基本经济学原理:生产成本估算关系的系统推导

Roy E. Smoker
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摘要

本文讨论了应用经济理论背景下成本估算问题的一些经典分析、数据收集、呈现和解释方法。其目的是表明,基本的微观经济学原理蕴涵着数学性质,对于这些性质,参数的不确定值可以用统计分析方法来测量。统计可以被定义为对数字数据的收集、呈现、分析和解释,而经济理论关注的是变量之间的关系。由于经济现象不是从统计控制的实验中得到的,所以必须设计出分析非实验数据的特殊方法来解释相关的行为模式。在本文中,我研究了一个简单的方程,其中成本是一个或多个成本驱动因素的函数,并显示了产生自变量(成本驱动因素)的过程规范,产生未观察到的干扰的过程,以及将这些与观察到的因变量(例如,必须依靠统计推断的规则和标准,从给定的观察样本中发展出一种衡量经济理论关系的合理方法。最后,我探讨了假设的具体检验,以检查是否符合经典统计假设的正态性、均方差和连续误差的独立性。在将注意力转向统计实验和数据收集的特性之前,有必要描述成本估算者在开发或应用成本估算关系时必须考虑的系统的一些基本技术方面。首先,每个系统都由几个子系统及其相应的组件组成。这些组件被确定为需要进行成本估算的最低级别元素,它们被定义为基本工作分解结构(WBS)最终项目,当集成到整个系统中时,它们定义了通过对每个元素应用cer来估算的工作范围。对于WBS中的每个最终项目,成本估算人员必须选择适当的成本模型、CER或类似的成本进度曲线来估算成本。考虑什么是合适的取决于每个WBS最终项目的定义。必须解决下列问题:
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Basic Economic Principles: A Methodical Approach to Deriving Production Cost Estimating Relationships (CERs)
This article addresses some of the classical methods of analysis, data collection, presentation, and interpretation of cost-estimating problems in the context of applied economic theory. The purpose is to show that basic microeconomic principles imply mathematical properties for which the uncertain values of the parameters may be measured using statistical methods of analysis. While statistics may be defined as the collection, presentation, analysis, and interpretation of numerical data, economic theory is concerned with relationships among variables. Since economic phenomena are not obtained from statistically controlled experiments1, special methods of analysis of non-experimental data have to be devised to explain related patterns of behavior. In this article, I examine a simple equation where cost is a function of one or more cost drivers and shows that specifications of the process by which the independent variables (cost drivers) are generated, the process by which unobserved disturbances are generated, and the relationship connecting these to the observed dependent variables (e.g., cost) are necessary to rely on the rules and criteria of statistical inference to develop a rational method of measuring the economic theory relationship from a given sample of observations. Finally, I explore specific tests of hypotheses to check whether or not the classical statistical assumptions of normality, homoscedasticity, and independence of successive errors are met. Before turning attention to the properties of statistical experiments and data collection, it is necessary to describe some of the basic technical aspects of the system that a cost estimator must consider when developing or applying cost-estimating relationships. First, each system is made up of several subsystems and their corresponding components. These components, identified as the lowest-level elements for which a cost estimate is required, are defined as the basic work breakdown structure (WBS) end items that, when integrated into the total system, define the scope of work to be estimated by the application of CERs to each element. For each end item in the WBS, the cost estimator must select the appropriate cost model, CER, or analogous cost-progress curve to estimate the costs. Consideration as to what is appropriate depends on the definition for each WBS end item. The following questions must be addressed:
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