Corporate Restructuring: Empirical Evidence from Singapore

Corporate restructuring is one of the most challenging but widely researched areas in finance literature. A firm faces three restructuring choices: diversify, refocus or do nothing. Prior theoretical and empirical studies independently separate and examine the various determinants (i.e. firm-specifi...

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Bibliographic Details
Main Author: LIU, ZHI WAI
Format: Dissertation (University of Nottingham only)
Language:English
Published: 2015
Subjects:
Online Access:https://eprints.nottingham.ac.uk/29804/
Description
Summary:Corporate restructuring is one of the most challenging but widely researched areas in finance literature. A firm faces three restructuring choices: diversify, refocus or do nothing. Prior theoretical and empirical studies independently separate and examine the various determinants (i.e. firm-specific, industry-specific and general economic conditions) of restructuring decisions. This approach overlooks the important issue that determinants may simultaneously influence the restructuring decisions. Furthermore, prior studies provide inconclusive evidence with regards to investors’ reactions to restructuring announcements. Despite extensive research on corporate restructuring, little attention has been paid to empirically study corporate restructuring in Singapore. To rectify this deficiency, this study investigates the possible determinants that may be associated with the restructuring decisions and announcement effects of restructuring amongst Singapore-listed firms. The sample firms are listed on the Singapore Exchange and the time horizon extends from 2000 to 2011. A cross-sectional study employing a multinomial LOGIT regression is undertaken to examine the determinants of a firm’s restructuring choice. In addition to the LOGIT analysis, an event study is adopted to investigate the announcement effects of restructuring. A major contribution of this study is its inclusion of all firm types: diversifying, refocusing and no-change; single segment and multi-segment, in a unified empirical framework.