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The Role of Bargaining Costs in
Addressing the Depletion of Natural
Resources
The Case of California’s Groundwater
Andrew B. Ayres
UCSB, Bren School and Economics
Gary D. Libecap
UCSB, Bren School and Economics
Eric C. Edwards
Utah State, Applied Economics
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Outline
• Application: California provides opportunities for differential management adoption; critical basins
1.Introduction and Background
2.Model Predictions
3.Empirical Strategy
4.Results and Discussion
5.Conclusion
Overview 1/17
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California’s Puzzle
2/17Background
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Common-pool Resource Management
• Common-pool Resources (CPR)– Rivalry without excludability; Depletion
• Alleviation of CPR problem requires new institutions (Ostrom, 1990; Barzel, 1987)– Rational opposition (Grainger and Costello,
2015;Libecap, 1989)
• Groundwater: shared – yet renewable – CPR– Excessive pumping results from open-access
framework
3/17Background
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Research Agenda
• Research Questions:– Which basin and user characteristics explain the adoption of management?
– What determines the difficulty users will have in reaching agreement?
– When and why do basins adopt management?
• Few empirical investigations of returns to new institutions and bargaining costs
• Sustainable Groundwater Management Act (SGMA): Implementation can benefit from a better understanding of costs and benefits
4/17Background
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Rights and Regulation in California
• Correlative Rights– Overlying and Appropriative Rights– Retains important open-access characteristics: No mechanism for
internalizing full costs of pumping
Alternatives:• Groundwater Management Plans (GMPs)
– AB 3030 (1992): The original Groundwater Management Act– They may not restrict or redefine water rights
• Adjudication to Define Property Rights– Typically a stipulated judgement—bargaining among parties– Total pumping is often capped and pumping rights are assigned
5/17Background
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Twenty-four adjudications cover 32 groundwater basins (as defined by
Bulletin 118).
In addition, 91 basins have at least one GMP under AB 3030, SB 1938,
or AB 359.
Basins not pictured here (307) have adopted neither remedy.
Several basins are listed as critically overdrafted by CA DWR yet have not been adjudicated. This will be key for
our analysis.
6/17
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Model
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Analytic Model Predictions
• For basin-wide adjudication to be welfare enhancing– Aggregate Benefits of Adoption > Aggregate Costs of Implementation and Bargaining
• Private tradeoff of implementing management– Private cost of reduced pumping vs. private benefits of neighbors’ reduced pumping
Aggregate benefits increase with:• Hydraulic conductivity• Aridness or lack of precipitation• Well density• More valuable uses (sometimes
due to longer planning horizons)• Risk of collateral impacts
Bargaining costs increase with:• Number of Users/Logistics• Variance in Distribution of
Private Benefits
7/17
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Empirics
