Interrogating supply-side data

Transcription

1 Interrogating supply-side data Helani Galpaya Katmandu, March, 2015 This work was carried out with the aid of a grant from the International Development Research Centre, Canada and UKaid from the Department for International Development, UK.

2 Much data; many producers/publishers ITU/UN/WEF/OTHER INT L/NTL ORGs -Raw data -Composite indices (ranking countries) OPERATORS/SUPPLIERS -Financial data -Operational data (equipment, quality) -Complaints -Transaction Generated Data (Big Data) REGULATOR/ POLICY MAKER -Network level data for decision making and Monitoring -Complaints USERS - Quantitative surveys - Qualitative studies THIRD PARTY RESEARCH -Specialized Studies based on data obtained from all stakeholders

3 CONNECTIVITY

4 Is connectivity increasing? 100,000,000 Pakistan Mobile SIMs: ,000,000 80,000,000 70,000,000 60,000,000 50,000,000 40,000,000 30,000,000 20,000,000 10,000, Looks impressive

5 But PK is in middle of pack when compared to S Asian neighbors Mobile SIMs: ,000, ,000, ,000, ,000, ,000, ,000,000 50,000, Maldives Bangladesh India Pakistan Indonesia Phillipines Sri Lanka Thailand

6 But telecom data changes, fast: Most recent data is a must-have SIMs per 100 population 6

7 Who is actually ahead? Why? Aided by multiple millions of SIMs deregistered in PK in 2008 & and change of definition of active SIMs in India in

8 Which indicator benchmark? Different indicators can tell different stories Total number of mobile subscribers in India and Bangladesh Mobiles SIMs: India and Bangladesh 250 Mobile subscribers per 100 in India and Bangladesh Mobile SIMs per 100 population, India and Bangladesh In millions Per Year Year India Bangladesh India Bangladesh

9 Are the data comparable? E.g., How do you reconcile different financial years? Many countries Jan Dec (calendar year) E.g., Sri Lanka But many others differ India: Apr Mar Pakistan : Jul June So number of Internet users in per 100 inhabitants in 2013 reported by IN not comparable with PK Having quarterly data eliminates problem Especially important if benchmarks are used for mainstream regulatory work such as interconnection or retail tariff regulation

10 Prerequisites for comparison Internationally accepted definitions and procedures ITU (2010) Definitions of World Telecommunication/ICT Indicators, Geneva: ITU Make sure that the definitions are adhered to ITU has mobile broadband definition; use is inconsistent Mobile broadband subscribers refer to subscribers to mobile cellular networks with access to data communications (e.g. the Internet) at broadband speeds (here defined as greater than or equal to 256 kbit/s in one or both directions) such as WCDMA, HSDPA, CDMA2000 1xEV-DO, CDMA xEV-DV etc, irrespective of the device used to access the Internet (handheld computer, laptop or mobile cellular telephone etc). These services are typically referred to as 3G or 3.5G and include: Wideband CDMA (W-CDMA), an IMT G mobile network technology, based on CDMA 10

11 And whose data do you use? # of internet subscribers (millions), India Difference between Year NASSCOM data TRAI Data Ministry of Statistics & PI NASSCOM & TRAI numbers TRAI & Ministry numbers % 1% % 4% % 5% % 4% % 11% % 5% % Note: Based on Financial Year e.g refers to April 1999 Mar 2000 Source: NASSCOM Strategic Review 2005; TRAI; Ministry of Statistics and Program Implementation, Govt. of India

12 Useful Indicators to measure connectivity FIXED Number of fixed lines Number of fixed wireline phones Number of fixed wireless phones Total fixed access paths per 100 inhabitants MOBILE Number of mobile SIM cards Number of mobile SIM cards prepaid Number of mobile SIM cards postpaid Total mobile SIMs per 100 inhabitants ICT Number of mobile users Number of Internet users IN-COUNTRY ACCESS GROWTH Backbone map for a country Mobile coverage map per operator Base station map per operator BROADBAND Number of broadband connections per 100 inhabitants Can the method for estimating be improved?

