Scheduled monthly wages rose in all seven Kanto prefectures between 2020 and 2023, but the growth rates varied widely—from +12.9% in Tochigi to just +0.2% in Tokyo. The gap between Tokyo and Gunma narrowed from ¥86,000 to ¥70,400. These figures, however, do not represent the pay-raise rate experienced by the same workers over time.
Scheduled monthly wages in 2020 and 2023 (all ages, men and women combined)
| Prefecture | 2020 | 2023 | Increase | Increase rate |
|---|---|---|---|---|
| Tokyo | ¥396,300 | ¥397,000 | +¥700 | +0.2% |
| Kanagawa | ¥364,400 | ¥384,100 | +¥19,700 | +5.4% |
| Saitama | ¥324,700 | ¥347,300 | +¥22,600 | +7.0% |
| Chiba | ¥328,700 | ¥337,800 | +¥9,100 | +2.8% |
| Ibaraki | ¥325,800 | ¥340,600 | +¥14,800 | +4.5% |
| Tochigi | ¥314,900 | ¥355,400 | +¥40,500 | +12.9% |
| Gunma | ¥310,300 | ¥326,600 | +¥16,300 | +5.3% |
Tochigi gained ¥40,500, while Tokyo rose by only ¥700
The increase rates were +12.9% in Tochigi, +7.0% in Saitama, +5.4% in Kanagawa, +5.3% in Gunma, +4.5% in Ibaraki, +2.8% in Chiba, and +0.2% in Tokyo. In absolute terms, Tochigi gained ¥40,500 and moved into third place in Kanto by 2023.
Tokyo's increase was only ¥700, but its 2023 level of ¥397,000 remained the highest. The difference between the highest prefecture, Tokyo, and the lowest, Gunma, shrank by ¥15,600. Faster growth outside Tokyo narrowed the gap, but a substantial difference in wage levels remained.
The three-year difference also includes changes in industry mix and the survey population
Regional demand for labor can affect wage levels in different ways: manufacturing by companies such as Honda, Nissan, and Canon in Tochigi; R&D in Yokohama, Kawasaki, and Atsugi in Kanagawa; and manufacturing and logistics in Saitama. Tokyo started from a much higher level, making even modest shifts in composition harder to see as a large percentage gain.
But the 2020-to-2023 comparison does not track the same workers. The averages can change if the age, gender, industry, or company-size composition of surveyed employers and workers changes. The period also spans the COVID-19 pandemic, so it would be incorrect to say that “everyone in Tochigi got a 12.9% pay raise.” The data are better read as showing how the average composition and wage level of each regional labor market changed.
How to read these figures
This comparison uses nominal scheduled monthly wages. Bonuses and overtime pay are excluded, and the figures are not adjusted for inflation. Because the data combine all ages and both sexes, differences in age structure, industry composition, and company-size composition across prefectures also affect the averages.
What the table directly shows is the difference between the published 2020 and 2023 values. Explaining the causes or measuring changes in real wages requires additional data.
Conclusion: Regional gaps narrowed, but substantial differences in wage levels remain
Between 2020 and 2023, wage growth in northern Kanto, Saitama, and Kanagawa outpaced Tokyo, narrowing Kanto's maximum gap. Tokyo and Kanagawa still ranked at the top in 2023, however, and the three-year growth rates should not be interpreted as individual pay raises.
- Tochigi recorded the largest increase: +¥40,500, or +12.9%
- Tokyo rose only ¥700 but remained first in absolute wage level in 2023
- The Tokyo–Gunma gap narrowed from ¥86,000 to ¥70,400
- Changes in the average also reflect shifts in industry, age, and company-size composition
Source: Ministry of Health, Labour and Welfare, Basic Survey on Wage Structure (2020 and 2023)
📊 Analysis notes
- Statistics used: Ministry of Health, Labour and Welfare, Basic Survey on Wage Structure (e-Stat table ID: 0003426933, view on e-Stat)
- Area covered: Seven prefectures of the Kanto region
- Reference years: 2020 and 2023
- Data retrieved: June 6, 2026
- Note: The article centers on values published in the official statistics. Interpretation of the background may also involve factors not directly shown in the table, such as industry composition, age structure, and price trends, so the published figures should be distinguished from contextual interpretation.
Figures in the charts and tables were independently compiled and visualized from the statistical data above.