Evaluation of the Performances of Economic Entities under the Impact of the Accounting Model

Abstract: The accounting model has an important role through the influence in the adoption of decisions that involve planning, solving difficulties, evaluation, action orientation, control and audit. The accounting model realizes the connection between the economic activities and the decisional factors, the primary data regarding the economic activities appearing as an input in the accounting system, and the processed information, necessary for the management represents the output. At both the microeconomic and macroeconomic levels, there is a growing demand for accounting information, which is managed through the accounting model.

Keywords: accounting model; financial performance; evaluation; economic-financial indicators; econometric model

1. Introduction - The Influence of the Accounting Model on the Decisions of Users of Accounting Information

The accounting model involves all the flows, approaches and research tools of that information intended to participate in the organization and implementation of a successful financial management. The optimal use of an accounting model can be considered a first-rate desideratum, without the realization of which it would not be possible to carry out the proposed activities in the desired economic and financial conditions. The performance of the accounting model is dependent on the organization and use of an economic information system that ensures the provision of all useful information to substantiate the decisions taken, a system in which accounting information has the most important share. The accounting model needs a portfolio of data during the activity and even before the actual development of the transactions, aiming at directing the production, commercial and financial activity, depending on the economic situation.

In order to choose the indicators, it is necessary to present as widely and clearly as possible their limits for measuring the overall performance of the company (Tabară & Briciu, 2012, p. 230).

The accounting model is necessary to play an important role by influencing the adoption of decisions that involve planning, solving difficulties, evaluation, action guidance, control and audit. The accounting model must provide support, through the information developed, to the essential needs of internal and external users of accounting information, accounting being in fact a gear that quantifies, and processes and transmits economic and financial information about an economic entity. This is an additional reason why it can be said that the accounting model makes the connection between economic activities and decision makers, the primary data on economic activities appearing as an input in the accounting system, and the information processed by management is output. It is well known that at both the microeconomic and macroeconomic levels there is a growing demand for accounting information, which is managed through the accounting model. In a general sense, accounting information ensures the knowledge and management of assets, equity and obtained results. In this sense, the information reflecting the existence, the movement of the assets and liabilities elements, as well as regarding the obtained result, become accounting information, after being subjected to some processing, if they bring an extra knowledge and only insofar as they can be useful in characterizing an activity carried out by the respective economic entity. The need for accounting information is the basis for determining the economic-financial indicators and at the same time, ensures the necessary certainty for the elaboration of viable forecasts and the adoption of economic decisions at the level of economic entity. The information from the accrual accounting model presents a different, but more accurate, picture of the entity’s financial results, making it easier to know the cost of holding an asset over time in terms of net book value, taking into account depreciation and amortization. This emphasizes the possibility of taking decisions focused on the management of fixed assets due to the clear and transparent recording of their specific information (Boloş, Florea & Trifan, 2004, p. 8).

In figure 1 presents the role and importance of the accounting model for decision making.

Figure 1. The Role and Importance of the Accounting Model for Decision Making

Source: own processing after: Spătărelu & Petec, 2016, p. 611. https://stec.univ-ovidius.ro/html/anale/ENG/2016/2016-I-full/Section-V/32.Spatarelu_Ionut.pdf

For the current period, the accounting model is an opportunity to obtain useful information both for the entity itself and for an increasingly diverse range of users. Through its method of knowledge and its specific procedures, the accounting model provides the necessary amount of information that facilitates the discovery of aspects regarding the efficient use and mobilization of the necessary resources. The positive situation that allows a further development in terms of ensuring financial balance can be reflected only by the analysis, verification and interpretation of the level of cash for short periods of time, as well as the combination of receipts and payments in the period studied.

In accordance with the principles of the accrual accounting model, the financial statements indicate the income and expenses for the financial year, regardless of the date of payment or collection, which leads to a correct review of transactions and can support the determination of flows by applying the cash accounting model. In support of this view, the accrual accounting model provides information so that the auditor can capture the link between the revenue generated and the expenditure incurred, without the need for extra-accounting information, as in the case of using the cash accounting model. The calculation of net profit is favoured by the application of accrual accounting providing a more accurate picture of the real financial position of the business.

In general, three major objectives are influenced by the accounting model as shown in Figure 2.

Looking at the history of this field, since the industrial revolution, more than two centuries ago, elements of economic and financial analysis have appeared in works such as On the Economy of Machinery and Manufactures by Charles Babbage, Administration industrielle et générale by Henri Fayol, A Theory of Production written by Cobb CW and Douglas PH, but also in works belonging to the authors of the Romanian business school.

