UPDATE OF THE ECONOMIC VALUATION OF THAMES TIDEWAY...

UPDATE OF THE ECONOMIC VALUATION OF

THAMES TIDEWAY TUNNEL ENVIRONMENTAL

BENEFITS

Final Report

For the Department for Environment Food and Rural Affairs (Defra)

August 2015

eftec

73-75 Mortimer Street

London W1W 7SQ

tel: 44(0)2075805383

fax: 44(0)2075805385

[email protected]

www.eftec.co.uk

mailto:[email protected]

http://www.eftec.co.uk/

Update of Thames Tideway Tunnel Environmental Benefits Valuation Final Report

eftec August 2015 i

This document has been prepared for the Department for Environment Food and Rural Affairs

(Defra) by:

Economics for the Environment Consultancy Ltd (eftec)

73-75 Mortimer Street

London

W1W 7SQ

www.eftec.co.uk

Study team:

Allan Provins (eftec)

Erin Gianferrara (eftec)

Shannon Anderson (eftec)

Ece Ozdemiroglu (eftec)

Bruno Lanz (Graduate Institute Geneva and eftec associate)

Peer reviewers

Prof. Ian Bateman (University of East Anglia)

Dr. Paul Metcalfe (PJM Economics)

Acknowledgements

The study team would like to thank the peer reviewers and members of the Defra steering group for

their input and contributions to the study and reporting. Thanks also to staff from the Environment

Agency, Thames Water Utilities and Thames Tideway Tunnels who have provided data and

information that have supported the analysis.

eftec offsets its carbon emissions through a biodiversity-friendly voluntary offset purchased from

the World Land Trust (http://www.carbonbalanced.org) and only prints on 100% recycled paper.

http://www.eftec.co.uk/

http://www.carbonbalanced.org/


eftec August 2015 ii

CONTENTS

EXECUTIVE SUMMARY ................................................................................ iii

1. INTRODUCTION ................................................................................... 1

1.1 BACKGROUND ............................................................................................... 1 1.2 STUDY OBJECTIVES .......................................................................................... 1 1.3 REPORT STRUCTURE ......................................................................................... 2

2. APPROACH ........................................................................................ 3

2.1 THAMES TIDEWAY STATED PREFERENCE STUDY ............................................................... 3 2.2 AGGREGATE BENEFITS ESTIMATES - 2006 STATED PREFERENCE STUDY ....................................... 4 2.3 UPDATING THE THAMES TIDEWAY TUNNEL BENEFIT ESTIMATE ............................................... 5 2.4 SCOPE OF THE IMPROVEMENT ................................................................................ 6 2.5 ECONOMIC VARIABLES ....................................................................................... 7 2.6 AFFECTED POPULATION..................................................................................... 12

3. ANALYSIS .........................................................................................14

3.1 ECONOMETRIC ESTIMATION ................................................................................. 14 3.2 TRANSFERABLE WTP FUNCTION ............................................................................ 16

4. RESULTS ..........................................................................................21

4.1 AGGREGATE BENEFIT ESTIMATES ............................................................................ 21 4.2 ADMINISTRATIVE JURISDICTION ............................................................................. 22 4.3 BENEFITS JURISDICTION .................................................................................... 23

5. CONCLUSIONS ...................................................................................24

5.1 SUMMARY .................................................................................................. 24 5.2 KEY FINDINGS .............................................................................................. 24

REFERENCES ...........................................................................................26

ANNEX 1: LITERATURE REVIEW ....................................................................29

ANNEX 2: SCOPE OF THAMES TIDEWAY IMPROVEMENTS ......................................34

ANNEX 3: TEMPORAL AGGREGATION PARAMETERS .............................................49

ANNEX 4: ECONOMETRIC RESULTS ................................................................53

ANNEX 5: ANNUAL AGGREGATE BENEFITS .......................................................55

ANNEX 6: SENSITIVITY ANALYSIS ...................................................................57


eftec August 2015 iii

EXECUTIVE SUMMARY

ES.1 Introduction

In 2006, the study Thames Tideway - Stated Preference Survey (eftec, 2006) estimated the

monetary value of the benefits of the Thames Tideway Tunnel, in terms of the ecology, human

health, and amenity improvements. Results from the study were applied in a cost-benefit analysis

(CBA) of alternative options for reducing the incidence of combined sewer overflows (CSOs) in the

Thames Tideway (Nera, 2006). This informed the Regulatory Impact Assessment (RIA) for sewage

collection and treatment options in London that was undertaken in 2007. The 2006 CBA was

subsequently updated by Defra (2011) in the publication of the strategic and economic case for the

Thames Tideway Tunnel.

Defra expects to publish the Business Case for the Thames Tideway Tunnel, following the award in

2015 of competitively tendered contracts by Thames Water and the signing of a Government

Support Package outlined in a written Ministerial statement (Cabinet Office, 2014). The main

construction work is scheduled to commence in 2016.

ES.2 Study objective

The purpose of this study is to update the economic evidence concerning the benefits of reduced

frequency of CSOs to the Thames Tideway and the consequent environmental improvements and

reduction in risk to human health. The specific research aims are:

1. Establish any change in the scope of the expected benefits to the Thames Tideway, in relation

to the ‘with’ Thames Tideway Tunnel and ‘without’ Thames Tideway Tunnel (the baseline)

conditions, including the frequency of overflows from CSOs;

2. Review and update the analysis of the 2006 stated preference data to provide revised

monetary estimates of the benefits of improvements to the Thames Tideway; and

3. Determine the impact on aggregate benefits by accounting for changes in economic and

demographic variables over the appraisal period, including population and real income growth.

The scope of the study focuses on survey data compiled in the 2006 stated preference survey and

supporting information collated from relevant secondary data sources (e.g. projected population

growth, household income growth). The review of the baseline (the ‘without’ case) and impact of

the tunnel (the ‘with’ case) is informed by the evidence submitted for the Development for

Consent Order by Thames Water Utilities Limited (TWUL) (Thames Tideway Tunnel) (Thames Water,

2014).

ES.3 Thames Tideway stated preference study

The 2006 Thames Tideway stated preference study applied a contingent valuation design to

establish the benefits of the Thames Tideway Tunnel in term of household willingness to pay (WTP)

to reduce the impact of CSOs on the Thames Tideway. The impact of the tunnel option was

presented in terms of:

Impact on fish population: number of times per year when oxygen levels in the Tideway drop

low enough to either kill fish or prevent migration;


eftec August 2015 iv

Impact on sewage litter: number of times per year when sewage litter is visible following

overflows;

Impact on risk of suffering illness through contact with river water: number of times per year

when there is a higher risk to health following overflows; and

Frequency of overflows: number of times per year on average.

The 2006 study reported the benefits of the Thames Tideway Tunnel in annual aggregate terms

(£/year) for two alternative ‘jurisdictions’:

Administrative jurisdiction: this aggregated the benefits over the Thames Water sewerage

services customer base. This perspective is confined to the benefits that are derived by the

population who will finance the Thames Tideway Tunnel.

Benefits jurisdiction: this accounted for the benefits derived across the population of England

from improvements to the Thames Tideway.

ES.4 Updating the Thames Tideway Tunnel benefit estimate

The basis for updating the estimated benefits of the Thames Tideway Tunnel is provided by Defra’s

value transfer guidelines (eftec 2010a; 2010b), which set out the key principles for valuing

environmental impacts in policy and project appraisal. The guidelines highlight the main economic

relationships that are expected to influence WTP for environmental improvements:

Scope of the improvement: the ecological, human health and amenity benefits delivered by

the Thames Tideway Tunnel. Largely, the scope of the improvement assessed in the 2006 study

is consistent with the current situation. Further detail on this assessment is provided in the

Main Report and Annex 2.

Cost: this is the cost to households of enjoying the benefits that are provided. For a physically

located improvement in environmental quality - such as the Thames Tideway improvements -

this relates to the proximity to a household and the associated travel and time costs. The 2006

study and the updated analysis control for this relationship by applying a spatially sensitive

aggregation procedure (see Main Report).

Substitutes: the availability and quality of alternatives (substitutes) for the Thames Tideway

improvements. Review of water quality improvements at a national scale reveals positive

changes expected between 2009 and 2015 in most regions, although a lesser change in the

Thames River Basin District. These small changes suggest that the scope of substitutes remains

largely unchanged from that in 2006.

Income: the budget which constrains all economic demands of a household, including WTP for

environmental quality improvements. The 2006 study and the updated analysis explicitly

control for this relationship by including household income and other socio-economic

characteristics as a constraint on the value of the Thames Tideway improvements.


eftec August 2015 v

ES.4 Results

Annual aggregate benefits (£/year) associated with the improvements to the Thames Tideway are

mapped in Figure ES.1. This shows the spatial variation in aggregate benefits as determined by

increased distance from the Thames Tideway, differences in household income, and population

(number of households with an area). As expected, the greatest aggregate benefits are observed in

areas closest to the Thames Tideway in London and the South East, with a ‘distance decay’ effect

in aggregate benefits as distance from the Thames Tideway increases.

Table ES.1 reports the benefits estimates in present value terms, over a 120 year time horizon1.

Future values are discounted in line with HM Treasury (2003) guidance. Four scenarios are

considered which establish the sensitivity of results to different assumptions concerning household

income growth and population growth over the 120 year time horizon:

Scenario A: profiles annual benefits over time based on 2014 population and income levels.

This provides the most conservative aggregation scenario.

Scenario B: profiles annual benefits over time by incorporating forecast population growth.

This scenario is consistent with the statutory requirements of water companies to incorporate

population projections into medium to long term planning.

Scenario C: profiles annual benefits incorporating the effect of forecast growth in household

income on the value of the Thames Tideway improvements.

Scenario D: profiles annual benefits incorporating both forecast population growth and

household income growth. This represents the least conservative aggregation scenario.

In all four scenarios, annual benefits are assumed to commence from 2024 when the Thames

Tideway Tunnel becomes fully operational (year 10 of the 120 year time horizon). Annual aggregate

benefits are assumed to be zero during the period 2014-232.

Table ES.1: Aggregate benefit estimates – present value terms (2014, £)

Scenario Administrative jurisdiction

(Thames Water region)

Benefits jurisdiction

(National population)

Scenario A £2.7 bn £7.4 bn

Scenario B £3.4 bn £9.1 bn

Scenario C £3.8 bn £10.1 bn

Scenario D £4.7 bn £12.7 bn

Notes: Present values calculated based on: 3.5% discount rate for years 0 – 30; 3.0% rate for years 31 – 75; and

2.5% rate for years 76 – 120 (HM Treasury, 2003).

For the administrative jurisdiction (Thames Water sewerage customers only), overall benefits are

estimated to be in the region of £2.7 – £4.7 billion in present value terms (across Scenarios A-D).

Factoring in the national population, aggregate benefits are estimated to be in the region of £7.4 -

£12.7 billion in present value terms. Accounting for the scope of the benefits jurisdiction for the

Thames Tideway improvements – which is approximately four times the administrative jursidiction

population - almost triples the overall benefits estimates.

1 The updated analysis applies the 120 year appraisal time horizon to be consistent with TWUL Infrastructure

Provider financial model (Ernst & Young, 2014). 2 Annex 6 reports results from sensitivity analysis considering: (i) a 60 year time horizon consistent with the

original CBA (Nera, 2006); and (ii) the timing of benefits (assuming they commence in 2015).


eftec August 2015 vi

Figure ES.1: Annual aggregate benefit of Thames Tideway improvements (£/yr)

Note: Values presented in 2006 price terms. Aggregate annual values mapped at the ONS middle layer super output area

(MSOA) level – see Main Report for further detail.


eftec August 2015 1

1. INTRODUCTION

1.1 Background

In 2006, the study Thames Tideway - Stated Preference Survey (eftec, 2006) estimated the

monetary value of the benefits of the Thames Tideway Tunnel, in terms of the ecology, human

health, and amenity improvements. Results from the study were applied in a cost-benefit analysis

(CBA) of alternative options for reducing the incidence of combined sewer overflows (CSOs) in the

Thames Tideway (Nera, 2006). This informed the Regulatory Impact Assessment (RIA) for sewage

collection and treatment options in London that was undertaken in 2007.

The 2006 CBA was subsequently updated by Defra (2011) in the publication of the strategic and

economic case for the Thames Tideway Tunnel. This analysis accounted for revisions to the Thames

Tideway Tunnel project costs, inflated the benefit estimates to 2011 prices, and extended the

appraisal time horizon to 100 years from 60 years in the RIA to account for the expected lifetime of

the tunnel.

Defra expects to publish the Business Case for the Thames Tideway Tunnel, following the award in

2015 of competitively tendered contracts by Thames Water and the signing of a Government

Support Package outlined in a written Ministerial statement in June 20143. The main construction

work is scheduled to commence in 2016.

1.2 Study objectives

The purpose of this study is to review and update the economic evidence that informs the Business

Case for the Thames Tideway Tunnel, namely the benefits of reduced frequency of CSOs to the

Thames Tideway and the consequent environmental improvements and reduction in risk to human

health.

The specific research aims of the study include:

1. Establish any change in the scope of the expected benefits to the Thames Tideway, in relation

to the ‘with’ Thames Tideway Tunnel and ‘without’ Thames Tideway Tunnel (the baseline)

conditions, including the frequency of overflows from CSOs;

2. Review and update the analysis of the 2006 stated preference data to provide revised

monetary estimates of the benefits of improvements to the Thames Tideway; and

3. Determine the impact on aggregate benefits by accounting for changes in economic and

demographic variables over the appraisal period, including population and real income growth.

The scope of the study focuses on survey data compiled in the 2006 stated preference survey and

supporting information collated from relevant secondary data sources, including economic

information (price index, projected household income growth) and demographic data (2011 Census

and population projections over the time horizon for the analysis). The review of the baseline (the

‘without’ case) and impact of the tunnel (the ‘with’ case) is informed by the evidence submitted

for the Development for Consent Order by Thames Water Utilities Limited (TWUL) (Thames Tideway

Tunnel) (Thames Water, 2014).

3 See: Cabinet Office (2014).


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Aggregate benefit estimates are presented in 2014 price terms. The updated analysis applies the

120 year appraisal time horizon to be consistent with TWUL Infrastructure Provider financial model,

in which a 120 year life for regulatory capital value (RCV) purposes is assumed (Ernst & Young,

2014).

1.3 Report structure

This report sets out the approach and analysis undertaken to update the estimated benefits of the

Thames Tideway Tunnel. Following this introduction:

Section 2 presents the structure of the analysis and establishes the range of data and

information that supports the updated benefit estimates;

Section 3 reports the update of the econometric analysis of the 2006 stated preference data,

including estimated models and unit benefit values;

Section 4 presents aggregate benefit estimates for a number of scenarios that test the

sensitivity of results to key assumptions in projecting the profile of benefits overtime; and

Section 5 concludes and summarises the main findings of the study.

In addition, four supporting annexes are provided. Annex 1 provides a summary of economic

valuation literature that examines the validity of applying the results of stated preference studies

at subsequent points in time. Annex 2 provides a discussion of the scope of Thames Tideway

improvements and extracts from the 2006 study stated preference survey information, which

described the Thames Tideway improvements to respondents. Annex 3 presents the main

parameters applied for projecting benefits over time. Annex 4 reports further results from the

econometric testing undertaken as part of the updated analysis, including alternative model

specifications not tested in the 2006 study. Annex 5 presents annual aggregate benefit results for

the national population and the Thames Water customer base, respectively.


eftec August 2015 3

2. APPROACH

2.1 Thames Tideway stated preference study

The 2006 Thames Tideway stated preference study applied a contingent valuation design to

establish the benefits of the Thames Tideway Tunnel in term of household willingness to pay (WTP)

to reduce the impact of CSOs on the Thames Tideway4. It examined preferences for three

engineering options: (i) a large (7.2 metre diameter) tunnel across much of the central part of the

Tideway; (ii) a smaller (5 metre diameter) tunnel along the same length; and (iii) two tunnels (one

in the east and one in the west of the Tideway in London)5.

The impact of each tunnel option was presented in terms of:

1. Impact on fish population: number of times per year when oxygen levels in the Tideway drop

low enough to either kill fish or prevent migration;

2. Impact on sewage litter: number of times per year when sewage litter is visible following

overflows;

3. Impact on the risk of suffering illness through contact with river water: number of times per

year when there is a higher risk to health following overflows; and

4. Frequency of overflows: number of times per year on average.

The main survey questionnaire was administered to 875 respondents in total. Of these, 599 were

Thames Water customers. The remaining 276 other water company customers were sampled at

selected points in the rest of England.

