with higher profitability, which could justify the effect that a more efficient
management of working capital has on corporate profitability.
With regard to the correlations between the independent variables, high values are
found only between the cash conversion cycle and number of days accounts receivable
(0.45) and number of days of inventory (0.70). This was taken into account in
subsequent analyses in order to avoid potential multico linearity problems.
4. Methodology
The effects of working capital management on SME profitability was tested using the
panel data methodology. Specifically, estimates were obtained for the following
equations:
ROAit ¼ b0 þb1ARit þb2SIZEit þb3SGROWit þb4DEBTit þb5GDPGRit þhi
þlt þ 1it
ROAit ¼ b0 þb1INVit þb2SIZEit þb3SGROWit þb4DEBTit þb5GDPGRit þhi
þlt þ 1it
ROAit ¼ b0 þb1APit þb2SIZEit þb3SGROWit þb4DEBTit þb5GDPGRit þhi
þlt þ 1it
ROAit ¼ b0 þb1CCCit þb2SIZEit þb3SGROWit þb4DEBTit þb5GDPGRit þhi
þlt þ 1it
Where ROA measures the return on assets, AR the number of days accounts
receivable, INV the number of days inventories, AP the number of days accounts
payable, CCC the cash conversion cycle, SIZE the company size, SGROW the sales
growth, DEBT the debt level, and GDPGR the annual GDP growth. hi (unobservable
heterogeneity) measures the particular characteristics of each firm. The parameters lt
are time dummy variables that change over time but are equal for all the firms in each
of the periods considered.
This methodology presents important benefits. These include the fact that panel
data methodology assumes that individuals, firms, states or countries are
heterogeneous. Time-series and cross-section data studies not controlling for this
heterogeneity run the risk of obtaining biased results. Furthermore, panel data give
more informative data, more variability, less collinearity among variables, more
degrees of freedom and more efficiency (Baltagi, 2001).
Estimating models from panel data requires the researchers first to determine
whether there is a correlation between the unobservable heterogeneity hi of each firm
and the explanatory variables of the model. If there is a correlation (fixed effects), it
would be possible to obtain the consistent estimation by means of the within-group
estimator. Otherwise (random effects) a more efficient estimator can be achieved by