Session 3- assessing affordable access · 2018. 10. 11. · and attract new customers zero-rated services, social media bundles, blended bundles, build-your-own-bundle. multiple user

Session 3-

assessing

affordable access

Prof Alison Gillwald, Research ICT Africa,

UCT Nelson Mandela School of Public

Governance

ITU REGIONAL ECONOMIC DIALOGUE

Ougadougou 8 October 2018

Changed market conditions

saturated voice markets shifting to data

introduction of low-end smart phone driving data

declining revenue from traditional services

operators face becoming ‘dumb pipes’

multiple new business models emerging from data competition to retain and attract new customers

zero-rated services, social media bundles, blended bundles, build-your-own-bundle.

multiple user strategies to access and use Internet – substituted voice and text data services, public wi-fi for updates, U-tube.

More users, more devices, more services, more demand

2

OTT impact of international voice traffic

Nationally representative surveys of ICT access and use by households & individuals

aged 15-65; In 16 developing countries; Data represents 30% of the global

population; 28,900 face-to-face interviews; +/-3 margin of error

Sample sizes

Note: Pakistan excludes AJK, FATA, Gilgit-Baltistan (~2% of population)

Supply vs Demand-side indicators what’s the story?

Active SIMS vs

Unique

subscribers.

Disaggregation

by gender,

income,

education,

location.

5

86.9 83.8

73.9

63.358.5

48.239.7

80.4

147.1

135.8

83

72.1 74.9

52.1

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

1.80

0

20

40

60

80

100

120

140

160

Kenya South Africa Ghana Nigeria Tanzania Rwanda mozambique

RIA ITU Mean SIM card ownership

RAMP 1G pricing index

Quality adjusted prices, quality matters when assessing data market

Represents the ratio between the 1GB data basket and the average download and upload speeds, shows that the two dominant operators Vodacom and MTN offer higher quality, respectively.

In the same period Telkom’s quality was the lowest. However, since Q1 2016, it seems that smaller operators improved their quality, catching up with dominant operators in Q2 2016 (in line with increased network investments). Vodacom SA’s high prices are accompanied by higher Internet speeds, compared to MTN SA and Cell C, which are performing less well on the measure based on average download/upload speed (in Mbps) divided by 1GB basket costs.

7

Expanding undersea / terrestrial bandwidth…

Even in countries where there is over 50% 3G coverage, less than 20% critical mass connected to enjoy network effects –demand challenges greater than supply

side.

HOW WELL IS AFRICA CONNECTED?

Supply vs Demand-side indicators what’s the story?

Active SIMS vs

Unique

subscribers.

Disaggregation

by gender,

income,

education,

location. 86.9 83.873.9

63.358.5

48.239.7

80.4

147.1

135.8

83

72.1 74.9

52.1

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

1.80

0

20

40

60

80

100

120

140

160

Kenya South Africa Ghana Nigeria Tanzania Rwanda mozambique

RIA ITU Mean SIM card ownership

Higher connectivity in higher income countries; but

Asia and Africa lag behind in Internet use

11

Q1: Do you own a mobile phone?

Q2: Have you ever used the Internet? (Gmail, Google, Facebook, email)

Q3: Do you use social media like Facebook, Whatsapp, Twitter etc?

91%

75%

85% 84%89% 88%

61%65%

57%

74% 75%

68%

87%

61%

50%

40%

86%

73%

53%

73%

63% 65%

19%

30%

17%13%

26%

36%

26%

15%9% 10%

82% 80%

45%

67%

62% 62%

15%

30%

14%13%

29% 30%

26%

13%6% 9%

Argentina Colombia South Africa Peru Paraguay Guatemala India Nigeria Pakistan Bangladesh Ghana Cambodia Kenya Tanzania Rwanda Mozambique

Mobile phone ownership, Internet usage and social media use (% of aged 15-65 population)

Mobile phone owneship Internet usage Social media usage

Base Argentina Colombia South Africa Peru Paraguay Guatemala India Nigeria Pakistan Bangladesh Ghana Cambodia Kenya Tanzania Rwanda Mozambique

