extfieldsofstudy: Economics Business

s2fieldsofstudy: Economics Business

text:
Effect of Long-Term Debt on the Financial Growth of Non-Financial Firms Listed at the Nairobi Securities Exchange

A significant number of the non-financial firms listed at Nairobi Securities Exchange (NSE) have been experiencing declining financial performance which deter investors from investing in such firms. The lenders are also not willing to lend to such firms. As such, the firms struggle to raise funds for their operations. Prudent financing decisions can lead to financial growth of the firm. The purpose of this study is to assess the effect of Long-term debt on the financial growth of Non-financial firms listed at Nairobi Securities Exchange. Financial firms were excluded because of their specific sector characteristics and stringent regulatory framework. The study is guided by Trade-Off Theory and Theory of Growth of the Firm. Explanatory research design was adopted. The population of the study comprised of 45 non-financial firms listed at the NSE for a period of ten years from 2008 to 2017. The study conducted both descriptive statistics analysis and panel data analysis. The result indicates that Long term debt explains 21.6% and 5.16% of variation in financial growth as measured by growth in earnings per share and growth in market capitalization respectively. Long term debt positively and significantly influences financial growth measured using both growth in earnings per share and growth in market capitalization. The study recommends that, the management of non-financial firms listed at Nairobi Securities Exchange to employ financing means that can improve the earnings per share, market capitalization and enhance the value of the firm for the benefit of its stakeholders.

I. Introduction
Long term debt is part of the financial structure. Financial structure is the way a firm finances its assets through some combination of debt and equity that a firm deems as appropriate to enhance its operations (Kumah, 2013). The determination of a firm's optimal financial structure is vital in deciding how much money should be borrowed and the best mixture of debt and equity to fund business operations (Shubita&Alsawalhah, 2012). Therefore, the choice among the ideal proportion of debt and equity can affect the value of the firm, as well as financial performance.
Long term debt involves strict contractual covenants between the firm and issuers of debt, which is usually associated with high agency and financial distress costs (Tailab, 2014). Equally, Shubita and Alsawalhah (2012) observed that high long-term debt levels in the firm are not conducive for the effective operations of the firm since they increase the risk of bankruptcy. The high debt levels increase the interest rate, which may incapacitate the liquidity levels of the firm (Vermoesen, Deloof&Laveren, 2013). Long term debt is measured as long-term liabilities divided by total assets.
Long term debt is money that is owed to lenders for more than one year from the date of the current balance sheet. Long term debts are the most preferred sources of debt financing among well-established corporate institutions mostly by their asset base, and collateral is a requirement that many of deposits-taking financial institutions (Foyeke, Olusola&Aderemi, 2016). Pelham (2000) argued that long term debts providesmall firms with more competitive advantages when compared with large firms. According to the results, it was found out that there is a direct positive and significant relationship between long term loans and financial performance of small businesses. Pelham (2000) reported that long term debt was positively related to the growth/share/sales effectiveness and gross profit in small and medium-size manufacturing firms. However, Maniagi, Mwalati, Ondiek, Musiega, and Ruto (2013) noted that long term debt has a weak positive insignificant relationship with ROE. Further, EBaid (2009) revealed that there was no significant relationship between long term debt and financial performance measured using the return on assets.
Financial growth is a measure of efficient utilization of assets by a firm from principal business mode to generate revenues (Aburub, 2012).Financial growth is a general measure of the overall financial health of a firm over a given period(Onaolapo&Kajola, 2010). According to Buvanendraet al. (2017), the financial growth of a company is measured as the growth of market capitalization.Market capitalization refers to the total dollar market value of a company's outstanding shares (San &Heng, 2011). Market capitalizationis calculated by multiplying a company's shares outstanding by the current market price of one share (Buvanendra, Sridharan&Thiyagarajan, 2017). The return on investment, return on assets, market value, and accounting profitability reflect financial growth of firms (Ongore&Kusa, 2013).

1.1Statement of the Problem
A significant number of the non-financial firms listed at Nairobi Securities Exchange (NSE) have been experiencing declining financial performance which deter investors from investing in such firms (Muchiri, Muturi&Ngumi, 2016). The growth of non-financial firms listed at Nairobi Securities Exchange was 3.7% in 2017 against 4.2% in 2016 (NSE, 2017). Decline in financial performance deter lenders from lending to such firms (Muchiri, Muturi&Ngumi, 2016 Muchiriet al. (2016)examined the effects of financial structure on financial performance of listed Investment firms in Kenya, and the findings revealed that long term debt had a significant positive relationship with Return on Assets (ROA) and Return on Equity (ROE). The study did not explicitly indicate to what extent, thelong-term debt influencesfinancial performance of listed Investment firms. Further, the study focused only on Investment firms listed at the Nairobi Securities Exchange. The study intends to fill this conceptual gap by focusing on the effect of long-term debt on financial growth of non-financial firms listed at Nairobi Securities Exchange.