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Data
8/17Empirics
Variable Units Source
Precipitation (1950 - 2014 mean) Millimeters PRISM
Precipitation (1950 - 2014 spatial variance)
Millimeters PRISM
Basin Surface Area Acres DWR
Coastline Dummy Dummy DWR
Well Yield (Max/Average) Gal/min DWR
Number of Farms Count USDA
Number of Wells Count DWR
Number of Drinking Water Wells Count or Percentage DWR
Number of Agricultural Wells Count or Percentage DWR
Well Density Count/Acre DWR/Author
Number of Wells within 1000m of Coast Count or Percentage DWR/Author
Urban Population Growth (1950 - 2010) Decadal Average Growth Rate CA. Dept of Finance/ Author
State Water Project Connection Dummy Author's Data
Number of GMPs Number (also: Dummy if >0) DWR
Adjudication Dummy Author’s Data
Length of Adjudication Years Author’s Data
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Empirical Strategy
• Benefits: Ordered Logit Model to examine management choice: None, GMPs, Adjudication
𝑌𝑖∗ = 𝑋𝑖
′𝛽 + 𝑢𝑖• Costs:
– (1) Critical, unadjudicated basins: counterfactual for adjudicated basins
• Low vs. high transaction costs, holding benefits constant
– (2) Estimate Determinants of Adjudication Duration
• Cox Proportional-Hazard Model
9/17Empirics
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Results
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Ordered Logit Results - Benefits
Results 10/17
(1) (2) (3) (4) (5)
Mgt Type Mgt Type Mgt Type Mgt Type Mgt Type
Baseline Spec. SAD in Tier 3 SWP
Avg. Well Yield0.000721** 0.000565* 0.000655* 0.000535**
(0.000332) (0.000342) (0.000368) (0.000261)
Max. Well Yield0.000291***
(0.0000892)
Mean Precipitation 1950-2014
-0.0000684 -0.000442 -0.000154 -0.0000575
(0.000458) (0.000419) (0.000480) (0.000470)
Coastline Dummy-0.380 -0.233 -0.563 -0.655* -0.980*
(0.408) (0.363) (0.400) (0.393) (0.535)
Well Density46.21*** 38.37*** 47.07*** 37.84*** 42.79***
(12.25) (13.87) (13.71) (12.89) (12.56)
Percentage Ag Wells-0.501 -0.261 -0.719 -0.185
(0.629) (0.585) (0.643) (0.711)
Average Urban Pop. Growth (1950-2010)
0.0155** 0.0241** 0.0219**
(0.00703) (0.0101) (0.0101)
SWP Connection1.672***
(0.372)
Kappa 10.767** 0.925*** 0.829** 0.897*** 1.218***
(0.322) (0.310) (0.338) (0.329) (0.246)
Kappa 22.340*** 2.435*** 2.504*** 2.147*** 2.982***
(0.397) (0.396) (0.415) (0.360) (0.307)
N 184 209 184 184 184
(Standard errors) = * p<.1, ** p<.05, *** p<.01
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Ordered Logit Results - Benefits
Results 10/17
(1) (2) (3) (4) (5)
Mgt Type Mgt Type Mgt Type Mgt Type Mgt Type
Baseline Spec. SAD in Tier 3 SWP
Avg. Well Yield0.000721** 0.000565* 0.000655* 0.000535**
(0.000332) (0.000342) (0.000368) (0.000261)
Max. Well Yield0.000291***
(0.0000892)
Mean Precipitation 1950-2014
-0.0000684 -0.000442 -0.000154 -0.0000575
(0.000458) (0.000419) (0.000480) (0.000470)
Coastline Dummy-0.380 -0.233 -0.563 -0.655* -0.980*
(0.408) (0.363) (0.400) (0.393) (0.535)
Well Density46.21*** 38.37*** 47.07*** 37.84*** 42.79***
(12.25) (13.87) (13.71) (12.89) (12.56)
Percentage Ag Wells-0.501 -0.261 -0.719 -0.185
(0.629) (0.585) (0.643) (0.711)
Average Urban Pop. Growth (1950-2010)
0.0155** 0.0241** 0.0219**
(0.00703) (0.0101) (0.0101)
SWP Connection1.672***
(0.372)
Kappa 10.767** 0.925*** 0.829** 0.897*** 1.218***
(0.322) (0.310) (0.338) (0.329) (0.246)
