I suggested in a post last week that institutions could be considered as technologies based on people. They may inherit some of the properties of technologies, and so today I considered whether institutions in one country tend to affect the institutions in other countries and whether the effect is altered by the distance between the countries. I examined a single institution, a country's gender equality, measured by the GEM indicator from the United Nations described here (in a 5.5 MB pdf document on pages one and six).
The equation I looked at was
where the suffixes denote the value of the quantity in country i or c. denotes the distance between country i and country c. The population multiplier allows for greater effects from larger countries.
The GEM indicator is available here. The distance data is from here, and is in the form of population weighted distances between two countries including internal distances (in tens of thousands of kilometres). Population (in tens of millions) and gdp per capita (in thousands of current PPP US dollars) is from UN sources here.
A cross section of countries was considered for the year 2007: Argentina, Australia, Austria, Bangladesh, Belgium, Belize, Botswana, Brazil, Bulgaria, Cambodia, Canada, Chile, China, Colombia, Costa Rica, Croatia, Czech Republic, Denmark, Dominican Republic, Ecuador, Egypt, El Salvador, Estonia, Ethiopia, Finland, France, Georgia, Germany, Greece, Honduras, Hungary, Iceland, Iran (Islamic Republic of), Ireland, Italy, Japan, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Malaysia, Mauritius, Mexico, Mongolia, Morocco, Namibia, Nepal, Netherlands, New Zealand, Norway, Pakistan, Panama, Paraguay, Peru, Philippines, Poland, Portugal, Russian Federation, Saint Lucia, Singapore, Slovakia, Slovenia, Spain, Sri Lanka, Sweden, Switzerland, Thailand, The former Yugoslav Republic of Macedonia, Trinidad and Tobago, Turkey, Ukraine, United Republic of Tanzania, Uruguay, Viet Nam, and Yemen. Estimation was by non-linear least squares with bootstrapped standard errors.
The results are shown in the table. P values are in brackets.
The first specification finds that a country's gender equality is positively linked with other countries' gender equality, with the link diminishing with distance. The geographic localisation is quite strong; the chi parameter implies that the effect of a country's GEM on another country's GEM halves over 320 kilometres. The sharpness of the decline suggests that interpersonal movements may be important in the link.
When GDP per capita is introduced as a control in the second specification, the intercountry link becomes highly insignificant. In specification three with only GDP per capita as an explanatory variable, the R2 is almost the same as in specification two, indicating that the effect of intercountry links are substantially captured by GDP per capita. The explanatory power of the regressions involving GDP per capita are also far higher than for the regression involving only the intercountry links. The evidence supports gender empowerment as being much more directly linked to internal GDP per capita than external spillovers. I have not attempted to find the direction of causality in any links between intercountry spillovers, GDP per capita, and gender empowerment.
As an application, a very gender equal country is unlikely to have a major influence on regional equality except insofar as it boosts income in its neighbours. It would be interesting to see whether other institutions such as democracy are determined far more by internal conditions than external spillovers.