drivers of water conservation policies in rural and municipal systems: results of a regional survey...
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Drivers of water conservation policies in rural and municipal
systems: Results of a regional survey
Damian C. Adams and Chris N. Boyer
Oklahoma State University
Department of Agricultural Economics
Departmental Seminar
February 19, 2010
Background and problem statement
Water supply problems in Southeastern US No longer an urban city or ‘dry state’ problem Droughts, population growth, diminishing access,
other persistent factors (Dziegielewski and Kiefer, 2008).
Rural and small water utilities considering: Price-based conservation (PC) measures that
encourage conservation through consumers’ water bills
Non-price conservation (NPC) measures that reduce water demand or reduce waste (Olmsted and Stavins, 2008)
Price-based conservation
P3: $5.00
P2: $4.00
P1: $3.00
Q1: 5,000 Q2: 10,000
Water Price
Quantity of Water
Non-price conservation
New or smart meters Mandatory or voluntary watering
restrictions Education/awareness Leak detection Water budgets/audits Incentives for efficient irrigation systems Xeriscaping Rebates/retrofits
Background and problem statement
Use of water conservation tools is largely unknown in the southern United States.
Small and rural utilities ignored by the literature: Past studies provide little insight for non-urban
utilities (e.g., USGAO, 2000) Past studies fail to consider water managers’
attitudes and perceptions about water conservation, which can drive the adoption decision (e.g., Inman and Jeffrey, 2006).
Project overview
Survey of water supply managers in 4 Southeastern states: Oklahoma, Arkansas, Florida and Tennessee
Objectives(1) Identify use of water conservation tools in small water
systems in Southeastern states(2) Identify barriers to price and non-price conservation
programs by water systems(3) Evaluate factors affecting water conservation strategy
(PC, NPC) use
Funded by Oklahoma Water Resources Research Institute and the USDA National Water Program
Survey design
Questions cover six categories: System characteristics/demographics Planning and investment Notification and approval Price conservation programs Non-price conservation programs Consequences and barriers to conservation
Expert review and pre-test (n=82)
Survey method
Dillman (2008) survey method: Pre-survey introduction email Two online survey emails Reminder emails Final online survey email Pre-hardcopy postcard Cover letter and hardcopy survey Reminder postcard Final hardcopy survey
Response rates
StateResponse
sSystems
Response Rate
Oklahoma 292 500 58%
Arkansas 149 395 38%
Florida 155 306 51%
Tennessee 99 212 47%
Total 695 1413 49%
87% of respondents completed the online version Rural coverage bias for online survey not found
(Boyer et al., forthcoming)
Survey Results
Utility size – by state
Oklahoma Arkansas Tennessee Florida Total0%
10%
20%
30%
40%
50%
60%
70%
SmallMediumLarge
State
Perc
en
tag
e o
f syste
ms
Ownership type – by size
Small Medium Large0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
MunicipalPrivateCooperativePublic water associa-tionPublic facilityRural water associa-tionMulti-cityPublic trust
System size
Perc
en
t of
syste
ms
Water use – by size
Small (<0.5mgd)
Medium (0.5-2 mgd)
Large (>2mgd)0%
10%
20%
30%
40%
50%
60%
70%
80%
ResidentialIndustrialCommercialOil and gasAgricultureWholesaleWasteOther
System size
Perc
en
tag
e o
f to
tal u
se
Water source – by state
Tennessee Oklahoma Arkansas Florida0%
10%
20%
30%
40%
50%
60%
70%
80%
Surface waterGroundwaterPurchasedSecondary source
State
Perc
en
t of
syste
ms
Water source – by size
