Active travel and physical activity

The study hypothesised that there would be a change in levels of active travel (walking and cycling) as a result of the intervention of free bus fares for young people (see Chapter 4) which may lead to a change in physical activity. This section examines whether we can estimate the benefits from a change in physical activity as a result of the scheme.

Methodology

Chapter 4 of this study used data from the LATS and LTDS to determine the current levels of walking and cycling in London following the introduction of free bus fares. As with the previous outcomes we determined a counterfactual case using a comparison with the walking and cycling levels in the 25–59 age group over the same period. The research identified that there was no significant change

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in the total distance walked following the introduction of the free bus fares (Chapter 4). The study identified a small decline in the amount of cycling that the age group 12–17 were undertaking.

Combined together (walking and cycling changes) there was no significant change in the amount of physical activity for the 12–17 year old age group as a result of the policy, so no monetary value is included in the CBA framework.

One of the key methodologies that are available to determine the monetary value to society from changes in physical activity levels is the WHO (128) HEAT methodology. In the documentation it states that:

“HEAT should not be applied to populations of children, very young adults or older people since the available evidence was not sufficient to derive a relative risk for these age groups”

(p20).

Given this finding in HEAT’s application, it should be noted that more research is required to allow an assessment of the monetary benefit to society of increases in walking and cycling for children as a result of an intervention. The current methodology as applied to adults can be found at WHO (128) and DfT (129).

9.7 Crime

The study hypothesised that there would be a change in assaults as a result of the intervention [see chapter 6]. This section uses data from TfL and Chapter 6 to estimate the benefits from changes in assaults.

Methodology

Evidence from TfL indicates that crime rates on London’s transport network have declined over the period in which the intervention was implemented (see Table 9.14), despite increasing numbers of bus trips. It has not been possible to split this data into crime type or to determine a counterfactual from this data. For example, it has not been possible to identify the age of the crime victims and so compare 12-17 year olds with 25-59 year olds.

Table 9.14 Volumes of crime on the London transport network Total Crime

(notifiable)

2005/06 2006/07 2007/08 2008/09 2009/10

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Bus 39,142 38,482 33,125 27,170 24,976

Tram 428 418 402 411 403

LU/DLR 18,987 18,818 16,609 15,351 14,825

London Overground

490 553 447 535 517

Source: Transport for London (130)

Analysis was also carried out within the project using the Hospital Episodes Statistics (HES) data to determine whether there was a change in assaults associated with the intervention. It was hypothesized that an increase in bus trips could lead to an increase in assaults. The HES data was analysed using the assault rates in the same period to adults (25-59 years old) in London as the basis for the counterfactual. As shown in Table 9.15 this analysis resulted in the identification of an increase in assaults per year. However, the impact pathway is complex and it is difficult to prove causality (see Chapter 6). For this reason, this increase in assaults has only been included in the CBA framework as a sensitivity test.

Table 9.15 Counterfactual 2a: Expected assault rates based on a statistical analysis of what happened in the same period to adults in the 25-59 age group in London

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The best estimate of the social costs of assaults on buses in England is provided by Home Office

‘social costs of crime’ evidence, adapted to public transport for DfT (131). A weighted average value of £13,592 per assault on buses and trams has been used, at 2009/10 prices. For the derivation see Table 9.16.

Table 9.16 Derivation of a weighted average value per assault

Crime type Number

Estimated unit cost, £ (2006/7 prices) Costs of

113 Sources: DfT (131); HM Treasury (132).

Note: number of incidents includes multipliers for under-reporting.

A proposal early in the study was to use the value for Serious Injury from DfT advice (123), noting that the definition of Serious Injury by DfT (123) is: “Serious injury: records casualties who require hospital treatment and have lasting injuries, but who do not die within the recording period for a fatality”. Using the serious injury value, it was found that results would be an order of magnitude higher (>10 times higher), however the rationale for the assaults value is much stronger because it is much more specific to the outcome that has been measured. Therefore the results including the assaults value (Table 9.16) only are provided as a sensitivity test.

Calculations

Using the monetary values in Table 9.16 and the change in assaults in Table 9.15 the results for inclusion in the sensitivity test are provided in Table 9.17. It indicates that the change in benefit to society is of the order of -£1.9m (mean) within a 95% confidence interval of -£1.7m and -£2.1m.

Table 9.17 Sensitivity test: inclusion of social cost of assaults

Crime type Change in

assaults (Table 9.11)

Estimated unit cost, £ (2009/10 prices)

Benefit of change in assaults, £ (2009/10 prices)

Mean 140 13,592 -1,902,900

CI minimum 122 13,592 -1,658,241

CI maximum 157 13,592 -2,133,966

In summary, the project explored the inclusion of changes in assaults as a result of the intervention.

Unlike road safety, the major impact pathway is complex for crime, and it is difficult to demonstrate causality, as data were not directly linked to bus use, but admission to hospital. For this reason, the increase in crime observed after the intervention was introduced has been included as a sensitivity test.

114 9.8 Revenue

One of the consequences of the intervention is that those 12 – 17 year olds who would have

previously paid half fare in 2009 are now travelling for free. This reduces the revenue that would be received by TfL. The methodology used to calculate the change in revenue is described next.

Methodology

In the ‘do something’ scenario TfL will receive a revenue of £0 as those in the age group 12-17 who previously paid to travel by bus now are exempt from paying. In order to determine the level of revenue in the ‘do-nothing’ scenario two counterfactuals were tested based on the results from the user benefit calculations.^o

 Counterfactual 2a: Expected bus travel based on a statistical analysis of what happened in the same period to adults in the 25 – 59 age groups in London (Source: Chapter 3)

 Counterfactual 2c: Expected bus travel based on demand elasticities and trip generation factor (Source: Balcombe et al (72))

The calculations indicate that in the absence of the free fare, approximately 225m journeys (netting

£113m) would have been made by the age group 12-17 year olds within a 95% confidence interval of

£104m - £116m. Using counterfactual 2c this number is reduced to a loss of £99m.

Table 9.18 Revenue calculations

Expected trips in the counterfactual (A)

Child Half Fare (B)

Revenue (A*B)

Counterfactual 2a 225,426,555 (207,193,525, 232,056,748)

0.50 Mean £113m

CI Minimum £104m CI Maximum £116m

o For details on the calculation of the number of trips see User Benefit Section.

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Counterfactual 2c 197,997,600 0.50 £99m

Calculations

The results of this analysis are provided in Table 9.18. Using counterfactual 2a it is indicated that had the intervention not been in place that revenue of the order of £113m (within a 95% confidence interval of £104m and £116m) could have been realised in 2009.

Note that the results below on Bus Operating Costs include a sensitivity test which incorporates both Bus Operating Cost and Revenue changes.