Next Article in Journal
Experimental and Numerical Studies of the Aerodynamics of Stationary Two-Shaft Gas Turbine Exhaust System
Next Article in Special Issue
The Evaluation of Torrefaction Efficiency for Lignocellulosic Materials Combined with Mixed Solid Wastes
Previous Article in Journal
Analyzing the Performance of Thermoelectric Generators with Inhomogeneous Legs: Coupled Material–Device Modelling for Mg2X-Based TEG Prototypes
Previous Article in Special Issue
WACC for Electric Power Transmission System Operators: The Case of Colombia
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Information Value of Individual and Consolidated Financial Statements for Indicative Liquidity Assessment of Polish Energy Groups in 2018–2021

1
Faculty of Management, University of Warsaw, Szturmowa Street 1/3, 02-678 Warszawa, Poland
2
Institute of Economics and Finance, Warsaw University of Life Sciences, Nowoursynowska Street 166, 02-787 Warsaw, Poland
3
Faculty of Management and Technical Sciences, Warsaw Management University, Kawęczyńska Street 36, 03-772 Warsaw, Poland
*
Author to whom correspondence should be addressed.
Energies 2023, 16(9), 3670; https://doi.org/10.3390/en16093670
Submission received: 22 March 2023 / Revised: 17 April 2023 / Accepted: 21 April 2023 / Published: 24 April 2023
(This article belongs to the Special Issue Energy Economics and Policy Analysis)

Abstract

:
Electricity is currently one of the most popular sources of energy. Considering such widespread use of electric energy, we may ask, what is the economic cost of producing and supplying it? The climate crisis and the social pressure associated with it have triggered the necessity to make further investments in renewable and low-emission energy sources, while the COVID-19 pandemic has abruptly limited electricity consumption in industry. All these factors can have an impact on disruptions or loss in the liquidity of companies responsible for supplying electricity to end users. Guaranteeing cash flow for energy sector entities is a prerequisite for energy supply continuity. In this context, the selection and application of reliable sources of information are vital for the management of the financial liquidity of energy sector entities. The aim of this article is to prove the value of the financial information of individual (IFR) and consolidated financial statements (CFR) essential for the indicative liquidity assessment of Polish energy groups in 2018–2021. The hypothesis of this study is that individual and consolidated statements do not offer coincident analytical data due to the diversified role of their parent undertakings. We have applied indicative liquidity assessment analysis from a static and dynamic perspective to 2018–2021, on the basis of individual and consolidated financial statements. The results clearly show high dysfunction in the application of indicative liquidity assessment in the case of the individual financial statement of the parent company. This is mainly due to the role parent companies play in Polish energy sector groups, as they are mainly responsible for support processes.

1. Introduction

Currently, electric energy is one of the most popular sources of energy. Economies and societies are dependent on the continuous supply of electric energy to such an extent that its absence causes serious disruptions in their functioning. Given the widespread use of electric energy, the question of the economic cost of its production and delivery arises. On the one hand, it is an essential good that is difficult to do without, and, on the other hand, its production and transmission require significant infrastructure investments. The climate crisis and the associated social pressure have been driving further investments in renewable and low-emission energy sources, while the COVID-19 pandemic has sharply reduced electricity consumption in industry. All of these factors can have an impact on disruptions to or the loss of financial liquidity by entities responsible for delivering electric energy to end users, which can result in a lack of continuity and certainty of supply. In this context, the selection and use of reliable sources of information in managing their financial liquidity is of crucial importance.
Until the 1990s, the electricity market in Poland was completely closed. As a result of the systemic changes after 1989, electric energy became a product that can be produced and sold. Four energy conglomerates were established, covering the entire country, operating as vertically integrated capital groups with mandatory consolidated reporting. At the same time, the dominant units of these groups were listed on the Warsaw Stock Exchange. There is a research problem concerning the usefulness and informational value of the individual financial reporting (IFR) of dominant entities and the consolidated financial reporting (CFR) of capital groups for the purpose of assessing the financial situation, including the level of financial liquidity.
The aim of this article is to present the usefulness of financial information from individual and consolidated financial statements, necessary for the ratio analysis of the financial liquidity of Polish energy conglomerates in the years 2018–2021. The hypothesis of the study is that individual and consolidated reporting does not provide convergent analytical information due to the different roles of parent undertakings. The consolidated financial statement should play a key role in providing information on the functioning of the capital group, including the parent undertakings.
The paper characterizes the terminology related to the cognitive values of individual and consolidated financial reporting. The methodology of ratio analysis in terms of liquidity analysis is described. The specifics of energy conglomerates in Poland are presented, for which a comparative analysis of liquidity ratios in static and dynamic terms was carried out for the years 2018–2021 based on individual financial statements of parent companies listed on the Warsaw Stock Exchange and consolidated financial statements of their capital groups.

