@inproceedings{fd0c782ba2a245a79d6103484f592b5d,
title = "A VBA-Module for Converting Integrated Variables into Negative and Positive Cumulative Partial Sums",
abstract = "The objective of this paper is to present our software component entitled TDICPS. We demonstrated how this software component can be utilized by practitioners that are interested in transforming time-series variables into positive and negative parts to account for asymmetric impacts in empirical analyses. TDICPS is created by authors in VBA (Visual Basics for Applications) and it is a module for MS-Excel, which can convert a time-series variable into partial cumulative sums of positive and negative components. It also provides the graphs of these components for a large sample size consisting of more than one million values potentially. The software has also numerous options. In addition to the stochastic trend, the variable can have deterministic fragments also, such as both the drift and the trend or only the drift. Furthermore, an application is provided for decomposing the consumer price index and the interest rates of the US economy into partial segments of positive and negative variations. Any other potential variables can also be decomposed in a similar manner. The decomposed data can then be utilized for conducting asymmetric causality tests or producing the asymmetric impulse response functions as introduced by Hatemi-J (Empir Econ 43:447–456 [5]; Econ Model 36:18–22 [6]). This code is accessible at (Appl Comput Inform. forthcoming. [20]; https://github.com/alanmustafa/Transforming\_Data\_Into\_Cumulative\_Partial\_Sums [25]).",
keywords = "Asymmetry, CPI, Dynamic models, Negative changes, Positive changes, Software-component, The US interest rates, The VBA",
author = "Abdulnasser Hatemi-J and Alan Mustafa",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 17th Annual Scientific International Conference for Business on Digital Economy and Business Analytics, SICB 2021 ; Conference date: 25-10-2021 Through 27-10-2021",
year = "2022",
doi = "10.1007/978-3-031-05258-3\_13",
language = "English",
isbn = "9783031052576",
series = "Studies in Computational Intelligence",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "135--148",
editor = "Yaseen, \{Saad G.\}",
booktitle = "Digital Economy, Business Analytics, and Big Data Analytics Applications",
}