wp 4.4 · alcalá de henares (madrid, spain) 06 january 2013 massimo pizzol ... • harmonizing...
TRANSCRIPT
Evaluating Economic Policy Instruments for
Sustainable Water Management in Europe
The research leading to these results has received funding from the
European Community’s Seventh Framework Programme (FP7/2007-2013) /
grant agreement n° 265213 – project EPI-WATER “Evaluating Economic
Policy Instrument for Sustainable Water Management in Europe”.
WP 4.4.B Macroeconomic perspective on water quality issues of relevance to the System of Environmental-Economic Accounting for Water (SEEAW)
Aarhus University Alcalá de Henares (Madrid, Spain) 06 January 2013
Massimo Pizzol
Department of Environmental
Science
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1. Outline
• Case study
o Odense River Basin - water uses
o Policy/management issues and current EPI-mix
• Innovative policy mix
o Research questions
o Methodological approach
• Intermediate outputs
o EPI1 - Indirect effects
o EPI2 - Direct effects
• Next steps
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2. Odense River Basin - water uses
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60
1997 1998 1999 2000 2001 2002 2003 2004
Water Consumption (Mm3)
Households
Irrigation (privatecollection)
TOTAL Drinkingwater
Total industrial
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20
30
40
50
60
70
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82
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Water Consumption (Mm3)
1 City water, households
2 City water, industrial
3 City water, loss, etc.
4 Water supply TOTAL(1+2+3)
5 Filter flushing etc.
6 City water TOTAL (4+5)
Green tax reform
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3. Policy/management issues and current EPI-mix
Current EPI-mix
• Phosphorous Tax (Agriculture)
• Water Supply Tax (5 Kr./m3, households only)
• Wastewater Tax (BOD, N, P from sewage plants)
Water bodies fail to meet environmental objectives
• SW quality affected by: diffuse N&P load (agriculture), point
source pollution (sewage)
• GW quality affected by: reduced infiltration, excess
abstraction, leaching of contaminants
• Untreated DW is practice and priority in DK
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4. Research questions WP4.4B
• What is the EPI effect on water quality (WQ)?
• How can this be estimated ex-ante?
How do water quantity-oriented EPI improve water quality?
Improved Danish water supply tax on water abstraction
How can water quality issues related to nutrients be
addressed by an EPI?
Tax on nitrogen/nitrogen loss from diffuse sources
EPI1
EPI2
Concept: hybrid modelling
• Combine economical + environmental (physical) data
• In line with SEEAW (System for Environmental-Economic Accounts
for Water)
5
EPI 1
Tax on Water Abstraction
Econometric model
Elasticity of Water
Demand
Environmental model
Effect of reduced water abstraction on surface water
quality
OUTCOME
EPI 1 indirect effect on water
quality
EPI 2
Tax on N load from
agricolture
Economic model
Effect of EPI on N use by
farmers
Environmental model
Reduced N conc. in
surface water from reduced N on arable
land
OUTCOME
EPI 2 direct effect on water
quality
5. Methodological approach WP4.4.B
Partner Input Description Expected Deliverables
ACTEON
AU and ACTEON will develop a comparative analysis between the two cases, in the like of mirror cases but specifically focusing on the dimensions of policy implementability.
O7: Co-authored note: literature review and comparative analysis of the institutional pre-conditions and transaction costs.
UVEG
UVEG will contribute to the ex-ante assessment of EPI1 by helping with the regression modelling and based on data provided by AU/NERI
O2 and O6: Regression modelling
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6. Contributors other than AU
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EPI 1
Tax on Water Abstraction
Econometric model
Elasticity of Water
Demand
Environmental model
Effect of reduced water abstraction on surface water
quality
OUTCOME
EPI 1 indirect effect on water
quality
7. EPI1 - scenarios
• BAU scenario - existing tax unchanged (5 Kr./m3)
• EPI scenario T1 increase 25% of tax value*
• EPI scenario T2 increase 30% of tax value*
*Percent increase every ten years (year 2020, 2030, 2040, etc.)
