Fixed-Mobile Substitution
and the
Promotion of Universal Service
Glenn A. Woroch
University of California at Berkeley
Universal Service Policy
Meets Mobile Ubiquity
Should mobile access be counted toward
the goal of universal service?
 Should subsidies for fixed service be
reduced or eliminated?
 Should mobile access be subsidized in
certain markets, e.g., rural areas?
►Answers depend on fixed-mobile
substitution

Lifeline Program

Targeted subsidy to promote telephone access
 Federal
program implemented by 50 states.
 Discount off monthly phone bill set by FCC, states.

Eligibility
 Income
test: HH income below threshold based on
Federal Poverty Guidelines.
 Program test: HH participates in a federal assistance
program (Medicaid, SSI, etc.).
 HH must “self certify” each year.
Lifeline Program

Implementation
 Eligible
Telecommunications Carries (ETCs)
implement through billing.
 Discounts range $6.75-$14.78 with an average of
$11.00
 Composed of federal SLC ($6.75), plus state match,
plus federal 50% match (up to $1.75).
 Only one fixed/mobile line covered per household.

Participation
 ~19
million eligible but only ~6 million participate.
 Overwhelmingly on fixed not mobile.
Lifeline Programs Across States
State
State +
federal
discount
Avg annual
discount
Income
eligibility
as % of
FPG
Estimated
participation
rate
% of
households
participating
% of sample
households
with Lifeline
California
$12.00
$128.32
150%
119.2%
27.79%
32.88%
Florida
$12.00
$130.21
125%
13.5%
2.12%
5.4%
Illinois
$10.85
$94.40
125%
9.0%
1.26%
3.8%
Maine
$12.00
$130.13
130%
99.2%
Massachusetts
$14.50
$160.96
175%
28.4%
6.77%
15.11%
Michigan
$9.75
$103.92
150%
20.1%
3.74%
3.62%
New Jersey
$6.75
$69.62
150%
5.9%
0.95%
4.26%
$10.74
$115.87
150%
34.6%
8.31%
14.48%
$6.75
$76.81
150%
19.9%
3.76%
5.15%
Pennsylvania
$10.50
$110.92
150%
5.5%
1.03%
2.48%
Texas
$12.00
$121.19
125%
18.6%
3.5%
1.68%
New York
Ohio
U.S. Total/Average
$121.97
30.7%
Household Panel Dataset

TNST’s ReQuest® Market Monitor
household panel
 Nationwide,
30K+ per quarter, 10 quarters
(3Q99-4Q01).
 Survey responses and demographics.

TNST’s Bill Harvesting® database
 Fixed
and mobile “bill harvesting” (~ 25%
response rate).
 Not a panel but some re-sampling (~ 10% of
bill submitters).
Lifeline Participation



Identified by service designation on household
fixed line bill.
Lowest income group participation rate ~30%,
gradually falls with income to 2% for highest
group.
Lifeline also related to:
 Marital
Status
 Size of household
 Composition of household
 Ages of children
$7 der
,5 $
$1 00 7,50
0,0 - $ 0
9
$1 00 - ,99
2,5 $1 9
2
0
$1 0 - ,49
5,0 $1 9
4
$2 00 - ,99
0,0 $1 9
9
0
$2 0 - ,99
5,0 $2 9
4
$3 00 - ,99
0,0 $2 9
9
0
$3 0 - ,99
5,0 $3 9
4
$4 00 - ,99
0,0 $3 9
9
0
$4 0 - ,99
5,0 $4 9
4
$5 00 - ,99
0,0 $4 9
9
0
$6 0 - ,99
0,0 $5 9
9
$7 00 - ,99
0,0 $6 9
9
$7 00 - ,99
5,0 $7 9
00 4,9
$1 - $ 99
00 99
,00 ,9
0 o 99
ro
ve
r
Un
Percent of Sampled Households
Lifeline Participation by Income
35%
30%
25%
20%
15%
10%
5%
0%
Lifeline-Mobile Decision
Household income, size, state
Eligibility
LL participation
LL subsidy
Awareness
Household education, mobility, carrier switching
Access
Choice
Fixed-Mobile Cross-Price Effects


Lower fixed charges of Lifeline could elicit cross
price effect on mobile subscription
But the Lifeline “experiment” is not random
 Might
mobile response to lower fixed price be an
“income effect”?

Controlling for income & demos, wish to see
fixed price effect of Lifeline on mobile
 Check
if Lifeline has an incremental effect on HH
purchase of cable, personal, Internet to see if it is a
“pure price effect”
Empirical Problems
Errors arise in measuring fixed and mobile
prices.
 Self selection into Lifeline program.
 Unobserved household characteristics.

► All likely correlated with determinants of
mobile subscription decision.
Solutions

Re-sampling of households
 Controls

for time-invariant characteristics
Instrumental variables
 Purges
prices of common unobservable
household factors

Two stage estimation
 Regress
fixed and mobile bills on instruments
 Probit choice model of cellular subscription on
fitted prices
Cross Elasticity Estimates
Base Model
Low
Income
(<$20k)
High
Income
(>$20k)
Complete Sample
1.42
1.88
1.06
Without Mobile
Phone Initially
1.79
1.97
1.62
With Lifeline
Currently
1.73
2.17
0.83
Never Lifeline
1.58
-0.22
1.85
Cross Elasticities (cont’d)
Complete
Participation
States*
Partial
Participation
States
No Mobile
Lifeline
States**
Mobile
Lifeline
Allowed
Complete
Sample
0.92
1.39
2.35
1.19
Without Mobile
Phone
Initially
0.85
2.03
3.03
1.72
With Lifeline
Currently
0.08
2.06
2.43
1.62
Never Lifeline
-0.53
1.72
10.37
1.46
* - California and Maine; ** - California, Illinois, New York
Two Policy Experiments
1.
Withdraw the Lifeline discount from all
participating households
2.
Impose the average Lifeline discount on
all non-participating, eligible households
Policy Simulation
Experiment
Withdraw
Lifeline
Expand
Lifeline
Target
Population
Base Case
Mobile
Change
Current
Participant
20.4%
+9.8%
No Lifeline,
Income < 20k
14.3%
-4.5%
Conclusions





Mobile ubiquity presents challenges to the
design of universal service programs.
Modification, or elimination, of existing subsidies
turns on accurate measure of fixed-mobile
substitution.
A key universal service program, Lifeline,
provides a natural experiment to estimate FMS.
After correcting for endogeneity problems, cross
elasticities of access demand are quite large.
Simulation of expansion/contraction of Lifeline
confirms that mobile subscription significantly
impacted by fixed subsidies.