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摩托车拥有和使用的动态分析:面板数据建模方法。

A dynamic analysis of motorcycle ownership and usage: a panel data modeling approach.

机构信息

Department of Transportation Technology and Management, Feng Chia University, 100 Wenhua Road, Taichung 40724, Taiwan, ROC.

出版信息

Accid Anal Prev. 2012 Nov;49:193-202. doi: 10.1016/j.aap.2011.03.006. Epub 2011 Mar 30.

DOI:10.1016/j.aap.2011.03.006
PMID:23036396
Abstract

This study aims to develop motorcycle ownership and usage models with consideration of the state dependence and heterogeneity effects based on a large-scale questionnaire panel survey on vehicle owners. To account for the independence among alternatives and heterogeneity among individuals, the modeling structure of motorcycle ownership adopts disaggregate choice models considering the multinomial, nested, and mixed logit formulations. Three types of panel data regression models--ordinary, fixed, and random effects--are developed and compared for motorcycle usage. The estimation results show that motorcycle ownership in the previous year does exercise a significantly positive effect on the number of motorcycles owned by households in the current year, suggesting that the state dependence effect does exist in motorcycle ownership decisions. In addition, the fixed effects model is the preferred specification for modeling motorcycle usage, indicating strong evidence for existence of heterogeneity. Among various management strategies evaluated under different scenarios, increasing gas prices and parking fees will lead to larger reductions in total kilometers traveled.

摘要

本研究旨在基于大规模车主问卷调查面板数据,考虑状态依存性和异质性效应,开发摩托车拥有和使用模型。为了考虑到替代品之间的独立性和个体之间的异质性,摩托车拥有模型的建模结构采用了考虑多项、嵌套和混合逻辑回归公式的离散选择模型。针对摩托车使用情况,开发并比较了三种面板数据回归模型——普通、固定和随机效应模型。估计结果表明,前一年的摩托车拥有情况对当年家庭拥有的摩托车数量产生了显著的正向影响,这表明摩托车拥有决策中存在状态依存效应。此外,固定效应模型是摩托车使用情况建模的首选规格,这表明存在很强的异质性证据。在不同情景下评估的各种管理策略中,提高油价和停车费将导致总行驶里程的大幅减少。

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Comparison of traffic-injury related hospitalisation between bicyclists and motorcyclists in Taiwan.台湾自行车骑行者与摩托车骑行者交通伤相关住院情况的比较。
PLoS One. 2018 Jan 17;13(1):e0191221. doi: 10.1371/journal.pone.0191221. eCollection 2018.