Differences in the education levels amongst countries are measured using three scales:
E_{1ij} is the difference between countries i & j in the % of literate adults ,
E_{2ij} is the difference between countries i & j in the proportion of the population enrolled in 2nd level education – adjusting for the age profile of the country,
E_{3ij} is the difference between countries i & j in the proportion of population enrolled in 3rd level education – adjusting for the age profile of the country,
The scores for each of the three indicators, and the resultant factors (see below concerning the confirmatory factor analysis), can be found in an Excel spreadsheet attached at the bottom of this page. This spreadsheet contains the values for 22,350 country pairs (i.e. n x n1 for 150 countries) for three specific time periods (1995, 2005 and 2015). The precise coding for these variables is explained below. Please note that in accordance with the arguments and analyses presented in our JIBS paper, the absolute value of the education dimension is the appropriate form if you are using it as an indicator of psychic distance.
EDUCATION INDICATOR CALCULATIONS
E_{1ij} = (E_{1i }– E_{1j})
Where, E_{1i} = 100 – % of illiterate adults (15+, male & female) for the exporting country (i)
And, E_{1j} = 100 – % of illiterate adults (15+, male & female) for the importing country (j)
E_{2ij} = (E_{2i }– E_{2j})
Where, E_{2i} = # of students in 2^{nd} level education / estimated population under the age of 15 for the exporting country (i)
And, E_{2j} = # of students in 2^{nd} level education / estimated population under the age of 15 for the importing country (j)
E_{3ij} = (E_{3i }– E_{3j})
Where, E_{3i} = # of students in 3^{rd} level education / estimated population under the age of 15 for the exporting country (i)
And, E_{3j} = # of students in 3^{rd} level education / estimated population under the age of 15 for the importing country (j)
Edu ^{F} – is the singlefactor solution, using principal component analysis, for E_{1ij}, E_{2ij} and E_{3ij}
Edu ^{F} (abs) = absolute value of Edu ^{F}
Edu Dist – is Edu ^{F} (abs) rescaled such that ‘no difference’ equals zero (0), and the maximum value equals ten (10)
Edu ^{f}– Difference in Education Factor:
The preceding three indicators have be reduced to a single factor using confirmatory factor analysis (cfa). This factor score has been estimated using the full set of country pairs (22,350) and time periods (3). The individual factor loadings and the Cronbach alpha are reported below.
Cronbach Alpha 
Factor Loading 

Edu^{ f }– 3 item factor score for differences in education  0.884  
E_{1ij} – Difference in literacy  0.895  
E_{2ij} – Difference in % in 2nd level education  0.915  
E_{3ij} – Difference in % in 3rd level education  0.893 
SOURCES
The primary source for the education data is :


 World Bank DataBank – World Development Indicators, [www document] https//datbank.worldbank.org/source/worlddevelopmentindicators# (accessed 27 March 2018).

MISSING DATA
For the three education metrics, missing data represents 5.6% of the cells. In most instances, given the confirmatory nature of the items, the missing item was estimated via a multivariate regression of the other education items in the same time period. However, in the case of Somalia in 2015, there was minimal education data available via our primary source – World Development Indicators. In this case, the education items were estimated using data from several of the industrial development items which are correlated with education.