EASI / 01Experimental · August 2026

Equality
at scale.

How much equality can a country sustain while being large, rich and industrially complex — and how much of a good everyday life is broadly accessible without being rich?

Tokyo: rail lines through the urban fabric.Manish Tulaskar / Unsplash ↗

The question

Gini is not the whole story.

A six-million-person welfare state and a 124-million-person industrial economy are not exactly the same problem. So I built an index that asks whether countries remain equal relative to the structural difficulty of their scale, while refusing to reward a country merely for being equally poor.

The result changed my mind. Japan does better than the global model expects, but once the comparison is restricted to rich industrial economies, population size stops explaining much of the equality gap with Northern and Central Europe.

Japan#26of 169 scored countries

EASI81.1

Human equality91.5

Scale residual+1.8

Population124m

Japan is about 1.8 Human Equality points above the global model's expectation for its population, income and industrial complexity. Within high-income industrial peers, however, it is almost exactly at expectation.

EASI v1.0 / formula

50%Human Equality100 − UNDP coefficient of human inequality

30%Shared DevelopmentUNDP Inequality-adjusted HDI percentile

20%Scale OverperformanceResidual after population, GNI/capita and industrial complexity

Why not equality ÷ population? That would mechanically punish every large country. A residual asks the more useful question: how much more or less equal is this country than we would expect given its scale and economic structure?

Japan vs. Nordics

Japan81.1#26 global

Denmark88.1#7 global

Finland89.9#5 global

Norway84.8#17 global

Sweden81.8#23 global

Adjusting for scale does not make Japan the world's most equal rich country. Finland, Denmark, Norway and Sweden all remain ahead in EASI v1.

Pedestrians in a narrow Tokyo alley lined with small shops — Tokyo: tiny storefronts and shared pedestrian space.Tsuyoshi Kozu / Unsplash ↗

People walking and cycling on a Copenhagen street — Copenhagen: calm streets, bicycles and everyday public life.Alain Rouiller / Unsplash ↗

