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iso3
stringclasses
1 value
year
int64
2k
2.02k
age_class
stringclasses
14 values
category
stringclasses
11 values
amount_jpy
float64
55
385k
JPN
2,000
25-29
Clothing & footwear
11,649
JPN
2,001
25-29
Clothing & footwear
11,699
JPN
2,002
25-29
Clothing & footwear
11,383
JPN
2,003
25-29
Clothing & footwear
11,096
JPN
2,004
25-29
Clothing & footwear
11,297
JPN
2,005
25-29
Clothing & footwear
12,141
JPN
2,006
25-29
Clothing & footwear
11,682
JPN
2,007
25-29
Clothing & footwear
13,137
JPN
2,008
25-29
Clothing & footwear
11,681
JPN
2,009
25-29
Clothing & footwear
11,395
JPN
2,010
25-29
Clothing & footwear
9,956
JPN
2,011
25-29
Clothing & footwear
10,433
JPN
2,012
25-29
Clothing & footwear
9,919
JPN
2,013
25-29
Clothing & footwear
11,234
JPN
2,014
25-29
Clothing & footwear
10,749
JPN
2,000
30-34
Clothing & footwear
13,563
JPN
2,001
30-34
Clothing & footwear
13,317
JPN
2,002
30-34
Clothing & footwear
12,370
JPN
2,003
30-34
Clothing & footwear
12,710
JPN
2,004
30-34
Clothing & footwear
12,608
JPN
2,005
30-34
Clothing & footwear
12,499
JPN
2,006
30-34
Clothing & footwear
12,394
JPN
2,007
30-34
Clothing & footwear
13,080
JPN
2,008
30-34
Clothing & footwear
12,759
JPN
2,009
30-34
Clothing & footwear
11,747
JPN
2,010
30-34
Clothing & footwear
11,730
JPN
2,011
30-34
Clothing & footwear
11,669
JPN
2,012
30-34
Clothing & footwear
12,034
JPN
2,013
30-34
Clothing & footwear
12,266
JPN
2,014
30-34
Clothing & footwear
12,546
JPN
2,000
35-39
Clothing & footwear
15,398
JPN
2,001
35-39
Clothing & footwear
15,111
JPN
2,002
35-39
Clothing & footwear
14,530
JPN
2,003
35-39
Clothing & footwear
14,246
JPN
2,004
35-39
Clothing & footwear
13,926
JPN
2,005
35-39
Clothing & footwear
14,270
JPN
2,006
35-39
Clothing & footwear
13,946
JPN
2,007
35-39
Clothing & footwear
13,345
JPN
2,008
35-39
Clothing & footwear
13,516
JPN
2,009
35-39
Clothing & footwear
13,305
JPN
2,010
35-39
Clothing & footwear
12,589
JPN
2,011
35-39
Clothing & footwear
12,120
JPN
2,012
35-39
Clothing & footwear
12,624
JPN
2,013
35-39
Clothing & footwear
12,837
JPN
2,014
35-39
Clothing & footwear
13,899
JPN
2,015
35-39
Clothing & footwear
13,038
JPN
2,016
35-39
Clothing & footwear
13,724
JPN
2,017
35-39
Clothing & footwear
12,411
JPN
2,018
35-39
Clothing & footwear
13,282
JPN
2,019
35-39
Clothing & footwear
12,876
JPN
2,020
35-39
Clothing & footwear
12,030
JPN
2,021
35-39
Clothing & footwear
10,912
JPN
2,022
35-39
Clothing & footwear
11,047
JPN
2,023
35-39
Clothing & footwear
11,362
JPN
2,024
35-39
Clothing & footwear
11,921
JPN
2,000
40-44
Clothing & footwear
18,596
JPN
2,001
40-44
Clothing & footwear
16,722
JPN
2,002
40-44
Clothing & footwear
16,496
JPN
2,003
40-44
Clothing & footwear
16,319
JPN
2,004
40-44
Clothing & footwear
16,203
JPN
2,005
40-44
Clothing & footwear
15,362
JPN
2,006
40-44
Clothing & footwear
14,798
JPN
2,007
40-44
Clothing & footwear
16,229
JPN
2,008
40-44
Clothing & footwear
15,063
JPN
2,009
40-44
Clothing & footwear
14,701
JPN
2,010
40-44
Clothing & footwear
14,232
JPN
2,011
40-44
Clothing & footwear
14,300
JPN
2,012
40-44
Clothing & footwear
14,382
JPN
2,013
40-44
Clothing & footwear
13,817
JPN
2,014
40-44
Clothing & footwear
14,296
JPN
2,015
40-44
Clothing & footwear
14,666
JPN
2,016
40-44
Clothing & footwear
13,964
JPN
2,017
40-44
Clothing & footwear
14,323
JPN
2,018
40-44
Clothing & footwear
14,434
JPN
2,019
40-44
Clothing & footwear
13,167
JPN
2,020
40-44
Clothing & footwear
11,900
JPN
2,021
40-44
Clothing & footwear
12,545
JPN
2,022
40-44
Clothing & footwear
12,302
JPN
2,023
40-44
Clothing & footwear
12,624
JPN
2,024
40-44
Clothing & footwear
13,181
JPN
2,000
45-49
Clothing & footwear
19,882
JPN
2,001
45-49
Clothing & footwear
18,273
JPN
2,002
45-49
Clothing & footwear
17,808
JPN
2,003
45-49
Clothing & footwear
17,788
JPN
2,004
45-49
Clothing & footwear
16,310
JPN
2,005
45-49
Clothing & footwear
17,395
JPN
2,006
45-49
Clothing & footwear
17,358
JPN
2,007
45-49
Clothing & footwear
16,721
JPN
2,008
45-49
Clothing & footwear
17,270
JPN
2,009
45-49
Clothing & footwear
15,751
JPN
2,010
45-49
Clothing & footwear
15,479
JPN
2,011
45-49
Clothing & footwear
15,816
JPN
2,012
45-49
Clothing & footwear
15,410
JPN
2,013
45-49
Clothing & footwear
16,415
JPN
2,014
45-49
Clothing & footwear
16,016
JPN
2,015
45-49
Clothing & footwear
15,371
JPN
2,016
45-49
Clothing & footwear
15,105
JPN
2,017
45-49
Clothing & footwear
15,083
JPN
2,018
45-49
Clothing & footwear
14,237
JPN
2,019
45-49
Clothing & footwear
15,412
End of preview. Expand in Data Studio

