| country | iso2c | iso3c | year | PDB | import | LPDB | Limport |
|---|---|---|---|---|---|---|---|
| Afghanistan | AF | AFG | 2019 | 1.879944e+10 | NA | 23.65709 | NA |
| Africa Eastern and Southern | ZH | AFE | 2019 | 1.006527e+12 | 2.693757e+11 | 27.63753 | 26.31937 |
| Africa Western and Central | ZI | AFW | 2019 | 8.239336e+11 | NA | 27.43736 | NA |
| Albania | AL | ALB | 2019 | 1.540183e+10 | 6.926960e+09 | 23.45775 | 22.65869 |
| Algeria | DZ | DZA | 2019 | 1.934597e+11 | 5.049085e+10 | 25.98833 | 24.64506 |
| American Samoa | AS | ASM | 2019 | 6.470000e+08 | 6.140000e+08 | 20.28786 | 20.23551 |
| Andorra | AD | AND | 2019 | 3.155149e+09 | NA | 21.87230 | NA |
| Angola | AO | AGO | 2019 | 7.089796e+10 | 1.208015e+10 | 24.98451 | 23.21483 |
| Antigua and Barbuda | AG | ATG | 2019 | 1.725352e+09 | 1.180426e+09 | 21.26870 | 20.88914 |
| Arab World | 1A | ARB | 2019 | 2.898669e+12 | 1.095860e+12 | 28.69527 | 27.72256 |
| Argentina | AR | ARG | 2019 | 4.477547e+11 | 6.584562e+10 | 26.82751 | 24.91058 |
| Armenia | AM | ARM | 2019 | 1.361929e+10 | 7.458380e+09 | 23.33475 | 22.73260 |
| Aruba | AW | ABW | 2019 | 3.395799e+09 | 2.448676e+09 | 21.94580 | 21.61881 |
| Australia | AU | AUS | 2019 | 1.394671e+12 | 3.017675e+11 | 27.96368 | 26.43292 |
| Austria | AT | AUT | 2019 | 4.445962e+11 | 2.317757e+11 | 26.82043 | 26.16904 |
| Azerbaijan | AZ | AZE | 2019 | 4.817424e+10 | 1.771247e+10 | 24.59809 | 23.59753 |
| Bahamas, The | BS | BHS | 2019 | 1.301620e+10 | 4.813800e+09 | 23.28946 | 22.29475 |
| Bahrain | BH | BHR | 2019 | 3.865332e+10 | 2.520771e+10 | 24.37790 | 23.95042 |
| Bangladesh | BD | BGD | 2019 | 3.512317e+11 | 6.491919e+10 | 26.58471 | 24.89641 |
| Barbados | BB | BRB | 2019 | 5.367139e+09 | 2.076309e+09 | 22.40356 | 21.45386 |
| Belarus | BY | BLR | 2019 | 6.441012e+10 | 4.235334e+10 | 24.88854 | 24.46931 |
| Belgium | BE | BEL | 2019 | 5.358658e+11 | 4.381723e+11 | 27.00715 | 26.80588 |
| Belize | BZ | BLZ | 2019 | 2.386792e+09 | 1.200665e+09 | 21.59322 | 20.90614 |
| Benin | BJ | BEN | 2019 | 1.439071e+10 | 4.900152e+09 | 23.38985 | 22.31253 |
| Bermuda | BM | BMU | 2019 | 7.423465e+09 | 1.916492e+09 | 22.72791 | 21.37376 |
| Bhutan | BT | BTN | 2019 | 2.735683e+09 | 1.221921e+09 | 21.72965 | 20.92369 |
| Bolivia | BO | BOL | 2019 | 4.089532e+10 | 1.285342e+10 | 24.43428 | 23.27688 |
| Bosnia and Herzegovina | BA | BIH | 2019 | 2.048261e+10 | 1.115812e+10 | 23.74284 | 23.13543 |
| Botswana | BW | BWA | 2019 | 1.672591e+10 | 7.694781e+09 | 23.54022 | 22.76381 |
| Brazil | BR | BRA | 2019 | 1.873288e+12 | 2.766348e+11 | 28.25872 | 26.34596 |
| British Virgin Islands | VG | VGB | 2019 | NA | NA | NA | NA |
| Brunei Darussalam | BN | BRN | 2019 | 1.346924e+10 | 6.810533e+09 | 23.32367 | 22.64174 |
| Bulgaria | BG | BGR | 2019 | 6.888101e+10 | 4.184055e+10 | 24.95565 | 24.45713 |
| Burkina Faso | BF | BFA | 2019 | 1.603281e+10 | 4.994381e+09 | 23.49790 | 22.33158 |
| Burundi | BI | BDI | 2019 | 2.576519e+09 | 6.146072e+08 | 21.66971 | 20.23649 |
| Cabo Verde | CV | CPV | 2019 | 2.252177e+09 | 1.281435e+09 | 21.53516 | 20.97125 |
| Cambodia | KH | KHM | 2019 | 2.708939e+10 | 1.692145e+10 | 24.02241 | 23.55185 |
| Cameroon | CM | CMR | 2019 | 3.966776e+10 | 9.333198e+09 | 24.40380 | 22.95684 |
| Canada | CA | CAN | 2019 | 1.743725e+12 | 5.897067e+11 | 28.18704 | 27.10289 |
| Caribbean small states | S3 | CSS | 2019 | 3.762101e+10 | NA | 24.35083 | NA |
| Cayman Islands | KY | CYM | 2019 | 5.941897e+09 | 2.695691e+09 | 22.50529 | 21.71492 |
| Central African Republic | CF | CAF | 2019 | 2.221301e+09 | 7.621378e+08 | 21.52136 | 20.45164 |
| Central Europe and the Baltics | B8 | CEB | 2019 | 1.674816e+12 | 1.000248e+12 | 28.14672 | 27.63127 |
| Chad | TD | TCD | 2019 | 1.131495e+10 | 4.280250e+09 | 23.14939 | 22.17728 |
| Channel Islands | JG | CHI | 2019 | 9.921387e+09 | NA | 23.01796 | NA |
| Chile | CL | CHL | 2019 | 2.782851e+11 | 8.275387e+10 | 26.35191 | 25.13914 |
| China | CN | CHN | 2019 | 1.427997e+13 | 2.496153e+12 | 30.28988 | 28.54577 |
| Colombia | CO | COL | 2019 | 3.230317e+11 | 7.006718e+10 | 26.50102 | 24.97272 |
| Comoros | KM | COM | 2019 | 1.195020e+09 | 3.524664e+08 | 20.90143 | 19.68047 |
| Congo, Dem. Rep. | CD | COD | 2019 | 5.177583e+10 | 1.520526e+10 | 24.67019 | 23.44491 |
| Congo, Rep. | CG | COG | 2019 | 1.397664e+10 | 4.944507e+09 | 23.36065 | 22.32154 |
| Costa Rica | CR | CRI | 2019 | 6.441767e+10 | 2.024983e+10 | 24.88865 | 23.73141 |
| Cote d'Ivoire | CI | CIV | 2019 | 6.038289e+10 | 1.328419e+10 | 24.82397 | 23.30984 |
| Croatia | HR | HRV | 2019 | 6.186716e+10 | 3.128256e+10 | 24.84826 | 24.16633 |
| Cuba | CU | CUB | 2019 | 1.034276e+11 | 1.097100e+10 | 25.36214 | 23.11852 |
| Curacao | CW | CUW | 2019 | 3.026124e+09 | NA | 21.83055 | NA |
| Cyprus | CY | CYP | 2019 | 2.594702e+10 | 1.957878e+10 | 23.97932 | 23.69771 |
| Czechia | CZ | CZE | 2019 | 2.525482e+11 | 1.714581e+11 | 26.25487 | 25.86760 |
| Denmark | DK | DNK | 2019 | 3.464987e+11 | 1.787159e+11 | 26.57115 | 25.90906 |
| Djibouti | DJ | DJI | 2019 | 3.088854e+09 | 4.763669e+09 | 21.85107 | 22.28428 |
| Dominica | DM | DMA | 2019 | 6.115370e+08 | NA | 20.23149 | NA |
| Dominican Republic | DO | DOM | 2019 | 8.894137e+10 | 2.485188e+10 | 25.21124 | 23.93620 |
| Early-demographic dividend | V2 | EAR | 2019 | 1.176766e+13 | 3.098301e+12 | 30.09638 | 28.76187 |
| East Asia & Pacific (excluding high income) | 4E | EAP | 2019 | 1.721322e+13 | 3.689049e+12 | 30.47670 | 28.93639 |
| East Asia & Pacific (IDA & IBRD countries) | T4 | TEA | 2019 | 1.719202e+13 | 3.682249e+12 | 30.47547 | 28.93454 |
| East Asia & Pacific | Z4 | EAS | 2019 | 2.703249e+13 | 7.111765e+12 | 30.92806 | 29.59277 |
| Ecuador | EC | ECU | 2019 | 1.075958e+11 | 2.585981e+10 | 25.40165 | 23.97596 |
| Egypt, Arab Rep. | EG | EGY | 2019 | 3.186788e+11 | 7.801253e+10 | 26.48745 | 25.08014 |
| El Salvador | SV | SLV | 2019 | 2.688114e+10 | 1.238847e+10 | 24.01469 | 23.24003 |
| Equatorial Guinea | GQ | GNQ | 2019 | 1.136413e+10 | 4.971586e+09 | 23.15373 | 22.32700 |
| Eritrea | ER | ERI | 2019 | NA | NA | NA | NA |
| Estonia | EE | EST | 2019 | 3.129045e+10 | 2.168307e+10 | 24.16658 | 23.79980 |
| Eswatini | SZ | SWZ | 2019 | 4.495267e+09 | 1.931360e+09 | 22.22629 | 21.38149 |
| Ethiopia | ET | ETH | 2019 | 9.591261e+10 | 2.002207e+10 | 25.28670 | 23.72010 |
| Euro area | XC | EMU | 2019 | 1.348115e+13 | 6.045597e+12 | 30.23231 | 29.43035 |
| Europe & Central Asia (excluding high income) | 7E | ECA | 2019 | 1.488770e+12 | 5.537850e+11 | 28.02897 | 27.04004 |
| Europe & Central Asia (IDA & IBRD countries) | T7 | TEC | 2019 | 4.159710e+12 | 1.385214e+12 | 29.05647 | 27.95688 |
| Europe & Central Asia | Z7 | ECS | 2019 | 2.290822e+13 | 9.606836e+12 | 30.76252 | 29.89350 |
| European Union | EU | EUU | 2019 | 1.569405e+13 | 7.206672e+12 | 30.38430 | 29.60603 |
| Faroe Islands | FO | FRO | 2019 | 3.266433e+09 | 1.726425e+09 | 21.90696 | 21.26932 |