13 Proportion of individuals using the Internet Base indicator in composite indices such as: NRI (Network Readiness Index) KEI (Knowledge Economy Index) IDI (ICT Development Index) Best measurement method recommended by ITU: demand-side survey on proportion of individuals using the Internet (from any location) in the last 12 months (HH7)

14 Various methods can be used to estimate the number of Internet users Internet Users = multiplier x Internet Subs (supply side) Where The multiplier = a number used to reflect that each subscription is used by more than one individual (e.g. at kiosks) Internet subscriptions = Internet subscription of all types (speeds, technologies etc. ) Wired, wireless etc.

15 Building on foundations of sand Multipliers chosen at discretion of Country administrations Perverse incentive to use higher multiplier to show high Internet penetration in country Difficulties in counting Internet subscriptions include Over-counting (counting all Internet-capable SIMs, irrespective of use) Under-counting (being able to only count SIMs that have subscribed to a data package; SIMs with only voice packages may use Internet, but operators cannot count; impossible for pre-paid) General difficulty with multiple ownership (one user with fixed and many SIM connections) leading to questionable multipliers

16 Difficult to find rationale for multipliers Country Fixed Internet Subscriptions (000s), 2009 Internet Users (000s), 2009, ITU method ITU multiplier Russia 88,068 59, Mauritius Liberia Liechtenstein Hong Kong, China 3,042 4, Côte d'ivoire Sudan 44 4, Iraq Uganda 30 3, Afghanistan 2 1,

17 Improvement proposed by LIRNEasia % of Internet users increase with Education and Income components of Human Development Index (HDI) of a country Education component - mean of years of schooling for adults and expected years of schooling for children Income component- Logarithm of GNI per capita (PPP$). Health component of HDI is not used, due to lack of evidence that internet penetration is correlated with life expectancy Studied the correlation between Internet penetration rate of countries which conducted demand side surveys and the education and income components of HDI 2011 Data on countries which have conducted demand-side surveys was obtained from ITU and RIA Sub index Education_GNI Index, consisting of education and income components of the HDI index was calculated using DIY HDI: Build Your Own Index on UNDP website. Both Education and Income were given equal weight

18 Strong correlation between Education_GNI Index and Internet penetration Proportion of individuals using the Internet y = 1.26e 4.8x R² = HDI_EdGNI Education_GNI Index 2011

19 Step 1: If survey is available, use it since survey results are first best If representative survey from regional organization is available, use their data (e.g. RIA) If survey from current year is not available, use previous year s data with adjustment Adjust by average growth for country grouping (e.g., middle income countries etc.)

20 Step 2: In the absence of survey data use Education_GNI Index to estimate proportion of Internet users Derive model using income and education components of Human Development Index (HDI) vs. Internet penetration rate for countries which have conducted a survey (annually after HDI report has been released) Use this model to impute % of Internet Users for countries which have never conducted a survey If Internet penetration rate provided by country administrator is within +/- 7 percentage point band around calculated estimate -> use country reported figure Else use imputed figure

21 Proportion of Internet users according to ITU 2011 Less than 30% countries show different Internet penetration rates Oman Antigua & Barbuda Kuwait Bahamas Barbados Andorra Gabon Cuba Libya Turkmenistan Proportion of Internet users according to new method 2011 X Survey data from RIA but not same as ITU Internet penetration rate

22 PRICE & AFFORDABILITY

23 Broadband Baskets: a realistic method of price comparison In selecting an operator, consumers are likely to think about ALL costs including Connection charge, monthly rental etc. ITU ICT price basket methodology takes these issues into account and has created Broadband Baskets consisting of Monthly cost of 1 GB use per month with at least 256kbps connection for a period of 24 months (includes Initial Connection Fee/24) Affordability measured by dividing the cost of the Broadband basket by National average monthly GNI per capita RIA (Research ICT Africa) has further developed this methodology and also measure the cost of the following baskets in addition to the ITU basket Monthly cost of uncapped use per month with at least 256kbps connection for a period of 24 months.

