Analysis of the Relationship between Long-Term Decisions and Value Creation

Jamel L, Derbali A and Harbi ER

Published on: 2019-10-08

Abstract

Maximizing value is a major priority that conditions the behavior of market players and guides the decisions and choices of leaders and funders. The objective of our research is to produce an explanatory model of the variation of the value of the company in relation to the long-term financial decisions and according to the performance indicators. For this purpose, the results were very conclusive for the Economic Value Added (EVA) indicator which proved its relevance, by dominating the other variables, in explaining the change in value in the long term.

Keywords

Long-term financial decisions; Value creation; Free cash-flows; Gross operating surplus; Return on equity

Introduction

From the very beginning of the first economic and financial theories, the concept of value has been central to the reflections held on the company, its evolution and its economic and social purpose. Value is considered a target to be achieved, measured and maximized. It represents, among other things, the wealth of the shareholder and has become the center of gravitational attraction around which all modern financial theories revolve, even if they are sometimes placed in different orbits [1]. However, while the majority of authors agree on the legitimacy of value creation and its maximization as the ultimate goal for business, the debate about how to achieve this goal is still alive. In this context, the analysis of long-term decisions that are strategic in nature and related to the company's jobs and resources is of great interest because of their impact on the value of the business. To this end, we conducted research to identify potential relationships between long-term decisions (investment and financing) and the change in the value of the company. Our research focused on the financial statements (balance sheets, income statements and financing tables) of 27 companies listed on the Casablanca financial market.

Theoretical Analysis Framework

Strategy and finance that have, for a long time, evolved independently, have come together around the concept of value. It creates a strong link between the two disciplines; some authors speak of strategic value or even financial strategy [2-3]. Indeed, strategic decisions reflect long-term choices; contribute to the development of appropriate policies to achieve the objectives set and condition the process of resource allocation for the purpose of creating and maximizing value. In this context, we can see that value is not only a research object but rather a target and an end in itself; recent conceptual developments focus on how to achieve this value and maximize it in the eyes of funders. The latter form the capital market, in particular the stock markets where the values ??of companies are indexed in relation to a confrontation between supply and demand which judge the performances of these companies, the behavior of their managers and the strategic axes of the companies of their development.

Thus, the creation of value becomes the ultimate objective sought by the shareholders who delegate this mission to the executives in the context of an agency relationship. The relationship between the shareholder and the manager is conditioned by the nature of that relationship. The latter may experience ups and downs according to the coherence or divergence with respect to the objective sought and with respect to the maximization of the utility function of each of the protagonists. In this context, we can also point out the studies that concerned the explanation of the value of the company by variables of a strategic nature, notably the study carried out by Rappaport 1987 and that of Caby et al. 1996 which focused on eleven accounting indicators explaining the value and which were grouped into five categories: economic performance, activity, financing policy, investment policy, dividend distribution policy. Also, it must be emphasized that these studies revealed more or less significant links between the variables studied and the value of the company. However, we noted a deficiency in explanatory models of value, particularly in terms of the joint influence of these variables on the value of the firm and the long-term effect. Our study fits into this framework of analysis. We question the levers of value creation that can explain the variation of the value of the company in the long term. To this end, several indicators raise some questions: is the long-term change in the value of the company significantly related to investment decisions? Does it take advantage of the leverage associated with the debt structure? Can the annual performance highlighted in the income statements better explain the change in value in the long term? Although some studies have not revealed clear evidence between the fundamental indicators contained in the accounting and financial information, we believe that in a long-term horizon these indicators are able to restore a significant part of the information contained in the long-term change in the company's share price, particularly with the introduction of an indicator that has raised many questions: the EVA. In fact, the purpose of our study is to highlight the form of potential links between, on the one hand:- Long-term financial decisions (investment and financing) that reflect strategic choices and are reflected in balance sheet changes; The annual performance of companies in terms of growth (EVA, free cash flows, gross operating surplus, and return on equity) which is reflected in the profit and loss accounts; And on the other hand: The change in the value of the enterprise expressed by the market value, i.e. the price multiplied by the total number of shares and by the adjusted market value in relation to dividend distributions and various payments made to shareholders. Based on the premise that management decisions are aimed at maximizing the value of the business, an investment or financing decision should result in an increase in the value of the business. Similarly, we question the contribution of the capital structure in the value of the company, notably through the lever of the debt due to the tax savings; the efficiency gain and a better efficiency for seize growth opportunities [4-9]. The investment and financing decisions that can be identified from the balance sheets, the financing and flow tables, in addition to the annual performance recorded by the company, should reflect the competitiveness of the company as well as its economic profitability because it is not enough to invest and finance this investment but it is still necessary that the company is able to make it profitable. In this sense, financial accounting indicators should in principle contribute to adjusting and improving the shareholder's image of the portfolio in which he invests. Consequently, the information published in the profit and loss accounts undeniably participates in the process related to the decision to buy or sell the security and in the formation of the investment portfolio.