The first profile work in Romania Compte-Rendu de l’administration des domaines de son Altesse le Grand Vézir Réchid Pacha, depuis le 1er Mars 1853 jusqu’au 1er Maj 1854 belongs to Ionescu Ion de la Brad and was published on June 9 1954. The paper is the first study of accounting and economic analysis, addressing both theoretical and practical issues using data from the Journal and the General Ledger but also from the Profit and Loss Account and Balance Sheet, as the author called them.

Later, other profile publications appear, which include the Critical Analysis of the Balance Sheet of an Enterprise by Slavescu V. published in 1928, The Analysis of the Economic Activity of Industrial Enterprises written by Gheorghiu Al., Margulescu D. and Nisulescu E. in 1961. The current issue being debated around the world is the measurement of adding value to shareholders and is becoming a key issue as more and more entities are open to achieving this. There is no consensus on this quantification of the value created, although most specialists admit the achievement of added value as a major goal of an economic entity. Modern methods of analysis supported by the accounting model try to highlight value creation as opposed to traditional measurements. From the point of view of other creators of specific economic content, the processes, phenomena but also the activities are taken into account in order to achieve some useful goals/results from a social point of view (Epuran & Mihai, 1979, p. 7).

Another opinion is that the economic-financial analysis investigates how to obtain the economic-financial purposes, the determining causes and of the sources regarding the improvements from the perspective of the conscious use and with reasoning specific to the field of the resources of all types in close connection with the imposed requirements and exigencies (Cojocaru, 1997, p. 33).

The research methodology designed to carry out this study, related to the proposed objectives, is based on the following: preliminary documentation, bibliographic documentation, identification of information and criteria that may be useful in addressing the research topic, analysis of all information collected, and establishing ways to interpretation of the information obtained.

The information in the form of data of the researched entities was processed combining the methodology of economic-financial analysis with the methodology of financial diagnosis. Analysis based on the study of financial statements combines the retrospective and forecasting analysis with static and dynamic analysis.

The methodology of financial-accounting analysis referred to methods of qualitative analysis and methods of quantitative analysis, and the methodology of financial-accounting diagnosis focused on methods, techniques and procedures that established the strengths and weaknesses of business financial management either for maintaining existing strategies, or for substantiating new development strategies in a competitive environment.

4. Indicators of the Economic-Financial Analysis Used to Establish the Performance in the Field of Constructions

The objective of the analysis of the economic-financial indicators represents for a wide category of users the obtaining of information that refer to the economic-financial performance, the financial situation, and to the cash flows. The entities that are the object of scientific research in the field of constructions (CAEN code 41-Construction of buildings) are located in the territorial area of the South-Muntenia Region and are placed in the top 34 within the region.

The answers to business problems can be found in the volume of data generated by day-to-day operations, which is an unimaginable increase in construction, which is why entities can analyse, manipulate and provide meaning in a more efficient way to this huge volume of data, leading to a real competitive advantage in the field (Iosif, 2019, p. 57).

In the case of the relationship between two or more influencing factors, the values from the comparison base and the actual ones are used, establishing the difference of all the factors and then, by gradual substitution, the influence of each factor is recorded. This control technique requires compliance with the following rules (Iosif, 2019, p. 38):

Starting from the understanding of the analysis as a method of knowledge, it can be deduced that in the management process, the economic-financial analysis is an operational tool, to know the operation of the system and, on this basis, to initiate measures to regulate malfunctions (Ișfănescu, Stănescu & Băicuși, 1999).

It is time to decide at the end of the research the evolution of the economic-financial indicators studied for the established period: The financial accounting through precise and relevant information from the economic-financial analysis within the accounting model creates an added value within the economic entities in the field constructions.

Solvency reflects the general state of the financial balance of the entities and their ability to pay all monetary obligations (immediate and remote) to third parties. An entity is solvent when the amount of fixed, financial and current assets is at least equal to the total debts or liabilities, and may be solvent, even if at some point, due to lack of liquidity, it does not have the ability to pay. Thus, financial solvency is the ability to repay at maturity the rates and interest on loans committed to banks or other financial institutions. The general solvency ratio is determined as the ratio between total assets and total debt. This indicator reflects the degree of coverage of debts on total assets and the entity’s ability to convert assets into liquidity in order to meet payment obligations. This rate reflects an entity’s ability to meet its maturities in full, both in the short and medium and long term. The level of the coefficient estimated by banks that analyse the financial indicators of the entities when granting them loans must be higher than 1.5 (150%), and the increase in its value indicates a greater financial independence of the economic entity. In situations where it approaches the lower limit, the entity can no longer hope to enter into new medium and long-term loans, as, by continuing to lend, creditors will voluntarily expose themselves to additional risk. Solvency is based on an efficient activity, which results in benefits, being considered the expression of the quality of the financial activity carried out in a given management period in connection with the use and insurance of funds. Losses lead to insolvency.