| Fiji | FJ | FJI | 2019 | 5.444407e+09 | 3.209509e+09 | 22.41785 | 21.88938 |
| Finland | FI | FIN | 2019 | 2.685149e+11 | 1.066669e+11 | 26.31617 | 25.39298 |
| Fragile and conflict affected situations | F1 | FCS | 2019 | 1.842155e+12 | 4.870788e+11 | 28.24196 | 26.91169 |
| France | FR | FRA | 2019 | 2.728870e+12 | 8.882314e+11 | 28.63491 | 27.51250 |
| French Polynesia | PF | PYF | 2019 | 6.022276e+09 | 2.572340e+09 | 22.51873 | 21.66808 |
| Gabon | GA | GAB | 2019 | 1.687441e+10 | 3.711866e+09 | 23.54906 | 22.03480 |
| Gambia, The | GM | GMB | 2019 | 1.813610e+09 | 6.243942e+08 | 21.31858 | 20.25229 |
| Georgia | GE | GEO | 2019 | 1.763834e+10 | 1.120136e+10 | 23.59334 | 23.13930 |
| Germany | DE | DEU | 2019 | 3.889178e+12 | 1.601984e+12 | 28.98922 | 28.10226 |
| Ghana | GH | GHA | 2019 | 6.833797e+10 | 2.690821e+10 | 24.94773 | 24.01570 |
| Gibraltar | GI | GIB | 2019 | NA | NA | NA | NA |
| Greece | GR | GRC | 2019 | 2.052528e+11 | 8.574467e+10 | 26.04751 | 25.17464 |
| Greenland | GL | GRL | 2019 | 2.997310e+09 | 1.533066e+09 | 21.82098 | 21.15054 |
| Grenada | GD | GRD | 2019 | 1.213485e+09 | NA | 20.91676 | NA |
| Guam | GU | GUM | 2019 | 6.355000e+09 | 3.547000e+09 | 22.57251 | 21.98937 |
| Guatemala | GT | GTM | 2019 | 7.717232e+10 | 2.153476e+10 | 25.06931 | 23.79293 |
| Guinea-Bissau | GW | GNB | 2019 | 1.486477e+09 | 4.453663e+08 | 21.11967 | 19.91441 |
| Guinea | GN | GIN | 2019 | 1.344286e+10 | 5.830608e+09 | 23.32171 | 22.48639 |
| Guyana | GY | GUY | 2019 | 5.173760e+09 | NA | 22.36687 | NA |
| Haiti | HT | HTI | 2019 | 1.501609e+10 | 5.107129e+09 | 23.43239 | 22.35390 |
| Heavily indebted poor countries (HIPC) | XE | HPC | 2019 | 8.033559e+11 | 2.542256e+11 | 27.41206 | 26.26149 |
| High income | XD | 2019 | 5.721830e+13 | 1.723238e+13 | 31.67789 | 30.47781 | |
| Honduras | HN | HND | 2019 | 2.488223e+10 | 1.474048e+10 | 23.93742 | 23.41386 |
| Hong Kong SAR, China | HK | HKG | 2019 | 3.630745e+11 | 6.393460e+11 | 26.61787 | 27.18371 |
| Hungary | HU | HUN | 2019 | 1.640205e+11 | 1.299396e+11 | 25.82326 | 25.59034 |
| IBRD only | XF | IBD | 2019 | 3.124659e+13 | 7.443807e+12 | 31.07293 | 29.63840 |
| Iceland | IS | ISL | 2019 | 2.468134e+10 | 9.662622e+09 | 23.92931 | 22.99153 |
| IDA & IBRD total | ZT | IBT | 2019 | 3.372236e+13 | 8.083661e+12 | 31.14918 | 29.72087 |
| IDA blend | XH | IDB | 2019 | 1.077750e+12 | 2.065463e+11 | 27.70590 | 26.05379 |
| IDA only | XI | IDX | 2019 | 1.397671e+12 | 4.315091e+11 | 27.96583 | 26.79055 |
| IDA total | XG | IDA | 2019 | 2.475421e+12 | 6.394805e+11 | 28.53743 | 27.18392 |
| India | IN | IND | 2019 | 2.835606e+12 | 6.023151e+11 | 28.67328 | 27.12405 |
| Indonesia | ID | IDN | 2019 | 1.119100e+12 | 2.130346e+11 | 27.74355 | 26.08472 |
| Iran, Islamic Rep. | IR | IRN | 2019 | 2.836495e+11 | 7.735255e+10 | 26.37101 | 25.07164 |
| Iraq | IQ | IRQ | 2019 | 2.336361e+11 | 7.228250e+10 | 26.17703 | 25.00385 |
| Ireland | IE | IRL | 2019 | 3.989330e+11 | 4.966358e+11 | 26.71206 | 26.93112 |
| Isle of Man | IM | IMN | 2019 | 7.314968e+09 | NA | 22.71319 | NA |
| Israel | IL | ISR | 2019 | 4.024705e+11 | 1.095532e+11 | 26.72089 | 25.41968 |
| Italy | IT | ITA | 2019 | 2.011302e+12 | 5.687271e+11 | 28.32980 | 27.06667 |
| Jamaica | JM | JAM | 2019 | 1.583077e+10 | 8.243797e+09 | 23.48522 | 22.83273 |
| Japan | JP | JPN | 2019 | 5.117994e+12 | 9.085919e+11 | 29.26378 | 27.53516 |
| Jordan | JO | JOR | 2019 | 4.450282e+10 | 2.187324e+10 | 24.51882 | 23.80853 |
