SEIGs, GPIs, and BCAs:
Playing to Different Stakeholders
Dennis Coates and Scott Farrow
Department of Economics
UMBC
1
www.umbc.edu
Outline
•
•
•
•
SEIG
Regional Issues
BCA Issues
Conclusion
2
SEIG is Problematic
• Criticisms not new – Walker (2008)
• Impact themes overlap
– Double counting
– Dubious categorization of costs and benefits
• Impact theme relative importance unclear
– Politically determined
– Not transparent
3
Examples
• Personal entertainment
– Health and Well-Being
– Economic and Financial
– Recreation and Tourism
• Contribution to economic growth
– Economic and Financial: Contribution to GDP
– Economic and Financial: Changes in investment, etc
– Employment and Education: Direct and indirect job
creation
– Employment and Education: Annual and hourly wages
4
SEIG is Problematic 2
• Who are the stakeholders/decision-makers?
– General Public
– Gambling “Interests”
– Policy makers and politicians
• Unstructured information may be better than
none at all
– Unbiased/disinterested research
– Value judgments left to stakeholders
5
SEIG is Problematic
Summary
• Flexibility or All things to all people
• Adding Lemons and Cherries?
• Conflating Positive with Normative
6
Focus on two topics:
• Regional analysis
–
–
–
–
Unit of Analysis
Spillovers
Economic Development
Interjurisdictional competition
• BCA
–
–
–
–
Impacts or markets
Surplus or risk loving uncertainty
Problem or pathological gamblers
Equity
7
Issues in Regional Analysis
•
•
•
•
Unit of Analysis
Interjurisdictional Competition
Spillovers
Economic Development
8
Unit of Analysis
• Anielski and Bratten SEIG
– Four possibilities
• Individual, Household
• Community – neighborhood, town or city; clubs or interest
groups; may be geographic but need not be
• Regions – “larger geographic areas than communities”
• Province
– Two Unanswered Questions
• What is the political jurisdiction for the analysis?
• Given the political jurisdiction, how wide-spread is access to
gambling?
9
Spillovers/Externalities
What is the jurisdiction of the
analysis?
• Vaillancourt and Roy identify geographical dimension
as one of two significant methodological issues –
rationale for Canada as unit of analysis
• Smaller geographic area, the better for extracting
benefits from those other jurisdictions/populations
• Smaller geographic area, the more likely to export
costs onto other jurisdictions/populations
10
Spillovers
• Fiscal Federalism
– Multiple jurisdictions
– Boundaries set so costs and benefits are captured
• Costs
– Gambling
– Travel, etc
• Benefits
– Gambling
– Other
11
Economic Development
• Job creation
– Gambling
– Induced
• Income growth
– Gambling
– Induced
• Tax revenues
• Neighborhood revitalization?
12
Interjurisdictional Competition
• Gambler mobility
– Slot machines in MD
– More venues in BC , AU
• On the border
– Attract gamblers from neighbors
– Retain home grown gamblers
– Spillovers (MA and CT)
• Race to the Bottom
13
Selected Issues in GPIG & BCAG
1. GPIG
2. BCAG
–
Logic models and Surplus
–
Uncertainty
–
Problem or pathological gamblers
–
Equity
14
GPIG
• Within SEIG: Several valuation methods mentioned,
including GPIG and BCA.
• GPIG: suggestion to use modified National Income
and product accounts (e.g. GDP)
– History of concern in GDP for adjustments
(household labor, environment (net dep)…
– GDP: C+I+G+net exports or income (flow, not
stock/balance sheet)
15
GPIG: doesn’t resolve issues
•
GPIG comments (e.g. Anielski, GPINovaScota)
– Not implementing national income accounting : only identify candidates as
subset of SEIG
– Double counting: GDP of gambling + personal expenditures
– Should personal expenditures be wagers net of payouts as suggested? Aren’t
expenditures the wagers and the payouts income?
– Inequality adjustment: more later, how to investigate value judgment?
– Usual co-morbidity issues
– Property value (NIPA is a flow net of depreciation, property would need
separate balance sheet)
– Cost of bankruptcy, lost productivity: these are mediated in part through
markets; expected to be built into wages and risk based interest rates,
– Addiction: change in surplus mentioned but actually change in expenditure
(no surplus measures in GDP), more later
16
Logic Model: SEIG, GPIG, and BCA
Region or Province is central actor? What is causing what?
17
BCA: Links among markets, Gov’t and Externalities
Partial Equilibrium (can extend to general equilibrium)
Standing: Whose impacts count…e.g. Provincial
Input Markets
Government
Revenues and
expenditures
Gambling market
Consumers: CS
Producers: PS
(WTP: Risk
Loving)
Labor Market
Gambler’s income
Regional employment
Financial Markets
Borrowing/lending
External Effects
Household
Crime
Community
Legal conditions and multiple
market interactions
18
Is Gambling Consumer Well Analyzed?
• Fundamental issue of consumer behavior
Gamblers must be risk loving in this activity since the payout
is less than “fair”
• Complex links between surplus and Willingness to Pay
with uncertainty (latter preferred with uncertainty):
– Broader economic literature not resolved (expected and
non-expected utility) people such as two nobel prize
winners (Freidman, Markovitz)
• Current candidates:
• Consumer “expenditures”, but that is usually that is what is
deducted from total benefits to get consumer surplus
• Standard surplus (Grinols…at margin no effect)-• Distance surplus, but no link to change in price (Grinols)
• What happened to valuation under uncertainty?