2. Literature Review

A financial report constitutes an orderly collection of numerical data [1] concerning the entirety of the management and financial situation of an entity, while being a final element of the financial accounting cycle for a given period [2]. The Accounting Act imposes the obligation to prepare it on entities that are required to keep the accounts and specifies the basic elements of the report, consisting of a balance sheet, a profit and loss account, and additional information [3]. Entities whose financial reports are subject to a mandatory audit by a certified auditor also prepare a statement of cash flows and a statement of changes in equity. Consolidated financial statements always consist of five listed elements and are always subject to a mandatory financial audit.
In the academic literature, some definitions emphasize the usefulness of the financial report as a primary source of information on the financial and economic situation of a business entity and its ability to be used to assess the effectiveness of its operations [4]. For other authors, the financial report is primarily a way of presenting data [5], being the final link in the information process of accounting [6]. The literature classifies information, control, and evaluation as the most common purposes of financial reports [7]. For a financial report to have useful informational content, it should possess characteristics such as comprehensibility, usefulness, reliability, and comparability [8]. The qualitative characteristics of financial reporting that should primarily ensure faithful and fair presentation of the financial and economic situation of the entity are often raised in the literature [9,10].
The financial report is the primary source of information for financial analysis. Analysis is a research method that involves breaking down the analysed phenomenon into parts and considering each of these parts separately in order to understand the whole [11]. Financial analysis is a tool for evaluating the company’s performance through the use of preliminary financial statement analysis and ratio analysis [12]. The preliminary financial statement analysis concerns the analysis of its two basic elements, namely the balance sheet and the profit and loss account, and serves as a starting point for ratio analysis [13]. This analysis provides detailed information on possible causes of events observed in the preliminary analysis.
In the academic literature, examining the aspect of financial liquidity is most often associated with a simultaneous examination of profitability. This is due to the great difficulty in building an appropriate liquidity management strategy, given the importance of these categories and their interdependencies [14]. Financial liquidity is a factor that strengthens the existence of the entity, but, on the other hand, profitability alone does not ensure liquidity. Therefore, management must decide whether to choose a high profitability policy or a policy that maintains high liquidity [15,16]. Numerous studies describe the relationships between these financial categories in the literature, but the results are often debatable. One of the hypotheses concerns the negative relationship between profitability and liquidity, among others by Bolka and Wilinski [17], Eljelly [18], Kobik [19], and Ajanthan [20].
The necessity of making a choice between liquidity and profitability is often indicated in the literature [21,22]. Deloof [23], Lazardis and Tryfondidis [24], and Gołaś et al. [25] have demonstrated a positive relationship between liquidity and profitability. The latest research results of Czewińska-Florek [26] show the existence of multidirectional dependencies between liquidity and profitability. These depend on financial ratios and industry characteristics. Research has also been conducted on the relationship between financial liquidity and the competitiveness of defense industry companies [27]. It has been observed in the literature that working capital has a direct impact on a firm’s financial liquidity, and, therefore, supporting a working capital management strategy is worthwhile [28]. Zimon [29] investigated the main liquidity management strategies in Polish energy sector firms.
Research findings indicate that consolidated financial statements of capital groups have a greater informational value than individual financial statements of dominant entities (Abad et al. [30], Larran and Rees [31], Niskanen et al. [32], and Muller [33]). Other researchers [34] have found that the financial statements of parent companies do not show an incremental informational value. Research by Harris et al. [35], comparing the informational value of consolidated and individual financial statements between American and German firms in similar industries and of comparable size, demonstrated that the explanatory power of numerical data increases with consolidation. Studies by Choi and Mueller [36], Delvaille et al. [37], Lamb et al. [38], Macías and Muiño [39], Nobes [40], and Oliveras and Puig [41] confirm that the lower usefulness of individual financial statements results from companies preparing and using their reports for many tax or regulatory purposes. The literature indicates that research has been conducted on selected aspects of financial liquidity management in the energy sector, but there is a lack of comparative cognitive value research on individual and consolidated financial statements. The implementation of the objectives of the study will significantly expand the scope of knowledge in assessing the usefulness of reporting information for its recipients.
The importance of the comparative value of financial information (profit, book value, cash flows) contained in consolidated and individual financial statements was demonstrated by research on financial service firms in Nigeria from 2014–2018 [42]. The results indicate that both consolidated and individual financial information of parent undertakings are valuable, but consolidated financial statements are more valuable in terms of the informational value. Similar conclusions were reached by Sofi [43], who investigated the usefulness of financial statements prepared for investors when making decisions. There are also ambiguous research results in this area [44]. Divergent results may be due to differences in economic conditions, market structures in different countries, sample size, and variable selection.
Research on the usefulness of individual and consolidated financial statements for assessing financial stability was conducted by Cartini and Teodorii [45], but only for local government units. The results also show a clear difference between the results of the individual and consolidated financial statements. Other studies focused on the significance of reporting information based on IFRS compared to other reporting systems, and produced ambiguous results [46,47,48].
The above demonstrates the existence of a research gap in the area of examining the usefulness and usability of financial information regarding liquidity through the use of individual and consolidated financial statements. The verification of the usefulness of financial information for the purposes of assessing financial liquidity in accordance with the objectives of the article will increase the scope of the usefulness of research results for analytical and management purposes.

