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 antarnegara. 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[sunting | sunting sumber]

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
Denmark 4,190 255,066 57,675 39.5 17 37.8 5.7 100 107.7
Russian Federation 110,365 10,976 871 93.7 5.6 0.6 0.1 100 93.1
Ukraine 35,912 3,413 419 97.4 2.3 0.2 0 100 90
Kazakhstan 10,958 7,161 1,176 93.1 6.3 0.6 0.1 100 86.7
Lebanon 2,953 30,868 6,076 66.8 29.8 3.2 0.3 100 86.3
United States of America 239,279 301,140 44,911 30.7 33 30.7 5.5 100 85.1
Zimbabwe 6,690 2,913 479 93.9 5.8 0.3 0 100 83.8
Turkey 51,687 25,909 5,326 67 30.3 2.5 0.2 100 83.7
South Africa 31,034 19,613 3,051 72.3 24.9 2.6 0.1 100 83.6
Hong Kong, China 6,052 153,312 32,384 30.3 49.7 18.3 1.7 100 83.1
Philippines 56,730 8,799 1,849 88.1 11.1 0.8 0.1 100 82.9
Indonesia 157,869 11,839 2,393 81.1 17.6 1.3 0.1 100 82.8
Thailand 49,642 7,772 1,855 90.5 8.8 0.6 0 100 82.6
Venezuela 18,991 6,900 1,505 90.9 8.5 0.6 0 100 82.5
Brazil 135,385 23,278 5,117 66.6 30.5 2.7 0.2 100 82.1
Malaysia 18,382 27,007 5,831 61.4 35.3 3.1 0.2 100 81.5
Chile 12,461 49,032 11,742 45 48 6.6 0.4 100 81.4
India 767,612 4,706 1,040 94.4 5.2 0.3 0 100 81.3
Switzerland 6,101 512,562 95,916 5.2 46 38.8 10 100 80.6
Sweden 7,299 299,441 52,677 15.6 48.3 29.2 6.9 100 80.3
Egypt 52,710 7,285 1,852 90.4 9 0.6 0 100 80.3
Nigeria 80,462 3,620 894 94.9 4.9 0.3 0 100 80
Colombia 30,464 26,222 6,228 60.2 35.8 3.9 0.2 100 79.7
Seychelles 54 60,003 14,617 40 50 9.2 0.8 100 79.6
Argentina 28,265 15,638 4,032 72.1 26.1 1.7 0.1 100 79.6
Saudi Arabia 16,694 37,346 9,772 53.3 41.1 5.3 0.3 100 79.3
Namibia 1,256 19,899 4,531 67.5 28.3 4.2 0.1 100 78.7
Israel 4,947 137,351 38,164 30 44.8 23.7 1.5 100 78.7
Comoros 388 2,872 670 93.8 6.1 0.2 0 100 78.7
Cyprus 694 119,568 34,874 23.8 56.3 18.6 1.4 100 78.3
Mexico 73,380 35,872 9,718 53.5 40.6 5.7 0.3 100 78
Norway 3,733 380,473 92,859 19.4 32.5 40.6 7.5 100 77.8
Austria 6,761 203,931 57,450 28.2 31.8 37 3 100 77.8
Libya 4,291 28,397 6,563 58.1 35.7 6 0.1 100 77.7
Botswana 1,181 10,348 2,649 81 17.6 1.4 0 100 77.2
Germany 67,068 192,232 49,370 29 33.3 35.1 2.6 100 77.1
Haiti 5,813 3,532 960 92.3 7.5 0.2 0 100 76.1
Angola 9,273 14,708 3,934 69.1 28.8 2.1 0 100 75.6
Central African Republic 2,370 800 241 99.1 0.9 0 0 100 74.8
Bolivia 5,800 4,604 1,368 89.3 10.4 0.3 0 100 74.4
Zambia 6,151 1,817 548 96.8 3.2 0 0 100 74.1
Czech Republic 8,437 44,975 15,541 40 53.2 6.4 0.3 100 74
Singapore 3,955 281,764 90,466 20 34.2 41.4 4.4 100 73.9