Definition of Measurement Variables and Underlying Assumptions

The explanatory variables

In order to identify the potential links between the value of the company (variable explained) and the set of performance and value creation levers, we have chosen the following variables as explanatory variables:

Changes in property, plant and equipment

Tangible fixed assets reflect both production capacity for industrial enterprises and distribution and marketing capacities for commercial enterprises [10]. As a result, the annual change in property, plant and equipment reflects the net investments made by the company in a given year, particularly in terms of land, buildings, machinery and equipment ... These are decisions that fit into the logic of organic growth aimed at strengthening the company's production and distribution potential. Thus, the change in fixed assets should contribute to the increase of the value of the company in the long term.

Hypothesis 1: The net increase in fixed assets contributes to the increase in the value of the business

The structure of indebtedness: Structural debt reflects all external financial flows that finance both long-term growth decisions and short-term operational decisions. Thus, all of the company's debts have been included in the debt ratio (Total debts / Total resources), the average of which over a long-term horizon will be taken into account in measuring the impact of the debt on the change in the value of the business. In addition, according to the "Pecking order" model (Myers and Majluf, 1984), companies meet their financing needs by firstly using cash flows generated internally, then using external financing. As a result, companies with a high level of cash flow would be less dependent on new capital and less sensitive to the pressures of earnings and income forecasts. As a result, a high debt ratio could have a negative impact on the market value of the company as a result of potential market pressures on the valuation of the company [11-16]. This is in fact contrary to the proposal corrected by Modigliani and Miller who argue that enterprise value increases with indebtedness.

Hypothesis 2: Debt contributes to the weakening of the value of the company

The capital structure: Equity financing involves either internal fundraising through an appeal or a cash increase in capital, or retention of profits by way of reserve and carry-forward. Self-financing is a long-term decision aimed at supporting the company's growth options and strengthening its production potential [17]. Similarly, high self-financing should strengthen the firm's independence from external capital and ease the pressure of capital providers on prices. The self-financing variable is estimated by the average of the ratios of the financial autonomy over the number of years of the study, this ratio is equal to the ratio Capital / Total resources. Symmetrically with the debt analysis, a strong financial autonomy would contribute in the long term to the firming of the value of the company insofar as the company would be better placed to seize the growth opportunities and to negotiate a potential debt [18-23].

Hypothesis 3: Financial autonomy contributes to firming the value of the company

Return on equity: This ratio is expressed by the ratio (Net Result / Equity), the ratio of return on equity remains one of the most used indicators in the financial sphere and this, after its adjustment by the exceptional items. Indeed, this ratio reflects the return on capital employed in financing the investment and operating cycle of the company. In addition, the company creates value when the return on equity is greater than the cost of capital required by shareholders. Thus, a high average ratio should reflect a positive trend in value creation by the company [24].

