2015
Statistics
State Capacity Index
Composite measure of a government's ability to implement policies, collect taxes, enforce laws, and provide public services. Higher values indicate greater state effectiveness and institutional quality.
Interactive Trend
State Capacity Index
State Capacity Index
Source: EuropeVersus.com • Our World in Data
Display Mode
Year Range
→
Filter
Select Countries
4 selected
Aggregates
Global
Eurozone
Non-Euro EU
Non-EU Europe
Regional Comparison
🇪🇺
Europe
2015
1.48
🇪🇺
EU-27
2015
1.81
🇺🇸
USA
2015
1.86
🇮🇳
India
2015
0.77
🇨🇳
China
2015
0.71
Historical Data
| Year | 🇩🇪 Germany | 🇫🇷 France | 🇮🇹 Italy | 🇪🇸 Spain | 🇳🇱 Netherlands | 🇧🇪 Belgium | 🇦🇹 Austria | 🇮🇪 Ireland | 🇵🇹 Portugal | 🇬🇷 Greece | 🇫🇮 Finland | 🇸🇰 Slovakia | 🇸🇮 Slovenia | 🇪🇪 Estonia | 🇱🇻 Latvia | 🇱🇹 Lithuania | 🇱🇺 Luxembourg | 🇲🇹 Malta | 🇨🇾 Cyprus | 🇭🇷 Croatia | 🇵🇱 Poland | 🇸🇪 Sweden | 🇩🇰 Denmark | 🇨🇿 Czechia | 🇭🇺 Hungary | 🇷🇴 Romania | 🇧🇬 Bulgaria | 🇨🇭 Switzerland | 🇳🇴 Norway | 🇬🇧 UK | 🇮🇸 Iceland | 🇱🇮 Liechtenstein | 🇲🇨 Monaco | 🇦🇩 Andorra | 🇸🇲 San Marino | 🇻🇦 Vatican | 🇺🇦 Ukraine | 🇧🇾 Belarus | 🇲🇩 Moldova | 🇷🇺 Russia | 🇦🇱 Albania | 🇧🇦 Bosnia & Herzegovina | 🇷🇸 Serbia | 🇲🇪 Montenegro | 🇲🇰 North Macedonia | 🇽🇰 Kosovo | 🇬🇪 Georgia | 🇦🇲 Armenia | 🇦🇿 Azerbaijan | 🇹🇷 Turkey | 🇪🇺 Europe | 🇪🇺 EU-27 | 🇪🇺 Core EU | 💶 Eurozone (Agg) | 🇪🇺 Non-€ EU (Agg) | 🌍 Non-EU Eur (Agg) | 🇺🇸 USA | 🇨🇳 China | 🇮🇳 India |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2015 | 2.3 | 1.6 | 1.5 | 2.0 | 2.2 | 2.4 | 2.5 | 2.0 | 1.8 | 1.4 | 2.3 | 1.4 | 1.6 | 1.7 | 1.5 | 1.5 | — | — | 0.9 | 1.4 | 1.4 | 2.4 | 2.7 | 1.6 | 1.5 | 1.0 | 1.2 | 2.3 | 2.5 | 1.8 | — | — | — | — | — | — | 0.3 | 0.9 | 0.6 | 0.7 | 0.6 | 0.3 | 0.9 | 1.0 | 0.7 | — | 0.9 | 1.1 | 0.1 | 1.0 | 1.5 | 1.8 | 1.9 | 1.9 | 1.5 | 1.9 | 1.9 | 0.7 | 0.8 |