3. Methodology: Static and Dynamic Indicators of Liquidity

The methodology used involves the calculation of appropriate financial ratios and their comparison with sectoral (industrial) or time-based benchmarks, referred to as financial indicators. The most extensive and useful group of indicators were the two-variable relation indicators, referred to as financial ratios. Liquidity, debt, efficiency (effectiveness), profitability, and capital market ratios (for entities in stock trading) were the most frequently used ratios in the research. This study presents selected liquidity ratios as crucial for evaluating the maintenance of financial liquidity, which is significant from the perspective of the continuity of enterprise operations in the short term.
Financial liquidity can be perceived as the value of cash assets that can be easily converted to cash without a loss of value to cover short-term liabilities [49,50]. Liquid assets consist of cash on hand and in bank accounts, their equivalents, and short-term securities [51]. Improved financial liquidity reduces the likelihood of bankruptcy [52,53]. Therefore, the time it takes to convert assets into cash and the degree of certainty associated with this conversion can be perceived as two important dimensions of liquidity [54].
The concept of liquidity refers to the ability to promptly settle current obligations and should be distinguished from the concept of solvency, which refers to the ability to cover obligations with all owned assets [55]. Solvency can be defined as the effectiveness of a company to fulfil its obligations, which include long-term and current debt [56]. In this context, solvency can be measured by debt ratios.
In static liquidity measurement, relationships based on balance sheet data are examined. Liquidity ratios are used to measure a company’s ability to fulfil current liabilities [57]. The current ratio (CR), quick ratio (QR), and cash-to-current-liabilities ratio (CSHR) are the most commonly described ratios in the literature. Measuring liquidity using static liquidity ratios involves the problem wherein the ratio is only a test of asset values and not their quality [58,59]. Therefore, a company’s current liquidity ratio may not reflect its actual liquidity situation. The liquidity ratios (static and dynamic) used in the study are presented in Table 1.
The current ratio (CR) indicates how many times short-term assets cover short-term liabilities. The recommended value ranges from 1.2 to 2.0. A value above 3 is considered too high and is a signal of low efficiency in utilizing current assets and maintaining excessively high cash balances (financial surplus). A value below 1 is considered too low and indicates payment difficulties. The interpretation of this indicator requires an assessment of the optimal level of receivables, inventory, cash, and current liabilities for the company.
The quick ratio (QR), also known as the “acid test,” has a recommended value of approximately 1. A value above 1.5 is considered too high and indicates either a surplus of cash balances (financial surplus) or an excessively high level of receivables. A value below 0.8 is considered too low and may indicate existing payment difficulties and the risk of overdue liabilities. The cash liquidity ratio (CSHR) illustrates the proportion of current liabilities that can be settled immediately without waiting for expected receivables. Its recommended value ranges from 0.1–0.2. A value above 0.3 is considered too high, and when combined with a low value of the quick liquidity ratio, it indicates a dominance of cash turnover in the company.
The dynamic assessment of liquidity is based on cash flow data. Sufficiency and cash efficiency indicators were used in the analysis. Sufficiency indicators describe the ratio of operating cash to various types of expenses, such as total liabilities, long-term liabilities, or short-term liabilities. Indicators in this group show the company’s ability to repay the liabilities of the entity (capital group) under evaluation using available funds obtained from the primary activity.
Cash efficiency indicators illustrate the relationship between operating cash, revenue, assets, and EBIT (earnings before deducting interest and taxes). The ratio of operating cash to total assets or short-term assets shows to what extent they are financed from this source. It is assumed that the higher the level of cash efficiency indicators, the better the company’s financial liquidity. These indicators should have an upward trend over time [60]. Financial ratios should not be interpreted in isolation from the industry and the stage of the company’s operations. Therefore, the calculation of ratio values is often the starting point for further in-depth analysis.
Companies subject to this study, as parent undertakings in capital groups, prepare individual financial statements and consolidated financial statements. The annual consolidated financial statement of the capital group includes data from the dominant unit and non-dominant units. The annual consolidated financial report of a capital group includes data from the parent entity and its dependent entities at all levels, presented as if the capital group were a single entity. The Accounting Act [3] defines the parent entity as a commercial company exercising control or joint control over another entity and specifies the details of these relationships. A dependent entity, on the other hand, is a commercial company controlled by the parent entity.
The consolidation of financial statements involves combining the financial statements of two or more separate economic entities that are financially linked and presenting them as if they were a single economic entity. The consolidation process involves summing the financial statements and making various adjustments, such as intercompany transactions, investments in entities subject to consolidation, differences resulting from fair value measurement, dividends paid and received, and margins on goods sold within the group. The consolidated income statement eliminates, among other things, intercompany transactions, dividend income from consolidated entities, and write-downs of subsidiary values.
Measurement of financial liquidity in a static context is based on data contained in balance sheets, while the dynamic approach also takes into account relevant items from cash flow statements (both individual and consolidated data of the studied groups and entities). These entities are parent entities in capital groups that include many dependent entities, which is why their consolidated financial statements, reflecting the results of the entire capital group, were studied. At the same time, all parent entities are listed on a regulated market, which obliges them to prepare consolidated financial statements according to IFRS, and this possibility is also available for individual financial statements, which all studied entities have used.

