NOU 2012: 16

Cost-Benefit Analysis

To table of content

4 Real price adjustment

4.1 Introduction

From the terms of reference of the Committee:

The cost-benefit analysis guide of the Ministry of Finance does not explicitly address the fact that analysis parameters may change over time, for example that the value of time and time savings may be assumed to increase in line with real wage growth in the economy. Correspondingly, the willingness to pay for environmental goods may change over time, whilst technological progress may change future costs. This type of considerations may have a major impact of the assessment of costs and benefits in long-term projects, like for example infrastructure investments within the transportation sector. The Expert Committee shall examine whether and, if applicable, how changes in parameter values over time may be included in the cost-benefit calculations.

In order to compare the current and future benefits and costs of a project, assumptions have to be made as to how the various calculation prices will develop during the analysis period. However, it is challenging to estimate how future prices will change relative to each other. A common simplification when calculating the economic benefits of a project is to keep all prices unchanged throughout the analysis period in real terms, i.e. it is assumed that all nominal prices increase at the same rate (in line with the increase in the retail price index). If the price of a good or a service on the benefit side of a project is expected to increase relative to the prices of other goods and services, the project will seem less profitable than is actually the case unless this is taken into consideration in the analysis. In the present Chapter, we will examine whether the assumption of constant calculation prices in real terms fails to reflect expected developments in some cases, thus implying that a change in real prices should be assumed for certain goods in the cost-benefit analysis. The adjustment in calculation prices motivated by an expectation that these will increase at a different rate than general inflation as measured by the retail price index is referred to as real price adjustment.

In Chapter 4.2, we explore the issue in more detail, before looking at the theoretical relationship between price growth and real wage growth in 4.3. Chapter 4.4 discusses real price adjustment of the value of time savings, which is often a key benefit component in cost-benefit analysis in the transport sector. Chapter 4.5 discusses price developments over time for environmental goods in general, whilst carbon price paths are examined specifically in Chapter 9. The valuation of health goods is primarily discussed in Chapter 10, but real price adjustment of the value of statistical lives is addressed in the present Chapter. Chapters 4.6 and 4.7 present the assessment and recommendations of the Committee.

4.2 Background and scope of discussion

Costs and benefits (in monetary values) arising at different points in time need to be modified such as to become comparable in a cost-benefit analysis. The most common method for making such a comparison is to convert the annual cost and benefit elements into a net present value. The net present value is the value today of the aggregate benefits and costs arising at various times during the project period. A net present value calculation discounts all future amounts by applying a discount rate.

It is currently common practice to assume constant real prices for the costs and benefits of a project throughout the project period. The prices used are most often those applicable in the base year or prices adjusted to the expected price level of the commencement year of the project. The net present value of the project is then determined by applying the real interest rate (the nominal interest rate less the expected percentage increase in the retail price index) as the discount rate. The choice of discount rate and its time profile are discussed in more detail in Chapter 5.

Keeping real prices constant throughout the project period is based on the assumption that all costs and benefits will undergo the same price developments as the standardised basket of consumption goods on which the retail price index is based. However, nominal price developments for some project-specific costs and benefits will deviate from the said index.

In a project context, this can be stated as follows: If a cost or benefit is valued at P0 in the base year, the relevant valuation in any given period t is determined as Pt=P0(1+p)t, where p is expected real price growth (price growth in excess of the growth rate of the retail price index) over the period. Such valuation will exceed the base year price if the nominal value is expected to increase at a higher rate than the retail price index, and vice versa. Making no real price adjustment means adopting an implicit assumption to the effect that every p=0, i.e. that the growth rate of the nominal price level of the various goods and services is identical to the growth rate of the retail price index.

4.2.1 Real price growth – general observations

Developments in the real prices and values of goods and services are influenced by a number of factors.

The prices of goods and services for which well-functioning markets, and thus market prices, exist will be determined by supply and demand. Reduced supply of a good will usually result in price increases until demand has adapted to the lower supply. Higher demand for a good will normally also result in higher prices for such good.1 In a small, open economy like Norway, nominal price changes for many goods will nevertheless be determined by the world market, adjusted for changes in the nominal exchange rate.

Changes in productivity or efficiency in the production of a service or a good may cause supply changes, and thus price changes. Classical examples are high-technology products like for example computers, for which major productivity improvements have been witnessed internationally, thus leading to lower prices in Norway as well. Such cost and price changes will spread through the input and product markets to other producers, thus also affecting other prices. Car prices, for example, depend on the prices of electronics, ironware, electricity, etc.

Chart 4.1 illustrates nominal price developments for different types of goods between 1979 and 2011. Retail price index developments are also indicated. Chart 4.2 illustrates real price developments (nominal price growth less inflation as measured by the retail price index) for these types of goods, and Table 4.1 specifies annual percentage growth in these and certain other real prices. We note that growth in real wages (real wage cost per hour for employers, but also the purchasing power of employees) has been 1.9 percent in the relevant period. The real price of clothing has declined by 3.6 percent, which is largely explained by the “China effect” on international prices and has very little to do with Norwegian wage cost growth (see for example Chapter 7 of Economic Analyses, 1/2011 (Statistics Norway, 2011). The real price of services relating to leisure and culture, on the other hand, has increased by 1.7 percent, which can largely be explained by domestic wage cost increases. The reduction in the real price of telecommunications services (5.8 percent) is principally caused by new technology and increased competition as the result of deregulation. We further note that the real price of foodstuffs has declined by 0.2 percent on average over the period, whilst electricity and heating oil prices have increased by an annual average of 2.4 percent. We also note from the table that annual inflation as measured by the retail price index was about 4.1 percent over the same period. Although historical figures do not necessarily say anything about the future, there is reason to believe that future price developments for different goods and services will continue to be differentiated.

Table 4.1 Real prices, average annual percentage increase, 1979 - 2011.

Foodstuffs

-0.21%

Clothing

-3.56%

Estimated rent

0.33%

Electricity, heating oils and other fuels

2.41%

Transportation services

1.53%

Telecommunications services

-5.79%

Services relating to leisure and culture

1.69%

Insurance

1.33%

Wage costs per man-hour

1.92%

-

-

Retail price index

4.09%

Source Statistics Norway

Figure 4.1 Nominal price developments for selected goods. Prices are inclusive of value added tax and other taxes. 1979 = 100

Figure 4.1 Nominal price developments for selected goods. Prices are inclusive of value added tax and other taxes. 1979 = 100

Source Statistics Norway

Figure 4.2 Real price developments for selected goods (nominal price growth less inflation as measured by RPI growth). 1979 = 100

Figure 4.2 Real price developments for selected goods (nominal price growth less inflation as measured by RPI growth). 1979 = 100

Source Statistics Norway

4.2.2 The issues examined by the Committee

A cost-benefit analysis will typically include a large number of prices, and real price adjustment may be challenging for a majority of these. A sensible approach may be to only consider real price adjustment of prices for which there are sound reasons to expect nominal growth to deviate from general inflation.

The Committee has chosen to focus on the examples mentioned in the terms of references of prices that may be subjected to real price adjustment; the value of time and environmental goods. There is, as will be discussed later in this Chapter, good reason to assume that the value of time will be influenced by real wage growth (which is normally positive, cf. Chart 4.2 and Table 4.1). Chapter 4.5 discusses factors that may suggest that the willingness to pay for certain environmental goods will increase at a rate in excess of general inflation.

In comparison, the British cost-benefit analysis guide, published by Her Majesty’s Treasury; the “Green Book” (HM Treasury, 2003), names the following examples of goods that should be subjected to real price adjustment:

  • High-technology products, the prices of which can be expected to decline in real terms.

  • Fuel prices, which may be influenced by resource scarcity.

  • Wages, if productivity growth implies that wage growth can be expected to outpace general inflation.

High-technology products are very hard to define precisely. Correspondingly, good long-term fuel price estimates are not readily available. The Committee has chosen not to address these two groups in further detail.

4.3 Theory – real wage growth and price growth

The price of labour – the real wage – differs from other prices inasmuch as it is, in addition to the price of an input, also an indicator of purchasing power. A “rich country” manages to maintain high average real wages over time.

The basis for real wage growth in an economy is capital accumulation and productivity improvements.2 More capital makes labour more productive on the margin, which results in higher equilibrium real wages. By productivity growth is meant growth in output per unit of input. Countries with high labour productivity growth normally experience high real wage growth. Chart 4.2 shows that real wages in Norway have increased by an average of about 1.9 percent annually over the period 1979–2011. See also Box 4.1.

Textbox 4.1 Productivity growth

A distinction is usually made between two productivity concepts. The most commonly used is single-factor productivity, which tends to be measured by developments in gross output per factor, for example per man-hour. By gross output is meant production less intermediates. Gross output will for example increase if labour is equipped with more capital goods or other inputs or if new natural resources are discovered.

Another frequently used productivity concept is total factor productivity. Total factor productivity growth is a measure of such part of gross output growth as cannot be attributed to changes in the quantity of one or more inputs, i.e. labour, capital, intermediates, etc. Consequently, total factor productivity provides a measure of how efficiently inputs in the economy are organised for the production of goods and services. The change in gross output less the growth in measured inputs is used as an approximate measure of total factor productivity growth (Statistics Norway, 2011). Sources of total factor productivity growth may be the development of new technologies (Research and Development – R&D), the dissemination of existing technologies, improved education and learning processes associated with the implementation of new technologies.

The impact of real wage increases on prices differs. Under perfect competition, standard economic theory suggests that wages (before tax) will over time be equal to the value of the marginal productivity of labour. If one sector of the economy experiences productivity growth that justifies real wage growth, labour will be attracted to such sector via higher wages. This may force real wages upwards in other sectors of the economy as well. The impact of developments in the real price of an input on developments in the real cost of a project depends, inter alia, on such input’s share of the original budget, the scope for factor substitution, as well as productivity growth as far as concerns the type of “production activity” to which the project is intended to contribute.

