{"title":"Basic Economic Principles: A Methodical Approach to Deriving Production Cost Estimating Relationships (CERs)","authors":"Roy E. Smoker","doi":"10.1080/1941658X.2010.10462229","DOIUrl":null,"url":null,"abstract":"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:","PeriodicalId":390877,"journal":{"name":"Journal of Cost Analysis and Parametrics","volume":"192 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cost Analysis and Parametrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/1941658X.2010.10462229","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
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: