In this subsection, we present results for the threefold Oaxaca-Blinder decomposition by computer and internet accessibility. A positive gap implies that firms with access to technology j have relatively high turnover compare to firms with no access to the technology. Conversely, a negative gap indicates that firms with no access to technology j have a higher turnover compare to firms with access to the technology.
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Figures 4.1 and 4.2 illustrate the existence of differences in turnover across firms with access to technology (computer and internet access, respectively) and those with no access to these technologies.
Figure 4. 1: Distribution of firms' turnover by computer accessibility
0
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Figures 4.1 and 4.2 also depict the turnover distribution by computer and internet accessibility respectively for some selected countries (the remaining countries’ distributions are shown in the Appendix 4 due to the lack of space). The figures illustrate that across all the countries, firms with access to these technologies, on average have higher turnover than those with no access to these technologies.
140 Figure 4. 2: Distribution of firms' turnover by internet accessibility
Note: Turnover distribution of the remaining countries are presented in Appendix Figure A-4.2 of the paper.
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SMEs with internet accessibility SMEs with no internet accessibility
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Contribution of endowments and returns to endowment
Tables 4.1 and 4.2 report the threefold mean decomposition results and the contribution of the key variable of interest (ICT capital stock) to computer and internet accessibility turnover gaps respectively. The full tables containing all covariates are presented in Appendix A1. Figure 4.3 and Figure 4.4 graphically illustrate the contribution of endowment and returns to endowment to both computer and internet accessibility turnover gaps. The results presented in Tables 4.1 and 4.2 confirm high mean turnover in favour of firms with access to computers or internet across the continent. This is shown by the positive and highly statistically significant turnover gaps for both computer and internet accessibility for almost all the countries. The descriptive statistics indicates that Mozambique has the highest turnover gap for both computer and internet accessibility, with both showing an average of over 500 per cent difference in turnover favouring firms with access to these technologies.
Figure 4. 3: Contribution of endowments and returns to computer accessibility turnover gap
-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0
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Figure 4. 4: Contribution of endowments and returns to internet accessibility turnover gap
For computer accessibility turnover gap firms with computers in South Africa and Zambia have a relative high turnover of over 400 per cent relative to firms with no computer access. Also, firms using internet have an average turnover of over 300 per cent relative to firms with not internet access. Uganda has the lowest difference in turnover for computer and internet accessibility, 165 percent and 65 percent on average respectively in favour of firms with access to the technologies. In all the countries firms with access to computer or internet register on average a higher turnover relative to firms with no computers or internet access.
-1.0 -0.5 0.0 0.5 1.0 1.5 2.0
