Erasmus University Rotterdam Erasmus School of Economics Master Accounting, Auditing and Control Master's Thesis Accounting, Auditing & Control Successful-Efforts
Earnings model for the cash-expense method
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- 6.3.1 Meeting assumptions
- 6.3.2 Regression model
Earnings model for the cash-expense methodThe third model focuses on the profit and loss account. This is the earnings model for the cash-expense method. This method prescribes that all research and development expenditures must be disclosed as cost when incurred. This method is incorporated in the third regression model. The first section of this paragraph tests the assumptions with the regression models. The second section provides the test results from the regression model. 6.3.1 Meeting assumptionsThe assumptions normality, homoscedasticity, linearity are tested. The histograms and the scatterplots are placed in appendix three. The assumption normality is met for all variables but the variable RDEXP is not normal distributed. The sample is 111 and this is large enough to base this assumption on the central limit theorem. The scatterplots show that the homoscedasticity and linearity assumptions are met. The fourth assumption is non multicollinearity. This assumption not met for the absolute variables net income before R&D expenditures and R&D expenditures. R&D expenditures are a component of the net income before R&D expenditures. This can not be tested differently. This should be kept in mind during the analysis. The other variables meet the assumption non multicollinearity. 6.3.2 Regression modelThe third analysis is for the earnings returns relation specified for the cash-expense method for disclosing research and development expenditures. The first model is with the variables scaled by market value. This model showed an explanatory power of 0,174. Beside that the variables are all significant. The increase in R&D expenditures has to a negative effect on the returns. The fourth assumption for regression is multicollinearity. This assumption is met, because the variance inflation factors are below ten. The SPSS results are presented below.
Afterwards this model is controlled with the variables common law/code law and RD intensity. The distinction between common law and code law isn’t significant. The R&D intensity is significant and increased the explanatory power to 0,303. This SPSS output is presented below. The other relations stay to exist.
This earnings model for the cash-expense method isn’t only tested with the scaled variables, but also with the absolute values. The model with the absolute values gives an explanatory power of 0,456. The variables have a significant relation with the returns. The net income has and positive effect on the returns. The R&D expenditures and the change variables have a negative impact on the returns. Only the variance inflation factor is for the non mutation variables above ten. This means that there is multicollinearity. This is caused because the research and development expenditures are part of the net income before R&D expenditures. The multicollinearity should be taken into account during the analysis of the results. The SPSS outputs are presented below
Also this model is controlled with control variables. The control variables are not significant and the explanatory power almost remains the same at 0,459. This means that the same relation holds.
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