urban population (as % of total), surface of the countries (all from World Bank105) and the KOF Index of Globalization (available at the Swiss Economic Institute KOF of the ETH Zurich106). We average all variables over the years from 1995 to 2000 as far as possible and mostly transformed them by taking their natural logarithms.
beyond 2009, however, the ICT-specic productivity changes are relatively volatile. In 2005, for example, a peak in the ICT curve with an average productivity increase of 7.57% is observable.
This value is highly inuenced by the productivity development of ICT in certain countries.
As described in section 6.4, we split the entire investigation period into subperiods. We use the median values of the input and output for three years and examine the periods t1,2 from (the median of) 2001-2003 to (the median of) 2005-2007, t2,3 from 2005-2007 to 2010-2012 and t1,3 from 2001-2003 to 2010-2012. The rst subperiod covers the `productive decade' between 1995-2005 and the second subperiod allows the analysis of a possible eect of the global nancial and economic crisis in 2007/08 on economic productivity.
Table 6.2: MEA Indicators of the Income Groups
M EC TC
K HK ICT K HK ICT K HK ICT
Worldwide
t1,3 1.04 1.01 1.14 0.92 0.92 0.87 1.09 1.09 1.28
t1,2 1.04 0.99 1.11 0.98 0.95 0.96 1.04 1.04 1.10
t2,3 0.99 1.03 1.07 0.95 0.98 0.95 1.04 1.04 1.14
Low Income
t1,3 0.95 0.75 0.71 0.94 0.73 0.71 1.00 1.00 1.01
t1,2 0.89 0.80 0.76 0.87 0.77 0.69 1.02 1.03 1.03
t2,3 1.01 0.98 1.00 0.99 0.97 0.98 1.00 1.01 1.01
Lower Middle Income
t1,3 1.04 1.00 1.05 0.95 0.89 0.76 1.08 1.13 1.26
t1,2 1.02 0.97 1.01 0.98 0.94 0.95 1.02 1.03 1.06
t2,3 1.02 1.04 1.07 0.98 0.94 0.90 1.07 1.11 1.20
Upper Middle Income
t1,3 1.04 1.08 1.10 0.94 0.93 0.86 1.10 1.12 1.36
t1,2 1.06 1.04 1.12 1.01 0.99 0.98 1.04 1.05 1.11
t2,3 0.99 1.05 1.05 0.90 0.95 0.89 1.06 1.08 1.21
High Income
t1,3 1.08 1.04 1.45 0.91 0.96 1.00 1.16 1.09 1.60
t1,2 1.07 1.00 1.25 0.97 0.94 0.98 1.08 1.06 1.34
t2,3 0.95 1.04 1.15 0.92 1.00 1.02 1.06 1.02 1.17
Note: Reported are the group median MEA values in the respective time periods. M denotes the Malmquist productivity index, EC the eciency change, TC the technical change of physical Capital (K), human capital (HK) or ICT.t1,2 denotes the period from 2001-2003 to 2005-2007,t2,3 from 2005-2007 to 2010-2012 andt1,3 from 2001-2003 to 2010-2012.
Table 6.2 shows the median values of productivity changes both worldwide and the respective income groups. For each of the three investigation periods, the median of the Malmquist pro-ductivity index, as well as its decomposition into eciency and technical change, are shown in the table for each of the input factors.
Worldwide, a productivity increase over the periodt1,3 is observable in each of the input factors.
The median productivity growth for physical capital lies at 4%, for human capital at 1% and for ICT at 14%. The median of technical change is 9% for both physical and human capital and 28% for ICT. As a result, there is a positive frontier shift in all input directions, whereby
it is most pronounced in the direction of ICT. The median of all input factors indicates an eciency decrease in the same period, 8% for both physical and human capital and 13% for ICT.
The eciency losses are largely attributable to economic developments in low-income countries.
These eciency losses are more moderate in the two higher income groups. In general, there have been noticeable eciency losses across all input factors and both subperiods. The reason for this is twofold. Firstly, the indicated decrease in eciency can be an eect of the implemented sequential frontier, capturing the eects of a technical regress (i.e. a recession) in the eciency change component. Secondly, it is an indication that the technological frontier is driven by (few) countries with high technical change in the respective input-dimensions whereas other countries were not able to catch up.
Comparing the income groups it can be noted that low-income countries have lost productivity on average across all input factors. Whereas the productivity loss in the median is only 5%
for physical capital, it is 25% for human capital and 29% for ICT. Thus, it can be noted that ICT is a rather inhibitory factor for the productivity change of low-income countries. There is only minor technical change in this group over the entire investigation period. The decline in productivity is mainly due to eciency losses and primarily in t1,2. The subperiod t2,3 in this income group is characterized by a relatively constant, stagnating productivity.