143 Table 4. 1: Oaxaca mean decomposition of turnover by computer accessibility
Variables Botswana Cameroon Ethiopia Ghana Kenya Mozambique Namibia
access to computer 12.325*** (0.070) 10.897*** (0.286) 12.548*** (0.209) 12.322*** (0.139) 11.841*** (0.122) 12.619*** (0.094) 12.175*** (0.245) no access to computer 11.056*** (0.163) 9.398*** (0.098) 11.258*** (0.125) 10.939*** (0.115) 10.720*** (0.117) 10.682*** (0.110) 10.743*** (0.097) total gap 1.269*** (0.166) 1.499*** (0.322) 1.290*** (0.265) 1.383*** (0.203) 1.120*** (0.172) 1.937*** (0.153) 1.433*** (0.255) endowments 1.284*** (0.277) 1.223*** (0.237) 1.389*** (0.295) 1.084*** (0.310) 1.107*** (0.188) 1.438*** (0.209) 0.962*** (0.205) log of ICT capital 0.358* (0.198) 0.042 (0.099) 0.341*** (0.096) -0.081 (0.090) 0.212** (0.090) 0.236** (0.116) 0.223*** (0.072) coefficients -0.468 (0.325) -0.775 (0.819) -1.790* (0.934) 0.246 (0.242) -0.107 (0.283) 0.700*** (0.239) 0.128 (0.494) log of ICT capital 0.595(0.551) 1.946**(0.938) 2.761**(1.336) 0.267(0.430) 0.202(0.523) -0.158(0.181) 0.091(0.433) constant -1.674 (1.234) -6.398*** (2.327) -5.940* (3.194) 0.860 (0.963) 0.183 (1.504) 2.408** (0.978) 0.251 (1.686) interaction 0.453 (0.397) 1.050 (0.784) 1.690* (0.907) 0.053 (0.315) 0.120 (0.270) -0.201 (0.257) 0.343 (0.513) log of ICT capital 0.377(0.359) 1.362** (0.654) 1.895** (0.903) 0.125 (0.206) 0.109 (0.294) -0.133 (0.148) 0.092 (0.417)
observations 255 280 282 280 277 280 307
Variables Nigeria Rwanda South Africa Tanzania Uganda Zambia Zimbabwe
access to computer 11.468*** (0.200) 12.564*** (0.170) 12.260*** (0.146) 11.452*** (0.161) 12.397*** (0.111) 11.389*** (0.117) 14.479*** (0.155) no access to computer 9.974*** (0.072) 11.197*** (0.094) 10.625*** (0.166) 9.992*** (0.103) 11.423*** (0.095) 9.744*** (0.085) 13.471*** (0.120) total gap 1.495*** (0.195) 1.367*** (0.201) 1.635*** (0.198) 1.460*** (0.189) 0.974*** (0.153) 1.645*** (0.124) 1.007*** (0.188) endowments 1.446*** (0.214) 1.438*** (0.277) 0.869*** (0.311) 1.191*** (0.244) 0.914*** (0.151) 1.214*** (0.172) 1.002*** (0.174) log of ICT capital 0.076 (0.115) 0.472*** (0.168) 0.618** (0.288) 0.142 (0.098) 0.142** (0.071) -0.079 (0.077) 0.383*** (0.112) coefficients -0.314 (0.569) -0.142 (0.434) 0.302 (0.306) -0.475 (0.450) -0.085 (0.168) -0.111 (0.173) -0.892*** (0.290) log of ICT capital 0.386 (0.829) 0.147 (0.852) -0.348 (0.933) 0.846 (0.966) 0.114 (0.432) 0.984*** (0.335) 0.852 (0.615) Constant -1.753 (2.123) -1.115 (1.385) -1.278 (1.503) 1.185 (1.529) -0.224 (1.483) 0.138 (1.022) -5.646*** (1.600) interaction 0.363 (0.558) 0.072 (0.494) 0.464 (0.400) 0.745 (0.462) 0.146 (0.160) 0.542*** (0.196) 0.897*** (0.302) log of ICT capital 0.215 (0.439) 0.074 (0.421) -0.127 (0.346) 0.571 (0.654) 0.044 (0.168) 0.600*** (0.225) 0.369 (0.265)
observations 265 279 290 263 351 276 281
Note: Standard errors in parentheses are obtained using Bootstrap inference based on 100 replications. *** p<0.01, ** p<0.05, * p<0.1. All country specifications include control variables. See
144 Table 4. 2: Oaxaca mean decomposition of turnover by internet accessibility
Variables Botswana Cameroon Ethiopia Ghana Kenya Mozambique Namibia
access to internet 12.451*** (0.147) 10.837*** (0.456) 12.841*** (0.228) 12.330*** (0.209) 11.986*** (0.163) 12.844*** (0.130) 12.270*** (0.500) no access internet 11.836*** (0.089) 9.631*** (0.107) 11.354*** (0.134) 11.231*** (0.104) 10.906*** (0.103) 11.052*** (0.118) 10.893*** (0.101) mean tunover gap 0.615*** (0.165) 1.206*** (0.460) 1.487*** (0.264) 1.099*** (0.234) 1.081*** (0.205) 1.792*** (0.163) 1.377*** (0.513)