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8. EPI1 Price structure
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05
10
15
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25
30
35
40
45
00
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20
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40
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1980 1990 2000 2010 2020K
r-/m
3
m3
/pe
rso
n
Per capita household water cons. (estimate)[m3/person]
Total variable price [Kr./m3]
Year 2010
Variable water price 5.55
Groundwater fee [Kr./m3] 1.00
Abstraction tax [Kr./m3] 5.00
Wastewater variable price [Kr./m3] 21.85
Fixed water price [Kr.] 480.00
Fixed wastewater price [Kr.] 0.00
VAT (%) 25.00%
Total variable price (including taxes
and VAT) [Kr./m3] 41.75
Total fixed price (Including taxes and
VAT) [Kr.] 600.00
Vandforsyningsyd (main ORB water supplier)
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9. SCENES-based population and water use scenarios
0
5,000,000
10,000,000
15,000,000
20,000,000
25,000,000
30,000,000
1990 2000 2010 2020 2030 2040 2050 2060
ehWS (m3) EcF ehWS (m3) FoE ehWS (m3) PoR ehWS (m3) SuE
0
50000
100000
150000
200000
250000
300000
350000
1970 1980 1990 2000 2010 2020 2030 2040 2050 2060
POP ORB EcF POP ORB FoE POP ORB PoR POP ORB SuE
Future
households
water
withdrawals
(ehWS, in m3)
Future population
(POP, in nr of
inhabitants)
scenarios for
ORB
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10. EPI1 indirect effects
Scenario (Economy First, SCENES) 2015 2020 2025 2030
Population ORB 251188 260061 270270 280092
Water Sold (m3) 24378707 26277887 28177068 31041628
Future Tax (dkk) T1 (25% / 10 y) 6.3 7.8 7.8 9.8
T2 (30% / 10 y) 6.5 8.5 8.5 11.0
∆-ehPC (M1, elasticity= -0.366) T1 -0.5 -1.0 -1.0 -1.7
T2 -0.5 -1.3 -1.3 -2.2
∆-ehPC (M2, elasticity= -0.287) T1 -0.4 -0.8 -0.8 -1.4
T2 -0.4 -1.0 -1.0 -1.7
Water savings (m3) T1M1 114297 265961 276525 486114
T2M1 137157 326246 339204 610495
T1M2 89502 208264 216536 380657
T2M2 107402 255470 265617 478055
• Period 2015-2030 decrease in estimated household per capita
water consumption (ehPC)
• Significant water savings for both EPI scenarios (T1, T2) and
elasticity models (M1, M2)
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EPI 2
Tax on N load from
agricolture
Economic model
Effect of EPI on N use by
farmers
Environmental model
Reduced N conc. in
surface water from reduced N on arable
land
OUTCOME
EPI 2 direct effect on water
quality
11. EPI2 - scenarios
• BAU scenario - price of mineral fertilizer = 6.22 DKK/kg N
• EPI scenario 1 - tax on mineral fertilizer, price = 20 DKK/kg N
• EPI scenario 2 - tax on mineral fertilizer, price = 40 DKK/kg N
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12. EPI2 direct effects
• Decrease in use of fertilizer proportional to tax level
• Changes in crop distribution observed
• EPI scenario 2 excessive obstacle to agriculture
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
45.0
Wintercereals
Springcereals
Oil seeds Root crops Temporarygrass
Permanentgrass
Set aside Other
Crop distributions
Baseline (BAU) Feriliser price 20 DKK (SCP20) Fertiliser price 40 DKK (SCP40)
Scenario Fertilizer type Fertiliser use
(kg)
∆-Fertiliser use
(kg) ∆-Profit all (dkk)
∆-Transfer
(dkk)
BAU Mineral 12205232.55 0
SCP20 Mineral 4386802.873 -7818430 -102790894 60789124
SCP40 Mineral 127599.0443 -12077634 -131829965 5141274
Comparative analysis for EPI2
• “Mirror” study: ACTEON Sèine Normandie
• What happens when same EPI applied in different contexts?
