Exit Cost Index

Phase 3 — blended sub-components + regional dispersion

A post-scarcity measure — how free are you from the compulsion to work?

The Exit Cost Index asks one operational question: if you stopped earning tomorrow, could you survive with dignity? Lower exit cost means greater freedom to leave the labor market without destitution. This is the economic foundation of post-scarcity, measured per country.

Updated 2026-04-26. 38 countries with composite score.

Map boundaries are from Natural Earth and may not reflect current political realities or disputed territories. Hover for country detail.

Top 25 by composite score

NetherlandsDenmarkLuxembourgIcelandNorwaySwedenAustriaBelgiumNew ZealandFinlandGermanySloveniaSwitzerlandCroatiaEstoniaSpainPortugalItalyLatviaFranceIrelandCzech RepublicLithuaniaUnited KingdomPoland7.47.37.37.27.17.06.96.96.76.56.56.36.36.36.16.16.05.95.95.85.65.45.35.15.0

* Composite computed on a subset of axes (weights re-normalized; income + healthcare always required). See methodology.

Income substitutionWeight 35%

Cash transfers that replace earned income when work stops.

  1. 1.Denmark8.4
  2. 2.Luxembourg8.1
  3. 3.Netherlands7.6
  4. 4.Portugal7.4
  5. 5.Spain7.0
Healthcare independenceWeight 25%

Access to essential health services without depending on an employer.

  1. 1.Iceland10.0
  2. 2.Canada10.0
  3. 3.Norway9.8
  4. 4.New Zealand9.8
  5. 5.Australia9.8
Housing decommodificationWeight 20%

Public spending that lowers the dependence between work and shelter.

  1. 1.Albania10.0
  2. 2.Cyprus9.9
  3. 3.New Zealand9.7
  4. 4.North Macedonia8.7
  5. 5.Malta8.6
Food securityWeight 10%

Access to adequate food independent of income.

  1. 1.Switzerland10.0
  2. 2.Italy10.0
  3. 3.Cyprus10.0
  4. 4.Kazakhstan10.0
  5. 5.Belarus10.0
Digital & mobility accessWeight 10%

Connectivity and movement without employer-tied tools.

  1. 1.Netherlands10.0
  2. 2.Denmark10.0
  3. 3.Luxembourg10.0
  4. 4.Iceland10.0
  5. 5.Norway10.0

