Revenue-Expense Matching, Political Connections and Firm Investment Efficiency: Evidence from Malaysia

Abstract Research aim: This study examines the interplay between revenue-expense matching, political connections, and firm investment efficiency within the Malaysian context. Design/ Methodology/ Approach: Drawing on the revenue-expense matching framework proposed by Dichev and Tang (2008), we construct a measure of matching quality and employ ordinary least squares (OLS) regression on a sample of 570 Malaysian publicly listed firms over the period 2000-2017 to investigate two key issues: (1) the extent to which matching quality influences investment efficiency, and (2) whether political connections moderate this relationship. Research finding: The empirical evidence indicates that stronger revenue-expense matching is positively associated with improved investment efficiency. However, this beneficial effect is significantly weakened in the presence of political ties. Further analyses suggest that this moderating influence is particularly pronounced among government-linked companies. Additionally, high-quality matching appears to reduce both overinvestment and underinvestment, although these advantages are markedly less evident in politically connected firms. Practitioner/Policy implication: While previous research has explored the intersection of financial reporting quality, political affiliations, and corporate investment, this study is among the first to empirically link revenue-expense matching with investment efficiency in the context of political embeddedness. The findings not only enhance understanding of how accounting quality and institutional structures interact to shape investment decisions in emerging markets, but also offer policy insights by highlighting the need for governance mechanisms that curb political influence and foster more efficient capital allocation. Research limitation: This study acknowledges limitations, including potential measurement issues, limited generalizability beyond Malaysia, and endogeneity concerns that future research could address using causal inference methods.