**3. Results**

### *3.1. Bivariate Analysis of Productive Performance and ICT Capital*

Figures 3–6 present the relationships between the four performance indicators and the share of ICT capital stock. Each dot indicates pooled data on the energy sector in 14 countries from 2000 to 2014. The vertical axis shows the performance indicator and the horizontal axis shows the share of each type of ICT capital stock.

To compare the relationship between productive performance and ICT capital stock share among countries with different economic scales, this study divides the 14 countries into two groups. The first group comprises countries with a large economic scale. France, Germany, Italy, the U.K., and the U.S. are selected for this group. The other group comprises countries with a medium or small economic scale. Austria, the Czech Republic, Denmark, Finland, Luxembourg, the Netherlands, Slovenia, Spain, and Sweden are included in this group. These two groups are distinguished from one another by different colors in the scatter plot figure. Grey color is used to indicate the large-economic-scale group in each figure.

**Figure 3.** The scatter plot of labor productivity (LP) and information and communications technology (ICT) capital share. (**a**). Information Technology (IT) capital share; (**b**). Communication technology (CT) capital share; (**c**). Software capital share; (**d**). Share of total ICT capital. **Note:** The vertical axis shows the LP and the horizontal axis shows the capital share in gross capital stock. Grey color represents countries with a large economic scale.

**Figure 4.** The scatter plot of capital productivity (CP) and ICT capital share. (**a**). IT capital share; (**b**). CT capital share; (**c**). Software capital share; (**d**). Share of total ICT capital. **Note:** The vertical axis shows the CP and the horizontal axis shows the capital share in gross capital stock. Grey color represents countries with a large economic scale.

**Figure 5.** The scatter plot of material productivity (MP) and ICT capital share. (**a**). IT capital share; (**b**). CT capital share; (**c**). Software capital share; (**d**). Share of total ICT capital. **Note:** The vertical axis shows the MP and the horizontal axis shows the capital share in gross capital stock. Grey color represents countries with a large economic scale.

**Figure 6.** The scatter plot of the total factor productivity (TFP) change and ICT capital share. (**a**). IT capital share; (**b**). CT capital share; (**c**). Software capital share; (**d**). Share of total ICT capital. **Note:** The vertical axis shows the TFP change and the horizontal axis shows the capital share in gross capital stock. Grey color represents countries with a large economic scale.

Figure 3 shows that the relationship between ICT capital and LP differs based on the type of technology. Figure 3a,b imply that there are negative relationships between LP and the shares of IT and CT capital. Meanwhile, Figure 3c implies that the share of software capital has a positive relationship with LP. These relationships are similar in both economic scale groups. Finally, Figure 3d indicates an ambiguous relationship between LP and the share of total ICT capital. These results indicate the importance of using not only total ICT capital data but also specific ICT capital data.

The ambiguous relationship between LP and total ICT capital should be investigated in more detail using specific ICT capital data because there are several possible explanations for it. One possibility is that each ICT capital stock has an ambiguous relationship with LP. Another possibility is that the effect of each type of ICT capital on LP is canceled out if the ICT capital data are integrated. In the former situation, there is an ambiguous relationship between LP and ICT capital. In the latter situation, the relationship between LP and each ICT capital share should be considered carefully. Otherwise, the estimation results might lead to a misleading discussion and policy implications.In addition to LP, CP is observed to have different relationships based on each type of ICT capital share. Figure 4 shows that there is a positive relationship between CP and software capital share (see Figure 4c), even though there is an ambiguous relationship with total ICT capital share (Figure 4d). Finally, Figures 5 and 6 show the relationship of ICT capital with MP and TFP, respectively. In contrast to Figures 3 and 4, there are similar trends in the four figures in Figures 5 and 6, which show that there are diverse effects of ICT capital among the performance indicators. Additionally, there is no large difference between the economic scale groups. Based on these findings, this study further investigates the relationship between the performance indicators and ICT capital share using an econometric approach.

### *3.2. Determinant Analysis of the Productive Performance Indicators*

Tables 3–5 present the results of the determinant analysis, focusing on the impact of ICT capital share on the productive performance indicators. Table 3 indicates the results of the determinant analysis that does not expressly consider the differences in the specific types of ICT capital. Table 4 shows the results of the determinant analysis that applies three ICT capital shares separately as determinant variables to consider the differences in specific ICT capital characteristics. In addition to the two models, this study applies the interaction term of each ICT capital share and the renewable energy share to investigate the hypothesis that the impact of ICT capital is different due to the degree of renewable energy diffusion (see Table 5).

**Table 3.** The results of the determinant analysis using integrated information and communications technology (ICT) capital data.


Note: \*\*\* and \*\* indicate significance at the 1 and 5% levels, respectively. The random effect model is applied for all estimations.

**Table 4.** The results of the determinant analysis using individual ICT capital data.


Note: \*\*\* and \*\* indicate significance at the 1 and 5% levels, respectively. The fixed effect model is applied for the model with the MP.

The 2nd stage of the analysis includes the preferred specification from fixed effects or random effects based on the results of a Hausman test.

First, this study compares the impacts of specific ICT capital shares and the total ICT capital share on the productive performance indicators in Tables 3 and 4. From Table 3, a significant effect of the total ICT capital share on CP and MP is not observed. Meanwhile, Table 4 shows that CT and

software capital shares significantly affect CP, with different signs. Additionally, IT and CT capital shares significantly affect MP, with different signs. These results imply that the total ICT capital share does not significantly affect CP and MP because the effects of specific ICT capital shares are canceled out. This finding can be clarified if and only if specific ICT capital shares are applied separately to consider the differences in ICT capital characteristics, which is necessary to precisely understand the impact of ICT capital.


**Table 5.** The results of the determinant analysis using individual ICT capital with interaction terms.

Note: \*\*\*, \*\*, and \* indicate significance at the 1, 5, and 10% levels, respectively. The fixed effect model is applied for the model with CP and MP.
