Debt ratio

The term debt ratio refers to a financial indicator that measures the degree of leverage of a company. The debt ratio is defined as the ratio of total debt to total assets, expressed as a decimal or percentage. It can be interpreted as the proportion of a company’s assets financed by debt.

A ratio greater than 1 indicates that a significant proportion of the company’s assets are financed by debt, which means that the company has more liabilities than assets. A high ratio indicates that the company is at risk of defaulting on its debt in the event of a sharp rise in interest rates. A ratio below 1 means that the company is financing the majority of its assets with equity.

Data

The data originate from the web side Mendeley data and are a side-product of the research published by @stanivsic2020empirical. The data involve various primary and secondary data on the Serbian companies from the 2007-2015. They also include the data regarding the accontancy audits. The near explanation of the data presents the above given paper The debt ratio is expressed as the share of (AOP 0424 + AOP 0441 + AOP 0442) / AOP 0071 accounts.

Hypothesis

Larger companies have financial planning, i.e. the size of the company and the financial planning, the larger the firm, the more secure the financial financial planning is more likely. Based on these, my hypothesis is that it will be smaller than the debt ratio.

Our aim is to provide some graphical analysis explaining this fact. We attempt to refute this hypothesis through graphical analysis.

Data processing and results

udaje <<- read.csv2("udaje.csv")      # import of the .csv data to data.frame  
                                               # udaje become global - see operator <<-
#########   cleaning data - identification, where are the data missing 
library(Amelia)
missmap(udaje) 

udaje <<- na.omit(udaje)
missmap(udaje)

For continuing the analysis, the database needs even more reconstruction. First of all, we need exclude variables we do not need for achieving our goals. Inspecting the paper of @stanivsic2020empirical we decided to use just “AOP 0424”,“AOP 0441”,“AOP 0442”,“AOP 0071” columns

selected.cols <- c("AOP424","AOP441","AOP442","AOP71")    
udaje.tmp <<- udaje[,selected.cols]  # extracting just columns defined in the previous line
# substitution of txt variables to numeric ones  (change nothing!!!!)
# rather redundant commands, but avoiding problems of confusing data types (numeric vs texts)
udaje.tmp <- apply(udaje.tmp, c(1,2),  # I defined function within apply  - conversion of data from text to numeric types
                    function(x) as.numeric(as.character(x)))
udaje.tmp <<- data.frame(udaje.tmp)
udaje.tmp$debt.ratio <- ((udaje.tmp$AOP424 + udaje.tmp$AOP441 + udaje.tmp$AOP442) / udaje.tmp$AOP71)
udaje.tmp$total.assets <- udaje.tmp$AOP71                           # CHANGE

# 1st and 3rd quartle of total assets
# identification of the 25th percentil - 25 percent of the firms have  less total.assets then quart1
quart1 <- quantile(udaje.tmp$total.assets, probs = 0.25)    
quart3 <- quantile(udaje.tmp$total.assets, probs = 0.75)
# library
library(ggplot2)      # highly popular library for plotting, however, I have not used it
                      # see https://r-graph-gallery.com/ to choose th3e plot and find an appropriate code

 

boxplot(udaje.tmp$debt.ratio[udaje.tmp$total.assets >= quart3], udaje.tmp$debt.ratio[udaje.tmp$total.assets <= quart3], 
         names = c("Large firms", "Small firms"), # CHANGE
         ylab = "Debt.ratio", 
         main = "Figure")

We are not able to see, whether the boxex overlay, because of the oulier data. That is, why I decided to change the vertical axes scale in the graph as follows

boxplot(udaje.tmp$debt.ratio[udaje.tmp$total.assets >= quart3], udaje.tmp$debt.ratio[udaje.tmp$total.assets <= quart3], 
         names = c("Large firms", "Small firms"), # CHANGE
         ylab = "Debt.ratio", 
         main = "Figure",
        ylim = c(0,10))

Now, we clarly see that boxes (rectanles) overlay - ther is no difference between large and small firms if speaking about debt ratio.