Kappa 22.340*** 2.435*** 2.504*** 2.147*** 2.982***
(0.397) (0.396) (0.415) (0.360) (0.307)
N 184 209 184 184 184
(Standard errors) = * p<.1, ** p<.05, *** p<.01
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Ordered Logit Results - Benefits
Results 10/17
(1) (2) (3) (4) (5)
Mgt Type Mgt Type Mgt Type Mgt Type Mgt Type
Baseline Spec. SAD in Tier 3 SWP
Avg. Well Yield0.000721** 0.000565* 0.000655* 0.000535**
(0.000332) (0.000342) (0.000368) (0.000261)
Max. Well Yield0.000291***
(0.0000892)
Mean Precipitation 1950-2014
-0.0000684 -0.000442 -0.000154 -0.0000575
(0.000458) (0.000419) (0.000480) (0.000470)
Coastline Dummy-0.380 -0.233 -0.563 -0.655* -0.980*
(0.408) (0.363) (0.400) (0.393) (0.535)
Well Density46.21*** 38.37*** 47.07*** 37.84*** 42.79***
(12.25) (13.87) (13.71) (12.89) (12.56)
Percentage Ag Wells-0.501 -0.261 -0.719 -0.185
(0.629) (0.585) (0.643) (0.711)
Average Urban Pop. Growth (1950-2010)
0.0155** 0.0241** 0.0219**
(0.00703) (0.0101) (0.0101)
SWP Connection1.672***
(0.372)
Kappa 10.767** 0.925*** 0.829** 0.897*** 1.218***
(0.322) (0.310) (0.338) (0.329) (0.246)
Kappa 22.340*** 2.435*** 2.504*** 2.147*** 2.982***
(0.397) (0.396) (0.415) (0.360) (0.307)
N 184 209 184 184 184
(Standard errors) = * p<.1, ** p<.05, *** p<.01
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Ordered Logit Results - Benefits
Results 10/17
(1) (2) (3) (4) (5)
Mgt Type Mgt Type Mgt Type Mgt Type Mgt Type
Baseline Spec. SAD in Tier 3 SWP
Avg. Well Yield0.000721** 0.000565* 0.000655* 0.000535**
(0.000332) (0.000342) (0.000368) (0.000261)
Max. Well Yield0.000291***
(0.0000892)
Mean Precipitation 1950-2014
-0.0000684 -0.000442 -0.000154 -0.0000575
(0.000458) (0.000419) (0.000480) (0.000470)
Coastline Dummy-0.380 -0.233 -0.563 -0.655* -0.980*
(0.408) (0.363) (0.400) (0.393) (0.535)
Well Density46.21*** 38.37*** 47.07*** 37.84*** 42.79***
(12.25) (13.87) (13.71) (12.89) (12.56)
Percentage Ag Wells-0.501 -0.261 -0.719 -0.185
(0.629) (0.585) (0.643) (0.711)
Average Urban Pop. Growth (1950-2010)
0.0155** 0.0241** 0.0219**
(0.00703) (0.0101) (0.0101)
SWP Connection1.672***
(0.372)
Kappa 10.767** 0.925*** 0.829** 0.897*** 1.218***
(0.322) (0.310) (0.338) (0.329) (0.246)
Kappa 22.340*** 2.435*** 2.504*** 2.147*** 2.982***
(0.397) (0.396) (0.415) (0.360) (0.307)
N 184 209 184 184 184
(Standard errors) = * p<.1, ** p<.05, *** p<.01
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Ordered Logit – Marginal Effects
Results 11/17
Average Well Yield
Mean Precipitation
Well DensityPercentage
Ag Wells
Average Urban
Growth
One Standard Deviation around Mean
None -7.32% 1.47% -4.51% 4.10% -9.89%
GMP 4.44% -0.89% 2.77% -2.46% 6.03%
Adj. 2.89% -0.57% 1.74% -1.64% 3.86%
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Critical Basin Comparison
VariableCritical,
UnadjudicatedAdjudicated
Significance Level
Fitted Values (Benefits) 0.8213 0.8142 -
Basin Area 1,219,700 145,651 **
Mean Spatial Precip. Variance 1950-2014
5459.1 4027.3 -
Number of Wells 3269.4 342.9 ***
Well Heterogeneity 0.15415 0.09209 **
Percentage Drinking Wells 0.561 0.566 -
Percentage Ag Wells 0.399 0.192 **
N 8 32
* p<.1, ** p<.05, *** p<.01
Results 12/17
• We wish to hold benefits constant, explore determinants of bargaining costs• Critical basins are proper counterfactual if benefits scores are similar
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Mean Std. Dev.
