wp 4.4 · alcalá de henares (madrid, spain) 06 january 2013 massimo pizzol ... • harmonizing...

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

1

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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10

20

30

40

50

60

1997 1998 1999 2000 2001 2002 2003 2004

Water Consumption (Mm3)

Households

Irrigation (privatecollection)

TOTAL Drinkingwater

Total industrial

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10

20

30

40

50

60

70

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82

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83

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84

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85

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86

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90

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91

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99

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00

20

01

20

02

20

03

20

04

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

3

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

4

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

6

6. Contributors other than AU

7

EPI 1


Econometric model

Elasticity of Water

Demand

Environmental model


quality

OUTCOME


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

20

25

30

35

40

45

00

10

20

30

40

50

60

70

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)

11

EPI 2

Tax on N load from

agricolture

Economic model


farmers

Environmental model

Reduced N conc. in


land

OUTCOME


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

15

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...

16

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

8

• 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


Hausman : p= 0.7325 ; There is not endogeneity

1

9

19. ECONOMETRIC MODEL: RESULTS 2 (UVEG)

20

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

21

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)

23

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.

24

EPI 1


Econometric model

Elasticity of Water

Demand

Environmental model


quality

OUTCOME


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)

25

25. EPI1 – env. model

EPI 1


Econometric model

Elasticity of Water

Demand

Environmental model


quality

OUTCOME


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

26

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


Hausman : p= 0.6254 ; There is not endogeneity

27

11.Econometric model - results

28

28. NEXT STEPS EPI1 – env. model

EPI 1


Econometric model

Elasticity of Water

Demand

Environmental model


quality

OUTCOME


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

29

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)

30

EPI 2

Tax on N load from

agricolture

Economic model


farmers

Environmental model

Reduced N conc. in


land

OUTCOME


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)

31

EPI 2

Tax on N load from

agricolture

Economic model


farmers

Environmental model

Reduced N conc. in


land

OUTCOME


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

wp 4.4 · alcalá de henares (madrid, spain) 06 january 2013 massimo pizzol ... • harmonizing...

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