A researcher has estimated the following multiple regression model to investigate the determinants of capital structure in an emerging market based on data from 2016. LEV = 1.32 – 0.10TANG - 0.28PROFIT + 0.19GROWTH + e (0.92) (0.03) (0.25) (0.04) Residual sum of squares = 200 Total sum of squares = 620 Number of Observations = 90 Standard errors of the coefficients are given in parentheses. The variables are: LEV = Leverage (total debt to total assets). TANG = Tangibility (net fixed assets to total assets). PROFIT = Profitability (net income to total assets). GROWTH = Firm growth (Percent change in sales). e = residual For each independent variable slope coefficient, test the null hypothesis that it is equal to zero against the alternative hypothesis that it is not equal to 0. The critical t value is 1.96 at the 5% significance level for a two-tailed test.
A researcher has estimated the following multiple regression model to investigate the determinants of capital structure in an emerging market based on data from 2016.
LEV = 1.32 – 0.10TANG - 0.28PROFIT + 0.19GROWTH + e (0.92) (0.03) (0.25) (0.04)
Residual sum of squares = 200
Total sum of squares = 620
Number of Observations = 90
Standard errors of the coefficients are given in parentheses.
The variables are:
LEV = Leverage (total debt to total assets).
TANG = Tangibility (net fixed assets to total assets). PROFIT = Profitability (net income to total assets). GROWTH = Firm growth (Percent change in sales). e = residual
For each independent variable slope coefficient, test the null hypothesis that it is equal to zero against the alternative hypothesis that it is not equal to 0. The critical t value is 1.96 at the 5% significance level for a two-tailed test.
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