| Kazakhstan | KZ | KAZ | 2019 | 1.816672e+11 | 5.162914e+10 | 25.92544 | 24.66735 |
| Kenya | KE | KEN | 2019 | 1.003784e+11 | 2.040841e+10 | 25.33221 | 23.73921 |
| Kiribati | KI | KIR | 2019 | 2.168915e+08 | 1.770832e+08 | 19.19491 | 18.99213 |
| Korea, Dem. People's Rep. | KP | PRK | 2019 | NA | NA | NA | NA |
| Korea, Rep. | KR | KOR | 2019 | 1.651423e+12 | 6.024602e+11 | 28.13266 | 27.12429 |
| Kosovo | XK | XKX | 2019 | 7.899738e+09 | 4.458675e+09 | 22.79010 | 22.21812 |
| Kuwait | KW | KWT | 2019 | 1.386963e+11 | 6.113585e+10 | 25.65555 | 24.83636 |
| Kyrgyz Republic | KG | KGZ | 2019 | 9.371275e+09 | 5.712150e+09 | 22.96091 | 22.46586 |
| Lao PDR | LA | LAO | 2019 | 1.874056e+10 | NA | 23.65396 | NA |
| Late-demographic dividend | V3 | LTE | 2019 | 2.305021e+13 | 5.997968e+12 | 30.76870 | 29.42244 |
| Latin America & Caribbean (excluding high income) | XJ | LAC | 2019 | 4.804547e+12 | 1.154893e+12 | 29.20058 | 27.77503 |
| Latin America & Caribbean | ZJ | LCN | 2019 | 5.659966e+12 | 1.408779e+12 | 29.36444 | 27.97374 |
| Latin America & the Caribbean (IDA & IBRD countries) | T2 | TLA | 2019 | 5.413987e+12 | 1.329786e+12 | 29.32001 | 27.91604 |
| Latvia | LV | LVA | 2019 | 3.422555e+10 | 2.078247e+10 | 24.25624 | 23.75738 |
| Least developed countries: UN classification | XL | LDC | 2019 | 1.150501e+12 | 3.291171e+11 | 27.77122 | 26.51968 |
| Lebanon | LB | LBN | 2019 | 5.160596e+10 | 2.182063e+10 | 24.66690 | 23.80612 |
| Lesotho | LS | LSO | 2019 | 2.390702e+09 | 2.254607e+09 | 21.59485 | 21.53624 |
| Liberia | LR | LBR | 2019 | 3.319597e+09 | NA | 21.92311 | NA |
| Libya | LY | LBY | 2019 | 7.208196e+10 | 2.495205e+10 | 25.00107 | 23.94022 |
| Liechtenstein | LI | LIE | 2019 | 6.436467e+09 | NA | 22.58525 | NA |
| Lithuania | LT | LTU | 2019 | 5.480853e+10 | 3.942493e+10 | 24.72711 | 24.39766 |
| Low & middle income | XO | LMY | 2019 | 3.042453e+13 | 7.084425e+12 | 31.04627 | 29.58892 |
| Low income | XM | 2019 | 4.452784e+11 | 1.464719e+11 | 26.82197 | 25.71010 | |
| Lower middle income | XN | 2019 | 6.278115e+12 | 1.741505e+12 | 29.46809 | 28.18577 | |
| Luxembourg | LU | LUX | 2019 | 6.989051e+10 | 1.229631e+11 | 24.97020 | 25.53515 |
| Macao SAR, China | MO | MAC | 2019 | 5.508229e+10 | 1.762450e+10 | 24.73209 | 23.59256 |
| Madagascar | MG | MDG | 2019 | 1.410466e+10 | 4.820540e+09 | 23.36977 | 22.29615 |
| Malawi | MW | MWI | 2019 | 1.107731e+10 | NA | 23.12816 | NA |
| Malaysia | MY | MYS | 2019 | 3.651777e+11 | 2.108930e+11 | 26.62365 | 26.07462 |
| Maldives | MV | MDV | 2019 | 5.726095e+09 | NA | 22.46830 | NA |
| Mali | ML | MLI | 2019 | 1.728025e+10 | 6.558445e+09 | 23.57283 | 22.60402 |
| Malta | MT | MLT | 2019 | 1.600456e+10 | 2.326293e+10 | 23.49614 | 23.87013 |
| Marshall Islands | MH | MHL | 2019 | 2.319967e+08 | 2.700258e+08 | 19.26223 | 19.41403 |
| Mauritania | MR | MRT | 2019 | 7.894765e+09 | 4.033370e+09 | 22.78947 | 22.11787 |
| Mauritius | MU | MUS | 2019 | 1.443635e+10 | 7.481609e+09 | 23.39301 | 22.73571 |
| Mexico | MX | MEX | 2019 | 1.305211e+12 | 5.077188e+11 | 27.89739 | 26.95319 |
| Micronesia, Fed. Sts. | FM | FSM | 2019 | 3.940000e+08 | 2.720777e+08 | 19.79186 | 19.42160 |
| Middle East & North Africa (excluding high income) | XQ | MNA | 2019 | 1.433134e+12 | 4.574683e+11 | 27.99088 | 26.84897 |
| Middle East & North Africa (IDA & IBRD countries) | T3 | TMN | 2019 | 1.416000e+12 | 4.483066e+11 | 27.97886 | 26.82874 |