Research Objectives
To assess the effect of Long-term debt on the financial growth of Non-financial firms listed at Nairobi Securities Exchange.

1.3StatisticalHypothesis
There is no significant effect of Long-term debt on the financial growth of Non-financial firms listed at Nairobi Securities Exchange.

Theoretical Review
The study is guided by Trade-Off Theory and Theory of Growth of the Firm.

2.1.1Trade-Off Theory
Trade-Off Theory postulated by Myers (1984) emphasizes a balance between tax-saving arising from debt, decrease in agent cost and financial distress (Shahar, Shahar, Bahari, Ahmad, Fisal&Rafdi, 2015). Myers (1984) finds that the benefit of the tax shield is offset by the costs of financial distress, and agency cost. In other hard, the optimal level of leverage is achieved by balancing the benefits from interest payments and costs of issuing debt (Jahanzeb, Bajuri, Karami&Ahmadimousaabad, 2014).The balance between tax-saving arising from debt, decrease in agent cost, and financial distress has a significant effect on the financial growth.
Sheikh and Wang (2010) argue that the trade-off theory is expected to choose a target financial structure that maximizes financial growth by minimizing the costs of prevailing market imperfections. The trade-off theory is also referred to as tax-based theories and bankruptcy costs. It assumed each source of money has its own cost and return. These are associated with the firm's earning capacity and its business as well as insolvency risks (Awan & Amin, 2014). Therefore, a firm with more tax advantage will issue more debt to finance business operations, and the cost of financial distress as well as, benefit from tax-shield are balanced (Chen, 2014).
The purpose of the theory is to explain the fact that firms are mainly financed partly with debt, and partly with equity. It stipulates that there is an advantage to financing with debt, the tax benefits of debt and there is a cost of financing with debt, the costs of financial distress including bankruptcy costs of debt and nonbankruptcy costs. The marginal benefit of further increases in debt declines as debt increases, while the marginal Effect of Long-Term Debt on the Financial Growth of Non-Financial Firms Listed at the NSE DOI: 10.9790/5933-1105020109 www.iosrjournals.org 3 | Page cost increases so that a firm that is optimizing its overall value will concentrate on the trade-off when choosing how much equity and debt to use for financing.

Theory of Growth of the Firm
The theory was propagated by Penrose (1959). Penrose argued that firms had no determinant to long run or optimum size, but only a constraint on current period growth rates (Penrose, 1959).According to the theory, financial means for expansion could be found through retained earnings, borrowing, and new issues of stock shares. Retained earnings are one ofthe most important sources to finance new projects in emerging economieswhere capital markets are not well developed. However, firms in the start-up period, when initial investments have not matured yet or whose investment projects are substantially larger than their current earnings, will not have enough financial means from retained earnings and will face a constraint in their growthproject. Firms in this situation may seek external sources of financing; however, the extent of borrowing could be limited by internal factors like high debt-equity ratios that would expose both borrower and lender to increased risk. In other cases, financing of growth projects may be limited by shallow financial markets. Rajan and Zingales (1998) found that industrialsectors with a great need for external finance grow substantially less in countries without well-developed financial markets.
This theory is relevant to this study since it informs the dependent variable which is financial growth. The current studies which have used this theory of firm's growth are; Diaz Hermelo (2007) who conducted a study on the determinants of firm's growth: an empirical examination and Pervan and Višić (2012) who conducted a study on the Influence of firm size on its business success. Figure 1 shows the conceptual framework. Independent Variable Dependent Variable

Figure 1: Conceptual Framework of Long-TermDebt and Financial Growth
Long-term debt is the independent variable. The dependent variable is the financial growth measured using growth in earnings per share and growth in market capitalization.

III. Research Methodology
The study adopted positivism research philosophy. Explanatory research design was also adopted. The study conducted both descriptive statistics analysis and panel data analysis. Panel analysis permits the researcher to study the dynamics of change with short time series. The combination of time series with cross-section can enhance the quality and quantity of data in ways that would be impossible using only one of these two dimensions (Gujarati, 2009 Table 1 shows the descriptive statistics forlongtermdebt, earnings per share, and market capitalization. The descriptive results show that the mean value for long-term debt had a mean of 0.200195with a minimum of 0.000000and a maximum of 1.126967. The standard deviation for long term debt was 0.186595. The mean value for earnings per share was 6.468265with a minimum of -46.744, a maximum of 100.0483, and a standard deviation of 15.03232. The mean value for market capitalization as another measure of financial growth wasKshs.24600 million with a minimum of Kshs.116 million and a maximum of Kshs.721,000 million.