4. Results

In 1997, the Energy Law was adopted, which laid the foundations for the energy market in Poland [61]. The electricity market in Poland was fully opened in July 2007. The basic groups of participants in the electricity market in Poland include energy producers, entities servicing energy transmission (system operators), entities servicing energy trading (market operators), and customers. The energy conglomerates formed through the consolidation of the Polish market, which are the subject of this study, are Polska Grupa Energetyczna (PGE) and the Energa Capital Group, Enea Capital Group, and Tauron Capital Group. They were created on the basis of existing production and transmission infrastructure, often as groups of separate entities that were later subject to horizontal and vertical consolidation. Polish energy groups are mainly engaged in the production, distribution, and sale of energy from conventional sources (coal). Supplementary areas of activity include the production and sale of heat, energy from gas fuels, and energy obtained from renewable sources (RES). The basic parameters of the studied entities are presented in Table 2.
The Polish Energy Group, established in 2007, originally consisted of 81 subsidiary companies, which have been continuously undergoing restructuring and reorganization [62]. The PGE Polish Energy Group SA, as the parent company, serves as the corporate centre and engages in wholesale sales. Energa SA was created at the initiative of the State Treasury, the Energy Concern Energa SA, and the Ostrołęka Power Plant Group SA, which became subsidiary companies. In April 2020, PKN Orlen SA became the dominant shareholder of Energa SA [63]. The Western Group was formed in 2002, and was then transformed into the Enea Energy Group. Additionally, the Kozienice Power Plant, the largest coal-fired power plant in Poland, joined the ENEA Group. Tauron Polska Energia SA (the dominant unit of the Tauron Group) is a holding company that oversees corporate functions such as management, strategic investments, regulations, personnel, finance, controlling, purchasing, and internal auditing [64]. The Tauron Group is the largest distributor and the second-largest producer of electricity in Poland. These entities operate in a similar range of services provided, under comparable economic conditions, and with similar coverage of the Polish territory. Therefore, the results of the liquidity analysis can be compared between the entities.
Comparative financial liquidity ratio analysis of energy entities based on balance sheet data indicates a deterioration of liquidity levels in the years under study (Table 3). The Enea Group stands out positively in terms of these indicators, with a decisive majority of readings at a level indicated as correct. The Enea Group also exhibits the greatest impact of inventories on the level of quick liquidity (QR), as the largest difference between current liquidity (CR) and quick liquidity (QR) ratios can be observed. Another characteristic of this capital group is having a relatively high level of highly liquid assets in the form of cash and equivalents. On the other hand, the static liquidity ratios of the Tauron Group are decisively the weakest, as there were no values above 1 for any of the analysed years. This indicates a permanent mismatch between current assets and short-term liabilities, both at the parent entity level and at the level of the entire capital group. There is also a large disparity in the results for individual years. For the Enea and Energa Groups, 2018 was the best in terms of static liquidity, while it was the weakest period for the PGE and Tauron Groups. This suggests that the static liquidity situation is not determined by external factors such as the economic situation in the country, but by internal factors, such as management efficiency or the phase of the entity’s development, e.g., in conducting capital-intensive investment projects.
The current ratio (CR), despite a systematic decline in subsequent years among the studied entities, has values close to the expected ones in the case of the Enea and PGE Groups. In the case of the values, they oscillated in the range of 1.1–2.2, whereas in the PGE Group, only in 2018, the value of the indicator decreased below 1. It should be noted that in the case of the Tauron Group, only in 2019–2020 did the current ratio approach 1, which indicates an excessively high level of short-term liabilities compared to current assets. The situation observed in the examined period in the case of the Energa Group is concerning, due to the systematic decrease in the value of the discussed current ratio to 0.6 in 2021, which is considered a significantly unfavourable reading. In 2021, all capital groups had a current ratio below 1.2. The challenges in terms of the necessary working capital indicate that liquidity ratios in the energy industry are lower than those described as a target in the literature review.