24 Affordability of Fixed BB is increasing in developing countries, but still higher than developed countries Source: ITU, Measuring the Information Society 2013, D/Statistics/Documents/publications/mis2013/MIS2013_without_Annex_4.pdf

25 What about other prices? E.g. BB, wholesale & retail? With 83 footnotes in the most recent publications we did

26 QUALITY

27 Measuring BB quality: trade offs across differing approaches (who can measure?) Diagnostics conducted by Service Providers (ISPs/operators) Pros Easy to implement Cons Results based on equipment placed in the most optimized points of the network Not representative of the actual speeds Users National Regulatory Authorities (NRAs) Represents actual user experiences In a position to request operator involvement when necessary Assumes user s PC is virus-free, with no parallel process running etc. Dependant on user s willingness to participate Large files impact user s data limits Known test locations will prompt operators to optimize networks in selected areas 27

28 Download (kbps) Download speeds: Indonesia performs among the lowest (2014) H 1100 H 1500 H 1800 H 2000 H 2300 H BSNL (1Mbps)-Bangalore,IN BSNL (4Mbps)-Delhi,IN NTC (512kbps)-Kathmadu,NP SLT (2Mbps)-Colombo,LK Telkom Speedy Instant (512kbps)-Jakarta,ID 3BB (10Mbps)-Bangkok,TH BSNL (4Mbps)-Chennai,IN Dhiragu (512kbps)-Male,MV PTCL (4Mbps)-Karachi,PK Dialog LTE (4Mbps)-Colombo,LK Internux LTE (72Mbps)-Jakarta,ID

29 Actual vs Advertised (%) Delivers what was promised (advertised): Indonesia is not bad (2014) H 1100 H 1500 H 1800 H 2000 H 2300 H BSNL (1Mbps)-Bangalore,IN BSNL (4Mbps)-Delhi,IN NTC (512kbps)-Kathmadu,NP SLT (2Mbps)-Colombo,LK Telkom Speedy Instant (512kbps)-Jakarta,ID 3BB (10Mbps)-Bangkok,TH BSNL (4Mbps)-Chennai,IN Dhiragu (512kbps)-Male,MV PTCL (4Mbps)-Karachi,PK Dialog LTE (4Mbps)-Colombo,LK Internux LTE (72Mbps)-Jakarta,ID

30 Kbps per USD Value for Money: Indonesia highest (2014) H 1100 H 1500 H 1800 H 2000 H 2300 H BSNL (1Mbps)-Bangalore,IN BSNL (4Mbps)-Delhi,IN NTC (512kbps)-Kathmadu,NP SLT (2Mbps)-Colombo,LK Telkom Speedy Instant (512kbps)-Jakarta,ID 3BB (10Mbps)-Bangkok,TH BSNL (4Mbps)-Chennai,IN Dhiragu (512kbps)-Male,MV PTCL (4Mbps)-Karachi,PK Dialog LTE (4Mbps)-Colombo,LK Internux LTE (72Mbps)-Jakarta,ID

31 Useful Indicators to measure Quality Voice Quality Call drop rates % of connections with good voice clarity Call success rate Broadband Quality Broadband upload/ download speed (kbps/mbps) RTT or Round Trip Time (mili-second Jitter (mili-second) Packet-Loss (as a %) Broadband availability (as a %)

32 Quality is more than download speed Service Download (kbps) Upload (kbps) Latency (Round Trip Time, RTT) (ms) Jitter (ms) Packet Loss (%) Browsing (Text) Browsing (Media) Downloading Transactions Streaming media VOIP Games Highly relevant; ++ Very relevant; + Relevant; - Irrelevant RTT has implications on client-server interactive systems - Jitter adds to the noise of the transmission - Packet Loss affects streaming media 32 Source: Gonsalves, T.A & Bharadwaj, A. (2009)

33 INDUSTRY-STRUCTURE INDICATORS

34 Do you know a competitive market when you see one? There was only ONE broadband service provider (Company A) in the country until Since then, there has been 4 service providers: A, B, C, D. Is this a competitive industry? What if we saw this? Year A s share B s share C s share D share % % 2% 2% 1% % 1% 2% 2% %.5% 2.5% 2% % 0.25% 2.75% 2%

35 HHI (Hirschman Herfindahl Index) is basic measure of market concentration Define Market Fixed? Mobile? Voice telephony (fixed and mobile)? Internet Services? Identify market share of each operator M1, M2, M3. Subscriber share, revenue share, minute share? HHI = (M 1 ) 2 + (M 2 ) 2, (M 3 ) 2 + +(M n ) 2 US Dept of Justice says Greater than1800 concentrated market Between moderately concentrated Less than 1000, concentrated M&A activity increasing HHI by100+ and HHI >1800 automatic review (etc.)