All respondents 1,240 1,425 1,610 1,478 1,357 1,407 5,069 1,706 2,002 2,020 1,145 2,123 1,179 1,102 1,118 1,091

There is a significant gender gap in ownership of phones

90%

75%

83%87%

92% 91%

79%

71% 68%

87%82%

78%

92%

66%62%

51%

91%

75%

87%82%

88%84%

43%

58%

43%

58%

69%

62%

83%

57%

39%

32%

-1% 0%-4%

7% 5% 8%

46%

18%

37% 34%

16%20%

10%15%

37% 37%

-20%

0%

20%

40%

60%

80%

100%

120%


Mobile phone ownership (% of aged 15-65 population)

Male Female Gap

Q: Do you own a mobile phone?

BaseArgentina Colombia South Africa Peru Paraguay Guatemala India Nigeria Pakistan Bangladesh Ghana Cambodia Kenya Tanzania Rwanda Mozambique

Male Female Male Female Male Female Male Female Male Female Male Female Male Female Male Female Male Female Male Female Male Female Male Female Male Female Male Female Male Female Male Female

All respondents 478 762 487 938 795 1,020 508 970 879 478 656 751 2,478 2,591 912 896 1,060 942 1,092 928 547 653 735 1,388 544 664 531 669 556 655 527 644

Gender gap in ownership

(%)

Male phone owners (% of

male population)

Female phone owners

(% of female population)

Male phone owners (% of male population) =

⎻

Gender gap in Internet in Africa

As markets

become

saturate greater

parity in

ownership

Smaller gap

than Internet

But other

cultural,

demographic,

urbanisation,

factors at play

13

…..and a higher gender divide in Internet use



All respondents 478 762 487 938 795 1,020 508 970 879 478 656 751 2,478 2,591 912 896 1,060 942 1,092 928 547 653 735 1,388 544 664 531 669 556 655 527 644

Q: Have you ever used the Internet? (Gmail, Google, Facebook, email)

87%

71%

57.0%

81%

63%

75%

26%

38.9%

21% 18%

33%

45%

32%

18%13% 14%

86%

75%

50.3%

69%

64% 57%

11%

21.0%

12%7%

22%30%

22% 12%5% 7%

1%-6%

12% 14%

-1%

23%

57%

46% 43%

62%

34%34%

31% 32%

62%

50%

-20%

0%

20%

40%

60%

80%

100%

120%

Internet usage

Male Female Gap

Gender gap in Internet

usage (%)

Male internet users

(% of male population)

Female internet users


Male internet users (% of male population) =

⎻

In addition to gender, there is also an urban-rural divide in

mobile ownership


Urban Rural Urban Rural Urban Rural Urban Rural Urban Rural Urban Rural Urban Rural Urban Rural Urban Rural Urban Rural Urban Rural Urban Rural Urban Rural Urban Rural Urban Rural Urban Rural

All respondents 1,208 32 986 439 1,050 765 1,178 300 824 533 550 857 2,200 2,869 1,147 661 793 1,209 808 1,212 721 479 897 1,226 727 481 720 480 711 500 718 453

Q: Do you own a mobile phone?

90%93%

88%84%

93%90%

71%

79%

59%

78%

84%81%

93%

76%

63%

55%

100%

71%

81%83% 83%

86%

55% 54% 56%

72%

63% 64%

85%

53%

46%

33%

-11%

24%

8%1%

11%4%

22%

31%

5% 7%

25%21%

9%

30% 27%

41%

-20%

0%

20%

40%

60%

80%

100%

120%


Mobile phone ownership (% of aged 15-65 population)

Urban Rural Gap

Urban rural gap in

ownership (%)

Urban mobile phone owners

(% of urban population)

Rural mobile phone owners

(% of rural population)

Urban mobile phone owners (% of urban population) =

⎻

Gender gap in mobile phone ownership

As markets

become

saturate greater

parity in

ownership

Smaller gap

than Internet

But other

cultural,

demographic,

urbanisation,

factors at play

16

…..and an even higher urban-rural divide in Internet use

Q: Have you ever used the Internet? (Gmail, Google, Facebook, email)



