Statistical and Computational Methods to Assess Uncertainty and Risk in Accounting

Falta, Michael (2005) Statistical and Computational Methods to Assess Uncertainty and Risk in Accounting. [QUT Thesis]

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Abstract

Informed economic decisions are made on the basis of accounting data. It is therefore crucial to have rigorous and scientific approaches for measuring, modelling and forecasting accounting numbers. Dr Falta’s research was motivated by two observations. Firstly, in accounting practice, decision-making often relies on subjective quantifications and forecasts of business activities and, thus, does not account for uncertainty in a rational way. Secondly, there are some academic foundations for statistical approaches to accounting, yet none has been developed carefully enough for results to penetrate and to contribute to practitioners’ needs. Dr Falta applied components of mathematics, statistics, econometrics, finance and computing to aspects of accounting and auditing. He developed an enhanced framework for scientific measurement of business process costing and recording accounting transaction data. This has enabled a better understanding of risk in accounting-based decision-making. His research is being incorporated in projects with the Royal Australian Navy and SunWater.

ID Code:	16053
Item Type:	QUT Thesis
Keywords :	Accounting allocation problem; Activity-Based Costing (ABC); Activity-Based Risk Analysis (ABRA); Accounting measurement; Auditing analytical procedures; Depreciation; Mathematical Formulation of Activity-Based Costing (MF-ABC); Statistical Activity Cost
Department:	Faculty of Business
Institution :	Queensland University of Technology
Copyright Owner :	Copyright Michael Falta
Deposited On:	03 Dec 2008 13:55
Last Modified:	03 Dec 2008 13:55

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