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題名 現場樣本次數及時間偏誤之修正─以淡水河流域濕地價值評估為例
Addressing on-site sampling bias: A case study on measuring recreational values of Tamsui river wetlands作者 吳宛霓
Wu, Wan-Ni貢獻者 蕭代基
Shaw, Dai-Gee
吳宛霓
Wu, Wan-Ni關鍵詞 旅行成本法
現場抽樣樣本
偏誤調整
遊憩價值日期 2021 上傳時間 4-Aug-2021 15:58:11 (UTC+8) 摘要 旅行成本法可以估計社會對特定地點的遊憩需求函數，然而受到現場抽樣的限制，現場樣本存在非負整數、截頭以及內生分層三大特性，導致現場母體（on-site population）的機率分布與母體（population）的機率分布不一致。本研究針對此估計偏誤，進行機率密度函數的修正。本文首先假設旅行次數與停留時間彼此獨立，比較四種模型修正旅行次數偏誤的結果。研究顯示在獨立假設下，以負二項分配假設旅行次數的機率分布、以卜瓦松分配假設停留時間機率分布較為合適。參考Englin與Shonkwiler（1995）的作法，修正現場母體的機率密度函數偏誤。而後放寬旅行次數與停留時間彼此獨立的假設，同時考慮旅行次數與停留時間對現場樣本的影響，假設次數與時間的母體均為卜瓦松分配，採用條件卜瓦松模型（conditional Poisson model，CPM）進行需求函數的估計。並參考Shaw（1988）的作法修正現場母體的機率密度函數偏誤。依據實證結果顯示，旅行次數受旅行成本高低、年紀大小、性別與戶外活動頻率影響，而停留時間則受性別以及是否曾參與環保團體影響。若採獨立假設對旅行次數進行調整，適合以負二項分配作為母體假設，則每年遊客對於淡水河流域濕地的遊憩價值約為新台幣2,100元；若採非獨立的估計方法，針對旅行次數與停留時間兩部分同時進行調整，將母體以條件卜瓦松分配進行設定，其遊憩價值約為新台幣6,540元。 參考文獻 鄭蕙燕、張偉祐、林政德（2000）。四草野生動物保護區遊客之遊憩效益與時間成本：截斷式波爾生模型之應用。農業經濟半年刊，67，161-179。蕭代基、鄭蕙燕、吳珮瑛、錢玉蘭、溫麗琪（2003）。環境保護之成本效益分析：理論、方法與應用。俊傑書局。薛暖瑋（1988）。視覺媒體需求模式。碩士論文，國立臺灣大學經濟學研究所。Berkhout, P., & Plug, E. (2004). A bivariate Poisson count data model using conditional probabilities. Statistica Neerlandica, 58(3), 349-364.Bockstael, N. E., & Strand, I. E. (1987). The effect of common sources of regression error on benefit estimates. Land Economics, 63(1), 11-20.Burke, M., Hsiang, S. M., & Miguel, E. (2015). Global non-linear effect of temperature on economic production. Nature, 527(7577), 235-239.Burt, O. R., & Brewer, D. (1971). Estimation of net social benefits from outdoor recreation. Econometrica, 39(5), 813-827.Cameron, A. C., & Trivedi, P. K. (1986). Econometric models based on count data. Comparisons and applications of some estimators and tests. Journal of Applied Econometrics, 1(1), 29-53.Cesario, F. J. (1976). Value of time in recreation benefit studies. Land Economics, 52(1), 32-41.Clark, T. E., & West, K. D. (2007). Approximately normal tests for equal predictive accuracy in nested models. Journal of Econometrics, 138(1), 291-311.Dell, M., Jones, B. F., & Olken, B. A. (2009). Temperature and income: reconciling new cross-sectional and panel estimates. American Economic Review, 99(2), 198-204.DePaula, G., & Mendelsohn, R. (2010). Development and the impact of climate change on energy demand: evidence from Brazil. Climate Change Economics, 1(03), 187-208.Deschênes, O., & Greenstone, M. (2007). The economic impacts of climate change: evidence from agricultural output and random fluctuations in weather. American Economic Review, 97(1), 354-385.Deschenes, O., Greenstone, M., & Shapiro, J. S. (2017). Defensive investments and the demand for air quality: evidence from the NOx budget program. American Economic Review, 107(10), 2958-89.Deyak, T. A., & Smith, V. K. (1976). The economic value of statute reform: The case of liberalized abortion. Journal of Political Economy, 84(1), 83-99.Englin, J., & Shonkwiler, J. S. (1995). Estimating social welfare using count data models: an application to long-run recreation demand under conditions of endogenous stratification and truncation. The Review of Economics and Statistics, 77(1), 