak sah; tidak ditemukan teks untuk ref bernama "BergOstryEE"
  11. ↑ Wojciech Kopczuk, Emmanuel Saez, and Jae Song find that "most of the increase in the variance of (log) annual earnings is due to increases in the variance of (log) permanent earnings with modest increases in the variance of transitory (log) earnings." Thus, in fact, the increase in earnings inequality is in lifetime income. Furthermore, they find that it remains difficult for someone to move up the earnings distribution (though they do find upward mobility for women in their lifetime). See their "Earnings Inequality and Mobility in the United States: Evidence from Social Security Data since 1937," Quarterly Journal of Economics. 125, no. 1 (2010): 91–128.
  12. ↑ Diarsipkan 2017-10-19 di Wayback Machine Credit Suisse, Research Institute – Global Wealth Databook 2013

Bacaan lanjutan

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Buku
Artikel
Also available as Smeeding, Timothy M.; Thompson, Jeffrey P. (2011). "Recent trends in income inequality (book chapter)". Research in Labor Economics (book series). 32. Emerald Group Publishing Limited: 1–50. doi:10.1108/S0147-9121(2011)0000032004.{{cite journal}}: Pemeliharaan CS1: Postscript (link)
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