Hypothesis 4: Return on equity contributes to improving the value of the business

Economic profitability: Economic profitability is measured by the ratio (Gross operating surplus / Turnover); this ratio, which is very traditional, measures the profitability linked to the company's operating cycle, whatever the nature of the activity carried out (commercial or industrial) [25]. Indeed, the very nature of the report implies to the numerator the EBITDA that is generated by the difference between, only the income and expenses related to the operation. Other income and expenses, expenses and gains and financial as well as exceptional items are excluded. Likewise, EBITDA's share of sales should reflect operational efficiency that could have a positive impact on the company's competitiveness and competitive behavior. To this end, we believe that the economic profitability as expressed by the ratio above should have a positive long-term impact on the value of the company [26-32].

Hypothesis 5: Economic profitability contributes to improving the value of the business

Free cash flows: One of the most widely used methods by investors in financial valuation through flows and by financial analysts is the available cash flow method or the free cash flows, these flows are calculated from the following formula : FCF = EBE - ?WCR - investments + asset disposals - taxes. We can see that the evaluation by the method of flows has experienced a significant growth in recent years; this reflects the importance given by market professionals to the concept of "cash". Indeed, it is not enough that the company presents a beneficiary image to have the blessing of the shareholders. The latter are rather seduced by the cash flows that represent the result of the company. In our analysis, the FCFs play an important role in the definition of the value of the company, we think that the more the companies generate cash, the better they would be noted by the financial analysts and the better would they be valued by the potential purchasers [33].

Hypothesis 6: Free cash flows contribute to the long-term improvement of the value of the company

Economic value created per year EVA / Economic value added: The traditional profitability ratios discussed above in previous assumptions have been strongly criticized in recent developments in the financial literature, particularly with respect to encouraging decision-making to inflate these indicators in the short term to the detriment of value of the business in the long run. Following these criticisms, several authors have turned to the exploration of new indicators, especially those related to residual income or "residual income" denoting the difference between net income and economic assets [34]. These analyzes are based on the apprehension of the economic asset in relation to the cost of capital that it generates. In this context, the EVA indicator was developed by Stern and Stewart, the EVA can be expressed by the following formula:

EVA = Operating profit after taxes - CMP * Capital

According to Stern et al. (1995), EVA is a global indicator that integrates all facets of financial management. This integration refers to a single measure that can provide the best information about the value created over a period of time. As a result, the EVA indicator should, in principle, better reflect the value created by the firm over a given period. Similarly, this indicator would be significantly associated with the long-term change in the market value of the company.

Hypothesis 7: The economic value created contributes to the long-term improvement of the value of the enterprise

The explained variable: The value of the business is the variable we want to explain in this study. Indeed, if we can agree on maximizing the value of the company as the ultimate goal of the managers and various employees within the company (at least within the shareholding stream), several difficulties are still haunting the definition of this value, the multiplicity of evaluation methods (heritage, flow and economic methods) bear witness to this conceptual difficulty. However, the market value, that is, the value of the security for listed companies, is the value to which the set of indicators converge. As a result, we preferred to adopt the approach based on the valuation granted by the market, i.e. the share price of the company for the listed companies, which are the subject of our study [35-41]. For Jensen (2001), the success of the company is measured by the change of the entire market value of the company in the long run. For this purpose, the dependent variable that we will seek to explain is the change in the total value (price * quantity) over a five-year time horizon. In the same vein, an adjustment is proposed by Pablo Fernandez in the definition he proposes for the measurement of shareholder value added, which is the difference between the wealth held by the shareholders at the end of a given year and the wealth held. At the end of the previous year. This definition should not be confused with the market value of the stock. Indeed, Pablo Fernandez proposes the following adjustment:

Added share value = Increased market value + Dividends paid during the year Payments received on capital increase + other payments to shareholders (amortization of capital ...) Conversion of convertible bonds

To make an additional adjustment, the second variable that we will try to explain is the shareholder value added as defined above. Subsequently, two variables will be used to represent the change in the value of the business: the change in market value as defined by Jensen (2001) and the shareholder value added as defined by Fernandez (2001).