The percentage of researched entities that have an average annual general solvency ratio below 1.5 varies between 25.71% and 34.29%, which means that over 65% of the studied entities do not have difficulties in covering their debts on the assets they hold them, which reflects an ability of these entities to cover their obligations to creditors.

Following the research on the economic-financial information related to the economic entities belonging to the field of constructions in the South-Muntenia Region of Romania, the situation of the General Solvency Rate in the period 2015-2019 is presented in Figure 1.

Figure 3. Graphic Representation Regarding the Grouping of Entities According to the Level of GSR Annual Average

Following the research, it is noted that the studied entities belonging to the construction field in the South-Muntenia Region of Romania, in an average percentage of 65% recorded in the period 2015-2019 an appropriate level of the General Solvency Rate (Rgs), having no difficulties in paying debts.

The global autonomy rate shows the share of own sources in the total means used to finance the activity of an entity. The share of own financing sources is recommended to be at least 33% of the total sources available to the economic entity in the practical activity.

This indicator reflects the financial independence of the entity. Increasing the share of equity in the balance sheet liability has beneficial effects on total financial autonomy, the higher the equity the less the entity uses loans to finance investments.

To finance the activity, two categories of own financing sources and borrowed financing sources are used. The two categories of funding sources identified complement each other, and it is necessary to respect certain proportions between them in order to maintain the financial independence of the economic entity. Recourse to credit in an uncontrolled manner results in risks that jeopardize the entire activity of the entity. A level of this rate higher than 30-40% is considered satisfactory for reaching the financial balance, while the normal level is according to theory and practice around the level of 50%. Above this limit, the entity may enter into bank loans, but this must be supplemented by the condition that the rate of return is higher than the interest rate. A high level of the rate in question reflects the specific nature of the financing of the activity, giving a high degree of security in financing, while a low level reflects a danger to the financial stability of the entities which would thus rely too heavily on debt.

Following the study on the evolutions in dynamics of the Rate on global autonomy carried out on entities belonging to the construction field in the South-Muntenia Region of Romania, the situation of the General Autonomy Rate in the period 2015-2019 is shown in Figure 4.

Figure 4. Graphic Representation Regarding the Grouping of Entities According to the Level of RAG Annual Average

Analysing Figure 4 it is observed that the share of entities that register an optimal global autonomy is between 62.86% and 68.57% in the analysed period with an evolution that proves constancy.

Therefore, the study conducted for the entire period considered reveals that the entities in the field of construction in the South-Muntenia Region of Romania, recorded in 2015-2019 at least appropriate levels of the Global Autonomy Rate.

The net profit of an entity is an important indicator of the performance of a business, because on the one hand it indicates the demand for its products or services, and on the other hand it indicates how efficient the entity is in providing them. Profit dynamics can be determined by many factors, from which can be noted: the volume of services, setting prices/tariffs for products/services, the volume of production costs (wages, raw materials, etc.), quality of services, labour productivity, speed of capital rotation.

Following the study on the evolutions of profit/loss made on the 34 entities belonging to the field of constructions in the South-Muntenia Region of Romania, the situation in the period 2015-2019 is presented in Figure 5.

Figure 5. Graphic Representation Regarding the Grouping of Entities According to the Level of the Average Annual Result of the Financial Year

In the analysed period, a favourable situation is highlighted by the graphic presentation of the dynamics of the result at the level of the 34 entities in the field of constructions from the South-Muntenia Region of Romania. It is a favourable evolution compared to the significant reductions in 2012 and 2013. The financial performance of the entities studied in the field of constructions in the South-Muntenia Region of Romania, appreciated based on the evolution of the result of the financial year registered a constant and favourable trend in 2015-2019, at region level, the highest percentage of entities that record losses is only 13.5% in 2019.