Global ranking

169 scored countries

Search High-income industrial only

#	Country	EASI	Human equality	Scale ±	Population	Industry
1	SloveniaSVN	92.3	95.1	+2.0	2.1m	94.9
2	CzechiaCZE	92.2	94.9	+3.0	10.8m	94.7
3	SlovakiaSVK	90.3	94.7	+3.9	5.5m	90.9
4	IcelandISL	90.1	95.0	+0.5	0.4m	76.7
5	FinlandFIN	89.9	94.1	+1.3	5.6m	87.4
6	HungaryHUN	88.6	94.1	+3.9	9.7m	89.4
7	DenmarkDNK	88.1	94.5	+0.1	5.9m	89.0
8	NetherlandsNLD	87.8	93.6	+0.9	18.1m	85.6
9	BelarusBLR	87.6	93.7	+6.4	9.1m	79.1
10	BelgiumBEL	87.5	93.7	+0.6	11.7m	90.1
11	CanadaCAN	86.8	92.5	+2.8	39.3m	75.0
12	CroatiaHRV	86.6	93.3	+3.0	3.9m	78.5
13	AzerbaijanAZE	85.9	93.2	+12.5	10.3m	34.4
14	SerbiaSRB	85.7	92.7	+6.9	6.8m	71.0
15	GermanyDEU	85.0	92.9	+0.6	84.5m	95.6
16	United KingdomGBR	84.9	92.1	+1.9	68.7m	82.9
17	NorwayNOR	84.8	93.8	-1.2	5.5m	74.2
18	EstoniaEST	84.5	93.2	+1.2	1.4m	87.9
19	CyprusCYP	83.7	92.3	+1.9	1.3m	68.5
20	AustraliaAUS	82.9	91.4	+2.2	26.5m	65.4
21	UkraineUKR	82.0	91.9	+11.3	37.7m	51.8
22	KazakhstanKAZ	81.9	91.7	+7.3	20.3m	50.9
23	SwedenSWE	81.8	92.6	-0.5	10.6m	87.4
24	ArmeniaARM	81.6	91.7	+8.8	2.9m	47.2
25	IrelandIRL	81.5	93.5	-2.2	5.2m	90.3
26	JapanJPN	81.1	91.5	+1.8	124.4m	89.2
27	Moldova (Republic of)MDA	80.9	91.7	+9.3	3.1m	54.0
28	AustriaAUT	80.5	92.9	-0.6	9.1m	91.9
29	United Arab EmiratesARE	80.3	92.1	+0.1	10.6m	74.6
30	SwitzerlandCHE	79.7	92.5	-2.3	8.9m	90.9
31	GreeceGRC	78.9	91.1	+3.6	10.2m	67.4
32	Russian FederationRUS	78.6	91.4	+4.4	145.4m	75.6
33	Korea (Republic of)KOR	78.4	91.6	+0.4	51.7m	94.9
34	New ZealandNZL	77.8	91.2	+0.9	5.2m	74.2
35	LatviaLVA	77.1	91.7	+1.2	1.9m	79.8
36	AndorraAND	76.9	91.8	-0.4	0.1m	48.8
37	GeorgiaGEO	76.3	89.7	+6.9	3.8m	46.1
38	KyrgyzstanKGZ	75.4	90.3	+14.4	7.1m	49.4
39	FranceFRA	75.2	91.0	+0.8	66.4m	82.8
40	PolandPOL	74.8	90.5	+1.4	38.8m	82.5
41	MontenegroMNE	74.8	89.6	+3.8	0.6m	47.0
42	MaltaMLT	72.9	91.4	-2.1	0.5m	83.1
43	LithuaniaLTU	72.2	91.2	+0.0	2.9m	84.1
44	ArgentinaARG	72.1	88.4	+4.2	45.5m	63.3
45	TongaTON	72.1	89.0	+9.0	0.1m	48.4
46	RomaniaROU	70.3	90.2	+0.7	19.1m	83.9
47	SpainESP	69.7	89.5	+0.1	47.9m	81.9
48	SeychellesSYC	69.6	89.2	+1.4	0.1m	51.3
49	AlbaniaALB	68.6	87.2	+5.3	2.8m	43.5
50	LuxembourgLUX	68.5	91.1	-4.5	0.7m	79.1
50	United StatesUSA	68.5	89.3	-0.6	343.5m	76.5
52	MongoliaMNG	67.7	86.7	+7.5	3.4m	30.5
53	PortugalPRT	67.6	89.6	-0.6	10.4m	84.1
54	ItalyITA	67.5	89.7	-1.2	59.5m	90.0
54	North MacedoniaMKD	67.5	89.0	+1.6	1.8m	78.6
56	BulgariaBGR	65.5	89.0	+0.2	6.8m	82.2
