Measuring the Social and Distributional Impacts of Road Pricing Schemes
TAG Unit 3.12.4

February 2007

Contents

1. Introduction
   1.1 Guidance for schemes that include road pricing
   1.2 Background: social and distributional impacts
   1.3 The social and distributional impacts of road pricing schemes

2. Gathering evidence
   2.1 The research questions
   2.2 Data required
   2.3 Mapping areas of multiple deprivation

3. Household surveys
   3.2 Trip data
   3.3 Household and individual characteristics

4. Selecting an appropriate survey methodology
   4.2 Response rates and bias in the achieved sample
   4.3 Sampling
   4.4 Data collection

5. Using and analysing the survey data
   5.2 Analysing trip data
   5.3 Mapping trip data
   5.4 Analysing questionnaire data

6. Using qualitative research

7. Using the evidence
   7.1 Interpreting research findings
   7.2 Proportionality and minimum requirements
   7.3 Reporting format for supporting analyses on social and distributional impacts
   7.4 Ongoing use of the social research data

8. Further information

9. References

10. Data provenance

1. Introduction

1.1 Guidance for schemes that include road pricing

1.1.1 This Unit provides guidance on requirements for measuring social and distributional impacts using social research methods when projects include road pricing schemes. Where appropriate, it refers to guidance in other TAG Units, rather than repeating that guidance.

1.1.2 An overview of the modelling and appraisal issues, including scheme design issues, arising in the analysis of road pricing schemes can be found in Introduction to Modelling and Appraisal for Road Pricing (TAG Unit 2.12). Further detailed guidance for analysts may be found in:

• Designing Effective Road Pricing Schemes (TAG Unit 3.12.1), which discusses approaches to the design of effective road pricing schemes;
• Modelling Road Pricing (TAG Unit 3.12.2) provides advice on the modelling of road pricing schemes;
• Guidance on the issues arising when appraising road pricing schemes is provided in Appraisal of Road Pricing Schemes (TAG Unit 3.12.3); and
• The current unit, Measuring the Social and Distributional Impacts of Road Pricing Schemes (TAG Unit 3.12.4) provides guidance on the use of social research methods to assess the social and distributional impacts of road pricing. This guidance covers a range of quantitative and qualitative social research methods. It does not cover the assessment of distributional impacts using other methods, for example modelling techniques. See TAG Unit 3.12.3 for how to incorporate social research and other analysis of distributional impacts into business cases.

1.1.3 This unit represents the current state of knowledge. This is a rapidly developing area where we are likely to learn from further evidence as it emerges and also from the practical implementation of road pricing schemes. This unit will be revised and updated as further information becomes available or in light of any comments received during consultation and in the application of the unit.

1.2 Background: social and distributional impacts

1.2.1 'Social' impacts relate to the impacts on people, whether they be first order effects, such as trip suppression or modal shift, or second order effects, such as reducing access to employment or improvements in air quality. There are points of overlap between social, economic and environmental impacts, because economic and environmental impacts can have social consequences and vice versa. Social research provides one of the toolkits, alongside economics and physical science, which can be used to measure and explain these impacts.

1.2.2 'Distributional' impacts relate to the extent to which there are differences in the way these social impacts affect different groups in society, such as rich and poor, young and old, men and women, people from different ethnic groups, people living in urban and rural areas, and so on. In relation to road pricing schemes, it is important to consider the distributional impacts for two key reasons:

• We know from previous research^[1] that equity and perceived equity are key factors in the public acceptability of road pricing schemes. A well-designed scheme may well produce positive benefits for some of those who are most vulnerable to social exclusion. It is advisable to have a clear understanding of these benefits and the evidence that underpins them before engaging in detailed political and public debate.
• It is important to identify if any negative first or second order impacts are disproportionately concentrated amongst groups who may already be vulnerable to disadvantage, such as those experiencing or at greater risk of experiencing health and/or mobility problems, social exclusion and labour market disadvantage. From a social policy perspective it is clearly important to avoid this as far as possible - local transport schemes should work alongside rather than contravene other local social policy objectives. In support of this, DfT's Feasibility Study of Road Pricing in the UK^[2] noted that road pricing schemes should promote social inclusion and accessibility.

1.2.3 In addition, local authorities are under certain legal obligations to consider the equality impacts of their policies and service delivery. The Disability Discrimination Act 2005 introduces a new disability equality duty on all public authorities, including local authorities and government departments, to promote disability equality, which comes into effect on 4 December 2006. The disability equality duty is a series of legal requirements with which a public authority must comply and applies equally to both external policy functions and their role as an employer. Further information and practical advice can be found on www.dotheduty.org or the Disability Rights Commission (now the Equality and Human Rights Commission) website www.equalityhumanrights.com.

1.2.4 The Gender Equality Duty for public bodies will come into effect on 6 April 2007. The Equality Act of 2006 amends the Sex Discrimination Act 1975 and requires public authorities to pay due regard to promoting gender equality and eliminating sex discrimination. This means service providers and public sector employers will have to design employment and services with the different needs of women and men in mind. They will need to set their own gender equality goals in consultation with their service users and employers and take action to achieve them.

1.2.5 This duty will complement the race equality duty introduced in the Race Relations (Amendment) Act 2000, which gives all public authorities a positive duty to eliminate unlawful racial discrimination and promote race equality and good race relations. All public authorities are required to introduce an Action Plan, which should lead to positive outcomes for both the public and staff, including a demonstrable commitment to valuing diversity and improved community satisfaction with better designed services.

1.2.6 Note that this guidance does not obviate a local authority's need to comply with its legal or other responsibilities, for example, requirements for Environmental Impact Assessments, Race Impact Assessments etc, nor should it be assumed that compliance with this guidance will in itself guarantee that all legal obligations will be met. Local authorities are advised to check they are meeting all necessary legal requirements. The aim of this guidance is to highlight the social and distributional issues that may be particularly relevant for road pricing schemes and to provide technical advice on how to gather sufficiently robust evidence. This evidence will then be available for a range of purposes, including business cases, impact assessments and public consultation.

