FINANCIAL ANALYSIS OF LIQUIDITY, PROFITABILITY AND SOLVENCY WITH
EVA AS A MODERATE VARIABLE IN IMPROVING ECONOMIC VALUE ADDED
MANUFACTURING COMPANIES TIMES OF COVID-19 PERIOD 2019 -2020

FINANCIAL ANALYSIS OF LIQUIDITY, PROFITABILITY AND SOLVENCY WITH
EVA AS A MODERATE VARIABLE IN IMPROVING ECONOMIC VALUE ADDED
MANUFACTURING COMPANIES TIMES OF COVID-19 PERIOD 2019 -2020

Financial Liquidity Ratio, Profitability and Solvency, EVA Moderating Variable; Value-
Added Firm Value (PBV)

The purpose of this study is to find out how financial performance can be applied as a
measuring tool in increasing the Economic Value Added (VA) which contributes to the
increase in Firm Value as measured by its PBV in Manufacturing Companies Listed on the
IDX during the Covid-19 Period 2019 to 2020 The methodology used is the Quantitative
Method by Calculating and Testing Data on X & Y variables from a population of 193
manufacturing companies listed on the IDX 2019-2020, with a sample of 36 companies that
meet the sampling criteria and cover all of the variables studied are 72. Financial Liquidity
Performance measured by CAR, Profitability through ROA, ROI & ROE, while Solvency is
measured by DAR & DER. The Moderating EVA variable is measured by NOPAT – CAPITAL
CHARGES, the Dependent Variable is the Economic Value Added (VA/ Value Added) Firm
Value indicated by the increase in PBV (Price Book Value) as measured by the Market Price
Per Common Share Divided by Book Value Per Share Normal. The research period is limited
to the period before & after the recession which in this case is limited to the Covid19 period
for the 2019-2020 period. Based on the results of the Multiple Regression Analysis Test, it
shows that the regression equation is as follows: Y = 70,560 + 0.035X1 – 0.123X2 + 0.001X3
+ 7.396 X4 + 1.196 X5 – 0.123 X6 + 0.034 X7 + E. Average PBV during the two years of
covid 19 of 70,560 with the other variables at constant state. 7.396, t-count value = 9.956 > ttable
1.98422, significance 0.000 <0.05 or 5%. So ROE has a significant positive effect on
PBV (Y2). While the CAR (X1) with Beta 0.035. T-count value = 1.137 < t-table significance
0, 260 > 0.05 or 5%. So CAR does not have a significant positive effect on PBV (Y2). Likewise
ROA, ROI, DAR & DER are shown by Beta Values: (-0.123);0.001; 1.196, (-0.123) and EVA
0.034 with t-count value -1.034; 0.025; 1.547;-0.802 and EVA t-count value 1.557 < t-table
1.98422. significance > 5%. So the independent variable has no positive effect on PBV (Y2).
ROA (X2) & DER (X6) have a negative effect on PBV (Y2), meaning that if ROA & DER
increase by one unit, then PBV decreases by one unit. On the other hand, if ROA & DER
decrease by one unit, then Y (PBV) will increase by one unit. The results of the R-squared test
are shown to be R 0.811a, R Square 0.658 and Adjusted Square 0.620, meaning that the model
in this study can explain the influence of var X on Y by 62% of which 38% is influenced by
variables outside the model. F test results of 17,576 significance 0.000 < 5% Then all X
variables simultaneously have a significant positive effect on var Y. Based on the Sobel test
results show that: All independent variables X (CAR, ROA, ROI, ROE, DAR & DER with EVA
as the moderating variable is not effective in moderating / mediating the dependent variable Y
(PBV) which means it is important to select & test other moderating variables such as PER or
Tobin's which are expected to be more effectively used as moderating variables in increasing
firm value (PBV), because these variables

Margaretha Prihatiningsih, Yusup Hari Subagya, Vitalis Ari Winidyaningsih

https://jurnal.stie-aas.ac.id/index.php/IJEBAR

2022

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