57	IsraelISR	65.1	89.0	-1.9	9.3m	82.7
58	SamoaWSM	65.0	86.3	+8.3	0.2m	46.1
59	Brunei DarussalamBRN	64.9	90.3	-2.8	0.5m	60.6
60	TajikistanTJK	64.1	86.1	+14.3	10.4m	17.3
61	Venezuela (Bolivarian Republic of)VEN	63.9	85.5	+10.5	28.3m	41.7
62	Marshall IslandsMHL	63.6	85.7	+6.5	0.0m	36.3
63	OmanOMN	63.6	87.7	+0.0	5.0m	64.4
64	UruguayURY	63.6	87.1	+0.5	3.4m	63.6
65	Hong Kong, China (SAR)HKG	63.1	88.3	-4.4	7.4m	79.1
66	FijiFJI	62.9	85.8	+4.7	0.9m	45.3
67	JordanJOR	62.6	84.7	+6.3	11.4m	53.4
68	Bosnia and HerzegovinaBIH	61.9	86.2	+1.2	3.2m	67.2
69	ChinaCHN	61.7	84.8	+2.4	1422.6m	77.3
70	ThailandTHA	61.2	85.0	+1.6	71.7m	70.3
71	TuvaluTUV	59.4	84.2	+7.5	0.0m	6.5
72	IndonesiaIDN	58.9	83.6	+5.4	281.2m	53.3
72	VanuatuVUT	58.9	84.0	+13.0	0.3m	13.5
74	Viet NamVNM	58.8	83.7	+2.5	100.4m	75.2
75	SingaporeSGP	58.5	87.6	-10.0	5.8m	97.8
76	MalaysiaMYS	57.9	86.7	-1.4	35.1m	85.2
77	EcuadorECU	57.5	83.0	+3.5	18.0m	46.1
78	PhilippinesPHL	56.9	83.2	+6.2	114.9m	48.4
79	KiribatiKIR	56.8	83.4	+8.9	0.1m	20.9
80	ChileCHL	55.7	83.9	-0.8	19.7m	58.2
81	Sri LankaLKA	55.3	82.5	+2.9	23.0m	53.4
82	JamaicaJAM	54.9	83.0	+4.8	2.8m	38.0
83	Solomon IslandsSLB	54.7	82.8	+11.6	0.8m	30.9
84	TürkiyeTUR	51.5	83.5	-3.0	87.3m	74.2
85	BahamasBHS	50.6	83.2	-2.2	0.4m	34.6
86	Palestine, State ofPSE	50.5	80.3	+4.1	5.4m	45.8
87	PeruPER	50.0	80.1	+1.2	33.8m	43.9
88	MauritiusMUS	49.6	83.8	-4.3	1.3m	72.5
89	El SalvadorSLV	49.0	82.2	+1.5	6.3m	63.0
90	Iran (Islamic Republic of)IRN	48.6	80.9	-0.5	90.6m	66.9
91	AlgeriaDZA	47.9	79.3	+1.5	46.2m	33.4
91	MexicoMEX	47.9	82.2	-1.5	129.7m	74.4
93	Costa RicaCRI	47.7	82.5	-3.7	5.1m	72.1
94	NauruNRU	47.2	85.3	-4.7	0.0m	75.4
95	MyanmarMMR	46.6	78.4	+6.4	54.1m	37.9
96	Bolivia (Plurinational State of)BOL	45.7	79.0	+1.5	12.2m	45.4
97	Dominican RepublicDOM	45.3	81.8	-2.8	11.3m	66.8
98	TunisiaTUN	44.1	80.3	-0.6	12.2m	62.9
99	PanamaPAN	43.5	80.4	-5.8	4.5m	52.6
100	ParaguayPRY	42.9	80.0	-1.0	6.8m	49.4
101	IraqIRQ	42.4	77.2	+1.3	45.1m	25.0
102	PalauPLW	42.0	79.9	-3.0	0.0m	24.6
103	HondurasHND	41.4	77.6	+0.9	10.6m	59.1
104	Sao Tome and PrincipeSTP	41.3	76.4	+2.0	0.2m	17.4
105	NicaraguaNIC	40.4	76.5	+0.6	6.8m	42.9
106	Papua New GuineaPNG	40.1	73.5	+4.6	10.4m	10.0
107	EgyptEGY	39.6	78.0	-1.0	114.5m	46.3
108	BarbadosBRB	39.3	79.4	-5.5	0.3m	56.6
109	MaldivesMDV	38.9	79.5	-5.1	0.5m	52.2
110	KenyaKEN	38.7	73.3	+2.1	55.3m	24.0
111	MalawiMWI	38.3	71.0	+7.3	21.1m	11.3
112	BrazilBRA	37.4	77.2	-3.1	211.1m	57.4
