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GEORGE FORD CHIEF ECONOMIST THE PHOENIX CENTER July 15, 2009 National Press Club The Broadband Adoption Index: Policy Paper No. 36.

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Presentation on theme: "GEORGE FORD CHIEF ECONOMIST THE PHOENIX CENTER July 15, 2009 National Press Club The Broadband Adoption Index: Policy Paper No. 36."— Presentation transcript:

1 GEORGE FORD CHIEF ECONOMIST THE PHOENIX CENTER July 15, 2009 National Press Club The Broadband Adoption Index: Policy Paper No. 36

2 Create an economically meaningful and policy relevant index of broadband adoption that also is capable of handling heterogeneous connection modalities (e.g. fixed and mobile).

3 If the $7B achieves universal availability over the next few years, the U.S. will probably not change rank.

4 General Form Goal: 1.Provide for meaningful performance evaluation across geo-political units (intra- and internationally). 2.Incorporate the underlying economics of adoption and deployment 3.Accommodate different connection modalities

5 Population is not a Target Population is not a target of adoption as implied by OECD statistics In the U.S., telephones were ubiquitously available and nearly universally adopted, yet TEL/POP was only 0.493. In Sweden, it was the same, but their TEL/POP was 0.686.

6 Broadband Nirvana (Phoenix Center Policy Paper No. 29, July 2007) CountrySubscriptionRankCountrySubscriptionRank Sweden0.5411 New Zealand0.39816 Iceland0.4892 Portugal0.39217 Czech Republic0.4783 Japan0.3918 Denmark0.4784 United Kingdom0.38919 Finland0.4775 United States0.3820 Germany0.4496 Luxembourg0.37821 Netherlands0.4377 Greece0.36222 Switzerland0.4298 Slovak Republic0.35123 France0.4249 Ireland0.34724 Canada0.41910 Poland0.34125 Hungary0.41111 Spain0.33826 Belgium0.4112 Australia0.31527 Austria0.40613 Korea0.25428 Italy0.40414 Mexico0.24729 Norway0.40315 Turkey0.21230

7 BB/POP tells you Little 0 0.2 0.4 0.6 0.8 1 Share of Potential Market Population 1.0 OECD (BB/POP) Ignores business connections (could assume proportional to households and scale up; no loss of generality). H max = 0.33 Economy A Pop/HH = 3 (eg, Portugal) H max = 0.50 Economy B Pop/HH = 2 (eg, Sweden) Range of Deception (Economy A outperforms B, but BB/POP says otherwise.)

8 Trends in OECD Rank: The Fall (Connections/Capita) 20012002200320042005200620072008 Korea IcelandDenmark Canada DenmarkKoreaNetherlands SwedenBelgiumIcelandNetherlands Iceland U.S.IcelandDenmarkIcelandDenmarkKorea Norway DemarkNetherlandsCanadaSwitzerland SwedenBelgiumSwitzerlandFinlandNorway Finland NetherlandsSwedenBelgiumNorwayFinland Korea U.S.Japan CanadaSweden SwitzerlandFinlandSwedenCanada Luxembourg U.S.NorwayBelgium Canada SwedenJapanUK U.S.UKLuxembourg Belgium U.S.France Japan Germany U.S. US

9 Trends in OECD Rank: The Rise (Connections/Capita) 20012002200320042005200620072008 Korea IcelandDenmark Canada DenmarkKoreaNetherlands SwedenBelgiumIcelandNetherlands Iceland U.S.IcelandDenmarkIcelandDenmarkKorea Norway DemarkNetherlandsCanadaSwitzerland SwedenBelgiumSwitzerlandFinlandNorway Finland NetherlandsSwedenBelgiumNorwayFinland Korea U.S.Japan CanadaSweden SwitzerlandFinlandSwedenCanada Luxembourg U.S.NorwayBelgium Canada SwedenJapanUK U.S.UKLuxembourg Belgium U.S.France Japan Germany U.S. US

10 Trends in OECD Rank: The Rise (Connections/Capita) 2007 Denmark Netherlands Norway Switzerland Iceland Finland Korea Sweden Luxembourg Canada 1996 PSTN Subscription Rank TOP 10 Denmark Netherlands Norway Switzerland Iceland Finland Sweden Luxembourg Canada 10 THE PHOENIX CENTER Telecom Rank not in sequence.

11 OECD Rank (Fixed Telephones 1996; Broadband Dec 2007) NameBB # TEL # NameBB # TEL # NameBB # TEL # Denmark12UK1112Ireland2123 Netherlands210Belgium1217Italy2220 Norway37France139Czech Republic2325 Switzerland45Germany1413Hungary2426 Iceland56United States1516Portugal2524 Sweden61Australia1611Greece2614 Korea721Japan1715Poland2729 Finland88Austria1819Slovak Republic2827 Luxembourg94New Zealand1918Turkey2928 Canada103Spain2022Mexico30 90% Match80% Match

12 Food for Thought Top 10 in broadband; 9 are Top 10 in Wireline Telephone (only 5 in 2001) Bottom 10 in broadband; 8 are Bottom 10 in Wireline Telephone (7 in 2001) Of the 14 above the U.S. in broadband, 12 are also above the U.S. in telephone subscriptions Of the 15 below the U.S. broadband, 12 are also below the U.S. in telephone subscriptions 12 THE PHOENIX CENTER

13 Convergence to Telephone Rank Time Telephone Rank – Broadband Rank * Most other countries follow a similar path. 13 THE PHOENIX CENTER

14 Terminal Expectations: Broadband and Wireline Telephone Ranks Year (June Data) CorrelationAvg. Difference in Ranks 20020.6005.8 20030.6425.5 20040.6685.1 20050.7284.4 20060.7724.1 20070.8243.3 20080.8613.1 14 THE PHOENIX CENTER

15 Other Issues with OECD-Style Metric Today, it includes only Fixed Connections At the request of a few countries, OECD now plans to collect and report mobile broadband in the near future. Broadband = 256kbps or more Counted if you buy it or use it (in a specified interval of time) But how is the data to be used as a measure of adoption performance?