All respondents 1,208 32 986 439 1,050 765 1,178 300 824 533 550 857 2,200 2,869 1,147 661 793 1,209 808 1,212 721 479 897 1,226 727 481 720 480 711 500 718 453

86%90%

61%

81%

74%70%

27%

42%

18% 19%

36%

51% 53%

33%

22% 24%

91%

69%

40%

49%44%

61%

14%

22%

16%11%

17%

31%

16%

5% 5% 4%

-6%

23%

35%40% 40%

13%

48% 49%

13%

42%

54%

40%

69%

84%77%

85%

-20%

0%

20%

40%

60%

80%

100%

120%


Internet usage (% of aged 15-65 population)

Urban Rural Gap

Urban rural gap in

Internet usage (%)

Urban Internet users

(% of urban population)

Rural Internet users

(% of rural population)

Urban Internet users (% of urban population) =

⎻

Digital paradox that more people come online greater inequality there is:

Ownership and use of ICTs by income

WHAT ARE THE BARRIERS TO

GETTING ON LINE? AND STAYING

ONLINE?

5. Mobile phone type

12%

28%34%

22%30% 30%

55%

31%

53% 52%

40% 42%

58%66% 66%

77%

10%

10%

8%

17%5%

14%

16%

46%

25%

14% 37%

10%

14%

11%

25%5%

78%

63%58% 61% 65%

57%

28%23% 22%

35%

24%

48%

28%23%

9%18%

Argentina Colombia South Africa Peru Paraguay Guatemala India Nigeria Pakistan Ghana Bangladesh Cambodia Kenya Tanzania Rwanda Mozambique

Mobile phone ownership by type (% of aged 15-65 mobile phone owners)

Basic Phone Feature Phone Smart Phone

• Higher smartphone ownership in higher income countries

5. Mobile phone type – gender gap

• The smartphone gap is smaller than the internet gap

76%

60% 63% 64% 63% 65%

31%26%

20%

35%

25%

52%

32%

25%

10%

19%

81%

64%

54%59%

66%

49%

24%20%

27%

34%

20%

46%

25%21%

9%16%

-6% -6%

14%8%

-5%

25% 24% 25%

-32%

4%

20%12%

21%17%

1%

17%

-40%

-20%

0%

20%

40%

60%

80%

100%

120%


Smartphone ownership (% of aged 15-65 mobile phone owners)

Male Female Gap

Gender gap in

smartphone ownership

(%)

Male smartphone owners


Female smartphone owners


Male smartphone owners (% of male population)

=

⎻

44%

74%

43%

60%

43%

32%

43%

57%

32%

73%

35%

68%

57%

53%

66%

79%

35%

26%28%

32%

22%24%

10%

15%

7%

21%

8%

39%

14%

21%

11% 12%

21% 21%

7%

45%

19%

26%

33%

18% 17% 16%

27%

59%

16%13%

11%

14%17% 17%

40%

6%

19%

7%

12%

3%

10%

3%

11%

16%

7%8%

7%7%

1% 1%

32%

8%

3%

18%

22%

11%10%

17%

32%

23%

2%

11%13%

1% 0% 0%

11%

1% 1%

19%

27%

6%

16%19%

27%

47%

7%

50%

37%

49%

18%

54%

16%

59%

55%

23%

8%

14%12%

40%

12%

5%

11%

26%

15%

3%


Reasons for not owning a mobile phone (% of aged 15-65 non-mobile phone owners)

I cannot afford a mobile phone My phone is broken I don’t know how to use it

My phone got stolen No mobile coverage where I live No electricity at home to charge the mobile phone

I don’t need it I am not allowed to own one

6. Barriers for mobile phone ownership

• Non owners: Asia - lack of need; LATAM - Affordability, Africa -Affordability

6. Barriers for Internet use

• Non users: Still a significant % of in Asia (and some in Africa) don’t know what the

Internet is. In LatAm, many don’t know how to use it.