Let us, as an example, look at a project with no scope for substitution, i.e. where the inputs are used in a fixed proportion to each other (so-called Leontief technology). The scale of the good/service output over time is assumed to be constant. Assume that L0 units of labour are needed in the base year and that the real wage is W0. Real wage costs are then L0*W0. Annual growth in real wage costs can then be expressed as the percentage growth in the real wage per hour (VW) less the percentage productivity growth (VL), i.e. VW-VL.

Table 4.1 puts average real wage growth at 1.9 percent for the period 1979-2011. Assume that we expect the same real wage growth over the lifespan of the relevant project. We then note that real wage cost developments depend on expected productivity growth, which will be project-specific. For most types of service production (e.g. health and care services, maintenance, bus transportation), there is reason to believe that productivity growth is below the average for the economy and that real wage costs will increase over time, i.e. that real wage costs in period t, Lt*Wt= L0*W0(1+VW-VL)t, will exceed those in the base year. For other types of production, especially certain types of capital-intensive goods production, the opposite will apply. Hence, this line of reasoning predicts that real prices of goods and services in capital-intensive production can be expected to decline over time, whilst real prices of goods and services in labour-intensive production can be expected to increase over time. Only if productivity growth equals real wage growth will real wage costs be constant over time (cf. the presentation of historical data in Table 4.1 and the “Baumol Effect”3). Box 4.2 provides a brief overview of key aspects of economic growth theory.

4.4 The value of time savings and real price adjustment

4.4.1 The value of time and previous evaluations

In order to evaluate how the value of time or time savings should be subjected to real price adjustment we need to look at the basis and methods for the valuation of time. Such valuation is based on the premise that time savings may be used for alternative purposes that could not have been realised in the absence of these savings. Correspondingly, additional time used will involve a cost in the form of the value of the alternative time uses crowded out by such additional time use. Major parts of the economic benefits from investments in, for example, improved roads, new airports or upgraded railway lines are precisely in the form of (travel) time savings. The benefits of investments in new IT systems will in many cases take the form of a reduction in time use. One may also envisage investments or projects (for example reorganisations) in other sectors that may influence the utilisation of time. In cost-benefit analysis, the time saved needs to be valued at its value in its new use, less its value in its previous use, in line with the opportunity cost principle.

The value of time reflects the fact that time is used differently for different purposes. The value of time is determined by the activity to which time is devoted, and the value of such activity. Little or no value is, for example, attributed to time “wasted” (e.g. in waiting for the bus). Time spent on productive work or on holidays and recreational activities may, at the same time, be accorded a high value. The value of time spent working on the train may differ from that of time spent listening to the radio in the car. The value of time will also differ between people. Persons who are “pressed for time” will for example have a high willingness to pay for fast transportation. Studies show that high-income groups generally place a higher value on time than other groups.

The NOU 1997: 27 Green Paper includes a fairly thorough discussion of the value of time, with a special focus on the transportation sector. That report classified the value of time into two categories: the value of time at work and the value of time outside work; private time. This Committee has chosen to adopt the same classification.4

The value of time at work

The NOU 1997: 27 Green Paper notes that the cost of travel for work purposes has traditionally been linked to the value of the production lost during travel time, in line with the opportunity cost principle and economic theory. The employer’s valuation of the loss of production is measured by real wage costs. By real wage costs are here meant the employer’s total labour expenses, i.e. wages, employer’s social security contributions, social costs and any other costs involved in using labour.5 The background to this approach is that the real wage reflects the marginal productivity of labour in a profit-maximising enterprise. From the perspective of the employer, the cost of increased time use at work equals the value of the loss of production as the result of reduced time for production.

However, the NOU 1997: 27 Green Paper goes on to note that there may be several reasons why real costs differ from those implied by the theoretical model. Labour market imperfections caused by, for example, market power on the supply or demand side, market regulation or wage formation rigidities may result in the opportunity value of labour not being reflected in the gross real wage on the margin.

The NOU 1997: 27 Green Paper also discusses how the value of travel time is influenced by what use is made of such travel time. The better the scope for work during travel, the less worth is a reduction in travel time. If basing the value of time spent on travel for work on the employer’s real wage costs, one therefore needs to adjust for such time during travel as is spent efficiently. If, for example, the traveller is able to work at half efficiency throughout the journey (or work at full efficiency for half the journey), it necessarily follows that only half of the travel time represents real man-hours lost. If one fails to adjust for this in the calculations, one exaggerates the economic value of investments that contribute to reducing travel time. Likewise, such an adjustment will convey a more accurate impression of the real economic benefits from investments that improve opportunities for work during the journey, without reducing actual travel time (an example may be the installation of web access facilities on airplanes). Hjorthol (2008) analyses the use of travel time onboard trains in Norway. She finds that “more than half of those undertaking business travel or other work-related journeys, … , spend the [travel] time doing work”.6

In principle, the personal time costs or gains of employees should be included in the calculation of the costs of increased travel time, in addition to the employer’s costs. For example, for a given reduction in travel time it will, under such a broader cost concept, be of relevance whether a train journey is filled to capacity and one needs to stand up, or whether there is enough room to sit down and read a book. This approach suggests, inter alia, that it will be appropriate to apply different values of time in respect of different means of transport, depending on the said factors. Consequently, investments that influence comfort or work opportunities will influence the values of time.7

Although studies have previously been conducted based on the method of adjusting for how travel time can be used efficiently (e.g. Institute of Transport Economics (“TØI”) in Norway (Ramjerdi et al., 1997)), it is in the most recent Norwegian value of time survey from TØI and SWECO (Samstad et al., 2010) recommended to apply the employer’s time costs from its loss of labour input as the value of employees’ business travel, without adjusting travel time for work opportunities, etc.

Textbox 4.2 Economic growth theory

Neo-classical growth theory

Basic (neo-classical) growth theory was developed in the 1940s and 1950s. This theory is often referred to as the Solow-Swan model after the important contributions of Robert Solow and Trevor W. Swan in the 1950s.1

The key assumption in this type of model is diminishing returns on capital in the economy. One additional unit of capital per unit of labour yields a smaller increase in production quantity than did the previous unit of capital. For a given savings rate, the economy will grow when capital is accumulated, but the assumption of diminishing returns on capital means that when investments have reached a certain level, one additional unit of capital will exactly compensate for the loss of the capital depreciated each period, thus implying that the economy will no longer grow – in the sense that GDP per capita will remain constant. This is termed the steady state. Higher levels of savings and investment will shift this state and result in increased per capita production and higher consumption and real wage levels in the long run.2 The model describes the transition (growth) of the economy from one steady state to the other, but it does not seek to explain why the economy experiences growth in the long run, i.e. after it has reached the steady state. In order to achieve growth in the steady state it has to be assumed that the economy experiences productivity growth (caused by labour-saving technological progress). In other words, the model is not intended to shed light on how such growth arises, and the theory is therefore often referred to as an exogenous growth model.

The model also delivers predictions for developments in the real wage level. During the period until the steady state is reached, real wages will increase because the economy as a whole (including the capital stock and production per unit of labour) is growing. Once the economy has reached the steady state, no further real wage growth will be experienced. Only exogenous productivity growth can deliver real wage growth in the long run (in the steady state).

Cass (1965) and Koopmans (1965) refined the model by letting the savings rate be determined by utility-maximising consumers. This is termed the Ramsey model (after Ramsey (1928)), which models how the savings rate of consumers is determined by, and interacts with, other parameters in the model. This model does not explain long-term economic growth either.

These models, as described above, assume a closed economy in which the market interest rate is determined endogenously. Norway is a small, open economy, and it is therefore more commonly assumed that the market interest rate, and thus the capital level, in Norway is determined exogenously from abroad. (Savings and investment levels do not have to match in an open economy). Hence, the open-economy version of the neo-classical model loses its transition dynamics unless further assumptions are adopted in such model, since the capital level is no longer determined by domestic savings. Real wage growth in the steady state is driven by exogenous productivity growth in the open-economy version as well.

Endogenous growth models

Endogenous growth models explain how economic growth, including real wage growth, happens in the long run as well. One of the mechanisms modelled results in the assumption of diminishing returns on real capital being moderated or eliminated. A well-known example of this is Romer (1986), which introduces positive spillover effects from investments in knowledge-intensive capital goods. This results in growth in the steady state as well.

In addition, Romer (1990) and Jones (1995) model productivity growth by letting different varieties of capital being produced on the basis of patents resulting from R&D production. Producers of finished goods generate demand for the new capital goods, and the productivity of their capital increases with the number of new varieties to which they get access. This results in welfare gains and lasting economic growth.3

Other models achieve similar outcomes by introducing public goods in the production process (Barro, 1990), or by introducing interaction effects between capital goods and human capital (Lucas, 1988).

Another type of endogenous growth theory models enterprises that upgrade and improve, and thus replace, existing capital goods. These models are often referred to as Schumpeterian models4 (Aghion & Howitt, 1992).

1 Solow (1956) and Swan (1956).

2 However, the model also shows that it is theoretically possible for savings to be too high, resulting in a situation where the long-term consumption level would increase if savings were reduced.

3 This is often termed Spence-Dixit-Stiglitz love-of-variety effect in the literature.

4 After Joseph Alois Schumpeter’s term “creative destruction”; see Schumpeter (1934).

The value of leisure time

One may also use the opportunity cost concept in the valuation of private time savings.8 The classical theoretical framework assumes that the net real wage per hour reflects the opportunity value of one hour of leisure. By net real wage is meant the wage less marginal tax. Since the labour supply response of the consumer will be such that the last hour spent on work will, on the margin, give the consumer the same utility as does one additional hour of leisure, the implication is that the consumer values private time, or leisure, at the net real wage on the margin. If the consumer has not made such adaptation, it will be possible to change the amount of work and thus achieve a higher utility level. According to this reasoning, the net real wage will always express the value of one hour of additional leisure on the margin.

