I ran into something rather puzzling when I was looking into some of the things that determine the success or failure of countries. I know Fukuyama did a whole book on the subject, but it was not especially satisfying. It seemed to back into its conclusions without offering much empirical support.
I do think that Fukuyama was onto something, though. There is a paper, available online, by Bo Rothstein that approaches issues of trust from the direction of game theory. Start with the famous “prisoner’s dilemma,” in which two prisoners are being interrogated separately. If both remain silent, there will not be enough evidence to convict either, and they will both go free. However, the one who confesses first will receive a light sentence and the other will bear the greater punishment. This problem has two equilibrium points: one confesses and takes the intermediate reward (or less punishment), or neither confesses and both collect the reward of going free. In essence, countries can reach several equilibrium points in how the citizens of each country treat each other. Rothstein points out that we often act against our rational self-interest. For example, we refrain from stealing even when there is no chance of being detected. We will even give up some value for the opportunity to punish someone who we feel has cheated us, which makes no monetary sense. If we expect that we will be cheated, however, we will take the opportunity to cheat ourselves. We can reach a stable equilibrium of either trusting and acting on trust, or mistrusting and acting on that mistrust.
Measuring trust is not an easy thing, so I chose a close substitute. I figured that the index of perceived corruption by Transparency International was a reasonable estimate of trustworthiness. This assumes that the perception is accurate, and gives an idea of the degree of trust in that society. In Transparency’s corruption index, 10 is angelic and anything below 5 indicates a problem. As a measure of prosperity, I used per capita GDP, according to the CIA Factbook.
The correlation? 90%! You can’t get a much tighter correlation in real life.
The figures and more thoughts are on the jump page.
The correlation with GDP growth was very weak: only about 20%. My guess is that GDP per capita represents growth over a long period, while the only figures for GDP growth in common circulation were for either one year or a very short period. Places like Iraq and Afghanistan show tremendous GDP growth, having been nearly destroyed over the past 20 years. India and China also show great growth, but relatively high corruption. I would be very surprised to see them sustain both high rates over the long term.
One possible mechanism by which corruption and lack of trust can destroy wealth is by considering transaction costs. If you are likely to be shaken down by a corrupt cop on your way to work, your cost of commuting includes more than just the mileage on your car. The cost you pay to avoid being cheated, or to bribe an official to receive an ordinary service, makes other locations cheaper and more attractive in comparison.
Country | Corruption | GDP |
Afghanistan | 2.5 | 700 |
Albania | 2.4 | 4500 |
Algeria | 2.8 | 5900 |
Angola | 2 | 1900 |
Argentina | 2.8 | 11200 |
Armenia | 2.9 | 3900 |
Australia | 8.8 | 28900 |
Austria | 8.7 | 30000 |
Azerbaijan | 2.2 | 3400 |
Bahrain | 5.8 | 17100 |
Bangladesh | 1.7 | 1900 |
Barbados | 6.9 | 16200 |
Belarus | 2.6 | 6000 |
Belgium | 7.4 | 29000 |
Belize | 3.7 | 4900 |
Benin | 2.9 | 1100 |
Bolivia | 2.5 | 2400 |
Bosnia and Herzegovina | 2.9 | 6100 |
Botswana | 5.9 | 8800 |
Brazil | 3.7 | 7600 |
Bulgaria | 4 | 7600 |
Burkina Faso | 3.4 | 1100 |
Burundi | 2.3 | 600 |
Cambodia | 2.3 | 1700 |
Cameroon | 2.2 | 1800 |
Canada | 8.4 | 29700 |
Chad | 1.7 | 1200 |
Chile | 7.3 | 9900 |
China | 3.2 | 5000 |
Colombia | 4 | 6300 |
Congo, Democratic Republic of the | 2.1 | 600 |
Congo, Republic of | 2.3 | 700 |
Costa Rica | 4.2 | 9000 |
Côte d’Ivoire | 1.9 | 1400 |
Croatia | 3.4 | 10700 |
Cuba | 3.8 | 2800 |
Czech Republic | 4.3 | 15700 |
Denmark | 9.5 | 31200 |
Dominican Republic | 3 | 6000 |
Ecuador | 2.5 | 3300 |
Egypt | 3.4 | 3900 |
El Salvador | 4.2 | 4800 |