All countries

#
1Netherlands7.68.95.78.810.0−6%7.4
2Denmark8.49.23.29.010.0−6%†7.3
3Luxembourg8.16.54.29.910.0−0%7.3
4Iceland5.910.04.28.810.0−2%7.2
5Norway6.69.83.38.810.0−3%7.1
6Sweden6.49.24.79.010.0−5%†7.0
7Austria6.19.04.59.49.5−4%6.9
8Belgium5.99.34.98.710.0−5%6.9
9New Zealand4.19.89.76.89.8−11%6.7
10Finland5.77.67.57.69.8−8%6.5
11Germany4.79.55.19.69.8−6%6.5
12Slovenia4.38.24.88.79.3−0%†6.3
13Switzerland5.57.63.710.010.0−5%6.3
14Croatia5.87.74.89.28.3−6%†6.3
15Estonia4.78.24.08.29.6−2%6.1
16Spain7.06.94.59.110.0−13%6.1
17Portugal7.46.44.27.99.0−11%†6.0
18Italy6.18.74.610.09.1−17%5.9
19Latvia6.15.04.68.19.7−3%5.9
20France5.78.76.28.79.0−19%5.8
21Ireland1.78.76.19.410.0−5%†5.6
22Czech Republic5.07.34.38.38.9−13%5.4
23Lithuania4.46.74.69.19.1−11%5.3
24United Kingdom2.48.36.69.010.0−17%5.1
25Poland2.46.44.79.79.0−4%†5.0
26South Korea2.97.92.99.310.0−9%†5.0
27Hungary4.18.35.77.29.8−22%5.0
28Japan3.87.40.79.28.5−4%4.9
29Canada2.810.01.88.39.9−14%4.8
30Bulgaria6.44.54.18.08.1−17%†4.8
31Greece5.04.91.49.08.7−6%4.7
32Romania3.25.64.56.59.4−6%†4.7
33Turkey4.06.27.1—9.2−22%†4.6
34Chile4.35.96.56.410.0−23%4.6
35United States2.78.41.58.39.9−12%4.6
36Australia3.99.81.87.510.0−24%4.5
37Slovakia5.86.84.38.89.2−30%4.5
38Israel5.46.21.38.58.9−25%4.1
39Serbia—6.16.68.48.9−9%†—
40Colombia—6.71.44.67.6−30%†—
41Montenegro—5.68.58.39.1−11%†—
42Costa Rica—6.71.37.28.8−25%—
43Malta—5.88.68.59.8−8%†—
44Peru—3.84.31.98.0−18%†—
45Mexico—5.72.56.48.2−23%—
46Cyprus—6.39.910.09.2−8%†—
47North Macedonia—5.98.77.39.7−10%†—
48Albania—5.110.03.58.6−5%†—
49Cote d'Ivoire—1.6—2.41.8−12%†—
50Nauru—5.3—4.28.2−9%†—
51Djibouti—4.4—0.25.4−20%†—
52Palestine—3.5—4.88.7−14%†—
53Libya—6.8—3.18.0−10%*—
54Dominica—7.5—3.38.0−10%*—
55Guatemala—2.8—0.34.7−24%†—
56Saint Vincent—8.3—3.57.1−10%*—
57Burkina Faso—1.7—1.80.0−15%†—
58Sao Tome and Principe—3.4—0.04.5−19%†—
59Bahamas—8.3—6.89.6−10%*—
60Uruguay—6.8—7.09.5−18%†—
61Argentina—5.0—3.49.2−21%†—
62Tajikistan—4.2—5.24.0−13%†—
63Cambodia—3.2—2.15.9−10%*—
64Senegal—1.8—4.34.6−13%†—
65Indonesia—3.7—9.56.6−11%†—
66Haiti—2.3—0.02.8−19%†—
67Tanzania—1.9—0.00.2−19%†—
68Cameroon—1.8—0.02.5−21%†—
69Kazakhstan—7.3—10.09.8−5%†—
70Grenada—8.0—6.86.2−23%†—
71Kuwait—9.0—8.710.0−10%*—
72Burundi—3.0—0.00.0−15%†—
73Lebanon—6.2—1.67.8−13%†—
74Maldives—5.3—7.68.5−5%†—
75Kenya—2.7—0.00.8−16%†—
76Antigua and Barbuda—8.5—7.66.6−10%*—
77Zimbabwe—4.2—0.01.8−30%†—
78Somalia—0.0—0.00.0−10%*—
79Dominican Republic—5.2—1.39.4−17%†—
80Timor-Leste—3.0—0.00.8−4%†—
81Togo—1.2—0.01.5−15%†—
82Zambia—4.4—1.00.0−30%†—
83Malawi—2.2—0.00.0−16%†—
84Botswana—4.6—0.04.2−30%†—
85Afghanistan—1.2—0.00.0−10%*—
86Trinidad and Tobago—7.5—4.78.0−18%†—
87Guinea-Bissau—1.3—0.00.0−10%†—
88Vietnam—4.1—8.28.3−13%†—
89Benin—0.8—0.00.6−11%†—
90Cape Verde—4.1—3.76.9−21%†—
91Philippines—3.9—3.65.7−17%†—
92COM—3.7—0.00.4−6%†—
93GMB—2.3—0.03.0−17%†—
94Liberia—1.9—0.00.3−12%†—
95Kyrgyzstan—6.5—9.09.5−3%†—
