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Phase space reconstruction: Methods in applied economics and econometrics.

机译：相空间重构：应用经济学和计量经济学中的方法。

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Market responses to unpredictable events such as preference change, food contamination, or changes in technology and information are not always known. Phase space reconstruction, a tool designed to analyze nonlinear time series, is investigated for use as an econometric tool to detect nonlinear dynamics economic time series. It is applied to examine consumer responses to unpredictable events, changes in dynamic livestock cycles, and nonlinear structure in regression residuals. The empirical application of phase space reconstruction analyzing economic behavior demonstrates an intuitive, appealing, and straightforward demonstration as to the use of this diagnostic tool.;The first essay investigates how to reconstruct dynamic consumer reactions from market events using phase space reconstruction. This approach can provide important and unique empirical insights into consumer reactions to product recall or contaminant events. We apply phase space reconstruction analysis to U.S. meat demand, demonstrating distinct differences between intertemporal shorter run impacts from food safety incidents (e.g., E. Coli and BSE) relative to longer run health effects (e.g., cholesterol). Moreover, we show that consumers have reacted to food safety events differently depending on the particular food contaminate associated with that event.;In the second essay, phase space reconstruction is investigated as a diagnostic tool for determining the structure of detected nonlinear processes in regression residuals. Empirical evidence supporting this approach is provided using simulations from an Ikeda mapping and the S&P 500. Results in the form of phase portraits (e.g., scatter plots of reconstructed dynamical systems) provide qualitative information to discern structural components from apparent randomness and provide insights categorizing structural components into functional classes to enhance econometric/time series modeling efforts.;The third essay applies the technique of phase space reconstruction to investigate U.S. livestock cycles. Results are presented for both pork and cattle cycles, providing empirical evidence that the cycles themselves have slowly diminished. By comparing the two livestock cycles important insights can be made. The phase space analysis suggests that the biological constraint has become a less significant factor in livestock cycles while technology and information are relatively more significant.
机译：市场对不可预测事件（如偏好变化，食品污染或技术和信息变化）的反应并不总是已知的。研究了相空间重构（一种用于分析非线性时间序列的工具），用作计量经济工具来检测非线性动力学经济时间序列。它用于检查消费者对不可预测事件，动态牲畜周期变化以及回归残差的非线性结构的响应。相空间重构在分析经济行为方面的经验应用证明了这种诊断工具的使用的直观，吸引人和直接的演示。第一篇文章探讨了如何利用相空间重构从市场事件中重构动态的消费者反应。这种方法可以为消费者对产品召回或污染事件的反应提供重要而独特的经验见解。我们将相空间重构分析应用于美国肉类需求，证明了食品安全事件（例如大肠杆菌和BSE）对跨时期的短期影响与长期健康影响（例如胆固醇）之间的明显差异。此外，我们表明，消费者对食品安全事件的反应有所不同，具体取决于与该事件相关的特定食品污染物。；在第二篇文章中，研究了相空间重构作为一种诊断工具，用于确定回归残差中检测到的非线性过程的结构。使用池田制图和S＆P 500的模拟提供了支持该方法的经验证据。相图形式的结果（例如，重构动力系统的散点图）提供了定性信息，可以从明显的随机性中辨别出结构组件，并提供对结构进行分类的见解。将组件分为功能类以增强计量经济学/时间序列建模的工作。第三篇文章应用相空间重构技术研究美国牲畜周期。提出了猪和牛周期的结果，提供了经验证明周期本身已逐渐减小。通过比较两个牲畜周期，可以得出重要的见解。相空间分析表明，生物学限制已成为牲畜周期中不太重要的因素，而技术和信息则相对重要。

著录项

  • 作者

    McCullough, Michael Paul.;

  • 作者单位

    Washington State University.;

  • 授予单位 Washington State University.;
  • 学科 Economics General.;Economics Agricultural.
  • 学位 Ph.D.
  • 年度 2008
  • 页码 147 p.
  • 总页数 147
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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