There are some objections to this approach. Firstly, many employees may have less flexible working arrangements than assumed by such model, for example because working hours are largely predetermined or because one receives as fixed annual salary. This would mean that employees are not necessarily able to fine tune their trade-off between work and leisure, thus implying that many employees work more or less than they would have preferred.

Secondly, far from everyone in Norway is involved in income-generating work. Many of those who are not in employment are likely to consume more leisure than they would if they had been able to take a job at the current market wage. This suggests that their valuation of leisure is lower than the net real wage observed in the market.

Thirdly, many people will probably argue that they derive inherent utility from being at work, apart from the real wage they receive from their employer, or that much work is in actual fact investment in human capital/learning from which the employee will benefit later. These factors suggest that the value of leisure time exceeds the net real wage; by choosing to consume one additional hour of leisure, one does not only forgo the wages lost, but also other benefits from work.

Fourthly, the value of leisure time will depend on how time is spent (whether the time is used efficiently, the level of comfort, etc.). In the transportation sector, for example, the values of time will thus be influenced by whether the journey is an activity holiday or other factors that influence the valuation of time use.

Willingness to pay surveys as a valuation method and previous evaluations9

Empirical studies of willingness to pay offer an alternative approach to the valuation of time. The idea is to uncover travellers’ willingness to pay for travel time savings by using statistics or questionnaires. Such an approach brings out directly how each person values the journey.

There are two main types of surveys: revealed preferences and expressed preferences (also frequently termed indirect and direct methods, respectively). The first method is premised on observations of actual behaviour. In the transportation sector, for example, one can use available data on journey lengths, prices, alternatives, travel habits, etc., to estimate the implicit values attributed by road users to time savings when making travel choices. The second method, expressed preferences, is based on hypothetical behaviour, and may again be divided into conditional valuation (direct questions about willingness to pay) and conjoint analysis (where the respondent is requested to take a view on simultaneous changes in several factors, thus revealing the indirect willingness to pay).

In the NOU 1997: 27 Green Paper, the Committee concluded with a recommendation to apply the “simple opportunity cost method” for minor projects. The Committee acknowledged the value of willingness to pay analyses for major projects, but expressed some scepticism about attaching too much weight to hypothetical methods.

The following is stated in Guidance on Using Profitability Assessments in the Public Sector (NOU 1998: 16 Green Paper; Cost-Benefit Analysis): ”In those cases where no designated surveys are carried out, the Committee recommends starting out from wages inclusive of tax and employer’s social security contributions and wages exclusive of tax and employer’s social security contributions, respectively, depending on whether the time savings are used to increase working hours or to increase leisure hours.”

4.4.2 The value of time over time

Time is a major component on both the cost and the benefit side of calculations in many areas. In the cost-benefit analysis of, for example, a new stretch of road, values of time will play an absolutely key role on the benefit side of the analysis. However, the travel time savings are not only realised in any one year, but also in the distant future. It is therefore necessary to estimate the economic benefits from motorists arriving one hour earlier for every year of the analysis period. The calculations of future values may have a decisive impact on the profitability of investment projects where much of the benefits from the project come in the form of the value of time savings.

We noted from Chapter 4.4.1 that the value of time is influenced by a number of factors, although wages before or after tax – depending on what type of time we wish to put a price on – are normally a key component in the valuation of time. An exemption is the use of willingness to pay studies, where the valuation of time is not directly dependent on wages. However, it is reasonable to assume a positive correlation between changes in real wages and changes in the willingness to pay for time savings, since wages are amongst the factors influencing the willingness to pay.

It is reasonable to expect the elements that make up the value of time at present to also determine the value of time in future. Hence, one must examine these factors in order to say something about developments in the value of time over time.

Time saved at work

It was explained above that time savings at work should be valued on the basis of the employer’s measure for the actual production benefits resulting from the time released. In addition, the value of the time savings was influenced by the employee’s work opportunities and inconveniences/benefits associated with the journey. The same principles should form the basis for projections of the value of time savings at work.

Historically, wage level increases have outpaced retail price index increases by a considerable margin, cf. Chart 4.2 and the discussion of the relationship between productivity growth, capital and wages in Chapter 4.3 above. If it is assumed that Norway will continue to experience real wage growth in future as well, it may be concluded that the value of time will develop differently from retail price developments.

In some contexts it is reasonable to assume that the employee’s inconvenience costs and effective utilisation of time have changed. Means of transport are becoming more comfortable and better adapted for work during travel. Opportunities for engaging in work or leisure activities via laptops, mobile phones, etc., have increased the utilisation of travel time and reduced personal inconvenience costs. If one assumes that this trend will continue, a projection of the valuation of reduced travel time based exclusively on real wage growth will overestimate the actual economic benefits from the travel time saved.10

If information about all elements that influence time costs is available for the coming years, it will be appropriate to include this in the cost-benefit analysis. However, it will in most cases be problematic to estimate projections for, in particular, changes in employees’ personal inconvenience costs associated with travel time.

Time saved during leisure hours (private time)

It was noted in 4.4.1 that the net real wage was the measure of the value of one hour of leisure in the classical theoretical framework. Within such framework, one hour saved that results in one additional hour of leisure for the consumer must therefore be valued at the current net real wage level in a cost-benefit analysis. Moreover, the same must apply for every year, including future years. Consequently, it is reasonable to assume, based on the classical theoretical framework, that the growth rate of the net real wage and of the value of leisure time saved will be equal.

However, as with the description of the value of time at work, the description of the value of leisure time in 4.4.1 showed that the value of time is influenced by more elements than wages. Inflexible work arrangements and the uses to which saved leisure time is put are elements that will also affect the value of saved leisure time in future.

If using empirical willingness to pay surveys to assess the value of leisure time, it is not obvious that one should use wage level growth to estimate growth in these values of time. It has therefore become common practice in many countries to use data on the elasticity of the willingness to pay with respect to income to estimate how much the values of time will increase over time.11 This elasticity measures by how many percent the willingness to pay for time savings increases when income increases by one percent. If this elasticity of the willingness to pay is known, and one also has a good estimate for future income growth, one will be able to estimate developments in the willingness to pay over time on that basis. It is normally assumed that this elasticity has a value of between 0 and 1. If it is 0, the values of time do not depend on the income level, and must therefore be expected to develop in line with general inflation. If the elasticity is 1, the values of time are growing in step with real income. If it is 0.5, the values of time will increase by half the growth rate of real income.

Let us assume, as an example, that the benefit side of an investment in the transportation sector comprises, inter alia, travel time savings. If annual real income growth is estimated to be 3.0 percent, the value of each hour saved will increase by E*3 percent every year, with E being the said elasticity. If calculations show this to be 0.5, the implied assumption in this example is that the value of time will increase by 1.5 percent every year. If an estimate of the current value of travel time has been established through willingness to pay surveys, such estimate is used to find the future value of time as well.

4.4.3 Empirical studies, elasticities and the income concept

Empirical studies of values of leisure time over time

In order to improve understanding of how values of leisure time change over time, a number of studies have sought to shed light on the issue. One type of empirical study looks at the income dependence of values of time in cross-sectional data. By obtaining information on various individuals’ wage income and their willingness to pay for time savings, one can establish a measure for the correlation between income and values of time. If one also has an average income growth estimate, this information can be combined to provide a measure for the value of future time savings in the project analysis.

However, differences in the willingness to pay between income groups at a specific point in time do not necessarily tell us anything about how the average willingness to pay will change if society as a whole becomes richer.

A more appropriate approach is therefore to compare the values of time from reasonably similar value of time studies conducted in the same country or area at an interval of a few years, and study how the willingness to pay for time savings seems to vary with the general income level in society. Such national value of time studies have been carried out in, inter alia, Norway, the United Kingdom and Sweden.

In Sweden, exactly identical analyses have been performed in 1994 and in 2007 to establish how values of time develop over time, WSP Analysis & Strategy (2010). Börjesson et al. (2012) has analysed the findings and has found – based on cross-sectional data for the two years – that the elasticity of the willingness to pay with respect to the value of time is not significantly different from zero for income groups below the median income. For income groups above the median income, the elasticity is estimated to be in the region of 1. In other words, according to the said article, the elasticity with respect to the value of time is not constant, but positively correlated with income. Hence, when the average income increases, the elasticity also increases.

A similar study has recently been published by the Institute of Transport Economics for Norwegian data (Ramjerdi et al., 2012). This also compares data from two studies (from 1996 and 2009). The authors find that elasticities based on cross-sectional data are in the region of 0.5-0.6, but if one looks at the willingness to pay of each income group, little change has been recorded over this time period. This implies, according to the authors, an elasticity for the population as a whole of about 1. Moreover, the authors note that the reason for the differences between the findings from cross-sectional data and time series data is that the portion of income people allocate for consumption is what is relevant for evaluating elasticity, whilst the income information from cross-sectional data does not correspond to the budget portion allocated to consumption.

A final type of study is labelled meta studies in the literature. These may draw on data from many more sources than do the national value of time studies, and for many years, not only one or two. Mark Wardman has conducted a series of meta studies on British data (Wardman, 2001, Wardman, 2004 and Abrantes and Wardman, 2011). In the latest and most up to date analysis, the authors find an elasticity of the willingness to pay with respect to GDP of 0.9.

Which income measure should be used in cost-benefit analysis for the value of leisure time?

The simplest theoretical approach discussed above suggests that the opportunity cost of leisure is determined by the net real wage per hour. A person who receives more capital income or other non-labour-related income will not experience any change in her opportunity cost of leisure. However, if her real wage increases, the opportunity cost of leisure increases. Consequently, it is correct to use net real wage growth as a measure of the increase in the value of leisure time, according to this theory.