• Get scientific insight on limits and applicability of hybrid
modelling in ex-ante assessment
Focus on Policy implementability:
• Active institutions implicated: roles and responsibilities
• Institutional capacity: resources, nr involved bodies, staff,
monitoring capacity
• Institutional framework: mandate to work on pollution,
enforcement powers and practices
• Regulations
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13. NEXT STEPS: Mirror study
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14. EPI2 policy implementability - issues of relevance
•Institutional pre-conditions
•DK tradition for untreated DW, and for green taxes
•Role of agricultural sector in adoption of taxes
•Transitional costs
•What is the "usual" path for green taxes?
•Cost of inspection and documentation
•Distributional effects: who will be more affected by the tax
(specific crop/fertilizer types)?
•Implementability: role of the CAP, WFD and other national
policies
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15. SEEAW UN Statistical Division 2003
OBJECTIVES:
• harmonizing methods/standardizing concepts for water
accounts
• provide conceptual framework for organizing eco/env info
• Address cross-sectorial issues and integrated resource
management
CONTENT:
• definitions + set of standard tables
• part 1 (consolidated): framework, physical/hybrid
supply&use tables, asset accounts
• part 2 (experimental): quality accounts, economic
valuation...
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16. NEXT STEPS: SEEAW and water quality
SEEAW based on material from UN 2003
New version expected form EEA but not provided
• SEAAW part 2 – Water quality (experimental): quality
accounts, economic valuation...scientific gaps
• How to assess WQ in SEEAW?
• Define water quality (e.g. What substances and indicators? spatial
differentiation and basin segments?)
• Can existing monitoring data be linked to hybrid accounts and how?
• How to extend SEEAW to macro level?
• Instrument targeted for basin Combine data on several basins?
Thank you!
The research leading to these results has received funding from
the European Community’s Seventh Framework Programme (FP7/2007-2013) / grant agreement n° 265213 –
Project EPI-WATER “Evaluating Economic Policy Instrument for Sustainable Water Management in Europe”.
BACK-UP SLIDES
1
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• Solve by OLS:
ehPC = 71.160 - 0.464 dfVP - 0.017 dfFP
R2 = 0,952
Significance: Constant : 0.000 ; dfFP : 0.006 ; dfVP : 0.000
• Solve by IV: In the first stage dfVP is quantified using the
variables POP and dfFP
ehPC = 68.025 - 1.080 dfVP - 0.024 dfFP
R2 = 0,984
Significance: Constant : 0.000 ; dfFP : 0.012 ; dfVP : 0.000
Hausman : p= 0.7325 ; There is not endogeneity
1
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19. ECONOMETRIC MODEL: RESULTS 2 (UVEG)
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20. SEEAW
Prepared by UN Statistical Division based on SEEA 2003
OBJECTIVES:
• harmonizing methods/standardizing concepts for water accounts
• provide conceptual framework for organizing eco/env info
• Address cross-sectorial issues and integrated resource management
CONTENT:
• definitions + set of standard tables
• part 1 (consolidated): framework, physical/hybrid supply&use tables,
asset accounts
• part 2 (experimental): quality accounts, economic valuation, examples (!)
WP4.4.b working in a context of scientific gaps
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21. SEEAW – Examples (framework)
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22. SEEAW – Examples (hybrid supply table)
Physical and monetary values
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1. Total output and supply (Monetary units)
of which
1.a Natural water (CPC 1800)
1.b Sewerage services (CPC 941)
2. Total supply of water (Physical units)
2.a Supply of water to other economic units
of which 2.a.1-Wastewater to Sewerage
2.b Total returns
3. Total (gross) emissions (Physical units)
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23. Performance of the system in place
Water quality
RIVERS:
• 96% at risk of not obtaining WFD good ecological status in 2015.
• natural appearance undergone major physical changes in last decades
(disappearance of streams)
• short water retention less vulnerable than lakes to N&P pollution.
• Major pollution pathway from pollution sources to the fjord/sea
LAKES:
• score below WD good ecological status
• 86% classified as at risk (15% because they are not monitored).
• N&P content higher than WFD good ecological status.
• long water retention worsen effect of N&P pollution
COASTAL AREAS:
• 100% classified as at risk, including fjord area
• terminal recipient of discharges and un-remediated pollution.
