菲律賓NAIA國內和國際空中交通的決定因素;Determinants of Domestic and International Air Traffic at NAIA, Philippines

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Title:	菲律賓NAIA國內和國際空中交通的決定因素;Determinants of Domestic and International Air Traffic at NAIA, Philippines
Authors:	瑞諾索;Reynoso, Crisaulo Marquez
Contributors:	國際永續發展碩士在職專班
Keywords:	空中交通預測;宏觀經濟因素;計量經濟學模型;air traffic forecasting;macroeconomic factors;econometric modelling
Date:	2021-07-14
Issue Date:	2021-12-07 12:16:10 (UTC+8)
Publisher:	國立中央大學
Abstract:	由於菲律賓的群島性質，尼諾·阿基諾國際機場 (NAIA) 經歷了來自國際和國內空中交通的大量空中交通。相應地，影響它們的因素也存在差異。因此，本研究旨在確定影響 NAIA 國內和國際客運量和貨運量的宏觀經濟因素。使用 2001 年至 2013 年的交通數據，連同九個潛在的宏觀經濟因素，形成一個 156 個月的模型訓練數據集。然後採用雙向逐步選擇的多元回歸來確定影響交通量的重要因素。結果顯示，國際航空旅客最重要的預測因素是旅客到達量，而國內旅客的主要決定因素是國際儲備總額。另一方面，貨量受貨幣匯率和出口數據等多種因素影響。本研究創建了四個方程，對應於國際航空客運和貨運模型及其國內對應模型。然後使用 2014 年至 2019 年為期 72 個月的測試集來評估每個模型的準確性。然後使用回歸結果預測 NAIA 到 2029 年 12 月的空中交通量。;Due to the Philippines’ archipelagic nature, the Ninoy Aquino International Airport (NAIA) experiences high volumes of air traffic coming from both international and domestic air traffic. Correspondingly, there are differences in the factors influencing them. This study, therefore, sought to determine the macroeconomic factors affecting domestic and international passengers and cargo volume in NAIA. The traffic data from 2001 to 2013 were used, together with nine potential macroeconomic factors, to form a 156-month dataset for model training. Multiple regression with bi-directional stepwise selection was then employed to determine the significant factors affecting the traffic volumes. Results revealed that the most important predictor for international air passengers is Tourist Arrival volume, while the primary determinant for the domestic passenger is the Gross International Reserve. On the other hand, the cargo volumes are affected by several factors such as currency exchange rate and export figures. Four equations were created in this study, corresponding to the models for international air passenger and cargo and their domestic counterparts. A 72-month testing set, from 2014 to 2019, was then used to evaluate the accuracy of each model. The regression results are then used to forecast the air traffic in NAIA up to December 2029.
Appears in Collections:	[International Environment Sustainable Development Program] Electronic Thesis & Dissertation

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