113	Lao People's Democratic RepublicLAO	36.0	75.1	+0.2	7.7m	27.2
114	Tanzania (United Republic of)TZA	35.9	70.9	+3.7	66.6m	13.3
115	ColombiaCOL	35.9	76.9	-3.9	52.3m	50.9
116	YemenYEM	34.9	70.2	+10.2	39.4m	6.0
117	NepalNPL	33.6	71.1	+0.6	29.7m	22.4
118	Timor-LesteTLS	33.3	72.3	+0.1	1.4m	10.3
119	RwandaRWA	32.9	69.8	+2.2	14.0m	14.3
120	MoroccoMAR	32.7	73.9	-3.4	37.7m	54.5
121	GabonGAB	32.4	76.3	-6.0	2.5m	43.4
122	CambodiaKHM	32.2	73.7	-1.0	17.4m	54.5
123	UgandaUGA	29.7	69.4	+0.7	48.7m	36.4
124	Cabo VerdeCPV	29.5	73.2	-4.0	0.5m	28.7
125	BangladeshBGD	29.5	71.0	-3.4	171.5m	40.2
126	ZimbabweZWE	28.5	70.1	-0.0	16.3m	29.7
127	Congo (Democratic Republic of the)COD	28.5	65.9	+4.2	105.8m	10.8
128	GuatemalaGTM	27.5	73.1	-6.8	18.1m	55.4
129	IndiaIND	26.8	70.1	-3.0	1438.1m	39.1
130	BurundiBDI	26.2	65.4	+5.9	13.7m	3.0
131	MadagascarMDG	25.5	66.1	+2.8	31.2m	9.8
132	Saint LuciaLCA	25.0	70.9	-13.3	0.2m	38.4
133	BotswanaBWA	24.9	70.7	-10.7	2.5m	40.2
134	EthiopiaETH	23.8	66.1	+1.2	128.7m	7.9
135	NigeriaNGA	23.5	68.3	-2.4	227.9m	29.4
136	BhutanBTN	22.8	70.0	-10.3	0.8m	33.5
137	AfghanistanAFG	22.7	65.6	+1.3	41.5m	12.5
138	MaliMLI	20.5	67.5	-0.0	23.8m	28.7
139	CongoCOG	20.3	68.0	-7.8	6.2m	48.6
140	South AfricaZAF	20.2	67.6	-12.2	63.2m	58.1
141	PakistanPAK	20.1	67.4	-3.7	247.5m	34.3
142	NamibiaNAM	19.1	67.6	-11.0	3.0m	38.8
143	MauritaniaMRT	18.3	67.2	-5.8	5.0m	19.8
144	SudanSDN	17.5	64.7	-0.7	50.0m	6.1
145	LesothoLSO	16.3	66.3	-6.1	2.3m	45.0
146	LiberiaLBR	15.8	64.1	-0.8	5.5m	16.3
147	Guinea-BissauGNB	15.7	64.7	-2.5	2.2m	9.1
148	DjiboutiDJI	15.1	67.1	-8.3	1.2m	30.1
149	ZambiaZMB	14.8	64.3	-4.4	20.7m	19.1
150	Eswatini (Kingdom of)SWZ	14.6	64.9	-16.6	1.2m	64.1
151	NigerNER	14.2	63.3	-0.2	26.2m	13.1
152	GhanaGHA	14.0	64.6	-8.6	33.8m	29.2
153	TogoTGO	13.6	63.9	-5.7	9.3m	31.9
154	SenegalSEN	13.4	65.2	-6.5	18.1m	35.6
155	MozambiqueMOZ	12.9	61.3	-0.6	33.6m	8.0
156	GambiaGMB	11.5	63.6	-5.0	2.7m	15.3
157	CameroonCMR	10.9	62.5	-8.5	28.4m	26.5
158	South SudanSSD	10.8	58.3	+0.2	11.5m	0.9
159	HaitiHTI	10.1	61.8	-6.4	11.6m	18.8
160	Central African RepublicCAF	9.8	61.5	-2.6	5.2m	25.4
161	Sierra LeoneSLE	7.4	60.5	-4.3	8.5m	13.6
162	Côte d'IvoireCIV	7.2	60.6	-12.9	31.2m	32.8
163	ChadTCD	7.0	60.5	-3.5	19.3m	10.3
164	BeninBEN	7.0	61.5	-9.6	14.1m	34.2
165	ComorosCOM	6.9	60.3	-11.0	0.9m	22.0
166	AngolaAGO	6.7	60.1	-11.8	36.7m	20.3
167	GuineaGIN	6.3	61.0	-8.3	14.4m	22.0
168	Burkina FasoBFA	4.2	59.8	-6.5	23.0m	17.3
169	SomaliaSOM	2.7	56.9	-7.2	18.4m	19.8