Adj. Duration (Yrs) 7.6 5.8
13/17Results
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Predictions – Adjudication Duration
Results 14/17
Measure Predicted SignPrediction from Conceptual
Model
Basin Size - Number of Users/Logistics
Spatial Variance in Recharge - Variance in Private Benefits
Number of Wells - Number of Users
Well Heterogeneity - Variance in Private Benefits
Wells within 1000m of Coastline - Variance in Private Benefits
Wells within 1000m: Quadratic + Variance in Private Benefits
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Results – Adjudication Duration(1) (2) (3) (4)
Adj Duration Adj Duration Adj Duration Adj Duration
Basin Area-0.00000111 -0.000000810 -0.00000292*** -0.00000272***
(0.000000988) (0.000000950) (0.000000899) (0.000000767)
Mean Spatial Precip. Variance 1950-2014
-0.0000509 -0.0000483 -0.0000698 -0.0000601
(0.0000496) (0.0000400) (0.0000588) (0.0000510)
Avg. Well Yield-0.000244 -0.000128 -0.000304 -0.000166
(0.000356) (0.000376) (0.000335) (0.000358)
Number of Wells-0.00129*** -0.00127*** -0.00117*** -0.00109***
(0.000229) (0.000258) (0.000202) (0.000211)
Proportion of Wells within 1000m of Coastline
-5.845 -5.279 -107.3*** -114.5***
(4.037) (4.333) (29.08) (35.26)
Proportion of Wells within 1000m Squared
433.9*** 466.0***
(122.5) (146.4)
Well Heterogeneity-10.24*** -17.02** -10.34*** -17.60**
(3.523) (7.585) (3.690) (7.581)
Controls
Coastline Dummy0.354 -0.0792 1.340*** 0.987**
(0.782) (0.930) (0.455) (0.400)
Average Number of Farms 1940-19590.00343*** 0.00342*** 0.00430*** 0.00425***
(0.000704) (0.000746) (0.000866) (0.00100)
Percentage Drinking Wells-0.0677 0.118
(0.868) (0.776)
Percentage Ag Wells3.160 3.480
(2.785) (2.512)
N 23 23 23 23
(Standard errors) = * p<.1, ** p<.05, *** p<.01
Results 15/17
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Results – Adjudication Duration(1) (2) (3) (4)
Adj Duration Adj Duration Adj Duration Adj Duration
Basin Area-0.00000111 -0.000000810 -0.00000292*** -0.00000272***
(0.000000988) (0.000000950) (0.000000899) (0.000000767)
Mean Spatial Precip. Variance 1950-2014
-0.0000509 -0.0000483 -0.0000698 -0.0000601
(0.0000496) (0.0000400) (0.0000588) (0.0000510)
Avg. Well Yield-0.000244 -0.000128 -0.000304 -0.000166
(0.000356) (0.000376) (0.000335) (0.000358)
Number of Wells-0.00129*** -0.00127*** -0.00117*** -0.00109***
(0.000229) (0.000258) (0.000202) (0.000211)
Proportion of Wells within 1000m of Coastline
-5.845 -5.279 -107.3*** -114.5***
(4.037) (4.333) (29.08) (35.26)
Proportion of Wells within 1000m Squared
433.9*** 466.0***
(122.5) (146.4)
Well Heterogeneity-10.24*** -17.02** -10.34*** -17.60**
(3.523) (7.585) (3.690) (7.581)
Controls
Coastline Dummy0.354 -0.0792 1.340*** 0.987**
(0.782) (0.930) (0.455) (0.400)
Average Number of Farms 1940-19590.00343*** 0.00342*** 0.00430*** 0.00425***
(0.000704) (0.000746) (0.000866) (0.00100)
Percentage Drinking Wells-0.0677 0.118
(0.868) (0.776)
Percentage Ag Wells3.160 3.480
(2.785) (2.512)
N 23 23 23 23
(Standard errors) = * p<.1, ** p<.05, *** p<.01
Results 15/17
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Results – Adjudication Duration(1) (2) (3) (4)
Adj Duration Adj Duration Adj Duration Adj Duration
Basin Area-0.00000111 -0.000000810 -0.00000292*** -0.00000272***