The course of changes in the quick ratio (QR) values was similar to the course of changes in the current ratio (CR), due to the relatively low impact of inventories in this segment of activity. The recommended value of this ratio, which is one, occurred in the case of the Enea and Energa Groups in 2018. The ratios of other entities examined in this position show values 20–30% lower than the reference values, with an unfavourable deviation of the ratio value in the case of Tauron, even up to 50% of the expected reading. It should be noted that lower values of the quick liquidity ratio (QR) in the energy sector also resulted from the increase in inventory values, in which entities in the conventional (coal) energy sector disclose their rights to emit CO2 for their own needs.
The cash liquidity ratio (CSHR) has the lowest information value among those studied. The recommended value of this ratio is around 0.2, although values below this level may not indicate difficulties in maintaining financial liquidity on the balance sheet date. However Enea Group, when the best values of the current and quick liquidity ratios appear, the level of cash in relation to short-term liabilities is the highest. On the other hand, the Tauron Group, in which the level of static liquidity was far from sufficient, had a level of cash similar to the reference level. This indicates that the cash liquidity ratio (CSHR) has limited cognitive significance and should not be used to draw far-reaching conclusions. The results of the static ratio analysis of financial liquidity indicate a correlated course of changes in CR, QR, and CSHR ratios for individual entities. Fluctuations resulted from different dynamics of changes in the value of current assets and short-term liabilities and the overall decline in the ratio of the short-term liabilities of the studied entities. In the case of PGE, a systematic increase in the value of current assets is noticeable. The variations in the values of the components of Tauron Group’s balance sheet were minimal, resulting in the relative stability of the indicators, albeit at a very low level.
The next group of indicators under scrutiny were the dynamic liquidity ratios, with the results presented in Table 4. It should be noted that some of the readings from the individual financial statements of the parent entities in the examined capital groups have negative values, indicating a lack of positive cash flows from operating activities. Such entities do not possess the capacity to repay their liabilities. The first ratio examined was the overall debt service coverage ratio. The dominance of holding companies without significant operational activities in the examined groups resulted in a lack of positive cash flows from this area. Exceptions to this rule are only PGE SA (except for 2019) and Tauron SA, which generated a positive financial surplus in 2021. The construction of the debt service coverage ratios determines that the lowest reading pertains to covering overall liabilities with surpluses from operating activities. The highest readings in this group of dynamic liquidity ratios were recorded in the relation of financial surplus to short-term liabilities. The obtained results, often exceeding 0.9, indicate that long-term liabilities play a significant role in the balance sheet structure of the analysed entities. This is due to both the high demand for long-term investment funds for the transformation of conventional energy sources and the high values of long-term reserves, especially those arising from employee benefits. Generally, the debt service coverage ratios confirm the previously observed trends, with the best level of this metric demonstrated by the Enea Group, whereas the Tauron Group’s performance was the weakest among the analysed entities.
The overall debt service coverage ratio in the analysed entities usually ranged from 10% to 30%, with few deviations. An increasing trend in the ratio is desirable, as it indicates the ability to generate surplus cash to cover debts. During the analysed period, there was an upward trend in the ratio for all entities, with the ratio not falling below 17% between 2020–2022. The best situation regarding the coverage of overall debts with an operating surplus was observed in 2021, wherein the highest reading of 32% was recorded. Among the analysed consolidated financial statements, the Enea Group exhibited the most stable level of the ratio, which ranged between 12% to 28%. At the same time, the lowest values, similar to static liquidity ratios, ranging from 9% to 21%, were recorded by the Tauron Group.
The long-term debt service coverage ratio is a refinement of the previous ratio and indicates the proportion of long-term debts that can be covered by operating cash flows. It is similar in interpretation to the popular financial market ratio and often used as a bank covenant, i.e., net debt/EBITDA (earnings before interest, taxes, depreciation, and amortization). Changes in the value of this ratio are similar to the changes in the overall debt service coverage ratio. The highest values were recorded in 2021, wherein the Enea Group had a record level of 70%. This was a result of a significant reduction in the level of long-term debts in the capital group. All analysed entities had lower values of this ratio in 2018–2019, ranging from 14% to 24%, except for the PGE Group, which had a reading of around 30% in those years. In 2020–2021, there was a significant improvement in the value of the analysed ratio, mainly due to an increase in the operating surplus value.
