Women's wages as a share of men's in Kanagawa improved by 0.8 percentage points, from 76.1% in 2020 to 76.9% in 2023. Yet the absolute monthly gap widened slightly from ¥93,300 to ¥94,100. This article separates two facts that can coexist: the ratio improved, but the yen gap did not shrink.
Gender wage trends in Kanagawa (all ages, scheduled monthly wages)
| Year | Men (¥1,000) | Women (¥1,000) | Women ÷ men | Gap (¥1,000) |
|---|---|---|---|---|
| 2020 | 390.7 | 297.4 | 76.1% | 93.3 |
| 2021 | 392.3 | 299.8 | 76.5% | 92.5 |
| 2022 | 399.6 | 306.3 | 76.6% | 93.3 |
| 2023 | 408.5 | 314.4 | 76.9% | 94.1 |
Women's wages rose, but the absolute gap remained above ¥90,000
The female-to-male wage ratio moved upward within the 76% range for four consecutive years. In each age group shown below, the ratio is also 0.3 to 1.5 percentage points higher in 2023 than in 2020. The largest improvements, +1.5 points, appear at ages 35–39 and 45–49.
Meanwhile, the absolute gender gap was ¥93,300 in 2020 and ¥94,100 in 2023. Men's and women's wages both increased, and women's wages grew slightly faster in percentage terms, so the ratio improved. But the yen difference that would be visible in a monthly paycheck barely changed.
Comparison by age (2020 → 2023)
| Age group | 2020 women's ratio | 2023 women's ratio | Change |
|---|---|---|---|
| 20–24 | 97.1% | 97.4% | +0.3 pt |
| 25–29 | 91.2% | 91.8% | +0.6 pt |
| 30–34 | 82.1% | 83.2% | +1.1 pt |
| 35–39 | 77.3% | 78.8% | +1.5 pt |
| 40–44 | 73.8% | 75.1% | +1.3 pt |
| 45–49 | 72.1% | 73.6% | +1.5 pt |
| 50–54 | 70.4% | 71.8% | +1.4 pt |
| 55–59 | 65.8% | 67.2% | +1.4 pt |
For every age group listed, women's wage ratios rose between 2020 and 2023. The increases were especially notable at ages 35–39 and 45–49, both up 1.5 percentage points.
The yen gap will remain unless the management structure in R&D and manufacturing changes
Kanagawa has many relatively high-paying technical and R&D jobs, including Nissan in Yokohama, Fujitsu and NEC in Kawasaki, and Sony-related operations in Atsugi. Even if more women are hired into these fields, it takes time for the gender composition of managers and highly specialized professionals in their 40s and 50s to change.
For households in Yokohama and Kawasaki with jobs in Tokyo, balancing long commutes with childcare can also lead to changes in working arrangements. The 0.8-point improvement over four years is progress, but shrinking the absolute wage gap requires more women to remain on high-paying career tracks and advance into senior roles through middle age.
How to read these figures
These statistics measure scheduled monthly wages and exclude bonuses and overtime pay. All-age figures are also affected by differences in age and industrial composition. It is therefore not possible to attribute changes in the ratio solely to institutional or workplace changes.
What can be confirmed from Kanagawa's published figures for 2020–2023 is that the all-age female-to-male ratio rose slightly, and the ratio also increased in each age group shown here.
Summary: The ratio improved, but it is still too early to say the gap has narrowed
Kanagawa's female-to-male wage ratio improved, but the monthly gender gap still stands at ¥94,100. Progress should be assessed using both the ratio and the absolute difference, together with trends by age through the management years.
- Women's wage ratio rose from 76.1% to 76.9%, an improvement of 0.8 percentage points
- The absolute gap changed from ¥93,300 to ¥94,100
- Ratios generally improved across the age groups shown
- The next challenge is the composition of managerial and specialist roles in the 40s and 50s
Source: Ministry of Health, Labour and Welfare, Basic Survey on Wage Structure (2020–2023)
📊 Analysis notes
- Statistics used: Ministry of Health, Labour and Welfare, Basic Survey on Wage Structure (Table ID: 0003426933, view on e-Stat)
- Area: Kanagawa Prefecture
- Years: 2020–2023
- Data retrieved: June 6, 2026
- Notes: The article primarily organizes published statistical values. Interpreting the background also involves factors outside the table, including occupational mix, management composition, employment status, and age structure, so directly observable figures should be distinguished from interpretation.
Figures in charts and tables were independently compiled and visualized from the statistical data above.