(0.000000988) (0.000000950) (0.000000899) (0.000000767)
Mean Spatial Precip. Variance 1950-2014
-0.0000509 -0.0000483 -0.0000698 -0.0000601
(0.0000496) (0.0000400) (0.0000588) (0.0000510)
Avg. Well Yield-0.000244 -0.000128 -0.000304 -0.000166
(0.000356) (0.000376) (0.000335) (0.000358)
Number of Wells-0.00129*** -0.00127*** -0.00117*** -0.00109***
(0.000229) (0.000258) (0.000202) (0.000211)
Proportion of Wells within 1000m of Coastline
-5.845 -5.279 -107.3*** -114.5***
(4.037) (4.333) (29.08) (35.26)
Proportion of Wells within 1000m Squared
433.9*** 466.0***
(122.5) (146.4)
Well Heterogeneity-10.24*** -17.02** -10.34*** -17.60**
(3.523) (7.585) (3.690) (7.581)
Controls
Coastline Dummy0.354 -0.0792 1.340*** 0.987**
(0.782) (0.930) (0.455) (0.400)
Average Number of Farms 1940-19590.00343*** 0.00342*** 0.00430*** 0.00425***
(0.000704) (0.000746) (0.000866) (0.00100)
Percentage Drinking Wells-0.0677 0.118
(0.868) (0.776)
Percentage Ag Wells3.160 3.480
(2.785) (2.512)
N 23 23 23 23
(Standard errors) = * p<.1, ** p<.05, *** p<.01
Results 15/17
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Results – Adjudication Duration(1) (2) (3) (4)
Adj Duration Adj Duration Adj Duration Adj Duration
Basin Area-0.00000111 -0.000000810 -0.00000292*** -0.00000272***
(0.000000988) (0.000000950) (0.000000899) (0.000000767)
Mean Spatial Precip. Variance 1950-2014
-0.0000509 -0.0000483 -0.0000698 -0.0000601
(0.0000496) (0.0000400) (0.0000588) (0.0000510)
Avg. Well Yield-0.000244 -0.000128 -0.000304 -0.000166
(0.000356) (0.000376) (0.000335) (0.000358)
Number of Wells-0.00129*** -0.00127*** -0.00117*** -0.00109***
(0.000229) (0.000258) (0.000202) (0.000211)
Proportion of Wells within 1000m of Coastline
-5.845 -5.279 -107.3*** -114.5***
(4.037) (4.333) (29.08) (35.26)
Proportion of Wells within 1000m Squared
433.9*** 466.0***
(122.5) (146.4)
Well Heterogeneity-10.24*** -17.02** -10.34*** -17.60**
(3.523) (7.585) (3.690) (7.581)
Controls
Coastline Dummy0.354 -0.0792 1.340*** 0.987**
(0.782) (0.930) (0.455) (0.400)
Average Number of Farms 1940-19590.00343*** 0.00342*** 0.00430*** 0.00425***
(0.000704) (0.000746) (0.000866) (0.00100)
Percentage Drinking Wells-0.0677 0.118
(0.868) (0.776)
Percentage Ag Wells3.160 3.480
(2.785) (2.512)
N 23 23 23 23
(Standard errors) = * p<.1, ** p<.05, *** p<.01
Results 15/17
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How Costs Block Management
• Examples
– San Joaquin and the Central Valley: Large, many users, heterogeneous demand
– Seaside and Salinas: Disparate bargaining positions result from spatial distribution of pumpers
Discussion 16/17
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Conclusions
• Reliable determinants of management benefits include– Well Yields (Commonality) – Precipitation (Value) – Well Density (Heterogeneity/Commonality) – Population Growth/ Ag Users (Value)
• Bargaining costs robustly controlled by– Basin Size (Logistical, Informational Costs)– Number of Wells (Number of Actors)– Spatial Distribution of Actors Near Coastline (User/Resource Heterogeneity)– Well Type Heterogeneity (User Heterogeneity)
• SGMA implementation can be informed by this work: demonstrate where adjudication will be costly or shed light on types of CPR problems for which less stringent restrictions are appropriate