In relation to the other input factors, the productivity development of ICT has increased over time in lower middle income countries. While the increase in t1,2 is only 1% and thus behind the increase for physical capital, productivity increases by 7% int2,3 and thus stronger than for physical (2%) and human capital (4%). Over the entire period, ICT exceeds the other input factors. The increase in productivity can be explained by technical change. The productivity change for ICT is also the highest in countries with upper middle income. In t1,3, productivity change for ICT is at 10%, whereas the productivity change for physical (4%) and human capital (8%) lies behind. The productivity increase for ICT, however, is considerably stronger in t1,2
(12%) than in t2,3 (5%). This can also be observed in the high income countries, where the productivity change for ICT in t1,2 at 25% is considerably higher than in t2,3 at 15%. However, ICT's productivity growth in this income group is remarkably higher than that for other input factors and thus has a positive impact on the productivity development of economies. Int2,3 we can observe a productivity decrease in the direction of physical capital in the two upper income groups and a productivity increase in the direction of human capital.
In the two higher income groups we can observe that ICT's productivity growth has slowed down over time. In t1,2, the average ICT-specic productivity change is 12% in the upper middle income countries and 25% in the high income countries. Int2,3, the average ICT-specic productivity change is 5% in the upper middle income countries and 15% in the high income countries. In the group of low income countries, the ICT-specic productivity decreases in t1,2
but ceases to decrease further in t2,3. In the group of lower middle income countries, the average ICT-specic productivity change is 1% in t1,2 and 7% in t2,3. Hence, the productivity growth in this income group has accelerated over time. The fact that we can observe an increase in ICT-specic productivity growth in the lower middle income group and a slowed ICT-specic productivity growth in the two upper income groups over time, can be explained by two possible reasons. The rst explanation is that the slowed ICT-specic productivity growth is due to
the nancial and economic crisis, which had a stronger impact on the economies of developed countries (see e.g. Karshenas 2009). The second explanation is that productivity development on the frontier is slowly weakening and developing countries catch up. The latter is supported by the saturation and catch-up process of the worldwide ICT distribution, shown in section 3.3, but is not evident from the eciency changes in table 6.2.
Taking all countries together, we nd ICT to have the highest productivity index values as well as technical change of all other input factors. Table 6.2 shows that the median of ICT productivity changes increases with the income groups. In order to verify the general validity of the statement that the productivity has risen with increasing development stage, we will consider the distribution of the respective country values below.
Figure 6.5 shows the density plots of the MEA Malmquist productivity index for ICT by income group for the period t1,3 as well as the subperiods t1,2 and t2,3. As indicated in table 6.2, ICT productivity changes rise with higher income groups. It can be seen that the densities shift to the right as the income group increases. For the periodt1,3 the peak of the curve of low income countries is below the value of 1 and indicates a productivity decrease in ICT for the majority of the countries concerned. For the two middle income groups, the peak is already around 1, for the lower middle income countries slightly below and slightly above for the upper middle income countries. Both distributions of the middle income groups have a positive skew, whereby few countries inuence the mean value positively. Mostly apparent is the shift of high income countries. In this group, only a few countries have an ICT productivity decline. In general, it can be seen that the distribution of productivity indices in t2,3 is relatively less dispersed across the income groups than int1,2. Figure 6.5 also shows that productivity changes in low and lower middle income countries in the second subperiodt2,3are more positive than in the rst subperiod t1,2. Conversely, gure 6.5 shows that productivity changes in upper middle and high income countries in the rst subperiod t1,2 tend to be higher than in the second subperiod t2,3. The density plots of the ICT eciency change values by income group are shown in table D1 in the appendix.
In this section we have shown that the worldwide productivity in the input-direction of ICT has increased by 14% and thus more than the other input factors. In contrast to the rst subpe-riod t1,2 (before the global nancial and economic crisis and part of the `productive decade'), productivity growth in ICT has slowed down in t2,3, but continues to exceed the productivity growth for the other input factors. We nd that developing countries benet to a lesser extent from the productivity-enhancing eects of ICT, compared to developed countries, which is con-sistent with parts of the literature (Papaioannou and Dimelis 2007, Dedrick et al. 2013). A comparison is most likely to be possible with Youse (2011), due to both a similar investigation period (2002-2006) as well as a country classication by income according to the World Bank Atlas method. Youse (2011) also nds ICT to play a major role in the growth of high and upper middle income groups, but not so in the lower middle income group countries.
Figure 6.5: Density Plots of Productivity Change in ICT by Income Group
0 1 2 3
0.00.51.01.52.02.53.0
Low Income Countries
Density
0 1 2 3
0.00.51.01.52.02.53.0
Lower Middle Income Countries
Density
0 1 2 3
0.00.51.01.52.02.53.0
Upper Middle Income Countries
Density
0 1 2 3
0.00.51.01.52.02.53.0
High Income Countries
Density
period t1,3 subperiod t1,2 subperiod t2,3
Note: Figure shows the density plots of ICT MEA Malmquist values (x-axis) according to the respective income groups and investigated periods. A Gaussian kernel is used. The smoothing bandwidth is estimated by the method of Sheather and Jones (1991).
This is remarkable as poorer countries could theoretically have been rapidly catching up in the past, which means that developing countries have the potential to skip several initial phases of ICT development as the way has already been paved by developed countries . As an example, the wired and mostly more expensive xed-network technology compared to mobile communications technology can be mentioned in this respect. By skipping these technologies, the developing countries would at least have the potential to make greater progress in ICT productivity. Com-paring the two subperiods, it is noticeable that ICT productivity growth has increased in the two lower income groups over time, while the productivity growth has slowed down in the two upper income groups.