Small Medium Large0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
Surface waterGroundwaterPurchasedSecondary source
System size
Perc
en
t of
syste
ms
Changes in water demand (per-capita)
Small Medium Large0%
10%
20%
30%
40%
50%
60%
Decreased >10%Decreased 5-10%Stayed sameIncreased 5-10%Increased >10%
System size
Perc
en
t of
syste
ms
Conservation use – by state
Florida Oklahoma Arkansas Tennessee0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
NonePCNPCBoth
State
Perc
en
t of
wate
r syste
ms
Conservation use – by size
small (<0.5mgd) medium (0.5-2mgd)
large (>2mgd)0%
10%
20%
30%
40%
50%
60%
70%
80%
NonePCNPCBoth
System size
Perc
en
t of
wate
r syste
ms
Type of non-price conservation
New o
r sm
art m
eter
s
Man
dato
ry re
stric
tions
Educ
ation/
awar
enes
s
Leak
det
ectio
n
Budg
ets/au
dits
Efficien
t irrigat
ion
system
s
Xeris
caping
Volunt
ary re
stric
tions
Rebat
es/re
trofit
s0%
2%
4%
6%
8%
10%
12%
Type of non-price tool
Use r
ate
Factors impacting demand
Small Medium Large0%
5%
10%
15%
20%
25%
30%
35%
40%
Population growthBusiness growth and economyWeatherInfrastructure leaksYard useChange in water ratesHigher standard of livingConservationWaste by consumers
System size
Perc
en
t of
syste
ms
Utilities’ plans to meet future demand
Small Medium Large0%
10%
20%
30%
40%
50%
60%
70%
80%
New supply - traditionalReplace/improve infras-tructursNew supply - alternativeChange ratesManage demandNo plans
System size
Perc
en
t of
syste
ms
Perceptions on climate change
Climate change will negatively and seriously impact supply
Yes 23%
No 29%
Not sure 39%
Plans for responding to climate change
Conservation program 14%
Repair infrastructure 5%
New supplies 16%
No plan/Studying 14%
Alternative supplies 3%
Perceptions of elasticity
5%35%
60%
Perceived Impact of a 10% Price Increase on Water Use
Increase
Decrease
10% indicated that demand would be elastic (10% or more change in demand per 10% increase in price)
Residential customers typically respond to a 10% increase in water rates with a 1% - 3% reduction in water usage (AWWA, 2000)
Barriers to conservation
No need for conservation
Limited staff
Insufficient funds for programs
Revenue requirements
Concern for low-income customers
Cost-effectiveness
Decision-maker awareness
Not enough political supports
Regulatory requirements
Not enough people care
Impacts on growth
0% 10% 20% 30% 40% 50%
Percent of systems
Barriers to conservation – key differences by size
Small Medium Large0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
Limited staffInsufficient funds for programsDecision-makers have lit-tle awareness of policy ef-fectiveness
System size
Perc
en
t of
syste
ms
Factors affecting conservation
Drivers of Water Conservation Strategy – Bivariate Probit Model
Probability of adopting PC and NPC, given demographics, etc:
• Φ2 is the bivariate standard normal cumulative distribution function
• x is a matrix of independent variables, • βPC and βNPC are vectors of parameter estimates, and
• ρ is the correlation between the equations for PC and NPC.
Allows direct examination of correlation between price and non-price conservation use
),','[|1,1Pr 2 xxxNPCPC NPCPC
Model statistics
Price-based Conservation
(PC)
Non-price Conservation
(NPC)
Model fit (Percent correctly predicted)
92.52% 74.96%
Model test statistics Statistic P-value
Log Likelihood -311.22 -
Likelihood ratio: χ2 (84 d.f.) 770.34*** 0.0000
ρ (Relationship between PC and NPC) -0.0430 0.8227
LR test of rho = 0: χ2 (1 d.f.) 0.0502 0.8227
* Significant at the 10% level; ** Significant at the 5% level; *** Significant at the 1% level. § Excludes insignificant variables, except two variables central to the study: climate change and Arkansas.