4.2Trend Analysis
This section presents the analysis of the trends of the variables. The study conducted a trend analysis to establish the movement of the variables overa period of time.Trend analysis for long term debt,earnings per share, and market capitalization are presented in figure 2.

Figure 2: Long TermDebtTrend Line
Financing using long term debt dropped from 2008 to the lowest in 2010. However, long term debt rose again from 2011 to the highest in 2013. Long term debt is money that is owed to lenders for more than one year from the date of the current balance sheet. The study by Ebaid (2009) found that there was no significant relationship between long term debt and return on assets. Long term debts are the most preferred sources of debt financing among well-established corporate institutions mostly by their asset base, and collateral is a requirement for many of deposits-taking financial institutions. According to Githire and Muturi (2015), long term debt has a positive and significant effect on the financial performance.  The trend line shows that earnings per share rose steadily from 2008 to reach the highest in 2010. However, earnings per share dropped further from 2011 to 2012 before rising again in 2013. Earnings per share further dropped drastically to reach lowest in 2017. Earnings per share is considered avital accounting indicator of risk, entity performance, and corporate success. It is used to forecast potential growth in future share price, because changes in EPS are often reflected in share price behavior. Smart and Graham (2012) concur by suggesting that an entity's growth rate is determined by performance indicators such as earnings per share, which is disclosed in the financial statements of companies according to the specifications of the specific accounting standards applied in the respective country. Furthermore, authors have argued that EPS has become a useful investment decision tool for investors because it indicates prospects and growth (Mlonzi, Kruger &Ntoesane, 2011). According to Robbetze, de Villiers, and Harmse (2017), earnings per share correlated best with the changing behavior of share prices.

Figure 4: Market Capitalization Trend Line
Market capitalization was lowest in 2009 and sharply rose to highest in 2015. Market capitalization is important in projecting the size of an organization because it shows the organization's value. Market capitalization is a measure of the value of companies and stock markets which is an on-going market valuation of a public firm whose shares are publicly traded on a stock exchange computed by multiplying the number of outstanding shares held by the shareholders with the current per share market price at a given time. A market capitalization calculation is a critical part of any stock valuation formula as it represents the total market value of all the company's outstanding shares. Market capitalization can be used as a proxy for the public opinion of a firm's net worth and is a determining factor in some forms of stock valuation. Market capitalization represents the public consensus on the value of a firm's equity. According to Koila, Kiru, and Koima (2018), using the random-effects model also revealed that market capitalization could not be used to predict the outcome of return on equity within the listed firms in the Nairobi Securities Exchange.

Correlation Analysis
The study a conducted correlation analysis between Long term debtand financial growth measured using growth inearnings per share and growth in market capitalization. Table 2 shows the correlation matrix of long-term debtand growth inearnings per share as a measure of financial growth. The results found that,long term debt and growth in earnings per share are positively associated. Long term debt involves strict contractual covenants between the firm and issuers of debt, which is usually associated with high agency and financial distress costs. High long-term debt levels in the firm's financial structure is not conducive to the effective operation of the firm, since they increase the risk of bankruptcy. According to Opungu (2016), long term debt-equity ratio has a negative effect on return on assets and return on equity but has an insignificant effect on return on capital employed. The results found that long term debt and growth in market capitalization arepositively associated. The scarcity of long-term finance is a key impediment to greater investment, and the financial growth. Access to long term financing is one of the critical financial sector policy challenges facing firms. The long-term debt, preferred stock, and common stock together would contribute as the total capital of the firm. The ratio allows the investors to figure out the total risk of investing in a particular business, which can be easily determined by the long-term debt to capitalization ratio. It also shows how financially the company is. The results contrast Lixin and Lin (2008) in a study on the relationship between debt financing and market value of real estate companies of China that long-term borrowing and commercial credit financing has a positive correlation with the firm's market value.

