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題名 汽車保有率之預測─以2001年至2030年之中國各省分為例
Forecasting Vehicle Ownership by Provinces of China: 2001-2030作者 朱芷宜
Zhu, Zhi-Yi貢獻者 胡偉民<br>黃柏鈞
Hu, Wei-Min<br>Huang, Po-Chun
朱芷宜
Zhu, Zhi-Yi關鍵詞 汽車保有率
Gompertz成長模型
人均GDP
ARIMA模型
Vehicle ownership
Gompertz growth model
GDP per capita
ARIMA model日期 2021 上傳時間 1-Nov-2021 12:09:46 (UTC+8) 摘要 隨著21世紀經濟的蓬勃發展，中國的汽車數量開始急遽攀升，而汽車普及的同時，卻也造成能源消耗與環境污染等成本，為了兼顧兩者之平衡，預測未來汽車發展趨勢實為重要，其數據可提供政府規劃相關政策，及早因應日後的潛在問題。本文利用中國2001年至2019年31個省分的長期追蹤資料，採Gompertz成長模型分析實質人均GDP對汽車保有率之長期影響，並以ARIMA模型預測2020年至2030年的人均GDP發展，最後合併上述兩模型之實證結果，預測各省分未來十年的汽車保有率。根據研究結果，中國各省分未來的汽車保有率飽和數量多為700餘輛，而十年後(2030年)汽車保有率將達300餘輛之水準。雖然中國汽車市場已進入成長趨緩之階段，然其發展空間依舊不容小覷。對此，中國政府應該採取更積極的措施以應對交通造成之環境問題。
The number of vehicles has experienced a tremendous expansion as Chinese economy grows rapidly in the 21st century. This comes with social costs, such as energy consumptions and CO2 emissions. In order to achieve a balance between economic development and environmental protection, it is important for the government to understand the future development of automotive market.This paper aims to make projections of the growth in vehicle ownership in 31 provinces of China from 2020 to 2030. Based on annual province-level data from 2001 to 2019, I forecast the levels of GDP per capita from 2020 to 2030 and apply Gompertz growth model to predict vehicle ownership rates for each province in the next decade. The results suggest that the vehicle ownership saturation levels for most provinces are estimated to be about 700 vehicles per 1,000 people, and they will reach 300 vehicles per 1,000 people by 2030. These findings have implications for Chinese government authority to take actions on transport and environmental policies.參考文獻 王莎莎、陳安、蘇靜與李碩（2009）。組合預測模型在中國GDP預測中的應用。山東大學學報（理學版），44（2），56-59。古繼寶、亓芳芳、吳劍琳（2010）。基於Gompertz模型的中國民用汽車保有量預測。技術經濟，29（1），57-62。沈中元（2006）。利用收入分布曲線預測中國汽車保有量。中國能源，28（8），11-15。冒小棟與張貞貞（2014）。基於ARIMA模型的江西省GDP的預測與分析。產業分析（商界論壇），34，259。張麗（2007）。天津市人均GDP時間序列模型及預測。北方經濟（學術版），3，44-46。Al-Shatti, A. S. (2014). The effect of fiscal policy on economic development in Jordan. International Business Research, 7(12), 67-76.Badoe, D. A., & Miller, E. J. (2000). Transportation–land-use interaction: empirical findings in North America, and their implications for modeling. Transportation Research Part D, 5(4), 235-263.Box, G. E., Jenkins, G. M., Reinsel, G. C., & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control. Hoboken, New Jersey: John Wiley & Sons.Button, K., Ngoe, N., & Hine, J. (1993). Modelling vehicle ownership and use in low income countries. Journal of Transport Economics and Policy, 27(1), 51-67.Ceylan, H., Başkan, Ö., & Ozan, C. (2018). Modeling and forecasting car ownership based on socio-economic and demographic indicators in Turkey. TeMA-Journal of Land Use, Mobility and Environment, Special issue 1, 47-66.Cullinane, S. (2002). The relationship between car ownership and public transport provision: a case study of Hong Kong. Transport Policy, 9(1), 29-39.Dargay, J., & Gately, D. (1997). Vehicle ownership to 2015: implications for energy use and emissions. Energy Policy, 25(14-15), 1121-1127.Dargay, J., & Gately, D. (1999). Income`s effect on car and vehicle ownership, worldwide: 1960-2015. Transportation Research Part A: Policy and Practice, 33(2), 101-138.Dargay, J., Gately, D., & Sommer, M. (2007). Vehicle ownership and income growth, worldwide: 1960-2030. The Energy Journal, 28(4), 143-170.Dritsaki, C. (2015). Forecasting real GDP rate through econometric models: an empirical study from Greece. Journal of International Business and Economics, 3(1), 13-19.Eissa, N. (2020). Forecasting the GDP per Capita for Egypt and Saudi Arabia Using ARIMA Models. Research in World Economy, 11(1), 247-258.Hirota, K. (2007). Passenger car ownership estimation toward 2030 in Japan. Studies in Regional Science, 37(1), 25-39.Huo, H., & Wang, M. (2012). Modeling future vehicle sales and stock in China. Energy Policy, 43, 17-29.Ingram, G. K., & Liu, Z. (1997). Motorization and road provision in countries and cities. World Bank Policy Research Paper (1842).Kobos, P. H., Erickson, J. D., & Drennen, T. E. (2003). Scenario analysis of Chinese passenger vehicle growth. Contemporary Economic Policy, 21(2), 200-217.Lam, W. H., & Tam, M. L. (2002). Reliability of territory-wide car ownership estimates in Hong Kong. Journal of Transport Geography, 10(1), 51-60.Lescaroux, F., & Rech, O. (2008). The impact of automobile diffusion on the income elasticity of motor fuel demand. The Energy Journal, 29(1), 41-60.Li, S., & Zhao, P. (2015). The determinants of commuting mode choice among school children in Beijing. Journal of Transport Geography, 46, 112-121.Modis, T. (2013). Long-term GDP forecasts and the prospects for growth. Technological Forecasting and Social Change, 80(8), 1557-1562.Patsalidis, A. (1977). Regional car ownership forecasting in Britain. Civil Engineering, 1977(8), 183-186.Pendyala, R. M., Kostyniuk, L. P., & Goulias, K. G. (1995). A repeated cross-sectional evaluation of car ownership. Transportation, 22(2), 165-184.Smeed, R. J. (1951). Likely increases of road traffic in Great Britain. Research Note.Tanner, J. C. (1978). Long‐term forecasting of vehicle ownership and road traffic. Journal of the Royal Statistical Society: Series A (General), 141(1), 14-41.Wang, Y., Teter, J., & Sperling, D. (2011). China’s soaring vehicle population: even greater than forecasted? Energy Policy, 39(6), 3296-3306.Wu, T., Zhao, H., & Ou, X. (2014). Vehicle ownership analysis based on GDP per capita in China: 1963-2050. Sustainability, 6(8), 4877-4899.Xu, Z., Wang, X., & Jin, Y. (2014). Regional GDP prediction based on improved BP neural network model. International Journal of Multimedia and Ubiquitous Engineering, 9(4), 51-62.Yang, Z., Jia, P., Liu, W., & Yin, H. (2017). Car ownership and urban development in Chinese cities: A panel data analysis. Journal of Transport Geography, 58, 127-134.Yin, C., & Sun, B. (2018). Disentangling the effects of the built environment on car ownership: A multi-level analysis of Chinese cities. Cities, 74, 188-195.Zhao, C., Nielsen, T. A. S., Olafsson, A. S., Carstensen, T. A., & Fertner, C. (2018). Cycling environmental perception in Beijing–A study of residents` attitudes towards future cycling and car purchasing. Transport Policy, 66, 96-106. 描述 碩士
國立政治大學
財政學系
108255032資料來源 http://thesis.lib.nccu.edu.tw/record/#G0108255032 資料類型 thesis dc.contributor.advisor 胡偉民<br>黃柏鈞 zh_TW dc.contributor.advisor Hu, Wei-Min<br>Huang, Po-Chun en_US dc.contributor.author (Authors) 朱芷宜 zh_TW dc.contributor.author (Authors) Zhu, Zhi-Yi en_US dc.creator (作者) 朱芷宜 zh_TW dc.creator (作者) Zhu, Zhi-Yi en_US dc.date (日期) 2021 en_US dc.date.accessioned 1-Nov-2021 12:09:46 (UTC+8) - dc.date.available 1-Nov-2021 12:09:46 (UTC+8) - dc.date.issued (上傳時間) 1-Nov-2021 12:09:46 (UTC+8) - dc.identifier (Other Identifiers) G0108255032 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/137705 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 財政學系 zh_TW dc.description (描述) 108255032 zh_TW dc.description.abstract (摘要) 隨著21世紀經濟的蓬勃發展，中國的汽車數量開始急遽攀升，而汽車普及的同時，卻也造成能源消耗與環境污染等成本，為了兼顧兩者之平衡，預測未來汽車發展趨勢實為重要，其數據可提供政府規劃相關政策，及早因應日後的潛在問題。