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題名 雙界二分選擇詢價法-願付價格之起價點偏誤研究
作者 吳孟勳
貢獻者 江振東
吳孟勳
關鍵詞 三要素混合模型
加速失敗模型
起價點偏誤
定錨效果
three-component mixture model
accelerated failure time model
starting point bias
anchoring effect
CVDFACTS
日期 2006
上傳時間 2009-09-14
摘要 為了處理在願付價格的研究中,極端受訪者對於估計結果所造成的誤差。本文沿用Tsai(2005)所建議採用的三要素混合模型,將受訪者區分為價格再高都願意支付、願意支付合理價格以及價格再低都不願意支付等三種類型。在評估願付價格時,以加速失敗模型(accelerated failure time model,簡稱AFT model)針對願意支付合理價格的受訪者進行估計,並且在考慮不同起價點可能會造成不同程度的起價點偏誤(starting point bias)或是定錨效果(anchoring effect)的情形下,提出一個起價點偏誤調整模型來做探討。我們並以CVDFACTS中的高血壓之願付價格資料進行實證分析。分析結果發現,教育程度越高的男性對於能降低高血壓病患罹患心臟血管相關疾病之新藥願意付較高的金額。此外我們也發現在此筆資料中,不同起價點確實會造成不同程度的偏誤,經由偏誤調整後會得到較高的願付金額。
A study of willingness-to-pay often suffers from the bias introduced by extreme respondents who are willing to or not willing to pay any price. To overcome the problem, a three-component model proposed by Tsai (2005) is adopted. Under such a circumstance, respondents are classified into three categories, i.e. respondents who are willing to pay any price, unwilling to pay any price, or willing to pay a reasonable price. The willingness-to-pay for those subjects who are willing to pay a reasonable price is again modeled by an accelerated failure time model (AFT model). In this study, we, however, propose an unified model that allows us to look into the issue related to starting point bias and anchoring effect, simultaneously.
     Willingness-to-pay for cardiovascular disease treatment from a longitudinal follow-up survey- CVDFACTS, is investigated using the new model. Through the use of the model, we are able to detect the effects of starting point biases, and make a proper adjustment accordingly. Our analysis indicates that male respondents with higher education level have an inclination to pay higher price for the new treatment. Besides, we also discover that starting point bias does exist in this dataset.
參考文獻 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」。博士論文,東吳大學經濟系。
劉韶翔(2006)「三要素混合模型探討-雙界二分選擇詢價法之應用」。碩士論文,政治大學統計研究所。
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.
Bateman, I., (2002), “Economic valuation with stated preference techniques:a manual”, Edward Elgar Pub
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 R. L. Prentice, (1977), “A Study of Distributional Shape in Life Testing”, Technometrics, 19:69-75.
Frydman, H. ,(1994), “A Note on Nonparametric Estimation of the Distribution Function from Interval-censored and Truncated Observations”, Journal of the Royal Statistical Society, Series B, 56, 71-74.
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 M. L. Moeschberger, (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.
Moore, R. J. ,(1982), “Algorithm AS 187: Derivatives of the Incomplete Gamma Integral”, Applied Statistics, 31, 330-333.
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.
Turnbull, B. W. ,(1976), “The Empirical Distribution Function with Arbitrarily Grouped Censored and Truncated Data”, Journal of the Royal Statistical Society, Series B, 38, 290-295.
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.
描述 碩士
國立政治大學
統計研究所
94354017
95
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0094354017
資料類型 thesis
dc.contributor.advisor 江振東zh_TW
dc.contributor.author (Authors) 吳孟勳zh_TW
dc.creator (作者) 吳孟勳zh_TW
dc.date (日期) 2006en_US
dc.date.accessioned 2009-09-14-
dc.date.available 2009-09-14-
dc.date.issued (上傳時間) 2009-09-14-
dc.identifier (Other Identifiers) G0094354017en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/30919-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 統計研究所zh_TW
dc.description (描述) 94354017zh_TW
dc.description (描述) 95zh_TW
dc.description.abstract (摘要) 為了處理在願付價格的研究中,極端受訪者對於估計結果所造成的誤差。本文沿用Tsai(2005)所建議採用的三要素混合模型,將受訪者區分為價格再高都願意支付、願意支付合理價格以及價格再低都不願意支付等三種類型。在評估願付價格時,以加速失敗模型(accelerated failure time model,簡稱AFT model)針對願意支付合理價格的受訪者進行估計,並且在考慮不同起價點可能會造成不同程度的起價點偏誤(starting point bias)或是定錨效果(anchoring effect)的情形下,提出一個起價點偏誤調整模型來做探討。我們並以CVDFACTS中的高血壓之願付價格資料進行實證分析。分析結果發現,教育程度越高的男性對於能降低高血壓病患罹患心臟血管相關疾病之新藥願意付較高的金額。此外我們也發現在此筆資料中,不同起價點確實會造成不同程度的偏誤,經由偏誤調整後會得到較高的願付金額。zh_TW
dc.description.abstract (摘要) A study of willingness-to-pay often suffers from the bias introduced by extreme respondents who are willing to or not willing to pay any price. To overcome the problem, a three-component model proposed by Tsai (2005) is adopted. Under such a circumstance, respondents are classified into three categories, i.e. respondents who are willing to pay any price, unwilling to pay any price, or willing to pay a reasonable price. The willingness-to-pay for those subjects who are willing to pay a reasonable price is again modeled by an accelerated failure time model (AFT model). In this study, we, however, propose an unified model that allows us to look into the issue related to starting point bias and anchoring effect, simultaneously.
     Willingness-to-pay for cardiovascular disease treatment from a longitudinal follow-up survey- CVDFACTS, is investigated using the new model. Through the use of the model, we are able to detect the effects of starting point biases, and make a proper adjustment accordingly. Our analysis indicates that male respondents with higher education level have an inclination to pay higher price for the new treatment. Besides, we also discover that starting point bias does exist in this dataset.
en_US
dc.description.tableofcontents 第一章 緒論 1
     
