Doctoral Dissertation Research: Discrete Time-Series Cross-Section Models of Political Economy
Doctoral Dissertation Research: Discrete Time-Series Cross-Section Models of Political Economy
批准号:
0918320
负责人:
Andrew Martin
金额:
$0.7万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-09-15 至 2010-08-31
中文摘要
离散时间序列横截面(TSCS)数据是包括政治学和经济学在内的许多学科中非常重要的数据类型。TSCS数据具有时间维度和空间维度,具有丰富的分析结构。然而,这种相关的数据结构带来了多种可能的错误来源,并提出了几个重要的方法挑战。本研究将发展一种新的分析TSCS数据的方法:一个具有二维随机效应和p阶自回归误差的贝叶斯广义线性多水平模型,用于分析离散TSCS数据的时空依赖性。该模型使实质性研究人员能够更好地理解所调查的动态过程并进行比较研究。估计所提出的模型的参数并进行计算以促进模型比较是困难的,并且计算量很大。本项目将通过设计一种混合马尔可夫链蒙特卡罗算法来解决这些技术难题,并特别注重仿真效率。为了便于模型选择,本研究还将开发一种相对简单的计算贝叶斯因子的方法。一个设计良好的、用户友好的、开源的R包也将提供给实现所提出的模型和方法的科学界。这个项目将把这个模型应用于国际政治经济学领域的几个重要问题。实质上,该模型将被应用于政治学中“民主优势”理论的研究。
英文摘要
Doctoral Dissertation Research: Discrete Time-Series Cross-Section Models of Political EconomyDiscrete time-series cross-sectional (TSCS) data are a very important type of data in a variety of disciplines, including political science and economics. TSCS data have both a time and spatial dimension and are thus rich in structure for analysis. However, this correlated data structure invites multiple possible sources of error and raises several important methodological challenges.This research will develop a new method for analyzing TSCS data: a Bayesian generalized linear multilevel model with two-dimensional random effects and p-th order autoregressive errors for analyzing the temporal and spatial dependence of discrete TSCS data. The model empowers substantive researchers to better understand the dynamic process under investigation and to conduct comparative studies. Estimating the parameters of the proposed model and performing computations to facilitate model comparison are difficult and computationally intense. This project will solve these technical difficulties by designing a hybrid Markov Chain Monte Carlo algorithm with a special focus on simulation efficiency. To facilitate model choice, this research will also develop a relatively easy means of computing Bayes factors. A well-designed, user-friendly, and open source R package will also be provided to the scientific community that implements the proposed model and methods.This project will apply the model to several important questions in the field of international political economy. Substantively, the model will be applied to studying the "democratic advantage" theory in political science.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
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Molecular Systematics of Lamniform Sharks Using Creatine Kinase Genes
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依托单位:
海外基金