The validity of 2006 study was examined in detail in eftec (2006). In accordance with conventional

validity testing protocols for stated preference studies (Bateman et al., 2002), the analysis

considered both the content validity of the survey and construct validity of the results. Content

validity refers to how well respondents understood the information provided on the Thames

Tideway improvements and whether their responses are genuine reflections of the value derived

from reduced impacts to fish populations, sewage litter, and human health risk. Construct validity

relates to whether stated preference survey results are consistent with prior expectations, based

on both underpinning economic theory and empirical results from other studies. Overall it was

concluded in eftec (2006) that the study demonstrated a high level of construct validity and that no

significant biases are evident in survey responses. Further assessment of the validity of the 2006

survey is not undertaken in this study.

Applying the 2006 survey data to provide an updated benefit estimate for the Thames Tideway

Tunnel, however, entails the implicit assumption that it is valid to utilise this information on

preferences for the Thames Tideway improvements approximatety nine years after it was elicited.

In effect this represents a ‘temporal transfer’ of economic valuation evidence. Annex 1 presents a

summary of empirical literature that has tested the temporal stability of individuals’ preferences

and WTP for environmental quality improvements. In general, the available evidence tends to

4 See Annex 1 for a short introduction to the contingent valuation method.

5 The proposed route of the tunnel as presented to respondents in the 2006 survey is set out in Annex 2 (see

Appendix to Annex 2 – extract of 2006 survey show material). Annex 2 also presents the route of the tunnel and location of the main CSOs (see Figures A2.1 and A2.2).


eftec August 2015 4

support the temporal transfer of economic valuation data in the short to medium term (e.g. around

10 years) as there is no evidence that unequivocally challenges the assumption of the stability of

individuals’ preferences over such a timespan.

A key conclusion, though, is that temporal transfers should take into account adjustments to

valuations that may be required because of intervening changes in economic factors that are

expected to influence WTP. For example, if household incomes have altered since the original

survey then this should be accounted for as it may change the constraints upon individuals’ ability

to express their WTP (a similar argument can be made with respect to changes in the availability of

substitute good). These general economic relationships and their expected influence on WTP for

the Thames Tideway improvements are outlined in Section 2.3.

2.2 Aggregate benefits estimates - 2006 stated preference study

2.2.1 Calculation of annual aggregate benefits

The 2006 study reported the benefits of the Thames Tideway Tunnel in annual aggregate terms. A

‘spatially sensitive’ aggregation process was applied, which estimated unit WTP for a given

geographical area, and multiplied this by the household population of that area (the number of

households) to calculate the annual benefit. Therefore annual benefits were estimated as:

𝐵𝑗 = 𝑊𝑇𝑃𝑗 × 𝑎𝑓𝑓𝑒𝑐𝑡𝑒𝑑 𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛𝑗 [1]

Where Bj is the annual benefit (£/year) for the geographical area j, WTPj is the unit WTP for area j

(£/household/year) and the affected population is the household population of area j (number of

households). In the 2006 study, annual benefits were calculated at the ONS enumeration district

level, which represented approximately 120 households (see Section 2.5.1).

The 2006 study grouped geographical areas under two alternative ‘jurisdictions’ (boundaries):

1. Administrative jurisdiction: this aggregated the benefits over the Thames Water sewerage

services customer base (i.e. summing annual benefit estimates for the ONS enumeration

districts within the Thames Water region). This perspective is confined to the benefits that are

derived by the population who will finance the Thames Tideway Tunnel.

2. Benefits jurisdiction: this accounted for the benefits derived across the population of England

from improvements to the Thames Tideway (i.e. summing annual benefit estimates for all

enumeration districts within England).

In the original CBA, the annual benefit values for the administrative and benefits jurisdictions were

projected over a 60-year time horizon in present value terms in 2006 nominal prices (Nera, 2006).

The Defra (2011) update extended the time horizon to 100 years and inflated the annual values to

2011 prices.

2.2.2 Aggregate benefit estimates from the 2006 study

Aggregate benefit estimates from the 2006 study for the ‘large tunnel option’ are reported in Table

2,1. They are approximately £66 million per year for the administrative jurisdiction and £174

million per year for the benefits jurisdiction. Note that the benefits jurisdction (national

population) includes the administrative jurisdiction (Thames Water customer base), so the two


eftec August 2015 5

benefit estimates are not additive. In 2014 price terms, these estimates are equivalent to £83

million per year (administrative jurisdiction) and £218 million per year (benefits jurisdiction)6.

Table 2.1: Aggregate benefit estimates for the Thames Tideway Tunnel from the 2006 stated

preference study (2006, £)

Population

(no. households)

Annual aggregate value

(£m/yr)

Aministrative jurisdiction –

Thames Water customer base Approx. 5.0m £66m

Benefits jurisdiction – national

population (England) Approx. 20.5m £174m

Source: Table E.1 ‘large tunnel’ (eftec, 2006).

The annual benefits estimates (£/year) are derived from the calculation of a spatially sensitive unit

value (£/household/year) using a ‘transferable’ WTP function. The function-based approach for

estimating unit WTP within a given geographical area controlled for: (i) declining WTP per

household as distance from Thames Tideway increases; and (ii) variation in household socio-

economic characteristics in terms of socio-economic group (SEG). This approach is in contrast to

assuming constant WTP across a geographical area (e.g. average WTP), which implies all all

households in a given jurisdiction have the same WTP.

As Bateman et al. (2006) establish, applying a (constant) average value per household estimate

does not account for the spatial sensitivity in unit WTP and hence systematically over-estimates

aggregate benefits. In particular, calculating an average household WTP over the entire beneficiary

population will result in those with very high values – i.e. those likely to live close to the Tideway -

skewing the average WTP upwards to a level which is considerably higher than that of the typical

(median) household. Allowing the WTP to vary spatially (reflecting the expected decline in values

as distance from the Tideway increases) mitigates against this upward skew and provides a more

representative (and conservative, lower) aggregate value.

2.3 Updating the Thames Tideway Tunnel benefit estimate

Based on equation [1] above, the spatially sensitive estimates of unit WTP and the affected

population represent the two main parameters to be updated in this study. Population estimates

for the administrative and benefits jurisdictions are reviewed in Section 2.6 in relation to the

aggregation process.

The basis for establishing updated unit WTP values is provided by Defra’s value transfer guidelines

(eftec 2010a; 2010b), which set out the key principles for valuing environmental impacts in policy

and project appraisal. This includes an outline of the economic relationships that are expected to

influence economic values associated with environmental improvements. Household WTP for

improvements to Thames Tideway should be expected to be impacted by:

𝑊𝑇𝑃𝑗 = 𝑓(𝑠𝑐𝑜𝑝𝑒 𝑜𝑓 𝑖𝑚𝑝𝑟𝑜𝑣𝑒𝑚𝑒𝑛𝑡, 𝑐𝑜𝑠𝑡, 𝑠𝑢𝑏𝑠𝑡𝑖𝑡𝑢𝑡𝑒𝑠, 𝑖𝑛𝑐𝑜𝑚𝑒) [2]

Where WTPj denotes unit WTP for area j (£/household/year) and f(…) denotes that WTP is a

‘function of’ (i.e. determined by):

6 Based on the consumer price index (CPI) (see Section 2.5.4).


eftec August 2015 6

Scope of the improvement: as presented by changes in the ecological, human health risk and

amenity characteristics included in the survey;

Cost: this is the cost to households of enjoying the benefits that are provided. For a physically

located improvement in environmental quality - such as the Thames Tideway improvements -

this relates to the proximity to a household and the associated travel and time costs;

Substitutes: the availability and quality of alternatives (substitutes) for the improvement and

benefits provided; and

Income: the budget which constrains all economic demands of a household, including WTP for

environmental quality improvements.

These four factors are examined to assess how the unit value estimates from the 2006 study should

be updated. Scope is reviewed in Section 2.4. Substitutes, incomes and changes to prices are

reviewed in Section 2.5 (as ‘economic variables’). In addition, the size and socio-economic

characteristics of the affected population are also examined to update the aggregate benefits (see

Section 2.6).

2.4 Scope of the improvement

The scope of the improvement in the Thames Tideway is defined by the information presented to

respondents in the 2006 study. This included: (i) the frequency of overflows; (ii) the impact on the

health of fish and other wildlife; (iii) the impact on sewage litter; and (iv) the impact on the risk of

suffering illness though contact with river water. The benefits of the improvements were

represented as the difference between the ‘without’ Thames Tideway Tunnel case and the ‘with’

Thames Tideway Tunnel case:

‘Without’ the Thames Tideway Tunnel: the ‘baseline’ and continuing situation in the Thames

Tideway accounting for upgrades to sewage treatment works that – at the time of the study -

were expected to be completed by 2014.

‘With’ the Thames Tideway Tunnel: the impact of the Thames Tideway Tunnel in reducing the

frequency of overflows and impact on fish and wildlife, sewage litter and risk of illness.

The information presented to respondents in the 2006 study concerning the impact of the Thames

Tideway tunnel is described in Annex 2, and relevant extracts of the explanatory material are

included in the Appendix to Annex 2 for reference.

Subsequent to the 2006 study, the tunnel element of the Tideway improvements has been split

between the separate construction of the Lee Tunnel and the Thames Tideway Tunnel.

Construction work for the Lee Tunnel is due to be completed by the end of 2015. This means the

Lee Tunnel will be operational in advance of the Thames Tideway Tunnel, and hence the

improvements that will be delivered by it now form part of the baseline (the ‘without’ Thames

Tideway Tunnel case) for the updated benefits estimate for the Thames Tideway Tunnel.

The Lee Tunnel captures discharges to the River Lee (a tributary of the Thames Tideway) from the

CSO at the Abbey Mills pumping station (Stratford). Captured overflows are then conveyed to the

Beckton sewage treatment works. Abbey Mills represents the single largest CSO in volume terms

and consequently the Lee Tunnel addresses approximately 40% of total discharge (by volume) from

all CSOs that impact the Thames Tideway. However, given that the Lee Tunnel only addresses one


eftec August 2015 7

overflow (out of 35 in total), and that it impacts solely the lower tidal reaches of the Tideway, it

does not influence the sewage litter and human health risk impacts as described in the 2006 study.

This is because these impacts are largely determined by frequency and location of overflows, and

therefore are only addressed by the Thames Tideway Tunnel.

The main benefit of the Lee Tunnel is in relation to an improvement in conditions for fish and other

wildlife in the lower reaches. However, while the Lee Tunnel does result in significant

improvement, it does not achieve the satisfactory thresholds for the health of aquatic species.

These are only attained with the Thames Tideway Tunnel. As a result, the description of the

Thames Tideway Tunnel impact in the 2006 study is consistent with current information. This

assessment is presented in more detail in Annex 2, which sets out incremental improvements that

are delivered with respect to fish and ecology by the sewage treatment upgrades, the Lee Tunnel,

and the Thames Tideway Tunnel.

Overall it is concluded that the information provided to respondents in the 2006 study adequately

represents the beneficial impact of the Thames Tideway Tunnel, even when considering the

separate effect of the Lee Tunnel.

2.5 Economic variables

Changes in cost, substitutes and household income (and other socio-economic variables) are

expected to influence household WTP in real terms. For example changes in (real) household

income can impact the value of the Thames Tideway improvements relative to other goods and

services.

The general change in price levels over time (inflation) affects the nominal value of WTP. Since

valuations elicited in the 2006 study are in 2006 nominal prices, they are inflated to 2014 price

terms to ensure that they reflect a consistent level of purchasing power in the present day.

2.5.1 Cost/distance

A negative relationship between unit WTP and distance from spatially explicit improvements in

environmental quality is routinely observed in (non-market) economic valuation studies (Bateman

et al., 2006). Distance decay in benefits arises from the increased cost (e.g. travel and time costs)

a household faces the further they are away from a given environmental amenity. The effect may

also pick up the effect of lower costs to reach substitute assets which more distant households

experience. The 2006 study explicitly controlled for distance decay in unit values via the

application of a transferable WTP function. This was used to estimate WTP at the ONS enumeration

district level (approx. 120 households), by calculating the distance between the centre-point of the

enumeration district and the Thames Tideway.

Data available for the updated analysis is based on ONS output areas, which represent the spatially

disaggregated levels at which 2011 Census data are provided7. Lower layer super output areas

(LSOAs) represent on average 650 households, whilst middle layer super output areas (MSOAs)

represent around 7,500 households. As detailed subsequently, the MSOA level is the lowest level at

which household income data are available; hence this is used in the analysis. Distance to the

7 ONS output areas have replaced enumeration districts as the basis for provided spatially disaggregated Census data. See: http://www.ons.gov.uk/ons/guide-method/geography/beginner-s-guide/census/enumeration-districts--eds-/index.html [Accessed August 2015].

http://www.ons.gov.uk/ons/guide-method/geography/beginner-s-guide/census/enumeration-districts--eds-/index.html

http://www.ons.gov.uk/ons/guide-method/geography/beginner-s-guide/census/enumeration-districts--eds-/index.html


eftec August 2015 8

Thames Tideway is calculated from the MSOA centre point to the closest part of the improved

Thames Tideway.

2.5.2 Substitutes

Potential substitutes for the Thames Tideway improvements can be broadly or narrowly defined.

For example, substitutes for Thames Water customers could be improvements to other local water

bodies. Similarly, for the national population, substitutes could be improvements to other water

bodies in closer proximity to them than the Thames Tideway. Beyond this though, a household may

regard improvements to other aspects of environmental quality and amenity as substitutes to the

Tideway improvements (e.g. enhanced woodland recreation opportunities).

The effect of substitute quality and availability is, in part, captured within the distance decay

function approach used in the 2006 study. Indeed, this indicates to some extent, the iconic status

of the River Thames, since positive WTP is observed at considerable distance from the Tideway

improvements and outside of the Thames Water region. Nevertheless, it is necessary to examine in

general whether the quality of substitutes has changed since the 2006 study and whether this would

be expected to impact preferences for the Thames Tideway improvements. Focusing on the overall

status of the water environment in England, Table 2.2 summarises the proportion of water bodies

at good ecological status by River Basin District (RBD) in 2009 and as expected in 2015.

Table 2.2: Water Framework Directive classification for River Basin Districts in England

River Basin

District % of RBD surface water bodies at good ecological status or better

2009 Predicted 2015

Thames 23 25

Anglian 18 19

Humber 18 19

Northumbria 43 49

North West 30 33

Severn 29 34

South East 19 23

South West 33 42

Source: Environment Agency river basin management plans: https://www.gov.uk/government/collections/river-basin-

management-plans [Accessed September 2014].

In total for England, 24% of surface water bodies are assessed to be at good or better status (EA,

2013). However the overall quality of the water environment is not expected to improve

substantially over the period 2009 – 2015. The average increase in water bodies achieving good

status is around 6 percentage points, but is lower in the Thames RBD at 2 percentage points. This is

further illustrated in Figure 2.1 which shows the relatively minor predicted changes in WFD status

between 2009 (panel a) and 2015 (panel b) for the Thames RBD. Hence it is assumed that the

quality and availability of substitutes for the Thames Tideway has not changed significantly since

the 2006 study and this is not a key sensitivity to address with respect to updating unit WTP values.


eftec August 2015 9

Figure 2.1a: Thames RBD ecological status (2009)

Figure 2.1b: Thames RBD predicted ecological status (2015)

Source: Environment Agency – Water Framework Directive status data (August 2014).

2.5.3 Household income and other socio-economic variables

Sample profile

The 2006 survey data are re-weighted to reflect the current population profile. This is to ensure

that the aggregate benefits estimates are representative of the respective populations for the

administrative and benefits jurisdictions for the main demographic and socio-economic

characteristics (age, gender and socio-economic group). Re-weighting is based on 2014 ONS Census

updates. Table 2.3 provides a comparison of the 2006 population profiles to the 2014 data.


eftec August 2015 10

Table 2.3: Population profile (2006 vs. 2014)

2006 2014

England Thames Water

region

England Thames Water

region

Gender1

Male 49% 49% 49% 49%

Female 51% 51% 51% 51%

Socio-economic group2

SEG AB 52% 60% 54% 63%

SEG C1

SEG C2 48% 40% 47% 37%

SEG DE

Age in years3

18-34 29% 34% 32% 32%

35-59 44% 43% 40% 40%

60+ 27% 23% 27% 27%

Notes: 2006 profile as reported in eftec (2006). 2014 profile based on: 1Estimates from ONS (2012a); 2Estimates available at:

http://www.nomisweb.co.uk/census/2011/qs611ew; and 3Estimates from ONS (2014a). SEG = socio-economic group. Market

Research Society definitions are: A = professionals, very senior managers, etc.; B = middle management in large

organisations, top management or owners of small businesses, educational and service establishments; C1 = junior

management, owners of small establishments, and all others in non-manual positions; C2= skilled manual labourers; D =

semi-skilled and unskilled manual workers; E = state pensioners, casual and lowest grade workers, unemployed with state

benefits only.

