Abstract
Econometrics is currently one of the most popular approaches to economic analysis. To better support advances in these areas as much as possible, it is necessary to apply econometric problems to econometric intelligent systems. The article describes an econometric OLAP framework that supports the design of a multidimensional database to secure econometric analyses to increase the effectiveness of the development of econometric intelligent systems. The first part of the article consists of the creation of formal rules for the new transformation of the econometric model (TEM) method for the econometric model transformation of multidimensional schema through the use of mathematical notation. In the proposed TEM method, the authors pay attention to the measurement of quality and understandability of the multidimensional schema, and compare the proposed method with the original TEM-CM method. In the second part of the article, the authors create a multidimensional database prototype according to the new TEM method and design an OLAP application for econometric analysis.
Highlights
The field of econometrics has developed rapidly in the last three decades, and its applications can be found in several areas, such as determination of the level of interest rates, estimation of the price elasticity of oil demand, and the production analysis of business
We introduce an upgraded transformation of the econometric model (TEM) method, which is based on our original TEM-CM method, for conceptual database design based on econometric models
We present the Because no comprehensive approach to creating econometric systems using online analytical processing (OLAP) exists, our goal is to suggest a new econometric model for online analytical processing (EM-OLAP) framework to improve the design of econometrics-based intelligent systems
Summary
The field of econometrics has developed rapidly in the last three decades, and its applications can be found in several areas, such as determination of the level of interest rates, estimation of the price elasticity of oil demand, and the production analysis of business. Econometrics has become an interesting tool that enables the extraction of useful information regarding important business matters related to a company and the economy. The application of econometric models is a nontrivial process that requires a good understanding of mathematics and statistics. Several econometric software programs and tools exist. Another study (Kusters et al 2006) introduced several specific problems related to present econometric and prognostic software. The authors mentioned that it is not possible to solve these problems using methodological innovations; rather, a correct and appropriate construction of the database is required. Software and database designers should establish an environment in which information, along with time series to be predicted, can be stored to enable a consequent analysis and methodological improvements.
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