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EPI 1
Tax on Water Abstraction
Econometric model
Elasticity of Water
Demand
Environmental model
Effect of reduced water abstraction on surface water
quality
OUTCOME
EPI 1 indirect effect on water
quality
24. EPI1 – economic model
Objective: determine how (EPI-induced ) price changes influence
water use in ORB input to hydrological model
Information retrieved:
•Time series data on water supply in ORB (primary data)
•Economic and climatic variables (Price, income, temperature,
precipitation)
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25. EPI1 – env. model
EPI 1
Tax on Water Abstraction
Econometric model
Elasticity of Water
Demand
Environmental model
Effect of reduced water abstraction on surface water
quality
OUTCOME
EPI 1 indirect effect on water
quality
Future scenarios, drivers of change:
- expected future water withdrawal (SCENES, 2006-2010)
- population increase (SSP, 2012)
Estimate of water savings (EPI scenario):
-use of elasticity to drive water abstraction
-time horizon 2030-2050
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26. Econometric model and variables (with UVEG)
General econometric model:
Water use = β1* V1(price) + β2*V2(income) +
β2 * V3(climate)+ … + ε
(Arbués et al., 2003; Dalhuisen et al., 2003; Ruijs et al., 2008; Schleich and
Hillenbrand, 2009)
Variables:
dtVP: Deflated total variable price (Kr/m3) (2010=100)
dtFP: Deflated total fixed price (Kr/m3) (2010=100)
ehWS: Total water sold to households (m3)
POP: Users (person)
ehPC: per capita household water consumption (m3/person)
(ehWS/POP)
• Solve by OLS:
lnehPC = 6.047 - 0.287 lndfFP - 0.118 lndfVP
R2 = 0,928
Significance: Constant : 0.000 ; lndfFP : 0.000 ; lndfVP : 0.003
• Solve by IV: In the first stage lndfVP is quantified using the
variables POP and lndfFP
ln ehPC= 4.275 - 0.186 lndfFP - 0.469 lndfVP R2
= 0,980
Significance: Constant : 0.000 ; dfFP : 0.007 ; dfVP : 0.000
Hausman : p= 0.6254 ; There is not endogeneity
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11.Econometric model - results
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28. NEXT STEPS EPI1 – env. model
EPI 1
Tax on Water Abstraction
Econometric model
Elasticity of Water
Demand
Environmental model
Effect of reduced water abstraction on surface water
quality
OUTCOME
EPI 1 indirect effect on water
quality
SWAT Thodsen et al. (in preparation) models conc. nutrients, Nitrates,
Ammonium, organic N, dissolved P, organic P, etc. based on data
on (absolute) loads of N, P, etc. (calibrated for ORB)
Modeling water abstraction:
•Geographic location of the abstraction (sub-basin)
•Monthly/yearly abstraction
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Hypothesis:
•Upstream segment:
abstraction-related WQ
changes
•Fjord: abstraction no
influence on water/nutrient
loads
Objectives:
•Historical analysis
with/without water
abstraction tax
•BAU + EPI1 future
scenarios
29. NEXT STEPS EPI1 – env. model (SWAT)
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EPI 2
Tax on N load from
agricolture
Economic model
Effect of EPI on N use by
farmers
Environmental model
Reduced N conc. in
surface water from reduced N on arable
land
OUTCOME
EPI 2 direct effect on water
quality
30. EPI2 - economic model
•Optimization model (Fonnesbech-Wulff et al., 2010- Tech. report):
maximization of farmer’s profit (calibrated for ORB)
•Variables (and restrictions): matrix descriptive of farmers (ID
code of the farm, dimension, type of activities, and crop distribution), yield
functions (Yield = ƒ(amount of fertilizer), price of crops, costs (prices of
fertilizers, pesticides + fixed costs per crop)
•Output (of interest) amount of N applied to soil (with fertilizers)
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EPI 2
Tax on N load from
agricolture
Economic model
Effect of EPI on N use by
farmers
Environmental model
Reduced N conc. in
surface water from reduced N on arable
land
OUTCOME
EPI 2 direct effect on water
quality
31. NEXT STEPS EPI2 – env. model
N-LES (Simmelsgaard et al., 2000): models annual nitrogen losses at
ORB scale
Variables: crop rotations, soils and nitrogen input, water
percolating in root zone
Output: conc. of nutrient in surface water at specific monitoring
stations within ORB