Economic valuation and stated preferences techniques

The framework of economic valuation is cost benefit analysis (see the previous section), that is, a comparison of all the advantages and disadvantages of a range of alternative solutions in monetary terms. If a good or service contributes positively to human wellbeing, it has an economic value. In economic valuation, willingness to pay (WTP) serves as a weighing method to state the trade-off required for the policy options being appraised. Economic valuation helps governments to make decisions on environmental protection or other policies based on people’s statements. Moreover, it is a method used to investigate people’s WTP for a benefit, or their willingness to accept (WTA) payment in exchange for losses. With regard to the notions used in economic valuation,

The term ‘choice’ is equivalent to ‘decision’, ‘stated preference’ or ‘economic transaction’. Rational, preference-based decisions increase individual welfare. This means the respective transactions are efficient. The individual demand can be inferred from a measurement of the increase in welfare caused by an increased provision of a particular good. (Fischer 2004 p. 28)

There are three categories of economic valuation: Benefits transfer (BT), revealed preferences (RP), and stated preferences (SP) (Bateman et al. 2002). Hanley et al.

(2006) describe benefits transfer as a method for taking value estimates from original

studies, adjusting them, and transferring them to a new context. The revealed preferences method, which is also known as indirect valuation, depicts the ways in which a non-marketed good influences actual markets for other goods through a proxy market. An example of revealed preferences would be the measurement of the economic value of noise disturbance as reflected in house prices. Houses in noisy areas are supposed to be cheaper compared to houses in quieter, but otherwise comparable areas. Stated preference methods are direct valuation methods and were developed to value environmental resources that are not traded in any market, including proxy markets (Birol et al. 2006). Stated preference methods use a hypothetical choice scenario, which is based on what people say rather than on what they do (for a theory of preference see Russell & Wilkinson 1979). People are asked in a questionnaire to attach an economic value to goods and services in the constructed or hypothetical market (Pearce & Özdemiroglu 2002). The stated preference method was employed in the current study. However, there is a question as to how reliably stated preferences express the true preferences of an individual. One important problem WTP (or the stated preferences method) faces is that

it does not omit preferences based on ignorance and haste, preferences deformed by malice, resentment or fear […]. Still less does it ask or permit its users to ask […] as to whether even corrected preferences could give us a reliable way of ranking social alternatives. (Nussbaum 2001 p. 193)

This leads us to ask how, in fact, preferences emerge. Slovic (2003 p. 500) researched the construction of preferences and found that, if the choice task is complex and important, ‘decision making is a highly contingent form of information processing, sensitive to task complexity, time pressure, response mode, framing, reference points, and numerous other contextual factors’. Hence ‘truth ultimately resides in the process, rather than in the outcome’ (Slovic ibid. p. 500). In short, preferences and values are not discovered by stated preference studies, but they are actively constructed during the choice process (Schkade & Payne 1994; Slovic 2003; Svedsäter 2003). In addition to the issue of preferences being constructed on the spot, one must also question whether peoples’ choice behaviour is rational (see e.g., Fischer et al. 1999). McFadden (1999) states that choice behaviour can be described as a decision process produced by beliefs and perceptions based on available information and influenced by affect, attitudes, and preferences. And to what extent does the available information affect choice behaviour? It was found that the nature of information provided in stated

preference studies can strongly influence WTP estimates. If a message is relevant to the respondent, the information is carefully processed. If respondents lack prior knowledge on the good in question, information bias may occur. Detailed information on the planned transaction provided in the questionnaire cannot eliminate the problem of information bias (Ajzen et al. 1996). Despite these findings, stated preferences can be considered a useful method for eliciting peoples’ views on planned economic transactions such as the implementation of a credit system. It clearly should not be the only method relied on, but it is one that yields valuable information on individuals’

opinions. In the area of marketing, discrete choice models have been demonstrated to be a valuable method for predicting market share for new products based on consumers’ expressed preferences between choice alternatives (Magidson et al. 2003).

There are two main stated preference techniques:

- Choice modelling (CM) seeks to elicit people’s preferences for the individual characteristics of non-marketed goods or services. This technique is suitable for determining WTP or acceptance of changes in the characteristics of the item in question. It focuses on rankings, which are easier for respondents to deal with.

Money values are introduced into each choice option in order to provide a common base.

- Contingent valuation (CV) concentrates on a non-marketed good or service as a whole. This technique is appropriate if there is a clear need for analysis based on the whole good rather than on its attributes. With contingent valuation, respondents are asked direct questions about their maximum or minimum WTP for a good or service. The context is a hypothetical but realistic scenario that includes a description of the item in question and the proposed payment vehicle (for instance, a tax or donation) (Pearce & Özdemiroglu 2002).

The results of a stated preference study serve to estimate welfare changes from the proposed scenario.

The overall aim of this study is to assess farmers’ relative preferences for different loan characteristics, and the impact of those preferences on the implementation of credit unions. The choice modelling method was chosen over the contingent valuation method because relative preferences for the attributes (different loan characteristics) of the good in question (the loan) had to be assessed, and not preferences for the whole good (the loan). As loans are a marketed good, the concept

of economic valuation does not entirely apply because it is primarily concerned with non-marketed goods, such as the environment. Nevertheless, of the various types of economic valuation, stated preference techniques may be considered the most appropriate methodology for this study if we use it in the sense of marketing research (see Magidson et al. 2003). For this purpose, a hypothetical credit market has been created, so that respondents can directly express their WTP for different loan schemes.

The outcomes of the stated preference analysis show which loan characteristics the population in the research area prefer. Stated preference techniques were chosen because in the research region, Shida Kartli, local residents’ preferences with regard to credit systems and loan characteristics had not previously been investigated in detail.

The constructed rural finance market consists of two rural credit systems: loans with individual liability and loans with joint liability. Respondents had to choose between the two credit systems, and their preferences for the different loan attributes of the chosen loan type were examined. The value attached to a good or item — in this case, the rural credit system selected — was revealed through the hypothetical credit market, which contained different prices for different credit systems. Prices were expressed in interest and commission paid for loans. Respondents’ preferences with regard to the two possible rural credit systems and their various attributes were investigated through a survey containing a choice experiment.