Japan Household Spending by Age of Household Head (家計調査) + Aging Context

Japan's household consumption by age of household head — 11 categories × 14 age classes, 2000–2024 (家計調査, English columns) — with a 65+ spending gradient joined to the national 65+ population share on iso3 × year.

Why this exists

Japan is the world's oldest large economy, and its official 家計調査 shows how spending shifts as the household head ages. This lifts that detail table out of the Japanese-only source, translates it, and adds a ready-made elderly-vs-average gradient against Japan's 65+ population share. The aging signal is in the data: 65-and-over households spend ~1.13× the average on medical care but ~0.85× on culture & recreation.

Tables

File Grain Layer
jpn_household_spending_by_age.csv iso3, year, age_class, category, amount_jpy L0
jpn_spending_age_gradient.csv iso3, year, category, amount_all_avg_jpy, amount_65plus_jpy, elderly_index, elderly_pop_share_pct L1 (家計調査 + World Bank 65+ share)

Notes on the data

  • amount_jpy = average monthly yen per two-or-more-person household. age_class ∈ {Average (all ages), 25-2980-84, 65 and over}. Income lines are absent (only published for 勤労者世帯).
  • elderly_index = amount_65plus_jpy / amount_all_avg_jpy; elderly_pop_share_pct = Japan's 65+ population share that year (World Bank).

Sample queries

-- How elderly spending tilts by category, latest year
select category, elderly_index, elderly_pop_share_pct
from jpn_spending_age_gradient where year = 2024 order by elderly_index desc;

-- Food spending by age of household head
select age_class, amount_jpy from jpn_household_spending_by_age
where category = 'Food' and year = 2024 order by amount_jpy desc;

License & attribution

Combined sources — see the LICENSE file for full terms. When reusing you must:

  • 出典:総務省統計局「家計調査」(e-Stat 経由取得)を加工して作成 (PDL 1.0 requires 出典表示 + 加工明記)
  • Source: World Bank WDI (CC BY 4.0)
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