Methodology of Analysis and Measurement of Variables

The time horizon of the change in value and the choice of price

To measure the long-term impact of investment decisions, debt structure and equity, a five-year horizon has been taken into consideration which is justified by the nature of the sample we are going to study and which mainly consists of industrial enterprises. Similarly, we have used the weighted average price by transaction volumes in both the block and central markets. This average was calculated between the beginning of March and the end of April in the estimate of the market value of the companies studied. We chose this time range for the following reasons:

  1. A legal obligation set by the CDVM concerning the publication of half-yearly accounts within three months of the closing date of each semester;
  2. The "leakage of information" effect, which means that a lot of financial information is already starting to circulate in the Casablanca square by the first week of March;
  3. The time standard of publication of information and which has been confirmed by several analysts of the place, this standard is in the last three weeks of March. For this purpose, the month of March is characterized by the reflex of the small carriers who react in a spontaneous manner according to the confirmation or the reversal brought by the published information as for their growth expectations.
  4. The month of April has also been incorporated into the analysis as institutional investors prefer to react only after reading it by the financial analysts of the place. As a result, during the month of April, courses are affected by the reaction of institutional investors to the publication and reading of accounting and financial information.
  5. Exceptionally, for the IB Morocco and Unimer values, the months of June and July were included in the analysis. This period is justified by the fact that the two companies have a financial year that runs from 01/04/N to 31/03/N+1. As a result, we used the same lag of two months for these two values, that is, the months of June and July. However, for the impact of the period 2006/2007 we selected the months of April and May 2007 because the financial statements have not yet been published and as a result, we have selected the closest dates.

Description of the sample

The study sample is made up of 27 listed companies, 21 of which belong to the industrial sector, 5 to the commercial sector and one to the transport sector, i.e. more than 450 balance sheets and profit and loss accounts entered and processed. The 21 companies in the industrial sector can be divided as follows: for the 5 enterprises belonging to the commercial sector, 3 are specialized in the distribution of transport equipment, one company distributes fertilizers and the last is specialized in the distribution of hardware. Banks, finance companies, insurance companies and investment companies have been excluded from the analysis because their financial structures are fundamentally different from those of the companies studied and their activities are not evaluated according to the same performance indicators. The comments concerned the period from 1999 to 2018, and covered the accounting documents (balance sheets, profit and loss accounts, financing tables) for the same period.

Proposed Models

We have chosen two year ranges to measure the impact of the different variables on the long-term change in the value of the enterprise: 2000-2017 and 2001-2018. Thus, to constitute a table grouping all the variations we have adopted the following approach:

- The change in the enterprise value between 2000 and 2017 is measured against the net increase in investment in 2000;

- The change in the value of the enterprise between 2001 and 2018 is measured against the net increase in investments in 2001;

- The change in the value of the company between 2000 and 2017 is measured in relation to the average debt ratio, the average capital ratio, the average return on equity, the average of the ratio of economic profitability between 2000 and 2017;

- The change in the value of the enterprise between 2001 and 2017 is measured against the average of the debt ratio, the average of the capital ratio, the average return on equity, the average of the ratio of economic profitability between 2001 and 2018;

- The change in the value of the company between 2000 and 2017 is measured in relation to the sum of free cash flows from 2000 to 2017;

- The change in the value of the company between 2001 and 2018 is measured in relation to the sum of free cash flows from 2001 to 2018;

- The change in the value of the firm between 2000 and 2017 is measured in relation to the sum of the EVA (without adjustments) from 2000 to 2017;

- The change in the value of the enterprise between 2001 and 2018 is measured in relation to the sum of the EVA (without adjustments) from 2001 to 2018.