endowments 0.421*** (0.153) 1.139*** (0.301) 1.087*** (0.349) 1.015*** (0.220) 0.857*** (0.216) 1.309*** (0.260) 1.053*** (0.285) log of ICT capital 0.150** (0.073) 0.219 (0.149) 0.291*** (0.110) -0.056 (0.075) 0.099 (0.065) 0.292*** (0.085) 0.181** (0.085)
coefficients 0.298 (0.385) -0.442 (5.141) 0.205 (0.364) 0.425 (0.409) 0.328 (0.365) 0.960*** (0.314) 0.974 (0.966) log of ICT capital 1.019 (1.050) 1.241 (5.631) 0.382 (0.871) 0.526 (0.513) 0.439 (0.732) -0.148 (0.235) -0.294 (0.807) constant -1.499 (1.532) -8.023 (18.706) 2.538 (1.658) 2.288 (1.752) 2.419 (2.271) 2.793* (1.499) 0.284 (2.578)
interaction -0.103 (0.392) 0.510 (5.101) 0.195 (0.394) -0.341 (0.424) -0.104 (0.316) -0.477 (0.290) -0.650 (0.943) log of ICT capital 0.187 (0.238) 0.682 (3.631) 0.215 (0.514) 0.176 (0.199) 0.184 (0.317) -0.095 (0.155) -0.235 (0.652)
observations 255 280 282 280 277 280 307
Variables Nigeria Rwanda South Africa Tanzania Uganda Zambia Zimbabwe
access to internet 11.171***(0.332) 12.624***(0.233) 12.157***(0.246) 11.419***(0.251) 12.227***(0.176) 11.446***(0.106) 14.544***(0.169) no access internet 10.229***(0.097) 11.371***(0.080) 11.140***(0.133) 10.211***(0.101) 11.724***(0.063) 10.042***(0.101) 13.783***(0.142) mean turnover gap 0.942***(0.345) 1.253***(0.244) 1.017***(0.282) 1.208***(0.287) 0.503**(0.197) 1.404***(0.153) 0.761***(0.223)
endowments 0.844**(0.405) 1.278***(0.271) 0.753***(0.237) 0.792***(0.294) 0.281(0.234) 1.305***(0.171) 0.791***(0.206) log of ICT capital 0.207 (0.134) 0.394*** (0.129) 0.236*(0.131) 0.206**(0.095) 0.082*(0.047) 0.031(0.066) 0.331***(0.094)
coefficients -0.076(8.673) -0.078(0.465) 0.312(0.334) -0.509(5.963) 0.542(0.388) 0.029(0.125) -0.327(0.303) log of ICT capital -1.084 (4.705) 0.052 (1.410) 1.010 (0.913) 1.140 (11.143) 0.299 (0.868) 0.518** (0.252) -0.130 (0.603) constant 0.482(22.045) -1.416(2.202) -2.134(2.093) -0.320(13.716) 1.042(1.775) -0.276(0.772) -1.048(1.554)
interaction 0.174(8.676) 0.053(0.467) -0.048(0.342) 0.925(5.907) -0.320(0.394) 0.070(0.142) 0.297(0.351) log of ICT capital -0.541(2.509) 0.022(0.613) 0.255(0.242) 0.646(6.674) 0.097(0.313) 0.220**(0.110) -0.032(0.152)
observations 265 279 290 263 351 276 281
Standard errors in parentheses are obtained using Bootstrap inference based on 100 replications. *** p<0.01, ** p<0.05, * p<0.1. All country specifications include control variables. See appendix Table A-4.3 for full table. All country specifications include control variables in the second stage of estimation.
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The threefold mean decomposition divides the total turnover gap into three different parts, namely the differences in endowments, differences in coefficients and interactions. The endowment effect, which captures the contribution of differences in observable characteristics of the two groups of firms, suggests that the mean turnover of firms with no computer or internet access would increase if these firms possess the characteristics or endowments of firms with computer or internet access. In each country, the inter-group differences in average endowment account for more than half of the overall turnover gap for computer and internet accessibility. Table 4.1 indicates that South Africa registers the lowest contribution of differences in endowments to computer accessibility turnover gap, with Ethiopia having the highest in contribution of endowment. Differences in endowments account for about 53.2 per cent of the overall computer accessibility turnover gap in South Africa and it explains about 108 per cent in Ethiopia.
