Table 3.2: Output of the Principal Component Analysis
Comp. 1 Comp. 2 Comp. 3 Comp. 4 Comp. 5
Telephone Lines 0.284 -0.297 -0.517 0.738 -0.140
Internet Users 0.388 -0.414 -0.444 -0.665 -0.198
Broadband Internet Subscribers 0.095 -0.192 -0.133 -0.024 0.967
Mobile Cell Subscribers 0.824 0.541 0.159 0.022 0.049
PCs 0.285 -0.640 0.702 0.113 -0.056
Standard derivation 86.277 20.734 8.149 6.090 2.594
Proportion of Variance 0.932 0.054 0.008 0.005 0.001
Cumulative Proportion 0.932 0.986 0.994 0.999 1.000
Note: All Variables are in values per 100 people and averaged over the years of 2002-2012.
Based on 178 observations, the Principal Component Analysis is conducted using the singular value decomposition, which examines the covariances/correlations between the individual variables.
the ve variables of ICT infrastructure can be merged to a single variable that comprises most of the information.
This procedure can also be applied for the calculation of ICT infrastructure in the individual years. In this case, only the former four variables are used, since data for the number of PCs is only available as average value over the period 2002-2009. Also in this variant, the variables load on the rst principal component, whereby all loadings have a positive sign. We can observe these high variances on the rst principal component in combination with constant signs for all available years 2001-2012. As a result of this annual variant, the four ICT variables can be merged to a single variable that comprises most of the information for a total of 148-167 countries (depending on the respective year). Figure A1 in the appendix illustrates the rst component loadings of the PCA. Table A1 in the appendix shows the explaining proportion of the rst component to the total variance.
Figure 3.2: Boxplot of the ICT Infrastructure Variable
050100150
Value of ICT Infrastructure Variable
Myanmar India China Mexico Brazil Russia United States South Korea Germany Finnland Switzerland Luxembourg Hong Kong
OECD
Worldwide Average
Selected Countries Means of Aggregates
Note: Distribution of the ICT infrastructure variable.
the median of 64.2, the value for Columbia and Tunisia near the mean of about 72. The box, with the 1st and 3rd quantiles as its lower and upper margins, has a comparably low position, which means that 75% of the countries have a value of ICT infrastructure below 112 while a few countries show fairly high values. These are either countries which are mere cities (Hong Kong, Luxembourg) or small advanced countries (Switzerland, Finland). While the worldwide mean value is in the middle of the box, the mean value of the OECD countries lies in the upper whisker between the positions of the U.S. and South Korea.
In gure 3.3 the global distribution of ICT infrastructure is plotted on a world map. Higher values of ICT infrastructure are represented by darker areas. These can be observed in North America (mean value of ICT infrastructure 127.90) and Europe (121.77). South, East (30.33) and West Africa (30.83) as well as Central Asia (34.37) present lower values.34
We now turn to the analysis of the second version in which the variable for ICT infrastructure is calculated for each year of our investigation period. Figure 3.4 illustrates the distribution and the development of the respective years in boxplots. It can be seen that there are substantial
34 An enlarged map illustrating the European distribution of the ICT infrastructure is given in gure A2 of the appendix.
Figure3.3:WorldmapoftheICTInfrastructureVariable
1.97 192
Note:GlobaldistributionoftheICTinfrastructurevariable.Countrieswithmissingdatarepresentedbywhitecolor.Figure 3.4: Boxplots of the ICT Variable in the Course of Time
2001 2003 2005 2007 2009 2011
050100150200
Year
ICT Value
Mean Values of Income Groups Low Income
Low Middle Income Upper Middle Income High Income
Note: Distribution of the ICT variable in the course of time.
Mean values of the income groups are shown as dashed lines.
cross-country dierences in the stage of ICT infrastructure. Over the whole period 2001-2012 it is observable that there is on average an increase of the ICT infrastructure variable. Starting from the initial year 2001 the disparity between the ICT infrastructure values widenes steadily. While in 2001 the dierence between the highest (121.78) and the lowest (0.08) ICT infrastructure value is 121.7, it increases to a value of 188.51 (dierence between 198.38 and 9.87) in 2012. Countries with consistently high ICT infrastructure values are, inter alia, the countries in the OECD and Russia. The main reason for the increasing disparity over time are countries that were not able to improve their ICT.
It can be seen from the boxes (with the 1st and 3rd quantiles as its lower and upper margins) that the ICT values increase between 2001 and 2012 on worldwide average. The mean value increased from 29.77 in 2001 to 110.57 in 2012. The position of the boxes with respect to the whiskers reects the changes in the distribution. It can be seen in 2001 that both the box as well as the median line have a comparably low position. Over the years, the position of box and median line rises so that the distributional skewness declines over time. A graphical comparison of the densities between 2001 and 2012 is given in gure 3.5. The gure illustrates that in 2001 the distribution is right-skewed. In 2012, the skewness considerably diminishes.
Figure 3.5: Density Plots of the ICT Variable in 2001 and 2012
0 50 100 150
0.0000.0050.0100.015
ICT in 2001
Density
0 50 100 200
0.0000.0020.0040.0060.008
ICT in 2012
Density
By considering the courses of mean values by income groups in gure 3.4, the development stage of ICT worldwide becomes apparent. In general, countries with higher income levels also have higher values of ICT in contrast to countries with lower income levels. The mean values of the low-income group of countries lies on the lower whisker on every boxplot in the investigation period, the mean values of the high-income group of countries is on the upper whisker for every year.
The mean ICT values of both, low middle as well as upper level-country groups, are positioned in the boxes. They are separated by the median of the respective years, with the mean value of the upper middle-income countries being closer to the median of the total distribution. In the course of time, the mean values of both country groups move away from those of the low-income group towards the group of countries with high income.
Especially remarkable are the curve shapes of the respective income groups, illustrating the saturation and catch-up process of the worldwide ICT distribution. Whereas there seems to be a saturation of ICT in the high income countries represented by lower growth rates of the ICT value over time, the low-income countries show a growing rate until 2006, followed by a linear growth until 2012. Both curves, for low middle as well as upper middle income, are s-shaped as diusion rates usually are. Increasing growth rates of ICT values in the early years are followed by decreasing growth rates in the later years of the period.