1.2.7 In January 2006, DfT commissioned the University of the West of England to undertake a Rapid Evidence Assessment (report forthcoming) of the social and distributional impacts of road pricing. This study involved a systematic international search for empirical social and economic research from existing and near-market road pricing schemes ('near-market' referred to designed but unimplemented schemes for which relevant analysis had been undertaken e.g. Edinburgh). The evidence was reviewed (including an assessment of its robustness) and drawn together. This current guidance has been based on and builds upon the findings from the REA.

1.2.8 This unit explains how social research methods can be used to help to estimate and explain the social and distributional impacts of road pricing. These methods should be used to complement the information that is traditionally used in appraisal to estimate such impacts, an overview of which can be found in Appraisal of Road Pricing Options (TAG Unit 3.12.3).

1.2.9 Social Research techniques can help to complement more conventional appraisal methods in three key ways:

• First, by providing information that can help to better understand and predict the second order social impacts of road pricing which are not traditionally picked up using conventional appraisal methods - for example, increasing or decreasing access to key services and/or employment opportunities.
• Second, by obtaining information that can be used to predict the way in which social impacts will be distributed across different groups in society at a more fine grained and detailed level than can be achieved via coarser appraisal methods. This is important for the design of schemes, including considering which complementary measures are the most appropriate.
• Third, by providing additional detail to explain the causal processes of impacts. As above, this is important for scheme design and deciding appropriate complementary measures.

1.2.10 Each of these in turn can aid in improving scheme design and the associated package of complementary transport measures that may be being developed. In other words, this unit provides guidance on how to use social research to identify problems and provide evidence to formulate potential solutions, as well as to generate evidence on potential benefits that will be vital for public acceptability.

1.2.11 The next section gives some further information about what is already known about the social and distributional impacts of road pricing schemes; section 2 covers appropriate research questions and data requirements; sections 3 to 5 provide more detail on household surveys, points to consider when selecting an appropriate methodology and analysis of survey data; section 6 briefly covers qualitative research; and section 7 provides advice on interpreting, using and presenting the social research evidence.

1.3 The social and distributional impacts of road pricing schemes

1.3.1 We do not yet fully understand the social and distributional impacts of road pricing. It is acknowledged, however, that these impacts are important and that they can be positive as well as negative, depending on whom they affect and in what ways, leading a scheme to be either more or less progressive in its impacts. The balance and distribution of positive and negative impacts depends on scheme design and implementation and for this reason, these factors need to be taken into account early in the design stage, so that the positive impacts can be maximised and any negatives minimised. This point was highlighted in the Rapid Evidence Assessment that was recently commissioned by DfT:

'If it is possible, by moving the boundary, by redefining the basis of the charge, by allowing different methods of paying the charge, by providing exemptions for certain groups, or by using the revenues to improve the provision of alternative modes of travel in order to reduce the impact on at-risk groups, then this should be given serious consideration right from the outset (Bonsall and Kelly, 2005)'^[3]

1.3.2 What this quotation does not recognise, however, is that if a scheme is built on robust evidence, including evidence that the needs of at-risk groups have been properly taken into account, it will not only be more progressive, but it is also more likely to win public support. Public perception of equity is just as important in determining public acceptability as the actual equity or distribution of impacts. Gathering robust evidence on the social and distributional impacts is therefore also important in areas where levels of deprivation and/or numbers of people in at-risk groups are not high, because it is likely to be important in gaining public acceptability.

1.3.3 The SEU's report on transport and social exclusion, Making the Connections^[4], highlighted some of the potential equity benefits of road pricing schemes. For example, those on low incomes often live in the most congested areas, and as a result could benefit from the effects of reduced congestion through road pricing. These are typically taken to include more reliable bus journeys, improved air quality, and reductions in traffic noise and community severance. If the package of demand management measures being considered includes, for example, improved public transport, then this could have positive distributional impacts, but it will be necessary to collect evidence to make informed decisions about how to maximise this.

1.3.4 In order to make the most of these opportunities, it is first necessary to understand how the positive and negative impacts of a proposed scheme are likely to be distributed across different socio-economic and socio-demographic groups. The next stage is to consider whether it would be beneficial to make changes to the scheme design - such as those listed in the quotation above - and what the effects of these changes would be on the social and distributional impacts (as well as on other factors, such as the efficiency of the scheme).

1.3.5 DfT's recent Rapid Evidence Assessment highlighted that income is important in determining social and distributional impacts. People who are on low incomes and who have no or limited choice about using a car for some or all trips may be at risk of experiencing direct and/or indirect negative consequences of road pricing schemes.

1.3.6 DfT is developing an evidence base to find out who the groups we need to pay particular attention to are, but it is likely that they will include:

• Households and individuals on a low income - our current estimate is that this means people in the bottom two quintiles of the income distribution, particularly those who:
• Have no choice about when to travel e.g. to work, to drop children at school, to hospital, for informal caring obligations.
• Have no choice about how to travel e.g. people with mobility problems (particularly disabled people and older people), carers of these people (including both formal and informal carers), shift workers.

1.3.7 These people may become vulnerable to transport-related social exclusion if a road pricing scheme restricts their accessibility to jobs, healthcare, education, food shops and social networks. These are some of the possible secondary impacts of a scheme and in taking action to resolve these issues, there are clear links with local Accessibility Planning. There are both social and geographical dimensions to consider. Some of these people may be geographically concentrated in deprived areas and/or areas with poor public transport access and/or poor local services and amenities; others will be more dispersed, more difficult to identify and harder-to-reach for the purposes of research and successful transport planning. It is important that research, analysis and scheme design take account of both the geographically concentrated and the geographically dispersed.