Overall, differences in endowment favour firms with access to computer across Africa. These findings indicate that if firms with no computer access had similar endowments as firms with access to computer in these countries they are likely to raise their average turnover. The results of internet accessibility decomposition for the respective countries are comparable to that of computer accessibility model. However, in Uganda the difference in total endowment shows an insignificant effect on the internet accessibility turnover gap.
The returns aspect of the turnover gap measures the differences in coefficients or
returns to firms’ endowments. It measures differences in returns to endowments of
the two groups of firms. These findings indicate that return to the firms’ endowment make no significant contribution in determining the computer accessibility turnover gap in most of the countries with the exception of Ethiopia, Mozambique and Zimbabwe. The findings for Mozambique suggest higher return to endowment for firms with access to computers, as the coefficient effect favours firms with computer access. This implies that if firms with no access to computers have the same endowments as firms with computer access they are likely to achieve on average a higher turnover equivalent to the coefficient gap. In contrast, this is not the case in Ethiopia and Zimbabwe, as the coefficient effect gives an advantage to firms with no computer access. In the case of Ethiopia, since the contribution of differences in
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endowment exceeds 100 per cent it is suggestive that difference in returns to endowment favours firms lacking computer access. The findings suggest if Ethiopian and Zimbabwean firms with computer access have similar endowments as firms with no computer access their turnover might improve by 180 percentage points and 90 percentage points, respectively. The findings were no different for internet accessibility turnover gap, which shows that return to endowments is insignificant in all countries except Mozambique. Differences in coefficients favour of firms with internet access. This implies that if firms with no internet access have similar endowments as firms with internet access their average turnover is likely to rise by 96 percentage points.
Table 4.1 and Table 4.2 show that the interaction effects do not contribute to computer and internet accessibility turnover gaps in all countries. In general, the findings suggest that disparities in turnover between firms with computer and internet accessibility and those with no access to these technologies are largely driven by the observed characteristics of firms or returns to these endowments rather than an interaction of both endowment and returns.
Contribution of individual covariates
The results of the detailed decomposition provide more insight into the contribution of each explanatory variable to the endowment, return and interaction effects. A positive and significant contribution indicates the widening of the turnover gap and conversely, a significant negative contribution reduces the gap. Appendix Tables A- 4.1 and A-4.3 present full results of the detail decomposition. Figures 4.5 and 4.6 show a graphical display of the contribution of ICT capital to computer and internet accessibility turnover gaps, respectively. At the mean the endowment effect across Africa is driven mainly by differences in the factors of production; ICT capital stock, employment level, non-ICT capital stock and raw materials, in addition to the formality index. The contributions of the remaining firm level characteristics to endowment effect are statistically insignificant in almost all the countries.
The variable of interest, the endowment of ICT capital, is positive and statistically significant in explaining the mean turnover gap for both computer and internet
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accessibility in nine (9) of the sampled countries42. In all these countries, differences in ICT capital endowment account for more than 10 per cent of the turnover gap for both computer and internet accessibility decompositions. The positive and significant endowment/characteristics effect of ICT capital favours firms with access to either technology, implying that firms with no access to either computer or internet will have high average turnover if they are equipped with similar ICT capital endowments possessed by firms with access to these technologies. As expected firms with access to computers or internet have high levels of ICT capital stock.
Figure 4. 5: Contribution of ICT capital to computer accessibility turnover gap
Differences in ICT capital endowment contributes the largest to computer accessibility turnover gap in Botswana, South Africa and Zimbabwe, accounting for over 50 per cent of the computer accessibility turnover gap at the mean. ICT capital endowment differences explain about 61 per cent of the turnover gap in South Africa, 58 per cent in Botswana and 50.2 per cent in Zimbabwe. That is, if firms with no computers access in Botswana, South Africa and Zimbabwe are endowed with similar ICT capital possessed by firms with computer accessibility their turnover will increase on average by 58, 61 and 50 percentage points, respectively. Differences in
42
The endowment effect of ICT capital stock is positive and significant in determining sources of computer accessibility gap in the following countries: Botswana, Ethiopia, Kenya, Mozambique, Namibia, Rwanda, South Africa, Uganda and Zimbabwe. Whiles its contribution to internet accessibility turnover gap was significant in all these countries with the exception of Kenya. It was also positive significant in Tanzania.
