Bringing the Environment into Environmental Economics Kurt Schwabe Associate Professor of Environmen

1
Bringing the Environment into Environmental
EconomicsKurt SchwabeAssociate Professor of
Environmental and Natural Resource
PolicyDepartment of Environmental
SciencesUniversity of California,
RiversideVisiting Flagship FellowCSIROAdelaide
, South AustraliaFebruary 27, 2008
2
Objectives

• Enjoy myself and drink a beer
• Reiterate importance of more accurate
  representations of the environment in our models
• Estimated costs of environmental regulations
• Perceived benefits from market-based instruments
  and, ultimately, their effectiveness
• Highlight importance of working more closely with
  natural, physical, chemical, or biological
  scientists
• Getting it right
• Unified Front

3
Outline

• I. Genesis of Bringing the Environment into
  Economics
• Early Mass Balance Process Models from RFF
• Seminal Articles on Using Permits to Control
  Pollution
• II. Case study 1 Nutrient Mgmt in the Neuse
  River Basin, NC
• Soil type and hydrology
• III. Case study 2 Nitrogen Mgmt and
  Californias Groundwater
• Supplies
• Importance of accounting for non-uniformity of
  irrigation
• Importance of treating nitrogen as a capital
  input stock pollutant
• Importance of accounting for water-nitrogen-yield
  relationships
• IV. Conclusions

4
Environment and Economics History of thinking
and modeling the environment

• Boulding (1966) Economics of the Coming of the
  Spaceship Earth
• Earth is a closed system
• Whats produced, consumed, discarded stays
• Ayres and Kneese (AER 1969) Kneese, Ayres, and
  dArge (1970)
• Formalized Boulding into a mass-balance framework
  using a GE framework
• Identifies processes and bi-products often
  overlooked with neoclassical approach

5
Resources for the Future Process Models

• Spofford et al. (1976) Environmental Quality
  Management An Application to the Lower Delaware
  Valley
• Empirical application incorporating process
  models
• Imposed material and energy balance
• Residuals biological oxygen demand heat,
  sludge, particulates, SO2, nitrogen, phenols,
  ash)
• Industries petroleum, municipal, incinerators,
  sugar refining, thermal power
• Changes in one residual stream would have a
  direct consequence on other residual streams
• Provided Framework to consider interactions with
• the environment

6
(No Transcript)
7
Efficiency and the Environment

• Dales (1968) Pollution, Property, and Prices
• Conceptualizes how markets for pollution can
  result in efficient solutions
• Montgomery (JET 1972) Markets in Licenses and
  Efficient Pollution Control Programs
• Formalized Dales (1968)
• Focused on air quality
• Tietenberg (1973 1985)
• Adds support and evidence of potential gains from
  market based instruments

8
Efficiency and the Environment (Montgomery, JET
1972)
9
Efficiency and the Environment
10
The Costs of Nutrient ReductionThe Neuse River
Basin Experience

• Kurt A. Schwabe
• Collaborators
• Dr. Wendall Gilliam Distinguished University
  Professor
• Department of Soil Science
• Dr. Robert Evans Distinguished Professor
• Department of Biological and Agricultural
  Engineering
• Dr. Wayne Skaggs Distinguished University
  Professor
• Department of Biological and Agricultural
  Engineering
• Dr. V. Kerry Smith Distinguished University
  Professor, Department of Agricultural and
  Environmental Economics
• Dr. Jim Easley, Professor
• Department of Agricultural Economics
• at the time the research was performed all were
  at North Carolina State University
• Schwabe (REE 2000 RAE 2001)

11
Current Problems and Policies

• Over ½ our river and lakes too polluted for
  swimming
• 48 of Coastal Waters are nutrient enriched
• Nonpoint sources, the largest unregulated source
  of water pollution, responsible for gt 50 of the
  problem
• Annual Water Pollution Control Costs ? 58
  billion

12
(No Transcript)
13
Objectives

• Focus on two objectives
• to evaluate the role of soil characteristics and
  location (hydrology) on the potential cost
  savings from an incentive-based (IB) system
  versus a command and control (CAC)
• to describe and evaluate cost savings from
  different regulatory systems

14
Empirical Model Development

• Two Objectives
• 1. Detail
• production activities
• control technologies
• environmental influences
• 2. Realism
• substitutability
• separability
• Continuity
• _____________
• Response functions/functional relationships are
  of limited ability for entire process...
• Use mathematical programming framework employing
  a structural process
• design...