4.4Effect of Long Term Debton Financial Growth
Panel regression analysis was conducted on growth in earnings per share and growth in market capitalization.The random model was estimated to determine whether there was a significant relationship between long term debt and variation in the growth in earnings per share. Table 4 presents the panel regression model on long term debt versus growth inearnings per share as a measure of financial growth. The fitted model from the result is Growth in EPS = -1.08621+ 0.500407LTD Where: EPS = Earnings Per Share LTD = Long Term Debt As presented in Table4, the coefficient of determination R-Square is 0.216. The model indicates that long-term debt explains 21.6% of variation in the growth inearnings per share as a measure of financial growth. This means 21.6% of the variation in the growth inearnings per share as a measure of financial growth is influenced by long-term debt. The findings further confirm that, the relationship between long term debt and growth in earnings per share as a measure of financial growth is positive and significant with a coefficient of (β =0.500407, p=0.000). It implies that, there exists a positive and significant relationship between long term debt and growth in earnings per share as a measure of financial growth since the coefficient value was positive,and the p-value was0.000< 0.05. It means that, a unitary increase in long term debt leads to growth in earnings per share as a measure of financial growthby 0.500407units holding other elements of financial structure constant. Long term debts are the most preferred sources of debt financing among well-established corporate institutions mostly by their asset base, and collateral is a requirement for many of the deposits-taking financial institutions.
The results do not agree with Salim and Yadav (2012) that long term debt has a negative relationship with earnings per share. Further, Tifow and Sayilir (2015) noted that long-term debt has a significant but negative relationship earnings per share. Fatoki and Olweny (2017) describes earnings per share, as one of the most important financial statistics that is noteworthy for investors and financial analysts. It shows the earnings that a firm has achieved in a fiscal period for an ordinary share and often is used to evaluate the profitability and risk associated with earning and judgments about stock prices. Table 5 presents the regression model on long term debt versus growth of market capitalization as a measure of financial growth. The fitted model from the result is Growth inMarket Capitalization = 2.583273+0.498664LTD Where: LTD = Long Term Debt As presented in Table 5, the coefficient of determination R-Square is 0.0516. The model indicates that, long term debt explains 5.16% of the variations in the growthin market capitalization as a measure of financial growth. It means 5.16%of the variation in the growthin market capitalization as a measure of financial growthis influenced by long term debt. The findings further confirm that, the regression model for long term debtand growthin market capitalization as a measure of financial growthis positive and significant with a coefficient of (β =0.498664, p=0.000). It implies that, there exists a positive and significant relationship between long term debt and growthin market capitalization as a measure of financial growthsince the coefficient value was positive and the p-value 0.000<0.05. It means that a unitary increase in long term debt leads to growth in market capitalization as a measure of financial growth by 0.498664units holding other elements of financial structure constant.The scarcity of long-term finance is a key impediment to greater investment and growth of the firm. Access to appropriate instruments of long-term financing is one of the critical financial sector policy challenges facing firms. The results agree with Lixin and Lin (2008) in a study on the relationship between debt financing and market value of listed real estate companies of China that long-term borrowing and commercial credit financing have a positive correlation with the firm's market value.

4.5Hypothesis Testing
The hypothesis was tested using p-value method.The acceptance/rejection criterion was that, if the pvalue is greater than the significance level of 0.05, we fail to reject the Ho,but if it's less than 0.05 level of significance, the Hois rejected.The null hypothesis was that,there is no significant effect oflong-term debt on financial growth of Non-financial firms listed at Nairobi Securities Exchange. The results in Table 4 show that, long term debt and growth inearning per share as a measure of financial growthispositively and significantly related withp-value=0.000<0.05. Further, the results in Table 5 shows that, long term debt and growth in market capitalization as a measure of financial growth ispositive and significantly related with p-value=0.000<0.05. The null hypothesis was therefore rejected and concluded that, there is a significant relationship betweenlong-term debt and financial growth of Non-financial firms listed at Nairobi Securities Exchange.

V. Conclusion
Based on the findings, the study concluded that long term debt has a positive and significant relationship with financial growth measured using growth inearning per share. Long term debts are the most preferred sources of debt financing among well-established corporate institutions mostly by their asset base, and collateral is a requirement for many of the deposits-taking financial institutions. Long term debt involves strict contractual covenants between the firm and issuers of debt, which is usually associated with high agency and financial distress costs. Highlong-term debt levels in the firm are not conducive to the effective operations of the firm since they increase the risk of bankruptcy.
The study also concluded that, long term debt has a positive and significant relationship with financial growth measured using growth inmarket capitalization. Inability of non-financial firms to accesslong-term finance is a key impediment to greater investment and growth of the firm. Access to long-term financing is one of the critical financial sector-wise policy challenges facing firms.