However, this method does not take into consideration a number of factors like inflexible working hours, the scope for partial utilisation of the time (e.g. reading during the journey), etc. If one does instead use willingness to pay surveys in combination with an elasticity to estimate the future value of leisure, it becomes less obvious that the real wage is necessarily the appropriate income concept. We concluded above that the value of time changes for more reasons than changes in wages only. If there is a correlation between these causes and, for example, a country’s gross domestic product (GDP) per capita, it is conceivably also acceptable to use GDP per capita as the income concept. However, one should to the extent possible use the same income concept in preparing estimates for future values of time as was used in estimating the actual elasticity; see also Box 4.3.

Textbox 4.3 Various income measures

The white paper on long-term perspectives for the Norwegian economy, which is submitted to the Storting every fourth year, provides estimates for future Norwegian income growth. The most recent of these white papers, Report No. 9 (2008-2009) to the Storting, presents three different future income growth estimates for Norway until 2060; see Table 4.2. The estimates, which are generated by using the general equilibrium model MSG6 (Heide et al., 2004), are based on a number of assumptions and therefore cannot necessarily be considered forecasts.

Gross domestic product (GDP) per capita is a measure of annual national value added, and is a frequently used measure of a country’s real income level. Disposable real income also includes, in addition to total value added, net capital and wage income from abroad, including dividend and interest income generated by the Government Pension Fund Global. The magnitude of such interest income means that growth in average disposable real income is estimated to be somewhat higher than GDP growth. Norway’s petroleum revenues may result in the three income concepts mentioned above varying somewhat more over time than is the case for other countries.

Table 4.2 Income growth indicators. Percent

Average annual growth 2007-2060

Percentage change from 2007 to 2060

Disposable real income per capita

1.6

128

GDP per capita

1.4

109

Mainland GDP per capita

1.7

149

Source Report No. 9 (2008-2009) to the Storting; Long-Term Perspectives for the Norwegian Economy 2009

Differentiation of values of time

In principle, cost-benefit analysis should be based on the income level of those individuals who are affected by the investment. The aggregation level of values of time may, however, hide major differences between individuals. For example, the Ministry of Transport and Communications notes, in its feedback to the Expert Committee, that cost-benefit analyses carried out by the transportation bodies in Norway apply the same values of travel time for journeys throughout the country, irrespective of project type. Since a number of unit prices, including values of time, will vary with wage income, there is little doubt, according to the Ministry of Transport and Communications, that areas with high mean incomes will exhibit a higher willingness to pay, and thus higher estimated unit prices. In other words, using the national average in the analysis of investments in high-income areas will, for example, result in the underestimation of time costs. Corresponding objections also apply if one expects different income growth in different geographical locations.

Börjesson and Eliasson (2011) (in Anderstig et al., 2011) note, based on Swedish data, that the value of travel time varies considerably, and not only with the income of the traveller, but also with the specific purpose of travel, the number of children and other factors.

If cost-benefit analysis is conducted using the same value of time irrespective of where in the country the measure would be implemented, and irrespective of e.g. the mode of transport, one deviates from the general cost-benefit analysis principle that the benefit side shall be based on the actual willingness to pay (and thus deviates from the principle adopted elsewhere in the analysis).

4.4.4 Real price adjustment practice – various perspectives

Traditional practice within the area of transportation in Norway has been to use an elasticity of 0 for cost-benefit analysis purposes – i.e. to apply the current values of time and assume no real price adjustment, thus implying that all prices are subject to the same nominal rate of change. The value of time at work has not been subjected to real price adjustment either. In other words, it has not been common practice in Norway to subject the values of time used in cost-benefit analysis to real price adjustment.

If one assumes that the willingness to pay for time savings does in actual fact increase over time, the absence of real price adjustment over time will result in projects where time savings feature heavily on the benefit side being perceived as less profitable than in fact they are. Consequently, this might in theory result in economic underinvestment in time-saving measures. Likewise, projects that result in increased time use (for example road projects proposing a routing around, instead of through, certain areas) will appear to be less costly, and thus more profitable, than is actually the case.

However, values of time are also used in other sectors. The Committee is aware that cost-benefit analyses within the ambit of the Ministry of Trade and Industry value time savings associated with simplifications for the business sector, and that time savings often form an important part of the benefits from ICT projects. The Ministry of Defence has informed the Committee that it prepared a designated cost-benefit analysis guide for investment activities within the defence sector in 2010. Wages12 are used as the calculation price of the value of time saved. The guide recommends that average annual real wage growth be put at 1.5 percent. Other prices are also subjected to real price adjustment.

Guides in several other countries recommend using an elasticity of between 0.5 and 1 for travel time savings during leisure hours and 1 for time savings at work. The following is a listing of recommendations from guides in some countries and findings from selected Norwegian studies/reports:

  • EU: a consortium lead by the German IER institute (University of Stuttgart, Institute of Energy Economics and the Rational Use of Energy) prepared, over the period 2004-2006, a proposal for harmonised guidelines for transportation infrastructure projects in Europe through an EU-funded research project called HEATCO (Harmonised European Approaches for Transport Costing and Project Assessment).

    The HEATCO report (2006) concludes that analyses based on cross-sectional data are not adequate for preparing estimates over time. Instead, the report refers to the study by Wardman (2004), which finds an elasticity of 0.72 with regard to GDP per capita for all purposes of travel. As explanation of why the elasticity deviates from 1, they observe that low-income workers may have less flexibility in adapting their time, that household income may differ from personal income, and that travel time may be used in an efficient manner.

    HEATCO recommends using an elasticity of 0.7 for both work and leisure travel (HEATCO, pages 63-64), with GDP per capita as the income measure.13

  • United Kingdom: The web-based document WebTAG (2012) represents the official British cost-benefit analysis framework within the area of transportation. It recommends using an elasticity of 0.8 for private journeys, with GDP per capita as the income measure. The value of time at work is assumed to increase at the same rate as labour income (inclusive of estimated costs in excess of gross wages, like insurance, pensions, etc.). WebTAG also presents estimates for the specific values to be used in the analyses.

  • Sweden: Sweden adheres to the transportation sector guidelines of the Swedish Transport Administration. ASEK 5 (Swedish Transport Administration, 2012) recommends using an elasticity of 1 for the value of travel time, based on willingness to pay surveys (leisure). The income measure is GDP per capita. Gross wages are used for work journeys. These prices are also subjected to real price adjustment based on GDP per capita. It may also be mentioned that ASEK 5 recommends adjusting the value of time for train journeys to reflect that 15 percent of the time is used for work.

  • The consultancy firm COWI has been commissioned by the Norwegian Public Roads Administration to analyse which unit costs should be subjected to real price adjustment, and based on which forecasts (COWI, 2010). The recommendations in the COWI report are primarily based on a review of the literature, and it follows from the report that it is largely based on discretionary assessments. The report concludes by recommending an elasticity of 0.8 for leisure journeys, as well as the use of disposable real income as the basis for adjustment. It is also recommended that the value of time during business travel be subjected to real price adjustment, based on disposable real income.

  • A study based on Norwegian data (Ramjerdi et al., 2010) finds elasticities for different means of transport of between 0.25 and 0.62. In addition, it finds that high-income groups have a higher value of time than low-income groups. The estimates are based on cross-sectional data. The report emphasises that these elasticities are low compared to those found in other studies, and that more research is required on the elasticity of the value of time. In the meantime, the authors of the report propose using an elasticity of 1 for all means of travel during leisure hours. Ramjerdi (2012), discussed in 4.4.3, finds elasticities of about 1.

COWI’s recommendations on real price adjustments are used in the input from the Norwegian National Rail Administration and the Norwegian Public Roads Administration for the National Transport Plan 2014-2023. The Government plans to publish the National Transport Plan in the spring of 2013.

4.4.5 Summary: Real price adjustment of the value of time savings

Valuation is based on the premise that time savings may be used for alternative purposes that could not have been realised in the absence of these savings. Time is commonly divided into two categories: work and leisure.

The value of time at work has traditionally been related to the loss of production at work. The employer’s valuation of the loss of production is measured by real wage costs. However, Chapter 4.4 discussed reasons why real costs may differ from real wages. Labour market imperfections may imply that the value of labour is not reflected in gross real wages on the margin. The value of travel time savings at work may also depend on how such travel time is used. The more efficiently travel time is used, the less valuable are travel time savings. One may also adjust for the personal time costs of the employees.

The value of time at work over time may be estimated on the basis of wage level projections, potentially adjusted for expected changes in employees’ inconvenience costs and their effective utilisation of the time.

For time savings during leisure hours, the classical theoretical framework suggests that the net real wage per hour reflects the opportunity cost per hour of leisure. However, we have in Chapter 4.4 discussed several reasons why this relationship may be more complex – for example inflexible working hours, unemployment and inherent utility from time spent at work.

An alternative method for valuing time savings during leisure hours is to use willingness to pay surveys. The idea is to reveal travellers’ willingness to pay for travel time savings by using statistics or questionnaires.

The value of leisure time over time may, by using the classical theoretical framework, be projected on the basis of expected changes in net wages. However, it is more common to use a method seeking to estimate an elasticity of the willingness to pay with regard to real income for purposes of estimating how much values of time will increase over time. This elasticity measures by how many percent the willingness to pay for time savings increases when income increases by one percent (normally assumed to be between 0 and 1). A number of attempts have been made at estimating such elasticity, and different methods exist. Two recent studies (Abrantes and Wardman, 2011, and Ramjerdi et al., 2012) arrive at point estimates of about 0.9 and 1, respectively. The most recent recommendations from Sweden and the United Kingdom (both for the transportation sector) are to use elasticities of 1 and 0.8, respectively.

4.5 Price developments over time for environmental goods

The valuation of goods that are not traded in the market is discussed in Chapter 2.6. The terms of reference stipulate that the Committee shall examine whether and, if applicable, how changes in calculation prices for environmental goods over time may be included in the cost-benefit calculations. The reason for highlighting environmental goods in this context is that a number of factors suggest that the willingness to pay for such goods may increase at a higher rate than general inflation. The most important factor is that the supply of environmental goods cannot, as a main rule, be expanded, and that these environmental goods are thereby assumed to become scarcer over time, given growing populations, production and consumption. Moreover, it is possible that at least some environmental goods may be “luxury goods”14 – i.e. that demand for these increases relatively more when the income level increases.