1.3.8 Not everybody on a low income will experience negative impacts - some might experience positive or neutral impacts. This will partly depend on other factors, such as economic activity (whether they are working, looking after a family or retired for example) and whether public transport meets or can meet their needs. People living on low incomes have a range of social characteristics, which may help to determine the impact of a road pricing scheme. Below is a list of factors that are often associated with low income, some of which are also associated with the ability (or limited ability) to use public transport, and which are therefore likely to be important in an analysis of the social and distributional impacts of road pricing schemes:

• Worklessness i.e. workless households and families - either couple or lone parent.
• Low paid work - including in some cases shift work.
• Old age - on average, pensioners and older people have lower household incomes^[5] - the most vulnerable to social exclusion and poverty are women and those aged 80+ (although transport-related exclusion could start to occur at a younger age, as access to a private vehicle starts falling after the early-mid 70s).
• Disability - analysis shows that disabled people on average have lower incomes^[6]. People with long-standing illness or disability that affects their mobility and/or their ability to use public transport may be disproportionately affected by road pricing schemes if their travel choices become more restricted.
• Ethnicity - on average, Black and Minority Ethnic (BME) groups have lower incomes and evidence suggests that some BME groups may have a high dependence on the car. But there is a high degree of heterogeneity amongst different BME groups and research therefore needs to be conducted at the local level.
• Carers - being a carer for another person e.g. a disabled person may restrict the carer's own mobility choices.
• Dependence on income from benefits - some of the key benefits include Jobseekers Allowance, Income Support, Incapacity Benefit, Disability Living Allowance and Carer's Allowance.
• Students.

1.3.9 The impacts of road pricing schemes, both positive and negative, could vary considerably between and within these different groups, and they have been included simply as a guide. But it is not sufficient to limit distributional analysis to looking at different income groups. It is also important to look at the interactions between different socio-economic, socio-demographic and geographical characteristics, and to find out about the choices that are available and that can be made available to people through the package of complementary measures accompanying the scheme. The most effective way of doing this will be by conducting some social research. The remainder of this unit explains how you can do this.

1.3.10 In order to appraise options effectively, it will be necessary to demonstrate an evidence-based understanding of whether negative and positive impacts are likely to disproportionately affect groups who may already be vulnerable to social exclusion, how many of these people there are in and around the proposed scheme options, where they live in relation to the proposed options, where they currently travel to, what their other transport options are and/or might potentially be.

1.3.11 A core requirement is that proposers demonstrate that they have considered the impacts of schemes on the above groups and any other vulnerable groups identified by addressing the research questions outlined in the following section.

2. Gathering evidence

2.1 The research questions

2.1.1 To summarise, the objectives of gathering evidence on social and distributional impacts are to:

• Identify positive impacts and messages based on robust evidence.
• Identify potential problems with the distribution of impacts.
• Develop appropriate solutions (e.g. complementary measures) for scheme design and implementation.

2.1.2 The first stage of any social research process is the development of researchable questions (or research questions). Based on what is already known about the social and distributional impacts of road pricing, the Department has developed the following provisional research questions. Analysts will need to provide evidence that these have been addressed. It is important to note that these are research questions i.e. a list of the kinds of issues that research (e.g. household surveys, qualitative research, data mapping etc) will need to be designed to address. They cannot simply be lifted and placed in a questionnaire for members of the public as they stand (see paragraph 3.3.4 for further assistance that the Department will provide with developing actual questionnaire questions).

Travel behaviour

• What are the socio-demographic and socio-economic characteristics of those who travel by car and by other modes - at times and on routes relevant to the scheme? What journeys are they making (i.e. for what purposes are they travelling and from where/to)?
• Are there any differences in the way different social groups respond (in terms of travel behaviour) to a road pricing scheme? If so, what are the differences in behaviour? Which are the key socio-demographic and socio-economic factors that are associated with these differences? (the answer to this will need to be derived from the answers to some of the more specific questions below).
• More specifically, which, if any, socio-demographic and socio-economic characteristics are associated with making different types of behavioural choice, for example, changing mode, changing time of travel, route and/or destination, or trip suppression?
• Which trips do people feel are the most 'essential'? Which car trips do people feel are the most 'essential'? Are there any differences between different social groups in their assessment of which trips and which car trips are essential? Why are these trips/car trips seen as the most essential?

Travel options - choice and flexibility

• For car trips (particularly those that may be affected by the particular scheme), what options do people feel they have other than using the car? This could include not just public transport, walking and cycling, but other provisions and initiatives, such as community transport and taxicard schemes. To what extent are people aware of the available options? What are people's preferences in terms of alternatives to using the car? To what extent and in what ways do each of these factors vary according to different socio-economic and socio-demographic characteristics?
• Which car trips, if any, do people feel either they would not or could not make in a different way (i.e. at a different time, by a different mode, via a different route, to a different destination etc), and why? NB it is likely to be important to be able to distinguish between ability to pay, necessity of paying and willingness to pay. (Source: University of the West of England, Rapid Evidence Assessment: Understanding Distributional Impacts of Road Pricing, forthcoming).

'Vulnerable' groups

• Are there any 'vulnerable' groups (e.g. groups vulnerable to social exclusion; those with limited ability to pay; and those whose travel needs combine necessity of paying with limited ability to pay) that are likely to be affected by the scheme? What are the positive and negative impacts on these groups likely to be? What are the socio-economic and socio-demographic characteristics of 'vulnerable' groups in the particular local area?
• To what extent are vulnerable groups geographically concentrated (for example in deprived areas as defined by the Index of Multiple Deprivation)? Are there any vulnerable groups that are not geographically concentrated, i.e. that are spread across the area, which may be affected by the scheme (e.g. disabled people, carers)? If so, what are the socio-economic and/or socio-demographic characteristics of these groups? Where are the vulnerable groups (i.e. where do they live) in relation to the road pricing scheme and the key services, jobs and social networks that they need to access?
• What are the travel behaviour patterns, travel choices and flexibility of vulnerable groups (this involves analysis of the questions in the sections above)?
• For those on low incomes are there any wider implications of travelling by car either becoming more costly or being paid for in a different way? Will peoples' access to jobs and key services, e.g. doctors, hospitals, schools, food shopping and informal caring obligations, be affected and if so, how? What alternatives are people aware of and willing to use?

Complementary measures

• What are the most appropriate complementary measures to include in the scheme package? What are people's preferences (and why)? Analysts will need to think about further research questions, depending on the package of complementary measures they are considering.
• How can the travel needs of any vulnerable groups, including both those who may be car-dependent and those with a real or perceived limited ability to pay, best be met once the scheme is in place?
• It is important to avoid, as far as possible, the use of hypothetical questions, for example, 'what would you do if this road pricing scheme were introduced' or 'how would you make your journey to work/hospital/college etc if a £2/£3 etc road pricing was introduced'? Instead the objective should be to develop a survey that will give an accurate measure of people's current travel behaviour, the options they perceive are available to them and the flexibility they have to change behaviour etc. The data from the survey will underpin an analysis of the potential impacts of a road pricing scheme on different sub-groups of the population, and will provide evidence on which complementary measures would best suit people's needs.