37%

11% 14%7%

18% 15%11% 10%

6% 9%18%

9%

27%

16%

3% 3%

23%

27%

8%

51%26%

47%

9%

21%

3%

14%

5%

41%11%

11%

3%

14%

19%

24%

37%

7%

24%

8%

8%

14%

19%

23%

7%

23%

22%

64%

43%

76%

5%

0%

16% 3%2%

5%

4%

4%

1%

2%

1%

3%

4%

2%

33%

1%

5%

35%0%

10%

28% 14%

64%

39%

69%

41%

67%

21%

26%

1%

9%

0%2%

0%

9% 6%

1%

8%

1%

4%

1%

3%

2% 2%

3%

1%4% 2%10%

3%

15% 16%

1% 3% 2%8%

1%7%

1% 2%7% 5% 5% 5%


Reasons for not using the Internet (% of aged 15-65 non-Internet users)

No interest / not useful I don’t know how to use it No access device computer /smartphone Too expensive I don’t know what the internet is No time, too busy Other

6. Barriers for MORE internet use

72%

90%

4%

84%

53%

84%

1%

10% 9%

68%

83%

3%

78%

65%

84%

1%

8%

2%

58%

66%

47%

53%56%

52%

41%

55%

43%

51%

58%

24%

59%61%

54%

29%

19%

37%40% 41%

10%

58%

29%

49%

26%

55%

12%

31%

21%

8%

48%

27%

38%

5%

9%6%

30%

33%

16%

9%

19%

24%

6%

0%

11%

27%30%

6%

39%

30%

41%

6%

24%

12%

24%

30%

3%

42%

30%

38%

4%

14%

6%9%

19%

2%

18%15%

21%

4%6% 5%

9%

16%

3%

18%

8%

26%

1%3%

5%

1% 0%

6%4%

0% 0%

6%

0%

6%

Argentina Colombia South Africa Peru Paraguay Guatemala Tanzania Rwanda Mozambique

Limitations for Internet usage (% of aged 15-65 Internet users)

Worried about getting virus/malware Worried about surveillance/privacy invasion The internet is too expensive to use

The internet is very slow Lack of time Lack of interesting content for me

None Few people to communicate with via the internet Lack of local language content

I find it difficult to use Someone restricting the use (e.g. family, spouse, parents) Other

• What limits more use among current users?: Cost & Speed in most African

countries; malware & privacy concerns in LatA

Reason for not using the Internet

I don’t know what the Internet is

No access devices

Don’t know how to use it

No interest


Tanzania

I don’t know what the Internet is

No accessdevices

No interestToo expensive

Not allowed touse it

South Africa

I don’t know what the Internet

is

No accessdevices



KenyaI don’t know

what the Internet is

No accessdevices


No time

Nigeria

I don’t know what the

Internet is

No accessdevices

No interestToo

expensive

I don’t know how to use it

Ghana

Lack of devices and internet

illiteracy are main inhibitor of

Internet use

….Lack of t ime & data costs in Asian countries; and in the remaining

African countries

26

27%

18%22%

33%

12% 11%17%

22%

17%3%

15%

8%

70%

12%

21%

16%

49%

19%

21%

7%

20%

18%

33%

18% 30%

52%

5%

45%

3%

0%

1%4% 0%

2%9%

1%

0%4%

2%2%2%

3% 3%1% 0% 0%

1%2% 0% 1%1% 0% 0% 2%2% 1% 2% 0% 1% 0% 0%1% 2% 2% 1% 1% 1% 1%1% 0% 0% 0% 1% 0% 1%

India Nigeria Pakistan Bangladesh Ghana Cambodia Kenya

Limitations for Internet usage (% of aged 15-65 Internet users)

Nothing, no limitation Speed of internet Lack of time Data cost

No internet connection in the area Other Privacy concerns Lack of content in my language

Not allowed to use it more (family, spouse, parents) I find it difficult to use Worried about getting virus/ malware

Q: What is your main limitation for your use of the internet? (Single response question)

Base India Nigeria Pakistan Bangladesh Ghana Cambodia Kenya

Internet users 919 529 427 266 311 804 440

FINANCIAL INCLUSION: WHO IS

BANKED,UNBANKED, USING

MOBILE MONEY?