Figure 4.3  Supply of, and demand for, environmental goods – an illustration

Figure 4.3 Supply of, and demand for, environmental goods – an illustration

This reasoning is based on traditional market theory, cf. Chart 4.3. Curves 1 and 2 here designate possible demand curves for an environmental good, with 2 representing a higher income level than 1. A and B specify possible supply curves for the environmental good, with B representing an impairment of the environmental good relative to A. However, most environmental goods are not traded in a market, thus implying that we are not faced with supply and demand curves in the ordinary sense. The question of for which situations and, if applicable, how such calculation prices are to be calculated is therefore important. This includes the issue of how to define and delimit an environmental good for which the willingness to pay is to be estimated. Without calculation prices to start out from, the question of price developments over time is meaningless, at least for practical analysis purposes.

The range of environmental goods is very wide. Valuation possibilities and methods will depend on which environmental good we are dealing with. The discussion of developments over time should therefore be made with reference to environmental goods or groups of environmental goods that are as specific as possible.

The Committee will focus on discussing future price developments for environmental goods for which established calculation prices are available at present, i.e. prices that are actually used in cost-benefit analysis. These calculation prices are primarily based on calculations relating to health effects and political decisions/commitments. This will include a discussion of real price adjustment of the value of a statistical life. In addition, the Committee will discuss how to deal with calculation prices for individual goods based on different types of willingness to pay surveys.

It is important to recall that cost-benefit analysis will include qualitative and/or quantitative descriptions, but not monetary values, for a large number of environmental effects. Future developments in value may also be important with regard to such environmental effects. The Committee does not specifically address such environmental effects, but emphasises that a description of future access to, and scarcity of, non-valued environmental goods, and their future importance, forms a natural part of a cost-benefit analysis.

Furthermore, the Committee notes that the Government appointed a separate expert committee in October 2011 to examine, inter alia, the value of nature and ecosystem services in Norway. The Committee will here restrict itself to a brief discussion of various types of environmental goods and valuation methods. We then look at what the literature says about real calculation price developments for environmental goods that actually lend themselves to being valued.

4.5.1 What are “environmental goods”?

”Environmental goods” is an established concept in traditional environmental economics. Some environmental goods, such as fresh air, clean water and accessible recreation areas form part of people’s consumption, and this has a direct impact on welfare. Other environmental goods may be considered production process inputs, thus contributing indirectly to goods and services we are used to obtain in markets. Insect pollination of fruit trees is an example, another one is nature’s inherent ability to absorb and purify waste emissions from production.

Textbox 4.4 Ecosystem services

The term “ecosystem services” is fairly new, but is now in widespread use in the literature. Key projects like the Millennium Ecosystem Assessment and The Economics of Ecosystems and Biodiversity (“TEEB”) use this approach, cf. Millennium Ecosystem Assessment (2005) and Kumar (2010). This approach describes the various types of benefits people obtain from the earth’s ecosystems.

Ecosystem services are often divided into four main categories:

  • ”Supporting services” – like for example soil regeneration, photosynthesis and nutrient cycling. These are basic processes on which all life, and all other ecosystem services, depend. The economic value of these services only shows up indirectly, through the production and consumption they support. These exist in fixed quantities, i.e. they can be impaired through human influence, but not expanded.

  • ”Regulating services” – such as pollution filtration in wetlands and plants, climate regulation through carbon sequestration in forests and soils, as well as insect pollination of plants. These services can be said to be closer to human economic activities, and can to some extent be replaced. Water may be filtered naturally in intact wetlands, but also in technical facilities.

  • ”Provisioning services” – which give us, inter alia, meat, fish, fruit, cotton and flax, cereal products and medicines based on plant materials. Some of these products – like berries and mushrooms – are in most cases used directly in people’s own consumption. But products like fish, agricultural goods and textiles represent enormous markets, nationally and globally. The provisioning services therefore provide many goods that can be treated as ordinary market goods in a cost-benefit analysis.1

  • ”Cultural services” are those that provide us with recreation, spiritual and aesthetic experiences, learning and belonging. These services are predominantly of direct benefit to us, and not market-traded. A nature area within travelling distance is an environmental good with no market price, and provides a free ecosystem service. The largest number of willingness to pay surveys has been carried out for environmental goods with these characteristics.

1 It is a matter of opinion whether one chooses to call these goods “environmental goods”. Traditionally, economists have distinguished between environmental goods and goods from the harvesting of biological resources.

In other words, the range of environmental goods is very wide. The Committee will not describe this range, but briefly discusses the concept of “ecosystem services”, which is in frequent use, and which describes the benefits we obtain from nature and ecosystems in a systematic manner. This concept can be closely linked to the concept of environmental goods, and includes a division into four main categories, cf. Box 4.4.

Ecosystem services originate from ecosystems and cycles of nature, and depend on certain functions of these. The ecosystem concept describes nature from a human benefit perspective, in line with the concept of “environmental goods”, and is therefore suited for cost-benefit analysis. Let us take, for example, the environmental good “clean water”, which is negatively affected by pollution. Nature, for example wetlands, does on the other hand have an ability to purify. If the pollution exceeds the ongoing capacity to purify, water quality will deteriorate and the environmental good will be impaired. The ability of nature to purify may be described as a “regulating ecosystem service” (cf. Box 4.4). The service contributes to, or “produces” the environmental good clean water, which again contributes to new ecosystem services (like for example the “cultural” services swimming and recreational fishing). This illustrates the close link between ecosystem services and environmental goods. In the following, we will primarily focus on the concept of environmental goods.

4.5.2 Valuation of environmental goods

The total economic value of environmental goods is usually separated into use value and non-use value. (Some authors use the terminology “active use value” and “passive use value” (Bergstrom and Randall, 2010).) Use values may be direct (for example through recreation or harvesting), or indirect (for example through insect pollination, which again creates products that can be harvested). Option values include the value of environmental goods being saved for later use. Non-use values include the value of environmental goods existing and being preserved, even if one does not plan to experience them personally.15

A general discussion of methods for the valuation of environmental goods or ecosystem services that are not traded in the market can be found in Chapter 2.6. We also refer to the discussion in Chapter 9, where the Committee addresses how different valuation principles for non-market goods can often answer fundamentally different questions. As a basis for discussion of future price developments, we will here look at some specific examples.

The monetary valuation of environmental goods may take place through direct and indirect methods, cf. Chapter 2.6. Direct methods include “contingent valuation”, where respondents express their willingness to pay for an environmental good to be maintained or improved, or alternatively what economic compensation they need in order to accept the loss or degradation of such environmental good. Because the method is very flexible, it is possible to examine people’s willingness to pay for virtually anything – large or small, simple or complex, close or distant. The NOU 1997: 27 Green Paper recommended that one should limit the use of contingent valuation to “... areas where the agents directly or indirectly can be assumed to have some experience of valuing the relevant environmental good in economic terms.” (NOU 1997: 27 Green Paper, Chapter 10.3.) On the other hand, this is the only approach that can, in principle, uncover non-use values. It is quite possible that Norwegians have a willingness to pay for preserving a nature area they are not using – whether on grounds of principle, or because they wish to have the option of later use.

A large number of willingness to pay surveys based on contingent valuation have been conducted, the vast majority of which have taken place in other countries than Norway. The surveys are wide in scope. They may address anything from specific nature areas, animal and plant species, air and water quality, to the willingness to pay for reducing the risk of accident or death. In the latter approach, respondents’ willingness to pay is often combined with dose-response relationships between the state of health and environmental quality.

Indirect valuation methods seek to reveal preferences and derive the willingness to pay from people’s actual behaviour. The travel cost method, for example, involves estimating the value of nature areas on the basis of visitors’ travel costs. This method restricts itself to measuring the travel costs of actual users as a minimum estimate of their willingness to pay. Hedonistic valuation is a method based on the fact that the market price of a property – a house, holiday home or apartment – depends on many different factors, some of which are environmentally related. One can seek to isolate the effects of air quality, noise and proximity to nature through regression analyses, and use the estimates as calculation prices. There are also examples of differences between other market prices being analysed with a view to calculating implicit values of environmental goods.

One may also calculate the social cost of damage associated with a specific environmental state, compared to the cost of an alternative state. Local emissions of sulphur, nitrogen oxides and particles, for example, have health implications. Knowledge about dose-response relationships between air quality and morbidity/mortality, as well as knowledge about the number of people affected, will be key elements of such social cost of damage functions. Dose-response knowledge may be linked to surveys of people’s willingness to pay for changes to their state of health and changes to their risk of death. Chapter 10; Valuation of life and health, discusses methods and calculations for this type of willingness to pay. Such calculation prices are used in cost-benefit analysis in, inter alia, the transportation sector. In a report for the Climate and Pollution Agency, Sweco has sought to quantify the cost of emissions of priority environmental toxins (Magnussen et al., 2010). The health implications dominate these calculations as well.

Moreover, it is possible to estimate what it would cost society to make up for the loss of an environmental good. In principle, one may for example estimate the cost of a purification solution to replace an area of wetlands. In other cases one may estimate the cost of countering the inconvenience, for example through measures for the soundproofing of homes. An advantage of such replacement and compensation calculations is that calculation prices are based on amounts associated with actual or potential projects. These will, on the other hand, result in calculation prices that only partially reflect the environmental damage. Soundproofing a home alleviates problems indoors, but not on the outside, and an area of wetlands is more than simply a water purification facility.

Calculation prices can also be derived from political decisions. Political authorities, nationally and locally, make decisions that impose certain costs on enterprises and consumers, and which thus indirectly put a monetary value on environmental goods. In some cases, a national environmental target will reflect an international commitment. If, for example, the Storting adopts a noise target, the marginal cost of reaching such target can be used to arrive at a calculation price for noise level changes.