19
Expenditures and Surplus contrasted
Fundamentally different measures
Price
P
Demand
Q
Quantity
Expenditures (P*Q)
Consumer surplus (Total WTP less expenditures)
20
Risk Loving, and Paying to Gamble
at point of indifference
(Contrasts: Insurance--paying not to gamble)
Gamblers: Z= ex-ante WTP for access to gamble (including travel and
house take); if cost is less, a “surplus” but not the standard surplus.
Utility
Z
E(U(G))=U(I)
E(I)
I
Income
21
WTP to gamble and change in location
(related to “distance surplus”)
• ZG Gambler: WTP ex-ante for gamble can include
–
–
–
–
Fixed fee (travel)
House/state take
“surplus” if doesn’t have to pay the full amount
If gambling location gets closer, same WTP but more may
go for gambling and/or surplus, gamble more
• ZNG Non-gambler: may have WTP in a smaller amount
that is not sufficient to travel so no observed
“gamble”; as locations get closer, then ZNG may be
sufficient to gamble; new entry of gambling.
• Price of gamble is extracted from WTP
• If offered better gamble (e.g. “looser slots”) at least
willing to pay earlier amount and may get added
utility surplus.
22
Problem or Pathological Gamblers
• Consumer sovereignty or not?
– Standard model: people responsible and
understand own actions
– Non-standard model (some aspects of Behavioral
economics)
• Lack of control (some with WTP to be “normal”), then a
modest surplus loss ( Australian report or Vining and
Weimer (JBCA, 2011) based on gambling to P&P
gamblers that returns less than expected.
• Other behavioral: could be issues in lack of
understanding of probabilities
23
Surplus Loss from Addiction
•
(Vining/Weimer/Thomas) smoking, ~25% loss in Total Surplus
– Preliminary oddity: if only use distance surplus as consumer benefit,
then addiction adjustment appears small.
24
Equity and BCA
Increasing attention with new Administration in U.S. and
regulatory analysis
• Standard approach in textbooks is to consider distributional
weighting using marginal utility of income for different
income classes, but lack of agreement on weights
– Sensitivity: default in BCA is equal MU(income) which is an
Atkinson weight of 0.
– As an assumption, easily varied, perhaps to find cross-over point
– Some guidance; UK Greenbook for regulatory analysis specifies
Atkinson weight of 1; US Census reports .25, .5, .75
– Example from Analysis of VLTs in Maryland (Farrow and
Shinogle)
25
Distributional weights based on values of inequality aversion,
e, used by the U.S. Census Bureau and the UK Treasury
Population Mean US HH
Quintile,
Income by Quintile: Default:
Median, % 2007
e=0
e=.25
e=.5
0-20
$11,551
1
1.4
20-40
$29,442
1
1.1
Median
$50,233
1
1.0
40-60
$49,968
1
1.0
60-80
$79,111
1
0.9
80-100
$167,971
1
0.7
e=.75
2.1
1.3
1.0
1.0
0.8
0.5
e=1
3.0
1.5
1.0
1.0
0.7
0.4
4.3
1.7
1.0
1.0
0.6
0.3 D
Data source: US Census, 2008b; author’s calculations
26
Short example: VLT’s in Maryland
Base case: positive (but uncertain) Net Benefits
Video Lottery Terminals
Basic Model I:
direct effects
only
Basic Model I
Mil 2008 $
Specific Secondary effects
Mil 2008 $
Benefits
Delta CS: Consumer distance
Delta Gov't Revenue
Delta G: Annaul fee for Prob.
Gamb
Delta PS: MD Profits
MIPAR
$25 Delta CS: Consumer distance
$913 Delta Gross Gov't Revenue
$6
$913
$6
$36 Delta PS: MD Profits
New sales tax
Unemployment effects
Welfare benefits
$25
$980 Modified Benefits
$36
$2.5
$0
$982
Costs
Delta Gov Rev (2% Admin)
Delta Gov Rev: other cost
External costs
$27 Delta Gov Rev (2% Admin)
$48 Delta Gov Rev: other cost
$428 External costs
Loss in lottery sales
Loss in other taxes
Change other CS or PS
$27
$48
$428
57
34
0
Welfare costs
$503 Modified Costs
$594
Annual Net Benefits
$477 Modified Net Ben
$389
27
Distributional Weights: Can change sign
Extended model with Distributional effects
w/Distributional
impact:gambler
w/Distributional
impact:gambler
e=.5
e=.25
~4:1
2:1 weight
$43
$31
$913
$913
$6
$6
$36
$36
$2
$2
$0
$0
$1,000
$989
$27
$27
$48
$48
$428
$428
$57
$57
$34
$34
971
345
$1,565
$938
-$565
$50
28
Summary
What can be learned from gambling analyses
• SEIGs and GPIGs: potential impacts of interest
to various stakeholders
• Regional Issues: spillovers, race to the bottom
• BCA issues: framework exists but lacks central
WTP measure based on gambling; can include
addiction and equity.
29
Extra slides
30
Simulation results
(using @Risk with Excel)
31