Abstract
Purpose – This study aims to examine the existence of capital structure dynamics and speed of adjustment during different economic periods. This study adds to the existing body of literature by investigating the factors influencing adjustment process toward target debt in developing economies. Design/methodology/approach – By employing two-step generalized method of moment (GMM) and sensitivity analysis, the study highlights critical factors which affect firms’ adjustment mechanism for target debt. Findings – Dynamic GMM estimations confirm the substance of past leverage on current debt, which recognizes the existence of dynamic capital structure. The findings corroborate that adjustment process is subject to trade-off between convergence rate and cost of being off-target. The fraction of financing of Pakistani firms confirms the pattern of pecking order hypothesis. The outcome of study clearly validates the significance of dynamic trade-off modeling for optimal capital structure. Research limitations/implications – As more data become available, the authors would extend this study to investigate the sectoral analysis to find how capital structure dynamics are different across sectors and how distinctive behavior of each sector differently affects the adjustment process toward target debt across each sector. In addition, sector-level and macro-economic factors could be incorporated to examine how external factors affect the firm’s speed of adjustment across sectors. Practical implications – The present study provides valuable insights for banking and corporate sector, mainly in Pakistan. The companies could take into consideration the firm-level factors which affect the adjustment process toward target debt. Likewise, the borrowing and lending procedures could be advanced by complying with dynamic mechanism of speed of adjustment. Furthermore, the findings of this research provide obstinate grounds for future research. Originality/value – Both the use of dynamic GMM adjustment model and sensitivity analysis along with Sargan test validate the health of instruments and values.
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