75%of 15-65 population in IN and 60 & in ZA have their own bank

account. All others, less than 50% of the 15-65 aged are banked

28

34% 32%

59%

27%

12%

27%

74%

34%

6%11%

28%

12%

34%

12%

28%

11%

3% 2% 3% 2% 3% 2% 3%7%

0% 1% 2% 1% 0%3% 2% 2%


Access to bank accounts (% of aged 15-65 population)

I have my own bank account I use someone else bank account


All respondents 1,240 1,425 1,610 1,478 1,357 1,407 5,069 1,706 2,002 2,020 1,145 2,123 1,179 1,102 1,118 1,091

Q1:Do you have access to a bank account?

Similarly, low credit & debit card ownership

29

44%

27%

35%

25%

15% 17%

25%28%

3%

9%5%

17%

7%

18%

10%

Argentina Colombia South Africa Peru Paraguay Guatemala India Nigeria Bangladesh Ghana Cambodia Kenya Tanzania Rwanda Mozambique

Credit or debit card ownership (% of aged 15-65 population)

Owns a credit or debit card

Base Argentina Colombia South Africa Peru Paraguay Guatemala India Nigeria Bangladesh Ghana Cambodia Kenya Tanzania Rwanda Mozambique

All respondents 1,240 1,425 1,610 1,478 1,357 1,407 5,069 1,706 2,020 1,145 2,123 1,179 1,102 1,118 1,091

Q:Do you have a credit card or debit card??

Pakistan data excluded as this question was not administrated in

Pakistan

Mobile money: High use In Kenya, Ghana, Mozambique, South Afr ica and

Paraguay. But low elsewhere.

30

Q: Do you ever use mobile phone for financial transactions: to send or receive money?

5%11% 10%

4% 1% 4% 4% 7%0%

27%

1% 2%6%

1%

1%

1%9%

1%

53%

4% 1%4%

13%

3%

31%

3%

74%

32%

1%

0%

1%

0%

1%1%

1%0%

0%

6%

1%

5%

Argentina Colombia South Africa Peru Paraguay Guatemala India Nigeria Pakistan Bangladesh Ghana Cambodia Kenya Mozambique

Mobile money usage (% of aged 15-65 mobile phone owners)

Yes, through mobile banking Yes, through mobile money Yes, through both

Base Argentina Colombia South Africa Peru Paraguay Guatemala India Nigeria Pakistan Bangladesh Ghana Cambodia Kenya Mozambique

Mobile phone owners 1,116 1,297 1,552 1,234 1,209 1,214 3,252 1,180 1,208 1,531 934 1,526 1,074 667

31

Q: Do you ever use mobile phone for financial transactions: to send or receive money?

BaseArgentina Colombia South Africa Peru Paraguay Guatemala India Nigeria Pakistan Bangladesh Ghana Cambodia Kenya Mozambique

Male Female Male Female Male Female Male Female Male Female Male Female Male Female Male Female Male Female Male Female Male Female Male Female Male Female Male Female

Mobile phone owners 425 691 438 859 666 886 443 791 772 437 586 628 2,000 1,252 660 520 777 431 962 569 452 482 597 929 507 567 340 327

Gender gap in mobile money use almost everywhere (except

Argentina, Colombia)

1% 0%

10%

1%

58%

6%

1%

5%

13%

4%

33%

3%

76%

35%

0.5% 2%

9%

0%

50%

3%0%

3%

12%

1%

29%

3%

73%

29%

48%

10%

82%

14%

43%

73%

40%

13%

68%

12%

24%

4%

17%

Argentina Colombia South Africa Peru Paraguay Guatemala India Nigeria Pakistan Bangladesh Ghana Cambodia Kenya Mozambique

Male Female Gap

E COMMERCE IN THE GLOBAL

SOUTH : WHAT?, HOW

MUCH?,WHY? AND WHY NOT?

43%

23%

8%

36%

16% 18% 19%

8%12%

3%

18%

6%9% 6% 4% 5%


Trading or E-commerce apps (selling and buying online e.g. ebay)

Use of trading & transport apps: Best performance from Latin American

countr ies. Ghana outl ier (good performance) in Afr ica

33

Q: Are you using these types of Mobile apps on your phone?