104-112.Fleming, C. M., & Cook, A. (2008). The recreational value of Lake McKenzie, Fraser Island: an application of the travel cost method. Tourism Management, 29(6), 1197-1205.Freeman III, A. M., Herriges, J. A., & Kling, C. L. (2014). The Measurement of Environmental and Resource Values: Theory and Methods. Routledge.Haab, T. C., & McConnell, K. E. (2002). Valuing Environmental and Natural Resources: The Econometrics of Non-market Valuation. Edward Elgar Publishing.Hausman, J. A., Hall, B. H., & Griliches, Z. (1984). Econometric models for count data with an application to the patents-R&D relationship. Econometrica, 52, (4), 909-38.Hindsley, P., Landry, C. E., & Gentner, B. (2011). Addressing onsite sampling in recreation site choice models. Journal of Environmental Economics and Management, 62(1), 95-110.Hsiang, S. M., Burke, M., & Miguel, E. (2013). Quantifying the influence of climate on human conflict. Science, 341(6151).Hsiang, S. M., Meng, K. C., & Cane, M. A. (2011). Civil conflicts are associated with the global climate. Nature, 476(7361), 438-441.Jim, C. Y., & Chen, W. Y. (2009). Value of scenic views: hedonic assessment of private housing in Hong Kong. Landscape and Urban Planning, 91(4), 226-234.Kawamura, K. (1973). The structure of bivariate Poisson distribution [Seminar Report]. Kodai Mathematical Seminar, Department of Mathematics, Tokyo Institute of Technology, 25(2), 246-256.Larson, A., & Starr, J. A. (1993). A network model of organization formation. Entrepreneurship Theory and Practice, 17(2), 5-15.McConnell, K. E. (1992). On-site time in the demand for recreation. American Journal of Agricultural Economics, 74(4), 918-925.Mendelsohn, R. (2019). An examination of recent revealed preference valuation methods and results. Review of Environmental Economics and Policy, 13(2), 267-282.Moore, F. C., & Lobell, D. B. (2014). Adaptation potential of European agriculture in response to climate change. Nature Climate Change, 4(7), 610-614.Pindyck, R. S., & Rubinfeld, D. L. (2013). Econometric Models and Economic Forecasts (4th ed.). McGraw-Hill Companies.Randall, A. (1994). A difficulty with the travel cost method. Land Economics, 70(1), 88-96.Ranson, M. (2014). Crime, weather, and climate change. Journal of Environmental Economics and Management, 67(3), 274-302.Rosenthal, D. H. (1987). The necessity for substitute prices recreation demand analyses. American Journal of Agricultural Economics, 69(4), 828-837.Schlenker, W., & Roberts, M. J. (2009). Nonlinear temperature effects indicate severe damages to US crop yields under climate change. Proceedings of the National Academy of Sciences, 106(37), 15594-15598.Shaw, D. (1985). Three Essays in the Economics of Recreation Demand (Doctoral dissertation, University of Michigan).Shaw, D. (1988). On-site samples` regression: problems of non-negative integers, truncation, and endogenous stratification. Journal of Econometrics, 37(2), 211-223.Shi, W., & Huang, J. C. (2018). Correcting on-site sampling bias: a new method with application to recreation demand analysis. Land Economics, 94(3), 459-474.Sills, E. O., & Abt, K. L. (Eds.). (2013). Forests in a Market Economy (Vol. 72). Springer Science & Business Media.Sohngen, B., Lichtkoppler, F., & Bielen, M. (2000). The value of day trips to Lake Erie beaches. Dept. of Agricultural, Environmental, and Development Economics, Ohio State University.Tobin, J. (1958). Estimation of relationships for limited dependent variables. Econometrica, 26(1), 24-36.Trice, A. H., & Wood, S. E. (1958). Measurement of recreation benefits. Land Economics, 34(3), 195-207.Weiqi, C., Huasheng, H. O. N. G., Yan, L. I. U., Zhang, L., Xiaofeng, H. O. U., & Raymond, M. (2004). Recreation demand and economic value: an application of travel cost method for Xiamen Island. China Economic Review, 15(4), 398-406.Zivin, J. G., & Neidell, M. (2014). Temperature and the allocation of time: implications for climate change. Journal of Labor Economics, 32(1), 1-26.Zivin, J. G., Hsiang, S. M., & Neidell, M. (2018). Temperature and human capital in the short and long run. Journal of the Association of Environmental and Resource Economists, 5(1), 77-105. 描述 碩士
國立政治大學
經濟學系
108258013資料來源 http://thesis.lib.nccu.edu.tw/record/#G0108258013 資料類型 thesis dc.contributor.advisor 蕭代基 zh_TW dc.contributor.advisor Shaw, Dai-Gee en_US dc.contributor.author (Authors) 吳宛霓 zh_TW dc.contributor.author (Authors) Wu, Wan-Ni en_US dc.creator (作者) 吳宛霓 zh_TW dc.creator (作者) Wu, Wan-Ni en_US dc.date (日期) 2021 en_US dc.date.accessioned 4-Aug-2021 15:58:11 (UTC+8) - dc.date.available 4-Aug-2021 15:58:11 (UTC+8) - dc.date.issued (上傳時間) 4-Aug-2021 15:58:11 (UTC+8) - dc.identifier (Other Identifiers) G0108258013 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/136556 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 經濟學系 zh_TW dc.description (描述) 108258013 zh_TW dc.description.abstract (摘要) 旅行成本法可以估計社會對特定地點的遊憩需求函數，然而受到現場抽樣的限制，現場樣本存在非負整數、截頭以及內生分層三大特性，導致現場母體（on-site population）的機率分布與母體（population）的機率分布不一致。本研究針對此估計偏誤，進行機率密度函數的修正。本文首先假設旅行次數與停留時間彼此獨立，比較四種模型修正旅行次數偏誤的結果。研究顯示在獨立假設下，以負二項分配假設旅行次數的機率分布、以卜瓦松分配假設停留時間機率分布較為合適。參考Englin與Shonkwiler（1995）的作法，修正現場母體的機率密度函數偏誤。而後放寬旅行次數與停留時間彼此獨立的假設，同時考慮旅行次數與停留時間對現場樣本的影響，假設次數與時間的母體均為卜瓦松分配，採用條件卜瓦松模型（conditional Poisson model，CPM）進行需求函數的估計。並參考Shaw（1988）的作法修正現場母體的機率密度函數偏誤。依據實證結果顯示，旅行次數受旅行成本高低、年紀大小、性別與戶外活動頻率影響，而停留時間則受性別以及是否曾參與環保團體影響。若採獨立假設對旅行次數進行調整，適合以負二項分配作為母體假設，則每年遊客對於淡水河流域濕地的遊憩價值約為新台幣2,100元；若採非獨立的估計方法，針對旅行次數與停留時間兩部分同時進行調整，將母體以條件卜瓦松分配進行設定，其遊憩價值約為新台幣6,540元。 zh_TW dc.description.tableofcontents 第一章、緒論 1一、研究背景與動機 1二、研究目的 4第二章、文獻探討 5一、顯示性偏好評估法 5二、旅行成本法 8第三章、研究方法 17一、理論模型 17二、獨立假設下的估計方法 23三、放寬獨立假設的估計方法 26四、蒙地卡羅模擬 29第四章、實證研究 35一、資料來源 35二、資料處理 36三、敘述統計 40四、實證模型選擇標準 45第五章、實證結果 49一、獨立假設下的旅行次數需求 49二、放寬獨立假設的旅行次數需求 56三、遊憩價值估計 59第六章、總結 61一、結論 61二、未來展望 63參考文獻 64 zh_TW dc.format.extent 1693622 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0108258013 en_US dc.subject (關鍵詞) 旅行成本法 zh_TW dc.subject (關鍵詞) 現場抽樣樣本 zh_TW dc.subject (關鍵詞) 偏誤調整 zh_TW dc.subject (關鍵詞) 遊憩價值 zh_TW dc.title (題名) 現場樣本次數及時間偏誤之修正─以淡水河流域濕地價值評估為例 zh_TW dc.title (題名) Addressing on-site sampling bias: A case study on measuring recreational values of Tamsui river wetlands en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 鄭蕙燕、張偉祐、林政德（2000）。四草野生動物保護區遊客之遊憩效益與時間成本：截斷式波爾生模型之應用。農業經濟半年刊，67，161-179。蕭代基、鄭蕙燕、吳珮瑛、錢玉蘭、溫麗琪（2003）。環境保護之成本效益分析：理論、方法與應用。俊傑書局。