Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Taming theComplexity ofDistributed Lag Models: A Practical Approach toMulticollinearity, Outliers, andAuto-Correlation inFinance Subject The topic of the resource Auto-correlated errors; Distributed lag model; Mean-Squared error; Multicollinearity; Outliers Description An account of the resource This research investigates the application of robust estimators within the finite distributed lag model (DLM), a critical framework in finance research capturing temporal dependencies between lagged explanatory variables and a response variable. Traditional Ordinary Least Squares (OLS) estimation faces challenges when dealing with high lag counts, multicollinearity, and outliers, potentially compromising parameter estimates and model reliability. Employing real-world data from the RBI, spanning the years 20222023 encompassing budgetary and economic variables of Indian states and Union Territories, the study demonstrates that the MMS estimator emerges as the most efficient estimator, showcasing enhanced robustness against outliers and multicollinearity. Additionally, the study reveals positive autocorrelation in residuals, underscoring the importance of robust methods in addressing such issues in financial modeling. This research contributes valuable insights to financial analysts and offers a more accurate understanding of dynamic relationships in financial systems. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. Creator An entity primarily responsible for making the resource Saha S.; Joshi H. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-922 LNNS, pp. 237-245. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-97-0975-5_21" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-97-0975-5_21</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197233085&amp;doi=10.1007%2F978-981-97-0975-5_21&amp;partnerID=40&amp;md5=70367cf41d8ad72d9230018ac4e91e0b" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197233085&amp;doi=10.1007%2f978-981-97-0975-5_21&amp;partnerID=40&amp;md5=70367cf41d8ad72d9230018ac4e91e0b</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981970974-8 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Saha S., Department of Statistics and Data Science, Christ (Deemed to be University), Bengaluru, India; Joshi H., Department of Statistics and Data Science, Christ (Deemed to be University), Bengaluru, India