2.1.3 The Department is building up an evidence base to answer these questions at a national level through social and economic research, and this guidance will be updated as new evidence becomes available. Scheme proposers will also need to address them at the local level in order to appraise the impacts of different options as well as to feed into scheme design. This means that areas considering road pricing schemes will need to conduct local data collection and research. There may also be additional questions pertinent to the social and distributional impacts of particular local schemes that s should include.

2.2 Data required

2.2.1 The next stage is to locate existing data and/or design a data collection exercise that will address the research questions outlined above. In order to assess the social and distributional impacts of schemes, it will be necessary to have the following information:

• Trip data - where are different types of people travelling from and to, and by what modes, and if possible and/or relevant to the scheme design, at what times?
• The socio-demographic and socio-economic characteristics of people making trips.
• Data relating to people's perceptions of their transport choices, essential trips and the wider implications of paying for road use differently through a road pricing scheme.

2.2.2 Local authorities may have already collected relevant data, for example for Accessibility Planning, and should make use of this data as far as possible. Existing national survey datasets, such as the National Travel Survey (NTS), Labour Force Survey (LFS), Family Resources Survey (FRS) and General Household Survey (GHS), can provide national-level findings, which may be useful for informing and weighting your local-level findings. However these national datasets will not provide locally specific data and results and therefore local data collection will be necessary. DfT (SRE) will aim to provide more specific further guidance on what national datasets can provide, but analysts are advised in the meantime to investigate this themselves.

2.2.3 The best ways to collect the kind of data listed at paragraph 2.2.1 is by the following methods:

• Household survey - using a random probability sample rather than quota sampling, to ensure that it is representative of households in the area. In order to gather data that will enable all the research questions outlined above to be answered, a face-to-face methodology is recommended.
• In addition, it may be necessary to supplement the survey (or quantitative) data collection with in-depth qualitative work with a sub-sample of those considered most vulnerable to negative social impacts.
• Separate public attitudes research may be necessary at some stage.

2.2.4 For an additional geographical dimension, the Index of Multiple Deprivation (IMD) can be used to identify the most (and least) deprived areas and this can be used, albeit as a fairly blunt instrument, in conjunction with data used for Accessibility Planning - e.g. public transport and local services data - to map the location of local areas that may need particular consideration in the design of road pricing schemes. Mapping is a core requirement for initial analyses. More information on this is provided below.

2.3 Mapping areas of multiple deprivation and other data

2.3.1 GIS maps are a useful way of incorporating both the geographical and the social factors that influence the social and distributional impacts into an easily interpretable whole.

2.3.2 Initial analyses to assess the social and distributional impacts of road pricing schemes, should include the formulation of a geographical picture of where those most likely to benefit from and to be at risk are in relation to the shape and boundaries of the scheme. Index of Multiple Deprivation (IMD) data is available publicly on the ONS Neighbourhood Statistics website^[7]. A series of local level maps can be built up to show the most deprived areas (for example, the first and second most deprived quintiles using IMD data - see figure 1 for national level example), the road network, the public transport network and the location of key services, such as hospitals, schools, major shopping centres and supermarkets, and major employment centres etc. Similar work may already have been conducted for Accessibility Planning. Analysts are encouraged to make best use of any such work alongside work done specifically for road pricing purposes.

2.3.3 In addition, local authorities may have access to more detailed data that is not publicly available. For example, they may already have data on where people who live in the most deprived areas travel to work, school etc, or they may even be able to obtain data from local hospitals, colleges, schools etc on where their service users travel from, particularly if LTAs have already been working jointly with other policy areas for Accessibility Planning.

2.3.4 Mapping National Statistics data can provide a useful overview of where people with particular characteristics (e.g. different income bands, IMD quintiles, people claiming particular benefits, and levels of car ownership) are concentrated. In conjunction with data on transport networks and levels of congestion, these maps can be used to make inferences about the likely potential impacts of the road pricing scheme. However, without actual data on people's travel behaviour and choices, these inferences will be based on generalised assumption rather than empirical evidence. A further weakness is that they will fail to take account of the hidden populations and individuals who may be more geographically dispersed, but are equally important in terms of considering the social and distributional impacts. We therefore recommend that analysts also conduct household surveys in addition, subject to the points outlined in paragraph 7.2 below on proportionality. Household surveys are covered in the next section.

Figure 1: Mapping of most deprived areas in England using IMD data

3. Household surveys

3.1.1 DfT's National Travel Survey (NTS) is an example of a household survey. Household surveys collect data about individual and household travel behaviour and characteristics such as household income, age, disability, ethnicity etc.

3.1.2 Household surveys are a core part of the detailed analysis required and should be used to collect the data required to assess the social and distributional impacts, which is outlined in the following sections. This data will then need to be analysed in order to answer the research questions outlined at paragraph 2.1.2 (see below for more information on data analysis).

3.2 Trip data

3.2.1 It will be necessary to collect the following data in relation to trip behaviour. For each trip:

• Start point
• Start time
• End point
• Arrival time
• If possible, route taken (DfT (SRE) will aim to pilot the feasibility of collecting route data)
• Mode
• Journey purpose
• If possible, distance travelled and trip chaining (DfT (SRE) will aim to pilot the feasibility of collecting these data)

3.2.2 People's trip data can be collected either through diaries, through face-to-face interviews or through a self-completion trip matrix. Diaries are a widely tried and tested method, with which many analysts will already be familiar. Further guidance on these options will be provided.

3.2.3 The trip data can form 'raw data' for modelling purposes. It can also be used to 'map' travel behaviour so that it is possible to see where at-risk groups are travelling in relation to the location and design of the pricing scheme, in order to inform decisions about scheme design and implementation. This can be done descriptively, but DfT (SRE) will test the possibility of using GIS maps to analyse trip behaviour as part of the household survey it is piloting. Further guidance will be provided on the basis of this pilot. Trip data can also be statistically analysed (for example, showing average trip rates, the spread of different trip purposes, travel at different times of the day etc) to show differences in travel behaviour for different social groups.