Changes in the short-term debt service coverage ratio differ from the trend in the sufficiency ratios, mainly due to larger differences in the readings between individual years. This is mainly due to the greater variability of short-term debts on the balance sheet date compared to long-term debts. The Enea and Tauron Groups exhibit the smallest deviations, as the consolidated readings range from 33% to 51% and 26% to 55%, respectively, whereas for the PGE Group, it is between 34% and 68%. The weakest results for this ratio were observed in 2019 (except for the PGE Group) due to the decrease in the value of operating cash flows and the increase in short-term debts.
The study of cash efficiency allows for the determination of how effective revenues, assets, and financial efficiency measured by EBIT profit are in generating positive cash flows. The results presented in Table 5 contain the reading “n/d” (not applicable), which indicates that negative cash flows from operating activities occurred during the period, while also recording negative operating results. Such a situation pertains to data contained in the individual financial statements of the entities being investigated, and warrants caution in interpreting the results of the analysis obtained using this information. Some of the indicators in Table 5 have negative values, which indicate negative cash flows from operating activities during the period. A negative evaluation of these values can be interpreted as the size of the surplus that needs to be covered in relation to the reference base of operating cash flows. Due to negative operating cash flows in the individual financial statements of the parent companies (with the exception of PGE SA 2018, 2020, and 2021, as well as Tauron in 2021), only the results obtained on the basis of consolidated financial statements will be subjected to evaluation.
The cash efficiency ratio of the consolidated sales of the entities being studied ranges from 0.10 to 0.22. Similar to the sufficiency indicators, a decline in the values of the indicators can be observed in 2019, which is associated with an overall decrease in the values of inflows from operating activities in the range of 0.10–0.18. The values for PGE were the least subject to fluctuations, ranging from 0.14–0.22 during the study period. The highest readings were recorded in 2021, indicating that the pace of growth in the operating surplus was higher than the pace of revenue growth. In the case of the Enea and Energa Groups, the level of the indicator was 0.26.
The values of the cash asset efficiency ratio are significantly lower than the cash sales efficiency ratios due to the higher asset values in the balance sheet resulting from the specific nature of the activities in the energy sector. It can be observed that after relatively stable ratios in 2018–2019, there was a significant improvement in the two subsequent years, mainly due to the increase in operating cash flows. The entities under investigation achieved their highest values in 2021 (with the exception of PGE), with the highest reading in the Energa Group at 0.17. As with the previous ratio, it can be concluded that the energy groups under study systematically improved their liquidity position in subsequent years, mainly due to higher generated financial surpluses from operating activities.
The last analysed performance ratio in this group is the operating profit efficiency ratio. This ratio determines the amount of cash that has been generated from the operating profit of the enterprise. In most cases, it is not possible to measure this ratio using individual financial statements. Observations made using data from consolidated financial statements indicate that the value of this ratio in the Enea and Energa Groups systematically improved in subsequent years, reaching a value of over 2.5 in 2021. This means that the generated operating surplus was more than twice the achieved operating result. If the latter is relatively low, the analysed ratio may take on high values, as evidenced by the example of the Tauron Group data. In 2020, the Tauron and Enea Groups, and in 2019, the PGE Group, recorded a negative operating result at the consolidated level, which is a concerning signal for the assessment of the level of both financial liquidity and operating profitability. One of the groups investigated that had a positive operating result in the studied years and positive operating cash flows was the Energa Group. The conducted analysis of financial liquidity using a dynamic approach shows values of ratios slightly lower than recommended, but that should not cause significant concerns about the loss of financial liquidity.