| Middle East & North Africa | ZQ | MEA | 2019 | 3.549945e+12 | 1.290507e+12 | 28.89795 | 27.88606 |
| Middle income | XP | MIC | 2019 | 2.997848e+13 | 6.938196e+12 | 31.03150 | 29.56806 |
| Moldova | MD | MDA | 2019 | 1.173680e+10 | 6.624383e+09 | 23.18599 | 22.61402 |
| Monaco | MC | MCO | 2019 | 7.383944e+09 | NA | 22.72257 | NA |
| Mongolia | MN | MNG | 2019 | 1.420636e+10 | 9.259603e+09 | 23.37696 | 22.94893 |
| Montenegro | ME | MNE | 2019 | 5.542054e+09 | 3.602221e+09 | 22.43563 | 22.00482 |
| Morocco | MA | MAR | 2019 | 1.289203e+11 | 5.402411e+10 | 25.58246 | 24.71270 |
| Mozambique | MZ | MOZ | 2019 | 1.551276e+10 | 1.061835e+10 | 23.46493 | 23.08585 |
| Myanmar | MM | MMR | 2019 | 7.506511e+10 | NA | 25.04162 | NA |
| Namibia | NA | NAM | 2019 | 1.254193e+10 | 5.832030e+09 | 23.25234 | 22.48663 |
| Nauru | NR | NRU | 2019 | 1.251601e+08 | 1.194385e+08 | 18.64510 | 18.59831 |
| Nepal | NP | NPL | 2019 | 3.418618e+10 | 1.417687e+10 | 24.25509 | 23.37488 |
| Netherlands | NL | NLD | 2019 | 9.101943e+11 | 6.620113e+11 | 27.53692 | 27.21855 |
| New Caledonia | NC | NCL | 2019 | 9.475655e+09 | NA | 22.97199 | NA |
| New Zealand | NZ | NZL | 2019 | 2.128469e+11 | 5.771160e+10 | 26.08384 | 24.77872 |
| Nicaragua | NI | NIC | 2019 | 1.269905e+10 | 6.252729e+09 | 23.26479 | 22.55628 |
| Niger | NE | NER | 2019 | 1.288956e+10 | 3.395520e+09 | 23.27968 | 21.94572 |
| Nigeria | NG | NGA | 2019 | 4.745175e+11 | NA | 26.88556 | NA |
| North America | XU | NAC | 2019 | 2.327254e+13 | 3.708577e+12 | 30.77830 | 28.94167 |
| North Macedonia | MK | MKD | 2019 | 1.260634e+10 | 9.602018e+09 | 23.25747 | 22.98524 |
| Northern Mariana Islands | MP | MNP | 2019 | 1.181000e+09 | 7.350000e+08 | 20.88963 | 20.41538 |
| Norway | NO | NOR | 2019 | 4.087428e+11 | 1.400144e+11 | 26.73635 | 25.66501 |
| Not classified | XY | 2019 | NA | NA | NA | NA | |
| OECD members | OE | OED | 2019 | 5.405301e+13 | 1.508010e+13 | 31.62099 | 30.34440 |
| Oman | OM | OMN | 2019 | 8.806086e+10 | 3.256853e+10 | 25.20129 | 24.20661 |
| Other small states | S4 | OSS | 2019 | 1.954423e+11 | 1.360433e+11 | 25.99853 | 25.63624 |
| Pacific island small states | S2 | PSS | 2019 | 1.072909e+10 | 6.308733e+09 | 23.09622 | 22.56520 |
| Pakistan | PK | PAK | 2019 | 3.209095e+11 | 6.262456e+10 | 26.49442 | 24.86042 |
| Palau | PW | PLW | 2019 | 2.818287e+08 | 2.175054e+08 | 19.45681 | 19.19773 |
| Panama | PA | PAN | 2019 | 6.972179e+10 | 2.803187e+10 | 24.96778 | 24.05661 |
| Papua New Guinea | PG | PNG | 2019 | 2.475107e+10 | NA | 23.93213 | NA |
| Paraguay | PY | PRY | 2019 | 3.792534e+10 | 1.332502e+10 | 24.35889 | 23.31291 |
| Peru | PE | PER | 2019 | 2.283460e+11 | 5.230132e+10 | 26.15413 | 24.68029 |
| Philippines | PH | PHL | 2019 | 3.768234e+11 | 1.524587e+11 | 26.65504 | 25.75016 |
| Poland | PL | POL | 2019 | 5.960585e+11 | 2.950095e+11 | 27.11360 | 26.41027 |
| Portugal | PT | PRT | 2019 | 2.399869e+11 | 1.033295e+11 | 26.20385 | 25.36119 |
| Post-demographic dividend | V4 | PST | 2019 | 5.101880e+13 | 1.457007e+13 | 31.56322 | 30.30999 |
| Pre-demographic dividend | V1 | PRE | 2019 | 1.427163e+12 | 3.296295e+11 | 27.98671 | 26.52124 |
| Puerto Rico | PR | PRI | 2019 | 1.051264e+11 | 4.940160e+10 | 25.37843 | 24.62325 |
| Qatar | QA | QAT | 2019 | 1.763713e+11 | 6.676978e+10 | 25.89586 | 24.92452 |
| Romania | RO | ROU | 2019 | 2.510178e+11 | 1.112081e+11 | 26.24879 | 25.43467 |
| Russian Federation | RU | RUS | 2019 | 1.693115e+12 | 3.520887e+11 | 28.15759 | 26.58715 |