Kuwait 2,291 119,101 42,897 21.8 55.5 21.5 1.2 100 73.8
Poland 30,255 26,056 9,109 55 41.5 3.3 0.1 100 73.7
Taiwan 18,359 151,752 53,336 22.5 45.1 30.8 1.7 100 73.6
Netherlands 12,914 185,588 83,631 23.3 30.9 43.6 2.2 100 73.2
Belize 188 9,998 3,130 76.3 22.6 1.1 0 100 73.1
Suriname 344 14,250 4,544 68.8 29.6 1.6 0 100 73
Nicaragua 3,424 3,432 1,147 92.5 7.3 0.1 0 100 73
Romania 16,692 14,044 5,137 69.3 29.2 1.4 0.1 100 73
Lesotho 1,079 3,457 1,105 92.4 7.5 0.1 0 100 72.9
Paraguay 3,910 10,934 3,726 73.2 25.6 1.3 0 100 72.8
Swaziland 628 4,360 1,393 90 9.8 0.2 0 100 72.7
Panama 2,322 22,292 7,509 57.3 38.5 4.2 0 100 72.7
Rwanda 5,306 723 245 99.3 0.7 0 0 100 72.7
Sao Tome and Principe 86 2,721 959 94.3 5.7 0.1 0 100 72.7
Canada 27,173 251,034 90,252 30 21.5 44.9 3.7 100 72.7
Korea 38,350 79,475 30,938 25.3 59.5 14.5 0.7 100 72.6
Papua New Guinea 3,752 8,470 2,821 81.1 18 0.8 0 100 72.4
Cape Verde 295 16,313 5,478 65 32.5 2.5 0 100 72.3
Antigua and Barbuda 63 19,011 6,281 58.8 38.3 3 0 100 72.2
Costa Rica 3,246 28,124 9,532 54.1 40.2 5.7 0.1 100 72.2
Dominica 50 24,086 8,349 55 40.3 4.7 0.1 100 72
St. Kitts and Nevis 34 23,613 8,185 56.3 39.1 4.6 0.1 100 71.9
St. Vincent and the Grenadines 71 10,196 3,492 73.8 25.1 1.1 0 100 71.9
Grenada 67 14,473 5,017 67.5 30.7 1.7 0 100 71.9
New Zealand 3,234 182,548 76,607 25.6 34.1 38.1 2.3 100 71.8
Ecuador 8,723 12,350 4,403 69.8 28.8 1.4 0 100 71.4
El Salvador 3,738 12,039 4,483 70 28.7 1.3 0 100 71
Ireland 3,488 183,804 75,573 20.9 36.5 40.4 2.2 100 70.9
Kenya 20,757 2,843 1,049 94.2 5.7 0.1 0 100 70.9
Oman 1,872 48,415 18,152 40 47.8 12 0.2 100 70.8
Peru 18,865 18,227 6,705 58.5 38.9 2.6 0 100 70.8
Gambia 908 864 324 99.2 0.8 0 0 100 70.8
Congo-Brazzaville 2,024 3,892 1,420 91.2 8.6 0.1 0 100 70.8
United Arab Emirates 3,777 126,791 51,882 20 50.6 28.2 1.3 100 70.5
Qatar 1,278 153,294 58,237 25 38.3 35 1.7 100 70.5
Portugal 8,614 89,074 38,846 25.8 54.8 18.7 0.8 100 70.1
Mozambique 11,441 811 313 99.3 0.7 0 0 100 70
Jamaica 1,719 11,401 4,393 70 28.8 1.2 0 100 69.9
Uruguay 2,400 47,002 17,998 39.6 48.3 11.9 0.2 100 69.8
Uganda 15,107 750 294 99.4 0.6 0 0 100 69.6
DR Congo 31,854 321 124 99.9 0.1 0 0 100 69.6
China 998,254 22,230 8,023 58.4 39.1 2.4 0.1 100 69.5
Madagascar 10,359 448 177 99.8 0.2 0 0 100 69.4
Guyana 474 3,801 1,506 91.6 8.3 0.1 0 100 69.2
Fiji 523 6,473 2,630 85 14.6 0.4 0 100 69
France 48,124 295,933 141,850 21.7 22.9 50.8 4.6 100 69
Barbados 200 22,289 8,108 55 41.5 3.5 0 100 69
Eritrea 2,781 2,125 875 96.3 3.7 0 0 100 68.9
