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Estimating spatial interdependence in automobile choice with multilevel data.

机译:利用多级数据估算汽车选择中的空间相互依赖性。

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摘要

Traditionally, researchers studying transportation choice have used data either acquired from household surveys or broad, region-wide aggregates. Problems with survey collection processes are well documented, including consumer resistance, rising costs and limited regional coverage. Aggregate data alone may not offer enough variation or provide sufficient observation of the choice making process. I apply a technique commonly used in health outcomes research, the use of census proxies, to the field of transportation research, facilitating the analysis of any geographic region while avoiding the necessity of conducting additional independent surveys. Specifically, in Chapter 2 I use the 2000 Bay Area Travel Survey (BATS) and the contemporaneous U.S. Census file to evaluate the use of census proxies in applied transportation research. My results indicate that a vehicle choice model composed of proxies effectively approximates survey model parameters, and is attractive in terms of traditional selection criteria and prediction.;The spatial proximity between individuals has been found to affect their likelihood of exhibiting herd behavior in the selection of travel mode choice. In Chapter 3, I use spatial econometrics to evaluate whether consumer interaction influences automobile choices in BATS, and discuss the impact of uncontrolled spatial effects on statistical inference. I find evidence for clustering in the proportionate ownership of several different auto types after controlling for potential confounders, and that spatial effects influence the probability of selecting certain car types.;In Chapter 4, I search for spatial effects in Fresno County Department of Motor Vehicles (DMV) micro-level registration records augmented with socioeconomic and demographic information from the United States census. The resulting dataset is essentially a synthetic survey composed of vehicle characteristics and proxies for household attributes. Again, I demonstrate that auto type ownership is spatially clustered. I address the confounding role of self-selection in area wide auto purchases by accounting for the decision to switch type ownership. In effect, I control for the possibility that individuals with like preferences congregate in certain regions, and estimate the effect of consumer interaction on the probability to select a given car type.
机译:传统上,研究交通选择的研究人员所使用的数据要么是通过家庭调查获得的数据,要么是广泛的,整个地区的汇总数据。调查收集过程中存在的问题已得到充分记录,包括消费者抵制,成本上升和区域覆盖率有限。单靠汇总数据可能无法提供足够的变化或无法充分观察选择过程。我将健康结果研究中常用的一种技术(人口普查代理的使用)应用于交通运输研究领域,以促进对任何地理区域的分析,同时避免进行额外的独立调查的必要性。具体来说,在第2章中,我使用2000年湾区旅行调查(BATS)和同期的美国人口普查文件来评估普查代理在应用交通研究中的使用。我的结果表明,由代理组成的车辆选择模型有效地近似了调查模型参数,并且在传统选择标准和预测方面具有吸引力。;人们发现个体之间的空间接近度会影响他们在选择种群时表现出成群行为的可能性。出行模式选择。在第3章中,我将使用空间计量经济学来评估消费者互动是否会影响BATS中的汽车选择,并讨论不受控制的空间效应对统计推断的影响。在控制了潜在的混杂因素之后,我发现了在几种不同汽车类型的比例所有权中聚集的证据,并且空间效应影响了选择某些汽车类型的可能性。在第4章中,我在弗雷斯诺县机动车辆部门寻找空间效应。 (DMV)微型注册记录,其中增加了来自美国人口普查的社会经济和人口信息。所得数据集本质上是一个综合调查,包括车辆特征和家庭属性代理。再次,我证明了自动类型所有权在空间上是聚类的。通过考虑转换类型所有权的决定,我讨论了自我选择在区域性汽车购买中的混杂作用。实际上,我控制了具有相同偏好的个人聚集在某些区域的可能性,并估计了消费者互动对选择给定汽车类型的可能性的影响。

著录项

  • 作者

    Adjemian, Michael Karabet.;

  • 作者单位

    University of California, Davis.;

  • 授予单位 University of California, Davis.;
  • 学科 Economics General.;Transportation.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 167 p.
  • 总页数 167
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 经济学;综合运输;
  • 关键词

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