Household income data

As spatially disaggregated household income data were not available for the 2006 analysis, the

study included socio-economic group (SEG) in the transferable WTP function as the principle

variable for controlling for the household budget constraint. Subsequently, model based estimates

of household income have been provided by the ONS at the MSOA level and can be applied in the

current study and updated analysis8. The availability of this data means that alternative

specifications can be estimated for the transferable WTP function, explicitly controlling for

household income (see Section 3).

Growth in household income (2006 – 2014 and 2014 – 2134)

As income constrains WTP, the value of environmental improvements may increase in real terms as

household income rises. Forecast growth in household income is provided by the Department for

Transport (DfT) in terms of growth in average GDP per household (DfT, 2014). This provides the

basis for updating stated household income by 2006 survey respondents to 2014 levels, and then

accounting for household income growth over the time horizon for the analysis.

The effect of household income growth on WTP is estimated through the income elasticity of

willingness to pay. This measures the responsiveness of WTP to changes in household income. The

elasticity estimate is derived from the econometric analysis reported in Section 3.2. This estimates

the income elasticity of WTP as 0.407; i.e. a 1% increase in household income leads to

approximately a 0.4% increase in WTP, all else being equal. The elasticity estimate is consistent

with results reported from other studies, including Jacobsen and Hanley (2009) who conducted a

meta-analysis of 46 contingent valuation studies and found an average income elasticity of WTP for

environmental conservation measures of 0.38.

8 Data are available for 2007/08 (latest year available), based on the ONS Family Resources survey See: http://data.gov.uk/dataset/household_earnings_estimates_-_model-based_estimates_of_income_for_msoas [Accessed September 2014].

http://data.gov.uk/dataset/household_earnings_estimates_-_model-based_estimates_of_income_for_msoas



Figure 2.2 presents the household income growth index from the DfT data and the calculated

income growth weighting factor, based on the estimated income elasticity of WTP, for the time

period 2014 - 21009. The growth factor is calculated as weight that is applied to estimated annual

aggregate benefits in a given year t:

𝐵𝑡 = ∑ (𝑊𝑇𝑃𝑗 × 𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛𝑗𝑛𝑗=1 ) × 𝑊𝑡 [3]

Where the weighting factor for household income growth Wt is calculated as:

𝑊𝑡 = (𝐺𝐷𝑃 𝑖𝑛𝑑𝑒𝑥 𝑣𝑎𝑙𝑢𝑒𝑡

𝐺𝐷𝑃𝑖𝑛𝑑𝑒𝑥 𝑣𝑎𝑙𝑢𝑒 𝑡0)

𝑒𝑊𝑇𝑃

[4]

GDP index valuet refers to the average GDP per household index in a given year in the appraisal

time horizon and t0 is the index (re-)based to 2014. The income elasticity of WTP is denoted by

еWTP. Annex 3 presents the calculated income growth weighting factor for each year from 2014 –

2134.

Figure 2.2: Household income growth index and calculated income growth weighting factor (2014 – 2100)

Source: income index value calculated from DfT (2014) average GDP per household for 2014 – 2100 (86 years). Note that DfT

forecasts are provided up to 2100. For years 87 to 120 of the time horizon no further growth in household income is

assumed.

Over the timespan shown in Figure 2.2 (2014 – 2100) household income is forecast to increase by a

factor of 12, whilst the calculated weighting factor applied to aggregate benefit estimates

increases by a factor of 2. In practice, this captures the expected diminishing marginal effect of

increased income on the value of environmental improvements over the appraisal time horizon.

9 Note that the GDP per household index is calculated by DfT (2014) using forecasts produced by HM Treasury

and the ONS.

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

2014 2024 2034 2044 2054 2064 2074 2084 2094

Index v

alu

e

Income index value Income adjustment factor



2.5.4 Nominal prices and price indices

Household WTP values elicited in the original study were stated in 2006 nominal price terms. To

account for the change in general price level these are inflated to 2014 prices using the Consumer

Price Index (CPI). Annex 3 presents the index values for reference.

The CPI is applied as this represents the Thames Tideway improvements as a consumer good which

is valued relative to the nation’s ‘shopping basket’. That is, it indicates the amount of money

needed in period y to purchase the same basket of goods and services in a different period x. In

contrast, an alternative such as the GDP deflator includes only domestic goods and omits those

imported goods which are included in the CPI10.

2.6 Affected population

The final component of the analysis is the affected population. As described in Section 2.2, the

spatially sensitive aggregation of unit WTP for the Thames Tideway improvements accounts for two

perspectives for the boundary of benefits: (i) the administrative jurisdiction; and (ii) the benefits

jurisdiction. Table 2.4 reports population estimates for 2006 (used in the aggregation of benefits –

see Section 4) along with estimates for 2014, and projections for 2024 when the tunnel is expected

to be fully operational and the Thames Tideway improvements are assumed to be first realised11.

Table 2.4: Population estimates (million households)

2006 2014 2024

Administrative jurisdiction

Thames Water customer base 5.0 a 5.6 b 6.2 b

Benefits jurisdiction

National population (England) 20.5 a 22.7 c 25.4 d

Notes: a Household population estimates applied in eftec (2006) based on 2001 Census data; b Population estimates provided

by Thames Water; C Population estimate from ONS (2012); d Forecast number of households from DfT (2014).

As with household income growth over time, an aim of this study is to assess the impact of

population growth on aggregate benefits. Forecast population for England (number of households) is

provided by DfT (2014) for 2014 – 2100, based on ONS population data and projections. Forecasts

for the increase in the Thames Water sewerage customer base (no. households) has been provided

by Thames Water for the period 2014 – 2040.

Projections for the administrative and beneficiary jurisdiction populations are presented in Figure

2.3. Annex 3 presents annual population numbers for each year of the time horizon for the analysis.

10 In this instance the selection of the price inflator is not a key sensitivity as the resulting difference in WTP

values obtained by using either is relatively minor. The comparative index values for 2014 are 125 (CPI) and 118 (GDP deflator) (re-based to 2006 = 100). Hence £1 in 2006 price terms would be inflated to 2014 nominal prices as £1.25 based on the CPI or £1.18 based on the GDP deflator. 11 Construction of the Thames Tideway Tunnel is scheduled to be completed in mid-2023, followed by pre-

operational testing (Thames Water, 2014).



Figure 2.3: Projected population – national and Thames Water region (households)

Notes: Projected household numbers based on DfT (2014) for population growth for 2014 – 2100 (86 years). Note that DfT

forecasts are provided up to 2100. For years 87 to 120 of the time horizon no further growth in population is assumed.

As with the treatment of household income growth, population growth is incorporated into the

estimation of annual aggregate benefits in a given year t as a weighting factor:

𝐵𝑡 = ∑ (𝑊𝑇𝑃𝑗 × 𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛𝑗𝑛𝑗=1 ) × 𝑉𝑡 [5]

Where the population weighting factor Vt is calculated as:

𝑉𝑡 =𝑃𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 𝑖𝑛𝑑𝑒𝑥 𝑣𝑎𝑙𝑢𝑒𝑡

𝑃𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 𝑣𝑎𝑙𝑢𝑒 𝑡0 [6]

Population index value refers to a calculated index for the administrative and beneficiary poplation

based to 2014 (t0) and t is the index value for a given year within the appraisal time horizon. Annex

3 presents the calculated population weighting factor for each year from 2014 – 2134.

As population growth is treated as a weighting factor for annual aggregate benefits (equation 5), no

explicit control is made for the geographical distribution of new households. Hence it is implicitly

assumed that the population distribution over the time horizon of the analysis remains consistent

with the present day12.

12

In reality population growth will vary spatially; hence the assumption of a uniform distribution over MSOAs is

a caveat that should be recognised when interpreting results. For example, if population growth is greater in the South East compared to other regions, then given the expected distance decay relationship, the analysis will tend to under-estimate future benefits. Accounting for the expected spatial distribution of population growth requires forecast of population growth at the MSOA level (or sub-region/region) in order to determine the population change in each year of the time horizon for each MSOA. This would require factoring in changing population in approximately 7,000 MSOAs over 120 years (approx. 840,000 cases). Available data indicates that the differential growth rate between London and the South East and the national population is 0.01 per year for the period 2024 – 2037 (ONS, 2012b). This equates to around 60,000 households being unaccounted for within the administrative jurisdiction over the 120 year time horizon. The likely impact on results of not undertaking a more detailed treatment of population growth is not expected to significantly affect aggregate results.

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

2014 2024 2034 2044 2054 2064 2074 2084 2094

National (England) Thames Water



3. ANALYSIS

3.1 Econometric estimation

3.1.1 Overview

The econometric analysis undertaken for the 2006 study examined the relationship between

household WTP for the Thames Tideway improvements in relation to distance from the Tideway and

other respondent-specific variables, including respondent age, gender, socio-economic group (SEG),

level of education, membership of environmental groups, and awareness of CSOs. This provided the

basis for assessing the construct validity of the study results and the specification of a transferable

WTP function for estimating household WTP for the ecology, human health, and amenity

improvements.

The analysis reported here focuses on the specification of the transferable WTP function, in order

to update the aggregate benefit estimates of the Thames Tideway Tunnel. Household WTP is

estimated for the ‘large tunnel option’ (7.2 m diameter), which is consistent with the proposal set

out in the Development for Consent Order for the Thames Tideway Tunnel (Thames Water, 2014).

In line with the expectations highlighted in Section 2.3, the analysis is confined to the general

economic relationships that are expected to influence household WTP for environmental

improvements. The key variables are distance from respondent’s home to the Thames Tideway and

household income. Whilst the scope of the improvement and availability of substitutes are also

identified as critical factors that influence household WTP, the assessment set out in Section 2.5.2

(substitutes) and Section 2.4 and Annex 2 (scope of improvement), suggest that these factors have

changed not significantly from the 2006 study, hence do not need to be explicitly controlled for.

3.1.2 Model specifications

The formal representation of WTP, which is taken to vary spatially across different geographical

areas due to differences in household characteristics such as income and distance to the Thames

Tideway, is provided by the basic linear model of the form:

𝑊𝑇𝑃𝑖 = 𝑥𝑖𝛽 + 𝜀𝑖 [7]

where 𝑖 indexes respondent households, 𝑥𝑖 is a vector of household characteristics (e.g. distance,

household income), 𝛽 is a vector of parameters estimated from the data, and 𝜀𝑖 is an error term.

Individual parameters 𝛽𝑘 measure the partial effect of 𝑥𝑘 on WTP; i.e. the change in WTP when

increasing a given variable by one unit while holding all other variables fixed.

In the 2006 study, respondents did not directly report 𝑊𝑇𝑃𝑖 but rather a payment card elicitation

format was used (see Annex 2), where they indicated: (i) the minimum amount they were certain

they would be willing to pay each year to secure the Thames Tideway improvements

(denoted 𝑤𝑡𝑝𝑖𝑙); and (b) the maximum amount they were certain they would not be willing to pay

(𝑤𝑡𝑝𝑖𝑢) for the improvements. This implies that:

𝑤𝑡𝑝𝑖𝑙 ≤ 𝑊𝑇𝑃𝑖 ≤ 𝑤𝑡𝑝𝑖

𝑢 [8]

Therefore ‘actual’ willingness to pay lies between the two amounts indicated on the payment card;

that is, a given respondent is willing to pay at least as much as 𝑤𝑡𝑝𝑖𝑙 but not as much as 𝑤𝑡𝑝𝑖

𝑢. In

the 2006 study, a conservative approach was adopted in estimating the value of the Thames

Tideway improvements, by using 𝑤𝑡𝑝𝑖𝑙 as a measure of respondents’ willingness to pay. In addition,



the specification test undertaken for the 2006 study13 indicates that 𝑤𝑡𝑝𝑖𝑙 is log-normally distributed

in the population. This shows a ‘positively skewed’ distribution for individual WTP, with a higher

number of respondents answering lower WTP values. Therefore the model estimated in the 2006

analysis is14:

𝑙𝑛(𝑤𝑡𝑝𝑖𝑙) = 𝑥𝑖𝛽 + 𝜀𝑖 [9]

where 𝜀𝑖 (the error term) is assumed to be normally distributed with mean 0 and standard deviation

𝜎. This model is estimated via ordinary least squares (OLS) and is a common specification for the

analysis of WTP data – since WTP is defined to be non-negative and its distribution is often

positively skewed (as above).

It is also appropriate to specify a model that accounts for the fact that a respondents’ actual WTP

may lie between 𝑤𝑡𝑝𝑖𝑙 and 𝑤𝑡𝑝𝑖

𝑢. Hence as an alternative to the OLS model [9], an interval data

model is also estimated. This model uses information on both the lower and upper bounds of WTP

responses and provides a richer interpretation of the data derived from the survey15. Since the

interval data model considers both 𝑤𝑡𝑝𝑖𝑙, 𝑤𝑡𝑝𝑖

𝑢, with the true 𝑊𝑇𝑃𝑖 falling somewhere in between,

results from the interval data model will imply higher unit WTP than the OLS model, the latter

being by definition a more conservative specification.

As shown by Cameron and Huppert (1989) the probability of selecting level 𝑤𝑡𝑝𝑖𝑙 on the payment

card conditional on 𝑥𝑖 can be written as:

𝑃𝑟𝑜𝑏 (𝑤𝑡𝑝𝑖𝑙) = 𝜙[(𝑙𝑛(𝑤𝑡𝑝𝑖

𝑢) − 𝑥𝑖𝛽 )/𝜎] − 𝜙[(𝑙𝑛(𝑤𝑡𝑝𝑖𝑙) − 𝑥𝑖𝛽 )/𝜎] [10]

where 𝜙 is the cumulative density function of a standard normal distribution. In this model,

parameters 𝛽 and 𝜎 can be estimated via maximum likelihood. As with the OLS model, the 𝛽

parameters measure the partial effects of variables included in vector 𝑥𝑖, hence the interpretation

of the estimates is the same in OLS and interval data models (see Wooldridge, 2010).

3.1.3 Explanatory variables

In the 2006 study results, the vector 𝑥𝑖 for the transferable WTP function includes a constant term,

a variable for the distance of the respondent to the Thames Tideway (in km) and a set of indicator

variables for socio-economic group (SEG). Statistical tests undertaken for the 2006 study indicate

that the relationship between distance and ln(WTPi) is linear. This assumption is retained in the

analysis reported here. However the model specification set out in Section 3.2 uses the natural

logarithm of income (in £k per year) instead of SEG, since the availability of household income data

at the MSOA level means that it is now possible to control for this at a spatially disaggregated level.

Using the natural logarithm of income is supported by the estimation results, as it is found to

provide an improved fit to the data compared to a specification with linear or quadratic income

terms16.

13

See Appendix 6 ‘Statistical Analysis’ (eftec, 2006). 14 Note that 𝑤𝑡𝑝𝑖

𝑙 is increased by one to avoid the log function being undefined for respondents who stated

zero WTP. 15

In the analysis reported here, the interval data model is estimated on the basis of: (i) the highest amount

the respondent stated they were certain they would pay (the last tick on the payment card); and (ii) the first amount the respondent was certain they would not pay (the first cross). A more conservative estimate can be obtained from the interval model based on (i) the highest amount the respondent stated they were certain they would pay (the last tick on the payment card); and (ii) the next amount on the payment card. Results for this alternative model are reported in Annex 6. 16 In the 2006 study respondent SEG was used to capture variations in income because spatially disaggregated

income data was not available for the aggregation procedure. The updated analysis incorporates income data



Annex 4 presents results for alternative model specifications for income as well as additional

individual characteristics (gender, age, and education). Whilst these models with more control

parameters have been estimated, the transferable function that is applied to estimate the benefits

of the Thames Tideway improvements is constrained to include only household income and distance

as the explanatory variables. Following from Sections 2.3 to 2.5 these are the key factors that are

expected to influence WTP, and this relationship can be expected to be consistent over time. In

contrast the relationship between other individual characteristics (e.g. gender and age) is typically

ad-hoc in nature (eftec 2010a; 2010b), with no firm expectations for the influence on a specific

environmental improvement (e.g. the Thames Tideway improvements) or their temporal

consistency.