| Rwanda | RW | RWA | 2019 | 1.034930e+10 | 3.741294e+09 | 23.06018 | 22.04270 |
| Samoa | WS | WSM | 2019 | 9.129505e+08 | 4.409345e+08 | 20.63219 | 19.90441 |
| San Marino | SM | SMR | 2019 | 1.616189e+09 | 2.315474e+09 | 21.20334 | 21.56288 |
| Sao Tome and Principe | ST | STP | 2019 | 4.129761e+08 | NA | 19.83890 | NA |
| Saudi Arabia | SA | SAU | 2019 | 8.385648e+11 | 2.189408e+11 | 27.45496 | 26.11207 |
| Senegal | SN | SEN | 2019 | 2.340400e+10 | 9.186798e+09 | 23.87617 | 22.94103 |
| Serbia | RS | SRB | 2019 | 5.151424e+10 | 3.139467e+10 | 24.66512 | 24.16990 |
| Seychelles | SC | SYC | 2019 | 1.868690e+09 | 1.701472e+09 | 21.34850 | 21.25476 |
| Sierra Leone | SL | SLE | 2019 | 4.076579e+09 | 1.546805e+09 | 22.12852 | 21.15946 |
| Singapore | SG | SGP | 2019 | 3.769016e+11 | 5.531798e+11 | 26.65525 | 27.03895 |
| Sint Maarten (Dutch part) | SX | SXM | 2019 | 1.407880e+09 | NA | 21.06535 | NA |
| Slovak Republic | SK | SVK | 2019 | 1.057117e+11 | 9.681579e+10 | 25.38398 | 25.29608 |
| Slovenia | SI | SVN | 2019 | 5.438665e+10 | 4.080292e+10 | 24.71938 | 24.43202 |
| Small states | S1 | SST | 2019 | 2.437924e+11 | 1.620174e+11 | 26.21958 | 25.81097 |
| Solomon Islands | SB | SLB | 2019 | 1.619155e+09 | 7.529303e+08 | 21.20517 | 20.43948 |
| Somalia | SO | SOM | 2019 | 9.420431e+09 | 5.423000e+09 | 22.96615 | 22.41391 |
| South Africa | ZA | ZAF | 2019 | 3.893300e+11 | 1.039350e+11 | 26.68769 | 25.36703 |
| South Asia (IDA & IBRD) | T5 | TSA | 2019 | 3.658210e+12 | 7.844331e+11 | 28.92799 | 27.38823 |
| South Asia | 8S | SAS | 2019 | 3.658210e+12 | 7.844331e+11 | 28.92799 | 27.38823 |
| South Sudan | SS | SSD | 2019 | NA | NA | NA | NA |
| Spain | ES | ESP | 2019 | 1.394320e+12 | 4.457221e+11 | 27.96343 | 26.82296 |
| Sri Lanka | LK | LKA | 2019 | 8.901498e+10 | 2.456991e+10 | 25.21207 | 23.92479 |
| St. Kitts and Nevis | KN | KNA | 2019 | 1.107856e+09 | NA | 20.82569 | NA |
| St. Lucia | LC | LCA | 2019 | 2.092082e+09 | NA | 21.46143 | NA |
| St. Martin (French part) | MF | MAF | 2019 | 6.522060e+08 | NA | 20.29587 | NA |
| St. Vincent and the Grenadines | VC | VCT | 2019 | 9.107667e+08 | NA | 20.62980 | NA |
| Sub-Saharan Africa (excluding high income) | ZF | SSA | 2019 | 1.828592e+12 | 4.352895e+11 | 28.23457 | 26.79928 |
| Sub-Saharan Africa (IDA & IBRD countries) | T6 | TSS | 2019 | 1.830461e+12 | 4.370749e+11 | 28.23559 | 26.80337 |
| Sub-Saharan Africa | ZG | SSF | 2019 | 1.830461e+12 | 4.370749e+11 | 28.23559 | 26.80337 |
| Sudan | SD | SDN | 2019 | 3.233808e+10 | 5.713051e+09 | 24.19951 | 22.46602 |
| Suriname | SR | SUR | 2019 | 4.016041e+09 | NA | 22.11356 | NA |
| Sweden | SE | SWE | 2019 | 5.338795e+11 | 2.329029e+11 | 27.00344 | 26.17389 |
| Switzerland | CH | CHE | 2019 | 7.213691e+11 | 4.123506e+11 | 27.30442 | 26.74514 |
| Syrian Arab Republic | SY | SYR | 2019 | 2.258305e+10 | 6.546690e+09 | 23.84047 | 22.60223 |
| Tajikistan | TJ | TJK | 2019 | 8.300814e+09 | 3.408735e+09 | 22.83962 | 21.94961 |
| Tanzania | TZ | TZA | 2019 | 6.102673e+10 | 1.036346e+10 | 24.83458 | 23.06155 |
| Thailand | TH | THA | 2019 | 5.439767e+11 | 2.729165e+11 | 27.02217 | 26.33243 |
| Timor-Leste | TL | TLS | 2019 | 2.027034e+09 | 1.004078e+09 | 21.42984 | 20.72734 |
| Togo | TG | TGO | 2019 | 6.992700e+09 | 2.260736e+09 | 22.66813 | 21.53896 |
| Tonga | TO | TON | 2019 | 5.120537e+08 | 3.338263e+08 | 20.05394 | 19.62613 |