本文利用中國2001年至2019年31個省分的長期追蹤資料，採Gompertz成長模型分析實質人均GDP對汽車保有率之長期影響，並以ARIMA模型預測2020年至2030年的人均GDP發展，最後合併上述兩模型之實證結果，預測各省分未來十年的汽車保有率。根據研究結果，中國各省分未來的汽車保有率飽和數量多為700餘輛，而十年後(2030年)汽車保有率將達300餘輛之水準。雖然中國汽車市場已進入成長趨緩之階段，然其發展空間依舊不容小覷。對此，中國政府應該採取更積極的措施以應對交通造成之環境問題。 zh_TW dc.description.abstract (摘要) The number of vehicles has experienced a tremendous expansion as Chinese economy grows rapidly in the 21st century. This comes with social costs, such as energy consumptions and CO2 emissions. In order to achieve a balance between economic development and environmental protection, it is important for the government to understand the future development of automotive market.This paper aims to make projections of the growth in vehicle ownership in 31 provinces of China from 2020 to 2030. Based on annual province-level data from 2001 to 2019, I forecast the levels of GDP per capita from 2020 to 2030 and apply Gompertz growth model to predict vehicle ownership rates for each province in the next decade. The results suggest that the vehicle ownership saturation levels for most provinces are estimated to be about 700 vehicles per 1,000 people, and they will reach 300 vehicles per 1,000 people by 2030. These findings have implications for Chinese government authority to take actions on transport and environmental policies. en_US dc.description.tableofcontents 第一章 緒論 1第一節 研究背景 1第二節 研究動機與目的 5第三節 研究架構 6第二章 文獻回顧 7第一節 影響汽車保有量之因素 7第二節 汽車保有率之預測 9第三節 人均GDP之預測 11第三章 模型介紹 13第一節 Gompertz成長模型 13第二節 時間序列ARIMA模型 16第四章 資料來源與統計分析 19第一節 資料來源 19第二節 Gompertz模型之變數定義與敘述統計 21第三節 Gompertz實證模型設定 24第四節 ARIMA模型之變數定義與敘述統計 27第五章 實證結果與分析 30第一節 Gompertz成長模型之實證結果 30第二節 ARIMA模型之實證結果 33第三節 未來汽車保有率之預測 37第六章 結論與建議 40第一節 結論與政策建議 40第二節 研究限制 41參考文獻 43附錄 47 zh_TW dc.format.extent 5218758 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0108255032 en_US dc.subject (關鍵詞) 汽車保有率 zh_TW dc.subject (關鍵詞) Gompertz成長模型 zh_TW dc.subject (關鍵詞) 人均GDP zh_TW dc.subject (關鍵詞) ARIMA模型 zh_TW dc.subject (關鍵詞) Vehicle ownership en_US dc.subject (關鍵詞) Gompertz growth model en_US dc.subject (關鍵詞) GDP per capita en_US dc.subject (關鍵詞) ARIMA model en_US dc.title (題名) 汽車保有率之預測─以2001年至2030年之中國各省分為例 zh_TW dc.title (題名) Forecasting Vehicle Ownership by Provinces of China: 2001-2030 en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 王莎莎、陳安、蘇靜與李碩（2009）。組合預測模型在中國GDP預測中的應用。山東大學學報（理學版），44（2），56-59。古繼寶、亓芳芳、吳劍琳（2010）。基於Gompertz模型的中國民用汽車保有量預測。技術經濟，29（1），57-62。沈中元（2006）。利用收入分布曲線預測中國汽車保有量。中國能源，28（8），11-15。冒小棟與張貞貞（2014）。基於ARIMA模型的江西省GDP的預測與分析。產業分析（商界論壇），34，259。張麗（2007）。天津市人均GDP時間序列模型及預測。北方經濟（學術版），3，44-46。Al-Shatti, A. S. (2014). The effect of fiscal policy on economic development in Jordan. International Business Research, 7(12), 67-76.Badoe, D. A., & Miller, E. J. (2000). Transportation–land-use interaction: empirical findings in North America, and their implications for modeling. Transportation Research Part D, 5(4), 235-263.Box, G. E., Jenkins, G. M., Reinsel, G. C., & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control. Hoboken, New Jersey: John Wiley & Sons.Button, K., Ngoe, N., & Hine, J. (1993). Modelling vehicle ownership and use in low income countries. Journal of Transport Economics and Policy, 27(1), 51-67.Ceylan, H., Başkan, Ö., & Ozan, C. (2018). Modeling and forecasting car ownership based on socio-economic and demographic indicators in Turkey. TeMA-Journal of Land Use, Mobility and Environment, Special issue 1, 