Ict For Development 2

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Mobile telephony provides Africa with the additional economic growth that was experienced by OECD countries in the 80s by the deployment of fixed line telephony. Lower prices will increase access and usage and amplify this effect. A competitive ICT sector is the only recipe for low prices and high service delivery. Policy and regulatory environment are very important factors for establishing a competitive ICT sector

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Ict For Development 2

  1. 1. ICT for Development ICT4D Dr. Christoph Stork 1
  2. 2. researchICTafrica Research network of universities and think tanks in 20 African countries No AfricanYear Research title countries2003 ICT Sector Performance Review 72004 Household e-Access & e-Usage Survey 112005 SME e-Access & e-Usage Survey 142006 ICT Sector Performance Review 17 Household e-Access & e-Usage Survey2007 17 (with focus poverty and demand elasticities) 2
  3. 3. TOC SME e-Access & Usage (why ICT matters) Access & Prices (policy and regulation makes a difference)Impact of Competition in Namibia (how ICTs can help) 3
  4. 4. Small and Medium Enterprisee-Access & Usage 4
  5. 5. 5
  6. 6. BACKGROUND• Aims: • Looking at the impact of ICTs, • Identifying obstacles and • Providing guidance for policy recommendations• SME sector is the sector in which most of the world’s poor are working and it contributes significantly to economic growth and employment• No random sampling: qualitative interviews, 3967 SMEs across 14 countries, 280 each• Intensive training of enumerators for them to understand every single participating business 6
  7. 7. Distinguishing by formality• Form of ownership?• Is your business registered with the Receiver of Revenues? (pay taxes?)• Is your business registered for VAT?• How many of your employees have a written employment contract?• Does your business strictly separate business from personal finances?• Does your business keep financial records? 7
  8. 8. Access to ICTs by formality Fixed Line Phones 100% Informal Semi formal 80% Formal 60%Internet Connection Mobiles 40% 20% 0% Computer Fax Post Box 8
  9. 9. ICT perceptions: ICTs are important or very important! Fixed Line Phones Dont have it 99% Have it 61%Internet Connection Mobiles 95% 41% 99% 71% 52% 31% 26% Computer Fax 98% 95% 83% Post Box 9
  10. 10. The more formal a SME is the moreICTs it has and uses. Usage intensity is the same (access/usage) Formality N Mean Rank Chi-Square df Asymp. Sig. Informal 1606 1275.4 ICT Semi-formal 1234 2112.36Possession 1327.61 2 0 Index Formal 1126 2852.24 Total 3966 Informal 1606 1361.15ICT Usage Semi-formal 1234 2069.24 1034.54 2 0 Index Formal 1126 2777.19 Total 3966 Informal 1606 1989.19ICT Usage Semi-formal 1234 1962.71 Intensity 0.64 2 0.726 Index Formal 1126 1998.17 Total 3966 10
  11. 11. Turnover and ICT expenditure = significantly and positively correlated across sector!Correlation coefficients that are significant at the 0.01 levelD: Manufacturing 0.483F: Construction 0.808G: Wholesale and retail trade; repair of motor vehicles, motorcycles and 0.736personal and household goodsH: Hotels and restaurants 0.219I: Transport, storage and communications 0.99J & K: Financial intermediation & real estate, renting and business activities 0.544M & N & O: Education, health, social work, other community, social and 0.905personal service activities 11
  12. 12. Informal business operate on a higher profit margin Mean Chi- Asym Ranks Formality N df Rank Square p. Sig. Informal 1590 2081.59 Profit Semi- margin: 1230 1913 formal after tax 26.051 2 0.000 profits Formal 1120 1875.94divided by turnover Total 3940 12
  13. 13. Informal businesses are more profitable Mean Chi- Asym Ranks Formality N df Rank Square p. Sig. Informal 1504 2020.61Profitability: after tax Semi- 1139 1761.75 profit formal 70.846 2 0.000 divided by total fixed Formal 1048 1686.98 assets Total 3691 13