Politicians adopt policy measures to realise objectives. When the policy measure is an environmental tax, the tax rate may on certain conditions be used as the calculation price. One condition is that the tax rate matches the adopted objective. It is, for example, fairly common for a tax to be one of several policy measures with an effect on the same environmental objective. In order for the tax to be used as a calculation price, it is in principle necessary for it to reflect the marginal cost of realising the objective. Furthermore, political decisions may reflect several, conflicting social considerations, thus implying that it is difficult to know what a tax rate actually expresses. (Such issues are discussed in more detail in Chapter 9 on carbon price paths.)

Different valuation methods may be combined. As far as the emission of nitrogen oxides is concerned, Norway has made a national commitment, through the Gothenburg Protocol, to reduce our national emissions to certain levels. Calculation prices may be derived from the marginal cost of meeting the commitment. At the same time, these emissions also have detrimental effects on people’s health, which may be addressed by social cost of emission calculations. However, these detrimental effects will usually vary between urban and rural areas, partly because they depend on concentrations locally and partly because the number of affected inhabitants varies considerably. One may in such cases have a national calculation price determined by the international commitment – and higher rates in some cities based on social cost of emission calculations. An example of this can be found in “Handbook 140: Impact Assessments” (Norwegian Public Roads Administration, 2006 – Chapter 5; Priced impacts).

4.5.3 Price developments for environmental goods

Scarcity and willingness to pay

A main argument for assuming an increasing willingness to pay for environmental goods is that the quantity of nature surrounding us is fixed. It is true that impaired ecosystems may in some cases be restored, but as a main rule we cannot create “more” nature than in a natural state. A growing population will gradually need more space, and growing production and consumption of material goods must, when taken in isolation, be assumed to increase the strain on the natural environment and ecosystems. For ordinary goods in fixed supply, one will intuitively assume that the market price increases with increased demand.

As with ordinary goods, the issue of more efficient use needs to be addressed here. When the production of goods and services can increase at a noticeably higher rate than labour input, this is measured as increased labour productivity. A strong increase in “environmental efficiency” may counter the underlying factors – and may result in the environmental strain remaining constant or declining despite population and production growth. A relevant global example is emissions of ozone-depleting gases, which have declined steeply because one has switched over to other substances in aerosols, insulation foams and cooling systems. The ozone layer does of course provide us with a “regulating” service, inasmuch as it protects the earth and its population from harmful UV radiation. If the ozone layer does actually get thicker in future, this may in principle justify a lower calculation price for the good, in the form of a lower price for the environmental damage associated with the emission of one unit of an ozone-depleting substance.

However, some questions remain. Firstly, such a calculation price is not a “technical” entity, but depends on human assessments. New knowledge may change such assessments. Future research may demonstrate that the dangers are greater than we believe at the moment, thus implying a much higher ambition level – or conversely: that the risk is exaggerated. Mankind may decide to be absolutely certain that a positive trend will not be reversed, or may want to take a precautionary approach to dealing with an unknown probability of catastrophic effects (cf. Chapter 8). Such caution may be reflected in strict regulation, and a continuation of high, maybe even increasing, emission shadow prices. But it is also conceivable that technological developments make ozone-friendly alternatives so cheap relative to CFCs, etc., as to make the additional costs insignificant.

Environmental goods as luxury goods?

It is often assumed that people with low incomes attach little weight to the state of the environment, and consequently have a low willingness to pay for environmental improvements, whilst they take a different view when income increases. Environmental goods are in the literature often assumed to be “luxury goods”, which are in market theory defined as goods with an income elasticity of demand in excess of 1.16 Assuming fixed relative prices, this means that the budget share of such goods increases when real income increases. However, Pearce (1980) argued early on that these ideas were unfounded.

However, environmental goods do not, as a general rule, have any known demand curve or budget share. Calculating income elasticities of demand with respect to environmental goods is therefore complex. Hökby and Söderquist (2003) is amongst the small number of studies carried out, and is based on five surveys concerning the willingness to pay for a reduction of overfertilisation in the Baltic Sea. It found income elasticities of demand with respect to environmental quality in the 0.6-1.3 interval. This suggests that the environmental good, as defined in the five surveys, may be characterised as a “normal good” – possibly a “luxury good”. It is of decisive importance to the viability of the conclusion whether the environmental good is defined identically, and perceived identically by the respondents, in all of the surveys. Different environmental goods must be assumed to differ in this respect, and elasticities cannot necessarily be transferred or combined. Another objection is that one cannot automatically conclude from calculations based on cross-sectional data – from respondents with different incomes at a given point in time – to the elasticity of demand with respect to income developments over time.

For cost-benefit analysis purposes one is not interested in demand functions, but in the willingness to pay for an environmental good, or more precisely for a specific “amount” of the good – most often defined as a specific environmental quality compared to another level of said environmental quality. As with values of time, calculations have also been made with regard to how such willingness to pay depends on income, i.e. the “elasticity of the willingness to pay with respect to income”17. In the Hökby and Söderquist study, the estimate for this elasticity falls in the 0.24–0.35 interval. It may again be objected that this estimate is based on cross-sectional data, and cannot be perceived as an elasticity with respect to changes in real income over time.

Flores and Carson (1997) note that the elasticity of the willingness to pay for a good is not necessarily related to whether the good is “inferior”, “normal” or a “luxury good”. From the perspective of the terms of reference, developments in the willingness to pay over time are precisely what is of interest, because calculation prices for environmental goods are often based on willingness to pay surveys. Hence, it is not necessarily important to determine which of these three classes of goods an environmental good falls into. However, it is important to recall that the willingness to pay may change over time for other reasons than income developments. Knowledge and preferences may, for example, change, as may also the state of the environment as such.

Individual willingness to pay surveys can hardly say anything much about developments in the willingness to pay over time, including the effect of income developments. Meta analyses of valuation surveys for a specific environmental good face the problem that individual surveys do not specify the mean income of respondents. However, such meta analyses have been conducted, and generally show that the willingness to pay for a given environmental good increases over time. Serret and Johnstone (2006) conclude, based on available analyses, that the elasticity of the willingness to pay with respect to income for environmental goods falls in the 0.3-0.7 interval.

In a paper commissioned by the Committee, which reviews the literature in this area, Ståle Navrud (Navrud, 2011) states that the income elasticity of the willingness to pay for environmental goods may be used as a “first approach” for determining increases in the relative value of environmental goods over time, for a given change in real income. Navrud (2011) is partly based on the same sources as Serret and Johnstone (2006). He tentatively recommends an elasticity of 0.3-0.5, but also recommends that this be updated based on further analyses of Norwegian studies. He then writes the following: “The income elasticities of demand for different environmental goods may differ, but the above interval seems to encompass both use and non-use value, different environmental goods and environmentally-related health effects.” (Navrud, 2011). This will, in particular, include the group of environmental goods associated with what we have termed “cultural” ecosystem services in Chapter 4.5.1.

However, Navrud, 2011, concludes by reiterating that other factors than real income also influence our valuation of environmental goods over time.

4.5.4 Price developments for the value of statistical lives

The value of reduced risk – or the value of statistical lives saved – will in many cases influence either the benefit side or the cost side of an analysis. Improved road safety will for example reduce the number of accidents, which may be of considerable value on the benefit side of various cost-benefit analyses.

In Chapter 10, we discuss the basis and methods for valuing risk and determining the value of a statistical life (VSL). In the present Chapter, we therefore restrict ourselves to discussing how to subject the value of statistical lives, and imputed calculation prices, to real price adjustment for cost-benefit analysis purposes.

As with the traditional environmental goods discussed above, no market exists for statistical lives or reduced risk. Although theory may indicate how the valuation of statistical lives will change with income,18 it is problematic to find a good theoretical basis for determining how such valuation will develop relative to the value of market goods. Consequently, willingness to pay surveys are needed to examine the valuation of such goods.

As with the willingness to pay for time savings (see Chapter 4.4.3), there are several methods for estimating the correlation between income developments and VSL. Studies based on cross-sectional data examine the relationship between different income groups and their willingness to pay. Other studies compare the willingness to pay across countries with different income levels. Meta analyses combine findings from several different studies. A fourth method for obtaining information about how the willingness to pay develops over time is to use (a minimum of) two identical surveys amongst the same population at different points in time. Based on developments over this time period one may thus estimate a correlation between income developments and the valuation of statistical lives.

Although the latter type of survey more pertinently answers the question we pose – i.e. how the willingness to pay for statistical lives develops with income – even such a set of data will be problematic to use. Changes in culture, age, health status and risk level will in themselves also influence preferences, irrespective of income. It may be difficult to adjust for such elements in empirical studies.

Hammitt and Robinson (2011) analyse the elasticity of the willingness to pay for statistical lives with respect to income in both rich countries (the United States) and developing countries. The authors find indications that the said elasticity may be considerably in excess of 1 in developing countries. They note that surveys have arrived at elasticity estimates of close to 3 (in Taiwan), although this may be caused by a change in attitudes in a rapidly growing economy. As far as high-income countries are concerned, it seems as if elasticities may be somewhat lower than in developing countries. The authors refer, inter alia, to a meta analysis from 2003 (Viscusi and Aldy, 2003), which estimates elasticities in the region of 0.5–0.6. Figures of this magnitude are used in public sector analyses in the United States (Hammitt and Robinson, 2011). Hammitt and Robinson note that subsequent meta analyses have come up with somewhat higher figures, in most cases between 0.4 and 1. Studies across medium-income countries have resulted in elasticity estimates in excess of 1.

OECD (2012) notes that few empirical studies examine the correlation between income and VSL on the basis of time series data. The OECD recommends, by reference to meta analyses based on cross-sectional data and observed practice, to subject VSL to real price adjustment on the basis of an elasticity of the willingness to pay of 0.8 and a sensitivity analysis of 0.4 (using GDP per capita as the income concept).