| Trinidad and Tobago | TT | TTO | 2019 | 2.377575e+10 | NA | 23.89193 | NA |
| Tunisia | TN | TUN | 2019 | 4.190554e+10 | 2.362736e+10 | 24.45868 | 23.88567 |
| Turkiye | TR | TUR | 2019 | 7.610059e+11 | 2.292080e+11 | 27.35791 | 26.15790 |
| Turkmenistan | TM | TKM | 2019 | 4.523286e+10 | 8.844000e+09 | 24.53509 | 22.90301 |
| Turks and Caicos Islands | TC | TCA | 2019 | 1.177285e+09 | NA | 20.88648 | NA |
| Tuvalu | TV | TUV | 2019 | 5.412320e+07 | NA | 17.80677 | NA |
| Uganda | UG | UGA | 2019 | 3.534816e+10 | 7.865670e+09 | 24.28851 | 22.78577 |
| Ukraine | UA | UKR | 2019 | 1.538830e+11 | 7.583286e+10 | 25.75946 | 25.05180 |
| United Arab Emirates | AE | ARE | 2019 | 4.179897e+11 | 2.955998e+11 | 26.75872 | 26.41227 |
| United Kingdom | GB | GBR | 2019 | 2.851407e+12 | 9.418299e+11 | 28.67883 | 27.57109 |
| United States | US | USA | 2019 | 2.152140e+13 | 3.116954e+12 | 30.70007 | 28.76788 |
| Upper middle income | XT | 2019 | 2.370037e+13 | 5.201663e+12 | 30.79651 | 29.28000 | |
| Uruguay | UY | URY | 2019 | 6.222239e+10 | 1.349366e+10 | 24.85398 | 23.32549 |
| Uzbekistan | UZ | UZB | 2019 | 6.028350e+10 | 2.665756e+10 | 24.82232 | 24.00634 |
| Vanuatu | VU | VUT | 2019 | 9.365263e+08 | 4.592509e+08 | 20.65769 | 19.94511 |
| Venezuela, RB | VE | VEN | 2019 | NA | NA | NA | NA |
| Viet Nam | VN | VNM | 2019 | 3.343653e+11 | 2.659763e+11 | 26.53550 | 26.30667 |
| Virgin Islands (U.S.) | VI | VIR | 2019 | 4.121000e+09 | 4.139000e+09 | 22.13936 | 22.14372 |
| West Bank and Gaza | PS | PSE | 2019 | 1.713350e+10 | 9.161700e+09 | 23.56430 | 22.93830 |
| World | 1W | WLD | 2019 | 8.794557e+13 | 2.436815e+13 | 32.10774 | 30.82430 |
| Yemen, Rep. | YE | YEM | 2019 | NA | NA | NA | NA |
| Zambia | ZM | ZMB | 2019 | 2.330867e+10 | 7.961078e+09 | 23.87209 | 22.79783 |
| Zimbabwe | ZW | ZWE | 2019 | 2.183223e+10 | 6.165817e+09 | 23.80665 | 22.54229 |
Metodologi penelitian
Pertemuan 1
Prodi PIWAR Politeknik APP Jakarta
Hari ini ☀️
- Administrasi
- Refresh OLS
Tentang Metodoologi penelitian
- Part 1 Melanjutkan math&stats.
- Regresi multivariat, mencari data perdagangan dan visualisasinya.
- Part 2 fokus ke metode penulisan laporan penelitian.
- Menulis TA penelitian.
- metode-metode lain selain regresi.
- Sebagian besar materi merupakan pengenalan minimal.
- Pendalaman bisa dilakukan di luar kelas.
Kenapa metodologi penelitian
- Meneliti pada hakikatnya adalah skill dasar:
- memahami bagaimana formulasikan pertanyaan.
- mencari cara menjawabnya.
- menggunakan tools data analytics & visualization menjadi semakin mainstream.
- skill bermain dengan data menjadi nilai penting.
- Diharapkan mahasiswa minimal ter-ekspose dengan data analytics & visualization yang bisa dikembangkan sendiri ke depan.
Informasi Pengajar
| nama | ruangan | matkul lain |
|---|---|---|
| Bayu Prabowo Sutjiatmo | Ruang Kaprodi PIWAR | - |
| Theresia Anindita | Ruang Pudir II | - |
| I Made Krisna | A2004 (Ruang Kerja Sama) | LLP |
Ekspektasi dari mahasiswa
- Sudah mahir probabilitas dan regresi sederhana.
- harusnya aman kalau lulus stats&math.
- Tidak perlu bisa bahasa inggris, but a good command of english will certainly be helpful
- Lumayan membantu jika bisa spreadsheet.
- Punya akses terhadap internet dan alat komputasi seperti laptop.
Beberapa aturan
- kuliah efektif antara 90 - 100 menit.
- Kehadiran tidak diwajibkan.
- Yang hadir wajib untuk tertib dan tidak boleh berisik.
- Mahasiswa dipersilakan meninggalkan kelas untuk alasan apapun.
- Tidak perlu ijin dulu.