  14. 14. Formal businesses have higher labour productivity Mean Chi- Asymp Ranks Formality N df Rank Square . Sig. Labour productivity: Informal 1571 1546.48 Value added (Sales minus Semi- direct costs, 1223 1968.59 rent, water, formal electricity etc.:) 479.988 2 0.000 divided by full- Formal 1114 2514.43 time employeesincluding owners that manage the business Total 3908 14
  15. 15. Formal businesses re-invest more Mean Chi- Asymp. Ranks Formality N df Rank Square Sig. Informal 1559 1834.37 Re- investment Semi-formal 1217 1908.94 rate: Invest 44.438 2 0.000ment divided by fixed Formal 1100 2118.79 assets Total 3876 15
  16. 16. Turnover or Sales ModelF1 F2 F3 F4 F5 F6 = β1 + β 2 + β3 + β4 + β5 + β6 +εFA FA FA FA FA FA F1= Turnover F2= AVERAGE water, electricity, cost F3= AVERAGE cost for your premises in terms of rent, land taxes mortgage payments F4= AVERAGE business expenditure on telephone calls, fax, postage, Internet F5= AVERAGE Wage Bill F6= AVERAGE Direct Cost (raw materials and other intermediary inputs or goods bought for resale) FA=Total value of fixed assets 16
  17. 17. ICT expenditure contributes significantly to higher salesRobust regression of turnover function  Formal Semi-formal Informal N 1048 1139 1504 R Square 0.7775 0.9199 0.9481 F 74.39 208.58 193.52 Sig. For equation 0 0 0 Mean Variance InflationFactor (VIF) 1.5 1.82 1.19Unstandardized Coefficients 3.93 2.77 51.28for ICT Usage ExpenditureSig. of ICT Usage Expenditure 0.000 0.000 0.000 17
  18. 18. Labour Productivity• V= Value Added• W= AVERAGE Wage Bill• ICTU= ICT Usage Index• ICTP = ICT Possession Index• EA=Full-time employees + owners that manage the business• W/EA is hence the average wage and V/EA labour productivity 18
  19. 19. Access to ICTs is linked to higher labour productivity N R Square F Sig. Mean VIF 3908 0.5695 32.21 0 1.01 Unstandardized t Sig. VIF Coefficients (Constant) -21836.49 -2.32 0.021 Average Wage 5.641971 7.75 0 1.01ICT Possession Index 12284.54 2.6 0.009 1.01 19
  20. 20. Usage of ICTs is linked to higher labour productivity N R Square F Sig. VIF 3908 0.5701 30.69 0.0000 1.02 Unstandardized t Sig. VIF Coefficients (Constant) -25785.1 -1.73 0.083 Average Wage 5.64 7.81 0 1.02ICT Usage Index 7659.58 2.24 0.025 1.02 20
  21. 21. No doubt! ICTs help SMEs tobecome more profitable 21
  22. 22. Main Obstacle to ICT adoption remains high cost   informal semi formal formal averageNetwork problems / unreliable infrastructure 11.3% 11.7% 10.5% 11.2% Lack of financial resources 10.6% 4.5% 7.3% 8.0% Lack of awareness & knowledge of ICTs 10.3% 8.4% 10.5% 9.7% High cost, too expensive 55.6% 60.8% 58.8% 57.9% Lack of skills & ICT illiteracy 2.8% 7.4% 6.9% 5.1% No need 9.5% 7.2% 6.1% 8.0% 22
  23. 23. Conclusion Part 2• Mobile phones are the most used tools in supporting the running of SMEs• Designing mobile financial applications to integrate informal SMEs into the formal economy (for example formal financial services) are promising avenues• The main constraint to ICT usage remains high investments and us age costs• Hence, effective regulations and policies that enable a competitive ICT environment will facilitate economic growth, employment and social inclusion - in particular for the poor 23
  24. 24. ICT Access & Prices 24
  25. 25. Access to fixed-line phones 2006 Fixed-line Subscribers per 100 inhabitantsSouth Africa 9.93 Botswana 8.75 Uganda 7.09 Namibia 6.84 Senegal 2.23 Ghana 1.48 Ivory Coast 1.40 Benin 1.02 Ethiopia 0.97Burkina Faso 0.93 Kenya 0.84 Nigeria 0.82 Zambia 0.78 Cameroon 0.65 Tanzania 0.41Mozambique 0.38 Rwanda 0.24 Source: ResearchICTafrica.net, (population based on IMF data) 25
  26. 26. Access to mobile phones 2006 Mobile Subscribers per 100 inhabitantsSouth Africa 68.15 Botswana 57.54 Cameroon 27.51 Namibia 26.86 Kenya 19.05 Nigeria 16.88Mozambique 14.97 Tanzania 14.55 Senegal 14.49 Ghana 12.59 Benin 11.31 Zambia 9.30 Ivory Coast 8.22 Uganda 6.73Burkina Faso 5.17 Rwanda 2.94 Ethiopia 1.15 Source: ResearchICTafrica.net, (population based on IMF data) 26
  27. 27. OECD Usage BasketsMinutes or units Low User Medium User High UserCell2Cell own Network Peak 6.91 15.60 39.48Cell2Cell own Network Off Peak 3.60 7.49 12.50Cell2Cell own Network Off Off Peak 3.17 7.49 17.11Cell2Cell other Network Peak 4.32 10.08 27.72Cell2Cell other Network Off Peak 2.25 4.84 8.78Cell2Cell other Network OffOffPeak 1.98 4.84 12.01Cell2Fixed Peak 3.17 6.83 16.80Cell2Fixed Off Peak 1.65 3.28 5.32Cell2Fixed Off Off Peak 1.45 3.28 7.28SMS Peak 16.16 25.33 33.60SMS Off Peak 8.42 12.16 10.64SMS Off Off Peak 7.41 12.16 14.56 27