Either:

?Ve1: The long-term change in the market value of the company.

?Ve2: The long-term change in the market value of the company adjusted by the sum of the dividends distributed;

?i: Net increase in fixed assets;

Re: The average ratio of indebtedness;

Rp: The average capital ratio;

Mr: The average profitability of equity;

Me: The average economic profitability;

?CF: The sum of the free cash flows of the period;

? EVA: The sum of the EVAs of the period.

a0: Constant

The two proposed models are as follows:

?Ve1 = a0 + ?1?i + ?2Re + ?3Rp + ?4Mr + ?5Me + ?6?CF + ?7?EVA

?Ve2 = a1 + ?8?i + ?9Re + ?10Rp + ?11Mr + ?12Me + ?13?CF + ?14?EVA

Analysis of the Results

Case of long-term change in market value without adjustment by dividends

Table 1 shows the result of the partial correlation between the different variables: the calculated correlation coefficients are those of Pearson. The results displayed show a symmetrical correlation between the debt structure and financial autonomy (-1), which is normal because the two ratios are symmetrically opposed in the balance sheet. However, one of the two variables will be excluded from the analysis to remedy the phenomenon of multicollinearity. In this context, we also note a strong correlation between the average EBITDA / CA and the average return on equity (0.70 at the 0.01 level), as well as a strong correlation between the sum of the EVAs and the sum of cash flows (0.76 at the level of 0.01) and a very strong correlation between the variation of acquisitions and the corresponding EVAs (0.73 at the level of 0.01). The strength of these links can be explained by the fact that companies that have a high economic return also have a high return on equity.

Table 1: Correlation matrix between explanatory variables.

 

Acquisitions

EBE / Average CA

Average  ROE

Average autonomy

Average indebtedness

Sum FCF

Sum EVA

Acquisitions

1

 

 

 

 

 

 

EBE / Average CA

0,313(*)

1

 

 

 

 

 

Average  ROE

0,287(*)

0,701(**)

1

 

 

 

 

Average autonomy

0,300(*)

0,515(**)

0,529(**)

1

 

 

 

Average indebtedness

-0,300(*)

-0,515(**)

-0,529(**)

-1,000(**)

1

 

 

Sum FCF

0,443(**)

0,474(**)

0,409(**)

0,367(**)

-0,367(**)

1

 

Sum EVA

0,730(**)

0,554(**)

0,455(**)

0,363(**)

-0,363(**)

0,763(**)

1

* signification au niveau 0.05

** signification au niveau 0.01

As a result, we can say that the economic return, which is the first ratio generated, has a positive effect on the return on equity. Similarly, the strong link between EVA and FCF can be explained by the ability of both indicators to provide similar information, particularly in terms of wealth creation. Lastly, the impact of investments seems stronger (strong correlation, r = 0.73) on the economic value created (EVA) than on free cash flows (moderate correlation, r = 0.443). These strong links would result in the presence of multicollinearity phenomenon that could affect the stability of the model. We will therefore remedy this situation by eliminating one of the variables in case two variables are highly correlated. The characteristics of the model are listed in Table 2.

Table 2: Summary of the model.

Model

R

R² adjusted

Durbin-Watson

Fisher

Signification

1

0,929 (a)

0,863

0,844

1,917

46,038

0,000(a)

a Predicted values: (constant), Sum EVA, Average debt, Average ROE, Acquisitions, Average EBE / CA, Sum FCF

b Dependent variable: Total value of the company

The Fisher test is very significant at 0% (F = 46,038), which shows the overall consistency of the model. The adjusted coefficient of determination is very strong R2 = 0.844. Similarly, the Durbin-Watson test is significant (1,917). We therefore have a model of very high quality. Table 3 presents the different coefficients of the model with their respective significance levels according to the Student's test. Regarding the 1st assumption regarding the contribution of acquisitions to the change in the long-term value of the company, it cannot be used according to the model, given the level of significance (0.457). However, this result does not mean the absence of the effect of the investments on the value of the company because the latter are strongly correlated with the EVA (Table 1) whose beta and the level of significance are too high. We can therefore say that investments have an indirect effect on the change in the value of the company. For the second hypothesis relating to the structure of the debt, we can see that the contribution of the debt to the market value of the company seems to oppose this hypothesis, based among others on the model of "Pecking Order" of Myers. But this result seems consistent with the analysis already made by Modigliani and Miller about the contribution of debt to firming the value of the company.