3.2 Transferable WTP function

3.2.1 Estimation results

Model estimates for the transferable WTP function are reported in Table 3.1. This reports results

for both the OLS model (equation 9 above) and the interval data model (equation 10 above). The

overall fit to the data for both models is reasonable and both are found to explain the observed

variation based on the respective F-test and Wald test statistics. Results for the models reported in

the Annex 4 demonstrate that most of the variation in WTP is captured by the distance and income

variables, since other covariates tested do not contribute substantially to improve the fit of the

model. Note that it is not possible to directly compare the explanatory power of the two models via

the reported R2 statistics as these are calculated differently given the alternative specifications and

estimation methods (in particular the dependent variable of both models is different).

Table 3.1: Transferable WTP function

OLS model Interval data model

Coefficient Std. err p-value Coefficient Std. err p-value

Constant 1.498 0.233 0.000 1.985 0.228 0.000

Distance (km) -0.003 0.001 0.001 -0.003 0.001 0.000

Ln(income)(£k) 0.407 0.066 0.000 0.357 0.064 0.000

Summary statistics

Model fit

Adj. R2 0.102 Pseudo R2 0.049

F-stat 32.94 Wald-Chi2 58.38

p-value 0.000 p-value 0.000

σ2 1.474 σ2 1.296

Observations1 n 603 N 603

Notes: 1 Consistent with the 2006 analysis, protest responses are not included in the estimation.

Results from both models accord with prior expectations and the findings from the 2006 study, and

all individual parameter estimates are highly statistically significant at the 1% level as indicated by

the reported p-values. In particular household WTP declines with distance from the Thames

Tideway, holding income constant, and increases with household income, holding distance

constant. Note also that the coefficient estimate for Ln(income) provides the estimate of the

income elasticity of WTP detailed in Section 2.5.3, which is consistent with results reported by

previous studies (see for example Jacobsen and Hanley, 2009).

at the MSOA level and sensitivity analysis has been undertaken to test alternative assumptions for the income variable (e.g. linear, quadratic, or logarithmic term) as well as the use of SEGs classifications. These specifications are reported in Annex 4.



The finding that the coefficients are significant and have signs that are in accordance with

expectations confirms the robustness of the estimates. In addition there is considerable consistency

between the coefficient estimates for the two alternative model specifications. The more

conservative approach to estimating WTP via the OLS model is evident in comparison of the

respective constant term coefficient estimates, which is lower (1.498) than for the interval data

model (1.985).

3.2.2 Application of transferable WTP function

The practical application of the transferable WTP function to estimate spatially sensitive WTP

values is demonstrated in Table 3.2. This applies the model coefficient estimates reported in Table

3.1 to the household parameter values for two selected MSOAs: (i) Greenwich 027 which is

approximately 4km from the Thames Tideway; and (ii) Darlington 001 which is approximately

353km from the Thames Tideway. Note that the level of household income is roughly equivalent

between the two areas, with Greenwich 027 (approx. £40.7k per year; 2006 prices) slightly higher

than Darlington 001 (approx. £37.3k per year; 2006 prices), so the main driver of the difference in

estimate WTP per household is distance from the Thames Tideway.

Table 3.2: Predicted WTP (£/hh/yr)1 for two MSOAs derived from the transferable WTP function (2006, £)

OLS model Interval data model

Coefficient

(β)

Greenwich

027

Darlington

001

Coefficient

(β)

Greenwich

027

Darlington

001

Constant 1.498 - - 1.985 - -

Distance2 -0.003 4.32 353.1 -0.003 4.32 353.1

Ln(income)3 0.407 3.71 3.62 0.357 3.71 3.62

Pred. WTP4 - £19.00 £6.95 - £25.98 £9.19

Notes: 1 Predicted WTP = exp[constant + β × Distance + β × Ln(income)] + 1; 2 Distance in km from Thames Tideway; 3

Natural log of household income in £k; 4 Predicted household WTP (£/hh/yr) in 2006 price terms.

The illustrative results presented in Table 3.2 show the distance decay effect for WTP for the

Thames Tideway improvements, with the predicted unit value for Greenwich 027 almost three

times greater than the predicted unit value for Darlington 001. Note that the constant term

represents an extrapolation of household WTP when the other explanatory variables are equal to

zero. The results show the expected difference between the OLS model predicted values and the

interval data model values, with the latter providing higher unit estimates for household WTP.

The overall application of the transferable WTP function is presented in Figure 3.1 and 3.2, which

maps estimated unit WTP for each MSOA in England (the benefits jurisdiction) and the Thames

Water region (the administrative jurisdiction), respectively. This shows the overall distance decay

in values across the benefits jurisdiction, with WTP ranging from a maximum value of

approximately £26.50 per household per year to a minimum value of approximately £3.80 per

household per year. Note that the decline in values is not uniform with increased distance from the

Thames Tideway improvements, since the transferable function also controls for the effect of

household income on WTP.



Figure 3.1: Predicted unit WTP by MSOA (£/yr) – benefits jurisdiction (£, 2006)

Note: Predicted WTP (£/hh/yr) based on OLS model specification (Table 3.2).



Figure 3.2: Predicted unit WTP by MSOA (£/yr) – administrative jurisdiction (£, 2006)

Note: Thames Water boundary mapped in accordance with MSOAs within Thames Water sewerage services area.

Predicted WTP (£/hh/yr) based on OLS model specification (Table 3.2).



Note that estimates of WTP from the transferable function may be interpreted as conservative

values. This is because the function has a log normal (ln) distribution for WTP and predicted values

at the MSOA level are equivalent to median WTP (Cameron and Huppert, 1989). The predicted

values mapped in Figures 3.1 and 3.2 therefore represent the amount that 50% of households in the

MSOA would ‘accept’ in a referendum. The use of unit values equivalent to the median is

conservative because of the skewed distribution for WTP, where mean (average) WTP is observed

to be greater than median WTP.

Conversion of estimated values to mean WTP at the MSOA level requires that the predicted value

from the transferable function is scaled by a constant term equal to exp(σ2/2), where σ2 is a

measure of the variance of the error term in the model estimation (see Table 3.1). However the

constrained set of explanatory variables included in the transferable function (distance and income

only) represent a limitation in the analysis. In particular, the error variance (σ2) of the transferable

function is higher than what would be observed with a ‘best fit’ model (which would include

relevant ad-hoc and contextual variables to provide an improved explanation of the data). A higher

error variance is therefore a consequence of estimating a transferable function, which if applied in

the aggregation procedure can significantly inflate benefit estimates. This effect, however, is an

artefact of the estimation procedure, rather than a reflection of individuals’ preferences. A

cautious response is therefore not to use the estimate of σ2 to scale-up predicted WTP values17.

17 This is the strategy employed in estimating aggregate benefits in Section 4 and predicted values at the MSOA

level are not scaled. The error variance (σ2) for the OLS specification of the transferable WTP function is 1.474 (Table 3.1). This implies a scaling factor of 2.1 based on the term exp(σ2/2). Hence predicted WTP from the function should be approximately doubled, but as noted in the main text the scaling reflects in part the effect of constraining the explanatory power of the model, and therefore there is an upward bias in results if the scaling factor is applied.



4. RESULTS

4.1 Aggregate benefit estimates

4.1.1 Calculation of aggregate benefits

Aggregate benefits estimates are reported for both the administrative jurisdiction (Thames Water

sewerage customer base) and benefits jurisdiction (national population). Benefits are calculated in

present value terms, based on projected annual aggregate values (£/year) over the 120 year time

horizon for the analysis. All values are reported in 2014 price terms. Future values are discounted

in accordance with HM Treasury (2003) Green Book guidance, applying a 3.5% discount rate for

years 0 - 30, a 3.0% rate for years 31 - 75, and a 2.5% rate for years 76 – 120.

Annual values are calculated through the transferable WTP function reported in Section 3.2, using

the more conservative OLS model specification. For reference, the (undiscounted) annual values

are mapped in Annex 5 for the benefits and administrative jurisdictions. This shows the spatial

variation in aggregate benefits as determined by increased distance from the Thames Tideway,

differences in household income, and population (no. of households) at the MSOA level. Note also

that the values mapped in Annex 5 are not adjusted for any of the aggregation assumption

scenarios presented subsequently.

4.1.2 Aggregation scenarios

To address the research aims set out in Section 1.2 four scenarios are applied to project annual

aggregate values. The purpose of this is to establish the sensitivity of results to different

assumptions concerning household income growth and population growth over the 120 year time

horizon:

Scenario A: this profile of annual benefits is based on 2014 population and income levels. It

does not include population growth or income growth over the 120 year time horizon. Hence it

provides the most conservative aggregation scenario for the administrative and benefits

jurisdictions.

Scenario B: this profile of annual benefits incorporates forecast population growth in line with

Figure 2.3. This scenario is consistent with the statutory requirements of water companies to

incorporate population projections into medium to long term planning. It does not factor in

income growth.

Scenario C: this profile of annual benefits incorporates the effect of forecast growth in

household income on WTP for the Thames Tideway improvements, scaling annual benefits by

the calculated weighting factor presented in Figure 2.2. This scenario does not factor in

population growth.

Scenario D: this profile of annual benefits incorporates both forecast population growth and

household income growth. Hence it represents the least conservative aggregation scenario for

the administrative and benefits jurisdictions.

In all four scenarios, annual benefits are profiled from 2024 when the Thames Tideway Tunnel

becomes fully operational (year 10 of the 120 year time horizon). Annual aggregate benefits are

assumed to be zero during the period 2014-23. Note that in Scenarios A, C, D, population growth

and income growth are projected up to 2100 based on the information available (year 87 of the 120



year time horizon). Beyond this no further growth in these parameters is assumed, which represents

a further conservative treatment of the aggregation process.

Annex 6 reports results from sensitivity analysis for the Scenario A – D aggregate benefit estimates:

(i) applying a 60 year time horizon consistent with the original CBA (Nera, 2006); and (ii) and

assessing an alternative assumption for the timing of benefits (assuming they commence in 2015).

4.2 Administrative jurisdiction

Table 4.1 presents aggregate benefit estimates for the Thames Water sewerage customer base and

the administrative jurisdiction. Across the four sensitivity scenarios the present value (PV) of

benefits over 120 years ranges from approximately £2.8 billion to £4.7 billion. In annual equivalent

value terms, this represents a series of equal cash flows over 120 years of £91 million per year to

£154 million per year18.

Table 4.1: Aggregate benefit estimates – administrative jurisdiction (2014, £)

Scenario Benefit, PV 120, £bn Annual equivalent value, £m

Scenario A 2.8 91

Scenario B 3.4 112

Scenario C 3.8 123

Scenario D 4.7 154

Notes: Present values calculated based on: 3.5% discount rate for years 0 – 30; 3.0% rate for years 31 – 75; and 2.5% rate for

years 76 – 120 (HM Treasury, 2003).

The profile of discounted annual aggregate benefits is presented in Figure 4.1. This shows the

effect of the alternative assumptions on household income growth and population growth on the

aggregate benefit estimates.

Figure 4.1: Profile of discounted annual benefits – administrative jurisdiction (2014, £m)

18 The annual equivalent value incorporating changing discount rates, is calculated using the formula:

Annual equivalent value = 𝑃𝑉 𝑜𝑓 𝑏𝑒𝑛𝑒𝑓𝑖𝑡𝑠

𝛼𝑡,𝑟 where 𝛼𝑡,𝑟 is the annuity rate 𝛼𝑡,𝑟 = ∑ ∏ (

1

1+𝑟𝑖)

𝑗𝑖=0

𝑡−1𝑗=0

0

20

40

60

80

100

120

2014 2024 2034 2044 2054 2064 2074 2084 2094 2104 2114 2124 2134

Scenario A Scenario B Scenario C Scenario D



Note that the discontinuity in the profile of discounted annual benefits for Scenarios A, C and D

from year 2100 is the result of assuming there no further growth in the household population and

household income parameters after this point.

4.3 Benefits jurisdiction

Table 4.2 presents aggregate benefit estimates for the benefits jurisdiction (national population -

England). Across the four scenarios present value of benefits over 120 years ranges from

approximately £7.4 billion to £12.7 billion. In annual equivalent value terms, this represents a

series of equal cash flows over 120 years of £242 million per year to £413 million per year.

Table 4.2: Aggregate benefit estimates – benefits jurisdiction (2014, £)

Scenario Benefit, PV 120, £bn Annual equivalent value, £m

Scenario A 7.4 242

Scenario B 9.2 299

Scenario C 10.1 330

Scenario D 12.7 413



The profile of discounted annual aggregate benefits is presented in Figure 4.2. This shows the

effect of the alternative assumptions on household income growth and population growth on the

aggregate benefit estimates.

Figure 4.2: Profile of discounted annual benefits – benefits jurisdiction (2014, £m)

0

50

100

150

200

250

300

2014 2024 2034 2044 2054 2064 2074 2084 2094 2104 2114 2124 2134

Scenario A Scenario B Scenario C Scenario D



5. CONCLUSIONS

5.1 Summary

The purpose of this study is to update the estimate of the monetary benefits of the environmental

and human health improvements in the Thames Tideway due to a reduction in the frequency of

CSOs. The analysis reviews the 2006 study data and identifies appropriate adjustments to benefits

estimates based on the criteria set out in Defra’s value transfer guidelines (eftec, 2010a).

The validity of applying the 2006 study data in the 2014 to the Business Case to be prepared by

Defra is assessed in relation to the current academic literature on the temporal transfer of WTP

evidence. It is concluded that it is valid to apply the 2006 study data in this way, provided that

changes in the factors found the influence the 2006 results are identified and controlled for. These

factors are: (i) the scope of environmental improvement; (ii) the availability and quality of

substitutes; and (iii) household income and distance from the Thames Tideway improvements. The

examination of these factors has found that the scope of the improvement and availability of

substitutes have remained largely the same since 2006. Any observed differences are relatively

minor and it is reasonable to assume that these would not substantially alter WTP responses.

Household income levels and the distance to the Thames Tideway are explicitly controlled for by

the application of the transferable WTP function.

The aggregation of the benefits of the Thames Tideway improvements over time and space

accounts for four different scenarios for how population and household incomes may change over

the next 120 years. Spatial analysis also differentiates between the administrative jurisdiction

(Thames Water sewage customers) and benefits jurisdiction (England) and incorporates the distance

decay in WTP as distance from the Thames Tideway increases.

Based on the administrative jurisdiction, overall benefits are estimated to be in the region of £2.8 –

£4.7 billion in present value terms (across Scenarios A-D) over 120 years. Factoring in the national

population, aggregate benefits are estimated to be in the region of £7.4 - £12.7 billion in present

value terms, over 120 years. Consideration of the scope of the benefits jurisdiction for the Thames

Tideway improvements – which is approximately four times the administrative jursidiction

population – almost triples the overall benefits estimates.

5.2 Key findings

5.2.1 Household WTP (unit value estimates)

Predominantly conservative assumptions have been applied in the analysis to update the estimates

of household WTP for the Thames Tideway benefits. This includes:

Using the OLS model specification for the transferable WTP function, which provides a

conservative lower bound estimate for predicted WTP in comparison to the alternative interval

data model specification. The sensitivity analysis reported in Annex 6 shows that updates to the

OLS function from the 2006 study – including re-weighting the sample data according to Table

2.3 - have a minimal impact on estimated values.

At the MSOA level, predicted WTP is equivalent to median WTP for the Thames Tideway Tunnel

improvements. Median WTP is observed to be lower than mean (average) WTP and predicted

values are not scaled with the error variance of the OLS model estimation. The main reason for



this is that the error variance is artificially higher because of the limited number of explanatory

variable included in the transferable WTP function. This can result in an upward bias in the

predicted unit WTP values. Therefore consistent with a conservative approach to updating

household WTP estimates, predicted WTP values are not scaled and are equivalent to median

WTP and the amount that would be acceptable by 50% households in an MSOA.

The effect of adopting a conservative strategy to estimating household WTP is as follows. Applying

an interval data model would give predicted WTP values in the region of 10 - 30% higher than the

OLS estimates, depending on the function selected (see Annex 6). Scaling WTP from the

transferable function would give predicted values around 100% higher for the OLS specification. A

similar uplift would apply to the interval data model estimates. In both cases, however, the uplift

is subject to an upward bias in the scaling factor that stems from the constrained set of variables

included in the transferable function.

5.2.2 Aggregate benefits

Aggregate results as reported in Section 4 and Annex 6 are particularly sensitive to the assumptions

applied in the aggregation procedure to calculate present value benefits. This includes assumptions

in regards to: (i) the boundaries of the beneficiary population (i.e. administrative vs, benefits

jurisdiction; (ii) population growth; (iii) household income growth; (iv) the time horizon for benefits

(illustrated as 60 years vs. 120 years); and (v) the commencement of benefits (2015 vs. 2024). As a

consequence a range of scenarios and sensitivities are presented in this report, demonstrating the

set of aggregate benefit estimates that result from these various assumptions. This includes results

for the sensitivity tests set out in Annex 6 that examine the time profile for benefits.