| 2014 | 2.1 | 1.7 | 1.4 | 2.0 | 2.3 | 2.5 | 2.5 | 2.1 | 1.8 | 1.4 | 2.4 | 1.3 | 1.6 | 1.7 | 1.5 | 1.5 | — | — | 1.2 | 1.4 | 1.4 | 2.6 | 3.0 | 1.6 | 1.5 | 1.1 | 1.2 | 2.4 | 2.6 | 1.8 | — | — | — | — | — | — | 0.5 | 1.0 | 0.6 | 0.6 | 0.6 | 0.4 | 0.9 | 1.1 | 0.7 | — | 0.8 | 1.0 | 0.1 | 1.1 | 1.5 | 1.8 | 1.9 | 1.9 | 1.5 | 1.9 | 1.9 | 0.7 | 0.8 |
| 2013 | 2.1 | 1.7 | 1.5 | 2.0 | 2.3 | 2.5 | 2.5 | 2.1 | 1.8 | 1.4 | 2.4 | 1.4 | 1.6 | 1.7 | 1.5 | 1.4 | — | — | 1.2 | 1.5 | 1.4 | 2.5 | 2.9 | 1.5 | 1.6 | 1.1 | 1.2 | 2.4 | 2.7 | 1.8 | — | — | — | — | — | — | 0.9 | 0.9 | 0.6 | 0.6 | 0.5 | 0.3 | 0.9 | 1.0 | 0.6 | — | 1.0 | 0.9 | 0.2 | 1.3 | 1.5 | 1.8 | 1.9 | 1.9 | 1.6 | 1.9 | 1.9 | 0.7 | 0.7 |
| 2012 | 2.3 | 1.7 | 1.5 | 2.0 | 2.4 | 2.4 | 2.4 | 2.1 | 1.7 | 1.4 | 2.5 | 1.4 | 1.5 | 1.6 | 1.4 | 1.4 | — | — | 1.2 | 1.5 | 1.4 | 2.6 | 3.0 | 1.6 | 1.5 | 1.1 | 1.4 | 2.5 | 2.6 | 1.8 | — | — | — | — | — | — | 0.9 | 0.9 | 0.6 | 0.7 | 0.5 | 0.4 | 0.9 | 0.9 | 0.7 | 0.1 | 1.0 | 0.8 | 0.1 | 1.3 | 1.5 | 1.8 | 1.9 | 1.9 | 1.6 | 1.9 | 1.9 | 0.7 | 0.8 |
| 2011 | 2.3 | 1.7 | 1.5 | 2.0 | 2.4 | 2.5 | 2.3 | 2.1 | 1.7 | 1.5 | 2.5 | 1.4 | 1.6 | 1.5 | 1.4 | 1.4 | — | — | 1.2 | 1.4 | 1.4 | 2.6 | 2.9 | 1.5 | 1.5 | 1.2 | 1.3 | 2.5 | 2.6 | 1.9 | — | — | — | — | — | — | 0.8 | 0.9 | 0.4 | 0.9 | 0.5 | 0.2 | 0.8 | 0.9 | 0.7 | 0.0 | 0.9 | 0.9 | 0.1 | 1.3 | 1.6 | 1.8 | 1.9 | 1.9 | 1.6 | 2.0 | 1.9 | 0.7 | 0.8 |
| 2010 | 2.0 | 1.7 | 1.5 | 1.8 | 2.4 | 2.4 | 2.3 | 1.8 | 1.7 | 1.5 | 2.5 | 1.4 | 1.6 | 1.5 | 1.3 | 1.3 | — | — | 1.2 | 1.4 | 1.5 | 2.3 | 3.0 | 1.5 | 1.6 | 1.2 | 1.3 | 2.5 | 2.7 | 1.9 | — | — | — | — | — | — | 0.8 | 1.0 | 0.4 | 0.8 | 0.5 | 0.2 | 0.7 | 0.7 | 0.7 | — | 0.9 | 0.9 | 0.1 | 1.4 | 1.5 | 1.8 | 1.8 | 1.8 | 1.6 | 2.0 | 1.9 | 0.7 | 0.7 |
| 2009 | 1.9 | 1.7 | 1.5 | 1.9 | 2.4 | 2.5 | 2.3 | 2.1 | 1.7 | 1.6 | 2.5 | 1.4 | 1.7 | 1.6 | 1.2 | 1.4 | — | — | 1.2 | 1.5 | 1.5 | 2.3 | 3.0 | 1.6 | 1.6 | 1.2 | 1.3 | 2.2 | 2.6 | 1.8 | — | — | — | — | — | — | 0.7 | 0.9 | 0.4 | 0.8 | 0.6 | 0.1 | 0.8 | 0.7 | 0.6 | — | 0.8 | 0.9 | 0.1 | 1.4 | 1.5 | 1.8 | 1.8 | 1.8 | 1.6 | 1.9 | 1.9 | 0.7 | 0.7 |
