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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
ImageDenmark4,190255,06657,67539.51737.85.7100107.7
ImageRussian Federation110,36510,97687193.75.60.60.110093.1
ImageUkraine35,9123,41341997.42.30.2010090
ImageKazakhstan10,9587,1611,17693.16.30.60.110086.7
ImageLebanon2,95330,8686,07666.829.83.20.310086.3
ImageUnited States of America239,279301,14044,91130.73330.75.510085.1
ImageZimbabwe6,6902,91347993.95.80.3010083.8
ImageTurkey51,68725,9095,3266730.32.50.210083.7
ImageSouth Africa31,03419,6133,05172.324.92.60.110083.6
ImageHong Kong, China6,052153,31232,38430.349.718.31.710083.1
ImagePhilippines56,7308,7991,84988.111.10.80.110082.9
ImageIndonesia157,86911,8392,39381.117.61.30.110082.8
ImageThailand49,6427,7721,85590.58.80.6010082.6
ImageVenezuela18,9916,9001,50590.98.50.6010082.5
ImageBrazil135,38523,2785,11766.630.52.70.210082.1
ImageMalaysia18,38227,0075,83161.435.33.10.210081.5
ImageChile12,46149,03211,74245486.60.410081.4
ImageIndia767,6124,7061,04094.45.20.3010081.3
ImageSwitzerland6,101512,56295,9165.24638.81010080.6
ImageSweden7,299299,44152,67715.648.329.26.910080.3
ImageEgypt52,7107,2851,85290.490.6010080.3
ImageNigeria80,4623,62089494.94.90.3010080
ImageColombia30,46426,2226,22860.235.83.90.210079.7
ImageSeychelles5460,00314,61740509.20.810079.6
ImageArgentina28,26515,6384,03272.126.11.70.110079.6
ImageSaudi Arabia16,69437,3469,77253.341.15.30.310079.3
ImageNamibia1,25619,8994,53167.528.34.20.110078.7
ImageIsrael4,947137,35138,1643044.823.71.510078.7
ImageComoros3882,87267093.86.10.2010078.7
ImageCyprus694119,56834,87423.856.318.61.410078.3
ImageMexico73,38035,8729,71853.540.65.70.310078
ImageNorway3,733380,47392,85919.432.540.67.510077.8
ImageAustria6,761203,93157,45028.231.837310077.8
ImageLibya4,29128,3976,56358.135.760.110077.7
ImageBotswana1,18110,3482,6498117.61.4010077.2
ImageGermany67,068192,23249,3702933.335.12.610077.1
ImageHaiti5,8133,53296092.37.50.2010076.1
ImageAngola9,27314,7083,93469.128.82.1010075.6
ImageCentral African Republic2,37080024199.10.90010074.8
ImageBolivia5,8004,6041,36889.310.40.3010074.4
ImageZambia6,1511,81754896.83.20010074.1
ImageCzech Republic8,43744,97515,5414053.26.40.310074
ImageSingapore3,955281,76490,4662034.241.44.410073.9
ImageKuwait2,291119,10142,89721.855.521.51.210073.8
ImagePoland30,25526,0569,1095541.53.30.110073.7
ImageTaiwan18,359151,75253,33622.545.130.81.710073.6
ImageNetherlands12,914185,58883,63123.330.943.62.210073.2
ImageBelize1889,9983,13076.322.61.1010073.1
ImageSuriname34414,2504,54468.829.61.6010073
ImageNicaragua3,4243,4321,14792.57.30.1010073
ImageRomania16,69214,0445,13769.329.21.40.110073
ImageLesotho1,0793,4571,10592.47.50.1010072.9
ImageParaguay3,91010,9343,72673.225.61.3010072.8
ImageSwaziland6284,3601,393909.80.2010072.7
ImagePanama2,32222,2927,50957.338.54.2010072.7
ImageRwanda5,30672324599.30.70010072.7
ImageSao Tome and Principe862,72195994.35.70.1010072.7
