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Conjoint Analysis versus Contingent Valuation: estimating Risk Values and Death Risk Equivalents in Road Traffic Krister Hjalte Department of Economics, Lund University, Sweden, e-mail: [email protected] Anna Norinder The Swedish Institute of Health Economics, Lund, Sweden, e-mail: [email protected] Anna Traw~n Department of Technology and Society, Lund University, Sweden, e-mail: [email protected] 1. Introduction Eliciting preferences for non-market goods has traditionally been done by help of stated preference methods, which could be seen as a group of direct methods in comparison to those indirect methods usually denoted revealed preference methods. The direct valuation methods include variants like contingent valuation (CV) and conjoint analysis (CA). The CV method has since long time been the most used technique in environmental economics but is also used in health and transport economics, even though more sparsely. The dominant technique in transport economics for example in valuation of travel time savings has been the CA or closely related methods, in the transport economics literature usually named stated preference methods. An extension of the original CA is sometimes called choice experiments that involve more experimental and involved analysis of choice behaviour. The terminology as well as the advantages and drawbacks with these methods are not quite clear demanding additional research for example comparing different stated preference methods according the influence of the context of the questionnaire and according the psychological process of making choices in different formats. For instance, it may be quite different to state a maximum willingness to pay for a specified good than choosing among goods with assigned prices. The purpose of this pilot study is to compare two direct valuation methods, the CV and CA, for estimating risk values for fatal and non-fatal road traffic accidents as well as death risk equivalents. The risk value for a fatal accident, the value of a statistical life, is defined as the average willingness to pay for a specified risk reduction divided by that risk reduction. Accordingly similar risk values are calculated for serious disabling injuries and slight injuries. With death risk equivalents, the health effects are valued in a common metric where the injury is presented in relation to death. A fatal injury has the value 139 one and good health has the value zero. This implies that for example two injuries which both are valued to 0.5 death risk equivalent each, together correspond to one fatal injury. 2. Case study Results from two studies, one CV (Persson et al. 2000) and one CA (Traw~n et al. 1999) are compared, both conducted in Sweden 1998 respectively 1999. The CV study was designed as a postal questionnaire and the CA study was performed as an assistant based pilot study with portable computers. The main purpose of the former study was to estimate the value of a risk reduction in road traffic for a slight, a serious disabling and a fatal injury. The purpose of the second one was to compare the results from the CV study with those from other stated preference methods for example CA. It was also possible to estimate the death risk equivalents for these injuries with both methods. All individuals in both studies were asked identical questions on background factors such as gender, age, household income, level of education, experience of road accidents etc. The respondents were provided with information on annual, baseline risks of dying or getting hurt in road traffic accidents. In order to make the risk perception scenarios as clear as possible each of these baseline risks were illustrated as a number of black filled squares in a square net encompassing 100,000 squares. 2.1 Contingent valuation The CV study was sent to 5,650 randomly chosen Swedes between the ages 18 and 74 (Persson et al. 2000) in 1998. An open-ended willingness to pay (WTP) question was chosen as the main valuation format and the individuals were asked to state how much he/she was willing to pay for a certain reduction in the risk of being killed in a traffic accident. The study was split into different sets of questionnaires where the size of the risk reduction was either 30 or 50 percent. Before asking the WTP question the pure private character of the risk reduction was carefully pointed out for the user, also stressing that it was confined to safety perse. This was described as: The safety device is not inconvenient, ugly or complicated to wear. Actually you do not notice it. However, # is only you personally who can benefit from it. The risk reduction has duration of just one year and will only affect your death risk. Other people's risk is not affected and an accident will not have any impact on your financial situation as we assume that all expenditures and financial losses will be covered by the insurance system. All respondents were asked to make voluntary direct payments for a safety device and to estimate their own annual risk for a fatal injury. A risk reduction 140 was then valued from the individuals' own perceived annual risk for death in a traffic accident. The CV question had the following appearance: How much would you at the most be willing to pay for reducing your own annual risk of dying in a traffic accident by one third (one fifth)? SEK ..................... per year 2.2 Conjoint analysis The CA study included 200 interviews and was performed with portable computers in Lund, Sweden. Respondents were found in parks and supermarkets during the summer of 1999. This study included not only CA questions, but also standard gamble and risk-risk trade off methods (Traw6n et al. 1999). For each of these methods, games with questionnaires were constructed for a slight, a serious disabling and a fatal injury, in total ten games. However, each individual answered only three games for one kind of injury, for example: risk-risk trade of, standard gamble and CA safety device, for a serious disabling