15
(No Transcript)
16
Details Associated with the Nonpoint Sources1

• 12 County-Level Farms
• ProductionR - Corn, Cotton, SoybeansxConservati
  on till, Conventional Till
• Regions -Piedmont, Upper Coastal Plain, Lower
  Coastal Plain
• Controlc -- Vegetative Filter Strips, Controlled
  Drainage
• Environmental Indicesc -- Erodibility,
  Transmissivity, Slope
• Field to stream 0.5 (?)
• Stream Transportc -- g(distance, flow,
  temperature)
• Nutrients -- nitrogen, phosphorus
• Additional Loadings -- swine operations
• R region c county_________________________
• 1Sources NCSU Departments of Soil Science, Crop
  Science, Agricultural and Biological Engineering,
  
• Cooperative Extension Service NCDEM.

17
(No Transcript)
18
Submodels to Evaluate Heterogeneity and Policy
Specification

• Full Ag Model model allowing for heterogeneity
  in production activity, control technology,
  transport coefficient, and soil type.
• Homogeneous Transport Substitutes a 0.3 decay
  rate for each countys transport coefficient,
  which initially ranged from 0.04 to 0.95. In the
  Tar-Pamlico Trading Program, DEM1995 assigned
  all discharges a 0.3 decay rate.
• Homogeneous Soil Imposes a homogenous soil
  index on all land types. Affects effectiveness
  and unit costs of control technologies, and
  runoff potential. Research by Camacho1989 in
  the Chesapeake Bay, and DEM1995 in the
  Tar-Pamlico River Basin do not control for soil
  type.
• ----------------------------------
• Policy IB (flexible) constraint on basinwide N
  loadings at estuary
• CAC (rigid) constraint on each countys N
  loadings at estuary
• -----------------------------------
• Each countys output of corn, cotton, and
  soybeans fixed.

19
(No Transcript)
20
(No Transcript)
21
Effects of the Environment Under Alternative
Policies for a 30 Nutrient Reduction
______________ CAC -- command and control
(restrictions on each source's estuarine
loadings) IB -- incentive based (restrictions on
basinwide estuarine loadings)
22
Conclusions

• Soil characteristics and the nutrient transport
  system are important factors influencing cost
  differences of the alternative policy instruments
  
• Regulatory systems that take advantage of
  differences in abilities to reduce nutrient
  loadings can lead to large cost savings

23
Nitrogen as a Capital Input and Stock Pollutant
A Dynamic Analysis of Corn Production and
Nitrogen Leaching under Non-Uniform
IrrigationKnapp and Schwabe. AJAE. 2008.
24
Extent of Problem

• Nitrate contamination widespread in US (Nolan et
  al. 1998)
• 52 of community/57 of domestic water wells
  contaminated by nitrates
• Nitrate Problem most severe in California (Criss
  and Davidson 2004)
• 10 - 15 of California water supply wells exceed
  nitrate MCL
• Caused more well closures than any other
  contaminant in California
• Can be fatal to babies (especially if in formula)
• Nitrate inhibits uptake of iodine in thyroid
  (California DHS 2005)
• Methemoglobinemia/blue baby syndrome (Knobeloch
  et al. 2000)
• Exposure to nitrate contamination in drinking
  water linked to gastric cancer
• (Morales-Suarez-Varela et al. 1995 Xu et al.
  1992 Yang et al. 1998)
• Result State considering tightening standards
  in rural areas