VI. Recommendations
The study revealed that,long term debt influences financial growth. The study recommends that, the management of non-financial firms listed at Nairobi Securities Exchange to employ financing means that can improve the earnings per share, market capitalization and enhance the value of the firm for the benefit of its stakeholders.


extfieldsofstudy: Physics Business

text:
Analysis of the DuPont model of the construction industry in the Baikal region

In the context of globalization, the role of the investment component in the dynamics of economic development is significantly increased. The DuPont model allows you to determine which factors caused the change in profitability or to make a factor analysis of the return on equity. The object of the study is construction companies (construction of residential and non-residential buildings) in the Baikal region of the Russian Federation (Irkutsk region, Republic of Buryatia, Zabaikalsky Krai). The article describes the methods of factor analysis developed by Filatov E. A., which make it possible to make an accessible and relatively simple conclusion about changes in the financial position of the enterprise, as well as to assess the degree of influence of factors on changes in the studied indicator. The purpose of this article is to generalize and systematize the theoretical and methodological foundations of factor analysis in a form that is accessible to specialists in the field of economics and management. The article should contribute to the formation of a basis for managers and economists to develop economic thinking, understanding the essence of economic processes and phenomena occurring within the framework of economic entities, and most importantly – the development of skills for their quantitative assessment, economic interpretation and search for reserves to improve the efficiency of functioning. The article was carried out within the framework of the scientific project of the Inc SB RAS no. XI.174.1.4 ‘Activation of the internal development potential of regions of resource specialization (on the example of the Baikal region)’

Introduction
Construction is one of the key fundforming industries, on which the formation of the national economy largely depends. In the structure of the gross value added of the Russian Federation for 2017, the construction sector occupies 6.2%.
Construction is a fundforming industry, on which the formation of the national economy depends, and that is, the formation of a complex economic, social, organizational, and scientific and technical system depends.
The construction industry sets the pace of economic development and is a very significant sector in the economy of many countries of the world. The relevance of the article is due to the dynamic development of construction services in the last few decades in the world economy. At the same time, this industry is very sensitive to even minor changes in the global market environment.

Research questions
Improving the methods of factor analysis is a key task of economic analysis. The more detailed the influence of factors on the value of the indicator is considered, the more accurate the results of the analysis and the assessment of the quality of the decision made. In some situations, without a deep and comprehensive study of the direct impact of factors, it is impossible to draw reasonable conclusions about the company's performance.
One of the most important tasks of financial analysis of any economic phenomenon is to identify factors whose level and dimensions have a decisive influence on the formation and change of the level of the phenomenon, considered as effective in relation to these factors (Hakstian, A. R., Roqers, W. D., & Cattell, R. B., 1982).
One of the main tasks of financial management in the company is to ensure financial stability, which could contribute to the growth of return on equity.
In order to evaluate the performance of any company, you need to use some methods of analysis. The analysis methodology is understood as a certain sequence of operations, techniques, actions, and rules for the most appropriate execution of analytical work ( Deterministic factor analysis is a method of studying the influence of factors that are related to the performance indicator is functional, that is, the performance indicator can be represented as the product of various factors (Kim, J. O., & Mueller, C. W., 1978b).
The profitability of the company and the growth of its value for shareholders is reflected by the profitability coefficients. Managing the profitability of an enterprise becomes a key task for all levels of management: strategic, tactical, and operational. DuPont has proposed a simple way to manage profitability by decomposing the profitability coefficient into factors that reflect various aspects of the company's activities.
In practical analytical work, the DuPont method was used by DuPont specialists in the 1920s.
The DuPont equation (also the DuPont Model or the DuPont Formula) is a modified factor analysis that allows you to determine which factors caused the change in profitability. The basis of the factor model in the form of a tree structure is the indicator of return on equity (ROE), and the signs are characterizing the factors of production and financial activity of the enterprise (Ivanov, P. I., 2019; Kazakova, N. A., 2018; Rozanova, N. M., & Zoroastrova, I. V., 2018). Simply put, the factors that affect ROE are broken down to find out which factors more or less affect the return on equity. The main three factors: 1. return on sales (this coefficient is calculated as the ratio of net profit to revenue (net) from all types of sales); 2. asset turnover (the asset turnover ratio or total capital return is calculated as the ratio of revenue from all types of sales to the total amount of assets); 3. the equity multiplier (the inverse of the financial independence coefficient or the autonomy coefficient characterizes the ratio of total assets to the organization's equity).
The purpose of the study is to analyze the DuPont model of the construction industry in the Baikal region using new author's methods of factor-based deterministic analysis (Filatov methods), which more reliably and argumentatively evaluated its results.

