{"title":"Exploring asymmetric dynamics of R&D spending and firm value nexus: Insights from panel autoregressive distributed lag analysis","authors":"Navjot Kaur, Balwinder Singh","doi":"10.1002/mde.4362","DOIUrl":null,"url":null,"abstract":"The present study aims to provide valuable insights into the impact of research and development (R&D) spending on firm value, considering both short‐term and long‐term dynamics while also considering any potential asymmetries in this relationship. This work is conducted using a sample of 185 listed Indian manufacturing firms over a time span of 18 years, that is, from 2006 to 2023. Both symmetric and asymmetric autoregressive distributed lag (ARDL) are employed on a final sample of 3330 firm‐year observations to unravel the intricacies of the aforementioned relationship. Based on the empirical findings from the symmetric ARDL model, it is revealed that R&D spending positively impacts the value of firms in the long run while showing no significant effect in the short run. On the contrary, the results from the asymmetric ARDL model present interesting insights. In the short run, positive (negative) changes in R&D spending appear to reduce (increase) the value of firms. However, in the long run, positive (negative) changes tend to increase (reduce) the value of companies. The key differentiator of the study is the identification of the asymmetrical impact of R&D spending on firm value. The paper argues that while R&D spending does influence firm value, the relationship between them is not inherently symmetrical. In particular, the impact of R&D spending changes from being statistically insignificant when using symmetric ARDL estimation to becoming significant when applying asymmetrical estimation methods. The findings remain largely consistent across different subsamples and alternative measurements of variables.","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1002/mde.4362","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
The present study aims to provide valuable insights into the impact of research and development (R&D) spending on firm value, considering both short‐term and long‐term dynamics while also considering any potential asymmetries in this relationship. This work is conducted using a sample of 185 listed Indian manufacturing firms over a time span of 18 years, that is, from 2006 to 2023. Both symmetric and asymmetric autoregressive distributed lag (ARDL) are employed on a final sample of 3330 firm‐year observations to unravel the intricacies of the aforementioned relationship. Based on the empirical findings from the symmetric ARDL model, it is revealed that R&D spending positively impacts the value of firms in the long run while showing no significant effect in the short run. On the contrary, the results from the asymmetric ARDL model present interesting insights. In the short run, positive (negative) changes in R&D spending appear to reduce (increase) the value of firms. However, in the long run, positive (negative) changes tend to increase (reduce) the value of companies. The key differentiator of the study is the identification of the asymmetrical impact of R&D spending on firm value. The paper argues that while R&D spending does influence firm value, the relationship between them is not inherently symmetrical. In particular, the impact of R&D spending changes from being statistically insignificant when using symmetric ARDL estimation to becoming significant when applying asymmetrical estimation methods. The findings remain largely consistent across different subsamples and alternative measurements of variables.