Macedonia, FYR 1,561 11,543 4,743 69.3 29.6 1.1 0 100 68.8
Sierra Leone 2,897 681 273 99.6 0.4 0 0 100 68.8
Ghana 13,501 1,811 743 97.7 2.3 0 0 100 68.6
St. Lucia 119 13,087 5,296 66.3 32.5 1.2 0 100 68.5
Tunisia 7,452 21,084 8,823 55 41.5 3.5 0 100 68.2
Gabon 869 21,860 9,240 55 41.3 3.7 0 100 68.2
Solomon Islands 298 9,868 4,261 73.8 25.3 1 0 100 68.1
Morocco 21,355 11,398 4,750 70 28.9 1.1 0 100 68.1
Côte d'Ivoire 11,501 2,640 1,104 95 4.9 0.1 0 100 68.1
Sri Lanka 14,326 5,033 2,101 87.9 11.9 0.2 0 100 68
Turkmenistan 3,352 36,570 15,305 40 52.1 7.8 0.1 100 68
Georgia 3,172 21,640 9,178 54.7 41.8 3.5 0 100 68
Togo 3,693 2,450 1,049 95.6 4.3 0 0 100 67.9
United Kingdom 48,220 243,570 111,524 18 28.8 50 3.2 100 67.7
Mauritania 1,832 1,967 865 97 3 0 0 100 67.7
Burkina Faso 7,721 1,273 543 98.7 1.3 0 0 100 67.7
Djibouti 508 3,465 1,488 92.8 7.2 0.1 0 100 67.5
Chad 5,485 1,131 483 99 1 0 0 100 67.5
Trinidad and Tobago 987 15,088 6,459 60 38.5 1.5 0 100 67.4
Malawi 7,417 207 89 100 0 0 0 100 67.3
Guinea 5,301 882 380 99.4 0.6 0 0 100 67.3
Iceland 253 211,592 104,733 20 30 47.3 2.7 100 67.3
Tonga 54 15,905 7,217 58.8 39.8 1.5 0 100 67.2
Senegal 6,423 2,597 1,125 95.3 4.7 0 0 100 67.2
Cameroon 10,459 2,603 1,115 95.2 4.8 0 0 100 67.2
Vanuatu 138 6,068 2,753 85 14.7 0.3 0 100 67.1
Benin 4,733 3,187 1,398 93.6 6.3 0.1 0 100 67.1
Samoa 92 34,537 15,132 40 53 6.9 0.1 100 67
Cambodia 9,151 2,644 1,155 95 4.9 0 0 100 67
Yemen 12,192 4,951 2,193 88.3 11.6 0.2 0 100 66.8
Iran 53,270 8,727 3,846 75 24.4 0.6 0 100 66.8
Liberia 2,118 2,173 987 96.5 3.5 0 0 100 66.7
Tanzania 22,038 951 423 99.3 0.7 0 0 100 66.6
Laos 3,618 5,393 2,411 86.7 13.1 0.2 0 100 66.5
Lithuania 2,537 23,411 10,635 47.5 48.5 3.9 0 100 66.5
Myanmar 34,180 2,214 941 97 3 0 0 100 66.4
Finland 4,195 171,821 95,095 29 22.3 47.2 1.6 100 66.4
Maldives 210 5,556 2,480 85 14.8 0.2 0 100 66.3
Bahamas 242 41,106 17,842 35 55.9 9 0.1 100 66.2
Spain 37,206 123,997 63,306 17.4 52.4 29 1.1 100 66.1
Mongolia 1,855 14,214 6,433 61.1 37.6 1.3 0 100 66.1
Syrian Arab Republic 13,352 7,073 3,198 82.7 16.9 0.4 0 100 66
Latvia 1,787 24,285 11,338 45 50.9 4 0 100 66
Greece 9,105 102,971 53,937 20.4 53.7 25.1 0.8 100 65.9
Jordan 3,858 14,364 6,589 60.3 38.3 1.4 0 100 65.9
Kyrgyz Republic 3,568 5,385 2,432 85.9 13.9 0.2 0 100 65.9
Viet Nam 61,765 4,857 2,215 87.8 12 0.2 0 100 65.8
West Bank and Gaza 1,739 8,979 4,200 73.1 26.3 0.6 0 100 65.8
Equatorial Guinea 365 19,525 9,130 55 42.6 2.4 0 100 65.8
Bosnia and Herzegovina 2,985 11,173 5,139 68.2 30.9 0.9 0 100 65.8
