Graduation Year

2026

Document Type

Dissertation

Degree

D.B.A.

Degree Granting Department

Business

Major Professor

Christos Pantzalis, Ph.D.

Co-Major Professor

Ehsan Sheybani, Ph.D.

Committee Member

Dirk Libaers, Ph.D.

Committee Member

Daniel Acheampong, Ph.D.

Keywords

Capital Market Conditions, Corporate Restructuring, Macroeconomic Phenomenon, Panel Logistic Regression, Regulatory Changes, Stock Valuations

Abstract

As an open economy, Singapore has experienced substantial transformations in its mergers and acquisitions (M&A) market over the past several decades, alongside evolving regulatory frameworks designed to maintain its position as a competitive international hub for corporate restructuring. Over the 20 years from 1990 to 2009, Singapore was exposed to a series of major economic shocks, including financial crises, geopolitical conflicts, terrorism, sectoral downturns, oil price shocks, and public health epidemics, all of which were accompanied by pronounced fluctuations in interest rates and equity market conditions. Against this backdrop, this dissertation examines the determinants of M&A waves in Singapore by contrasting neoclassical and behavioral explanations at the industry level. This study examines the effects of economic shocks, regulatory shocks, interest-rate shocks, and capital conditions within a neoclassical framework, while testing market-based behavioral variables within a behavioral framework. Hypotheses are examined across two analytical dimensions: models that include the interest-rate spread and models that exclude it, and, within each dimension, specifications with and without tight capital conditions. In total, ten panel binary logistic regression models are estimated, enabling systematic comparisons across theoretical frameworks and model specifications. The empirical strategy employs Monte Carlo simulation, principal component analysis, and panel logistic regression to ensure robustness and methodological rigor.

The results demonstrate that excluding the interest-rate spread neither weakens nor qualifies the study’s core findings; models estimated without the interest-rate spread yield empirically indistinguishable results from those that include it. Across all specifications, economic shocks emerge as the most powerful, stable, and consistent driver of M&A waves in Singapore, underscoring the central role of real economic disturbances in triggering large-scale corporate restructuring in a small, open economy. Tight capital conditions constitute a second key neoclassical determinant, exhibiting a strong and statistically significant positive main effect in models that include tight capital. However, the interaction between economic shocks and tight capital is statistically insignificant across all specifications, indicating that tight capital does not amplify or moderate the effect of economic shocks on M&A waves; instead, economic shocks and tight capital exert independent and additive effects. A further robust finding is the consistent statistical insignificance of the interest-rate spread across all models, confirming that interest-rate differentials do not play a central role in explaining M&A wave dynamics in Singapore once broader macroeconomic shocks and capital conditions are controlled for. Regulatory shocks are generally insignificant, although they emerge as marginally significant negative predictors in the neoclassical specification excluding the interest-rate spread, suggesting limited and context-dependent regulatory effects. The behavioral models provide partial and context-specific support for market-timing explanations of M&A waves. In the behavioral models, the 3-year compounded stock total return exhibits a statistically significant negative effect on M&A wave occurrence. However, in the combined models, this effect becomes marginally significant and ultimately disappears when tight capital is introduced. Stock market volatility and the market-to-book ratios are consistently insignificant across all specifications.

Model comparisons indicate that neoclassical models consistently outperform behavioral models in terms of goodness-of-fit and predictive accuracy. Among all estimated models, the neoclassical model with tight capital and the interest-rate spread emerges as the best-performing and key model, while combined neoclassical–behavioral models offer incremental improvements in fit without altering the identity of the key explanatory drivers. Importantly, the area under the receiver operating characteristic curve (ROC) remains uniformly high across all models, regardless of whether the interest-rate spread is included, confirming the strong predictive power of the models in identifying the M&A waves. Taken together, M&A waves in Singapore are fundamentally a macroeconomic phenomenon, driven primarily by real economic shocks and capital conditions rather than by interest-rate dynamics or speculative market behavior. By providing comprehensive evidence from a small, open economy, this dissertation strengthens the neoclassical interpretation of merger waves, clarifies the limited role of behavioral explanations at the industry level, and offers a coherent framework for understanding merger cycles in internationally integrated economies.

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