36 But what is the market? Fixed? Mobile? Voice? BB? Substitutability/elasticity India, BB market shares India, Mar Mobile HHI = BB HHI = Fixed HHI = 7034 MTNL 9% India, fixed market shares Other Private 8% Tata (20) 9.32% Idea (11) 9.19% India, mobile market shares Aircel (9) 4.06% Spice (2) 1.61% BPL (1) 0.49% MTNL (2) 1.35% HFCL (1) 0.11% Shyam (1) 0.04% Bharti (23) 23.74% Reliance (23) 17.54% BSNL 83% BSNL (21) 15.62% Vodafone/Hutchison (16) 16.90%

37 Market share based on SIMs? Revenue? Minutes? What if SMP definition was 60% for price regulation?

38 Market segmented by wholesale vs. retail E.g., Ofcom (UK regulator) reports wholesale (BT dominated, HIGHLY concentrated) vs. retail (less concentrated, many ISPs including BT) Other ways

39 IN UNDERSTANDING THE HEALTH OF THE ICT SECTOR

40 Traditionally prominance was for supply side data Supply side data = data produced by the suppliers of services: MNOs, equipment manf. Reluctance to share, even when demanded by regulation Incentives to over- or under-report Not comparable due to lack of agreement on definitions Internet user (good enough for most most people) daily active internet user (useful to operators)

41 Demand-side data: great for some measures, not for others. The right mix? Understand perceptions, opinions, feelings, satisfaction levels UK broadband satisfaction survey Combined with crowd-sourced testing LIRNEasia electricity sector customer satisfaction survey in LK, IN, BD IN worst actual performance But highest satisfaction levels

42 Big Data: bridging the gap between expressed vs. revealed preference How many minutes does it take, on average, for a vehicle to get from point A to B? Can survey ppl reasonable estimate Can do traffic monitoring estimate also But most people have cell phones CDR or VLR Analyze the digital trace

43 In short, when looking at supply-side data, QUESTION EVERYTHING Question EVERYTHING Who reported it? What incentives did reporter of data have? What was the data collection method? Is it a reasonable representation? Does the data in isolation say a story that s different from the data that s compared to others (over time, to other countries, etc.) Where possible, triangulate (supply+demand)

44 COMPOSITE INDEXES

45 Networked Readiness Index Figure 2: The Networked Readiness Index structure 1.1: The Networked Readiness Index 2014 Component subindexes Pillars Environment Political and regulatory environment Business and innovation environment Infrastructure and digital content Readiness Affordability Networked Readiness Index Skills Individual usage Usage Business usage Government usage Impacts Economic impacts Social impacts

46 Networked Readiness Index Networked Readiness Index : Breakdown of indicators used in the Networked Readiness Index 2014 by data source EXECUTIVE OPINION SURVEY 27 INDICATORS (50%) INDICATORS FROM OTHER SOURCES 27 INDICATORS (50%) TOTAL: 54 INDICATORS

47 rvice Index Figure 1.1. The three components of the E-Government De UN e-gov survey munication ture Index pital Index Expert assessment of online Presense of 193 states + Data from int l orgs OSI 1/ 3 EGDI HCI 1/ 3 Figure 1.1. The OSI Online Service Index TII 1/ 3 TII Telecommunication Infrastructure Index Chapter 1 presents an overview and broad analysis of th E-Government Survey data. It presents e-government dev and regional levels. It also analyzes the relationships of the HCI Human Capital Index

48 A4AI/Web Foundation: The affordability index Mix of subjective, perception indicators (survey) + objective data (mostly supply-side) No indicators of price or affordability!. One respondent per country in 2013 now 2

49 Composite indices Are great for getting attention of nations Countries want to lead; Donors love them May not stand scientific interrogation? Why is one sub-index weighed 1/3 while another is weighted 2/3? Etc. Often suffer from the same issues identified in supply-side and demand-side data How many respondents in expert survey? What incentives? How old/new and how comparable is objective data?