31%

15%10%

35%

10%

22%17%

6%

17%

2%

13%

1%9%

4% 5% 6%


Mobile app usage (% of aged 15-65 feature or smartphone owners)

Transport apps (public transportation info, taxis, Uber)


Feature or smartphone owners 982 1,020 1,552 972 809 846 1,397 795 571 936 458 878 1,074 789 660 667

Overall, higher use of transport and trading apps in urban areas

34

Q: Are you using these types of Mobile apps on your phone?

30%33%

27%

11% 13%

5%

36%

28%

11%7%

24%20%

23%

11%6% 5%

20%

14%

4%2%

13% 13%

3%0%

20%

4%

9%

1%5% 4%

8%4%







Feature or

smartphone owners954 28 755 265 919 633 825 147 578 231 362 484 711 686 575 220 272 299 417 519 332 126 465 413 678 396 555 234 443 217 498 169

43%

26%

36%

19%

11%

3%

39%

21% 20%

7%

22%

15%

24%

14%12%

4%9%

14%

4% 2%

20%

13% 12%

3%

20%

4%

14%

1%

7%3%

8%3%





And higher transport & trading app usage among men (compared

to women) in most countries

35

Q: Are you using these types of mobile apps on your phone?



Feature or

smartphone owners358 624 343 677 666 886 354 618 534 275 448 398 931 466 467 328 364 207 616 320 241 217 389 489 507 567 386 403 365 295 340 327

36%

26%

15% 15%11% 10%

45%

29%

15%

8%

27%

16%19%

14%

8%3%

22%

7%3% 2%

15%11%

2% 1%

8%10%

5% 4% 6% 4%8%

4%





51%

35%

25% 22%

9% 7%

44%

31%

24%

13%

22%

14%

22%

12% 11%

4%

14%7%

2% 3%

19% 17%

5% 7% 8% 10%7% 6% 5%

2%6% 5%





Platform use for sell ing in of labor: low overall, though sti l l a large

absolute number in Colombia.

36

5%

13%

6%5% 4% 5% 4%

8%

2%1%

2% 1%4%

1%

4%

8%


Usage of platforms: selling (% of aged 15-65 internet users)

Q: Some people find paid jobs or tasks by connecting directly with people who want to hire them using a website or mobile app. In the last year, have you earned money

by taking on jobs of this type?


Internet users 1,006 1,192 829 1,120 886 1,104 919 537 427 266 311 804 440 266 172 238

Barriers

SOCIAL MEDIA: WHO IS DOING

WHAT AND HOW MUCH ON SOCIAL

MEDIA?

4. Social media use – gender gap

80%

86%

46%

74%

61%

71%

22%

37%

18%

35%

18%

37%

31%

16%

8%13%

83%

77%

43%

64% 62%

55%

9%

20%

9%

23%

6%

25%22%

11%

5% 6%

-4%

10%6%

14%

-2%

22%

60%

47% 50%

33%

66%

32% 29% 30%

45%51%

-20%

0%

20%

40%

60%

80%

100%

120%


Social media usage (% of aged 15-65 population)

Male Female Gap

• The social media gender gap reflects the internet gender gap

Gender gap in Social

media usage (%)

Male Social media users


Female Social media users


Male Social media users (% of male population) =

⎻

Low number of people shared religion, political view and

sexual orientation in social media

Q: What information do you share on Social media (profile eg) ?