- Silakan tanya kapan saja jika bingung.
Tools
Kuliah ini dapat diakses di krisna.or.id/courses/metopel/slides
- pencet
E, tunggu, laluctrl+P(PDF) - klik kanan, save page as. (html).
- pencet
pasca-UTS anda butuh Zotero dan Quarto.
- downloadnya nanti aja siapa tau ada update.
Struktur kuliah
| minggu | konten |
|---|---|
| 1 | intro & regresi multivariat |
| 2 | Instalasi software yang diperlukan |
| 3 | Prinsip dasar OLS |
| 4 | Karakteristik umum data |
| 5 | Data serial waktu |
| 6 | Mencari dan melakukan visualisasi data |
| 7 | Visualisasi di R dengan ggplot |
| 8 | UTS |
Struktur kuliah
| minggu | konten |
|---|---|
| 9 | Proses membuat laporan yang baik |
| 10 | Melakukan review literatur |
| 11 | Metode lain di luar regresi |
| 12 | Metode kualitatif |
| 13 | Membuat diagram alir dan gap analysis |
| 14 | Menulis dokumen di RStudio |
| 15 | Menggunakan Zotero |
| 16 | UAS |
Nilai ✍🏾
| evaluation | covers | % |
|---|---|---|
| Tugas individu | semua | 30 |
| UTS | 7 minggu pertama | 30 |
| UAS | semua | 40 |
Slides saja mestinya cukup untuk dapat 100 di UTS dan UAS.
Tugas individu berupa membuat laporan dalam 3 format: pdf, html dan docx.
- contohnya begini.
- webpage ini dapat jadi portofolio anda.
Questions?
Question!
Ada yang bisa menjelaskan apa materi regresi di Math&Stats?
Apakah seperti ini?
\[ Y_i=\beta_0+\beta_1 X_i+\mu_i \]
Regresi
- Disebut juga dengan Ordinary Least Square (OLS).
- Digunakan untuk mencari parameter yang menghubungkan dua variabel.
- Metode OLS sangat sering digunakan untuk penelitian karena dia simpel namun powerful.
- Namun, bisa regresi saja tidak cukup!
- kita tau cara menyampaikan hasilnya dengan tepat.
Regresi univariat
\[ Y_i=\beta_0+\beta_1 X_i+\mu_i \]
- Y disebut juga variabel dependen
- X disebut juga variabel independen
- nilai Y dan X kita dapatkan dari data
- \(\beta_0\) dan \(\beta_1\) disebut parameter. Nilainya kita dapat dari hasil estimasi komputer.
- \(\mu\) disebut juga error term / residual. Dia bersifat independen
Regresi dengan R
- Melakukan itu semua dengan R dan RStudio, termasuk visualisasi data dan membuat laporan penelitiannya.
- Kelas ini akan fokus menggunakan data-data perdagangan dari berbagai sumber.
- Kenapa R dan RStudio?
- Gratis.
- Mature, intuitive dan mudah kalau mau pindah bahasa.
- Digunakan banyak profesional juga.
- Gratis!!!!
Contoh regresi dengan R
Menarik data World Development Indicators punya World Bank:
#| echo: true
library(WDI)
library(tidyverse)
indi<-c( # membuat dictionary
"PDB"="NY.GDP.MKTP.CD",
"import"="NE.IMP.GNFS.CD"
)
dat<-WDI( # Menarik data World Bank
country="all",
indicator=indi,
start=2019,end=2019,
)
dat$LPDB<-log(dat$PDB) # menambahkan transformasi log
dat$Limport<-log(dat$import)Menggambar grafik
library(ggrepel)
weleh<-subset(dat,iso2c%in%c("ID","KR","CN","US","GB","EU","SG",
"TL","BN","KH","MY","TH","JP"))
www<-dat %>% ggplot(aes(x=Limport,y=LPDB)) + geom_point() + geom_smooth(method="lm")
www+geom_label_repel(data=weleh,box.padding = 0.35, point.padding = 0.5, segment.color = 'grey50',label=weleh$country,min.segment.length = 0,nudge_y = -4) + theme_classic()
Figure 1: Hubungan impor dan PDB, 2019
Melakukan regresi
Call:
lm(formula = LPDB ~ Limport, data = dat)
Residuals:
Min 1Q Median 3Q Max
-1.67150 -0.25452 0.02952 0.30827 1.39515
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.6142 0.2905 -2.114 0.0356 *
Limport 1.0633 0.0118 90.126 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.4774 on 226 degrees of freedom
(38 observations deleted due to missingness)
Multiple R-squared: 0.9729, Adjusted R-squared: 0.9728
F-statistic: 8123 on 1 and 226 DF, p-value: < 2.2e-16R dan Regresi
- Kita perkuat landasan teori dulu
- Kita belajar karakteristik dan asumsi OLS
- Kita juga akan melakukan teknik-teknik regresi yang lebih maju:
- Regresi multivariat: \(Y_i=\beta_0+\sum_j^N \beta_j X_{i,j}+\mu_i\).
- Regresi dengan variabel kategori / Dummy.
- Regresi serial waktu.
- Anda akan menulis penelitian dengan regresi yang lebih kompleks.
Minggu depan
- Bawa laptop karena kita mau install-install software.
- Kalau sudah bisa install sendiri, ga perlu masuk gpp.
- Speknya ga perlu sakti-sakti. Ram 1Gb udah sangat cukup.