47-66.Cullinane, S. (2002). The relationship between car ownership and public transport provision: a case study of Hong Kong. Transport Policy, 9(1), 29-39.Dargay, J., & Gately, D. (1997). Vehicle ownership to 2015: implications for energy use and emissions. Energy Policy, 25(14-15), 1121-1127.Dargay, J., & Gately, D. (1999). Income`s effect on car and vehicle ownership, worldwide: 1960-2015. Transportation Research Part A: Policy and Practice, 33(2), 101-138.Dargay, J., Gately, D., & Sommer, M. (2007). Vehicle ownership and income growth, worldwide: 1960-2030. The Energy Journal, 28(4), 143-170.Dritsaki, C. (2015). Forecasting real GDP rate through econometric models: an empirical study from Greece. Journal of International Business and Economics, 3(1), 13-19.Eissa, N. (2020). Forecasting the GDP per Capita for Egypt and Saudi Arabia Using ARIMA Models. Research in World Economy, 11(1), 247-258.Hirota, K. (2007). Passenger car ownership estimation toward 2030 in Japan. Studies in Regional Science, 37(1), 25-39.Huo, H., & Wang, M. (2012). Modeling future vehicle sales and stock in China. Energy Policy, 43, 17-29.Ingram, G. K., & Liu, Z. (1997). Motorization and road provision in countries and cities. World Bank Policy Research Paper (1842).Kobos, P. H., Erickson, J. D., & Drennen, T. E. (2003). Scenario analysis of Chinese passenger vehicle growth. Contemporary Economic Policy, 21(2), 200-217.Lam, W. H., & Tam, M. L. (2002). Reliability of territory-wide car ownership estimates in Hong Kong. Journal of Transport Geography, 10(1), 51-60.Lescaroux, F., & Rech, O. (2008). The impact of automobile diffusion on the income elasticity of motor fuel demand. The Energy Journal, 29(1), 41-60.Li, S., & Zhao, P. (2015). The determinants of commuting mode choice among school children in Beijing. Journal of Transport Geography, 46, 112-121.Modis, T. (2013). Long-term GDP forecasts and the prospects for growth. Technological Forecasting and Social Change, 80(8), 1557-1562.Patsalidis, A. (1977). Regional car ownership forecasting in Britain. Civil Engineering, 1977(8), 183-186.Pendyala, R. M., Kostyniuk, L. P., & Goulias, K. G. (1995). A repeated cross-sectional evaluation of car ownership. Transportation, 22(2), 165-184.Smeed, R. J. (1951). Likely increases of road traffic in Great Britain. Research Note.Tanner, J. C. (1978). Long‐term forecasting of vehicle ownership and road traffic. Journal of the Royal Statistical Society: Series A (General), 141(1), 14-41.Wang, Y., Teter, J., & Sperling, D. (2011). China’s soaring vehicle population: even greater than forecasted? Energy Policy, 39(6), 3296-3306.Wu, T., Zhao, H., & Ou, X. (2014). Vehicle ownership analysis based on GDP per capita in China: 1963-2050. Sustainability, 6(8), 4877-4899.Xu, Z., Wang, X., & Jin, Y. (2014). Regional GDP prediction based on improved BP neural network model. International Journal of Multimedia and Ubiquitous Engineering, 9(4), 51-62.Yang, Z., Jia, P., Liu, W., & Yin, H. (2017). Car ownership and urban development in Chinese cities: A panel data analysis. Journal of Transport Geography, 58, 127-134.Yin, C., & Sun, B. (2018). Disentangling the effects of the built environment on car ownership: A multi-level analysis of Chinese cities. Cities, 74, 188-195.Zhao, C., Nielsen, T. A. S., Olafsson, A. S., Carstensen, T. A., & Fertner, C. (2018). Cycling environmental perception in Beijing–A study of residents` attitudes towards future cycling and car purchasing. Transport Policy, 66, 96-106. zh_TW dc.identifier.doi (DOI) 10.6814/NCCU202101661 en_US
