ABSTRACT
Firms must access financial markets to surpass financial barriers limiting innovation activities. However, an overreliance on debt might moderate creativity and innovativeness. From a sample of European manufacturing firms, and applying a system of equations using GSEM, we derive a function to determine the thresholds of the optimal acquisition of working capital and physical investment. Contrasting this information with the descriptive data, firms tend to under-finance working capital, as future short-term needs are more challenging to identify when designing investment plans. Additionally, we find evidence for the heterogeneous financial needs of firms operating in high-tech as compared to low-tech sectors, as well as other differences related to firm age. Overall, this paper demonstrates the existence of an optimal proportion of working capital and physical investment that maximizes innovation activities and firm performance, deriving diminishing returns from debt financing and the complementarities between short-term and long-term financial needs.
Acknowledgements
We thank the participants of the 25th Applied Economics Meeting (1st-2nd of June 2023) for their useful feedback, as well as the organizers and participants of the 11th summer school on Knowledge Dynamics, Industrial Evolution and Economic Development (KID 2023) (3rd to 7th of July 2023).
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
The data supporting the findings of this study are available from the corresponding author upon reasonable request.
Notes
1 GSEM are Generalized Linear Models (GLM) applied to Structural Equation Models (SEM).
2 The introduction of equation (4) in the modelling does not seem to cause multicollinearity issues. Providing only a linear expression or omitting the interaction between working capital and physical investment does not provide relevant differences in the coefficients, standard errors, or significance levels.
3 The coefficients of specification (1) cannot be interpreted directly as marginal effects. Equation (5) shows the marginal effects. Non-significant values must also be introduced to avoid biases in the interpretation of the marginal effects.
4 These are the values which do not include zeros.
5 We applied the following test: , under the null hypothesis that the two coefficients are equal.