Materials and methods
The initial data for the analysis of the DuPont model of the construction industry in the Baikal region using Filatov's methods (Filatov, E. A., 2018) are presented in table 1.
The object of the study is construction companies (construction of residential and non-residential buildings) in the Baikal region.
The sources of the information base on the financial results of construction companies in the Baikal region were financial statements according to Russian where: * 0 -past (base) period (year) taken as a basis for comparison; ** Ireporting (current) year; *** ∆ -change for the period is calculated as the difference between the fact and the plan (I -0).
The decrease in such basic absolute financial indicators as revenue by -9.01% and total assets by 10.65% is due to the depreciation of the ruble against the dollar during 2018 by 17.09%.
In this case, the original formula for factor analysis will have the following form (formula 1): The deviation balance is found as follows (formula 2): The algebraic sum of the influence of factors must necessarily be equal to the total increase in the effective indicator. The absence of such equality indicates mistakes in the calculations. Next, we will consider 10 methods of deterministic factor analysis developed by Filatov E. A.
Auxiliary data on the author's comparative coefficients for factor analysis are presented in tables 2, 3. Table 2. Multiple comparative coefficients for one factor in the whole Baikal region

Results
The result for methods 1.  As can be seen from the final result of tables 1, 5, 6, the purpose of the analysis is achievedthe determination of the influence of factors is disclosed without deviations.
The final change in the return on equity of the construction industry in the Baikal region had a positive impact: -decrease in the equity multiplier by -483.64%, caused an increase in return on equity by 7.15%.
The final change in the return on equity of the construction industry in the Baikal region had a negative impact: -an increase in asset turnover by 1.35% caused a decrease in return on equity by -0.34%.
The combined effect of three factors led to a decrease in return on equity by -38.83%.
The main decrease in the return on equity of the construction industry in the Baikal region is due to a decrease in the return on sales of the construction industry in the Baikal region. In turn, the decrease in the profitability of sales of the construction industry of the Baikal region is mainly due to a decrease in the net profit of the construction industry of the Republic of Buryatia by -60.1 million dollars.
The turnover of assets of the construction industry in the Baikal region has not changed much (a change of about 1%), which has almost no effect on the change in the return on equity of the construction industry in the Baikal region. The turnover of the construction industry of the main economy of the Baikal region -Irkutsk region decreased by 3%, which was offset by a 10% increase in the turnover of the construction industry of the Republic of Buryatia and the Zabaikalsky Krai.
The main increase in the return on equity of the construction industry in the Baikal region is due to changes in the equity multiplier of the construction industry in the Baikal region. In turn, the change in the equity multiplier of the construction industry in the Baikal region was mainly influenced by an increase in the equity of the construction industry in the Irkutsk region by +63.5 million dollars or 2.3 times.

Discussion
The investment attractiveness of the region depends on the level of return on equity. From the point of view of owners, profitability is most reliably displayed in the form of return on equity. This indicator is important for the company's shareholders, as it characterizes the profit that the owner will receive from one monetary unit of investment invested in the company. Return on equity provides an idea of the revenue that a company earns for shareholders. Return on equity is compared with possible alternative investments in shares of other companies, bonds, bank deposits, and so on. The minimum (standard) level of profitability of an entrepreneurial business is the level of bank deposit interest. The minimum regulatory value of the return on equity (ROE N ) is determined using the following formula 3: where: ROE N -the Minimum standard value of the return on equity indicator; ROE -return on equity; Sd -the average rate on Bank deposits for the reporting period; Sp -the income tax rate.
Let's calculate ROE N for 2017 in Russia. Weighted average interest rates on deposits (deposits) of individuals attracted by credit institutions in rubles for the whole of the Russian Federation up to 1 year, including «on demand» in 2017, based on data from the Central Bank of the Russian Federation, amounted to 5.86%. The income tax rate is 20%. As a result, ROE N = 0.0586 * (1 -0,2) = 0.0469 or 4.69%.
Let's calculate ROE N for 2018 in Russia. Weighted average interest rates on deposits (deposits) of individuals attracted by credit institutions in rubles for the whole of the Russian Federation up to 1 year, including «on demand» in 2018, based on data from the Central Bank of the Russian Federation, amounted to 5.35%. The income tax rate is 20%. As a result, ROE N = 0.0535 * (1 -0,2) = 0.0428 or 4.28%.
Count ROE N for 9 months of the year 2019 in the Russia. Weighted average interest rates on deposits (deposits) of individuals attracted by credit institutions in rubles for the whole of the Russian Federation up to 1 year, including «on demand» for 9 months of 2019, based on data from the Central Bank of the Russian Federation, amounted to 5.63%. The income tax rate is 20%. As a result, ROE N = 0.0563 * (1 -0,2) = 0.045 or 4.5%.