Equatorial Guinea | 1.9 | 2700 |
Eritrea | 2.6 | 700 |
Estonia | 6.4 | 12300 |
Ethiopia | 2.2 | 700 |
Fiji | 4 | 5800 |
Finland | 9.6 | 27300 |
France | 7.5 | 27500 |
Gabon | 2.9 | 5500 |
Gambia | 2.7 | 1700 |
Georgia | 2.3 | 2500 |
Germany | 8.2 | 27600 |
Ghana | 3.5 | 2200 |
Greece | 4.3 | 19900 |
Guatemala | 2.5 | 4100 |
Guyana | 2.5 | 4000 |
Haiti | 1.8 | 1600 |
Honduras | 2.6 | 2600 |
Hong Kong | 8.3 | 28700 |
Hungary | 5 | 13900 |
Iceland | 9.7 | 30900 |
India | 2.9 | 2900 |
Indonesia | 2.2 | 3200 |
Iran | 2.9 | 7000 |
Iraq | 2.2 | 1600 |
Ireland | 7.4 | 29800 |
Israel | 6.3 | 19700 |
Italy | 5 | 26800 |
Jamaica | 3.6 | 3800 |
Japan | 7.3 | 28000 |
Jordan | 5.7 | 4300 |
Kazakhstan | 2.6 | 7000 |
Kenya | 2.1 | 1000 |
Korea, South | 5 | 17700 |
Kuwait | 4.7 | 18100 |
Kyrgyzstan | 2.3 | 1600 |
Laos | 3.3 | 1700 |
Latvia | 4.2 | 10100 |
Lebanon | 3.1 | 4800 |
Lesotho | 3.4 | 3000 |
Liberia | 2.2 | 1000 |
Libya | 2.5 | 6400 |
Lithuania | 4.8 | 11200 |
Luxembourg | 8.5 | 55100 |
Macedonia | 2.7 | 6700 |
Madagascar | 2.8 | 800 |
Malawi | 2.8 | 600 |
Malaysia | 5.1 | 9000 |
Mali | 2.9 | 900 |
Malta | 6.6 | 17700 |
Mauritius | 4.2 | 11400 |
Mexico | 3.5 | 9000 |
Moldova | 2.9 | 1800 |
Mongolia | 3 | 1800 |
Morocco | 3.2 | 4000 |
Mozambique | 2.8 | 1200 |
Myanmar | 1.8 | 1900 |
Namibia | 4.3 | 7100 |
Nepal | 2.5 | 1400 |
Netherlands | 8.6 | 28600 |
New Zealand | 9.6 | 21600 |
Nicaragua | 2.6 | 2200 |
Niger | 2.4 | 800 |
Nigeria | 1.9 | 800 |
Norway | 8.9 | 37700 |
Oman | 6.3 | 13400 |
Pakistan | 2.1 | 2100 |
Panama | 3.5 | 6300 |
Papua New Guinea | 2.3 | 2200 |
Paraguay | 2.1 | 4600 |
Peru | 3.5 | 5200 |
Philippines | 2.5 | 4600 |
Poland | 3.4 | 11000 |
Portugal | 6.5 | 18000 |
Qatar | 5.9 | 21500 |
Romania | 3 | 6900 |
Russia | 2.4 | 8900 |
Rwanda | 3.1 | 1300 |
Saudi Arabia | 3.4 | 11800 |
Senegal | 3.2 | 1600 |
Serbia and Montenegro | 2.8 | 2300 |
Seychelles | 4 | 7800 |
Sierra Leone | 2.4 | 500 |
Singapore | 9.4 | 23700 |
Slovakia | 4.3 | 13300 |
Slovenia | 6.1 | 18300 |
Somalia | 2.1 | 500 |
South Africa | 4.5 | 10700 |
Spain | 7 | 22000 |
Sri Lanka | 3.2 | 3700 |
Sudan | 2.1 | 1900 |
Suriname | 3.2 | 3500 |
Swaziland | 2.7 | 4900 |
Sweden | 9.2 | 26800 |
Switzerland | 9.1 | 32800 |
Syria | 3.4 | 3300 |
Taiwan | 5.9 | 23400 |
Tajikistan | 2.1 | 1000 |
Tanzania | 2.9 | 600 |
Thailand | 3.8 | 7400 |
Trinidad and Tobago | 3.8 | 9600 |
Tunisia | 4.9 | 6900 |
Turkey | 3.5 | 6700 |
Turkmenistan | 1.8 | 5700 |
Uganda | 2.5 | 1400 |
Ukraine | 2.6 | 5300 |
United Arab Emirates | 6.2 | 23200 |
United Kingdom | 8.6 | 27700 |
United States | 7.6 | 37800 |
Uruguay | 5.9 | 12600 |
Uzbekistan | 2.2 | 1700 |
Venezuela | 2.3 | 4800 |
Vietnam | 2.6 | 2500 |
Yemen | 2.7 | 800 |
Zambia | 2.6 | 800 |
Zimbabwe | 2.6 | 1900 |
Awesome correlation. Note also the success of the Tit for Tat strategy in the iterated prisoners dilemma – a strategy which mirrors ethical behaviour.
It’s hard to say which way the cause and effect works here, but I do believe that a citizenry with virtues such as honesty, civic mindedness, are essential for an economically successful democratic society.
If you took out the countries that are wealthy solely from resource extraction, like Saudi Arabia, I suspect the correlation would be even higher.
Yes, Lex, and quoting GDP per person for Saudi Arabia is a little -er- optimistic. What does the income distribution look like? Hardly “normal”.
There is a measure of income inequality called the GINI index. You can represent absolute income equality with a straight line from zero going up at a 45 degree angle, so that 5% of the population has 5% of the wealth, 50% has 50%, etc. The GINI index represents the amount of “sag” that the real income distribution curve displays when the bottom 50% of the population receives less than 50% of the income.
I’ve played with GINI a little, too, and may have something to say about what else it implies. Wouldn’t ya know it, though – our friends the Saudis don’t show up on the list. I suspect they like to keep that kind of information within the family. Kuwait is missing, too.
The primary source for the data going into the GINI calculation is income taxes. This may be unreliable or missing.