The total debt rate reflects the share of financing sources attracted in the total liabilities of the entity, being calculated according to the relation:

This rate can be seen as complementary to the overall financial autonomy rate. The maximum allowed value is about 66%, and the normal level is 50%. A favourable situation is registered when the level of this rate decreases due to the repayment of the contracted credits. An increase in this rate may reflect a normal situation only if it is caused by an increase in trade payables by postponing payment terms to suppliers and closely following the gap in receipts and payments.

Another important factor is the financial structure of an entity which refers to the share of participation of various sources of financing in the formation of invested capital. It is identified with that part of the balance sheet that highlights the sources present in the entity, representing the structure of the liability items.

A high share of external financing sources leads to significant additional costs. The entity’s management may consider that the level of these costs can be borne by the optimal use of property, plant and equipment, the acquisition of which has led to an increase in the level of long-term indebtedness.

The global indebtedness ratio practically also reflects the image of the level of equity financing of the activity carried out in the entity (Vintilă, 2005, p. 219).

If a comparison were to be made between the financing structure containing all the elements (regardless of the nature and term for which they are attracted by the entity) and the financial (capital) structure, the latter is defined only on the basis of medium and long-term funding sources. The relationship that is established between the financial structure and the financing structure is practically a relationship from part to whole (Tudose, 2006, pp. 100-101).

Following the study on the entities belonging to the field of constructions from the South-Muntenia Region of Romania, the following emerged: the debt rate, considered as a global indebtedness rate registers a favourable level for a percentage between 62.86% and 68.57% of entities studied in the period 2015-2019. The situation of these entities proves the need for intense attention in view of the fact that a level higher than 66% reflects only an acceptable degree of rate. This situation is shown in Figure 7.

Figure 7. Graphical Representation Regarding the Grouping of Entities According to the Level of the Global Debt Rate

The study on the evolutions of global indebtedness shows a strong capitalization, so that the entities belonging to the construction field from the South-Muntenia Region of Romania, reach a moderate level of global indebtedness, being relatively financially independent from third parties.

The measurement of profitability is most often performed by two rates: ROA (rate of return on total assets) and ROE (rate of return on equity). ROA is calculated by reporting the profit after tax on the entity’s total assets. ROE is calculated by reporting the return on equity. The value of shareholders’ equity eliminates the consequences of the influence of any intangible asset and calculates by subtracting the value of all liabilities and intangible assets from the value of total assets. ROE is often considered to be the most relevant of the rates of return due to the fact that it determines the return on investment of shareholders/associates.

After the onset of the economic and financial crisis in 2008, there was a reduction in the score of the average annual economic rate of return ROA, and the average annual rate of return ROE, an obvious reason being the decrease in the result of the financial year recorded by the entities studied. There was a massive decrease until 2010. The present study captures 2015 as the year in which the score of these rates increases. ROE registers a reduction in 2017, following the evolution of net profit. All these aspects are reflected in Figure 6 - ROE and in Figure7 - ROA, respectively.

With the help of these rates, the way of using the capitals for the constitution of a patrimonial structure adequate to the activity carried out is characterized. The most important rates used for this purpose are: the rate of fixed assets and the rate of current assets.

1) The rate of fixed assets (RAI) is calculated as the ratio between fixed assets and total assets. The normal level of this rate differs from one entity to another, depending on the branch and sector of activity in which it operates. Thus, in the entities in the field of constructions the level will be much higher than in the entities with commercial activity. For an objective assessment, it is necessary that the evolution of this indicator be monitored over time, as well as in comparison with the values recorded at entities with a similar activity profile.

2) Current assets rate (RAC), expresses the share of current assets in total assets. This rate has different values depending on the sector of activity, with higher values in the production and distribution sector, while in the services sector the value is lower. Also, another important factor is the duration of the operating cycle. The level of the rate may also be influenced by certain economic factors, as well as market conditions, so that certain speculative factors may increase or decrease this rate, in particular changes in stock prices.

Figure 8 presents a comparison of the evolutions of the Fixed Assets Rate (RAI), of the Current Assets Rate (RAC), of the Return on Capital (ROE), of the Total Asset Rate of Return (ROA), of the Total Debt Rate (RDT). It is highlighted that the return on equity aims to change the debt from the perspective of debt within the total sources of financing. The higher the borrowing rate, the higher the ROE value will be compared to the ROA level and the use of debt is mirrored in increasing the level of the ratio between the value of total assets and the value of equity. Debts allow entities to increase the value of assets without resorting to a capital increase.

