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Structural equation modeling with time dependence: an application comparing Brazilian energy distributors
AStA Advances in Statistical Analysis ( IF 1.4 ) Pub Date : 2020-08-18 , DOI: 10.1007/s10182-020-00377-2
Vinícius Diniz Mayrink , Renato Valladares Panaro , Marcelo Azevedo Costa

This study proposes a Bayesian structural equation model (SEM) to explore financial and economic sustainability indicators, considered by the Brazilian energy regulator (ANEEL), to evaluate the performance of energy distribution companies. The methodology applies confirmatory factor analysis for dimension reduction of the original multivariate data set into few representative latent variables (factors). In addition, a regression structure is defined to establish the impact of the factors over the response “indebtedness” of the companies; this is a central aspect regularly discussed within ANEEL to identify whether a distributor may have difficulty to manage the concession. Most of the variables in this study are collected for 8 different years (2011–2018); therefore, a time dependence is inserted in the analysis to correlate observations. The SEM approach has several advantages in this context: it avoids using criticized deterministic formulations to measure non-observable aspects of the distributors, it allows a broad statistical analysis exploring elements that cannot be investigated through the simple descriptive studies currently developed by the regulator, and finally, it provides tools to properly rank and compare distances between companies. The Bayesian view is a powerful option to handle the SEM fit here, since convergence issues, due to sample size and high dimensionality, may be experienced via classical alternatives based on maximization.



中文翻译:

具有时间依赖性的结构方程模型:比较巴西能源分销商的应用

这项研究提出了贝叶斯结构方程模型(SEM),以探索巴西能源监管机构(ANEEL)考虑的金融和经济可持续性指标,以评估能源分销公司的绩效。该方法应用验证性因子分析,以将原始多元数据集的维数缩减为几个代表性的潜在变量(因子)。另外,定义了一种回归结构来建立因素对公司响应“负债”的影响。这是ANEEL内部定期讨论的主要方面,以确定分销商是否可能难以管理特许权。本研究中的大多数变量收集了8个不同年份(2011-2018年)的数据。因此,在分析中插入了时间依赖性以关联观察值。SEM方法在这种情况下具有多个优势:避免使用批评性的确定性公式来衡量分销商不可观察的方面;它允许进行广泛的统计分析,探索无法通过监管机构当前开展的简单描述性研究进行调查的要素;以及最后,它提供了适当排名和比较公司之间距离的工具。贝叶斯视图是处理SEM拟合的有力选择,因为由于样本量大和维数大,可能会通过基于最大化的经典替代方法遇到收敛问题。它允许进行广泛的统计分析,探索无法通过监管机构当前开发的简单描述性研究进行调查的要素,最后,它提供了适当地对公司之间的距离进行排名和比较的工具。贝叶斯视图是在这里处理SEM拟合的有力选择,因为由于样本量大和维数大,可能会通过基于最大化的经典替代方法遇到收敛问题。它允许进行广泛的统计分析,探索无法通过监管机构当前进行的简单描述性研究进行调查的要素,最后,它提供了适当地对公司之间的距离进行排名和比较的工具。贝叶斯视图是在这里处理SEM拟合的有力选择,因为由于样本量大和维数大,可能会通过基于最大化的经典替代方法遇到收敛问题。

更新日期:2020-08-18
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