3.3 Household and individual characteristics

3.3.1 It will be necessary to develop a questionnaire that will be used to gather data about the households and individuals taking part in the survey. The questionnaire will need to include questions (or variables) which will be used to categorise people (these will create independent variables, e.g. age, income, ethnicity) and questions which will inform us about people's behaviours and choices (these will create dependent variables, e.g. usual mode to travel to work). Some variables can be used to categorise or to inform (e.g. household car ownership can be both an independent and a dependent variable). The categorising or independent variables are what allow for distributional analysis, because they allow differences between groups with a different characteristics to be compared. The informing or dependent variables allow us to identify and measure what the social impacts are and to identify appropriate solutions to potential problems.

3.3.2 These are variables which will be used to categorise:

a) Household questions

• Household structure - number of people, age and sex, and, if possible economic activity of household members
• Number of cars household has use of (if any)
• Household tenure
• Household income
• Whether anyone in household has a disability or long-standing health problem that affects their mobility

b) Individual questions

• Age and sex
• Economic activity - working (employed or self-employed) full-time; working part-time; in full-time education; retired; home duties; unemployed - seeking work; unemployed - not seeking work
• Qualifications
• Driving licence holding
• Whether the individual ever drives the car (this can also be used as an informing question)
• Whether has a disability or long-standing health problem that affects their mobility
• Ethnicity

3.3.3 In addition, the following informing questions will be needed (and there may be others that are required at the local level):

• Frequency of use of different modes
• Location of current employment
• Frequency of trips to: healthcare services, food shops, leisure/social activities, visiting friends/family
• Which do people consider are their most important/essential car trips?
• Which trips do people feel they have a choice about, in terms of mode, route, timing and destination?
• What are people's preferred alternatives to car travel?
• Reactions to any particular measures that are being considered as part of the complementary package

3.3.4 While there are well established techniques for undertaking social research via household surveys, there has been very little such work directly assessing the social and distributional impacts of road pricing. There are a lot of risks and pitfalls if these surveys are not well planned, designed, piloted and carried out. DfT have commissioned the development of a questionnaire that local authorities will be able to use 'off the shelf' when commissioning a face-to-face household survey to inform analysis of the social and distributional impacts of road pricing. The questionnaire is now available. A report of the piloting work undertaken to develop it will be available by early 2007. The current guidance note will be updated to reflect progress with the questionnaire development work. Local areas planning a face-to-face household survey are strongly advised to use or draw upon this questionnaire. If analysts already have or are developing a questionnaire, we would recommend that it undergoes a similar level of testing and development, in which case we would still expect that lessons learnt from DfT's piloting process will be of use.

4. Selecting an appropriate survey methodology

4.1.1 There are a range of methods that can be used to collect data on the social and distributional impacts of road pricing schemes. It is recommended that analysts select the methods most appropriate to the local scheme and area in question, but they will need to demonstrate that scheme proposals have been developed taking into account appropriately robust data on the social and distributional impacts outlined above. This means that analysts will need to demonstrate that a) social and distributional impacts have been taken into account in decision-making and scheme design and b) that the decisions and design are appropriately evidence-based. At the same time evidence gathering needs to be both proportional and fit-for-purpose (see paragraph 7.2 below). The core requirements are data mapping and/or secondary analysis for initial analyses and a household survey for more detailed analyses.

4.1.2 There are three main ways of collecting data for household surveys: face-to-face, by telephone and by post. Each has pros and cons, but the two most tried and tested for collecting data on travel behaviour and attitudes are face-to-face and postal data collection.

4.1.3 The NTS uses a methodology involving face-to-face interviews and seven-day travel diaries for all household members. This is the most comprehensive approach to data collection about travel behaviour available. Face-to-face methods are more expensive than postal or telephone methods, but are more likely to generate data that can be used to generalise to the local population - because there is likely to be less bias in the achieved sample and because it is possible to generate more detailed information. However, work done as part of the development of the toolkit for Local Travel Surveys has revealed that there is only a small number of contractors available with an appropriately trained and skilled field force of interviewers.

4.1.4 DfT recently published a toolkit for Local Travel Surveys (LTS) which provides detailed guidance on how to do a good postal survey. However, there are drawbacks to this methodology for the purposes of assessing the social and distributional impacts of road pricing schemes. Analysts will need to carefully consider whether a postal survey - which is likely to generate a low response rate and is likely to be limited in terms of the amount and depth of information that can be collected (see below) - will meet their needs, and will need to provide justification for their decision.

4.1.5 The Department's current guidance for LTS does not recommend the use of telephone surveys, largely due to the lack of a good sample source. DfT will aim to investigate the possibility of the use of telephone surveys to gather questionnaire data in combination with postal self-completion diaries for the purposes of assessing the social and distributional impacts of road pricing schemes.

4.1.6 At this stage we would recommend a face-to-face methodology. Besides this, there are a number of other factors to consider when selecting a methodology.

4.2 Response rates and bias in the achieved sample

4.2.1 The achieved sample is the number of people who actually take part in the survey. Expressing this as a proportion of the number of people who were actually invited (and, strictly speaking, eligible) to take part gives the response rate. It is important to be clear before starting fieldwork what the definition of a responding case is. For example, where respondents are asked to complete a questionnaire and a diary, fully responding should be defined as completing both elements. Likewise, if a household survey involves every member of a household, fully responding should be defined as every household member completing the questionnaire and diary.

4.2.2 Another issue to consider is sample bias. Achieving a higher response rate can reduce sample bias, but not necessarily. Some sampling frames may have inherent sampling biases. For a number of methodological reasons, including the under-representation of some groups, the Electoral Register is not usually the best source for sampling.

4.2.3 In general, face-to-face surveys tend to achieve higher response rates than postal surveys, even when incentives such as prize draws and vouchers are provided, and are probably less likely to introduce bias into the achieved sample, as long as they are conducted to an acceptable standard.

4.3 Sampling

4.3.1 The surest way of achieving a statistically robust sample that is free of bias is to use random probability sampling. This involves selecting potential respondents in accordance with a strict design based on probability, where every member of the population has a known (and non-zero) chance of being selected.