薛暖瑋（1988）。視覺媒體需求模式。碩士論文，國立臺灣大學經濟學研究所。Berkhout, P., & Plug, E. (2004). A bivariate Poisson count data model using conditional probabilities. Statistica Neerlandica, 58(3), 349-364.Bockstael, N. E., & Strand, I. E. (1987). The effect of common sources of regression error on benefit estimates. Land Economics, 63(1), 11-20.Burke, M., Hsiang, S. M., & Miguel, E. (2015). Global non-linear effect of temperature on economic production. Nature, 527(7577), 235-239.Burt, O. R., & Brewer, D. (1971). Estimation of net social benefits from outdoor recreation. Econometrica, 39(5), 813-827.Cameron, A. C., & Trivedi, P. K. (1986). Econometric models based on count data. Comparisons and applications of some estimators and tests. Journal of Applied Econometrics, 1(1), 29-53.Cesario, F. J. (1976). Value of time in recreation benefit studies. Land Economics, 52(1), 32-41.Clark, T. E., & West, K. D. (2007). Approximately normal tests for equal predictive accuracy in nested models. Journal of Econometrics, 138(1), 291-311.Dell, M., Jones, B. F., & Olken, B. A. (2009). Temperature and income: reconciling new cross-sectional and panel estimates. American Economic Review, 99(2), 198-204.DePaula, G., & Mendelsohn, R. (2010). Development and the impact of climate change on energy demand: evidence from Brazil. Climate Change Economics, 1(03), 187-208.Deschênes, O., & Greenstone, M. (2007). The economic impacts of climate change: evidence from agricultural output and random fluctuations in weather. American Economic Review, 97(1), 354-385.Deschenes, O., Greenstone, M., & Shapiro, J. S. (2017). Defensive investments and the demand for air quality: evidence from the NOx budget program. American Economic Review, 107(10), 2958-89.Deyak, T. A., & Smith, V. K. (1976). The economic value of statute reform: The case of liberalized abortion. Journal of Political Economy, 84(1), 83-99.Englin, J., & Shonkwiler, J. S. (1995). Estimating social welfare using count data models: an application to long-run recreation demand under conditions of endogenous stratification and truncation. The Review of Economics and Statistics, 77(1), 104-112.Fleming, C. M., & Cook, A. (2008). The recreational value of Lake McKenzie, Fraser Island: an application of the travel cost method. Tourism Management, 29(6), 1197-1205.Freeman III, A. M., Herriges, J. A., & Kling, C. L. (2014). The Measurement of Environmental and Resource Values: Theory and Methods. Routledge.Haab, T. C., & McConnell, K. E. (2002). Valuing Environmental and Natural Resources: The Econometrics of Non-market Valuation. Edward Elgar Publishing.Hausman, J. A., Hall, B. H., & Griliches, Z. (1984). Econometric models for count data with an application to the patents-R&D relationship. Econometrica, 52, (4), 909-38.Hindsley, P., Landry, C. E., & Gentner, B. (2011). Addressing onsite sampling in recreation site choice models. Journal of Environmental Economics and Management, 62(1), 95-110.Hsiang, S. M., Burke, M., & Miguel, E. (2013). Quantifying the influence of climate on human conflict. Science, 341(6151).Hsiang, S. M., Meng, K. C., & Cane, M. A. (2011). Civil conflicts are associated with the global climate. Nature, 