The evolution of lobbying coalitionsCo-filing behavior in FCC docket 01-92 on Inter-carrier

Compensation

Work in progress, 9/30/2009Pierre de Vries, Economic Policy Research Center

University of Washington, Seattle

Acknowledgements

Bill Cline and Elhadji Sy (FCC), for providing the underlying public data in a usable form

Marc Smith and Tony Capone, for developing and supporting the NodeXL visualization tool

Jonathan Banks and Anthony Jones (USTelecom), for help in extracting the “et al.” data, and Risa Pavia (UW) for help in creating the fix list

Conclusions

1. Graph-theory clusters represent real-world alliances

2. Tracking the evolution of clusters can reveal shifts in alliances

3. Improving ECFS interfaces and data quality will improve public knowledge of lobbying activity

Co-filing AnalysisMetadata from FCC ECFS database, FCC docket 01-92, April 2001 –December 2008

– 2,9015 filings, 756 unique filers

Subsidiaries and “doing business as” entities are usually grouped together

– e.g. Cable and Wireless plc, Cable & Wireless, Cable and Wireless USA, Cable & Wireless North America.

– But for some large players, kept parts separate, e.g. Verizon and Verizon Wireless; AT&T and AT&T Wireless

Sub-set of FCC docket 01-92 where two or more entities file together

– Entities that only filed on their own are not shown

– Used either metadata given as multiple entity names, or extracted entities from filed documents where “et al.” or “filed on behalf of” given in metadata

Trade associations and coalitions have not been unpacked into their constituents

– Sometimes distorts data, e.g. AT&T is represented both on its own account and hidden within the “Missoula Plan Supporters” node

– Coalitions unpacked: Oregon Rural LECs, Five State Regulatory Commissions, Coalition for Rational Universal Service and Intercarrier Reform

Company name changes on acquisition/merger not accounted for:

– Frontier Communications Corporation was formerly known as Citizens Communications Corporation

– Don’t distinguish between “old” and “new” AT&T, or Verizon before and after MCI merge

Filing intensity varies over time

NPRM comments (8/21/01)

Reply comments (11/05/01)

Responses (10/18/02) to T-Mo et al Petition for Declaratory Ruling (filed 9/6/02)

FNPRM comments (5/23/05)

FNPRM reply comments (10/20/05)

Responses (10/25/2006) to FCC PN (issued 7/25/06) on Missoula Plan (filed 6/24/06)

FNPRM issued 11/5/08

Links between 01-92 and other dockets

All linked dockets 2001-2008, filtered: – Sub-graphs level 1.5 centered on 01-92 (i.e. all nodes linked to 01-92, and links between them)

– edge weight >40 (dockets on either side of the edge were noted together on a filing more than 40 times)

Edge width and color both indicate edge weight: wider/pinker means more joint mentions

FEDERAL-STATE JOINT BOARD ON UNIVERSAL SERVICE

IMPLEMENTATION OF THE LOCAL COMPETITION PROVISIONS IN THE TELECOMMUNICATIONS ACT OF 1996

ACCESS CHARGE REFORM

In the Matter of Inter-Carrier Compensation for ISP-Bound Traffic

In the Matter of Lifeline and Link-Up

Numbering Resource Optimization

Request Petition for Declaratory Ruling that AT&T's Phone-to-Phone IP Telephony Services are Exempt from Access Charges

In the Matter of IP-Enabled Services

In the Matter of Universal Service Contribution

Methodology Federal-State Joint Board on Universal Service

1998 Biennial Regulatory Review

In the Matter of Establishing Just and Reasonable Rates for Local Exchange Carriers

In the Matter of Federal -State Joint Board on Universal Service High-

Cost Universal Service Support

Petition of AT&T for interim declaratory ruling and limited waivers pleading cycle

established

Companies typically either always file solo, or always jointly

All solo (0%)

(0%, 20%]

(20%, 40%]

(40%, 60%]

(60%, 80%]

(80%, 100%)

All joint (100%)

498

3924 25

8 10

152

Percentage of filings made jointly

Num

ber o

f fier

s 25 entities filed with others in 40%-60% of

cases, e.g. tw telecom, Pac-West

498 entities always filed alone, e.g.

BellSouth, NARUC

152 entities always filed with someone

else, e.g. Broadview, Maine PUC

Solo filers excluded from

co-filing analysis

Links between Filers

If the names of A and filer B both appear on a particular filing…

… they are treated as being linked

A B

The more often they file together… … the darker the line connecting them (think of the lines being

stacked one on another)

A B

Filed on Date 1

A B

Filed on Date 1

A BA B

Filed on Date 3

A BA B

Filed on Date 2

A B

Different co-filing occurrences… … lead to a network structure

Filed on Date 1

A B

So far the graphs looked at all filings simultaneously. Looking at a sequence of dates shows different links at different times:

Date 1 Date 3

A B

Filed on Date 2

A B

C

A B

C

A B

Filed on Date 3

B

C

Date 2

A B

C

A B

C

A B

C

Deriving a Network Structure

The area of the blob is proportional to the total number of filings made over the whole period (solo or joint)

Additional node attributes (1): Size

AT&T filed many times (big blob), whereas PointOne filed seldom (small blob).

