Differences in the degree of industrial development amongst countries are measured using six scales:
I1ij is the difference between countries i & j in US$ GDP per capita ,
I2ij is the difference between countries i & j in energy consumption (equivalent kg coal pc) ,
I4ij is the difference between countries i & j in the % non-agricultural labour ,
I6ij is the difference between countries i & j in the % urban population ,
I9ij is the difference between countries i & j in the number of telephones (fixed and mobile) per 100 people , and
I11ij is the difference between countries i & j in the proportion of the % of the population who use the internet.
Note that, as one can see from the variable labels, there were five other indicators of industrial development at one time.
- Right from the very beginning I5ij – the % of GDP in manufacturing had a very low factor loading and was never included in our scales.
- Indicators I3ij – the number of cars per 1,000 people; I7ij – the number of newspapers per 1,000 people; I8ij – the number of radios per 1,000 people; and I10ij – the number of televisions per 1,000 people were all included in the initial version of my scales; however, they have been dropped in the 2020 revision. This was primarily because multiple nations ceased collecting the data in a consistent and systematic manner.
The scores for each of the six indicators in use, 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 n-1 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 2006 paper, the absolute value of the industrial development dimension is the appropriate form if you are using it as an indicator of psychic distance.
INDUSTRIAL DEVELOPMENT INDICATOR CALCULATIONS
I1ij = (I1i – I1j)
Where, I1i = GDP per capita ($US) for the exporting country (i)
and, I1j = GDP per capita ($US) for the importing country (j)
I2ij = (I2i – I2j)
Where, I2i = Energy consumption per capita (kg of coal equivalent) for the exporting country (i)
and, I2j = Energy consumption per capita (kg of coal equivalent) for the importing country (j)
I4ij = (I4i – I4j)
Where, I4i = 100- % of labour force in agriculture for the exporting country (i)
and, I4j = 100 – % of labour force in agriculture for the importing country (j)
I6ij = (I6i – I6j)
Where, I6i = % of population living in urban areas for the exporting country (i)
and, I6j = % of population living in urban areas for the importing country (j)
I9ij = (I9i – I9j)
Where, I9i = telephones (fixed and mobile) per 100 people for the exporting country (i)
and, I9j = telephones (fixed and mobile) per 100 people for the importing country (j)
I11ij = (I11i – I11j)
Where, I11i = % of people who use the internet in the exporting country (i)
and, I11j = % of people who use the internet in the importing country (j)
Ind Dev F – is the single-factor solution, using principal component analysis, for I1ij, I2ij, I4ij, I6ij, I9ij, and I11ij
Ind Dev F(abs) = absolute value of Ind Dev F
Ind Dist – is Ind Dev F (abs) re-scaled such that ‘no differences’ equals zero (0), and the maximum value equals ten (10)
The preceding six 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.
|Ind f – 6 item factor score for differences in industrial development||0.916|
|I1ij – Difference in GDP per capita||0.848|
|I2ij – Difference in energy consumption per capita||0.767|
|I4ij– Difference in % non-agricultural labour||0.855|
|I6ij – Difference in % urban||0.835|
|I9ij – Difference in phones per 100 people||0.880|
| I11ij – Difference in internet usage
The primary source for the industrial development data is :
- World Bank DataBank – World Development Indicators, [www document] https//datbank.worldbank.org/source/world-development-indicators# (accessed 27 March 2018).
For the six Industrial Development metrics, missing data represents 3.2% of the cells. In most cases, given the confirmatory nature of the items, the missing items was estimated via a multivariate regression of the other industrial development items in the same time period. However, in the case of Taiwan there was minimal industrial development data available via our primary source – World Development Indicators. In this case, the Industrial Development items were estimated using data from the CIA Fact Book and directly from the websites managed by the Taiwanese government.