AN EXPERIMENTAL EXAMINATION
OF TARGET BASED CONSERVATION
AUCTIONS
Peter Boxall, Orsolya Perger, Katherine Packman, and Marian
Weber
Department of Resource Economics & Environmental Sociology
University of Alberta
Goal:
Examine efficacy of target based auctions
• Uses experimental economic methods tied to
actual empirical data
– Benchmarked to a real Manitoba watershed
• Follows from work by Schilizzi & LataczLohmann
• Focuses on environmental target rather than a
contract target
The Policy Setting
• Canadian agri-environmental programs focus on
practice change through beneficial management
practice (BMP) adoption
• Rather than fixed payment – they use cost share
which can be variable
– Pay % of cost up to some maximum
• Our research shows that the payments are too
low and uptake (of course) is abysmal for the
“right” BMPs
• A role for MBIs ?
Environmental problem: Wetlands on
Agricultural Lands
• Up to 70% of wetlands have been lost; mostly
due to drainage
• Many programs focus on restoration
– Targets for restoration have been set in many
provinces
– Offsets, easements, reverse auctions
– Uptake of restoration is low
– Reverse auctions have been examined in a pilot
1948
1995
A watershed (catchment) somewhere in Prairie Canada
Use of subwatersheds
and placement of
monitoring
equipment provides
benchmarks for
hydrologic modelling
We tie our research to
the hydrologic model and
costs developed from a 16
yr panel of farm surveys
My students “love” to
visit Miami !!
An illustration: How Much Does it Cost to
Restore a Wetland in STC?
TOTAL
COSTS
of restoration
Opportunity
Costs
Private Costs
(to producers)
Nuisance
Costs
“Public” Costs
(if a program)
Restoration
Costs
Administration
Costs
Construction
Costs
Costs of Restoration
Wetland level
Median
Farm level
Size
Total Costs
Total
(acres)
costs/acre
0.282
$324.94
$1173.86
Mean
0.461
$440.25
$1395.61
SD
0.677
$446.82
$1085.81
Minimum
0.016
$99.09
$104.13
Maximum
8.759
$5507.54
$9891.70
Supply Curves for Wetland Restoration In “Acre Space”
The Producer level
Marginal costs (supply) for restoring 100% wetlands
in South Tobacco Creek
3000
Expensive abaters
2500
$/acre
2000
ID 103
ID 26
1500
$821/ac
$831/ac
1000
500
100 ac
0
0
50
100
150
200
250
300
350
400
Number of acres
The costs borne by an individual producer for 100% restoration
450
500
Supply Curves for Wetland Restoration In “Acre Space”
The Wetland level
Marginal costs (supply) of restoring each wetland in South Tobacco Creek
(excluding costs >$10,000 /acre)
12000
$/acre (discounted
10000
8000
6000
ID 103
4000
2000
0
0
50
100
150
200
250
300
350
400
450
500
Number of acres
The costs borne by an individual producer for restoring an individual wetland
Supply Curves for Wetland Restoration In “P Abatement Space”
The Wetland level
Marginal costs (supply) for each producer for using wetland restoration
to reduce phosphorus levels in South Tobacco Creek
(note - assumes 100% restoration on each farm)
1600
1400
1200
$/kg
1000
ID 103
800
ID 26
600
400
200
0
0
200
400
600
800
Phosphorus (kg)
1000
1200
1400
$/Quantity
Max Coverage
($/acre)
Or
Max EBI ($/kg)
Quantity N=12
$/Quantity
Illustrations of Experimental Procedures
Quantity N=36
Experimental Auction Design
• Each subject given a farm with parameters
– Costs and acres for up to 4 levels of restoration
• Subjects submit earn income and submit offers in each
period
– Offer consists of a quantity and price (bid/offer) choice pair
• Offers ordered using a selection rule ($/acre) and
cheapest offers selected until budget is exhausted or an
environmental target met
• Auctions are repeated 15 times;
– We call these repetitions periods
– Farm parameters change after 5 periods – these are rounds
• If target not met, auction in that period cancelled
• No communication allowed
• Random draw of a period within each round determines
payment
Rotation of farm costs