4.3.2 The best source for selecting a household sample is the Small User version of the Royal Mail Postcode Address File (PAF). The main advantage of the PAF is that it is the most comprehensive list of addresses in the UK and consequently is less subject to the bias that affects alternatives such as the Electoral Register. Because the PAF is a list of addresses rather than individuals, there may be a need for further sampling within the household.

4.3.3 The likelihood of producing a representative sample will be increased by stratifying the sample, using a variable (or variables) relevant to the research questions. The LTS advises stratifying on car ownership using out-put area data from the 2001 Census. You may also wish to stratify by other variables such as IMD rating, proportion of population from BME (Black and Minority Ethnic) backgrounds etc.

4.3.4 The LTS toolkit includes further guidance on sampling, which can be applied to various data collection techniques. Drawing a stratified random sample from the PAF can be complicated and may be beyond the competence of some market research companies. It is probably advisable to use a specialist sampling contractor.

4.3.5 It is recognised that sampling is complicated and we will provide further guidance in due course. As an early indication of overall sample sizes, we would estimate that an achieved sample of about 1500 cases would be sufficient for most areas, but precise sample size will depend on the number of sub-groups needed for analysis, the size of the area and the degree of variance expected on key variables.

4.4 Data collection

4.4.1 Response bias can introduce another source of bias into the survey. For example, if interviewers always call during the day, response is likely to be biased towards people who are at home during the day. This means that for face-to-face surveys, interviewers need to make several calls at different times and on different days. We would recommend a minimum of four calls before a household where the interviewer has failed to make contact with an occupant can be recorded as a 'non-contact'. This should help to reduce bias in the sample.

4.4.2 This is not an issue for postal surveys. On the other hand postal surveys are less accessible to people who have difficulties reading and writing or who may be put off by a written format - these may be some of the people who are most vulnerable to the negative impacts of road pricing schemes. This may introduce a damaging source of bias into the survey.

4.4.3 Ensuring that hard-to-reach groups are properly included in research is often a challenge when conducting social research with members of the public. It is necessary to build in plans for ensuring that people are given a full opportunity to participate by overcoming any barriers to participation. This might, for example, mean producing letters and fieldwork documents in languages other than English and in large print and Braille formats.

4.4.4 The LTS recommends a one-day travel diary for a postal survey. If a larger number of days is required, it is advisable to adopt a different method of data collection, probably a face-to-face survey. The rapport and support that a face-to-face methodology enables is more able to deal with this issue of under-reporting. People are far more likely to fill in their travel diaries accurately if a) an interviewer has explained in person to them how to fill it in properly b) an interviewer has had the opportunity to build up a rapport with the respondent. DfT SRE are investigating alternatives to the diary methodology and this guidance will be updated accordingly.

4.4.5 Questionnaires administered by interviewers can include more questions as well as more detailed and sophisticated questions. There is a limit to the level of detail that you can include in a postal survey because if it is too complicated it will either put people off filling it in (reducing the response rate) or people are more likely to fill it in inaccurately.

4.4.6 Proposers should produce a technical report explaining the methodology, so the Department and others are able to judge the robustness of the evidence.

5. Using and analysing the survey data

5.1.1 The objective of gathering the data described above is to enable scheme proposers to provide answers to the questions listed at paragraph 2.1.2. These answers need to be brought out in the analysis of the data, which will typically involve data tables and charts plus commentary on the key points. Data tables will mainly be cross-tabulations, but in some cases it may be advisable to conduct more sophisticated multi-variate analysis. Commentary needs to draw out the key points and needs to indicate levels of significance of findings. Significance tests can only reliably be performed on data that has been gathered on the basis of random probability sampling.

5.2 Analysing trip data

5.2.1 The trip data will need to be analysed by the various categorising or independent variables collected from the questionnaire (income group, age, household size, car ownership etc). This will provide evidence about current travel behaviour and the differences in behaviour between people with different socio-economic and socio-demographic characteristics. This kind of analysis is a core element of measuring the distributional impacts.

5.2.2 Examples of the kinds of analysis that will need to be performed, to show differences between different groups of people include:

• Average number of trips
• Journey purposes
• Use of different modes
• Journey start times
• Trip distances
• Destinations
• Trip chaining
• Car sharing
• ...etc.

5.2.3 This kind of analysis is likely to require some substantial manipulation of the data.

5.3 5.3 Mapping trip data

5.3.1 The trip data, if geo-coded, can also be mapped to provide a visual representation of where, when and for what purposes people with different characteristics, for example, those living in deprived areas or those within different income bands, are travelling from and to. For example, adding work trips by those in the lowest income households to the maps described in section 2.3 above will give a more accurate geographical picture of the commuting travel patterns of this group in relation to the proposed scheme. Similar analyses could be conducted in relation to all the key services that people need to access. DfT's Accessibility Planning policy defines these key services as access to work, education, healthy food shops, and healthcare, but it may also be appropriate to add social networks and informal carers. DfT intends to use the data collected from its household survey pilot to test the mapping of trip behaviour and further guidance will be provided.

5.4 Analysing questionnaire data

5.4.1 Depending on which method of data collection was used, there should be a substantial amount that can be learnt from analysing the responses to the questionnaires. Differences and similarities in the responses given by people with different characteristics - for example, in people's preferences for complementary measures, in what they view as 'essential' trips, in the travel choices they feel are available to them - can tell us a lot about the potential distributional impacts of a scheme, as well as the most appropriate complementary measures. (See section 6 on using the evidence).

5.4.2 The Department anticipates that the data generated from its piloting of a face-to-face household questionnaire will inform more detailed guidance on analysis and reporting during Autumn 2006.

5.4.3 For further advice, two guidance notes on Social Surveys (on survey design and data analysis and reporting) will shortly be available from DfT (SRE).

6. Using qualitative research

6.1.1 As outlined in paragraph 6.2 below, the ideal approach would be to undertake qualitative research as well as quantitative analysis as the two methods are mutually reinforcing in providing a detailed understanding of social and distributional impacts. Undertaking qualitative research is not a core requirement of the initial or the more detailed analysis, but should be considered as an option, particularly for more complex and/or innovative schemes and packages, and areas/schemes where the social and distributional may be particularly significant.

