A comparative analysis of long-term performance of construction and non-construction IPOs in India
A panel data investigation
Author(s): |
Harish Kumar Singla
|
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Medium: | journal article |
Language(s): | English |
Published in: | Engineering, Construction and Architectural Management, October 2019, n. 10, v. 26 |
Page(s): | 2447-2473 |
DOI: | 10.1108/ecam-01-2019-0009 |
Abstract: |
PurposeThe purpose of this paper is to analyze the long-term performance of construction sector initial public offers (IPO) made in India during 2006–2015. The study aims to compare the performance of the construction sector IPOs with the non-construction sector IPOs and finds the determinants of long-term performance of construction sector IPO with a time horizon of three years. The study also attempts to find out, if the long-term IPO underpricing that has been discussed in the literature, really exists or it is a myth. Design/methodology/approachThe study uses data of IPOs listed on National stock exchange during 2006–2015. In total, 281 IPOs are considered for the study, among which 44 are construction sector IPOs. IPOs anniversary performance of three successive years is calculated from the date of listing, and a random effect panel regression model with clustered robust estimates using the maximum likelihood method is performed to find out the determinants of IPO performance. The data are also tested for multicollinearity, stationarity and heteroscedasticity to ensure the robustness of results. FindingsThe results show that in the long-run construction sector IPOs outperform the non-construction sector IPOs, though the performance is below average when compared to market returns. The IPO underpricing is a myth, and IPO underperformance is a reality in India. The performance of construction sector IPOs is driven positively by market return, size of the firm and negatively by liquidity of the firm. Originality/valueThe paper is the first attempt to analyze the performance of construction sector IPOs, and compare it with non-construction sector IPOs. The study uses a random effect panel regression model with robust estimates using the maximum likelihood method to ensure the robustness of results. This is the first time the performance of IPOs is studied with a panel data approach. |
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26/02/2021