The greatest present value benefit estimate is obtained by assuming a profile of annual values that

commence in 2015 and incorporate population and household income growth over a 120 year time

horizon. This gives a total benefit estimate of £15.4 billion in present value terms (over 120 years)

for the benefits jurisdiction (national population) (see Annex 6). The most conservative aggregate

estimate for the benefits jurisdiction is provided by assuming no population growth or household

income growth with benefits profiled from 2024 over a 60 year time horizon. This gives a total

benefit estimate of £5.9 billion in present value terms (over 60 years). Similar sensitivity is evident

for the administrative jurisdiction boundary (the Thames Water customer base only), with the

equivalent present value benefit estimates ranging from £2.2 billion (over 60 years) to £5.8 billion

(over 120 years).

Subsequent use and reporting of the aggregate benefit estimates presented in this report should

explicitly state the associated aggregation assumptions. It will also be relevant to note the

conservative strategy adopted in estimating household WTP as an input to the aggregate benefit

estimates.



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ANNEX 1: LITERATURE REVIEW

A1.1 Introduction

The study ‘Thames Tideway - Stated Preference Survey’ (eftec, 2006) estimated the benefits of the

Thames Tideway Tunnel (TTT), in terms of the ecology, human health, and amenity improvements.

Results from the study were applied in a cost-benefit analysis (CBA) of alternative options for

reducing the incidence of combined sewer overflows (CSOs) in the Thames Tideway (Nera, 2006).

The objective of this project is to update the 2006 benefits estimate to inform the Business Case

for the Government Support Package for the TTT.

This annex reviews the economic literature concerning the validity and reliability of the ‘temporal

transfer’ of economic valuation evidence. In this case, temporal transfer involves updating the 2006

survey data to estimate the aggregate benefit estimate for the Thames Tideway improvements in

2014. The review therefore focuses on studies that test the temporal stability of individuals’

preferences for environmental improvements.

A1.2 Conceptual overview

Stated preference methods can be applied to value changes in the provision of non-market goods,

such as the quality of the water environment. They entail asking choice or direct valuation

questions to respondents via survey interviews. The questionnaire – which is often called the

‘survey instrument’ - presents a hypothetical market to the respondent in which they can purchase

changes in provision of the non-market good(s) of interest. It compiles various data on respondent

characteristics such as demographic and socio-economic factors, as well as attitudes and

perceptions. The contingent valuation method is a commonly applied technique where the change

in provision of the non-market good is described in terms of a discrete change, such as the impact

of an investment to improve water quality (i.e. the difference between the ‘with’ and the

‘without’ case).

The application of stated preference studies is underpinned by conventional economic theory and

the standard model of consumer choice. The cornerstone of the consumer choice model is one

simple assumption: individuals know their own preferences and, whatever choice is encountered,

they know what is best for them19. Economic valuation methods – which include stated preference

methods – represent individuals’ preferences in monetary terms, based on what they are prepared

to give up in order to secure a particular good or provision of a benefit such as the Thames Tideway

improvements. It is assumed that the trade-offs that an individual makes between their household

income (their budget constraint) and the provision of a good (i.e. the ‘willingness to pay’ (WTP)

measure of benefits) are indicative of their underlying preferences. It is these underlying

preferences that are employed when individuals make such choices (Bateman et al., 2002).

A distinction to make, therefore, is the notion of an individual’s ‘innate’ preferences for outcomes

such as improvements in environmental quality, and factors that influence choices such as income

and prices which constrain individuals’ preferences at a given point in time. In particular, the

consumer choice model is reliant on the assumption that individuals’ preferences are stable and

consistent between choices. Hence an individual facing the same choice at different points in time

19 In formal terms, an individual will opt for the choice option that yields the greatest level of ‘utility’ (i.e. the greatest degree of happiness, wellbeing, satisfaction). Preferences can therefore be described by a utility function that satisfies a number of assumptions about their consistency and the rationality of choices that are made.



is expected to express the same preference (all else equal). If a different preference is elicited at a

different point in time, this must be due to a change in the individual’s choice constraints (e.g.

household income, other expenditures/bills faced, unemployment, etc.) or due to external factors

(for example changes in the environmental quality). This implies that whilst preferences are

assumed to be stable, an individuals’ WTP for environmental quality improvements may be

observed to change over time due to changes in factors such as household income and the

availability and quality of substitutes.

An alternative perspective, however, is offered by the behavioural economics literature. This

challenges the assumption that stable preferences in the conventional economic theory sense

actually exist. Rather it is contended that preferences are ‘constructed’ and learnt by an individual

and consequently cannot be assumed to be invariant over time. Instead they are influenced by the

setting and framing of choice occasions (Hoeffler and Ariely, 1999; Simonson, 2007).

The issue therefore for the update of the Thames Tideway benefit estimate is whether it is valid to

assume that the preferences elicited for the ecology, human health, and amenity improvements in

the 2006 stated preference survey still hold in 2014. In other words, would the same survey

undertaken in 2014 give markedly different results, allowing for the expectation that individuals’

WTP may change due to changes in factors such as household income and substitute availability? To

this end the review of evidence focuses on studies that have assessed the temporal stability of

individuals’ preferences and WTP elicited via economic valuation methods.

A1.3 Review of evidence

The economic literature features three types of study that have examined preferences for

environmental improvements over time: (i) meta-analysis studies of multiple valuations from

multiple source studies; (ii) re-administration of the same stated preference survey to different

samples of the same population at different periods of time; and (iii) a formal ‘test-retest’

approach with the administration of the same stated preference survey to the same respondents at

different periods of time. In general the test-retest approach (iii) represents the most stringent

test of preference stability as it minimises the potential for differences in survey method and

respondent sampling to influence results. Re-administration of the same survey (ii) controls for

differences in survey method but can potentially be influenced by sampling factors. Meta-analysis

studies represent the weakest test as they typically combine studies with differing methodologies

as well as populations and hence make it difficult to separate methodological effects from changes

in preferences.

A1.3.1 Meta-analysis studies

While results from meta-analysis studies are often used as a source for value transfer applications,

the principal motivation for these studies in the economic valuation literature is to provide insight

into the potential influence of design, sampling, analysis, and methodological factors on the

estimation of non-market values.

Rolfe and Brouwer (2011) conducted a meta-analysis of sixteen separate choice modelling (choice

experiments only) studies, published between 2000 and 2010 with 130 individual WTP estimates

relating to river quality20. The study shows that, in general, the different features of the choice

20 Substantial variation was identified in the way that changes in the environmental good were described within the studies included in the meta-analysis. Where the good was defined in terms of river health, the key approaches were to identify changes in terms of absolute values (kilometres of waterways in good health) or



experiment studies in terms of design, sampling and analysis did not have significant impacts on

valuations. However, amenity outcomes were a highly significant indicator of values, with

attributes focused on recreation uses exhibiting significantly higher values, and attributes

concerned with wildlife significantly lower values. Rolfe and Brouwer posit that this may be

because values associated with recreation combined both use and non-use preferences, whilst

valuations for wildlife were only for non-use value. Trade-off framing and payment mechanisms

were also found to have a systematic effect on WTP and therefore specific survey design features

requiring more attention21.

An earlier study by Loomis and White (1996) compares WTP estimates, elicited using contingent

valuation, for preserving a number of different endangered species, many of which are aquatic

species. Over an 11-year period (1983 – 1994) they find no significant variation in valuations.

In general, the conclusions that can be drawn from meta-analysis studies such as these with respect

to the temporal stability of preferences are limited. In particular they tend to incorporate results

from different stated preference and revealed preference methods (e.g. Bateman and Jones 2003;

Nelson and Kennedy 2009; Johnston and Rosenberger 2010) and are dependent upon the ability to

specify parameters in meta-analysis functions that adequately control for the diverse range of

methodological influences, such that genuine variation in individuals’ preferences over time can be

identified.

A1.3.2 Re-administration of stated preference survey (same population, different sample)

Administration of the same stated preference survey within the same population at different

periods of time allows for analysis of whether individuals’ WTP, on average, changes over time; i.e.

whether there are changes in the demand for environmental quality that might lead to different

WTP values being elicited from the sample population. The typical test in these studies is the

comparison of the statistical equality of unadjusted average WTP values and WTP functions (i.e.

the equality of coefficient estimates and variances) (Brouwer and Bateman, 2005).

Bliem et al. (2012) test the stability of preferences for river restoration by employing two identical

choice experiments with a time difference of 1 year. The study shows that the underlying

preferences of individuals do not differ, in terms of the estimation of indirect utility functions. In

addition, differences in mean WTP estimates between both surveys were not found to be

statistically significant. This suggests that in the absence of any extreme events (e.g. flooding that

may have changed respondent views on flood control between surveys) individual preferences are

consistent over the time period tested in the survey. The findings are consistent with Brouwer

(2006) which tests whether preferences, elicited via contingent valuation, for improved bathing

water quality in the Netherlands are different before (a first survey administered in December

2002) and during an extreme weather event (a survey administered during the hot and dry summer

of 2003). Although it was expected that WTP would be higher after the event (but not that

underlying preferences changed) as the event made bathing water of good quality more scarce,

results were found to be statistically consistent over time. These results provide support for

updating aggregate benefit estimates elicited via the contingent valuation method used in eftec,

2006.

percentage values (percentage of waterways in good health). The same variation occurred across the indicator variants of river health description, where variables such as vegetation, fish and birds were described in both absolute and percentage terms across studies. For the meta-analysis, consistency and comparability was generated by transforming implicit prices from each study into a common standard of WTP per kilometre of river in good health (Rolfe and Brouwer, 2011). 21 Rolfe and Brouwer acknowledge that this result is contrary to expectations, suggesting that further work is necessary to understand how respondents view payment vehicles.



Metcalfe and Baker (2014) examine preferences for water and service improvements before and

after the 2008 economic downturn. This represents an interesting application that attempts to

examine how general economic conditions may influence respondent WTP. Results however are

inconclusive; post-economic downturn WTP payment card estimates are found to be lower, but

dichotomous choice WTP estimates were unaffected. Consistent with other studies, the

dichotomous choice WTP estimate is observed to be higher than the payment card estimates.

Metcalfe and Baker conclude that two alternative explanations for this result (i.e. strategic

behaviour or respondent uncertainty) are both potentially consistent with their findings, and hence

it is not possible concluded that WTP in this context was sensitive to changed economic conditions.

Dupont and Price (2014) consider a longer time period (8 years from 2004 to 2012) and compare the

results from two identical surveys that elicit WTP for health endpoints related to tap water quality

(microbial illness and cancer). The study also compares values elicited from choice experiment and

contingent valuation formats. The study finds that mean WTP estimates obtained from the

contingent valuation approach are statistically different: the estimates from 2012 are lower than

2004 results for reduced microbial risk and the joint microbial and cancer risk (WTP for decreased

cancer risk were not statistically different)22. In contrast, valuations derived from the choice

experiment approach are statistically equivalent.

Brouwer and Bateman (2005) also observe a change in WTP values (a decrease) for wetland

conservation between two identical contingent valuation surveys administered in 1991 and 1996.

However, the change in valuations is found to be associated with factors related to sampling and

ad-hoc characteristics of the population (e.g. a lower proportion of respondents who were members

of environmental groups; fewer direct users of the environmental good; and lower household

income), rather than a variation in underlying preferences. A key conclusion is that WTP models

that are expanded to include theoretically unanticipated determinants of WTP introduce ad-hoc

and potentially transitory factors into the comparisons of valuations. This can then lead to a

conclusion of non-transferability of WTP estimates and functions overtime. The implication of this

result is that temporal transfers of WTP should concentrate on controlling for the general economic

relationships that are expected to influence WTP for environmental quality improvements (e.g. the

scope of the improvement, the cost to the individual of enjoying the benefits provided, the

availability and quality of substitutes, and household income), rather than ad-hoc factors for which

no clear expectations are available.

A1.3.3 Test-retest of stated preference survey (same respondents)

Administering the same survey to the same respondents at different periods of time provides the

most direct approach to examining the consistency individual’s preferences over time. Again the

usual testing procedure is to compare the statistical equality of unadjusted average WTP values and

WTP functions.). A recent study by Brouwer and Logar (2014) compares the temporal stability of

preferences and WTP from a combined choice experiment and contingent valuation study for

improved river quality and reduced human health risk as a result of upgrading wastewater

treatment plants to remove micro-pollutants from water bodies. Each respondent was surveyed

twice six months apart. Valuations derived from both the choice experiment and contingent

valuation components of the survey were, on average, found to be numerically lower in the follow-

22 The study identifies that whether a respondent lives in Ontario is the most consistent predictor of WTP among demographic variables in the 2004 study, but this is not significant in 2012. This result may reflect a heightened awareness of drinking water quality in the early study following two high profile contamination incidents: an outbreak of E.coli in 2000 (resulting in multiple deaths and thousands of illnesses) and a similar, although less severe, outbreak of cryptosporidium in 2001. Hence Dupont and Price contend that temporal proximity to a high profile event may temporarily amplify WTP for water quality improvements, particularly via the contingent valuation format which in practice elicits a more direct WTP response than the choice experiment format.



up survey. However the differences in WTP estimates were not found to be statistically different

and the study concludes that valuations based on stated preference methods are stable, and hence

reliable, over the six-month time period. The finding is consistent with Cameron (1997) which

undertook a test-retest contingent valuation study with the same group of Australian residents for

three consecutive years. Over the time period (1993 – 1995) mean WTP for water quality

improvements for these respondents was not found to be statistically different.

A1.4 Summary

In summary, the empirical literature concerned with the temporal stability of individuals’

preferences for environmental quality improvements tends to find that WTP does not vary

significantly over short time periods. However, over longer time periods real WTP (i.e. accounting

for changes in the purchasing power of money) can change by statistically significant amounts, but

this is primarily related to factors that constrain WTP in the shorter term (e.g. household income).

The underlying economic factors that determine WTP are found to remain stable over short and

longer periods. Nevertheless, caution is required with respect to the influence of changes in ‘ad-

hoc’ determinants of WTP (i.e. variables with no strong expectations based on economic theory) as

it cannot be assumed that these are consistent over time.

Overall, the available evidence tends to support the temporal transfer of economic valuation data

in the short to medium term (e.g. around 10 years), in the sense that no results are observed that

unequivocally challenge the assumption of the stability of individuals’ preferences. However

temporal transfers should take into account adjustments to valuations to economic factors that are

expected to influence WTP (e.g. the availability of substitutes, household income). This is why this

study explicitly accounts for these economic factors (and the changes in environmental

improvements and population) when updating the 2006 WTP estimates.



ANNEX 2: SCOPE OF THAMES TIDEWAY IMPROVEMENTS

A2.1 Introduction

This annex reviews the scope of the improvement presented to respondents in the 2006 study and

compares this to the current information for the expected frequency of overflows to the Thames

Tideway. This comparison is critical to the assessment of how consistent the current information

for the impact of the Thames Tideway Tunnel, as set out in the Development for Consent Order, is

with the 2006 study. If there is a significant difference between the current information and the

2006 study – i.e. if the scope of the improvement is markedly different - it would not be

appropriate to use the 2006 survey data as the basis for updating the monetary estimate of the

benefits of the Thames Tideway Tunnel.

A2.2 Description of benefits in 2006 study

Table A2.1 summarises the scope of the improvement in the Thames Tideway presented to

respondents in the 2006 study. This was defined in terms of: (i) the frequency of overflows; (ii) the

impact on the health of fish and other wildlife; (iii) the impact on sewage litter; and (iv) the

impact on the risk of suffering illness though contact with river water. The benefits of the

improvements were represented as the difference between ‘without’ the Thames Tideway Tunnel

case and ‘with’ the Thames Tideway Tunnel case:

‘Without’ the Thames Tideway Tunnel: the ‘baseline’ and continuing situation in the Thames

Tideway accounting for upgrades to Mogden, Beckton, Crossness, Riverside and Long Reach

sewage treatment works, which at the time of the 2006 study were expected to be completed

by 2014.

‘With’ the Thames Tideway Tunnel: the impact of the Thames Tideway Tunnel as specified for

the 2006 study, which, at the time, was expected to be completed by 2021.

Note that Table A2.1 sets out the basic summary information shown to respondents as part of the

willingness to pay (WTP) elicitation question in the 2006 stated preference survey. Prior to being

asked their WTP for the Thames Tideway improvements, respondents were presented with broader

explanatory material detailing the background context and impacts on the Thames Tideway. The

development of the explanatory material was subject to an iterative design and test-(re)test

process, which is documented in the 2006 study report.



