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Determinants of subway travel in the New York City Metropolitan Area: An empirical research and econometric application of discrete choice and time series models to urban travel demand.

機譯：紐約都會區地鐵旅行的決定因素：離散選擇和時間序列模型對城市旅行需求的實證研究和計量經濟學應用。

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This dissertation deals with the modeling of transportation decisions in the New York City Area. Three different data sets are used: cross sectional data, micro sample data and time series data. The main model estimated is a logistic model developed earlier by McFadden and the independent variables are socio-economic variables, mode characteristic variables, and dummies. Each data set addresses a particular question. By using the first data set we find out that the estimation of the subway ridership is sensitive to spatial area. By using the second data set we estimate the behavior of the riders and show that their optimal decision based on optimizing their utility depends on the mode characteristics. We also derive the value of walking time and the value of auto in-vehicle time and we estimate aggregate elasticities for auto and bus. By using the third data set we estimate an aggregate elasticity for the demand for subway trips and estimate the impact of public policies such as increase in fare.; In addition, in this dissertation we attempt to develop an econometric approach that unifies time series and prediction from static models such as the logistic regression. By using one canonical model and varying the underlying assumptions and the distribution of the dependent variable we show that forecasting results can be obtained in ways not so different; only the optimizing algorithm is different. It appears that the two approaches underlined above are useful because they can be used to explain the dynamics of human behavior. This is one of the main contributions to the field of transportation economics.

機譯：本文主要研究紐約市區的交通決策模型。使用了三種不同的數據集：橫截面數據，微量樣品數據和時間序列數據。估計的主要模型是McFadden較早開發的邏輯模型，自變量是社會經濟變量，模式特征變量和虛擬變量。每個數據集都解決一個特定的問題。通過使用第一個數據集，我們發現地鐵乘車率的估計對空間區域敏感。通過使用第二個數據集，我們估計了騎手的行為，并表明基于優化其效用的騎手的最佳決策取決于模式特征。我們還導出了步行時間的值和汽車上車的時間的值，并估計了汽車和公共汽車的總彈性。通過使用第三組數據，我們估計了地鐵出行需求的總體彈性，并估計了公共政策的影響，例如票價上漲。另外，在本文中，我們嘗試開發一種計量經濟學方法，該方法將時間序列和靜態模型（例如邏輯回歸）的預測統一起來。通過使用一個典范模型并改變基本假設和因變量的分布，我們表明可以以不太不同的方式獲得預測結果。只有優化算法不同。上面強調的兩種方法似乎很有用，因為它們可用于解釋人類行為的動態。這是對運輸經濟學領域的主要貢獻之一。

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作者
Hantar, Michel Emanuel.;
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作者單位

City University of New York.;

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授予單位 City University of New York.;
學科 Economics General.; Economics Finance.; Transportation.; Operations Research.
學位 Ph.D.
年度 2000
頁碼 133 p.
總頁數 133
原文格式 PDF
正文語種 eng
中圖分類經濟學;財政、金融;綜合運輸;運籌學;
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Determinants of subway travel in the New York City Metropolitan Area: An empirical research and econometric application of discrete choice and time series models to urban travel demand.

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