Sweden adheres to the ASEK 5 guidelines for the transportation sector (Swedish Transport Administration, 2012). These recommend real price adjustment of accident costs, including VSL, based on an elasticity of the willingness to pay for statistical lives with respect to GDP per capita of 1. Real price adjustment based on an elasticity of 1 is also recommended in the United Kingdom.

4.6 The assessment of the Committee

The Committee is of the view that the advantages of real price adjustment of calculation prices need to be balanced against the uncertainty necessarily associated with such adjustment. Real price adjustment should therefore only be considered for cost and benefit components in respect of which there is a solid theoretical and empirical basis for estimating how developments in the valuation of such good will deviate from general inflation. When future developments in real calculation prices are subject to considerable uncertainty, and different development paths are of importance to the analysis, sensitivity estimates will be an appropriate alternative. The analysis shall also present and discuss how non-priced effects may change over time.

4.6.1 Price developments for time savings in cost-benefit analysis

The Committee recommends that the valuation of time savings be based on the opportunity cost principle. Furthermore, the Committee proposes that time use be divided into two main categories: work and leisure. More detailed categorisation may be used if good information is available.

The valuation of time at work should be based on the value added lost on the part of the employer (as measured by gross real wage costs). Any deviations from this should be based on good empirical measurements. The Committee refers to Chapter 3 on distribution effects, where it is noted that cost-benefit analysis based on individuals’ willingness to pay does measure the effects of projects and measures in monetary values, and not utility or welfare as such, and is of the view that the correct approach would, in principle, be to use the values of time of the persons affected by the relevant measure for analysis purpose. If adequate information about these values of time is not available, it is appropriate to use national averages.

The Committee takes the view that there may be good reasons why significant parts of the time travelled for business can be used efficiently at present. In principle, cost-benefit analysis should value the change in efficient time use. Estimates for changes in time use during working hours should therefore be adjusted, to the extent practicable, to ensure that analyses reflect changes in efficient working hours.

The valuation of leisure should be based on willingness to pay surveys. If such surveys are not available, it is appropriate to use the net real wage as the value of leisure.

Moreover, the Committee is of the view that economic theory and empirical research provide adequate support for the conclusion that the increases in the value of time must be expected to outpace general inflation. The Committee therefore recommends real price adjustment of values of time. This is of particular importance for projects where the value of time plays a key role on the benefit or cost side.

It seems appropriate to apply the same income measure in all analyses, to ensure that cost-benefit analyses are comparable across sectors. In the absence of specific estimates for long-term Norwegian real wage growth, the Committee recommends that GDP per capita development estimates from the most recent white paper on long-term perspectives for the Norwegian economy be used in respect of both work and leisure travel.

As far as real price adjustment of the value of leisure time is concerned, the most recent studies have found that the percentage increase in the general willingness to pay for leisure is equal or almost equal to real wage (or GDP per capita) growth, i.e. an elasticity of close to 1. However, some factors suggest that the elasticity is somewhat lower, and what can reasonably be assumed in this respect is fairly uncertain. It may seem as if low-income groups generally have a low elasticity.

Nonetheless, the Committee finds than an elasticity of 1, i.e. that the values of time increase in line with the (expected) GDP per capita growth rate, should be assumed. This is also in line with the most recent recommendations from the Swedish Transport Administration. The Committee emphasises the need for applying the same elasticity in all analyses across all sectors to ensure the comparability of such analyses.

4.6.2 Price developments for environmental goods in cost-benefit analysis

The Committee will distinguish between environmental goods whose valuation relates to health effects, political decisions/commitments and willingness to pay surveys, respectively.

The Committee is of the view that environmental goods valued on the basis of political commitments should be examined separately (see discussion of this in Chapter 9 on carbon price paths). If future changes in political commitments are expected, one may consider including the implications of such changes for imputed calculation prices. In principle, assumptions concerning future developments would have to be based on available knowledge about upcoming processes, contract negotiations and future commitments. Even if one were able to assume that the income level will influence people’s political behaviour in the form of voting and their expressed views on environmental issues, we have no basis for assuming that the implicit, political “willingness to pay” will be systematically correlated with income developments in society.

Including expected policy developments may also conceal a major element of uncertainty in the analysis, which the decision makers may be better served by having examined explicitly, for example in a sensitivity analysis. The decision makers who can influence the political environmental commitments will in many cases be same who shall assess whether to implement a measure. This is also an argument in favour of the analyst refraining from evaluations of future policy developments. All in all, this suggests that current policy, including established future targets and commitments, shall form the basis for determining calculation prices, and that adjustments to reflect policy development assumptions should be avoided. Such considerations should be discussed separately, or examined in a sensitivity analysis, if deemed to be of particular relevance.

The Committee finds, based on the discussion in Chapter 4.5.4, that the value of statistical lives should be subjected to real price adjustment in line with GDP per capita growth (i.e. an elasticity of the willingness to pay of 1 with respect to GDP per capita). Imputed calculation prices, like the established calculation prices for noise and some forms of local air pollution, are based on the valuation of health and mortality changes, in combination with knowledge about dose-response relationships between emissions, concentration levels and health effects. In view of the discussion of the value of statistical lives, it is also recommended that such calculation prices be subjected to real price adjustment based on GDP per capita growth. If relationships between environmental states and health effects (dose-response relationships) are expected to change over time, adjustment should also be made for such developments.

The Committee has been expressly requested to examine the use of future price paths for carbon emissions in cost-benefit analysis, which does in itself require something other than rule-of-thumb adjustment based on real income. This issue is addressed in Chapter 9.

Beyond these more established calculation prices, the Committee notes that many surveys have been conducted, and will be conducted, on the population’s willingness to pay for other environmental goods. The issue before the Committee has been whether to recommend a “rule-of-thumb” adjustment of calculation prices based on willingness to pay, using estimated future real income growth or other factors, and, if applicable, to which calculation methods and which groups of environmental goods this should apply.

There are methodological problems and challenges associated with surveys of people’s willingness to pay for environmental goods. If one chooses to use a calculation price from such a survey, it would at first glance also seem logical to utilise knowledge concerning developments in the willingness to pay over time – for example in the form of estimated elasticities of the population’s willingness to pay with respect to income. However, such knowledge comes from analyses that encompass fairly heterogeneous environmental goods. Hence, there would not seem to exist an adequate empirical basis for proposing general rules for the real price adjustment of calculation prices that are based on willingness to pay surveys for environmental goods. (If one chooses to utilise calculation prices from older surveys, these estimates should be adjusted, by using the retail price index, to the base year for the cost-benefit analysis unless there exists knowledge suggesting otherwise.)

There are, as discussed in Chapters 4.5.3 and 4.5.4, factors which may suggest that the calculation prices of several environmental goods should be increased over time, relative to the general price level. It may be appropriate to present and discuss such factors, and potentially also to use sensitivity analyses, when alternative future development paths are of importance to the analysis.

4.7 Summary recommendations

Based on the discussion in the present Chapter, the Committee makes the following recommendations:

General recommendations:

  • Real price adjustment (up or down) should only be considered for cost and benefit components where there is a firm theoretical and empirical basis for estimating how developments in the valuation of the relevant goods will deviate from general inflation.

  • When future real developments in calculation prices are subject to considerable uncertainty, and different development paths are of importance to the analysis, sensitivity calculations may be an appropriate alternative.

  • Cost-benefit analysis should also present and discuss how non-priced effects may change over time.

Values of time:

  • The Committee recommends that the valuation of time savings be based on the opportunity cost principle. Furthermore, the Committee proposes that time use be split into two main categories: work and leisure. The Committee is of the view that more precise categories may also be used if good information is available.

  • The valuation of time at work should be based on the value added lost by the employer (as measured by gross real wage costs).

  • Estimates of saved/increased working hours should, to the extent practicable, reflect the effective time gain/time loss.

  • The valuation of leisure should be based on willingness to pay surveys. If no such survey is available, it will be appropriate to use the net real wage as representing the value of leisure time.

  • The value of time at work should be price adjusted by using the expected growth in GDP per capita.

  • Correspondingly, the value of leisure time saved should be subjected to real price adjustment by using the expected growth in GDP per capita. This implies that the elasticity of the willingness to pay for leisure with regard to GDP per capita is 1.

  • If possible, the values of time of the people who are affected by the measure should be used in the analysis. If adequate information about these values of time is not available, it will be appropriate to use national averages.

Environmental goods:

  • The Committee finds that the value of statistical lives, and the imputed calculation prices (including health and mortality-related environmental effects), should be subjected to real price adjustment based on the growth in GDP per capita.

  • Calculation prices for health and mortality-related environmental effects should also be adjusted for estimated developments in the health effect of the environmental damage.

  • As far as concerns calculation prices based on individual willingness to pay for environmental goods, the Committee does not think there is an adequate empirical basis for proposing general real price adjustment rules.

  • Calculation prices derived from political decisions and commitments should be based on current policy and knowledge about future objectives and commitments. No adjustment should be made with respect to policy development assumptions. Such considerations may, for example, be addressed by a sensitivity analysis if deemed to be of particular relevance to the decision maker. As far as the calculation price for greenhouse gas emissions is concerned, reference is made to a separate discussion in Chapter 9.

  • Factors that influence the future scarcity and importance of affected environmental goods should be presented and discussed in the economic analyses, irrespective of whether calculation prices are available and used.

4.8 Bibliography

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Anderstig, Christer, Svante Berglund, Jonas Eliasson, Matts Andersson and Roger Pyddoke (2011). Congestion charges and the labour market: “wider economic benefits” or “losses”? Draft CTS Working paper 2011: X, Stockholm: Centre for Transport Studies.

Barro, Robert J. (1990). Government Spending in a Simple Model of Endogenous Growth. Journal of Political Economy, 103-125.

Baumol, William J., and William G. Bowen (1966). Performing Arts: The Economic Dilemma. New York: The Twentieth Century Fund.