16 OECD Style Index Fixed = Fixed/Population ? Index Mobile = Mobile/Population ? How do you rank across 2 dimensions? Can we just add the two for a single index? Do we get the SIM card problem for Europe? What about countries that do mostly one and hardly any of the other? What if the count is high but due to some having multiple connections rather than many having at least one form of connection? How do we deal with the fact that fixed is typically shared, mobile is often not (scaling problem).

17 How to Combine the Two? Can we just add: Fixed + Mobile Fixed is mostly shared, Mobile is mostly consumed by individuals Mobile counts will swamp fixed counts Should we scale Fixed by the share rate Fixed + Mobile/ShareRate (sharerate may be hh size) Assumes Mobile is a low quality fixed How do homogenize unlike things? We convert the counts to values What is the value of fixed? What is the value of mobile?

18 One Modality v i * = average social value of a connection of modality i at the target q i * = quantity of connections of modality i at the target

19 What is the Value of Broadband? Willingness to Pay (w) Social Premia (e) Externalities Spillovers Etc. Cost of Production (c) Net Social Value v = w + e - c

20 Target Adoption w c - e $ q*q* q v=0 c q

21 Social Value w c - e $ q*q* Social Value q v=0

22 Maximum Subscription is Not Ideal As long as c - e > 0, 100% consumption is not ideal. w c- e $ q*q* A q v=0 W Welfare Loss from excess consumption. qi*qi* q i v=0 V i * V i v=0 ViVi Social Value (V) Social Value = A - B

23 Optimal Consumption Depends on Costs If costs are higher, then optimal quantity is lower. w c- e $ q*q* w $ q*q* q Low Cost Market High Cost Market q

24 Optimal Consumption Depends on Demand If demand is lower, then optimal quantity is lower. w c- e $ q*q* w $ q*q* High Demand Market Low Demand Market q q

25 Simple Graph w c - e $ q*q* Avg. Value = v* = V/q* Soc. Value = v*q* = V q V

26 BAI at Time t Assumption: Marginal, thus average, valuation declines over time. Here, highest valued users adopt first. w cici $ q*q* q1q1 A B C q v=0

27 Two Modalities (f, m)

28 Does it simplify?

29 One Modality Diminishing Marginal Valuation

30 Simulation Two Modalities, f and m f is shared m is personal c f =40; c m = 20 Max value for m is 100 Average share rate: k = 2 Scale f demand to 200 (= 100·2) Personal Market = 2,000 persons Shared Market = 1,000 units (= 2,000/k) m is a mild net substitute for f

31 Willingness-to-Pay (Demand) System

32 Simulation Algorithm cici vivi qiqi qi*qi* q i v=0 Compute q *, V *, then scroll through quantities up to q v=0. We compute V at each quantity then compute weights. Do so in 10 percentage point intervals, so we have a 11 x 11 matrix of w i s.

33 BAI Simulation: Two Modalities

34 BAI Simulation: Two Modalities (Zero costs; no substitution)

35 BAI Simulation: Alternatives

36 Can this be done?

37 Econometric Implementation Data on What is Purchased? How much is Paid? Demographics of Buyers Cost data by modality BAI can be computed using this data Example provided in Paper No. 36

38 Target Setting

39 Some Portugal Targets Achieve at least 50% household broadband adoption. Increase public access to public Internet locations (16 per 100 POP). Increase number of computers in schools to one per five students. 100% of Central Government institutions with broadband access. 100% of hospitals with broadband access.

40 Target Setting It is unreasonable to expect a relatively poor and uneducated country to have the same broadband deployment and adoption rates as a relatively rich and educated country. Comparing such countries on per-capita terms says nothing about the success or failure of broadband policies. 50% adoption in Mexico or Turkey may be stellar, but in the U.S. would be considered a failure.

41 Target Setting VariableCoeft-stat C-9.95-4.81 LN(PRICE)-0.39-2.56 LN(GDPCAP)0.352.46 LN(GINI)-0.73-3.18 LN(AGE65)-0.29-2.60 LN(URBAN)0.993.89 LN(TEL)2.813.50 LN(TEL)^2-0.36-2.73 N = 30; June-08 data; R 2 = 0.93 Nearly all (93%) of the differences in fixed connections per capita across countries are explained by few demographic and economic endowments.

42 Summary Performance is a value-based concept Any modality that generates value must be included in performance measures Per- Capita Normalizations are misguided Anyway, not clear how to do it with multiple modalities Combining heterogeneous modalities is tricky, but the problem is understood The underlying economics of deployment and adoption must be considered for good policy Countries vary in their demand and cost profiles Maximal deployment/adoption assumes external effects are enormous

43 Summary Avoid the willy-nilly by focusing the analysis on the components of target setting Willingness to Pay Realistic size of the Social Premia Cost of deployment

44 44


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