Effects of investment opportunities on firms' financial performance: a fresh look through a dynamic panel approach and multivariate analysis

Abstract

The aim of this study is to investigate the macroeconomic component Investment Opportunities influence, extracted by the multivariate PCA method, on firms' financial performance. The analysis was conducted in two stages: i) Principal Component Analysis (PCA) to circumvent the multicollinearity problem and identification of the Investment Opportunities variable; and ii) Application of the Systemic Generalized Method of Moments (GMM) both to analyze the relationship between Investment Opportunities and firms' financial performance (measured by current and future ROE), and to correct for data endogeneity. The sample comprises 160 non-financial companies, with quarterly data from 2010 to 2020. We use the PCA method exploratively to identify the first principal component as the predictor variable in the econometric model. It was extracted from macroeconomic variables, which include GDP variation and activity indexes, confidence, and agents’ expectations in Brazilian economy. Finally, we applied the GMM panel data modeling.  The results showed that the Investment Opportunities variable has a positive and significant effect on companies’ financial performance, with persistent effects in future quarters. Furthermore, we demonstrate that financial performance is highly responsive to these opportunities with significant results in all estimated models. This study makes a practical and theoretical contribution by demonstrating, through multivariate analysis, how economic conditions are important exogenous drivers of firm performance and competitive advantage.