Question

What is the statistical tool that I should be using to determine the impact of working capital management on sustainable growth.

Answer 1

Solution:

• The sustainable growth rate (SGR) indicates  the maximum rate of growth that a company can sustain without any additional infusion of funds in the form of debt or  equity or debt.
• For achieving high sustainable growth you need to maximize sales efforts, and focus  on high-margin products, and managing inventory accounts payable and accounts receivable.
• Managing Inventory, accounts payable and accounts receivable is a part of working capital management, to determine the impact of working capital management on sustainable growth statistical tool like Regression analysis for assessing the  the impact of impact of working capital components on dependent variables like sustainable growth can be employed
• Regression analysis mathematically establishes he relationship between independent variables and the dependent variable.
• Regression Analysis provides a regression equation where the coefficients represent the relationship between each independent variable and the dependent variable.
• It can also predict the mean value of the dependent variable (Sustainable growth ) on specifying the values for the independent variables ( e.g. Inventory, accounts payable and accounts receivable) . You can also use regression to make predictions based on the values of the predictors the independent variables ( e.g. Inventory, accounts payable and accounts receivable.
• Regression analysis produces a regression equation where the coefficients represent the relationship between each independent variable and the dependent variable. You can also use the equation to make predictions.
• The equation has the form Y=a+b X, where Y is the dependent variable (that's the variable that goes on the Y axis), X is the independent variable (i.e. it is plotted on the X axis), b is the slope of the line and a is the y-intercept.

• The Formula for Multiple Linear Regression Is

  Yi​ = β0​ + β1​Xi1​ + β2​Xi2​ +...+ βp​Xip​ + ϵ

• where,

• for i=n observations:

• Yi​ =dependent variable

• Xi​= explanatory variables(Independent variable )

• β0​=y-intercept (constant term)

• βp =slope coefficients for each explanatory variableϵ=the model’s error term (also known as the residuals)​