Table A2.1: Impact of Thames Tideway Tunnel – summary information presented to 2006 stated

preference study respondents

Without

Thames Tideway Tunnela

With

Thames Tideway Tunnelb

Frequency of overflows 60 times per year on average

Fewer in dry periods 3 times per year on average

Health of fish and other

wildlife

1 or 2 times per year when oxygen

levels in the water drop low

enough to either kill some fish or

prevent migration (e.g. salmon)

Less than 1 time per year when

oxygen levels in the water drop

low enough to either kill some fish

or prevent migration (e.g. salmon)

Sewage litter May be visible anywhere along the

tidal Thames, but especially

visible close to outfalls following

overflows

Amounts to 10% of all litter

Small amount visible 3 times per

year following overflows.

Risk of suffering illness

through contact with

river water

Higher risk following each

overflow

High risk at all other times

Higher risk only following the

remaining 3 overflows per year.

High risk at all other times.

Notes: a ‘Without’ situation includes upgrades to Mogden, Beckton, Crossness, Riverside and Long Reach sewage treatment

works; b ‘With’ situation is ‘large tunnel option A’ from 2006 study.

The background information and material presented to respondents included:

Introductory information explaining the historic improvements to the River Thames in the 1960s

and 1970s, the operation of CSOs as part of the sewage and rainwater collection system in

London, and the context for the Thames Tideway Tunnel proposal [Showcard C.1];

A qualitative description of the impacts associated with CSOs, covering: (i) the effect of

reduced oxygen levels on fish health and migration; (ii) sewage litter attributable to CSOs; and

(iii) human health risks, elevated risk levels following CSO events, types of illness, and at risk

populations [Showcard C.2];

A summary of the impact of the Thames Tideway Tunnel on fish populations, sewage litter, and

human health, in terms of the ‘with’ and ‘without’ situations as detailed in Table A2.1

[Showcard C.3 and C.4a];

A payment ladder card to elicit household willingness to pay for the Thames Tideway

Improvements [Showcard C.5]; and

A ‘cheap talk’ script23 reminding respondents of the scope of the Thames Tideway

improvements and substitutes, household budget constraints, and other investments in water

and sewerage services that may affect household bills [Showcard C.6].

The Appendix to this annex provides the relevant extracts from the stated preference questionnaire

material.

23

Cheap talk scripts are a conventional component of stated preference surveys. They are included to remind

respondents of various factors that they should take into consideration when stating their willingness to pay responses, including budget constraints and other investments that may impact household bills.



A2.3 Thames Tideway Improvements

The 2006 study represented the overall improvements in the Thames Tideway as delivered by: (a)

the upgrades to the sewage treatment works, increasing the capacity to treat sewage in the London

area, which was included in the ‘without’ the Thames Tideway Tunnel baseline; and (b) the Thames

Tideway Tunnel, intercepting and preventing overflows and storm discharges to the Thames

Tideway.

Subsequent to the 2006 study, the tunnel element of the Tideway improvements has been split

between the separate construction of the Lee Tunnel and the Thames Tideway Tunnel.

Construction work for the Lee Tunnel commenced in 2010 and the tunnel is due to be completed by

the end of 2015. This means the Lee Tunnel will be operational in advance of the Thames Tideway

Tunnel, and hence the improvements that will be delivered by it will form part of the baseline (the

‘without’ Thames Tideway Tunnel case) for the updated benefits estimate for the Thames Tideway

Tunnel. As a result, the improvements delivered by the Lee Tunnel need to be explicitly established

in order to determine whether the descriptions of the Thames Tideway Tunnel benefits in the 2006

study are still representative of the current ‘with’ Thames Tideway Tunnel case (i.e. excluding the

Lee Tunnel impacts).

A2.4 Impact of Lee Tunnel

Figure A2.1 shows the route of the Lee Tunnel and the Thames Tideway Tunnel. The Lee Tunnel

(approx. 6.9km in length) captures discharges to the River Lee (a tributary of the Thames Tideway)

from the CSO at the Abbey Mills pumping station (Stratford). Captured overflows are then conveyed

to the Beckton sewage treatment works. Abbey Mills represents the single largest CSO in volume

terms and consequently the combination of the Beckton STW upgrade and the Lee Tunnel addresses

approximately 40% of total discharge (by volume) from all CSOs that impact the Thames Tideway.

The Lee Tunnel does not, however, prevent discharges from the 34 other CSOs along the stretch of

the Tideway from Acton (West London) to Greenwich (East London) that will be intercepted by the

Thames Tideway Tunnel (approx. 25km in length). The principal CSOs along the Tideway are shown

on Figure A2.1, whilst the full set of CSOs is detailed in the accompanying Figure A2.2.

A2.4.1 Frequency of overflows

In the 2006 study, the expected frequency of overflows to the Thames Tideway without the Thames

Tideway Tunnel from a given CSO was stated to be around 60 times per year on average (and fewer

in dry periods). Current information reports that the expected frequency of overflows without the

Thames Tideway Tunnel is greater than 50 times per year on average. Hence the 2006 study and

current information are broadly consistent. The construction of the Lee Tunnel has little impact on

the expected frequency of overflows to the Tideway as it only addresses one specific CSO (Abbey

Mills).



Figure A2. 1: Lee Tunnel and Thames Tideway Tunnel



Figure A2.2: Thames Tideway combined sewer overflows (CSOs)

Notes: CSO categories as defined by the Environment Agency: Category 1 – CSOs that operate frequently and have an adverse environmental impact; Category 2 – CSOs that

do not operate frequently but which have an adverse environmental impact; Category 3 – CSOs which have no significant environmental impact; and Category 4 – CSOs that

operate frequently but have been assessed as having no adverse environmental impact.



A2.4.2 Health of fish and other wildlife

The impact of CSOs on the ecology of the tidal Thames is monitored in relation to the four dissolved

oxygen (DO) standards that were established through the Thames Tideway Strategic Study (TTSS)24

(Thames Water, 2005). The standards define the frequency based on the number of times one of

the four standards can be breached over a 41 year period (Table A2.2).

Table A2.2: Thames Tideway dissolved oxygen (DO) standards

Standard DO

concentration

threshold (mg/l)

Duration

(tidesa)

Allowable return

period

(1 in x years)

Allowable no. of

exceedances in

41 years

1 4 29 1:1 years 41

2 3 3 1:3 years 13

3 2 1 1:5 years 8

4 1.5 1 1:10 years 4

Notes: a A tide is a single ebb or flood.

The Thames Tideway DO standards span a range of concentrations that imply negative impacts on

the health of fish and other (aquatic) wildlife. Table A2.3 presents the current information for the

progression of DO compliance for the Thames Tideway based on the incremental improvements

delivered by the sewage treatment upgrades, the Lee Tunnel, and the Thames Tideway Tunnel.

Table A2.3: Simulated number of exceedances and scenario compliance against DO standards

for the Tidal Thames

DO Standard 1 2 3 4

DO value and tidal

duration threshold

4 mg/l for 29

tides1

3 mg/l for 3

tides

2 mg/l for 1

tide

1.5 mg/l for 1

tide

Allowable exceedances in

41 years (frequency) 41 (1:1 yr) 13 (1:3 yr) 8 (1:5 yr) 4 (1:10 yr)

Scenario Simulated maximum number of exceedances of DO thresholds

A. System as in 2006 211 193 99 60

Fails Fails Fails Fails

B. STW improvements 123 114 66 41


C. STW improvements and

Lee Tunnel

75 40 12 7


D. STW improvements, Lee

tunnel and Thames

Tideway Tunnel

21 4 1 1

Compliant Compliant Compliant Compliant

Source: Adapted from Table 8-5 System Design Report (Scenarios A, C and D). Scenario B information provided by Thames

Tideway Tunnels (October 2014).

24 The DO standards were developed by the TTSS to provide a basis for comparing alternative options for

meeting obligations under the Urban Wastewater Treatment Directive (UWWTD) to limit pollution and the effects if discharges from the sewage treatment works and collection systems included discharges from CSO.



The scenarios set out in Table A2.3 represent:

A. The ‘existing system’: conditions prior to any improvements in the Thames Tideway. The

expected number of exceedances of all four DO standards implies extremely poor conditions for

aquatic organisms.

B. Sewage treatment works (STW) improvements: this scenario is equivalent to the ‘without’

Thames Tideway Tunnel case (the baseline) presented to respondents in the 2006 study. In

Table A2.1, the impact on the health of fish and other wildlife is stated to be 1 or 2 times per

year when oxygen levels in the river drop low enough to either kill some fish or prevent

migration. This is consistent with the simulated maximum number of exceedances of DO

thresholds for DO Standards 1 – 4 (between 1 to 3 times per year these standards are simulated

to be exceeded).

C. STW improvements and Lee Tunnel: this scenario is equivalent to the baseline incorporating the

impact of the Lee Tunnel which is relevant for the updated benefits estimate for the Thames

Tideway Tunnel. Under this scenario, despite significant improvements, the system fails all four

DO standards, and conditions in the Thames Tideway are still deleterious to aquatic organisms.

Hence the scenario remains broadly consistent with the ‘without’ Thames Tideway Tunnel case

presented to respondents in the 2006 study, as the simulated maximum number of exceedances

of thresholds for DO Standards 1 and 2 are within the range of 1 to 2 times per year.

D. STW improvements, Lee tunnel and Thames Tideway Tunnel: this scenario represents the ‘with’

Thames Tideway Tunnel case for both the 2006 study and the updated benefits estimate. Under

these conditions the system is compliant with all four DO standards. The simulated maximum

number of exceedances of the DO thresholds is consistent with the information provided to

respondents in the 2006 study (less than 1 time per year when oxygen levels in the water drop

low enough to either kill some fish or prevent migration).

Overall, the Lee Tunnel results in an improvement of the conditions in the Thames Tideway.

However the baseline impacts (with Lee Tunnel but without Thames Tideway Tunnel) are not

substantially different from the information provided to respondents in the 2006 study for the

‘without’ the Thames Tideway Tunnel case. Specifically, the Lee Tunnel does not improve

conditions sufficiently enough to meet the thresholds required for healthy river ecology and fish

populations. These thresholds are only achieved with the addition of the Thames Tideway Tunnel to

the system, which results in compliance across all four DO standards.

A2.4.3 Sewage litter

Sewage litter impacts from CSOs in the Thames Tideway are linked to the location and frequency of

overflows. When overflows occur, litter is deposited to the Tideway. The 2006 study informed

respondents that approximately 10% of litter in the Thames Tideway was attributable to CSOs, and

that litter would be especially visible close to outfalls following overflows. As noted above, the Lee

Tunnel only addresses the Abbey Mills CSO which discharges to the River Lee. This CSO had a screen

to capture litter contained within the overflow before it discharged, and so the removal of this CSO

would not have an impact on sewage litter. Further, the Lee Tunnel does not impact the litter

entering the Thames Tideway from the 34 other CSOs. Hence it is expected that there is no

substantial difference in the information provided to respondents in 2006 study with respect to

sewage litter impacts, and the case with Lee Tunnel operational in advance of the Thames Tideway

Tunnel.



A2.4.4 Risk of suffering illness through contact with river water

As with sewage litter, the risk of suffering illness through contact with river water is determined by

the location and frequency of overflows. In the 2006 study, this risk was stated to be higher

following each overflow and with a high risk at all other times25. Based on 60 overflows per year on

average (Table A2.1) without the Thames Tideway Tunnel, this suggest around 120 days per year

for elevated risk levels, assuming 2-day duration for elevated risk level following an overflow.

Information provided by Thames Tideway Tunnels indicates an exposure risk for human health for

approximately 150 days per year on average for the ‘without’ Thames Tideway Tunnel26.

The Lee Tunnel will have minimal impact on the risk of suffering illness through contact with river

water, since it only addresses one CSO and the majority of recreational use of the river (e.g. rowing

and boating) is in the Upper Tideway stretch (West London). Overall, the finding is that there is no

substantial difference in the information provided to respondents in 2006 study with respect to

human health risk. In addition, since the level of risk was expressed qualitatively (i.e. ‘higher risk’

following an overflow), the potential understatement of the ‘without’ impact in the 2006 study

(120 days per year on average versus 150 days per year based on current information) is not a key

consideration.

A2.5 Summary

The review of the information concerning the Thames Tideway improvements indicates that the

impacts described in the 2006 study are consistent with the current information, which factors in

the separate construction and operation of the Lee Tunnel. Given that the information provided to

respondents in the 2006 study are judged to remain a valid representation of the 'new' baseline and

improvement, this suggests that the 2006 survey data can be appropriately applied as the basis for

updating the monetary estimate of the benefits of the Thames Tideway Tunnel.

The impacts on sewage litter and human health risk are largely determined by frequency and

location of overflows. Given the Lee Tunnel only addresses one overflow, and that it impacts solely

the lower tidal reaches, these impacts are largely unchanged by its inclusion in the baseline despite

the large impact on the volume of discharges.

The main benefit of the Lee Tunnel is seen in its improvement on conditions for fish and other

wildlife in the lower reaches. The 2006 study ‘with’ and ‘without’ Thames Tideway Tunnel cases

related impacts to both fish migration and fish health based on the four DO standards for the

Thames Tideway. While the Lee Tunnel does result in significant improvements in terms of reduced

frequency of exceedances of the DO standards, the satisfactory thresholds for the health of aquatic

species are not achieved without the Thames Tideway Tunnel. Specifically, the baseline as

specified in the 2006 study of 1 – 2 events per year impacting on fish and ecology remains valid.

Overall the information provided to respondents in the 2006 study adequately represents the

beneficial impact of the Thames Tideway Tunnel, even when considering the fisheries

improvement.

25

Reference to ‘high risk’ at all other times relates to the general background risk associated with contact

with river water (in the River Thames and other rivers/non-bathing waters more generally), which arises from the typical levels of effluent, including pathogens. This information was included in the 2006 study to ensure that respondents did not perceive the impacts on the Thames Tideway as representing improvements that would result in water quality levels that were safe for activities entailing full immersion in water (e.g. swimming). 26

Pers. comm. Thames Tideway Tunnels, August 2014.



APPENDIX TO ANNEX 2: EXTRACT OF 2006 STATED PREFERENCE SURVEY SHOW

MATERIAL

SHOWCARD C.1

In the past, the tidal Thames has suffered from severe pollution from various sources.

Major improvements to sewage treatment were carried out in the late 1960s and 70s

that allowed fish to return to what was previously a dead river. Note that the tidal

Thames naturally appears brown in colour because of mud stirred up from the river

bed with the fast flowing water.

Since these improvements 120 species of fish have been identified returning to the

river. About 45 species of fish are present at any one time. The river is now a nursery

ground for many commercial species of fish as well as some rare and protected

species. The abundance of fish is used as an indication of all wildlife in and around

the river. Other wildlife, such as insects and birds, have also benefited from the

improvements.

The sewers of London collect both sewage and rainwater. The system works well in

dry weather. At times of heavy or moderate rain, the volume of sewage and rainwater

exceeds the capacity of the sewers and sewage treatment works resulting in

untreated sewage overflowing into the river. There are on average about 60 days

when sewers overflow each year, which could happen at one or a number of outfalls

situated between Chiswick and Beckton. Not all outfalls overflow every time, and

when they do the pollution impacts are likely to be different.



SHOWCARD C.2

The overflows may, particularly in the summer months, reduce the level of oxygen

available in parts of the river. This may last for several days and affect the health

of fish. On the worst occasions, some fish might die while others may be

prevented from migrating upstream to breed. It is difficult to assess the long term

impact on fish populations of these events, but some sensitive species (such as

smelt or salmon) may be lower in number than they would otherwise be or may be

unable to inhabit the tidal Thames.

The overflows bring with them sewage litter (human excrement, condoms, sanitary

towels) which may be seen floating on the river, often in clearly-visible grey slicks

of fat and grease, or deposited on the foreshore at low tide, particularly near

where overflows occur. But note that the majority of litter visible on or along the

tidal Thames, such as plastic bottles, bags, cans, shopping trolleys and so on, is

not related to sewage. Sewage litter is estimated to form about 10% of all litter on

the tidal Thames.

There is always some health risk through immersion or ingestion of river water

during, say, water sports such as rowing. However, this risk increases for several

days following an overflow due to the increased number of bacteria and viruses in

water (perhaps a 20 or 30 fold higher than normal). Those affected can suffer

diarrhoea, vomiting, and skin infections or irritation. Casual contact, for instance

with sewage litter on the foreshore, represents a further risk.



