Differences in Industrial Development

Differences in the degree of industrial development amongst countries are measured using nine scales:

I1ij   is the difference in US$ GDP per capita between countries i & j,

I2ij   is the difference in energy consumption (equivalent kg coal pc) between countries i & j,

I3ij   is the difference in the number of cars per 1,000 people between countries i & j,

I4ij   is the difference in the % non-agricultural labour between countries i & j,

I6ij   is the difference in the % urban population between countries i & j,

I7ij   is the difference in the # of daily newspapers per 1,000 people between countries i & j,

I8ij   is the difference in the number of radios per 1,000 people between countries i & j,

I9ij   is the difference in the number of telephones per 100 people between countries i & j, and

I10ij  is the difference in the number of televisions per 1,000 people between countries i & j.

Note that there was a tenth indicator (I5ij – the difference % of GDP in manufacturing); however, it had a very low factor loading and was dropped.  The scores for each of the nine remaining indicators, and the resultant factor (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 14,280 country pairs (i.e. n x n-1 for 120 countries). 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.

 

TIME PERIOD

For the majority of the industrial development indicators, the attached data represent the values for 1994 or 1995.  For the non-agricultural labour indicators, the data represent the values for 1990.

 

INDUSTRIAL DEVELOPMENT INDICATOR CALCULATIONS

Ind Dev F (abs) = absolute value of Ind Dev F

Ind Dev F is the single-factor solution, using principal component analysis, for I1ij, I2ij, I3ij, I4ij, I6ij, I7ij, I8ij, I9ij  and I10ij 

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)

I3ij = (I3i – I3j)

Where, I3i = passenger cars per 1,000 people for the exporting country (i) and, I3j = passenger cars per 1,000 people 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)

I5ij = (I5i – I5j)

Where, I5i = manufacturing as a % of GDP for the exporting country (i)     and, I5j = manufacturing as a % of GDP 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)

I7ij = (I7i – I7j)

Where, I7i = daily newspaper circulation per 1,000 people for the exporting country (i)                                                                                                           and, I7j = daily newspaper circulation per 1,000 people for the importing country (j)

I8ij = (I8i – I8j)

Where, I8i = radios per 1,000 people for the exporting country (i)               and, I8j = radios per 1,000 people for the importing country (j)

I9ij = (I9i – I9j)

Where, I9i = telephones per 100 people for the exporting country (i)        and, I9j = telephones per 100 people for the importing country (j)

I10ij = (I10i – I10j)

Where, I10i = televisions per 1,000 people for the exporting country (i) and, I10j = televisions per 1,000 people for the importing country (j)

 

Ind f  – Difference in Industrial Development Factor:

The preceding nine indicators have be reduced to a single factor using confirmatory factor analysis (cfa).  This factor score has been estimated using 14,042 country pairs (i.e. the 119 countries with full data).  The individual factor loadings and the cronbach alpha are reported below.

Factor
Loading
Cronbach
Alpha
  Ind f 9 item factor score for differences in industrial development 0.9532
  I1ij – Difference in GDP per capita 0.833
  I2ij – Difference in energy consumption per capita 0.747
  I3ij – Difference in cars per 1,000 people 0.907
  I4ij– Difference in % non-agricultural labour 0.882
  I6ij – Difference in % urban 0.817
  I7ij – Difference in newspapers per 1,000 people 0.813
  I8ij – Difference in radios per 1,000 people 0.851
  I9ij – Difference in phones per 100 people 0.937
  I10ij – Difference in TVs per 1,000 people 0.889

MISSING DATA

Of the 120 countries reported on here, Taiwan was the only country for which industrial development data was not available via our primary source – the United Nations Statistical Division.  In this case, the Industrial Development factor was derived using a separate estimate of GDP per capita, and the education variables, E1ij and E3ij.  A multivariate regression of these three indicators on Ind F for 99 countries yielded an adjusted r2 of 0.835.

SOURCES

The primary sources for these estimates were:

      • United Nations, Statistical Yearbook, New York, United Nations Statistical Division, 1995.
      • United Nations, ‘Social Indicator data’, [www document] http://www.un.org/depts/unsd/social/ (accessed 16 June 1998).

Differences_in_Industrial_Development_n14280.xlsx