Luxembourg 390 315,240 182,768 15 22.5 57 5.5 100 65.7
Estonia 1,055 33,701 15,724 40 53.3 6.6 0.1 100 65.7
Guinea-Bissau 836 424 199 99.9 0.1 0 0 100 65.7
Albania 2,237 9,450 4,451 72.7 26.6 0.7 0 100 65.6
Niger 7,014 937 434 99.3 0.7 0 0 100 65.5
Algeria 23,982 10,100 4,673 70 29.2 0.7 0 100 65.5
Sudan 23,811 1,291 595 98.9 1.1 0 0 100 65.4
Burundi 4,729 293 137 99.9 0.1 0 0 100 65.2
Azerbaijan 6,276 16,344 7,721 57.1 41.4 1.5 0 100 65.1
Croatia 3,498 26,551 12,639 41.2 54.1 4.7 0 100 65.1
Italy 49,117 241,383 138,653 20 20.5 56.5 3 100 65
Mali 6,464 955 455 99.4 0.6 0 0 100 64.7
Moldova 2,692 3,854 1,874 91.8 8.1 0.1 0 100 64.7
Nepal 17,273 1,998 951 97.7 2.3 0 0 100 64.7
Bangladesh 104,135 1,894 908 97.9 2.1 0 0 100 64.6
Mauritius 935 37,308 19,247 40 52.5 7.4 0.1 100 64.5
Hungary 7,915 28,379 14,068 40 55 4.9 0 100 64
Armenia 2,263 5,613 2,793 85.5 14.3 0.2 0 100 63.9
Tajikistan 4,022 3,168 1,581 94.3 5.7 0.1 0 100 63.8
Pakistan 106,365 4,248 2,106 90.8 9 0.1 0 100 63.8
Ethiopia 42,750 411 207 99.9 0.1 0 0 100 63.6
Australia 16,617 402,578 219,505 6.9 23.7 62.6 6.8 100 63.6
Japan 104,315 216,694 110,294 9.2 37.7 50.6 2.5 100 63.5
Montenegro 467 21,340 10,929 45 52.6 2.4 0 100 63.4
Belgium 8,387 255,573 148,141 17.4 22.1 57.3 3.2 100 62.6
Serbia 7,527 15,175 7,978 56.8 42 1.3 0 100 62.5
Bulgaria 5,991 16,818 8,825 55.2 43.4 1.4 0 100 62.5
Belarus 7,543 2,407 1,271 96.8 3.1 0 0 100 62.2
Malta 330 71,448 42,898 18.8 65 15.9 0.3 100 59.5
Bahrain 571 44,822 26,675 28.7 60 11.2 0 100 58.5
Brunei Darussalam 286 51,373 31,527 26.2 58.7 15 0 100 58.5
Slovenia 1,655 64,067 44,932 19.4 60.6 19.9 0.1 100 53.5
Slowakia 4,303 27,224 20,740 19.8 77.8 2.4 0 100 44.7

Lihat pula[sunting | sunting sumber]

Referensi[sunting | sunting sumber]

  1. ^ Kesalahan pengutipan: Tag <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. p. 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. 
  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. 
  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: Tag <ref> tidak sah; tidak ditemukan teks untuk ref bernama BanerjeeDuflo
  10. ^ Kesalahan pengutipan: Tag <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. ^ [1] Credit Suisse, Research Institute – Global Wealth Databook 2013

Bacaan lanjutan[sunting | sunting sumber]

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) (Emerald Group Publishing Limited) 32: 1–50. doi:10.1108/S0147-9121(2011)0000032004. 
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