476(7361), 438-441.Jim, C. Y., & Chen, W. Y. (2009). Value of scenic views: hedonic assessment of private housing in Hong Kong. Landscape and Urban Planning, 91(4), 226-234.Kawamura, K. (1973). The structure of bivariate Poisson distribution [Seminar Report]. Kodai Mathematical Seminar, Department of Mathematics, Tokyo Institute of Technology, 25(2), 246-256.Larson, A., & Starr, J. A. (1993). A network model of organization formation. Entrepreneurship Theory and Practice, 17(2), 5-15.McConnell, K. E. (1992). On-site time in the demand for recreation. American Journal of Agricultural Economics, 74(4), 918-925.Mendelsohn, R. (2019). An examination of recent revealed preference valuation methods and results. Review of Environmental Economics and Policy, 13(2), 267-282.Moore, F. C., & Lobell, D. B. (2014). Adaptation potential of European agriculture in response to climate change. Nature Climate Change, 4(7), 610-614.Pindyck, R. S., & Rubinfeld, D. L. (2013). Econometric Models and Economic Forecasts (4th ed.). McGraw-Hill Companies.Randall, A. (1994). A difficulty with the travel cost method. Land Economics, 70(1), 88-96.Ranson, M. (2014). Crime, weather, and climate change. Journal of Environmental Economics and Management, 67(3), 274-302.Rosenthal, D. H. (1987). The necessity for substitute prices recreation demand analyses. American Journal of Agricultural Economics, 69(4), 828-837.Schlenker, W., & Roberts, M. J. (2009). Nonlinear temperature effects indicate severe damages to US crop yields under climate change. Proceedings of the National Academy of Sciences, 106(37), 15594-15598.Shaw, D. (1985). Three Essays in the Economics of Recreation Demand (Doctoral dissertation, University of Michigan).Shaw, D. (1988). On-site samples` regression: problems of non-negative integers, truncation, and endogenous stratification. Journal of Econometrics, 37(2), 211-223.Shi, W., & Huang, J. C. (2018). Correcting on-site sampling bias: a new method with application to recreation demand analysis. Land Economics, 94(3), 459-474.Sills, E. O., & Abt, K. L. (Eds.). (2013). Forests in a Market Economy (Vol. 72). Springer Science & Business Media.Sohngen, B., Lichtkoppler, F., & Bielen, M. (2000). The value of day trips to Lake Erie beaches. Dept. of Agricultural, Environmental, and Development Economics, Ohio State University.Tobin, J. (1958). Estimation of relationships for limited dependent variables. Econometrica, 26(1), 24-36.Trice, A. H., & Wood, S. E. (1958). Measurement of recreation benefits. Land Economics, 34(3), 195-207.Weiqi, C., Huasheng, H. O. N. G., Yan, L. I. U., Zhang, L., Xiaofeng, H. O. U., & Raymond, M. (2004). Recreation demand and economic value: an application of travel cost method for Xiamen Island. China Economic Review, 15(4), 398-406.Zivin, J. G., & Neidell, M. (2014). Temperature and the allocation of time: implications for climate change. Journal of Labor Economics, 32(1), 1-26.Zivin, J. G., Hsiang, S. M., & Neidell, M. (2018). Temperature and human capital in the short and long run. Journal of the Association of Environmental and Resource Economists, 5(1), 77-105. zh_TW dc.identifier.doi (DOI) 10.6814/NCCU202100930 en_US
