Pattern classification on specifics of public sector investments and budgeting principles

Lukáš Bernat, Radka Michlová, H. Mitwallyová
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Abstract

The aim of the study is to find patterns in an exact complete data set containing the annual budget of all municipal subjects in the Czech Republic over the past 20 years. The focus of the analysis is on which resources could enable the development of and investment in municipal assets, especially estate property. The financial and real estate analysis (FAMA) method was chosen, which provides comparable indicators to calculate the debt service and other related features of subject performance on a municipal level. These indicators demonstrate whether municipal subjects follow responsible budgeting principles and/or how they utilize their own resources. Comparing similar studies using mentioned data and methodology there is a gap between context of data in time a relation chosen indicators. The reason of obstacle is to put data in time-series and properly analyze them. This appropriate items of indicators are aggregated so all the connections between them and other items are lost. In enormous amount of data study uses classification tools to unfold hidden patterns how does municipal budgeting develop in time without knowing details about each case in context of debt and assets. Study convert time dimension to static indicator of its dynamics a using pure K-Means classification conclude having 6 different clusters which differ each other in some of indicators. Within broader context of those clusters we propose an overview of municipal budgeting strategies. In big cities dominates financing of investment by debt and the rest of clusters differs usually significantly with small impact of their population size that is one of determinants budget income therefore essential budget part.
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公共部门投资具体情况的模式分类和预算编制原则
这项研究的目的是在一个准确完整的数据集中找到模式,该数据集包含捷克共和国过去20年所有市政科目的年度预算。分析的重点是哪些资源可以促进市政资产的开发和投资,尤其是房地产。选择了金融和房地产分析(FAMA)方法,该方法提供了可比指标,用于计算市一级的偿债情况和主体绩效的其他相关特征。这些指标表明市政主体是否遵循负责任的预算编制原则和/或如何利用自己的资源。比较使用上述数据和方法的类似研究,数据上下文与时间关系选择的指标之间存在差距。障碍的原因是将数据放在时间序列中并对其进行适当的分析。这些适当的指标项目被聚合,因此它们与其他项目之间的所有连接都会丢失。在大量的数据中,研究使用分类工具来揭示隐藏的模式,即在不了解债务和资产背景下每个案例的细节的情况下,市政预算是如何及时发展的。研究将时间维度转换为其动态的静态指标,使用纯K-Means分类得出结论,有6个不同的聚类,在某些指标上彼此不同。在这些集群的更广泛背景下,我们建议对市政预算战略进行概述。在大城市,债务投资融资占主导地位,而其他集群通常差异很大,其人口规模的影响很小,这是预算收入的决定因素之一,因此是必不可少的预算部分。
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