| 2008 | 1.9 | 1.7 | 1.5 | 1.9 | 2.4 | 2.5 | 2.4 | 2.1 | 1.7 | 1.5 | 2.5 | 1.4 | 1.7 | 1.6 | 1.4 | 1.5 | — | — | 1.2 | 1.5 | 1.5 | 2.3 | 2.9 | 1.6 | 1.7 | 1.2 | 1.5 | 2.2 | 2.6 | 1.9 | — | — | — | — | — | — | 0.7 | 1.0 | 0.5 | 0.8 | 0.5 | 0.1 | 0.7 | 0.7 | 0.8 | — | 0.9 | 0.9 | 0.2 | 1.4 | 1.5 | 1.8 | 1.8 | 1.8 | 1.6 | 2.0 | 2.0 | 0.7 | 0.8 |
| 2007 | 1.9 | 1.8 | 1.5 | 2.0 | 2.4 | 2.3 | 2.4 | 2.1 | 1.7 | 1.5 | 2.6 | 1.4 | 1.7 | 1.6 | 1.4 | 1.5 | — | — | 1.3 | 1.5 | 1.5 | 2.4 | 2.9 | 1.6 | 1.7 | 1.2 | 1.5 | 2.1 | 2.7 | 1.9 | — | — | — | — | — | — | 0.6 | 1.0 | 0.4 | 0.8 | 0.5 | 0.1 | 0.6 | 0.5 | 0.6 | — | 0.7 | 0.9 | 0.1 | 1.4 | 1.5 | 1.8 | 1.8 | 1.8 | 1.6 | 2.0 | 2.0 | 0.6 | 0.8 |
| 2006 | 1.9 | 1.8 | 1.4 | 1.9 | 2.4 | 2.3 | 2.3 | 2.1 | 1.7 | 1.5 | 2.6 | 1.4 | 1.7 | 1.5 | 1.4 | 1.5 | — | — | 1.2 | 1.5 | 1.4 | 2.4 | 2.9 | 1.6 | 1.6 | 1.2 | 1.5 | 2.1 | 2.7 | 1.9 | — | — | — | — | — | — | 0.6 | 1.0 | 0.3 | 0.7 | 0.5 | 0.2 | 0.4 | 0.3 | 0.6 | — | 0.5 | 0.8 | 0.1 | 1.2 | 1.5 | 1.8 | 1.8 | 1.8 | 1.6 | 2.0 | 2.0 | 0.6 | 0.8 |
| 2005 | 1.9 | 1.8 | 1.4 | 1.9 | 2.4 | 2.4 | 2.2 | 2.1 | 1.7 | 1.5 | 2.6 | 1.4 | 1.6 | 1.5 | 1.3 | 1.4 | — | — | 1.1 | 1.6 | 1.4 | 2.4 | 2.9 | 1.6 | 1.8 | 1.1 | 1.4 | 2.1 | 2.7 | 1.9 | — | — | — | — | — | — | 0.5 | 0.9 | 0.4 | 0.9 | 0.4 | — | — | — | 0.7 | — | 0.6 | 0.7 | 0.2 | 1.2 | 1.5 | 1.7 | 1.8 | 1.8 | 1.6 | 1.9 | 2.0 | 0.7 | 0.8 |
| 2004 | 1.8 | 1.8 | 1.4 | 1.9 | 2.4 | 2.4 | 2.2 | 2.1 | 1.7 | 1.3 | 2.5 | 1.4 | 1.6 | 1.5 | 1.3 | 1.4 | — | — | 1.1 | 1.6 | 1.3 | 2.3 | 2.9 | 1.6 | 1.8 | 1.1 | 1.5 | 2.1 | 2.7 | 1.9 | — | — | — | — | — | — | 0.5 | 0.8 | 0.3 | 0.7 | 0.3 | — | — | — | 0.6 | — | 0.2 | 0.6 | 0.2 | 1.2 | 1.4 | 1.7 | 1.8 | 1.8 | 1.5 | 2.0 | 1.8 | 0.6 | 0.7 |
