由於以往在願付價格的研究中，並未考慮到價格再高都願意支付的受訪者，以及價格再低都不願意支付的受訪者，因此可能會造成估計結果的偏差。本文除了沿用Tsai(2005)所建議採用的三要素混合模型，將受訪者區成價格再高都會願意付的人、願意付合理價格的人以及價格再低都不願意付的人等三類受訪者，且將願意付合理價格者的願付價格透過加速失敗模型(accelerated failure time model，簡稱AFT model)來作評估外，進一步就願意付合理價格的人可能會受到起價點的影響或是有「定錨效果」(anchoring effect)產生的問題來作探討，並就CVDFACTS的高血壓之願付價格資料來作實證分析。結果發現教育程度越高、收入越高以及男性對於能降低罹患心臟血管相關疾病新藥的願付價格也越高。此外我們也發現此筆資料確實有起價點偏誤(starting point bias)的情形。

In the past, studies on willing-to-pay (WTP) usually assume that all the respondents are willing to pay a reasonable price for a non-market good. In reality, some of the respondents might be willing to pay a very high price, while some others unwilling to pay anything. Following Tsai(2005), we adopt a three-component mixture model to take into account these there three types of respondents and modeling those who are willing to pay a reasonable price with an accelerated failure time (AFT) model. In addition, with a slight modification, we also incorporate issues regarding “starting point bias” and “anchoring effect” into the model. An empirical study based on the data collected from “CVDFACTS” shows that males, respondents with higher educational level, and those with higher family income are willing to pay higher prices for a new hypertension treatment. In addition, it is quite likely that “starting point bias” exists in the dataset.

一、 中文部分
吳珮瑛、劉哲良、蘇明達(2005)「受訪金額在開放選擇條件評估支付模式的作用－引導或是誤導」，農業經濟半年期刊，77期：1-43頁。

葉寶文(2002)「風險性之行為決策分析與其願付價值之研究」，東吳大學經濟系博士論文。

二、 英文部分
Alberini, A.,(1995), “Optimal Designs For Discrete Choice Contingent Valuation Surveys:Single-bound, Double-bound, and Bivariate Models”, Journal of Environmental Economics and Management, 68：287-306.

Alberini, A., B.Kanninen, and R.T. Carson, (1997), “Modeling Response Incentive Effects In Dichotomous Choice Contingent Valuation Data”, Land Economics ,73(3)：309-325.

Bishop, R. C. and T. A. Heberlein, (1979), “Measuring Values of Extramarket Goods: Are Indirect Measure Biased?”, American Journal of Agricultural Economics, 61：926-930.

Blamey, R.K., J.W. Bennett, and M.D.Morrison, (1999), “Yea-Saying in Contingent
Valuation Surveys”, Land Economics, 75(1)：126-141.

Boyle, K. J., R. C. Bishop, and M. P. Welsh, (1985), “Starting Point Bias in Contingent Valuation Bidding Games”, Land Economics, 61(2)：188-194.

Chen, C. H., C. F. Horng, and Y. C. Wu, (2004), “A Mixture Regression Model in Event History Analysis with Non-Susceptibility and General Interval Censorship”, unpublished manuscript.

Chien, Y.-L., C.Huang, and D. Shaw, (2005), “A General Model of Starting Point Bias in Double-Bounded Dichotomous Contingent Valuation Surveys”, Journal of Environmental Economics and Management, 50：362-377 .

Farewell, V. T. and Prentice, R. L. (1977) “A Study of Distributional Shape in Life Testing”, Technometrics, 19：69-75.

Hanemann, M., J. Loomis, and B. Kanninen, (1991), “Statistical Efficiency of Double-Bounded Dichotomous Choice Contingent Valuation”, American Journal of Agricultural Economics, 73：1255-1263.

Herriges, J.A. and J.F. Shogren, (1996), “Starting Point Bias in Dichotomous Choice Valuation with Follow-Up Questioning”, Journal of Environmental Economics and Management, 30(1)：112-131.

Klein, J. P. and Moeschberger, M. L. (1997), “ Suvival Analysis: Techniques for Censored and Truncated Data”, New York: Springer.

Lawless, J. F. (2003), “ Statistical Models and Methods for Lifetime Data”, 2nd edition. New Jersey：John Wiley.

Tsai, I.-L. ,(2005), “A Three-component Mixture Model in Willingness-to-pay Analysis for General Interval Censored Data” ,unpublished master’s thesis, National Chengchi University, Taiwan.

Whitehead, J.C., (2002), “Incentive Incompatibility and Starting-Point Bias in Iterative Valuation Questions”, Land Economics, 78(2)：285-297.

Yamaguchi, K. (1992),“Accelerated Failure-time Regression Models with a Regression Model of Surviving Fraction,” Journal of the American Statistical Association, 87：284-292.