25
Potential Solutions

• Treatment
• Quite expensiveapproximately 700 per ac-ft
• Dilution with high quality water
• Deepening of well
• Well abandonment
• Boiling? Worsens problem
• Bottled water? For drinking appr. 200,000 to
  500,000 per acre ft
• Source control
• Main Source of nitrate contamination -
  fertilizers from irrigated agriculture
• Water applied in excess of plant requirements
• Excess flows percolate below rootzone and enter
  groundwater

26
Approach

• Modeling
• Field level model
• Crop water production functions estimate from
  field experiments using neural net ideas
• Interseason carryover dynamics for N
• Spatial variability
• Evaluate
• Importance of spatial variation
• Behavioral regimes period by period vs. present
  value
• Alternative policy instruments

27
Neural Net Production Functions (Plot Level)

• Empirical Application (Tanji et al. 1979 Pang,
  Wu, and Letey 1998)
• 2-year field trial of corn production, Sacramento
  County, California
• Data Yield, N uptake, soil N, leachate N,
  mineralized N, carryover N
• (1) Yield f (applied water, N uptake)
• (2) N Uptake f (applied water, soil N)
• (3) N Leachate f (initial N, applied N, water)
• (4) Other N Losses f (applied N, initial N,
  water)
• Soil N f (initial N, applied N, N leachate)
• (6) Ending Soil N (soil N, N uptake, Other
  Losses)

28
Estimated Response Functions (w, n0na) Yield,
N-Uptake, N-leachate, and Carry-over N
29
Field-level production function

• Nonuniform (spatially variable) water
  applications over field
• (7)
• Where annual field average applied water
  depth.
• infiltration coefficient
• spatially distributed lognormal E(ß) 1
  s(ß) 0.3
• Field-level relationships for yield and nitrogen
• (8)
• (9)
• Discrete-time dynamic optimization problem
• (10)

30
Data
Market Prices and Production Cost data UC
Cooperative Extension Irrigation system costs
Posnikoff and Knapp (1997) Solver Nonlinear
Optimization using GAMS/CONCOPT Time horizon 30
years and a 5 discount rate
31
Model Specifications and Policy Instruments

• Behavioral Specification Spatial Specification
• Period-by-Period Optimization - PP Uniform - U
• Present value optimization PV Nonuniform - NU
• Four Models PP-U
• PP-NU
• PV-U
• PV-NU
• Three Policy Options Nitrogen Emissions Charge
  Pe
• Nitrogen Input Charge PN
• Water Input Charge PW

32
Time paths for nitrogen and water
applicationsdynamic and spatial comparisons
33
Time path for nitrogen leaching dynamic and
spatial comparisons
34
Table 1. Implications of Model Specification

• Assume PV-NU is correct specification
• Consequences of assuming PP optimization and
  irrigation uniformity

35
Table 2. Comparison of Optimal SS Values under
Alternative Policy Instruments with Nonuniform
Irrigation
36
Conclusions

• Previous research on nitrates and irrigated
  agriculture largely
• ignore field-level spatial variability and
  carry-over dynamics
• Consequences of overlooking spatial element
  severe
• Gross underestimate of nitrogen leaching and
  water application rates
• Overlooking dynamic aspects of problem results in
  lower nitrogen and higher water application rates
  than is optimal
• Higher perceived net benefits
• Water input charge results in fewer emissions at
  lower cost to grower than N input charge
• As expected, both less efficient than a N
  emissions charge

37
Summary

• Representation of environment (including
  biophysical processes) is important
• Influences estimated profits or costs of any
  activity
• Influences relative attractiveness of alternative
  policy instruments for pollution control / water
  allocation
• Influences effectiveness of permit system
• Working with natural scientists can provide
  multiple benefits
• Getting at ground truth
• Unified voice.