Dependent variablePrice-based
Conservation (PC)
Non-price Conservation
(NPC)
Independent variable§ Coefficient P-value Coefficie
nt P-value
Demographics
Florida 0.786*** 0.024 1.515*** 0.000
Oklahoma 0.883** 0.001 0.031 0.920
Arkansas 0.192 0.539 0.392 0.174
Small size (< 0.5 million gallons/day) 0.297* 0.065 -0.236 0.310
Groundwater source 0.434** 0.033 -0.462** 0.040
Has secondary source -0.756** 0.004 -1.241** 0.014
Government recommends cons. adoption -0.007 0.983 1.275*** 0.004
Management recommends cons. adoption -0.880** 0.039 0.162 0.692 Had a per-capita water use increase, last 5 yrs 0.279 0.122 -0.413* 0.099
Notify customers of rate changes - website 0.041 0.870 0.898*** 0.002
Notify customers of rate changes - meeting -0.102 0.538 -0.366* 0.056
Notify customers of rate changes - mail out 0.406** 0.011 -0.036 0.862
Attitudes and Perceptions
Determining rate schedule - cost of delivery 0.236** 0.028 0.190 0.129
Determining rate schedule - consumer waste 0.029 0.714 -0.177* 0.053
Increased the average rate in last five years 0.219 0.156 0.435** 0.022
Reason for past rate increase - treatment costs 0.412** 0.012 -0.194 0.406
Reason for past rate increase - system maintenance 0.599** 0.036 0.126 0.705
Reason for past rate increase - conservation 1.490*** 0.000 1.067*** 0.009
Internally studied demand elasticity 0.681** 0.027 -0.048 0.903
Believes users do not respond to price increases -0.119 0.443 -0.591*** 0.003
Climate change will not impact water supplies -0.056 0.743 -0.034 0.201
Dependent variablePrice-based
Conservation (PC)
Non-price Conservation
(NPC)
Independent variable§ Coefficient P-value Coefficie
nt P-value
Dependent variablePrice-based
Conservation (PC)
Non-price Conservation
(NPC)
Independent variable§ Coefficient P-value Coefficie
nt P-value
Future Planning
Meet future demand - alternative source 0.565** 0.029 1.204*** 0.000
Meet future demand - infrastructure expansion/replacement 0.410** 0.016 0.127 0.499
Meet future demand - manage demand 0.870*** 0.000 -0.210 0.460
Barrier to meeting demand - treatment costs 0.275* 0.083 -0.108 0.597
Barrier to meeting demand - consumer waste 0.001 0.940 -0.026* 0.063
Barrier to meeting demand - inability to increase withdrawals from source -0.479* 0.084 0.847*** 0.006
Barrier to meeting demand - population growth 0.123 0.448 -0.637*** 0.001
Notable implications
Lack of knowledge/resources a barrier to adopting conservation Elasticity studies Technical/staff resources
Significant educational opportunities Use of conservation programs/pricing Views on elasticity, revenue change,
climate change, etc Decision-making and information provision Planning and barriers
Conclusion
Key differences by utility size Use of conservation tools Attitudes/perceptions of barriers, climate change, elasticity
Very different set of factors drive PC, NPC decisions - implications for policy
Demographics, attitudes and perceptions, and future planning successfully predict conservation strategies
Using model to evaluate feasible water conservation tools for rural and small systems given their characteristics and consumers’ willingness to adopt (future work)
Thank you
Discussion - Demographic variables
Florida and Oklahoma utilities more likely to adopt PC; Florida utilities more likely to adopt NPC.
Small utilities were likely to adopt PC. This could be due to rural utilities trying to maintain revenue streams as they lose customers or face increasing production costs.
Systems using groundwater were more likely to adopt PC and less likely to adopt NPC.
Having a secondary water source to meet demand decreases the likelihood of PC and NPC.
More likely to adopt NPC if a government agency normally makes recommendations.
Less likely to adopt if utility management is responsible for making recommendations.
Systems that rely on mail-outs are more likely to use PC; those that post their information online are more likely to adopt NPC.
Discussion - Attitudes and perceptions Having increased average rates in the last five years increases
odds of NP. These utilities could be using NPC since price increases are already being used to cover inflation and increasing costs.
Having increased rates to signal conservation, increases odds of adopting PC and NPC.
Higher likelihood of PC if past rate increases were due primarily to treatment costs and system maintenance. PC might help utilities cover costs of delivery and infrastructure repair and maintenance more effectively than uniform rates or declining block rates.
Internally measuring water demand elasticity increases the likelihood of PC. Measuring a price demand elasticity helps providers better understand impacts on their revenue stream, and suggests critical self-evaluation that might result in more efficiency gains.
Views of potential impacts from climate change on water supplies are not significant.
Discussion - Future planning
Planning to use alternative water source increases likelihood of PC and NPC.
Planning to expand or replace infrastructure increases likelihood of adopting PC.
Believing that higher treatment costs are a barrier to meeting future demand increases PC adoption, which also implies PC is viewed as more effective for covering costs.
Viewing consumer waste and population increases as primary barriers to meeting demand reduces the likelihood of adopting NPC. This might suggest that NPC is not effective at reducing per-capita consumption.