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Corporate finance theories continue to be subjected to empirical testing for possible universalization. The outcomes of the tests have remained diverse, triggering a quest for customized methodological approaches in the conducting of such tests.
The aggregation of data in the tests involving behavioural based decisions on corporate financing is among the theoretical factors challenged by Dr. T. Ngonzi in the paper on “debating the evolution of accounting equation”. The author opines that aggregations tend to hide the practically important case data driven factors in decision making, while exploding the variable driven influences. Variable driven influences are observable through magnitudes. The problem here is that, the cases or corporate entities contributing the highest magnitudes in the aggregates of variable measurements tend to dictate the outcomes, hence skewed conclusions. This can be witnessed in the tests involving the pay-off, pecking order, and capital structure theories. Among the cases in point is the presentation of the “new accounting equation and the dynamic approach to accounting for capital structure” by Mr. P. Ntui (JFA 2013: 1(44) 55-63).
Using cross-case analysis, Ngonzi exposes the salient case characteristics that become influential in the determination of the selection of the financing options for additional assets, as companies appropriate emergent investment opportunities. These are labelled as “antecedent conditions”. The author also shows how the antecedent conditions influence the final settlement state of the companies’ capital structure. While having influence at the initial and final stages, the antecedent conditions are not captured though methods involving aggregations.
Cross-case analysis was also useful in the exposition of the transit or “short term characteristics” in the selection of reserves, borrowing or issue of equity to finance additional investment assets. The selected options and sequence of selection have shown to defy the logic and processes stipulated in the existing financial trade-off and pecking order theories. The theoretical characteristics only “emerge out of long term adjustments as companies fall back to desired states of settlement”, the author observes.
The author goes on to demonstrate modelling for dynamic processes in capital structure, in which he uses lagged variables to capture time differentials in data, and the effects of antecedent conditions. Potential financing options for investment opportunities can be closely predicted if lagged variables are used, rather than basing on the theoretical dictates of the trade-off or pecking order theories, which the study has already demonstrated to be inapplicable.
Tibuhinda Ngonzi, Department of Accountancy and Finance, St. Augustine University, Mwanza, Tanzania.
A paper about the study appeared in the Journal of Finance and Accounting