ImageCanada27,173251,03490,2523021.544.93.710072.7
ImageKorea38,35079,47530,93825.359.514.50.710072.6
ImagePapua New Guinea3,7528,4702,82181.1180.8010072.4
ImageCape Verde29516,3135,4786532.52.5010072.3
ImageAntigua and Barbuda6319,0116,28158.838.33010072.2
ImageCosta Rica3,24628,1249,53254.140.25.70.110072.2
ImageDominica5024,0868,3495540.34.70.110072
ImageSt. Kitts and Nevis3423,6138,18556.339.14.60.110071.9
ImageSt. Vincent and the Grenadines7110,1963,49273.825.11.1010071.9
ImageGrenada6714,4735,01767.530.71.7010071.9
ImageNew Zealand3,234182,54876,60725.634.138.12.310071.8
ImageEcuador8,72312,3504,40369.828.81.4010071.4
ImageEl Salvador3,73812,0394,4837028.71.3010071
ImageIreland3,488183,80475,57320.936.540.42.210070.9
ImageKenya20,7572,8431,04994.25.70.1010070.9
ImageOman1,87248,41518,1524047.8120.210070.8
ImagePeru18,86518,2276,70558.538.92.6010070.8
ImageGambia90886432499.20.80010070.8
ImageCongo-Brazzaville2,0243,8921,42091.28.60.1010070.8
ImageUnited Arab Emirates3,777126,79151,8822050.628.21.310070.5
ImageQatar1,278153,29458,2372538.3351.710070.5
ImagePortugal8,61489,07438,84625.854.818.70.810070.1
ImageMozambique11,44181131399.30.70010070
ImageJamaica1,71911,4014,3937028.81.2010069.9
ImageUruguay2,40047,00217,99839.648.311.90.210069.8
ImageUganda15,10775029499.40.60010069.6
ImageDR Congo31,85432112499.90.10010069.6
ImageChina998,25422,2308,02358.439.12.40.110069.5
ImageMadagascar10,35944817799.80.20010069.4
ImageGuyana4743,8011,50691.68.30.1010069.2
ImageFiji5236,4732,6308514.60.4010069
ImageFrance48,124295,933141,85021.722.950.84.610069
ImageBarbados20022,2898,1085541.53.5010069
ImageEritrea2,7812,12587596.33.70010068.9
ImageMacedonia, FYR1,56111,5434,74369.329.61.1010068.8
ImageSierra Leone2,89768127399.60.40010068.8
ImageGhana13,5011,81174397.72.30010068.6
ImageSt. Lucia11913,0875,29666.332.51.2010068.5
ImageTunisia7,45221,0848,8235541.53.5010068.2
ImageGabon86921,8609,2405541.33.7010068.2
ImageSolomon Islands2989,8684,26173.825.31010068.1
ImageMorocco21,35511,3984,7507028.91.1010068.1
ImageCôte d'Ivoire11,5012,6401,104954.90.1010068.1
ImageSri Lanka14,3265,0332,10187.911.90.2010068
ImageTurkmenistan3,35236,57015,3054052.17.80.110068
ImageGeorgia3,17221,6409,17854.741.83.5010068
ImageTogo3,6932,4501,04995.64.30010067.9
ImageUnited Kingdom48,220243,570111,5241828.8503.210067.7
ImageMauritania1,8321,9678659730010067.7
ImageBurkina Faso7,7211,27354398.71.30010067.7
ImageDjibouti5083,4651,48892.87.20.1010067.5
ImageChad5,4851,1314839910010067.5
ImageTrinidad and Tobago98715,0886,4596038.51.5010067.4
ImageMalawi7,4172078910000010067.3
ImageGuinea5,30188238099.40.60010067.3
ImageIceland253211,592104,733203047.32.710067.3
ImageTonga5415,9057,21758.839.81.5010067.2
ImageSenegal6,4232,5971,12595.34.70010067.2
ImageCameroon10,4592,6031,11595.24.80010067.2
ImageVanuatu1386,0682,7538514.70.3010067.1
ImageBenin4,7333,1871,39893.66.30.1010067.1
ImageSamoa9234,53715,13240536.90.110067
ImageCambodia9,1512,6441,155954.90010067