95%

87%

63%

95%93% 93%

83%

99%

61%

91%

96%

90%88%

90%

74%

90% 89%

74%

89%

93%

82%

85%

90%

67%

83%

96%

80%

84%

90%

69%

87%

83%

57%

86%88%

80% 80%

76%

65%

71%

92%

67%

56%

78%

73%

80%

76%

47%

80% 81%

70%71%

85%

56%59%

77%

72%

64%

83%

63%

80% 80%

54%

85% 86%

73%

63%

87%

52%

87%

76%78% 79%

84%

70%

36%37% 37%

41%

45%

41%

71%

80%

55%

67%69%

62%

45%

53%

41%

31%

44%

28%

49%

29%

52%

57%

79%

62%

71%

78%

69%

45%

66%

32%

23%

17%

11%

30%

16%

20%

40%

43%

48%

22%

33%

41%

19%

24%

10%

21% 20%

11%

25%

14%16%

26%

22%

32%

23% 23% 22%

5%

27%

8%

Argentina Colombia South Africa Peru Paraguay Guatemala India Nigeria Pakistan Ghana Bangladesh Kenya Tanzania Rwanda Mozambique

Types of information shared on social media (% of aged 15-65 social media users)

Gender Real Name Age Martial status Pictures or videos you and your family and friends Mobile Number / Email address Religion Political views Sexual orientation

39

Base Argentina Colombia South Africa Peru Paraguay Guatemala India Nigeria Pakistan Ghana Bangladesh Cambodia Kenya Tanzania Rwanda Mozambique

Social media users 993 1,246 669 999 802 878 754 496 369 323 251 680 423 241 156 230

Social media taxes: state coordination

40

To curb ‘gossip’ on social media platforms, all Internet subscribers in

Uganda are to pay a tax of 200 Ugandan shillings (USD0.05) daily to use

social media applications such as Facebook, Twitter, Instagram,

WhatsApp and Skype, among others.

A tax which requires a user to pay USD1.5 per month or USD18.00 per

year for daily access of social media apps in addition to the ordinary

cost of data.

All mobile money transactions were intended to be taxed one percent

tax but were reviewed down to 0.5%.

Traditionally secondary and primary tax of 30% on products and

services.

Those who are connected are educated and employed and in a position

to monitor, mobilise and critique

Tragedy of social networking, blogging taxes

http://www.theeastafrican.co.ke/business/Uganda-drops-some-mobile-money-taxes/2560-4667682-13sfpi6z/index.html

Uganda Mobile Peneteration – 48% - by pphone type

41

71

12

16

Basic phone Feature phone Smart phone

Uganda’s Internet (14%) and social media use (12%)

42

30

28

9

7

16

1312 12

0

5

10

15

20

25

30

35

Internet use Social media use

Urban Rural Male Female

Regressive taxes penalize poor, constrain take up

Income percentiles Income (USD)Cheapest 1 GB (USD)/Income

1GB + social media tax/ income

25% 5,23 53% 82%

50% 21,47 13% 19%

75% 65,47 4% 6%

90% 130,95 2% 3%

Unintended consequences of social networking tax

• Using Research ICT Africa Mobile Pricing (RAMP) index, the cheapest 1GB of data in Uganda is USD2.77.

• Even though this makes Uganda one of the cheapest countries in terms of data products, majority of Ugandans do not use the internet (78%, ITU, 2016).

• Effecting this tax will increase the price of the cheapest data product by a margin of USD1.5 to USD4.27, making it even more unaffordable.

• Furthermore, those who marginally afforded Internet services will be priced out of the market, increasing the percentage of the unconnected.

• Those who are connected are educated and employed and in a position to monitor, mobilise and critique

44

Digital Paradox

• More people connected greater digital equality

• Determinants of gender inequality - education and income

• Cultural factors not reveal directly by quantitative data – Asia

• Intersectionality

• Reduce digital inequality – structural inequality

• Short term strategies

Long terms solutions lie in demand stimulation, short term things can be done…

Recommendations

‣ Reduce secondary taxes, make services more affordable drive usage,

more profitable, greater company an general taxes, reinvest in network

extension, improve quality more favourable conditions for digital

economy

‣ Scrap USO and enable secondary spectrum use and community, micro

networks

‣ remove all excise duties on feature and entry level smart phones

‣ adopt wider digital economy approach – create open data, access to

big data

‣ enable public and private extension of free public Wi-Fi to towns and

rural with the connection of all public buildings;

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Documents

Session 3- assessing affordable access · 2018. 10. 11. · and attract new customers zero-rated services, social media bundles, blended bundles, build-your-own-bundle. multiple user