This article presents a list of Japanese regions by Human Development Index as of 2021. This article also includes a list of Japanese prefectures by historical HDI in 1990, 1995 and 2000 further below.
This is a list regions of Japan by Human Development Index calculated using the new methodology. [1]
| Rank | Region | HDI (2021) |
|---|---|---|
| Very high human development | ||
| 1 | Southern Kantō (Saitama, Chiba, Tokyo, Kanagawa, Yamanashi, Nagano) | 0.951 |
| 2 | Kansai (Shiga, Kyoto, Osaka, Hyōgo, Nara, Wakayama) | 0.928 |
| – |  Japan | 0.925 |
| 3 | Tōkai (Gifu, Shizuoka, Aichi, Mie) | 0.924 |
| 4 | Chūgoku (Tottori, Shimane, Okayama, Hiroshima, Yamaguchi) | 0.921 |
| 5 | Northern Kantō, Koshin (Ibaraki, Tochigi, Gunma) | 0.913 |
| 6 | Hokuriku (Niigata, Toyama, Ishikawa, Fukui) | 0.908 |
| 7 | Shikoku (Tokushima, Kagawa, Ehime, Kōchi) | 0.905 |
| Kyushu (Fukuoka, Saga, Nagasaki, Kumamoto, Ōita, Miyazaki, Kagoshima, Okinawa) | ||
| 9 | Hokkaido | 0.900 |
| 10 | Tōhoku (Aomori, Iwate, Miyagi, Akita, Yamagata, Fukushima) | 0.893 |
This is a list of Japanese prefectures by Human Development Index calculated using the old methodology. This data was taken from the 2007 paper "Gross National Happiness and Material Welfare in Bhutan and Japan" (Tashi Choden, Takayoshi Kusago, Kokoro Shirai, Centre for Bhutan Studies, Osaka University).
| Rank | Prefecture | HDI (1990) | HDI (1995) | HDI (2000) |
|---|---|---|---|---|
| 1 |  Tokyo | 0.9296 | 0.9448 | 0.9667 |
| 2 |  Aichi | 0.9115 | 0.9265 | 0.9460 |
| 3 |  Shiga | 0.9080 | 0.9229 | 0.9426 |
| 4 |  Shizuoka | 0.9056 | 0.9204 | 0.9402 |
| 5 |  Fukui | 0.9027 | 0.9204 | 0.9401 |
| 6 |  Toyama | 0.9031 | 0.9205 | 0.9392 |
| 7 |  Osaka | 0.9003 | 0.9177 | 0.9390 |
| 8 |  Nagano | 0.8980 | 0.9148 | 0.9365 |
| 9 |  Ishikawa | 0.8991 | 0.9163 | 0.9364 |
| 10 |  Hiroshima | 0.9032 | 0.9170 | 0.9361 |
| 11 |  Kyoto | 0.8952 | 0.9123 | 0.9333 |
| 12 |  Mie | 0.8934 | 0.9123 | 0.9329 |
| 13 |  Kanagawa | 0.8996 | 0.9119 | 0.9324 |
| 14 |  Yamanashi | 0.8944 | 0.9094 | 0.9319 |
| 15 |  Okayama | 0.8992 | 0.9152 | 0.9316 |
| 16 |  Kagawa | 0.8945 | 0.9122 | 0.9304 |
| 17 |  Gunma | 0.8957 | 0.9117 | 0.9303 |
| 18 |  Tochigi | 0.8955 | 0.9107 | 0.9294 |
| 19 |  Niigata | 0.8921 | 0.9095 | 0.9290 |
| 20 |  Hyōgo | 0.8950 | 0.9086 | 0.9290 |
| 21 |  Ōita | 0.8891 | 0.9076 | 0.9285 |
| 22 |  Gifu | 0.8921 | 0.9070 | 0.9263 |
| 23 |  Hokkaidō | 0.8863 | 0.9068 | 0.9260 |
| 24 |  Ibaraki | 0.8928 | 0.9080 | 0.9259 |
| 25 |  Yamaguchi | 0.8924 | 0.9084 | 0.9258 |
| 26 |  Miyagi | 0.8926 | 0.9071 | 0.9247 |
| 27 |  Fukushima | 0.8880 | 0.9044 | 0.9241 |
| 28 |  Tottori | 0.8887 | 0.9045 | 0.9239 |
| 29 |  Shimane | 0.8858 | 0.9021 | 0.9231 |
| 30 |  Fukuoka | 0.8896 | 0.9061 | 0.9228 |
| 31 |  Kumamoto | 0.8872 | 0.9045 | 0.9225 |
| 32 |  Ehime | 0.8862 | 0.9047 | 0.9221 |
| 33 |  Chiba | 0.8868 | 0.9019 | 0.9219 |
| 34 |  Yamagata | 0.8855 | 0.9014 | 0.9216 |
| 35 |  Saga | 0.8810 | 0.9021 | 0.9189 |
| 36 |  Iwate | 0.8792 | 0.8998 | 0.9186 |
| 37 |  Tokushima | 0.8831 | 0.9005 | 0.9182 |
| 38 |  Nara | 0.8794 | 0.8944 | 0.9169 |
| 39 |  Saitama | 0.8811 | 0.8956 | 0.9166 |
| 40 |  Kōchi | 0.8781 | 0.8964 | 0.9156 |
| 41 |  Wakayama | 0.8770 | 0.8957 | 0.9155 |
| 42 |  Miyazaki | 0.8780 | 0.8959 | 0.9148 |
| 43 |  Akita | 0.8777 | 0.8951 | 0.9142 |
| 44 |  Nagasaki | 0.8749 | 0.8949 | 0.9127 |
| 45 |  Kagoshima | 0.8762 | 0.8938 | 0.9127 |
| 46 |  Okinawa | 0.8810 | 0.8940 | 0.9111 |
| 47 |  Aomori | 0.8698 | 0.8877 | 0.9065 |
The economy of Bhutan is based on agriculture and forestry, which provide the main livelihood for more than 60% of the population. Agriculture consists largely of subsistence farming and animal husbandry. Rugged mountains dominate the terrain and make the building of roads and other infrastructure difficult. Bhutan is among the richest by gross domestic product (nominal) per capita in South Asia, at $3,491 as of 2022, but it still places 153rd, and among the poorest in the world. The total gross domestic product is only $2,653 million, and 178th according to IMF.
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