SHOWCARD C.3

Future situation after completion of agreed investment

in sewage treatment works

Year

2014

Health of fish and other

wildlife

1 or 2 occasions per year when oxygen levels in the water

drops low enough to either kill some fish or prevent

migration (e.g. salmon)

Sewage litter

May be visible anywhere along the tidal Thames, but

especially visible close to outfalls following overflows


Risk of suffering illness

through contact with

river water

Higher risk following each overflow


Frequency of overflows

60 times per year on average

Fewer in dry periods

Water bills

Ongoing and agreed investments in water supply, leakage

reduction and sewage treatment will increase water bills



Map

This map shows the route of the tunnel. The project could start in 2007 and will

require 14 years to plan and construct. So, if the tunnel goes ahead, this card

[SHOWCARD C.4(a)] summarises the changes that would happen in 2021.



SHOWCARD C.4 (a)

Future situation after completion

of agreed investment in sewage

treatment works

Future situation with further

investment in a tunnel for sewer

overflows – Option A

Year

2014

2021

Health of fish and

other wildlife

1 or 2 times per year when oxygen

levels in the water drops low

enough to either kill some fish or

prevent migration (e.g. salmon)

Less than 1 time per year when

oxygen levels in the water drops

low enough to either kill some fish

or prevent migration (e.g. salmon)

Sewage litter

May be visible anywhere along the

tidal Thames, but especially visible

close to outfalls following overflows


Small amount visible 3 times per

year following overflows.

Risk of suffering

illness through

contact with river

water

Higher risk following each overflow

event


Higher risk only following the

remaining 3 overflows per year.


Frequency of

overflows


Fewer in dry periods


Water bills

Ongoing and agreed investments

in water supply, leakage reduction

and sewage treatment will increase

water bills

Will continue to increase to finance

investments in water supply,

leakage reduction and sewage

treatment



SHOWCARD C.5

I would now like you to think what you and your household would be prepared to pay per year,

if anything, to achieve the future improvements offered by the Option A tunnel, over and

above your current bill and future increases to it. We are talking about the benefits of moving

from the situation we will have in 2014 to the situation described in 2021.

Starting at the top of the list [SHOWCARD C.5(a)] ask yourself: ‘Would my household and I be

prepared to pay 50 pence each year to support the tunnel project to reduce the impacts of

sewer overflows to the tidal Thames? Or would I prefer the tunnel project not to take place

and not pay that amount?’ Then do the same for £1, £2.50 and so on. If you do not wish to pay

anything, choose zero.

Proceed down this payment ladder and if you are almost certain you would pay the amounts of

money in the card for the tunnel, then place a TICK () in the space next to these amounts.

Going down the ladder, when you reach an amount that you are not sure you would be

prepared to pay then simply leave it BLANK.

When you reach an amount that you are almost certain that you would not pay, then place a

CROSS () next to the amount and STOP.

SHOWCARD C.5 (a)

Amount (per year)

(can be paid in monthly instalments)

Starting in 2007

Permanent increase in your water bill

Prepared to pay (, )

£0

50 pence

£1

£2.50

£5

£10

£15

£20

£25

£30

£35

£40

£50

£60

£75

£100

More than £100

Before you give me an answer, please consider the following [SHOWCARD C.6]:



SHOWCARD C.6

Studies have shown that many people say they are willing to pay more in surveys for

these types of investment than they actually would pay if the situation were real.

This is because when people actually have to part with their money, they take into

account that there are other things they may want to spend their money on.

They may take into account that water bills will continue to go up to support other

investments in water supply, leakage reduction and sewage treatment works.

They may also consider that the investments discussed address the sewage and

rainwater overflows in the tidal part of the Thames alone and not in any other part of

the Thames.

Those who use the tidal Thames for recreational activities may also take into account

that there are other water bodies they can use for recreation.

For this reason, when answering this question, please consider the benefits to you

and your family of reducing sewage overflows in the tidal Thames and imagine your

household actually paying the amounts specified.



ANNEX 3: TEMPORAL AGGREGATION PARAMETERS

Year CPIa

GDP per household

indexb

Household income

weighting factor

c

National population

b

(million

household)

TW population

d

(million

households)

Population weighting

factore

Discount factor

f

2006 100.00 - - - - - -

2007 102.34 - - - - - -

2008 106.06 - - - - - -

2009 108.30 - - - - - -

2010 111.92 - - - - - -

2011 116.90 - - - - - -

2012 120.24 - - - - - -

2013 123.27 - - - - - -

2014 125.22 1.00 1.00 23.0 5.62 1.00 1.0000

2015 - 1.00 1.09 23.2 5.68 1.01 0.9662

2016 - 1.01 1.20 23.5 5.74 1.02 0.9335

2017 - 1.02 1.21 23.7 5.79 1.03 0.9019

2018 - 1.02 1.19 24.0 5.85 1.04 0.8714

2019 - 1.03 1.30 24.2 5.91 1.05 0.8420

2020 - 1.04 1.31 24.4 5.97 1.06 0.8135

2021 - 1.04 1.20 24.7 6.03 1.07 0.7860

2022 - 1.05 1.21 24.9 6.08 1.08 0.7594

2023 - 1.06 1.22 25.1 6.14 1.09 0.7337

2024 - 1.06 1.25 25.4 6.20 1.10 0.7089

2025 - 1.07 1.29 25.6 6.25 1.11 0.6849

2026 - 1.08 1.30 25.8 6.30 1.12 0.6618

2027 - 1.08 1.31 26.0 6.36 1.13 0.6394

2028 - 1.09 1.32 26.3 6.41 1.14 0.6178

2029 - 1.10 1.36 26.5 6.46 1.15 0.5969

2030 - 1.11 1.37 26.7 6.51 1.16 0.5767

2031 - 1.11 1.35 26.9 6.56 1.17 0.5572

2032 - 1.12 1.36 27.1 6.61 1.18 0.5384

2033 - 1.13 1.37 27.3 6.66 1.19 0.5202

2034 - 1.14 1.49 27.4 6.68 1.19 0.5026

2035 - 1.15 1.53 27.5 6.70 1.19 0.4856

2036 - 1.16 1.55 27.5 6.73 1.20 0.4692

2037 - 1.17 1.56 27.6 6.75 1.20 0.4533

2038 - 1.18 1.58 27.7 6.77 1.20 0.4380

2039 - 1.19 1.59 27.8 6.78 1.21 0.4231

2040 - 1.20 1.64 27.9 6.80 1.21 0.4088

2041 - 1.21 1.65 27.9 6.82 1.21 0.3950

2042 - 1.22 1.67 28.0 6.84 1.22 0.3817

2043 - 1.23 1.69 28.1 6.86 1.22 0.3687

2044 - 1.24 1.70 28.2 6.88 1.22 0.3563



Year CPIa

GDP per household

indexb

Household income

weighting factor

c

National population

b

(million

household)

TW population

d

(million

households)


factore

Discount factor

f

2045 - 1.25 1.72 28.2 6.90 1.23 0.3459

2046 - 1.26 1.73 28.3 6.92 1.23 0.3358

2047 - 1.27 1.73 28.4 6.93 1.23 0.3260

2048 - 1.29 1.74 28.5 6.95 1.24 0.3165

2049 - 1.30 1.76 28.5 6.97 1.24 0.3073

2050 - 1.31 1.77 28.6 6.99 1.24 0.2984

2051 - 1.32 1.79 28.7 7.00 1.25 0.2897

2052 - 1.33 1.78 28.7 7.02 1.25 0.2812

2053 - 1.34 1.79 28.8 7.03 1.25 0.2731

2054 - 1.35 1.81 28.9 7.05 1.25 0.2651

2055 - 1.36 1.83 28.9 7.06 1.26 0.2574

2056 - 1.38 1.84 29.0 7.08 1.26 0.2499

2057 - 1.39 1.87 29.0 7.09 1.26 0.2426

2058 - 1.40 1.88 29.1 7.10 1.26 0.2355

2059 - 1.41 1.90 29.1 7.12 1.27 0.2287

2060 - 1.42 1.95 29.2 7.13 1.27 0.2220

2061 - 1.44 1.97 29.2 7.14 1.27 0.2156

2062 - 1.45 1.99 29.3 7.15 1.27 0.2093

2063 - 1.46 2.00 29.3 7.17 1.28 0.2032

2064 - 1.48 2.02 29.4 7.18 1.28 0.1973

2065 - 1.49 2.04 29.5 7.19 1.28 0.1915

2066 - 1.50 2.06 29.5 7.21 1.28 0.1859

2067 - 1.52 2.07 29.6 7.22 1.29 0.1805

2068 - 1.53 2.09 29.6 7.24 1.29 0.1753

2069 - 1.54 2.11 29.7 7.25 1.29 0.1702

2070 - 1.56 2.13 29.7 7.26 1.29 0.1652

2071 - 1.57 2.14 29.8 7.28 1.30 0.1604

2072 - 1.58 2.15 29.9 7.29 1.30 0.1557

2073 - 1.60 2.17 29.9 7.31 1.30 0.1512

2074 - 1.61 2.19 30.0 7.33 1.30 0.1468

2075 - 1.63 2.21 30.1 7.34 1.31 0.1425

2076 - 1.64 2.23 30.1 7.36 1.31 0.1384

2077 - 1.65 2.25 30.2 7.38 1.31 0.1343

2078 - 1.67 2.27 30.3 7.39 1.32 0.1304

2079 - 1.68 2.29 30.3 7.41 1.32 0.1266

2080 - 1.70 2.31 30.4 7.43 1.32 0.1229

2081 - 1.71 2.33 30.5 7.44 1.33 0.1193

2082 - 1.73 2.35 30.5 7.46 1.33 0.1159

2083 - 1.74 2.37 30.6 7.48 1.33 0.1125

2084 - 1.76 2.39 30.7 7.49 1.33 0.1092

2085 - 1.77 2.41 30.8 7.51 1.34 0.1060



Year CPIa

GDP per household

indexb

Household income

weighting factor

c

National population

b

(million

household)

TW population

d

(million

households)


factore

Discount factor

f

2086 - 1.79 2.43 30.8 7.53 1.34 0.1029

2087 - 1.81 2.46 30.9 7.54 1.34 0.1000

2088 - 1.82 2.48 31.0 7.56 1.35 0.0970

2089 - 1.84 2.50 31.0 7.58 1.35 0.0942

2090 - 1.85 2.52 31.1 7.59 1.35 0.0919

2091 - 1.87 2.54 31.2 7.61 1.35 0.0897

2092 - 1.89 2.57 31.2 7.63 1.36 0.0875

2093 - 1.90 2.59 31.3 7.64 1.36 0.0854

2094 - 1.92 2.61 31.4 7.66 1.36 0.0833

2095 - 1.94 2.63 31.4 7.68 1.37 0.0812

2096 - 1.95 2.66 31.5 7.70 1.37 0.0793

2097 - 1.97 2.68 31.6 7.71 1.37 0.0773

2098 - 1.99 2.70 31.7 7.73 1.38 0.0754

2099 - 2.01 2.73 31.7 7.75 1.38 0.0736

2100 - 2.02 2.75 31.8 7.77 1.38 0.0718

2101 - 2.02 2.75 31.8 7.77 1.38 0.0701

2102 - 2.02 2.75 31.8 7.77 1.38 0.0683

2103 - 2.02 2.75 31.8 7.77 1.38 0.0667

2104 - 2.02 2.75 31.8 7.77 1.38 0.0651

2105 - 2.02 2.75 31.8 7.77 1.38 0.0635

2106 - 2.02 2.75 31.8 7.77 1.38 0.0619

2107 - 2.02 2.75 31.8 7.77 1.38 0.0604

2108 - 2.02 2.75 31.8 7.77 1.38 0.0589

2109 - 2.02 2.75 31.8 7.77 1.38 0.0575

2110 - 2.02 2.75 31.8 7.77 1.38 0.0561

2111 - 2.02 2.75 31.8 7.77 1.38 0.0547

2112 - 2.02 2.75 31.8 7.77 1.38 0.0534

2113 - 2.02 2.75 31.8 7.77 1.38 0.0521

2114 - 2.02 2.75 31.8 7.77 1.38 0.0508

2115 - 2.02 2.75 31.8 7.77 1.38 0.0496

2116 - 2.02 2.75 31.8 7.77 1.38 0.0484

2117 - 2.02 2.75 31.8 7.77 1.38 0.0472

2118 - 2.02 2.75 31.8 7.77 1.38 0.0460

2119 - 2.02 2.75 31.8 7.77 1.38 0.0449

2120 - 2.02 2.75 31.8 7.77 1.38 0.0438

2121 - 2.02 2.75 31.8 7.77 1.38 0.0428

2122 - 2.02 2.75 31.8 7.77 1.38 0.0417

2123 - 2.02 2.75 31.8 7.77 1.38 0.0407

2124 - 2.02 2.75 31.8 7.77 1.38 0.0397

2125 - 2.02 2.75 31.8 7.77 1.38 0.0387

2126 - 2.02 2.75 31.8 7.77 1.38 0.0378



Year CPIa

GDP per household

indexb

Household income

weighting factor

c

National population

b

(million

household)

TW population

d

(million

households)


factore

Discount factor

f

2127 - 2.02 2.75 31.8 7.77 1.38 0.0369

2128 - 2.02 2.75 31.8 7.77 1.38 0.0360

2129 - 2.02 2.75 31.8 7.77 1.38 0.0351

2130 - 2.02 2.75 31.8 7.77 1.38 0.0342

2131 - 2.02 2.75 31.8 7.77 1.38 0.0334

2132 - 2.02 2.75 31.8 7.77 1.38 0.0326

2133 - 2.02 2.75 31.8 7.77 1.38 0.0318

2134 - 2.02 2.75 31.8 7.77 1.38 0.0310

Notes: a ONS (2014b) CPI re-based to 2006 = 100. b DfT (2014) WebTAG Databook – index re-based to 2014 = 100. c

Calculated weighting factor based on equation [4] – see Section 2.5.3. d Current (2014) Thames Water sewerage customer

household numbers provided by Thames Water. Customer growth forecasted using DfT (2014) WebTAG Databook – index

re-based to 2014 = 100. e Calculated weighting factor based on equation [6] – see Section 2.6. f HM Treasury (2003).



ANNEX 4: ECONOMETRIC RESULTS

Table A4.1: OLS model

1. Distance and

Ln(income)

2. Distance and

income

3. Distance and

quadratic income

4. Distance, income

and education

5. All co-variates 6. Distance and

SEG

Coeff. s.e. p-value Coeff. s.e. p-value Coeff. s.e. p-value Coeff. s.e. p-value Coeff. s.e. p-value Coeff. s.e. p-value

Constant 1.498 0.233 0.000 2.345 0.111 0.001 2.092 0.155 0.000 1.522 0.232 0.000 1.488 0.281 0.000 2.343 0.152 0.000

Distance -0.003 0.001 0.001 -0.003 0.001 0.000 -0.003 0.001 0.001 -0.002 0.001 0.003 -0.002 0.001 0.003 -0.003 0.001 0.000

Income - - - 0.014 0.002 0.000 0.033 0.007 0.000 - - - - - - - - -

Ln(income) 0.407 0.066 0.000 - - - - - - 0.374 0.067 0.000 0.383 0.070 0.000 - - -

Income sq. - - - - - - -0.000 0.000 0.003 - - - - - - - - -

Uni. (=1) - - - - - - - - - 0.210 0.107 0.050 0.213 0.108 0.048 - - -

Male (=1) - - - - - - - - - - - - 0.132 0.106 0.212 - - -

Age (25-35) - - - - - - - - - - - - -0.148 0.191 0.440 - - -

Age (35-45) - - - - - - - - - - - - -0.152 0.198 0.443 - - -

Age (45-55) - - - - - - - - - - - - 0.167 0.192 0.385 - - -

Age (55-65) - - - - - - - - - - - - -0.241 0.197 0.222 - - -

Age (65+) - - - - - - - - - - - - 0.005 0.206 0.982 - - -

SEG AB - - - - - - - - - - - - - - - 0.708 0.161 0.000

SEG C1 - - - - - - - - - - - - - - - 0.472 0.160 0.003

SEG C2 - - - - - - - - - - - - - - - 0.234 0.184 0.203

Summary statistics

Model fit

Adjusted r2 0.102 Adjusted r2 0.085 Adjusted r2 0.0966 Adjusted r2 0.106 Adjusted r2 0.110 Adjusted r2 0.0699

F-stat 32.94 F-stat 29.32 F-stat 22.29 F-stat 22.83 F-stat 9.16 F-stat 11.34

p-value 0.000 p-value 0.000 p-value 0.000 p-value 0.000 p-value 0.000 p-value 0.000

σ2 1.474 σ2 1.502 σ2 1.483 σ2 1.468 σ2 1.461 σ2 1.527

Obs.1 n 603 n 603 n 603 n 603 n 603 n 603

Notes: 1 Excludes protest responses.