injury. Before the game the respondents answered a '~est question" where one of the alternatives was dominant, i.e. one alternative was most advantageous regarding all attributes. This test was done to make sure that the respondents had understood the question and to test for non-logical answers. In the games however, alternatives that were dominated were not included in the choice set. The respondents answered two different CA games, each involving pair-wise choices with six choice pairs. In each choice pair, alternative descriptions of living areas or safety devices were presented according to a number of attributes with various levels. The alternatives were presented randomly and the respondents were asked to select alternative A or alternative B. In one of the CA games the respondents were asked to choose between two similar safety devices. The price and the risk reduction that the safety device would bring differed in the two scenarios. The price of the safety device varied between SEK 20, 100, 500, 1,000, 2,500, 5,000 and 10,000 and the risk reduction varied between 10, 30, 50 and 99 percent. The s~ifety device was described as: It is not inconvenient, ugly or complicated to wear. The risk reduction has duration of just one year and it is only you personally who can benefit from it. 141 An example of the CA question regarding safety devices is illustrated below. SUPPOSE YOU SHOULD PURCHASE A SAFETY DEVICE. WHICH AL TERNA TIVE DO YOU PREFER? ALTERNA TIVE A Price of the safety device SEK1, 000 Reduces your annual risk for a fatal injury with 30% 1) 2) AL TERNA TIVE B Price of the safety device SEK5,000 Reduces your annual risk for a fatal injury with 50% Alternative A Alternative B In the other CA game the respondents were asked to choose between two alternative living areas, which were described by three attributes: cost of accommodation, travel time to work/school and risk for a road accident. The alternatives that the respondent chose between were described as comparable with the original situation of living, i.e. the respondent should imagine that the size and standard of the flatJhouse and living area in the alternatives correspond to the original situation of living. To make the hypothetical choice as realistic as possible, the cost of accommodation and travel time varied depending on what the respondent had answered earlier about his/her own situation. Those respondents who had a travel time to work/school of 0-20 minutes had to choose between the levels 10, 20 and 30 minutes in the game. Respondents with a travel time of 21 minutes or more had to choose between the levels 20, 40 and 60 minutes. In the similar manner, the level of the cost of accommodation in the game depended on the respondents' real cost. For example, for a respondent with a cost of accommodation between SEK0 and 33,000 per year the levels in the game vary between SEK26,000, 27,000 and 29,000, see Table 1. Table 1: Levels of the cost of accommodation in the CA game, SEK Real cost of accommodation Leve~ ~ ~ e ~ame 26,000 27,000 0-33,000 48,000 50,000 34,000- 60,000 77,000 80,000 61,000- 100,000 130,000 135,000 101,000 and m o ~ 29,000 56,000 87,000 149,000 The levels of the risk attribute for a fatal injury varied between 2, 7 and 13 in 100,000 per year. In the game with a serious disabling injury the risk varied between 23, 40 and 52 in 100,000 per year, and for a slight injury between 200, 500 and 800 in 100,000 per year. These attributes and levels form a lot of possible combinations. Therefore an experimental design with 9 alternatives, was constructed. Each respondent was presented with 6 pairs of alternative descriptions of living areas. 142 The CA question regarding living areas had the following appearance: SUPPOSE YOU SHOULD MOVE. WHICH ALTERNATIVE DO YOU PREFER? Imagine that you use same transport mode to work/school as you do today. ALTERNATIVE A Cost of accommodation SEK48,000 per year (SEK4,000 per month) Travel time to work~school 30 minutes Risk for a fatal road accident 13 in 100,000 1) 2) ALTERNATIVE B Cost of accommodation SEK50, 000 per year (SEK4,167 per month) Travel time to work~school 20 minutes Risk for a fatal road accident 7 in 100,000 Alternative A Alternative B 3. Results Both the CV and the CA methods have been used to estimate a value of statistical life (VOSL), i.e. the marginal rate of substitution of wealth for risk as well as death risk equivalents. In both methods the value of risk reduction for a fatal, serious disabling and slight injury due to a traffic accident was estimated. Because we do not know in what way the respondents understood the attributes risk and cost of accommodation, we estimated the VOSL in three ways for the CA game where the respondents chose between living areas, in the calculations of VOSL with the CA method named "living area/family" the attributes cost of accommodation and risk for a road accident are used as they are presented in the game. In "living area/consumer" the estimates are made regard to the households' consumption, i.e. the cost of accommodation in the alternatives is divided by a weight of consumption for the family. This weight of consumption depends on the number of famUy members and the age of the children (SCB 1997). If the respondents care about their families, the risk for the family should be included in the analysis. In "living area/family risk", the risk in the alternatives is multiplied with the numbers of family members. Thereby we suppose that the family members exhibit the same risk and that the risks are independent of each other. 