国际货币基金会直到2015年世界经济预测 => 2010年预测数据

发表日子 2011-02-03 10:38:48
最后修正 2011-10-13 20:06:10

General government net lending/borrowing 2015

#国家/地区198019811982198319841985198619871988198919901991199219931994199519961997199819992000200120022003200420052006200720082009201020112012201320142015
21新加坡000000000011.55610.41711.8517.14118.29316.37214.44418.1869.38910.6239.9614.0183.3881.9522.9445.7035.31710.0385.224-0.8242.4131.4511.7921.892.072.203
22牙买加000000000002.5812.6942.3742.3171.682-3.675-6.17-5.944-4.008-1.407-3.884-6.158-5.628-4.766-3.543-4.376-3.918-6.395-9.892-7.123-3.226-1.314-0.0851.0442.156
23巴布亚新几内亚0000000000-4.811-2.579-8.054-8.949-2.9160.311.708-0.542-1.732-4.437-1.076-3.554-4.006-1.1091.5652.7046.5358.9552.509-7.656-1.1730.592-0.009-0.6891.42.15
24瑞典-5.71-4.691-6.586-5.131-3.034-3.665-0.3453.2943.3073.2383.363-0.076-8.886-11.173-9.066-7.317-3.314-1.6241.2161.1963.7261.663-1.404-1.1430.5612.0022.3823.7222.419-0.79-2.157-1.4390.1622.071.5591.701
25所罗门群岛0000000000-8.432-11.698-6.315-7.471-5.053-4.478-3.681-3.8370.553-2.648-6.233-8.918-7.016-2.4446.614-0.945-1.3571.267-0.2892.192.4252.2051.951.7511.5511.451
26格林纳达0000000000-9.784-5.398-1.801-0.195-3.518-0.569-3.702-6.034-2.906-3.341-3.034-7.897-17.878-4.439-2.580.45-6.107-7.889-5.072-6.561-2.936-1.214-0.2890.6060.8951.402
27伊朗0000000000-2.314-3.292-2.867-6.749-4.386-3.416-1.549-2.334-6.673-0.5526.0930.9160.5321.3441.6741.6680.0252.668-0.011-1.6970.3822.3532.0831.8112.0341.337
28多明尼加0000000000-5.661-3.642-2.72-1.736-4.177-3.597-1.983-2.806-4.562-11.401-10.859-8.458-5.32-1.256-0.8431.1593.612.2420.9130.841-1.182-0.648-0.0581.0491.121.164
29阿尔及利亚00000000003.1763.8830.751-5.916-1.8650.5873.9122.93-3.576-1.8959.763.741.1644.885.27113.66213.9146.1649.09-5.343-9.892-8.439-3.47-1.874-0.4511.011
30阿曼 00000000006.1050.661-5.416-7.59-8.148-4.4342.6625.617-4.840.46214.0528.7256.276.8736.33113.03714.47612.1717.1681.9926.7036.225.1223.9712.4590.846
31赖索托00-14.848-9.023-5.02-11.357-12.65-20.25-16.863-9.7-2.461-0.6042.5515.5965.8135.3985.0242.691-1.987-15.214-5.9080.017-3.456-0.4826.0695.04213.12410.0223.102-1.656-14.853-17.765-9.128-3.315-1.150.81
32澳大利亚000000000.9921.4280.284-2.225-4.168-4.146-3.225-2.033-0.8870.0630.3411.2741.6980.790.9291.5982.0732.4361.9561.543-0.513-4.109-4.572-2.48-0.60.0770.3660.699
33南非 00000000000000000000-1.53-1.128-1.083-1.816-1.190.0010.7721.149-0.461-5.166-5.792-4.497-3.086-1.549-0.4390.692
34香港000000000003.5692.9972.2551.102-0.3052.2386.742-1.6720.767-0.598-4.725-4.708-3.091-0.3181.054.2658.1020.0861.551.5621.7622.6673.3334.6250.656
35拉脫維亞000000000000000000-0.682-3.559-2.542-1.996-2.57-1.675-1.249-1.265-0.4940.641-7.495-7.841-11.947-7.597-1.792-0.2090.6910.648
36哈萨克斯坦00000000000000000000001.4242.8812.4565.7597.2114.7471.063-1.486-2.848-2.025-1.255-0.3460.1770.596
37塞舌尔000-9.79-9.804-14.566-17.771-1.8323.135-1.4864.1420.6992.048-6.165-2.254-4.039-6.492-8.443-10.061-7.208-11.546-8.488-14.722-0.837-0.8561.689-6.188-8.7342.2895.039-0.331.8770.7171.1720.7580.531
38安提瓜 和 巴布达00000000000000000-1.957-2.062-5.861-5.244-11.875-11.417-8.886-5.107-6.181-9.066-6.409-6.104-19.589-1.035-0.6190.1150.7481.1290.425
39巴拿马0000000000-1.4960.214-1.041-5.77211.1076.7712.156-0.799-2.131-1.209-0.607-2.327-3.291-4.705-4.895-2.6190.5113.4430.419-1.011-0.738-1.021-0.662-0.2260.1240.314
40瓦努阿图00000000000-5.531-2.323-3.669-1.493-2.586-1.777-0.507-6.432-0.534-6.08-3.213-3.513-1.3050.7761.8050.4730.2612.1010.053-0.0390.1540.2040.2040.2050.205
数据来源:国际货币基金会2010年。

表格 | 图像 | 闪电图像
| BCA | BCA_NGDPD | FLIBOR6 | GGR | GGR_NGDP | GGSB | GGSB_NPGDP | GGX | GGX_NGDP | GGXCNL | GGXCNL_NGDP | GGXONLB | GGXONLB_NGDP | GGXWDG | GGXWDG_NGDP | GGXWDN | GGXWDN_NGDP | 在业人口 | 人口 | 失业率 | NGAP_NPGDP | NGDP | NGDP_D | NGDP_FY | NGDP_R | NGDP_RPCH | NGDPD | NGDPDPC | NGDPPC | NGDPRPC | NGSD_NGDP | NID_NGDP | PCPI | PCPIE | PCPIEPCH | PCPIPCH | PPPEX | PPPGDP | PPPPC | PPPSH | 增长率 | 中国人
Net lending (+)/ borrowing (?) is calculated as revenue minus total expenditure. This is a core GFS balance that measures the extent to which general government is either putting financial resources at the disposal of other sectors in the economy and nonr Percent of GDP.

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