96Malaysia—5.4—6.910.0−19%†—
97Jamaica—4.4—0.09.3−18%†—
98Russia—8.5—9.89.9−10%†—
99Sri Lanka—5.9—8.13.8−15%†—
100Laos—4.8—3.05.5−12%†—
101South Sudan—1.1—0.00.0−23%†—
102United Arab Emirates—9.0—9.710.0−2%†—
103Guyana—7.2—5.18.2−24%†—
104Mauritania—1.7—0.02.4−8%†—
105Egypt—4.1—4.06.9−4%†—
106Sierra Leone—1.8—0.00.0−13%†—
107Ukraine—6.1—3.68.1−1%†—
108Tonga—6.8—7.35.8−3%†—
109KIR—5.7—1.59.1−0%†—
110DR Congo—1.8—0.00.0−24%†—
111Samoa—4.8—6.50.0−16%†—
112Honduras—5.7—1.84.4−25%†—
113Moldova—6.1—5.27.3−2%†—
114Central African Republic—0.9—0.00.0−22%†—
115Singapore—9.7—8.49.9−10%*—
116Seychelles—8.3—7.48.9−9%†—
117Barbados—6.0—3.96.2−11%†—
118Brazil—5.4—7.68.4−30%†—
119Nigeria—1.7—0.01.7−11%†—
120Mauritius—6.0—3.96.7−14%†—
121Armenia—3.9—8.87.9−3%†—
122Angola—1.4—0.01.6−30%†—
123Madagascar—2.6—0.00.0−14%†—
124Iran—6.0—2.38.5−13%†—
125Georgia—4.1—4.98.3−11%†—
126Namibia—3.6—0.05.4−30%†—
127Suriname—6.3—3.08.8−17%†—
128Belize—4.6—0.97.7−18%†—
129Fiji—6.5—4.36.9−7%†—
130Papua New Guinea—0.3—0.00.0−20%†—
131South Africa—7.3—6.17.4−30%†—
132Tunisia—4.6—5.17.2−10%†—
133Pakistan—2.6—1.64.2−10%†—
134Chad—0.0—0.00.0−15%†—
135Nepal—2.8—2.82.5−6%†—
136Eswatini—4.2—0.05.1−30%†—
137Ghana—2.6—1.16.5−22%†—
138Uganda—2.4—0.00.0−21%†—
139Palau—7.5—4.68.3−10%*—
140El Salvador—6.8—0.95.6−18%†—
141Niger—0.9—0.00.0−9%†—
142Bosnia and Herzegovina—5.7—8.38.6−6%†—
143Vanuatu—3.5—5.60.0−9%†—
144Ethiopia—0.3—0.00.0−7%†—
145Ecuador—8.0—3.57.3−25%†—
146Algeria—6.7—6.87.3−3%†—
147Mali—1.1—6.11.1−13%†—
148Myanmar—2.2—3.62.4−7%†—
149Uzbekistan—8.2—5.39.2−9%†—
150Mongolia—4.0—9.48.5−8%†—
151Yemen—2.2—0.00.0−14%†—
152Azerbaijan—6.2—7.59.3−2%†—
153Saint Kitts and Nevis—8.3—6.07.2−10%*—
154Paraguay—4.9—5.07.9−23%†—
155Belarus—6.6—10.09.9−0%†—
156Thailand—6.8—9.39.4−10%†—
157Saint Lucia—5.6—5.85.9−22%†—
158Lesotho—2.5—0.03.4−24%†—
159Guinea—1.3——0.5−6%†—
160Eritrea—1.7——0.0−10%*—
161Bangladesh—2.4——3.6−7%†—
162Solomon Islands—2.8——0.0−15%†—
163Oman—7.2——10.0−10%*—
164Rwanda—2.9——0.3−17%†—
165Jordan—7.3——10.0−10%†—
166India—3.9——6.2−1%†—
167Turkmenistan—8.5——0.0−19%†—
168SMR—7.3——10.0−10%*—
169Micronesia—5.8——1.5−18%†—
170Sudan—3.0——0.0−11%†—
171Syria—6.7——0.6−2%†—
172Tuvalu—7.4——0.8−17%†—
173Bahrain—8.0——10.0−10%*—
174Congo—2.5——2.6−29%†—
175Bolivia—5.0——7.7−19%†—
176MHL—5.0——5.5−13%†—
177Cuba—9.3——6.2−10%*—
178PRK—7.8——0.0−10%*—
179Panama—5.6——6.6−30%†—
180Brunei—9.0——10.0−10%*—
181AND—7.4——9.9−10%*—
182Gabon—1.8——6.0−16%†—
183Equatorial Guinea—3.2——5.1−16%†—
184Bhutan—6.1——9.4−4%†—
185Qatar—9.0——10.0−12%†—
186Iraq—3.4——7.9−6%†—
187Nicaragua—6.7——4.8−25%†—
188China—5.5——9.5−13%†—
189Venezuela—7.5——7.2−24%†—
190MCO—9.2——10.0−10%*—
191Morocco—5.8——9.4−17%†—
192Mozambique—2.0——0.0−30%†—
193Saudi Arabia—8.8——10.0−10%*—
194XKX——6.7—9.2−16%†—
195EAS————9.0−10%*—
196ECS————9.6−10%*—
197LCN————8.3−10%*—
198SST————0.0−10%*—
199SSF————0.9−10%*—
200Hong Kong————10.0−10%*—
201LIE————10.0−10%*—
202Macao————9.2−10%*—
▶Methodology