5. Discussion

The comparison and evaluation of the informational usefulness of individual and consolidated financial statements cannot be detached from the role of parent entities in a given capital group. In the conducted study, all parent entities only played the role of so-called holding companies, which supervise the entire activity of multi-level capital groups. Usually, they do not carry out significant operating activities, limiting their activities to support functions. This is evidenced by the basic financial figures describing the scale and results of the operations of the investigated dominant entities presented in Table 6.
The magnitude that affects the level of financial stability of companies and capital groups is represented by revenue from sales. The comparison of revenue figures, along with the achieved results on both an individual and consolidated level, is presented in Table 5. The revenue from sales of the entities under examination increased during a given period. There has been no collapse in sales that would explain the losses reported in the operational activity and net losses in the consolidated financial statements. In most cases, this was due to asset write-downs resulting from permanent impairment. In the case of the Tauron Group, in 2020, updates of write-downs and a reduction in the book value of loans granted to Stalowa Wola Power Plant were made, reducing the Group’s gross financial result by EUR 676 million [65]. In the case of Enea, an updating write-down of the value of the production assets of its subsidiary, Enea Wytwarzanie (Kozienice Power Plant), was made in the amount of EUR 723 million, and a reserve was created in the amount of EUR 47 million for future investment obligations towards Ostrołęka Power Plant [66].
In 2019, the Energa Group made an updating write-down of the value of assets in the Ostrołęka B Power Plant totalling EUR 93 million, as well as assets in the Elbląg Cogeneration Plant totalling EUR 17 million. In addition, in 2018, the updating write-downs of the value of wind and photovoltaic assets were reversed, totalling EUR 58 million [67]. In 2020, the net result of the Energa Group was affected by the loss of value of conventional coal assets [68]. In 2019, the loss of the PGE Group was a result of creating write-downs on the loss of value of assets in the conventional energy segment, mainly the Bełchatów and Turów complexes, as well as reversing write-downs in the renewable energy segment [69]. It should be emphasized that the events mentioned, which significantly burden the financial result, do not have a cash expenditure character, and therefore do not affect the assessed level of financial liquidity.
All dominant units were characterized by a relatively insignificant share of revenue from sales in relation to the revenue of the represented capital group. The highest share was in the case of the PGE Group, where operational revenue increased from 44% in 2018 to 68% in 2021, and in the case of the Tauron Group, where the increase was similar, from 48% to 71%. Such significant changes in the structure signify significant changes in the structure of the given group. In other capital groups, the revenue of the dominant unit was much less significant. In the Enea Group, it was quite stable and amounted to approximately 35%. The revenue of the dominant unit in the Energa Group was entirely marginal, as its share in consolidated revenue did not exceed 1%.
The stability of the functioning of an economic entity requires achieving a positive operating result. However, in the analysed dominant units, Enea and Energa, a negative operating result EBIT occurred in all the analysed years. In the case of companies that have a higher share in the group’s revenue (PGE and Tauron), positive financial results were much more common. The consequence of the holding role of dominant companies in the analysed energy concerns is much better results in terms of net profit than EBIT, which results from dividends paid by subsidiary units. The reversal of this relationship occurred only in 2018–2019 in the case of PGE SA and Tauron SA, which recorded negative net results with a positive EBIT value. This was due to the high financial costs incurred by these dominant units, which are most often responsible for financing the entire capital group.
The results of the conducted research in the area of financial liquidity also indicate the existence of serious dysfunctions in the interpretation of financial data contained in individual financial statements for use in ratio analysis. The main problem with using this information is the lack of observations of regularities that can be evaluated. In the case of static financial liquidity ratios, the financial statements of the dominant units in the Enea and PGE Groups indicate significantly higher levels of liquidity than data from consolidated financial statements. In the case of the Tauron and Energa Groups, the calculated liquidity ratios are very similar both when using individual and consolidated financial statements (with the exception of 2018 in the case of the Energa Group).
In the case of determining dynamic debt service coverage ratios, information from the individual financial statements turned out to be completely useless. The main reason for this was negative operating cash flows, which made it impossible to logically interpret the ability to repay liabilities. It should be noted that maintaining negative operating cash flows in subsequent years is not a standard situation. This is only possible in entities that do not play a significant role in generating positive cash flows, which are the basis for the stability and financial liquidity of any organization. This proves that the informational content of an individual financial statement for analysis purposes is determined by the nature of that unit, its size, and its role in the capital group.
Similar evidence is provided by the conducted ratio analysis in the area of cash flow efficiency. Some readings based on individual financial statements had negative values, which, with the prevailing positive values obtained on the basis of data from consolidated financial statements, may change the conclusions of the analysis. In addition, the values of the ratios estimated on the basis of consolidated data were significantly higher than the values based on individual data. Even with positive operating cash flow values from individual and consolidated financial statements, cash efficiency ratios were about five times higher based on consolidated data. Using only individual data in assessing the functioning of a market-regulated entity can lead to unjustified conclusions about the effectiveness of the capital group’s operation. The results of the study indicate that whereas differences in the values of liquidity indicators were not critical at the static level of assessment, the analysis of dynamic liquidity indicators unequivocally indicates that consolidated financial statements should be used to assess the performance of the capital group (including the effectiveness of the dominant entity). Confirmation of the hypothesis of the limited role of the dominant entities in perceiving the financial situation, including liquidity, is provided by information on cash flows from operating activities presented in Table 7. With few exceptions (mainly PGE SA), parent entities had negative cash flows from operating activities, which in practice should prevent them from maintaining stable operations in the longer term. Such a situation can occur continuously only in entities that do not perform a key function in operational processes. Therefore, assessing the financial situation using information derived exclusively from individual financial statements may be subject to significant cognitive error.
The measures of operating activities exhibit an upward trend during the observed period, which has had a positive impact on the indicators of solvency, asset efficiency, and sales. The value of the operating profit margin ratio is influenced by the value of EBIT, which can occasionally be negative. As described above, the values of operating profit and net profit may be unfavourably affected in the near future due to transformations within the energy sector.

