Abstract
In this study, a tool has been designed and developed for learning about the concept of lag order within a dynamic model, which can be used in any teaching classes on statistics and financial data computation. To show a solution for a complex and multi-step process of finding the optimal lag order for multiple variables data series based on an information criterion a module using Visual Basic for Applications (VBA) for Microsoft Excel (MS Excel) is being developed. This module can be used for estimating a multivariate dynamic model as well as determining the optimal lag order of such a model.
Highlights
The vector autoregression (VAR) model is regularly utilized by practitioners in the empirical analysis of time series data
In this research, we investigate the use of an algorithm named asymmetric causality test which is based on the optimal lag order determined by the information criterion, and design and develop a Visual Basic for Applications (VBA) module suitable for MS Excel 2013 so to help its user avoiding tasks of calculating the optimal lag order for a dataset
After selecting the optimal lag order, the VAR model can be used for multivariate cointegration analysis [37], conducting causality tests [28,38] and estimating the impulse response functions and variance decompositions [39,40]
Summary
The vector autoregression (VAR) model is regularly utilized by practitioners in the empirical analysis of time series data. This model is a seminal contribution by Sims [1], which allows for interaction between the variables in a multivariate sense. The VAR model is known for having good forecasting properties. It can be used for cointegration and causality testing. The full terms of this license may be seen at http://creativecommons.org/licences/by/4.0/legalcode
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