What this measures

The Exit Cost Index measures how decommodified a country's basic resources are — how much of food, healthcare, housing, income, and basic connectivity can be obtained without selling labor on the market. It extends Esping-Andersen's classical decommodification framework with four additional axes and a sub-national dispersion modifier, reframing it from welfare-state generosity to individual freedom from compulsory work.

How is it calculated?

Each axis is normalized to a 0-10 score using fixed anchors (not rolling min-max), so year-over-year comparisons remain stable. The raw composite is a weighted average over present axes — income and healthcare must both be present, otherwise the composite is null. The final composite is the raw composite multiplied by (1 − dispersion penalty).

Income substitution (Weight 35%)

Imported from this site's Decommodification Index — OECD replacement-rate tier only (gold standard methodology). Non-OECD countries are not scored on this axis because the ILO coverage tier measures formal legal coverage rather than actual benefit value, which inflates rankings of countries with broad-but-stingy systems.

Healthcare independence (Weight 25%)

Two-component blend (60/40): WHO Universal Health Coverage Service Coverage Index (0-100, anchors 30→0 / 90→10) and WHO catastrophic financial hardship in health (SDG 3.8.2, % of population, anchors 0→10 / 20→0). Hardship data older than 2015 is treated as missing — for those countries the score uses UHC alone. The blend captures both 'are services available' and 'can people afford to use them without ruin', correcting cases like the US where coverage exists but employer-tied insurance leaves people one job loss away from catastrophe.

Housing decommodification (Weight 20%)

Two-component blend (50/50): OECD SOCX TP82 — public expenditure on housing as % of GDP (anchors 0% → 0 / 1.5% → 10), and Eurostat ilc_lvho07a — housing cost overburden rate (% of households spending >40% of disposable income on housing, anchors 2% → 10 / 30% → 0). When only one sub-component is available, that one is used directly. The blend addresses the Phase 2 limitation where countries that decommodify housing through regulation rather than fiscal spending (Norway, Sweden, Switzerland) were systematically understated.

Food security (Weight 10%)

FAO Prevalence of moderate or severe food insecurity (%, lower is better). Latest year per country. Anchors: 50% → 0, 2% → 10.

Digital & mobility access (Weight 10%)

World Bank IT.NET.USER.ZS — individuals using the internet (% of population). Latest year per country. Anchors: 30% → 0, 95% → 10. A coarse proxy for the broader 'mobility/digital' axis; future phases will add public-transport access and broadband affordability.

Sub-national dispersion penalty

Multiplicative penalty (0–30%) applied to the composite to account for inequality the national average hides — capital vs. periphery, top quintile vs. bottom.

Three-tier source hierarchy. (1) Regional CV — coefficient of variation of TL2 regional disposable income from OECD CFE.EDS (29 countries with sub-national data). Linear ramp: CV ≤ 0.05 → 0 penalty; CV ≥ 0.30 → 30% penalty. This is the direct measurement: how much does regional disposable income vary inside the country. (2) National Gini — World Bank SI.POV.GINI as proxy fallback when regional data is unavailable, marked with † in the table. Linear ramp: Gini ≤ 25 → 0 penalty; Gini ≥ 50 → 30% penalty. Income Gini and regional dispersion correlate but are not identical. (3) Neutral 10% fallback when neither source has data, marked with *.

Honest limitations

  • Income data comes from OECD replacement-rate methodology, so non-OECD countries don't receive a composite score. They are still shown per axis where data exists.
  • Catastrophic health spending observations older than 2015 are treated as missing rather than blended (Norway 1998, Sweden 1996 etc. don't reflect current reality). Those countries' healthcare scores use UHC service coverage alone.
  • The housing cost overburden sub-component comes from Eurostat and covers EU + EFTA + UK + Balkans only. Non-European OECD countries (US, Canada, Japan, Korea, Australia, NZ, Mexico, Chile, Israel) are scored on public housing spend (SOCX TP82) alone. Future phases will add OECD AHD HC2.1 once it is exposed via SDMX.
  • Regional dispersion uses TL2 (sub-national level 2) disposable income from OECD CFE.EDS, available for 29 countries. The remaining 140+ countries fall back to national Gini, which captures income inequality but not strict geographic dispersion. Both signals are correlated; the marker (†) makes the source explicit.
  • Per-country drilldown into TL2 regions (US states, EU NUTS2, Russia oblasts, India states, Brazil estados) is reserved for a future phase. The dispersion penalty is a single number; the underlying regional variance is not yet visible in the dashboard.

Data sources

Intellectual lineage

This index extends the academic tradition of Gøsta Esping-Andersen (Three Worlds of Welfare Capitalism, 1990) and Lyle Scruggs's Welfare Generosity Index (2006+), reframing decommodification as 'exit cost' from individual rather than institutional perspective, broadening the measurement to non-cash dimensions (healthcare, housing, food, digital access), and adding a sub-national dispersion modifier. It is not a novel invention; it is a modern recombination of well-established sources.