Statistical considerations for predicting residual value of heavy equipment

Lucko, G; Anderson-Cook, C M and Vorster, M C (2006) Statistical considerations for predicting residual value of heavy equipment. Journal of Construction Engineering and Management, 132(7), pp. 723-732. ISSN 0733-9364

Abstract

Residual value needs to be considered in owning cost calculations for used heavy construction equipment. Its dependency on factors such as manufacturer and model, equipment age, and condition rating can best be examined by analyzing real market data from equipment auctions. Macroeconomic indicators can also be included to examine any potential influence of the overall economy on auction prices. This paper discusses statistical considerations for performing such a residual value analysis. Considerations include the study type, data properties, identifying outlier observations, regression assumptions, and formulating and selecting an appropriate regression model using the adjusted coefficient of determination. A second-order polynomial of equipment age with additive factors appears promising as the final regression model. Adjusted confidence and prediction intervals are created to correctly display residual value. Cross-validation using randomly split halves of the dataset is performed. Actual data for medium track dozers are used to illustrate the validity of the methodology.

Item Type: Article
Uncontrolled Keywords: confidence intervals; construction equipment; cost management; data analysis; economic factors; regression analysis; validation
Index terms: value analysis, construction equipment, economic indicator, manufacturer, regression analysis, cost management, methodology, dataset, regression model, heavy construction, data analysis, validity, validation, confidence interval, economic factor
Subjects: data management, economic concepts, professional development, practitioner, evaluation and assessment methods, accounting and finance, data analysis and analytics, research methods, statistical analysis, financial analysis, infrastructure and transport systems, construction equipment
Topics: Research Practice, Digital Applications, Cost Management, Roles and Professions, Engineering Principles, Information Management, Plant and Equipment
Descriptive scope: 4 PCTA

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