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This essay attempts to study the negative features of politics in Augustine's The City of God (De Civitate Dei). Augustine is not an anarchist who believes that the state and the authority are an irreplaceable tool to maintain peace. However, Augustine's thought has no place in the vision of a politics of perfection, in which all-wise rulers devise truly good and lasting solution for social problems and in which contented subjects live together in stable harmony. Politics is a realm in which fallible, sinful men work out imperfect, precarious solutions to recurring difficulties and tension. He thinks state and coercive are a result of human sinfulness. All coercive power like the institutions of property and slavery, was a divinely sanctioned remedy and punishment for sin. Augustine also made a new definition of the "Republic". He leaves just out of his definition of the republic entirely and to accept a minimalist and amoral description.

China's rapid urbanisation in the past 30 years has been a prominent issue in the world. However, few studies elaborate on the rapid spatial urbanisation from the perspective of local decision makers (in particular the Secretaries of Municipal Party Committees-the SMPCs). Local governors are always seeking promotions as they are in a competitive bureaucratic hierarchy. This research is, therefore, intended to explain the local decision-making driving force of spatial urbanisation by analysing the interaction between local decision makers' tenures and urban expansion. Based on the panel data of all 286 prefecture-level cities nationwide from 2000 to 2014, Stata 14.0 was applied to implement regression analysis. Research findings show that SMPCs have, in general, great incentives for promoting rapid urban development. Additionally, SMPCs who are transferred from other municipalities implement more rapid and larger-scale urban development than those who are locally promoted.

Abstract
Many surveys collect information on discrete characteristics and continuous variables, that is, mixed-type variables. Small-area statistics of interest include means or proportions of the response variables as well as their domain means, which are the mean values at each level of a different categorical variable. However, item nonresponse in survey data increases the complexity of small-area estimation. To address this issue, we propose a multivariate mixed-effects model for mixed-type response variables subject to item nonresponse. We apply this method to two data structures where the data are missing completely at random by design. We use empirical data from two separate studies: a survey of pet owners and a dataset from the National Resources Inventory. In these applications, our proposed method leads to improvements relative to a direct estimator and a predictor based on a univariate model.