6.1.2 Qualitative social research is a scientific approach to understanding social issues using in-depth accounts of people's views and experiences. Typical qualitative research methods include focus groups and depth (or in-depth) interviews. Rigorously analysed and well reported qualitative research can provide a clear and structured account of how issues are experienced by different groups within the population. Qualitative research is also useful for explaining experiences, views and perceptions.

6.1.3 Qualitative research may be necessary to provide a proper understanding of people's motivations, their options, their decision-making processes etc. These are likely to be complex issues that a survey will not be able to tackle properly.

6.1.4 For this reason, it is often helpful to use qualitative research methods alongside survey methods in order to achieve a greater depth of understanding of the issues being researched. Most of the research questions outlined at paragraph 2.1.2 can be tackled using survey methods, particularly the more detailed questioning allowed by face-to-face interviews, but some could very usefully be explored using qualitative methods. Examples of the questions that analysts could explore using qualitative methods include:

• Which trips do people feel are the most 'essential'? Which car trips do people feel are the most 'essential'? Are there any differences between different social groups in their assessment of which trips and which car trips are essential? Why are these trips/car trips seen as the most essential?

• For car trips (particularly those that may be affected by the particular scheme), what options do people feel they have other than using the car? This could include not just public transport, walking and cycling, but other provisions and initiatives, such as community transport and taxicard schemes. To what extent are people aware of the available options? What are people's preferences in terms of alternatives to using the car and why? To what extent and in what ways do each of these factors vary according to different socio-economic and socio-demographic characteristics?

• Which car trips, if any, do people feel either they would not or could not make in a different way (i.e. at a different time, by a different mode, via a different route, to a different destination etc), and why? NB it is likely to be important to be able to distinguish between ability to pay, necessity of paying and willingness to pay.

• Are there any 'vulnerable' groups (e.g. groups vulnerable to social exclusion; those with limited ability to pay; and those whose travel needs combine necessity of paying with limited ability to pay) that are likely to be affected by the scheme? What are the positive and negative impacts on these groups likely to be? What are the socio-economic and socio-demographic characteristics of 'vulnerable' groups in the particular local area?

• What are the travel behaviour patterns, travel choices and flexibility of vulnerable groups (this involves analysis of the questions in the sections above)?

• For those on low incomes, are there any wider implications of travelling by car either becoming more costly or being paid for in a different way? Will peoples' access to jobs and key services, e.g. doctors, hospitals, schools, food shopping and informal caring obligations, be affected and if so, how and why? What alternatives are people aware of and willing to use?

• What are the most appropriate complementary measures to include in the scheme package? What are people's preferences and why? Analysts will need to think about further research questions, depending on the package of complementary measures they are considering.

• How can the travel needs of any vulnerable groups, including both those who may be car-dependent and those with a real or perceived limited ability to pay, best be met once the scheme is in place?

6.1.5 If these questions are to be addressed through the survey approach, then suitable options for response categories for closed questions need to be developed. Open questions should be kept to an absolute minimum in any survey as they are difficult to analyse. Even for closed questioning, the kinds of issues described in paragraph 6.1.3 above would only work in a face-to-face interview, as they are likely to be too complex for a postal survey.

6.1.6 Qualitative research can also include discussion with local representative groups e.g. local groups representing disabled people, older people or people from ethnic minority groups. Consulting these groups does not replace the need to understand the views and experiences from people themselves, as it cannot be assumed that they will fully represent people's views, but it can provide a useful source of additional data as well as useful input into research design.

6.1.7 A robust approach to sampling and to data analysis are just as important in qualitative research as they are for surveys. The sampling and research design will need to allow for comparison between the views and experiences of different groups of people if it is to tell us anything about the distributional impacts of a scheme. We would recommend a purposive sampling approach and a detailed thematic analysis (for example using a matrix methodology). Contact DfT (SRE) for a guidance note on Qualitative Research.

7. Using the evidence

7.1 Interpreting research findings

7.1.1 The final stage of the process will be to ensure that the findings from the social research appropriately inform scheme design and implementation. In practice, this means that the analysis will need to be interpreted to inform sensible decision-making about factors such as the physical shape and design of the scheme, times and methods of payment, and the provision of suitable complementary measures. Some examples of how the analysis can be used to inform decisions and design are given below.

7.1.2 If congestion modelling indicates that the most efficient place for a cordon slices through an area of high deprivation which will involve frequent crossings of the boundary for residents to access jobs and schools, then this could suggest the need to either reconsider the boundary or to build in additional complementary measures to the scheme design. The option that is selected should be based on people's responses to the questionnaire and/or qualitative research.

7.1.3 Similarly, if the analysis shows that low income residents from outlying areas travel to work in the centre or the opposite side of town, then it would be sensible to ensure that their travel needs are properly catered for, based on evidence about their needs and choices rather than guesswork and assumption.

7.1.4 Dealing with analysis that shows that there are widely-dispersed groups of people who are heavily reliant on car travel but have restricted transport alternatives may be more challenging. An example of such a group may be people with a disability or long-standing illness that limits their ability to use public transport. The most immediate solution is to think about exemptions. But we know from the Family Resources Survey that 20% of the adult population has a long-standing illness or disability that affects their mobility or their ability to use public transport. This is a substantial proportion in terms of exemption, and much larger than the estimated 2.5 million Blue Badge holders, indicating that analysts need to be careful about making assumptions about solutions unless they are based on robust evidence. It may be more helpful to look at what people have said they would like their options to be before making decisions. Other options could include DRT or taxi-vouchers.

7.1.5 Analysis may indicate that some of the least well off - particularly those without cars - will experience substantial benefits as a result of the scheme. These findings also need to be demonstrated in the business case proposal.

7.1.6 The Department intends to provide further guidance on the interpretation and use of the analysis based on the data and analysis generated from its piloting of a face-to-face household questionnaire.

7.2 Proportionality and minimum requirements

7.2.1 Analysis of the social and distributional impacts of road pricing schemes will be a vital and necessary element of business case submissions. At the same time, the Department is conscious of the need for proportionality in the amount of resource that is allocated to this task. Proportionality needs to be judged on the basis of the anticipated scale of the social and distributional impacts, as well as the anticipated need for robust evidence for political debate and public acceptability. Various factors are likely to influence this:

• Nature of the local area, including socio-economic and socio-demographic characteristics of the population - the social and distributional impacts are likely to be more important in less well off areas; on the other hand there may be vocal interest groups articulating the 'unfairness' argument in some of the better-off areas.