Table A4.2: Interval data model

1. Distance and

Ln(income)

2. Distance and

income

3. Distance and

quadratic income

4. Distance, income

and education

5. All co-variates 6. Distance and

SEG

Coeff. s.e. p-value Coeff. s.e. p-value Coeff. s.e. p-value Coeff. s.e. p-value Coeff. s.e. p-value Coeff. s.e. p-value

Constant 1.985 0.228 0.000 2.727 0.106 0.000 2.529 0.150 0.000 2.007 0.227 0.000 1.959 0.273 0.000 2.712 0.147 0.000

Distance -0.003 0.001 0.000 -0.003 0.001 0.000 -0.003 0.001 0.000 -0.003 0.001 0.001 -0.003 0.001 0.001 -0.003 0.001 0.000

Income - - - 0.012 0.002 0.000 0.027 0.007 0.000 - - - - - - - - -

Ln(income) 0.357 0.064 0.000 - - - - - - 0.326 0.0654 0.000 0.325 0.068 0.000 - - -

Income sq. - - - - - - -0.000 0.000 0.007 - - - - - - - - -

Uni. (=1) - - - - - - 0.195 0.0985 0.048 0.198 0.099 0.045 - - -

Male (=1) - - - - - - - - - - - - 0.142 0.101 0.158 - - -

Age (25-35) - - - - - - - - - - - - -0.064 0.180 0.718 - - -

Age (35-45) - - - - - - - - - - - - -0.133 0.185 0.471 - - -

Age (45-55) - - - - - - - - - - - - 0.240 0.172 0.163 - - -

Age (55-65) - - - - - - - - - - - - -0.162 0.188 0.388 - - -

Age (65+) - - - - - - - - - - - - 0.018 0.198 0.929 - - -

SEG AB - - - - - - - - - - - - - - - 0.625 0.155 0.000

SEG C1 - - - - - - - - - - - - - - - 0.461 0.153 0.003

SEG C2 - - - - - - - - - - - - - - - 0.200 0.182 0.271

Summary statistics

Model fit

Pseudo r2 0.05 Pseudo r2 0.04 Pseudo r2 0.05 Pseudo r2 0.06 Pseudo r2 0.06 Pseudo r2 0.03

Wald-chi2 59.38 Wald-chi2 58.12 Wald-chi2 60.96 Wald-chi2 63.14 Wald-chi2 77.45 Wald-chi2 44.03

p-value 0.000 p-value 0.000 p-value 0.000 p-value 0.000 p-value 0.000 p-value 0.000

σ2 1.296 σ2 1.315 σ2 1.303 σ2 1.289 σ2 1.267 σ2 1.327

Obs.1 n 603 n 603 n 603 n 603 n 603 n 603

Notes: 1 Excludes protest responses.



ANNEX 5: ANNUAL AGGREGATE BENEFITS Figure A5.1: Annual aggregate benefit by MSOA (£/yr) – benefits jurisdiction (2006, £)



Figure A5.2: Annual aggregate benefit by MSOA (£/yr) – administrative jurisdiction (2006, £)



ANNEX 6: SENSITIVITY ANALYSIS

This annex reports results from supplementary sensitivity analysis in relation to: (i) estimating WTP;

and (ii) calculating aggregate benefits. It examines the main assumptions supporting the updated

benefit estimates for the Thames Tideway Tunnel:

Section A6.1 compares the sequential change in unit WTP values from the procedure to update

the transferable WTP function; and

Section A6.2 reports results from alternative aggregation assumptions in terms of: (i) applying a

60 year time horizon consistent with the original CBA (Nera, 2006); and (ii) and assuming that

benefits commence in 2015.

The results reported here provide further supporting information for interpreting the updated

benefit estimates; in particular in helping to establish the main assumptions and changes to the

2006 analysis that impact aggregate values.

A6.1 Estimating willingness to pay for Thames Tideway improvements

Section 3 describes the estimation of household WTP for the Thames Tideway improvements via a

transferable WTP function. The 2006 analysis estimated a conservative lower bound value, using an

OLS model specification controlling for distance from the Thames Tideway and socio-economic

group (SEG).

A6.1.1 Model specification

The updated analysis tests both the OLS model specification and an interval data model

specification (see Section 3.1.2) and revised the set of explanatory variables to include distance

from the Thames Tideway and household income. The 2006 sample data is also re-weighted to

reflect the 2014 population profile (see Section 2.5.3; Table 2.3). The updated analysis utilises

spatially disaggregated data on household income that is now available to replace the SEG indicator

variables. The use of income as an explanatory variable in the transferable function provides a

more explicit constraint on household WTP than SEG, which can only be regarded as a proxy

indicator for the household budget constraint.

The step-by-step updates to the transferable WTP function are:

Model 1: OLS model with distance and SEG as explanatory variables using 2006 sample data.

Model 2: OLS model with distance and SEG as explanatory variables using re-weighted 2014

population profile.

Model 3: OLS model with distance and natural log of income as explanatory variables using re-

weighted 2014 population profile.

Model 4: interval data model (last tick - first cross uncertainty) with distance and natural log of

income as explanatory variables using re-weighted 2014 population profile.



Model 5: interval data model (last tick – next amount on payment card uncertainty) with

distance and natural log of income as explanatory variables using re-weighted 2014 population

profile.

Models 3 and 4 are the two main specifications that are presented in Section 3.2.1 (Table 3.1).

Model 3 is the specification of the transferable WTP function that is used to calculated aggregate

benefits as reported in Section 4.

Comparing Model 1 and 2 provides evidence about the effect of reweighting the sample on unit

WTP values. Similarly, comparing Model 2 and 3 shows the impact of using income as an

explanatory variable instead of SEG (see also Section A6.1.2).

The comparison between Models 4 and 5 examine the sensitivity of WTP to alternative treatments

of the payment card data in the interval data model. Model 4 uses: (i) the highest amount the

respondent stated they were certain they would pay (the last tick on the payment card); and (ii)

the first amount the respondent was certain they would not pay (the first cross). Model 5 uses: (i)

the highest amount the respondent stated they were certain they would pay (the last tick on the

payment card); and (ii) the next amount on the payment card. Whilst Model 5 represents a more

conservative estimate than Model 4, the OLS specification for Model 3 is even more conservative.

This gives the lower bound estimate for the analysis since it is based only on (i) the highest amount

the respondent stated they were certain they would pay (the last tick on the payment card).

Table A6.1 reports mean and median predicted WTP for Models 1 – 5. Predicted values are

calculated for each model specification at the relevant sample means for the explanatory

variables27. Consistent with discussion included in Section 3.2.2 of the Main Report, the difference

between mean and median WTP is proportional to exp(σ2/2), where σ2 is a measure of the

variance of the error term in the model estimation. Estimation results for Models 1 – 5 are provided

in the appendix to this Annex for reference.

Table A6.1: Comparing predicted WTP from model specification changes (2006, £)

Model Predicted WTP (£/hh/yr)

Mean % diff. (mean)

Median

1. OLS distance + SEG 2006 sample profile 26.10 - 11.26

2. OLS distance + SEG re-weighted 25.71 -1.5 11.45

3. OLS distance + ln income reweighted 25.02 -4.1 11.45

4. IDM (last tick/1st cross) distance + ln income reweighted 31.96 +22.5 16.24

5. IDM (last tick/next amount) distance + ln income reweighted 28.02 +7.4 13.78

Notes: Percentage (%) difference in mean WTP calculated relative to Model 1. IDM = interval data model.

27 For comparison, mean and median WTP values reported in the 2006 study report (eftec, 2006) are non-

parametric; i.e. based directly on the responses from the sample without any assumption as to the distribution of responses. Mean WTP (£22.55/hh/yr) is the arithmetic mean of the WTP responses from the sample (excluding protest responses), and median WTP (£15/hh/yr) is the amount 50% of the sample were willing to pay (excluding protest responses). Both results reported here for the 2006 study are for the benefits jurisdiction for the large tunnel option (see Table 4.16; eftec, 2006). Mean and median WTP estimates reported in Table A6.1 (above) are calculated from model specifications with a log-normal distribution (see Section 3.1.2). Note that the transferable function specified in 2006 for calculating spatially sensitive WTP was also log-normally distributed.



Table A6.1 illustrates that OLS model predicted WTP values are relatively insensitive to the

different assumptions/variable specifications. Moving from Model 1 to Model 3 reduces predicted

WTP (at sample mean) by around 4.1% (approx. £1/hh/yr). Higher WTP values are evident for the

interval data model specifications (Models 4 and 5). Differences with Model 3 – the specification

used to estimate aggregate benefits - are around 28% (approx. £7/hh/yr) and 12% (approx.

£3/hh/yr) for Models 4 and 5, respectively. This highlights the conservative lower bound that is

provided by the OLS specification. Switching to the interval data model specification would imply

an uplift in benefit estimates of between 10 – 30%.

A6.1.2 Predicted WTP with updated household income data

Predicted WTP amounts are also reported by evaluating the transferable WTP function at different

data points, comparing the sample data to the ONS MSOA data that provides spatially disaggregated

estimates of household income. This provides an indication of the impact of using the MSOA data in

the transferable WTP function. Results are presented in Table A6.2.

Table A6.2: Comparing predicted WTP from model specification changes (2006, £)


Mean % diff. (mean)

Median

2. OLS distance + SEG re-weighted 25.71 - 11.45

2. OLS distance + SEG MSOA data 25.18 -2.1 11.20

3. OLS distance + income reweighted 25.38 - 11.45

3. OLS distance + income MSOA data 28.39 +10.6 12.87

Notes: Percentage (%) difference in mean WTP calculated relative to Models 2 and 3.

Differences in WTP amounts are not particularly substantial. However, the aggregation procedure

incorporating distance decay in unit values places more weight on the households closer to the

Thames Tideway, which is also where higher income levels are observed in the MSOA dataset. This

effect is observed by comparing predicted WTP for the Thames Water region (administrative

jurisdiction) to the national averages (benefits jurisdiction) set out in Table A6.3. Results are

provided in Table A6.3.

Table A6.3: Comparing predicted WTP from model specification changes – administrative

jurisdiction only (2006, £)


Mean % diff. (mean)

Median

2. OLS distance + SEG re-weighted 29.17 - 13.06

2. OLS distance + SEG MSOA data 29.30 +0.4 13.12

3. OLS distance + income reweighted 28.67 - 13.00

3. OLS distance + income MSOA data 35.69 +24.5 16.31

Notes: Percentage (%) difference in mean WTP calculated relative to Models 2 and 3.

What can be inferred from Table A6.3 is the effect of re-specifying the transferable function to

include household income and then applying the available spatially disaggregated household income

data to predict WTP. It shows that the main sensitivity in the aggregation procedure is the data

inputted to predict WTP, rather than the model estimation approach and the specification of the

transferable WTP function. This conclusion is supported by comparison of mean (average)



household income reported in 2006 survey data and the ONS modelled household income at the

MSOA level.

Table A6.3: Annual average household income (2006, £)

Administrative jurisdiction Benefits jurisdiction

2006 survey data £26,900 £25,800

ONS MSOA data (2007/08) £41,450 £33,040

Table A6.3 shows on average higher levels of household income for both the administrative and

benefits jurisdictions, in comparison to the 2006 survey data. Differences are greater in the

administrative jurisdiction compared to the benefits jurisdiction.

A6.2 Aggregating benefits

In the 2006 survey, respondent WTP was elicited via household water and sewerage bills as the

payment vehicle. Respondents were informed that bills would increase the following year (i.e.

2007) and that benefits would begin in 2021 (i.e. year 15 of the time horizon). This framing implies

that respondents would be willing to pay for the benefits of the tunnel during its 15 year

construction period, despite the fact that benefits would not be realised until its completion.

The aggregate results reported in Section 4, however, profile benefits from the current expected

completion date for the Thames Tideway Tunnel, which is 2024. This is a conservative aggregation

approach that does not assign any benefit value to the 9-year period between 2015 and 2025. The

following sensitivity analysis assesses the impact on aggregate results by profiling benefits from

2015. Two time-horizons for calculating present value benefits are considered: (i) the 120 year

period applied in Section 4; and (ii) a 60 year period, consistent with the original CBA (Nera, 2006).

A6.2.1 Administrative jurisdiction

Table A6.4 presents aggregate estimates for the administrative jurisdiction for benefits

commencing in 2024 (as per Section 4) and 2015 (sensitivity). The comparison is provided across

Scenarios A – D for both 120 and 60 year time horizons.

Table A6.4: Aggregate benefit estimates – administrative jurisdiction (2014, £)

Scenario

Benefits profiled from

2024


2015 % diff. % diff.

PV 120, £bn PV 60, £bn PV 120, £bn PV 60, £bn PV 120 PV 60

Scenario A 2.8 2.2 3.7 3.2 35 % 43 %

Scenario B 3.4 2.7 4.4 3.7 29 % 38 %

Scenario C 3.8 2.7 4.8 3.7 26 % 36 %

Scenario D 4.7 3.3 5.8 4.4 22 % 31 %



As shown in Table A6.4, adjusting the profile of benefits to commence in 2015 results in a

considerable increase in the present value estimates. The effect is an increase of between 22 - 35 %

for the 120 year time horizon and between 31 - 43% for the 60 year time horizon.



A6.2.2 Benefits jurisdiction

Table A6.5 presents aggregate estimates for the benefits jurisdiction for benefits commencing in

2024 (as per Section 4) and 2015 (sensitivity). The comparison is provided across Scenarios A – D for

both 120 and 60 year time horizons.

Table A6.4: Aggregate benefit estimates – benefits jurisdiction (2014, £)

Scenario


2024


2015 % change % change

PV 120, £bn PV 60, £bn PV 120, £bn PV 60, £bn PV 120 PV 60

Scenario A 7.4 5.9 10.0 8.5 35 % 43 %

Scenario B 9.2 7.2 11.9 9.8 29 % 38 %

Scenario C 10.1 7.3 12.7 10.0 26 % 36 %

Scenario D 12.7 8.9 15.4 11.6 22 % 31 %



As for the administrative jurisdiction, adjusting the timing of benefits results in a considerable

increase in the estimated present values. The effect is consistent with that of the administrative

jurisdiction; an increase of between 22 % - 35 % for the 120 year time horizon and between 31% -

43% for the 60 year time horizon. The relative change across Scenarios A – D is consistent between

administrative and benefits jurisdictions, as only the timing of benefits has been adjusted (i.e.

there is no change in the discount factors, income growth rate factors or population growth

factors).



APPENDIX TO ANNEX 6: ECONOMETRIC RESULTS

1. OLS distance + SEG 2006

sample profile

2. OLS distance + SEG

re-weighted

3. OLS distance + ln income

reweighted

4. IDM1 distance +

ln income reweighted

5. IDM2 distance +

ln income reweighted

Coeff. s.e. p-value Coeff. s.e. p-value Coeff. s.e. p-value Coeff. s.e. p-value Coeff. s.e. p-value

Constant 2.273 0.144 0.000 2.343 0.152 0.000 1.498 0.233 0.000 1.985 0.228 0.000 -0.002 0.001 0.001

Distance -0.003 0.001 0.000 -0.003 0.001 0.000 -0.003 0.001 0.001 -0.003 0.001 0.000 0.386 0.064 0.000

Ln(income) - - - - - - 0.407 0.066 0.000 0.357 0.064 0.000 1.722 0.226 0.000

SEG AB 0.740 0.155 0.000 0.708 0.161 0.000 - - - - - -

SEG C1 0.520 0.154 0.001 0.472 0.160 0.003 - - - - - - - - -

SEG C2 0.354 0.180 0.050 0.234 0.184 0.203 - - - - - - - - -

Summary statistics

Model fit

Adjusted r2 0.079 Adjusted r2 0.088 Adjusted r2 0.102 Pseudo r2 0.049 Pseudo r2 0.0

F-stat 11.49 F-stat 29.32 F-stat 32.94 Wald-chi2 59.38 Wald-chi2 63.29

p-value 0.000 p-value 0.000 p-value 0.000 p-value 0.000 p-value 0.000

σ2 1.586 σ2 1.502 σ2 1.474 σ2 1.296 σ2 1.350

Obs.1 n 603 n 603 n 603 n 603 n 603

Notes: IDM = interval data model; IDM1 = last tick/1st cross; IDM2 = last tick/next amount.

UPDATE OF THE ECONOMIC VALUATION OF THAMES TIDEWAY...

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