The main purpose of this study is to determine if a Bayesian approach can better capture and provide reasonable predictions for the complex linkage between crime and income inequality. In this research, we conduct a model comparison between classical inference and Bayesian inference. The conventional studies on the relationship between crime and income inequality usually employ regression analysis to demonstrate whether these two issues are associated. However, there seems to be lack of use of Bayesian approaches in regard to this matter. Studying the panel data of China from 1993 to 2009, we found that in addition to a linear mixed effects model, a Bayesian hierarchical model with informative prior is also a good model to describe the linkage between crime rate and income inequality. The choice of models really depends on the research needs and data availability. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/22551 |
| Date | 05 December 2013 |
| Creators | Zhang, Wenjie, active 2013 |
| Source Sets | University of Texas |
| Language | en_US |
| Detected Language | English |
| Format | application/pdf |
Page generated in 0.0022 seconds