-0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0
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ICT capital endowments account for less than 40 per cent of the computer accessibility turnover gap in the remaining countries, with Mozambique registering the lowest contribution of 13 per cent. Although difference in firm endowment does not contribute to internet accessibility turnover gap in Uganda, endowment of ICT capital favours firms with access to internet (see Table 4.2). This suggests that firms with no access to internet will have a high mean turnover if they possess similar ICT capital endowment. In five out of the nine countries43 in which differences in ICT capital endowment make a significant contribution to computer accessibility turnover gap, differences in non-ICT capital endowment do not contribute to this turnover gap. However, in the remaining four countries the positive contribution of ICT capital is re-enforced by a positive and significant contribution of non-ICT capital.
Figure 4. 6: Contribution of ICT capital to internet accessibility turnover gap
We now turn our focus to differences in returns to ICT capital endowment to the turnover gaps. The chapter finds no evidence to suggest that differences in return to ICT capital endowment statistically significant contribute to both computer and internet accessibility turnover gaps in most of the countries. Although differences in return to endowments (return/coefficient component of total gap) fails to contribute to computer accessibility turnover gap in Cameroon and Zambia, differences in
43 ICT capital makes positive and significant contribution to the computer accessibility in these
countries: Botswana, Mozambique, Namibia, South Africa and Zimbabwe. However, non-ICT capital does not contribute to the turnover gap in these countries.
-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0
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return to ICT capital endowment contributes positively to turnover gap between the two groups of firms. This finding shows that returns on ICT capital stock favours firms with computer accessibility, suggesting that in these countries firms with no computer access would earn higher turnover if they have comparable ICT capital stock as firms with computer access after controlling for all other endowments. Furthermore, the results for Zambia presented in Table 4.2 indicate that the return component of internet accessibility turnover gap is not statistically significant, in spite of this, return on ICT capital stock favour firms with access to internet in Mozambique. This finding indicates that if firms with no internet access have comparable amount of ICT capital endowment to firms with access they are likely to have a higher turnover resulting from high returns to ICT capital. This finding suggests that expansion of ICT capital stock perhaps makes labour more productive and also may replace other inputs (some form of non-ICT capital) used by the SME, thus leading to a direct deepening effect of ICT capital.
For the computer accessibility decomposition, the constant is significant in contributing to the gap in four countries (Cameroon, Ethiopia, Mozambique and Zimbabwe), while for the internet accessibility decomposition it is significant only in Mozambique. This indicates that in these countries there are some generic factors which tend to favour firms with computer or internet accessibility but are not captured in the two models. The interaction component of the total gap estimates the simultaneous e ect of di erences in endowments and coe cients. In almost all the countries the results indicate that this was insignificant with the exception of Ethiopia, Zambia and Zimbabwe. The interaction effect is positive and significantly different from zero in these three countries, which suggests that firms with access to computers have an advantage in terms of turnover due the that fact that they are better endowed with those characteristic which yield higher levels of average turnover.
Tables 4.3 and 4.4 present summaries of the mean decomposition of SME’s turnover by computer and internet accessibility. The tables contain the contribution of key variables and firm level characteristics. Few variables significantly contribute to computer accessibility turnover gap in Botswana and Zimbabwe, with the variables favouring firms with access to computer. However, Mozambique and Uganda have
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the highest number of variables which are significant in determining the sources of computer accessibility turnover gap. Some of the variables tend to favour firms with computer access, while others are in favour of SME with no computer access. Specifically, in Mozambique firms with computer access are more endowed with these variables compared to their counterpart with no computer access. Nonetheless, the returns on these endowments, especially raw materials and education, favour firms with no access to computers. Ghana and South Africa show/report the lowest number of variables which contribute significantly to internet accessibility turnover gap, with all these variables favouring firms using internet at the work place. Mozambique also registered the highest number of variables that are significant in determining the sources of internet accessibility turnover gap. Firms with internet access dominant by have relatively more endowment, while return to these endowment favours firms with no internet access.