However, one can see that they’re roughly equally linked to other filers. That means that AT&T filed more often on its own.

The more pink a blob is, the more important the filer is in the network.

The color represents the “eigenvector centrality”. A filer with high eigenvector centrality is connected to many filers who are themselves connected to many others. This “centrality metric” goes beyond simply counting the number of connections a filer has; connections to filers who are themselves highly connected confer more influence that connections to less well connected filers.

Google’s PageRank algorithm is a variant of this metric; a page is considered important if many other important pages link to it.

Additional node attributes (2): Color

• New Global Telecom and Verizon have the same influence in this graph (same color), even though Verizon filed more often (bigger blob)

• GCI, CompTel, and NCTA filed the same number of times (same size), but CompTel is the more influential (pinker), and GCI less (bluer)

• Even though CTIA filed often (big blob) it’s not very influential/connected in this network (blue color)

All co-filings 2001-2008 on inter-carrier comp docket 01-29

Nodes are laid out (by hand) to respect clustering

Clusters calculated using Clauset Newman Moore (2004) algorithm (Wakita & Tsurumi 2007 optimization) to find community structure, gathering vertices into groups such that there is a higher density of connections within groups than between them

A Time Series

Underlying data set has day-by-day granularity; these snapshots are integrated

over much longer periods

2001-2002

T-Mobile et al petition for

declaratory ruling

CLEC reply comments to

NPRM

2003-2004

Intercarrier Compensation Forum,

filed ICF Plan 5 Oct 2004

“Indep. Wireless Carriers”: T-Mobile, W Wireless, Dobson

“CMRS Petitioners”: T-Mobile, W Wireless, Nextel

CLECs’ “Cost-Based Intercarrier

Compensation Coalition” (CBICC)

2005 – summer 2006

Major CLECs – FNPRM comments & replies

Rural LECs and their associations

CLECs

CLECs, some eventually merging e.g. Lightship, CTC, Conversent; and Xspedius &

tw telecom

Fall 2006 – end 2007Missoula Plan Allies

Missoula Plan Opponents:

Mix of CLECs, ILECs and Indep. Wireless

Oregon Rural LECs, supporting Missoula Plan

Jan – July 2008

The calm before the storm

Aug/Sep 2008

CLECs opposing Verizon’s September 12

proposal, incl. uniform rate

ILEC/IXC coalition: Ex parte advocating federalizing VOIP, uniform comp rate

for all traffic

Oct 2008Five State regulatory

commissions objecting to “eleventh hour filings”

Mid-size rural LECs opposing flat rate comp, supporting status

quo OPASTCO/WTA Plan

Broadening CLEC coalition opposing change towards flat

rate

Small ILECs trying to slow down process

Nov/Dec 2008

Rural cellular – note they’re closer to the CLECs than the RLECs

Opposition to AT&T/IXC “self-help” from small

LEC and conf-call players

“Coalition for Rational Universal Service and Intercarrier Reform” –

urban & rural CLECs

Summary of Coalition Patterns

Rural LECs and their associations keep to themselves

Opponents are connected: ILECs, CLECs,

and cellular

Top 20 Impact Depends on Chosen Metric

Times Filed Number of Pages Joint Filings Connectedness (Degree)

Influence (Eigenvector)

AT&T Intercarrier Comp. Forum XO NuVox Hypercube

Verizon NTCA NuVox Cavalier Cavalier

NTCA Verizon Cavalier XO iBasis

CTIA Qwest Comm. Broadview Broadview NuVox

Qwest Comm. AT&T Pac-West RCN tw telecom

Verizon Wireless NuVox OPASTCO Pac-West Covad

XO XO RCN One CompTel

NuVox Broadview One tw telecom RCN

Level 3 Cavalier WTA T-Mobile One

T-Mobile Pac-West US LEC CompTel XO

Cavalier Verizon Wireless T-Mobile NCTA 360networks

Pac-West RCN tw telecom US LEC NCTA

USTA Nextel Focal Alltel PAETEC

Core Comm. US LEC Cbeyond Cellular South U.S. TelePacific

Sprint NASUCA Alltel McLeodUSA Citynet

US LEC CTIA McLeodUSA Covad Broadview

ITTA Core Comm. Dobson Hypercube nTelos

CenturyTel tw telecom Xspedius PAETEC R&B

Broadview Sprint Nextel iBasis Cellular South

OPASTCO BellSouth Western Wireless U.S. TelePacific Alpheus

* Filers that appear in three or more columns are color coded

CLECs not only band together, but also file a

lot, and often.NTCA carries the water for

RLECs

ObservationsGraph clusters seem to correspond to real-world interests

A large number of filings form one large connected graph (the blob in the center)– It’s connected in aggregate over the whole time series: shifting alliances