ImageYemen12,1924,9512,19388.311.60.2010066.8
ImageIran53,2708,7273,8467524.40.6010066.8
ImageLiberia2,1182,17398796.53.50010066.7
ImageTanzania22,03895142399.30.70010066.6
ImageLaos3,6185,3932,41186.713.10.2010066.5
ImageLithuania2,53723,41110,63547.548.53.9010066.5
ImageMyanmar34,1802,2149419730010066.4
ImageFinland4,195171,82195,0952922.347.21.610066.4
ImageMaldives2105,5562,4808514.80.2010066.3
ImageBahamas24241,10617,8423555.990.110066.2
ImageSpain37,206123,99763,30617.452.4291.110066.1
ImageMongolia1,85514,2146,43361.137.61.3010066.1
ImageSyrian Arab Republic13,3527,0733,19882.716.90.4010066
ImageLatvia1,78724,28511,3384550.94010066
ImageGreece9,105102,97153,93720.453.725.10.810065.9
ImageJordan3,85814,3646,58960.338.31.4010065.9
ImageKyrgyz Republic3,5685,3852,43285.913.90.2010065.9
ImageViet Nam61,7654,8572,21587.8120.2010065.8
ImageWest Bank and Gaza1,7398,9794,20073.126.30.6010065.8
ImageEquatorial Guinea36519,5259,1305542.62.4010065.8
ImageBosnia and Herzegovina2,98511,1735,13968.230.90.9010065.8
ImageLuxembourg390315,240182,7681522.5575.510065.7
ImageEstonia1,05533,70115,7244053.36.60.110065.7
ImageGuinea-Bissau83642419999.90.10010065.7
ImageAlbania2,2379,4504,45172.726.60.7010065.6
ImageNiger7,01493743499.30.70010065.5
ImageAlgeria23,98210,1004,6737029.20.7010065.5
ImageSudan23,8111,29159598.91.10010065.4
ImageBurundi4,72929313799.90.10010065.2
ImageAzerbaijan6,27616,3447,72157.141.41.5010065.1
ImageCroatia3,49826,55112,63941.254.14.7010065.1
ImageItaly49,117241,383138,6532020.556.5310065
ImageMali6,46495545599.40.60010064.7
ImageMoldova2,6923,8541,87491.88.10.1010064.7
ImageNepal17,2731,99895197.72.30010064.7
ImageBangladesh104,1351,89490897.92.10010064.6
ImageMauritius93537,30819,2474052.57.40.110064.5
ImageHungary7,91528,37914,06840554.9010064
ImageArmenia2,2635,6132,79385.514.30.2010063.9
ImageTajikistan4,0223,1681,58194.35.70.1010063.8
ImagePakistan106,3654,2482,10690.890.1010063.8
ImageEthiopia42,75041120799.90.10010063.6
ImageAustralia16,617402,578219,5056.923.762.66.810063.6
ImageJapan104,315216,694110,2949.237.750.62.510063.5
ImageMontenegro46721,34010,9294552.62.4010063.4
ImageBelgium8,387255,573148,14117.422.157.33.210062.6
ImageSerbia7,52715,1757,97856.8421.3010062.5
ImageBulgaria5,99116,8188,82555.243.41.4010062.5
ImageBelarus7,5432,4071,27196.83.10010062.2
ImageMalta33071,44842,89818.86515.90.310059.5
ImageBahrain57144,82226,67528.76011.2010058.5
ImageBrunei Darussalam28651,37331,52726.258.715010058.5
ImageSlovenia1,65564,06744,93219.460.619.90.110053.5
ImageSlowakia4,30327,22420,74019.877.82.4010044.7

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. (March 10, 2013). "Research ties economic inequality to gap in life expectancy". Washington Post. Diakses tanggal March 23, 2013.
  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 October 2013.
  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. Pemeliharaan CS1: Postscript (link)
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