  28. 28. 2006 Mobile Nominal Usage Costs 2006 Low OECD User Basket - cost in US$ using nominal end of 2006 exhange rates Nigeria 12.5 South Africa 10.9 Kenya 10.6Côte dIvoire 10.2Burkina Faso 9.7 Namibia 9.6 Cameroon 8.6 Zambia 7.9Mozambique 7.6 Benin 7.4 Senegal 7.3 Uganda 7.3 Botswana 7.0 Ghana 6.5 Tanzania 5.8 Rwanda 5.6 Ethiopia 2.2 28
  29. 29. 2006 Mobile PPP Usage Costs 2006 Low OECD User Basket - cost in US$ using implied PPP conversion rates Uganda 36.2Mozambique 32.4 Ghana 30.8 Rwanda 30.5Burkina Faso 29.2 Namibia 27.5 South Africa 27.2 Kenya 20.5 Nigeria 20.0 Botswana 18.4 Cameroon 18.4 Senegal 18.4Côte dIvoire 17.9 Benin 16.3 Tanzania 14.3 Ethiopia 13.3 Zambia 11.6 29
  30. 30. 2006 Fixed-line Nominal Usage Costs Cost of a local 1 minute call (peak rate)- cost in US$ using end of 2006 nominal exchange ratesBurkina Faso 0.15Côte dIvoire 0.12Mozambique 0.12 Kenya 0.11 Tanzania 0.10 Cameroon 0.10 Uganda 0.10 South Africa 0.07 Rwanda 0.07 Senegal 0.06 Namibia 0.05 Ghana 0.05 Nigeria 0.05 Botswana 0.05 Zambia 0.05 Benin 0.04 Ethiopia 0.00 30
  31. 31. 2006 Fixed-line PPP Usage Costs Fixed-Line: Cost of a local 1 minute call (peak rate) cost in US$ using implied PPP conversion ratesMozambique 0.49 Uganda 0.48Burkina Faso 0.46 Rwanda 0.39 Tanzania 0.26 Ghana 0.25 Kenya 0.21 Cameroon 0.21Côte dIvoire 0.21South Africa 0.19 Namibia 0.16 Senegal 0.15 Botswana 0.13 Benin 0.09 Nigeria 0.08 Zambia 0.07 Ethiopia 0.02 31
  32. 32. 2006 Fixed-line Nominal Usage Costs Cost of a local 3 minute call to US (peak rate)- cost in US$ using end of 2006 nominal exchange rates Zambia 4.77Burkina Faso 3.90 Ethiopia 3.42 Rwanda 3.00 Kenya 2.41 Namibia 2.20 Tanzania 2.14 Cameroon 1.81 Uganda 1.54 Benin 1.45 Botswana 1.15Mozambique 1.02 Ghana 1.01 Senegal 0.90Côte dIvoire 0.90 South Africa 0.52 Nigeria 0.35 32
  33. 33. 2006 Fixed-line PPP Usage Costs Fixed-line: Cost of a 3 minute call to the US (peak rate) cost in US$ using implied PPP conversion rates Ethiopia 20.7 Rwanda 16.5Burkina Faso 11.7 Uganda 7.7 Zambia 7.0 Namibia 6.3 Tanzania 5.3 Ghana 4.7 Kenya 4.7Mozambique 4.3 Cameroon 3.8 Benin 3.2 Botswana 3.0 Senegal 2.3Côte dIvoire 1.6South Africa 1.3 Nigeria 0.6 33
  34. 34. Conclusion Access• Access and usage varies considerably across Africa• Usage costs vary equally• Link between Tele-density and price is not straight forward: GDP per capita, competition in the sector, market structure, policies, regulation are all important factors 34
  35. 35. Affect ofCompetition in Namibia 35
  36. 36. Nominal Prices Nominal cost of OECD Usage Baskets in N$ Cheapest MTC September 2005 Cheapest MTC October 2007 296 Cheapest Switch October 2007 Cheapeast Cell One October 2007 250 228 210 174 147 101 10683 70 48 51 Low User Medium User High User 36
  37. 37. Real Prices Real cost of OECD Usage Baskets in N$ (September 2005 prices) Cheapest MTC September 2005 Cheapest MTC October 2007 296 Cheapest Switch October 2007 Cheapeast Cell One October 2007 221 202 186 174 130 89 9483 62 43 45 Low User Medium User High User 37
  38. 38. Price Change MTC MTC price change compared to September 2005 nominal prices real prices (in Sep 2005 prices)85% 85% 84% 75% 75% 75% Low User Medium User High User 38
  39. 39. Price Change of Cheapest overall Overall price change (cheapest available in Namibia) compared to September 2005 nominal prices real prices (in Sep 2005 prices) 71% 63% 58% 58% 52% 51% Low User Medium User High User 39
  40. 40. Conclusion• Mobile telephony provides Africa with the additional economic growth that was experienced by OECD countries in the 80s by the deployment of fixed line telephony.• Lower prices will increase access and usage and amplify this effect.• A competitive ICT sector is the only recipe for low prices and high service delivery.• Policy and regulatory environment are very important factors for establishing a competitive ICT sector 40

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