     第二章 相關理論與文獻回顧 3
     
     第三章 理論架構與分析模型
     一、三要素混合模型 8
     二、加速失敗模型 13
     三、起價點偏誤調整模型 15
     
     第四章 實證分析
     一、資料說明 22
     二、實證分析結果 28
     三、願付價格平均值與中位數之估計 39
     
     第五章 結論與討論事項
     一、結論 42
     二、討論事項 42
     
     參考文獻 44
     附錄
     附錄一 47
     附錄二 57
     附錄三 58
     附錄四 61
     附錄五 62
     附錄六 66
zh_TW
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0094354017en_US
dc.subject (關鍵詞) 三要素混合模型zh_TW
dc.subject (關鍵詞) 加速失敗模型zh_TW
dc.subject (關鍵詞) 起價點偏誤zh_TW
dc.subject (關鍵詞) 定錨效果zh_TW
dc.subject (關鍵詞) three-component mixture modelen_US
dc.subject (關鍵詞) accelerated failure time modelen_US
dc.subject (關鍵詞) starting point biasen_US
dc.subject (關鍵詞) anchoring effecten_US
dc.subject (關鍵詞) CVDFACTSen_US
dc.title (題名) 雙界二分選擇詢價法-願付價格之起價點偏誤研究zh_TW
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) 一、 中文部分zh_TW
dc.relation.reference (參考文獻) 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。zh_TW
dc.relation.reference (參考文獻) 葉寶文(2002)「風險性之行為決策分析與其願付價值之研究」。博士論文,東吳大學經濟系。zh_TW
dc.relation.reference (參考文獻) 劉韶翔(2006)「三要素混合模型探討-雙界二分選擇詢價法之應用」。碩士論文,政治大學統計研究所。zh_TW
dc.relation.reference (參考文獻) 二、 英文部分zh_TW
dc.relation.reference (參考文獻) 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.zh_TW
dc.relation.reference (參考文獻) 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.zh_TW
dc.relation.reference (參考文獻) Bateman, I., (2002), “Economic valuation with stated preference techniques:a manual”, Edward Elgar Pubzh_TW
dc.relation.reference (參考文獻) 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.zh_TW
dc.relation.reference (參考文獻) Blamey, R.K., J.W. Bennett, and M.D.Morrison, (1999), “Yea-Saying in Contingentzh_TW
dc.relation.reference (參考文獻) Valuation Surveys”, Land Economics, 75(1):126-141.zh_TW
dc.relation.reference (參考文獻) 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.zh_TW
dc.relation.reference (參考文獻) 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.zh_TW
dc.relation.reference (參考文獻) 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 .zh_TW
dc.relation.reference (參考文獻) Farewell, V. T. and R. L. Prentice, (1977), “A Study of Distributional Shape in Life Testing”, Technometrics, 19:69-75.zh_TW
dc.relation.reference (參考文獻) Frydman, H. ,(1994), “A Note on Nonparametric Estimation of the Distribution Function from Interval-censored and Truncated Observations”, Journal of the Royal Statistical Society, Series B, 56, 71-74.zh_TW
dc.relation.reference (參考文獻) 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.zh_TW
dc.relation.reference (參考文獻) 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.zh_TW
dc.relation.reference (參考文獻) Klein, J. P. and M. L. Moeschberger, (1997), “ Suvival Analysis: Techniques for Censored and Truncated Data”, New York: Springer.zh_TW
dc.relation.reference (參考文獻) Lawless, J. F. (2003), “ Statistical Models and Methods for Lifetime Data”, 2nd edition. New Jersey:John Wiley.zh_TW
dc.relation.reference (參考文獻) Moore, R. J. ,(1982), “Algorithm AS 187: Derivatives of the Incomplete Gamma Integral”, Applied Statistics, 31, 330-333.zh_TW
dc.relation.reference (參考文獻) 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.zh_TW
dc.relation.reference (參考文獻) Turnbull, B. W. ,(1976), “The Empirical Distribution Function with Arbitrarily Grouped Censored and Truncated Data”, Journal of the Royal Statistical Society, Series B, 38, 290-295.zh_TW
dc.relation.reference (參考文獻) Whitehead, J.C., (2002), “Incentive Incompatibility and Starting-Point Bias in Iterative Valuation Questions”, Land Economics, 78(2):285-297.zh_TW
dc.relation.reference (參考文獻) Yamaguchi, K. (1992),“Accelerated Failure-time Regression Models with a Regression Model of Surviving Fraction,” Journal of the American Statistical Association, 87:284-292.zh_TW