Figure 8. Graphic Representation on the Evolutions of RAI, RAC, ROE, ROA, and RDT

Given that the analysis of profitability targets entities that have a stable level of capital, it is considered that the level of capital at the end of the year is significantly equal to that at the beginning of the year, so that the return may target the ratio moment in time, without calculating by reporting the results at the end of the year to the capital invested at the beginning of the year.

Figure 9. Graphic Representation on the Comparative Evolution of Net Profit and Equity

Based on the arguments presented above and by comparing the evolution according to Figure 9. it is observed that the financial performance of the entities in the field of constructions from the South-Muntenia Region of Romania, appreciated based on the profitability rates completed by the other indicators, registered a significant improvement starting with 2015 and kept it throughout the analysed period, before the analysed period , since the onset of the 2009 crisis, with only regression.

5. Econometric Model Regarding the Level of Influence on the Global Solvency Rate in the Field of Constructions in the South-Muntenia Region of Romania

A novelty element brought to this research study is represented by the elaboration of an econometric model, in order to identify the microeconomic variables that explain the change of the General Solvency Rate at the level of the studied entities, for the period 2009-2019. Thus, the verification of the existence of an interdependence between the General Solvency Rate and the independent variables Total Asset Rate of Return (ROA), Total Debt Rate (RTD), Profit Margin (MP) was started.

The resulting regression equation will be of the form: F(x) = Y, where X is given by the general solvency ratio and Y the independent variables. After determining the indicators, we proceeded to test the correlations between them. Before testing the correlation level, an analysis of the descriptive statistics generated in the early phase was also performed. The next step was to analyse the level of correlation. Considering the correlations established between the indicators, the values being presented in table 1, the modelling was performed according to the mentioned variables.

After performing the correlation analysis, we proceeded to the tests necessary to obtain the linear multiple regression model. The first test performed in this regard is given by the Summary model in which R and R2 are presented, the closer they are to level 1, the more significant the regression equation. The Summary model is presented in table 2.

It is observed in both R and R2 that they have values that tend towards level 1, which demonstrates the increased level of significance of the regression that is to be obtained.

Another important test is given by the ANOVA function. A significant importance in ANOVA is the F test, also known as Fisher’s test. The higher this F test, the higher the significance level of the regression equation. The elements resulting from the ANOVA test are presented in Table no. 3.

From the analysis of the data presented above, it can be said that ANOVA proves through the Summary model, the achievement of a significant level of the regression equation, F having the value of 280,020 with a value of Sig. insignificant (.000b). Due to the fact that a significant level of correlation was obtained and the tests performed indicated the significance of the regression equation, we proceeded to determine the coefficients of the regression equation. With the help of the Coefficients function, the mathematical form of the equation was determined based on Table 4.

These significant links between the indicators, led to the realization of the linear multiple regression model, a model that highlights the existing economic-mathematical link between them. Starting from the coefficients obtained in the table above, the regression equation whose dependent variable is the general probability rate is the following:

As the values of the coefficients are significantly different from zero and the probabilities associated with the independent variables are lower than the statistical significance level of 5%, the pre-established research hypothesis is accepted. Adjusted R-squared demonstrates a strong intensity of the relationship between the dependent variable and the independent variables. Thus, according to table 4.2., 70.6% of the variation of the General Solvency Rate (GSR) is determined by the variation of the independent variables, the rest of the variation being caused by the variation of the residual variable.

The analysed indicators and rates show similar evolutions during the analysed period. The relationship established reflects an entity’s ability to meet commitments through all the resources that make up its equity or assets.

The identification of the regression model was performed to characterize the link between the evolution of the general solvency ratio (as a dependent variable) and the evolution of the variables Total return on assets, Total debt ratio and Profit margin (as independent explanatory variables) over the period. These indicators are often used in diagnosing the activity of an economic entity. Assessing the size of an entity’s economic activity and changing it over time are absolutely necessary in attracting and securing the resources needed to meet the proposed objectives. For the analysis of an entity’s activity, any analysis of an indicator must include a dynamic description of it. In order to obtain relevant results, the study contains information for a period of five years.

The conclusions of the study validate the statement: The evolutions of the rates and economic-financial indicators determining in establishing the financial performance register in the analysed period a trend that allows the realization of comparisons and correlations.