Bergstrom, John C., and Alan Randall (2010). Resource Economics. Cheltenham, United Kingdom, and Northampton, MA, United States.

Börjesson, M., and J Eliasson (2011). Experiences from the Swedish Value of Time study. Glasgow, United Kingdom: Proceedings of the European Transport Conference, Association of European Transport.

Börjesson, Maria, Mogens Fosgerau and Staffan Algers (2012). On the income elasticity of the value of travel time. Transportation Research. Part A: Policy & Practice, February 2012: 368-377.

Cass, David (1965). Optimum Growth in an Aggregative Model of Capital. Review of Economic Studies. 233-240.

COWI (2010). Real price adjustment of unit costs over time. (In Norwegian only. Norwegian title: Realprisjustering av enhetskostnader over tid.) Norwegian Public Roads Administration.

Fahlén, D., Thulin, E. and Vilhelmson, B (2010). What do people do when travelling? A study of passenger’s use of travelling time on regional public transport. (In Swedish only. Swedish title: Vad gör man när man reser? En undersökning av resenärers användning av restiden i regional kollektivtrafik.) Vinnova, Report VT 2010:15, Stockholm.

Flores, Nicholas and Richard Carson (1997). The Relationship Between Income Elasticities of Demand and Willingness to Pay. Journal of Environmental Economics and Management, 33, 287-295.

Hammitt, J. K. & Robinson, L. A. (2011). The income elasticity of the value per statistical life: Transferring estimates between high and low income populations. Journal of Benefit-Cost Analysis, 2 (1), pp. 1-27.

HEATCO (2006) (Developing Harmonised European Approaches for Transport Costing and Project Assessment). Deliverable 5 from the HEATCO project under the 6th EU framework programme.

Heide, Kim Massey, Erling Holmøy, Lisbeth Lerskau and Ingeborg Foldøy Solli (2004). Macroeconomic Properties of the Norwegian Applied General Equilibrium Model MSG6. Report 2004/18, Statistics Norway.

Hensher, David A (1977). Valuation of Business Travel Time. Oxford: Pergamon Press.

Her Majesty’s Treasury (2003). The Green Book. London.

Hjorthol, Randi (2008). Institute of Transport Economics (“TØI”) 983/2008.

Hökby, Stina and Tore Söderqvist (2003). Elasticities of Demand and Willingness to Pay for Environmental Services in Sweden. Environmental and Resource Economics 26: 361–383.

Jones, Charles I (1995). R&D-Based models of economic growth. Journal of Political Economy, 759-784.

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Kumar, Pushpam (ed.) (2010). The Economics of Ecosystems and Biodiversity: Ecological and Economic Foundations. London: Earthscan.

Lucas, Robert (1988). On the Mechanics of Economic Development. Journal of Monetary Economics, July 3-42.

Lyons, G. and Jain, J. Holley, D., (2006). The use of travel time by rail passengers in Great Britain. Centre for Transport and Society, Faculty of the Built Environment, University of the West of England, United Kingdom.

Mackie, P.J., M. Wardman, A.S. Fowkes, G. Whelan, J. Nellthorp and J. Bates (2003). Values of Travel Time Savings UK. Leeds, United Kingdom: Working Paper. Institute of Transport Studies, University of Leeds.

Magnussen, Kristin and Ståle Navrud (2010). Social cost of emissions of environmental toxins. (In Norwegian only. Norwegian title: Skadekostnader ved utslipp av miljøgifter.) Sweco Norway.

Millennium Ecosystem Assessment (2005). Ecosystems and Human Well-Being: Synthesis Report. Island Press.

Navrud, Ståle (2011). Willingness to pay for environmental goods – developments over time and use in Cost-Benefit Analysis (CBA). (In Norwegian only. Norwegian title: Betalingsvillighet for miljøgoder –utvikling over tid og bruk i Samfunnsøkonomiske analyser (SØA)) Presentation to the Expert Committee, 7 September 2011

Norwegian Public Roads Administration (2006). Handbook 140: Impact Assessments. (In Norwegian only. Norwegian title: Håndbok 140: Konsekvensanalyser.) Oslo.

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NOU 1998: 16 Green Paper, Cost-Benefit Analysis. Guidance on Using Profitability Assessments in the Public Sector. (In Norwegian only. Norwegian title: Nytte-kostnadsanalyser. Veiledning i bruk av lønnsomhetsvurderinger i offentlig sektor.) Ministry of Finance.

NOU 2003: 13 Competitiveness, Wage Formation and the Norwegian Kroner Exchange Rate. (In Norwegian only. Norwegian title: Konkurranseevne, lønnsdannelse og kronekurs.) Ministry of Finance, 125-128.

OECD (2012), Mortality Risk Valuation in Environment, Health and Transport Policies, OECD Publishing. http://dx.doi.org/10.1787/9789264130807-en

Pearce, David W. (1980). The Social Incidence of Environmental Costs and Benefits, in: T. O'Riodan and R.K. Turner (eds.): Progress in Resource Management and Environmental Planning, Volume 2, 63-87 Chichester: Wiley.

Ramjerdi, Farideh, Lars Rand, Inger-Anne F Sætermo and Kjartan Sælensminde. (1997) The Norwegian Value of Time Study. Institute of Transport Economics (“TØI”), Oslo.

Ramjerdi, Faridehm, Vegard Østli, Askill Halse, Nils Fearnley (2012), Value of travel time over time, Institute of Transport Economics (“TØI”)

Ramjerdi, Farideh, Stefan Flügel, Hanne Samstad and Marit Killi (2010) Report 1053B/2010. Institute of Transport Economics (“TØI”) and Sweco.

Ramsey, Frank P. (1928). A Mathematical Theory of Saving. Economic Journal, 543-559.

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Wardman, Mark (2004). Public transport values of time. Transport Policy, 363-377.

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WSP Analysis & Strategy (2010). Road users’ valuations of time – The national time value study 2007/08. (In Swedish only. Swedish title: Trafikanters värdering av tid – Den nationella tidsvärdesstudien 2007/08.) WSP report 2010:11.

Footnotes

1.

As long as producers are facing increasing marginal costs of production, expanded demand for these goods will result in higher prices. Consequently, economic theory suggests that when a country experiences economic growth, demand for luxury goods will grow more, and demand for necessities will grow less, than average, all else being equal. This will affect relative prices. A good or a service is defined as a luxury good if the income elasticity of demand of such good is greater than 1. By income elasticity of demand is meant how demand changes when income increases by 1 percent.

2.

Broadly defined (including human capital, natural resources, etc.)

3.

The theory that the prices of services increase by more than the prices of physical goods is often termed the Baumol Effect (Baumol and Bowen, 1966). Baumol and Bowen noted, in a well-known example, that the number of musicians needed to play one of Beethoven’s string quartets is still the same as in the 18th and 19th century. The lack of productivity improvement within entertainment is descriptive of many sectors where the work performed is the actual production. In their own words: “the work of the performer is an end in itself, not a means for the production of some good” (page 164).

4.

Some countries adopt more detailed classifications of time, for example by defining commuting time as a separate category. However, it may argued that reduced commuting time will result in either more time at work or more private time for each person. The Committee has therefore chosen to maintain the classification from the NOU 1997: 27 Green Paper.

5.

See Chapter 2.5 in Chapter 2 concerning general rules for the pricing of market goods for cost-benefit analysis purposes.

6.

See also Fahlén, Thulin and Vilhelmson (2010), which looks at Swedish data for both bus and train journeys, as well as Lyons, Jain and Holley (2006), which studies train journeys in England.

7.

The method of correcting for the utilisation of time is referred to in the literature as the cost savings principle. A detailed discussion can be found in Chapter 3 of Mackie, et al. (2003). The said article also discussed Hensher’s formula. Hensher (1977) systematises the use of time savings from business travel. The formula distinguishes between time savings used for work and time savings used for leisure. Hensher adjusts for the value of such time during the journey as can be used for work, as well as for the comfort level of the traveller.

8.

The value of private time is also discussed in the NOU 1997: 27 Green Paper.

9.

See also Chapter 2.

10.

An objection against this is again that more comfortable journeys will be reflected in lower wage growth than in a situation where travel comfort is not improved. Based on this assumption it is sufficient to use wage growth as a measure of increases in economic travel costs; all improvements for travellers in travel methods during work are reflected in wage changes.

11.

The literature terms this elasticity the “income elasticity of demand” with respect to the value of time. However, the income elasticity of demand will normally refer to how the quantity demanded of a good or a service changes when income increases by 1 percent. As far as the value of time is concerned, it is not a matter of how the quantity demanded changes, but how the willingness to pay changes when income increases. In this Chapter we therefore refer to this as simply the elasticity or as the elasticity of the willingness to pay.

12.

It is not specified whether these are gross or net wages.

13.

The HEATCO report also proposes that values of time relating to commercial traffic be adjusted by an income elasticity of demand of 0.7, based on the reasoning that the time costs can primarily be related to the driver and crew.

14.

Goods or services are defined as luxury goods if the income elasticity of demand with respect to such goods is in excess of 1, i.e. that the percentage increase in the demand for such goods exceeds the percentage increase in income. All else being equal, prices of luxury goods will increase relative to the average price level.

15.

In cases where an environmental good may be irredeemably lost, a “quasi-option value” may be attached to not destroying such good. More on this in Chapter 8.

16.

In contrast, an “inferior good” has an income elasticity of demand of less than zero, whilst “normal goods” have elasticities of between zero and one. See also footnote 17.

17.

In Chart 4.3, a change in demand will represent a horizontal shift, whilst a change in the willingness to pay will be vertical.

18.

One may model, by using life-cycle models, the relationship between the willingness to pay for risk reductions and income. One theoretical finding from such models is that VSL ≥ remaining lifetime consumption, i.e. that the willingness to pay for life must be at least as high as the value of remaining lifetime consumption (or income) since the model does not include the willingness to pay for life in itself (see Hammitt and Robinson (2011)).

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