| 2003 | 1.8 | 1.8 | 1.3 | 1.9 | 2.4 | 2.4 | 2.2 | 2.1 | 1.7 | 1.3 | 2.5 | 1.4 | 1.5 | 1.5 | 1.2 | 1.3 | — | — | 1.1 | 1.4 | 1.3 | 2.3 | 2.8 | 1.5 | 1.9 | 0.9 | 1.5 | 2.1 | 2.6 | 1.9 | — | — | — | — | — | — | 0.6 | 0.8 | 0.2 | 0.7 | 0.1 | — | — | — | 0.6 | — | — | 0.5 | — | 1.2 | 1.4 | 1.7 | 1.7 | 1.7 | 1.5 | 2.0 | 1.8 | 0.8 | 0.7 |
| 2002 | 1.8 | 1.8 | 1.4 | 1.8 | 2.4 | 2.4 | 2.2 | 2.0 | 1.7 | 1.3 | 2.5 | 1.4 | 1.5 | 1.4 | 1.2 | 1.3 | — | — | 1.1 | 1.5 | 1.3 | 2.3 | 2.8 | 1.5 | 1.9 | 0.9 | 1.5 | 2.2 | 2.6 | 1.9 | — | — | — | — | — | — | 0.6 | 0.7 | 0.1 | 0.6 | — | 0.0 | — | — | 0.6 | — | — | 0.5 | — | 1.2 | 1.4 | 1.7 | 1.8 | 1.8 | 1.5 | 2.0 | 1.9 | 0.7 | 0.5 |
| 2001 | 1.8 | 1.9 | 1.7 | 1.8 | 2.4 | 2.4 | 2.0 | 2.0 | 1.7 | 1.3 | 2.4 | 1.4 | 1.5 | 1.4 | 1.1 | 1.3 | — | — | 1.1 | 1.4 | 1.2 | 2.4 | 2.8 | 1.5 | 1.8 | 0.9 | 1.5 | 2.2 | 2.6 | 1.9 | — | — | — | — | — | — | 0.5 | 0.7 | 0.1 | 0.4 | — | — | — | — | 0.3 | — | — | 0.4 | — | 1.0 | 1.4 | 1.7 | 1.9 | 1.8 | 1.4 | 2.0 | 2.0 | 0.6 | 0.5 |
* = Incomplete data (<70% population coverage) - some countries using forward-filled values from previous years
Showing latest 15 years. Total data spans 16 years
(2000 – 2015)
Visual Comparison
🇪🇺 Europe
1.48
79.6%
🇺🇸 USA
1.86
100.0%
🇮🇳 India
0.77
41.4%
🇨🇳 China
0.71
38.2%
Key Insights
EUR vs USA
-20.4%
EUR vs IND
+92.2%
EUR vs CHN
+108.5%
Best Performer
USA
HOW EUROPE
IS DEFINED
Transparent, population-weighted calculations for fair comparisons
01
Europe
Includes all 50 European countries:
- — 27 EU member states: Germany, France, Italy, etc.
- — Other European: UK, Switzerland, Norway, etc.
02
Simple Sum
Used for absolute totals across all countries:
- — Step 1: Collect metric for each country
- — Step 2: Add all values together
- — Examples: Total population, total GDP
03
Population-Weighted
Used for per-capita metrics to reflect population size:
- — Step 1: Metric × population per country
- — Step 2: Sum all weighted values
- — Step 3: Divide by total population
Example: GDP/Capita PPP
$48,942
2024
Source
Our World in Data