Table 3: Estimation and significance levels of model coefficients.

 

Unstandardized coefficients

Standardized coefficients

t

Signification

B

Erreur standard

Bêta

Constant

-1255811594,08

604574121,639

 

-2,077

0,044

Acquisitions

4,018

5,356

0,065

0,750

0,457

EBE / Average CA

3491896378,458

2356024639,876

0,129

1,482

0,145

Average  ROE

-716364616,632

2327996567,054

-0,025

-0,308

0,760

Average indebtedness

3896188469,919

1546143727,772

0,175

2,520

0,015

Sum FCF

0,568

0,424

0,122

1,340

0,187

Sum EVA

4,264

0,690

0,777

6,177

0,000

Indeed, indebtedness has a positive coefficient in the model (0.175) at the level of significance of 1%. However, this result should be taken with caution because the companies we studied are highly deleveraged with an overall average debt ratio of 11%, this rate remains very low and does not allow us to define the perception of the debt of companies and to confirm or refute the behavior of their managers in the presence of a high level of indebtedness. With regard to hypothesis 3 on financial autonomy, it cannot be verified in the model. In fact, the financial autonomy variable was excluded from the model because of its complete correlation with the debt ratio (correlation coefficient = -1). However, we can deduce that this ratio would be detrimental to the long-term change in the value of the business in the event that we substitute it for that of the indebtedness. For the fourth hypothesis relating to the return on equity ratio, it cannot be used according to the model, given the level of significance (0.76). For the 5th hypothesis, the contribution of economic profitability (EBE / CA) in the explanation of the value can be considered as significant at the level of 14.5%. Regarding the 6th hypothesis relating to the contribution of cash flows to the increase in the value of the company, it cannot be used according to the model given the level of significance (0.187). However, this does not mean that the FCFs do not have an impact on the value because their sum is strongly correlated with that of the EVA (coef correlation = 0.763, table n ° 1). Finally, the 7th hypothesis is verified with a beta = 0.777 at the 0% significance level. We can note a clear dominance of the EVA indicator, which confirms its prevalence in the explanation of value in the long term and we can thus say that this indicator can be considered as the main variable which explains the long-term variation value of the business. To this end, we proceeded to the removal of variables whose contribution in the model is not significant. Then we ran the program with the remaining variables to output the following model (Table 4). In the latter model, the change in value is strongly related to the sum of the EVA for the same period which confirms the superiority of this indicator to reflect the evolution of the value in the long term. This predominance is further confirmed that the adjusted R2 is improved (0.847) and Fisher's level of significance is zero. In addition, Student's tests are significant at the 0% threshold for EVA, and 1.6% for indebtedness and 14.4% for average economic profitability. In our opinion, this model could be considered homogeneous, especially for VAS and economic profitability. However, the beta of the debt is to be taken with reserve in particular in relation to the structure of the overall indebtedness of our sample which remains very weak (11%) [42].

Table 4: Estimation and significance levels of model coefficients.

