Estimating Consumers’ Willingness to Pay for the Individual Quality Attributes with DEA

In a highly competitive environment a product’s commercial success depends increasingly more upon the ability to satisfy consumers’ preferences that are highly diversified. Since a consumer product typically comprises a host of technological attributes, its market value incorporates all of the individual values of technological attributes. If the willingness-to-pay (WTP) for individual technological characteristics of a product is known, one can conjecture the overall WTP or the imputed market price for the product. The market price listed by the producer has to be equal to or lower than this WTP for the commercial survival of the product. In this paper we propose a methodology for estimating the value of individual product characteristics and thus the overall WTP of the product with DEA. Our methodology is based on a model derived from the consumer demand theory on the one hand, and the recent theoretical developments on the flexible DEA frontiers on the other hand. The paper also presents a real case study for the mobile phone market, which is characterized by its high speed of innovation. The suggested model and its empirical applications has implications for the extension of DEA methodology to the estimation of market value of a complex multi-attribute product and/or of a value of quality attribute that is not explicitly marketable in isolation. We also expect that the framework will shed some light on the successful way of product differentiation when the cost information for individual characteristics is available

Comparing Efficiency Across Markets: An Extension and Critique of the Zhang and Bartels (1998) Methodology

The use of non-parametric frontier methods for the evaluation of product market efficiency in heterogeneous markets seems to have gained some popularity recently. However, the statistical properties of these frontier estimators have been largely ignored. The main point is that nonparametric frontier estimators are biased and that the degree of bias depends on specific sample properties, most importantly sample size and number of dimensions of the model. To investigate the effect of this bias on comparing market efficiency, this contribution estimates the efficiency for several datasets for two main product categories. Following Zhang and Bartels (1998), these results comprise re-estimates for the larger samples limiting their size to that of the smaller samples when the model dimensions for different samples are identical. Furthermore, sample sizes are adjusted to mitigate the eventual differences in dimensions in specification. This allows comparing market efficiency for different markets on a more equal footing, since it reduces the bias effect to a minimum making the comparison of market efficiency possible. However, the article also points out the critical limitations of this Zhang and Bartels (1998) approach in certain respects. Apart from reporting these negative results, we also offer some suggestions for future work.Market Efficiency, Heterogeneous Product Markets, Bias, Monte-Carlo Simulation

Measuring the value of product characteristics in the presence of price dispersion

Modeling the price of multi-attribute products generally requires an assessment of each attributes’ market value. In the presence of price dispersion, when similar products are sold at different prices, hedonic pricing models provide users with biased estimates of attribute value. This paper develops the hedonic pricing literature by proposing data envelopment analysis as a prior means of identifying a sub-sample of products which, after adjusting for attribute provision, display no price dispersion. These products then display a homogenous link between attributes and price, which can be modeled using hedonic pricing. This paper implements and evaluates this two-stage approach using 1000 observations from the UK mortgage market