143 Table 2: Value of risk for different injuries, million SEK Method Slight injury CV 30% risk red. Mean 0,9 CV 50% risk red. 0,5 Serious disabling injury Median Mean Median 0,4 20,0 8,8 0,2 11,0 5,3 Fatal injury Mean 95,2 Median 33,3 82,7 40,0 CA safety device 2,3 39,0 208,2 CA living area / family 2,4 66,8 242,0 CA living area / consumer 1,4 38,4 137,6 CA living area / family risk 1,2 29,7 113,7 1The VOSL for fatal injury in the CV study is calculated for the respondents that stated their own perceived annual risk to 5 in 100,000 while the VOSL in the CA study is calculated with the average risk 6 in 100,000. The estimates of a statistical life, i.e. the marginal rate of substitution of wealth for risk, from the CA study are all higher than those estimated by the CV method see Table 2. With the CV method the VOSL is between SEK33 and 95 million depending on the risk reduction and if you look at the mean or median value. The corresponding values with the CA method vary between SEK114 and 208 million. The health effects may be valued in a common metric, death risk equivalent, where the seriousness of the injury is presented in relation to death. The death risk equivalents are calculated as the risk value for a non-fatal injury divided by the risk value for a fatal injury. Table 3: Death risk equivalents for different injuries Method CV 30% risk reduction CV50% risk reduction CA safety device CA living area / family CA living area / consumer CA living area / family risk Slight injury Mean 0.009 0.006 Serious disabling injury Median -Mean Median 0.012 0.210 0.264 0.005 0.133 0.133 0,011 0,010 0,010 0,011 144 0,187 0,276 0,279 0,261 Our empirical findings indicate that the ratios for different states of health in relation to death, the death risk equivalents, are quite similar for the methods compared, see Table 3. The death risk equivalent for a serious disabling injury varies between 0.133 and 0.279. The lowest value is calculated by the CV method with 50 percent risk reduction while the highest value is estimated by the CA method with consideration to the households' consumption. For a slight injury the death risk equivalent varies between 0.005 and 0.012. The former value represents the median value from the CV method with 50 percent risk reduction. The highest value is also calculated by the CV method but with a risk reduction of 30 percent. 4. Discussion The comparison between estimates of the value of a statistical life derived by the CV method and the CA method showed that the latter method yielded higher values than the former. Likewise, when estimating risk values for nonfatal injuries, those derived by the CA method were higher than those derived by the CV method. There are several possible explanations for these results. First, the theoretical foundation differs between the elicitation methods. The values from the CA method are calculated by use of the random utility theory. This would have been comparable to the CV method, had this been a binary choice question (Boxall et al. 1996). However, the CV study used open-ended questions and therefore the results are not theoretically equivalent. Second, another aspect, highlighted by Boxall et al. (1996), is that in a CV format the respondents fail to consider substitutes, a problem that is obviously not apparent in a CA format. This has also been discussed in Stevens et al. (2000) where CV estimates are compared to CA. Contrary to Boxall et al., Stevens et al. argue that because CA estimates are sensitive to the model specification the method should be used with care, even though Stevens do not use the same pair-wise choice model as Boxall, but in stead use a ranking exercise. The model specification also includes levels of the cost attributes chosen. These levels determine the upper and lower boundaries-in between which the WTP estimates will fall. Hanley et al. (1998) also compare the CV and CA methods and conclude that CA is a promising method although many design issues are unresolved. Third, in our CA model no status quo alternative was included. This means that the respondents were forced to choose an alternative where they had to pay something. In the CV study, however, we accepted an answer of zero crowns. If these zero-bids are excluded in the calculations of mean values, the mean values from the CV method rise to approximately the same level as the ones from the CA method. A disadvantage of including a status quo alternative is that it could give a downward bias, since it is preferred to nonfamiliar alternatives (Salkeld et al. 2000). In our CA model we tried to replicate the scenario described in our CV study in order to compare the methods of eliciting a value of a statistical life. Despite ]45 our efforts, the comparison failed in a number of aspects. The first lesson from the exercise is that comparing CV and CA estimates demands a binary choice CV format. Constructing a binary choice bid vector is equally difficult as choosing the levels of the attributes in a CA format. Likewise, constructing a hypothetical scenario entails the same difficulties in both formats. However, the CA approach does not suffer from a "yea-saying" behaviour often connected to a binary choice CV, and the consideration of substitutes to a scenario is clearer in a CA format. Finally, an advantage with the CA format is that it could be conceptually more easily understood, and therefore yield values more consistent with a choice in a real life situation. 146 References Boxall, P. C., Adamowicz, W. L., Swait, J., Williams, M., Louviere, J. (1996) A comparison of stated preference methods for environmental valuation, Ecological Economics, 18, 243-253 Hanley, T. H., Wright, R. E., Adamowicz, V. (1998) Using choice experiments to value the environment - Design issues, current experiences and future prospects, Environmental and Resource Economics, 11 (3-4), 413-428 Persson, U., Hjalte, K., Nilsson, K., Norinder, A. (2000) Vardet av att minska risken for vagtrafikskador- Berakning av riskvarden for dOdliga, genomsnittligt sv&ra och lindriga skador med Contingent Valuation metoden, Institutionen for Teknik och Samh~ile, Lunds Tekniska H0gskola, Lunds Universitet, Bulletin 183 Salkeld, G., Ryan, M., Short, L. (2000) The veil of experience: do consumer prefer what they know best? Health Economics, 9, 267-270 SCB (1997) Inkomstf0rdelsningsunders0kningen 1995, Statistiska meddelanden, Be 21 SM 9701 Stevens, T. H., Belkner, R., Dennis, D., Kittredge, D., Willis, C. 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