 

Unstandardized coefficients

Standardized coefficients

t

Signification

B

Erreur standard

Bêta

Constant

-1037123734,42

528401354,028

-1,963

0,056

1037123734,425

EBE / Average CA

2910575366,118

1959816323,464

0,108

1,485

0,144

Average indebtedness

3618914403,500

1446752564,081

0,162

2,501

0,016

Sum EVA

5,013

0,367

0,914

13,667

0,000

 

Long-term change in market value with dividend adjustment

In this case, the variable that we will try to explain is the change in the market value adjusted by the dividends distributed during the same period. Indeed, the change in total value should be increased by the dividends distributed during the period because it is a simple transfer of wealth to shareholders. The same results and interpretations concerning Table 1 remain valid to address the tests of the change in value with the integration of dividends. Thus, the problems of multicollinearity will also be present in this analysis, particularly in relation to the strong link between the EVA and the FCF, the symmetrical link between the ROE and the economic profitability and the link between the EVA and the level of investment. The different coefficients of the model are presented in (Table 5) with their respective levels of meanings according to the Student's test. We can still note the strong dominance of the EVA indicator with standardized coefficients (betas) which remain practically stable except for the indebtedness where we note a slight decrease both in terms of beta and in the level of significance.

Table 5: Estimation and significance levels of model coefficients.

 

Unstandardized coefficients

Standardized coefficients

t

Signification

B

Erreur standard

Bêta

Constant

-1001332272,32

613905795,322

 

-1,631

0,110

Acquisitions

5,888

5,439

0,087

1,082

0,285

EBE / Average CA

3230794854,676

2392390161,225

0,109

1,350

0

Average  ROE

-755867760,792

2363929471,755

-0,024

-0,320

0,751

Average indebtedness

3558728975,116

1570008640,637

0,145

2,267

0,028

Sum FCF

0,708

0,430

0,138

1,647

0,107

Sum EVA

4,596

0,701

0,763

6,556

0,000

Table 6: Table 6: Summary of the model.

Model

R

R² adjusted

Durbin-Watson

Fisher

Signification

2

0,939(a)

0,883

0,867

1,847

55,132

0,000(a)

a Predicted values: (constant), Sum EVA, Average debt, Average ROE, Acquisitions, Average EBE / CA, Sum FCF

b Dependent variable: Value 2 dividends included

Similarly, the contribution of the profitability ratio becomes meaningless with a level of significance approaching 20%, giving way to the sum of the FCFs which remain strongly correlated with the EVA. As a result, we can say that the model has not changed globally with the integration of the parameter related to dividend distribution. The weight of the EVA in explaining the change in the value of the company remains strong especially compared to the change in shareholder wealth which takes into account the dividends distributed during the period. The contribution of the dividend parameter appears in the quality of the model (Table 6). The Fisher test is very significant at the 0% level with F = 55.132, which shows the consistency and homogeneity of the model. The quality of the model improved significantly with an adjusted R2 of 0.867 instead of 0.844. To this end, we believe that the adjustment of value by dividends can bring a further improvement to the quality of the explanatory model [43-45].

Conclusions

The main contribution of this study would be, in our opinion, the confirmation of the strong link between the change in the value of the company in the long term on the one hand, and the indicator of the EVA on the other hand. This result could have several consequences, particularly with regard to the adoption of this ratio in the general evaluation of companies listed by financial analysts and in the indexation of executive compensation in relation to this indicator. We can also note that increased investment has a positive effect on the creation of economic value, the link between strategic decisions and finance could be inferred from this relationship. In addition, this contribution is made in the context of a low-debt financial structure where the debt plays oddly in favor of the value of the company. On the other hand, we can also confirm the low significance that the ratio of economic profitability might have to the potential for creating the company's wealth. As a result, the obsolescence of this ratio could already be announced. However, our study suffered from several empirical limitations, particularly in relation to the limited number of observations we had and the weakness of long-term debt and equity-related events which has had the effect of limiting our field of investigation to only empirically observable data (internal growth, capital structure, annual performance, etc.). Finally, we can say that the long-term change in the value of the company is directly linked to the indicators linked to the long-term performance of the creation of value (EVA, FCF) and indirectly linked to long-term decisions, in particular in investment.

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