A: Fixed Farm
Rounds
1 - 15
B: Changing
Farm
Rounds
1-5
Rounds
6 - 10
Rounds
11 - 15
Experimental Treatments
• Budget versus target
– Target determined “exogenously” from budget based
approach (unlike S & LL work)
– Target is an explicit environmental improvement not
number of contracts
• Target based – potential for cost uncertainty
– Test use of a reserve price
– Actual reserve price not revealed to bidders
• Scale issues – degree of competition
– Test a “large” program: large budget & large target
– Test a “small” program: small budget & small target
• Strove for 3 replications of each treatment
Approaches used to analyze data
Behavioural
predictors
Auction
outcome 1
Integrated
Model
POCER
Auction
outcome 2
Market
outcomes
Auction
outcome 15
PMOR
RENT
Small program
No
reserve
price
45
Total auction
periods
76%
Target met
(% total periods)
52,312
Mean budget
spent ($)
1534
Mean cost
($/acre)
Large program
Reserve No
Reserve
price
reserve price
price
30
45
45
40%
73%
51%
44,584
88,976
80,408
1435
1780
1567
Rent - % bids above adoption costs
Small program
30
% bid over costs
20
10
0
-10
1
2
3
4
5
6
7
8
9
10 11 12 13 14 15
-20
-30
Period
Budget
Target - No reserve
Target - reserve
Rent - % bids above adoption costs
Large program
60
% bid over costs
50
40
30
20
10
0
-10
1
2
3
-20
4
5
6
7
8
9
10 11 12 13 14 15
Period
Budget
Target - no reserve
Target - reserve
Small Program
2000
$/acre
Cost
efficiency:
1500
$/acre acquired
1000
500
0
1
2
3
4
5
6
7
8
9
Target based - no reserve
Budget based
Large Program
10 11 12 13 14 15
Target based - reserve
2500
$/acre
2000
1500
1000
500
0
1
2
Budget based
3
4
5
6
7
8
9
Target based - no reserve
10 11 12 13 14 15
Target based - reserve
Small program
70000
Budget spent
50000
40000
30000
20000
10000
0
1
2
3
4
5
6
7
8
9
Target based - no reserve
Budget based
Large program
10 11 12 13 14 15
Target based - reserve
120000
100000
Budget spent
Budget spent
60000
80000
60000
40000
20000
0
1
2
Budget based
3
4
5
6
7
8
9
Target based - no reserve
10 11 12 13 14 15
Target based - reserve
Random effects GLS regressions (with robust standard errors)
Variables
% rent
Constant
Lag Y
Ln(Period)
Ln(Round)
Target dummy (TD)
Reserve Price dummy
(RPD)
Large Program dummy
(LPD)
TD*Period
TD*Round
LPD*TD
R2 (overall)
$/acre
13.496***
0.254*
1.416
-5.153***
-22.898***
-8.196**
1601.185***
0.049
50.598
-104.059*
-230.285
-191.834***
14.853***
335.253***
6.908
5.019*
-5.142
83.307
15.618
-101.364
0.475
*** P≤0.001; ** P≤0.01; * P≤0.05
0.501
Findings
• Target based auctions appeared to
outperform similar sized budget based
auctions
– budget based experiments led to higher
information rents gained by successful bidders as
well as higher acquisition costs regardless of the
program size
• Use of a reserve price increased the efficiency
of the target based approach even further
– reduced budget outlays and decreased the unit
acquisition cost as expected, but the effect was
not dramatic in all periods
• Use of a reserve price generated confusion
among bidders
– Increased number of “unsuccessful” auctions
• We did not find “strong” evidence of bidder
learning
– More apparent in target based approach
– Perhaps not surprising if subjects gradually learn
there is no budget cap and submit higher bids as
the auction periods progress until they are not
successful
• Program size influenced results: Smaller
programs in terms of budgets or targets led to
superior results
– small programs increase competition amongst
bidders, and this competition leads to higher
auction efficiency
Thanks to:
• AAFC’s Watershed Evaluation of Beneficial
Management Practices Program (WEBs)
• ACAAF – Ducks Unlimited for funding support
and advice
• Deerwood Soil and Water Management
Association, and Bill Turner
• Linking Environment and Agriculture Research
Network (LEARN)
• Stephanie Simpson, Curtis Rollins, Scott
Wilson