– In the course of the proceeding, one can find a link between opposing parties e.g. a proponent of the “Missoula Plan” like AT&T is linked to an opponent like XO via both of them co-filing with the CTIA at different dates (“Six Degrees of Kevin Bacon”)

There are many parties that only co-file once or twice– Most of them are pairs

– There are a few large groups of co-filers that show up only once in the record, and aren’t seen before or after

Frequent Filers are usually different from Cross-Connectors– Frequent filers like AT&T, CTIA and NTCA don’t often file in coalition

– Connectors that bridge alliances (e.g. Hypercube, iBasis) don’t file all that often

– Some fall in both groups, e.g. XO and Cavalier

Value of the approachInsiders can use graphs to identify:– detailed trends at a glance

– potential collaborators or defectors, e.g. by looking for coalition members who are bridges between groups, or peripheral

Outsiders can grasp the overall structure of a proceeding without having to read the entire record

News organizations can use:– cluster evolution to show changes in coalitions

– network structure to guide understanding of search results

Implications for FCCPoor quality of information input by filers impedes transparency– Endless misspellings of company names

– Not all entities involved in a filing are listed

– Filers make mistakes (e.g. mistyping docket number) but can’t remove mistakes; they simply file again

Require more information in metadata– Require all entities names to appear in the Filed on Behalf Of field, i.e. “et al.” not allowed

– Distinguish between ex parte letters and meetings

Use standard web techniques to facilitate data input and retrieval– Require log-in with company ID when submitting data to ECFS

– Require filer name to be registered; subsequently metadata can only be chosen from pre-registered information, not added de novo

– Offer drop-downs and auto-complete to add co-filers

– Provide web interfaces for downloading data in bulk, and as daily feeds

Improve systems for correcting errors– Allow filers to remove incorrect data (only filer can remove what was filed)

– Penalize errors, e.g. by naming and shaming

– Invest in cleaning up old data: requires public/private effort?

CaveatsGraph depends on metadata entered into ECFS by filers, which can be unreliable– misspellings (e.g. ATT for AT&T)

– inaccuracy (e.g. a filing attributed to AT&T was actually on behalf of a number of companies, and so is not counted as a co-filing)

– ambiguity (e.g. there are many companies whose name includes “Citizens”, and they all seem to be different)

Some Bad Data ExamplesBellSouth:

– BellSouth Coration – BellSouth Corpm – BellSouth Corps – BellSouth D.C. – BellSouth TELECOMMUN – BellSouth TELECOMMUNIC – BellSouth TELECOMMUNICA – BellSouth TELECOMMUNICAT – BellSouth TELECOMMUNICATI – BellSouth Telecommunication – BellSouth Cellular CORPOR

Misspellings of “Communications”:– Comminication– Commnications– Communictions – Commuications – Commuincations – Communcations – COMMUNIATIONS – Communicaitions – COMMUNICAITONS – Communicatiions – Communicatins – Communicationas – Communicationsn – COMMUNICCATIONS – Communictions – Communocations – Comunications – Coommunications – Cummunications

California PUC:– CALIFORNIA PUBLIC UTILIL – CALIFORNIA PUBLIC UTILIT – CALIFORNIA PUBLIC UTILITE – California Public Utilites Commission – CALIFORNIA PUBLIC UTILITI – California Public Utilities – CALIFORNIA PUBLIC UTILITIES COMMISSION – California Public Utilities Commission - 99-204 – California Public Utilities Commission and People of the State of

California – California Public Utiltiies Commission – Calilfornia Public Utilities Commission – Commissioners Lynch and Wood, California Public Utilities

Commission – People for the State of California and Ca. Public Utilities

Commission – People for the State of California and Cal. Public Utilities

Commission – People for the State of California and California Public Utilities

Commission– People of the State of California & Public Utilities Commission – People of the State of California and Cal. Public Utilities

Commission – People of the State of California and California – People of the State of California and California Public Utilities

Commission – People of the State of California and Public Utilities Commission – People of the State of California and the Cal Public Utilities

Commissoin – People of the State of California and the California Public Utilities

Commission – Public Utilities Commission of the State of California – State of California and the California Public Utilities Commission – State of California Public Utilities Commission – The People of the State of California and by proxy for CPUC – The People of the State of California by proxy for CPUC

Caveat (ctd): Coalitions are UnderstatedAnalysis puts a lower bound on connectivity– Some connections are not revealed through co-filing; entities may be

linked, e.g. through participation in a trade association, but not file together explicitly

– Co-filing is undercounted since we rely on the metadata entered into ECFS. Sometimes just one company name given, even though there multiple companies involved, or a list of company names may not include all filers. (This data can be obtained from the underlying document, but at the price of significantly more effort.)

– This analysis deals with only one docket; companies may co-file more frequently on other dockets

Conclusions (restated)

1. Graph-theory clusters represent real-world alliances

2. Tracking the evolution of clusters can reveal shifts in alliances

3. Improving ECFS interfaces and data quality will improve public knowledge of lobbying activity