Table 4. 3: Summary of mean decomposition by computer access
Variables Botswana Cameroon Ethiopia Ghana Kenya Mozambiq Namibia
log of employee +E +E +E +E +E +E +E, -R, -I
log of ICT capital +E +R, +I +E, +R, +I +E +E +E, +R
log of non-ICT capital +E +E +E -R
log of raw materials +E +E, +R +E +E +E +E, -R, -I +E, +R
sole proprietorship +R, -I -E, -R
sec. education -R, +I voc. education -R tertiary education +E -R -R. -I manufacturing construction -I -I formal semi-formal management control type -R, -I
Variables Nigeria Rwanda S. Africa Tanzania Uganda Zambia Zimbabwe
log of employee +E +E +E +E +E, +I
log of ICT capital +E +E +E +E +E, +I
log of non-ICT capital +E +E +E +E +E +R
log of raw materials +E +E +E
sole proprietorship -R sec. education +E +R, -I +R, -I +R, -I voc. education tertiary education +R, +I manufacturing -R, +I -R, +I construction formal +E +E +E, -R +E +E semi-formal +E management control type
Note: (+) Indicates favouring firms with computer access relative to firms with no computer access. (-) Indicates favouring firms with no computer access relative to firms with computer access. (E) Indicating significant endowment effect.
(R) Show significant return effect. (I) Indicates significant interaction effect.
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The differences in endowment of employees favour firms with access to computer or internet in twelve (12) countries. With respect to the internet accessibility gap, returns to endowment of employees and its interaction effect are both not significant in all countries. This finding is similar to the case of computer accessibility turnover gap, with the exception of Namibia. Return to employee endowment contributes negatively to computer accessibility turnover gap in Namibia, implies it favours firms with no computer access. That is, if Namibian firms with computers access had similar number and quality of employees as firms with no computer access they would on average improve their turnover.
Table 4. 4: Summary of mean decomposition of turnover by internet access
Variables Botswana Cameroon Ethiopia Ghana Kenya Mozambiq Namibia
log of employee +E +E +E +E +E +E +E
log of ICT capital +E +E +E +E
log of non-ICT capital +E +E
log of raw materials +E -R +E +E -R +R
sole proprietorship -E
sec. education -R, +I
voc. education -R
tertiary education +E, -R, -I
manufacturing -R -R
construction
formal +E +E
semi-formal -R +E
management control type
Variables Nigeria Rwanda S. Africa Tanzania Uganda Zambia Zimbabwe
log of employee +E +E +E +E +E
log of ICT capital +E +E +E +E +R, +I +E
log of non-ICT capital +E +E +E +E, -R, -I +E
log of raw materials +E
sole proprietorship sec. education voc. education tertiary education +R, +I +E manufacturing +R, -I construction -R, -I +R formal +E +E +E +E semi-formal +E
management control type +E
Note: (+) Indicates favouring firms with computer access relative to firms with no access to internet. (-) Indicates favouring firms with no computer access relative to firms with internet access. (E) Indicating significant endowment effect.
(R) Show significant return effect. (I) Indicates significant interaction effect.
The return on non-ICT capital endowment only contributes significantly to the internet accessibility turnover gap in Zambia, favouring firms with no internet access. For computer accessibility decomposition, return on non-ICT capital is significant in Namibia and Zimbabwe, though in both countries the endowment effect of non-ICT capital were both not significant in determining the sources of the
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computer accessibility turnover gap. In Namibia, the results suggest that if firms with access to computer use similar non-ICT capital in their production process as firms