Two trains at a Tokyo station platform — Mobility is another distribution system: it determines what geography costs.Muhammad Irfan / Unsplash ↗

EASI Urban β / 0.1

Equality of access,
not just income.

Tokyo raised a second question: if ordinary people can reach housing, jobs, shops and social life without a car or elite income, isn't that another kind of equality?

Urban β is intentionally conservative. It only uses comparable OECD inputs I could defend today; it does not yet measure the small lots, permissive mixed use, housing construction and rail-network reach that motivated the question.

50%Base EASI

30%Transit access

20%Housing security

β really means beta. Transit is OECD 2023 walking access to a public-transport stop in midsize/large functional urban areas. Housing security is 100 minus the bottom-quintile housing-cost overburden rate (2022 or latest). Chart values are rounded to the nearest percentage point. Japan has only 2 FUAs in the transit sample, so it is shown but excluded from the default robust ranking.

Urban β leaderboard

Require ≥4 FUAs

Robust transit coverage only

Germany54 FUAs · robust

87.4 Transit 95% · low-income housing overburden 18%

Hungary6 FUAs · robust

87.1 Transit 86% · low-income housing overburden 15%

Netherlands17 FUAs · robust

85.6 Transit 85% · low-income housing overburden 19%

United Kingdom44 FUAs · robust

85.2 Transit 95% · low-income housing overburden 29%

Belgium8 FUAs · robust

85.1 Transit 89% · low-income housing overburden 27%

Norway4 FUAs · robust

83.8 Transit 90% · low-income housing overburden 28%

Finland4 FUAs · robust

81.7 Transit 83% · low-income housing overburden 41%

Canada16 FUAs · robust

81.6 Transit 82% · low-income housing overburden 32%

Sweden4 FUAs · robust

80.8 Transit 91% · low-income housing overburden 37%

Switzerland5 FUAs · robust

80.6 Transit 93% · low-income housing overburden 36%

Ireland4 FUAs · robust

79.3 Transit 71% · low-income housing overburden 14%

France12 FUAs · robust

78.6 Transit 82% · low-income housing overburden 18%

Poland12 FUAs · robust

76.7 Transit 73% · low-income housing overburden 13%

Spain11 FUAs · robust

71.3 Transit 80% · low-income housing overburden 38%

Italy9 FUAs · robust

70.1 Transit 63% · low-income housing overburden 13%

United States122 FUAs · robust

59.5 Transit 49% · low-income housing overburden 47%

The missing variables are probably the most interesting ones.

Small-lot mixed use, zoning permissiveness, housing-construction response, amenity density, residential segregation and the number of jobs/services reachable in 30–45 minutes are exactly where Japan may distinguish itself. I am leaving them out until the data are good enough rather than manufacturing false precision.

What survived the test

Scale matters globally.

Across the 169-country model, a doubling of population is associated with roughly half a Human Equality point less after controlling for income and industrial complexity.

Not much among rich industrial peers.

Inside the 44 high-income industrial economies, the population coefficient becomes small and statistically insignificant. Germany is the crucial counterexample to a simple “Japan is huge” explanation.

The Tokyo hypothesis remains open.

Current national datasets are good at measuring redistribution and bad at measuring shared urban life. Urban β is a first checkpoint, not a verdict.

Open data & methodology

Reproduce it.

Download EASI v1 CSV ↓ Download Urban β CSV ↓ UNDP HDR data ↗ UNIDO statistics ↗ OECD transit data ↗ OECD housing data ↗