Conclusion
Analysis based on the DuPont method allows you to determine the strengths and weaknesses of economic entities. Each weak financial ratio may be subject to a deeper decomposition to get an accurate idea of the cause of the weakness. When the sources of problems are identified, the company's management can develop measures to improve return on equity, for example, improve cost control, improve asset management, improve marketing, and so on As you can see, the return on equity under the DuPont model depends on three factors: the level of return on sales, the speed of asset turnover, and the equity multiplier. Thus, the directions for improving the return on equity are directly indicated. DuPont's three-factor model shows the impact of operating activities (sales), investment and financial activities on the firm's return on equity.  11 Factor analysis is aimed at identifying the impact of individual factors on the performance indicator, so deterministic modeling of factor systems is a simple and effective means of formalizing the relationship of economic indicators, which serves as a basis for quantifying the role of individual factors in the dynamics of changes in the generalizing indicator (Bartholomew, D.J., 1984). Due to the fact that factor deterministic factor analysis is aimed at identifying the influence of factors on the value of the effective indicator of interest excluding error, it is most relevant for practical use in market relations (Joreskog, K. G., & Sorbom, D., 1979).


The current use and potential of cost bene fi t analysis in water sector projects

The investment needed in global water infrastructure is significant. Infrastructures in water supply and sanitation alone are expected to require USD 6.7 trillion by 2050. These infrastructures must provide investment justifications when seeking funding from disbursement sources, in competition with other services (such as health, education, transport, elderly care etc.). We present a review that identifies monetary valuation gaps in regional and global cost benefit analysis (CBA) guidelines that underpin investment justifications. Case studies of Scandinavian appraisal reports written according to these guidelines indicate an alarmingly low use of monetary valuation on socioeconomic and environmental impacts caused by water sector projects. The findings suggest a need for broader and more accessible recommendations for water sector specific valuation methods. The need to develop a more accessible CBA framework for water infrastructure project managers is theoretically discussed, with emphasis on utilising monetary valuation methods and secondary source data. We identify valuation methods fragmentally discussed in the guidelines that should be adapted and applied, in time and cost-efficient ways, to water infrastructure projects.

INTRODUCTION
Most water infrastructures are public entities, fiscally not profitable, environmentally and socio-economically crucial, and depend on disbursements. Therefore, decision makers and funding bodies must be made aware of both the financial, socioeconomic and environmental value of these projects (Sartori et al. ; Bouzit et al. ). Cost benefit analysis (CBA) is applicable in most fields and is often a required analysis step by decision makers responsible for awarding disbursements. Although the World Bank, Asian Development Bank, the European Commission (Sartori et al. ) and others have published CBA guidelines, they somewhat diverge in methodologies and insist on CBA expertise to execute the analysis. Several reports indicate an underutilised rate of use of these guidelines in the water sector and point to reasons such as a sector-wide lack of access to experts that execute CBA beyond financial evaluations. Projects suffer from a lack of access to CBA experts, alongside scepticism of both the robustness and need for CBA (Pollak ).
CBA is a decision support tool often required by disbursement sources, such as national governing bodies and regional and global financing institutes, to assess the impacts of an infrastructure project to society (Pearce et al. ). CBA has early roots. Historically, we find that the underpinning framework and execution of CBA have been tailored to fit the function of the needs of development policies. Initially, until the 1970s, the traditional approach looked to increase the level of welfare in monetary terms.
From the 1970s, the introduction of socio-economic factors appeared, to address equitable income distribution (Rolfe et al. ). From the 1990s onward, CBA with environmental externality valuations have been incorporated with more regularity. Today, CBA are used to win disbursements for water infrastructure projects in a funding pool that is limited and competed for by other sectors. Progress reports on United Nations sustainable development goals highlight that after following several years of steady increases, official development assistance disbursements to the water sector declined by two per cent from 2016 to 2017. However, disbursement commitments to the water sector jumped by 36 per cent between 2016 and 2017, indicating a renewed focus by donors on the sector (Guterres ). Water infrastructure projects apply for funding from limited disbursement funds in fierce competition with public health, roads and transport, capacity building, energy, resilience, military and education sectors. Therefore, the water sector cannot afford to ignore the non-market benefits of their projects in these competitive appraisal processes. Furthermore, disbursement funding sources and society as a whole cannot afford to continue investing in non-modular infrastructures in the water sector. Investments in water distribution networks and treatment facilities could avoid repeating past mistakes, such as sunk-hole investments that create fiscal With SDG target 6A, United Nations sets a favourable context to monetarily quantify cost-benefits of new technologies in water infrastructure appraisals. Water infrastructure in the developing world are holistically net beneficial (United Nations ), meaning their utility to society is net beneficial if socioeconomic and environmental impacts are also considered against financial costs. Justifying the worthiness of a project in such holistic terms is crucial in both the global and local disbursement context. As a rule, public water infrastructures cannot recover financial investment costs through market revenue streams such as tariffs.
In most economies, developing ones in particular, most public infrastructures may appear as sunk cost (i.e. costs not recoverable through other parts of society) if their values are not taken into account (Hussain et al. ; Quah ). Lagging on identifying the holistic value of projects leads to disadvantages when bidding for disbursement; not utilising valuation methods that other public sectors apply with relative success arguably leads to water infrastructures not winning funding in competition with these sectors. The infrastructures range across new build, operational, renovational, rehabilitative and decomissioning projects, as summarised in Table 1.
From assessments of reports within its own institute, global financing institute the World Bank identifies that approved appraisals over the past 20 years for infrastructures listed in Table 1