The research study highlights the role of economic and financial indicators in establishing and measuring economic performance at the entity level. This is directly influenced by the accuracy of the information that has as source the economic-financial analysis. The exercise of a sustained control over the economic-financial analysis by the entities in the field of constructions offers the possibility to follow the activity carried out, being able to identify ways to increase the performances achieved by them. Analysing the way in which the accounting model fulfils the function regarding the support in the decision-making process at the level of the entities in the field of constructions in our country shows a not at all great interest of these entities in organizing the economic-financial analysis. In this sense, one of the noted limitations is related to the lack of preparation of cash flow records and the economic-financial analysis must be categorically performed in accordance with the strategic horizon of the entity.

Boloş, M. I.; Florea, E.; Trifan, V. (2004). Examinarea critică a informałiilor furnizate de sistemul de contabilitate cash/ Critical examination of the information provided by the cash accounting system. Annals of the University of Oradea, Faculty of Economic Sciences Volume XIII, p. 8. http://anale.steconomiceuoradea.ro/en/journal-archive/.

Cojocaru, C. (1997). Analiza economico-financiară a exploataţiilor agricole şi silvice/Critical examination of the information provided by the cash accounting system. Bucharest: Economic Publishing House.

Epuran, M. & Mihai, I. (1979). Analiza activităţii economice a întreprinderilor/ Analysis of the economic activity of enterprises. Timişoara.

Iosif, Gh. N. (2019). Analiza Cifrei de afaceri a unei întreprinderi/ Analysis of the turnover of an enterprise. Economic Tribune, no. 11. Bucharest.

Iosif, Gh. N. (2019). Analiza economico-financiară și managementul riscului financiar/ Economic-financial analysis and financial risk management. Economic Tribune, no. 35. Bucharest.

Ișfănescu, A.; Stănescu, C. & Băicuși A. (1999). Analiza economico-financiară – cu aplicații în societățile comerciale industrial, de construcții și de transporturi/ Economic and financial analysis - with applications in industrial, construction and transport companies, Second edition. Bucharest: Economic Publishing House.

Tabară, N. & Briciu, S. (2012). Actualități și perspective în contabilitate și control de gestiune/ News and perspectives in accounting and management control. Iasi: Moldova Tipo Publishing House.

Tudose, M. B. (2006). Gestiunea capitalurilor întreprinderii. Optimizarea structurii financiare/ Enterprise capital management. Optimizing the financial structure. Bucharest: Economic Publishing House.

Vintilă, G. (2005). Gestiunea financiara a întreprinderii/ Financial management of the enterprise. Bucharest: Didactic and Pedagogical Publishing House.

1 PhD, Valahia University Targoviste, Romania, Address: Aleea Sinaia 13 Str., Targoviste 130004, Romania, Corresponding author: magdalena@danescu.eu.

AUDOE, Vol. 17, No. 5/2021, pp. 123-141

Correlations
		Total Asset Rate of Return (ROA)	Total Debt Rate (RTD)	Profit margin (MP)
Total Asset Rate of Return (ROA)	Pearson Correlation	1	-.442^**	.464^**
	Sig. (2-tailed)		.000	.000
	N	353	353	353
Total Debt Rate (RTD)	Pearson Correlation	-.442^**	1	-.401^**
	Sig. (2-tailed)	.000		.000
	N	353	353	353
Profit Margin (MP)	Pearson Correlation	.464^**	-.401^**	1
	Sig. (2-tailed)	.000	.000
	N	353	353	355
**. Correlation is significant at the 0.01 level (2-tailed).

Model Summary
Model	R	R Square	Adjusted R Square	Sig. F Change
1	.841a	.706	.704	.000
a. Predictors: (Constant), Profit margin, Total debt rate, Total asset rate of return

ANOVA^a
Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	95291608.751	3	31763869.584	280.020	.000^b
	Residual	39588522.538	349	113434.162
	Total	134880131.288	352
a. Dependent Variable: General solvency rate
b. Predictors: (Constant), Profit Margin, Total Debt Rate, Total Asset Rate of Return (ROA)

Coefficients
Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.	95,0% Confidence Interval for B
Model		B	Std. Error	Beta	t	Sig.	Lower Bound	Upper Bound
1	(Constant)	884.459	47.714		12.249	.000	490.615	678.303
	Total Asset Rate of Return ROA	-16.043	1.370	-.404	-11.710	.000	-18.737	-13.349
	RDT	-6.547	.680	-.321	-9.628	.000	-7.885	-5.210
	Profit Margin (MP)	32.527	1.364	.805	23.846	.000	29.844	35.209
a. Dependent Variable: General solvency ratio