• Nature of the proposed scheme - this could include the scale of the scheme, although the scale and location of links where pricing applies are likely to be more important indicators than the overall scheme budget. A clumsy inexpensive scheme may have more negative social and distributional impacts than a carefully-designed more costly scheme.

7.2.2 The core requirement for most schemes will be initial analysis based on secondary analysis of existing data, including the production of GIS maps, followed by more detailed analysis involving a household survey. If feasible, we would strongly recommend a survey involving face-to-face interviews, although telephone or postal surveys may suffice in areas where limited impacts are anticipated. But areas will need to justify this by producing evidence as to why they anticipate that the impacts will be limited. For example, in doing this they will need to take account of overall levels of social and economic disadvantage, not simply how many deprived Index of Multiple Deprivation (IMD) areas there are, in recognition of the fact that deprivation is sometimes dispersed throughout an area rather than concentrated. Equally, it is not sufficient to assume that lower than average levels of car ownership mean that, for instance, low income households will not experience impacts and therefore that no analysis is necessary. We know from the NTS that, while car ownership levels are much lower in the lowest income groups, those who do have access to a car are just as reliant on it as better off groups - the average figure therefore masks important differences that should not be overlooked.

7.2.3 In addition, some areas, perhaps those proposing more complex schemes, will want to conduct some qualitative research to gain a better understanding of issues such as choice, flexibility and preferred alternatives to car travel, possibly concentrating on the more at-risk groups, although qualitative research is not a core requirement.

7.2.4 In planning and designing social research, analysts should bear in mind that there is likely to be a need to return to the data at a later date for further analysis and insight as local schemes develop and take shape. Research projects and programmes should be designed with potential longer term research questions in mind.

7.3 Reporting format for supporting analyses on social and distributional impacts

7.3.1 The social research analyses will need to be presented in the format of a 'Supporting Statement on Social and Distributional Impacts'. This will form part of the Distribution and Equity Supporting Analysis (see TAG Unit 3.12.3 for more detail about the Supporting Analysis), and will need to include a written statement of up to 4 pages in length outlining the following:

• A brief summary of the package of social research undertaken (including any social surveys, qualitative research and mapping) and any planned research.
• A summary of key findings from the social research analyses (e.g. what are the key social and distributional impacts - beneficial and non beneficial, if these can be defined - that the social research indicates that the scheme is likely to have? What potential problems have been identified? Which complementary measures are best suited for the road pricing scheme?)
• A summary of how the analyses have been used to inform the scheme design (including design of scheme cordons/boundaries etc, any planned exemptions, planned public transport provision or other complementary strategies) i.e. what solutions have been developed on the basis of the evidence and why?
• A final summary outlining the overall strategy for dealing with the potentially non beneficial social and distributional impacts of the scheme and how impacts will be monitored before, during and after implementation to ensure they are successfully managed.

7.3.2 It will be necessary to attach technical annexes including outputs from the research such as maps and social survey/qualitative research report summaries (including details of the research methodology, such as sampling methodology, recruitment of respondents, research instruments e.g. questionnaires and topic guides, and details of how the analysis was conducted).

7.4 Ongoing use of the social research data

7.4.1 Linking back to public acceptability, the evidence on the social and distributional impacts that is gathered and presented for the purposes of option selection and scheme design will also be useful for marketing and communications purposes. Firstly, because areas will have some robust evidence on the positive impacts for vulnerable groups. Secondly, because areas will have evidence that they have analysed the negative impacts and amended scheme design accordingly.

7.4.2 The research and analysis described above will need to feed into the Supporting Statement for option appraisal along with modelling and other sources. But it will also provide a wealth of evidence for subsequent ongoing work on detailed scheme design. If it is well designed and conducted it will also be a valuable source for wider transport planning, LTPs and accessibility planning and it is advisable to design the research with these potential further uses in mind. It is therefore important that local authority officers responsible for TIF work alongside those responsible for LTPs and Accessibility Planning.

8. Further Information

The following documents provide information that follows on directly from the key topics covered in this TAG Unit.

9. References

1: Green E and Stone V (2004) Public Attitudes to Road Pricing in the UK: a Qualitative Study. DfT, London. Available on the DfT website at www.dft.gov.uk/pgr/statistics/datatablespublications/trsnstatsatt/earlierreports/attitudestoroadpricing.
2: DfT (2004) Feasibility Study of Road Pricing in the UK. DfT, London. See Terms of Reference pp.7.
3: Bonsall, P, Kelly, C. (2005) 'Road User Charging and Social Exclusion: The Impact of Congestion Charges on At-Risk Groups', Transport Policy, 12, 406-18.
4: Social Exclusion Unit (2003) Making the Connections: Final Report on Transport and Social Exclusion.
5: See for example Institute for Fiscal Studies (2006) Poverty and Inequality in Britain. According to data from the Family Resources Survey 2004/5 only single parent households have a lower weekly income than pensioner households (the figures for mean BHC were £283 for lone parents, £334 for single pensioners, £367 for pensioner couples, £423 for couples with children, £447 for singles without children, £531 for couples without children and £427 for overall)..
6: See for example Households Below Average Income, which shows that disabled adults aged 25 to retirement are twice as likely to live in low income households as their non-disabled counterparts: 30% compared with 15%.
7: www.neighbourhood.statistics.gov.uk/dissemination/.
8: For further information on Accessibility Planning, see DfT's Accessibility Planning Guidance at www.dft.gov.uk/pgr/regional/ltp/accessibility/.

10. Document Provenance

This Transport Analysis Guidance (TAG) Unit revises guidance published for consultation in July, 2006.

Technical queries and comments on this TAG Unit should be referred to:

Integrated Transport Economic Appraisal (ITEA) Division
Department for Transport
Zone 3/08 Great Minster House
76 Marsham Street
London, SW1P 4DR
E-mail: itea@dft.gsi.gov.uk
Tel: 020 7944 6176
Fax: 020 7944 2198