METHODOLOGICAL FRAMEWORK
Therefore, this paper looks at the current state of CBA by analysing the guidelines available to infrastructure projects seeking disbursements, and by analysing the practical application rate of CBA in the water sector. The paper adopts the methodology from a World Bank internal review of CBA execution in practice (Ward ) and extends it to a wider assortment of impact assessment guidelines while maintaining a focus on applicability to the water sector.
The use of applying the above methodology to multiple case studies of submitted disbursement proposals extends the methodology underpinning several disbursement guideline reviews (World Bank ).  We evaluate 15 CBA underpinned guidelines by regional and global financing institutes and governing bodies against the valuation method branches that comprise the total economic value framework. This approach identifies the major disbursement CBA guidelines, the content differences, the impacts each institution recommends projects to monetarily value, and how well the guidelines are practiced in reports submitted from a range of water sector projects in Scandinavia. The findings are compared against the categories of the total economic value framework, to identify which valuation methods and type of impacts are most widely underutilised in water sector CBA. Each of these underutilised valuation methods can provide decision makers insights on water projects impacts and will be outlined.
The theoretical framework is best illustrated by the grey box indicating the transition between current CBA practice as identified in literature, and the future of a more holistic, practically applicable CBA in the water sector. The paper will discuss the four tenets to transition an underutilised decision support tool in the water sector to a holistic and applicable CBA. The grey, chequered rectangle in Figure 1 discusses the four tenets of making monetary valuation more accessible; identifying applicable conditions, using relevant valuations, showing decision makers the value in using secondary data, and presenting decision makers assessment data in comparable units and relatable language.
The analysis of CBA guidelines and case studies of Scandinavian appraisal reports will reveal current coverage of these four tenets and identify gaps. The aim of this approach is to lay the foundations for tailored CBA guidelines to fit demands for less time-and cost-consuming data sourcing and ease monetary valuation without high dependency on expert insights.
The analysis of major CBA guidelines from national, regional and global disbursement sources such as governments and financing institutions are assessed against their alignment with the total economic value framework. We also focus on the Scandinavian CBA guidelines, to assess against the multinational guideline standards and if they meet project managers' expressed need for time efficient, cost efficient and non-dependence on experts to execute CBA. Case studies of Scandinavian water sector project reports underpinned by the analysed Scandinavian CBA guidelines are investigated to explore differences between monetary valued project impacts in guidelines and in practice.

RESULTS
CBA guidelines correctly identify that the range of projects utilising the guideline are too varied to provide specific valuation instructions and data source recommendations.
End users argue that guidelines lacking accessible and Results from analysis of CBA guidelines   Göteborg and Lidköpings municipality).

Valuation methods identified by guidelines
Several common theories held by all the CBA guidelines are mentioned earlier in this paper. In contrast, this paper also provides the opportunity to collate the monetary valuation methods that are heavily underutilised by the case study appraisals in practice. This section highlights those methods, and provides a platform to discuss the need to develop their applicability to water sector typologies to a greater degree.

DISCUSSION
Illustrating the gap between CBA potential and case study practice rates  | Total economic valuation tree, adopted from Barbier (1989), combined with findings from rate of use of monetary valuation methods in Scandinavian appraisals of water infrastructure projects as listed in

CONCLUSION
The current use of CBA is in many ways defined by the application of CBA guidelines in project appraisals that project owners submit to win disbursements. The development of these guidelines by disbursement sources such as finan- tion and CBA is not the only way to impact assess water infrastructure projects, this paper suggests developing the CBA to a more applicable and accessible decision support tool as the CBA and its incorporated total economic valuation provides an optimal framework to communicate impact in monetary units to decision makers.

DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.