Conclusions 17/17
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Summary Statistics
Appendix 18/17
Adjudicated GMP None TotalCritical,
UnadjudicatedNumber of Basins 32 91 307 430 8
Precipitation (mean)337 469 533 505 369
(161) (294) (445) (405) (201)
Precipitation (spatial variance)4,027 3,427 2,945 3,127 5,454
(6,113) (5,580) (5,127) (5,300) (5,094)
Basin Size (acres)145,652 207,126 52,540 92,184 1,094,380
(204,795) (1,002,996) (125,798) (479,070) (2,745,233)
Coastline Dummy0.28 0.23 0.28 0.27 0.5
(0.46) (0.42) (0.45) (0.45) (0.52)
Well Yield (maximum)2,450 1,816 1,150 1,493 2,824
(2,313) (1,705) (1,288) (1,633) (1,496)
Well Yield (average)710 565 432 502 777
(495) (541) (556) (550) (322)
Avg. Number of Farms (1940-1959)216 567 38 163 3,282
(464) (3,442) (156) (1,601) (9,346)
Number of Wells342 631 28 179 1,764
(571) (3,481) (93) (1,623) (4,898)
Percentage Drinking Wells 56.6 49.6 34.8 40 35.2
(29.2) (36.9) (40) (39.4) (32.5)
Percentage Agricultural Wells 19.2 17.3 12 13.7 29
(17.6) (23.5) (24.5) (23.9) (28.1)
Well Density (per acre)0.00171 0.00358 0.00136 0.00185 0.00123
(0.00212) (0.00751) (0.00315) (0.00448) (0.00169)
Well Heterogeneity0.092 0.0631 0.0347 0.045 0.00169
(0.0698) (0.0754) (0.0669) (0.0711) (0.0914)
Urban Population Growth (%)20.28 12.12 4.12 7.01 26.37
(33.24) (24.33) (17.33) (21.04) (19.68)
SWP Connection0.718 0.274 0.104 0.186 0.2
(0.456) (0.448) (0.306) (0.389) (0.421)
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Benefits of Groundwater Management
For basin-wide adjudication to be welfare enhancingAggregate Benefits of Adoption > Aggregate Costs of Implementation and Bargaining
𝑉𝑖0 = max
𝑤𝑖
0
∞
𝜋𝑖 𝑤𝑖 , ℎ𝑖 𝑒−𝛿𝑡 𝑑𝑡
𝑠. 𝑡 ℎ𝑖 = 𝑟𝑖 − 𝑤𝑖 − 𝜃 ℎ𝑖 − ℎ−𝑖 and 𝜃 =𝑘
𝑑
Define: 𝑉𝑀 ≥ 𝑉0
• We show: aggregate net benefits of management increase with– Hydraulic conductivity (𝑘)
– Aridness or lack of precipitation (𝑟)
– Well density (𝑑)
– More valuable uses (sometimes due to longer planning horizons) (𝜕𝜋𝑖
𝜕𝑤𝑖)
– Risk of collateral impacts (f𝑖 ∙ ℎ)
7/17Conceptual Model
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Conceptual Model: Costs of Adjudication
Private tradeoff of implementing managementPrivate cost of reduced pumping vs. private benefits of neighbors’ reduced pumping
Δ𝑖 = 𝑉𝑖𝑀 − 𝑉𝑖
0
𝐶 = 𝑔 𝑣 Δ𝑖
𝑣 Δ𝑖 =
𝑖=1
𝑁
(Δ𝑖 − 𝜇∆)2
• Benefits must be positive for some users in order for management to be considered– Some aquifers are so critical (drawdown, intrusion, subsidence, etc.) that all expect positive net benefits– Sometimes recalcitrant parties must be brought on board: institutional rule changes or side payments
• Bargaining to assign water rights and control extraction may be difficult due to:– Number of Actors: Number of Rights Holders, Number of Wells (Agrawal and Goyal, 2000; Libecap and Wiggins, 1984)– Resource Size and Characteristics: Basin Area, Conductivity, Coastline, Confinement, Variance in Recharge (Libecap
and Smith, 1999)– User Heterogeneity: Type of Use (Urban/Ag), Relative Position (to Coast, Other Users, Density), Consolidation (Ruttan,
2008; Libecap and Wiggins, 1987)– Monitoring and Enforcement: Metering, Watermaster– Asymmetric Information: Difficult to Measure
Conceptual Model 8/17