6. Conclusions

In conclusion, the energy sector is crucial for the functioning of modern civilization. The particular position of the energy sector provides significant market advantages but also presents many challenges. The main challenges include ensuring a stable and continuous electricity supply to all consumers, which requires financial stability, liquidity, and a transformation of the sector in Poland towards low-emission and renewable energy sources.
The study and evaluation of liquidity were utilized to assess the usefulness of financial information derived from individual and consolidated financial statements. The results clearly indicate significant dysfunction in the applicability of liquidity ratio analysis to information derived from the individual financial statements of the parent companies. In the case of static ratio analysis based on data from the balance sheet, the results were not significantly different; however, significantly higher indicator values were observed for data derived from individual financial statements in two capital groups. In the two remaining cases of the analysed capital groups, the results were similar. The verified research hypothesis equally applies to all surveyed entities. Alternatively, it can be tested using statistical tools that use a wider range of data, but for the energy sector in Poland, there are not enough entities on the market.
The assessment of liquidity using dynamic indicators based on operating financial surpluses demonstrates the lack of cognitive value in the area of individual financial statements. Negative operating cash flows of the controlling entities prevented the analysis and assessment of liquidity levels for these entities in the analysed years. This is largely due to the role played by the parent companies in the Polish energy sector capital groups. They are entities almost exclusively serving as holding companies, mainly engaged in support processes. The key financial data of energy production and raw material extraction entities, which are decisive in assessing the efficiency of the group’s activities, are represented by dependent companies, and their financial size is reflected in the consolidated financial statement.
This study used the financial statements of entities listed on regulated markets, which means that the scope and availability of data were at the expected level. All reports have been prepared in accordance with international financial reporting standards. The data quality may be limited only by the increased amount of liabilities due to reserves by individual entities. The specificity of the Polish energy sector includes, among others, high depreciation costs due to the loss of value of conventional (coal) assets, which results in operating losses and net results. Negative financial results also result from the creation of reserves for future investment liabilities. Most likely, extending the research horizon for a period longer than four years would be justified, but there are no arguments that this would change the result of testing the research hypothesis.
Directions for further research should concern research into the quality of individual and consolidated reporting in other countries, in particular with the use of financial information of non-public entities. Additionally, the deliberate selection of entities for research with a different role for their holding companies (dominant) could provide interesting results in the context of the utility value of individual and consolidated information. The results obtained from this study and further ones should influence the shaping of future energy markets and energy policy. In particular, this applies to the creation of financially effective organizational structures of entities in the modern energy sector based on renewable energy sources. In addition, the results may be helpful for users of financial reporting in various sectors of the economy, indicating the level of usefulness and limitations of individual types of financial reporting.

Author Contributions

Conceptualization, L.B., M.K. and A.K.; methodology, L.B., M.K. and A.K.; software, L.B., M.K. and A.K.; validation, L.B., M.K. and A.K.; formal analysis, L.B., M.K. and A.K.; investigation, L.B., M.K. and A.K.; resources, L.B., M.K. and A.K.; data curation, L.B., M.K. and A.K.; writing—original draft preparation, L.B., M.K. and A.K.; writing—review and editing, L.B., M.K. and A.K.; visualization, L.B., M.K. and A.K.; supervision, L.B., M.K. and A.K.; project administration, L.B., M.K. and A.K.; funding acquisition, L.B., M.K. and A.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Świderska, G.K.; Więcław, W. Sprawozdanie Finansowe bez Tajemnic; Difin: Warszawa, Poland, 2008; pp. 1–16. [Google Scholar]
  2. Maruszczak, K. Rola Sprawozdań Finansowych w Procesie Podejmowania Decyzji w Przedsiębiorstwie; Prawnicza i Ekonomiczna Biblioteka Cyfrowa, Wydział Prawa, Administracji i Ekonomii Uniwersytetu Wrocławskiego: Wrocław, Poland, 2015; p. 85. [Google Scholar]
  3. Ustawa z dnia 29 Września 1994 r. o Rachunkowości (tj. Dz. U. z 2023 r. poz. 120.). Available online: https://isap.sejm.gov.pl/isap.nsf/download.xsp/WDU20230000120/U/D20230120Lj.pdf (accessed on 15 April 2022).
  4. Żukowska, H. Sprawozdawczość Finansowa w Systemie Wymiany Informacji i Bezpieczeństwa Obrotu Gospodarczego; Wydawnictwo KUL: Lublin, Poland, 2016; p. 29. [Google Scholar]
  5. Tkocz-Wolny, K. Sprawozdanie finansowe przedsiębiorstwa jako forma prezentacji informacji ekonomicznej. Stud. Ekon. 2016, 287, 111–122. [Google Scholar]
  6. Kamiński, R. Sprawozdawczość Finansowa Przedsiębiorstwa w Regulacjach Polskich i Międzynarodowych; Wydawnictwo Naukowe UAM: Poznań, Poland, 2015; pp. 13–14. [Google Scholar]
  7. Garbusewicz, W.; Remlein, M. Sprawozdanie Finansowe Przedsiębiorstwa Jednostkowe i Skonsolidowane; PWE: Warszawa, Poland, 2011; p. 33. [Google Scholar]
  8. Rozporządzenie Komisji (WE) Nr 1126/2008 z dnia 3 Listopada 2008 r. Przyjmujące Określone Międzynarodowe Standardy Rachunkowości (MSR1) Zgodnie z Rozporządzeniem (WE) nr 1606/2002 Parlamentu Europejskiego i Rady Wraz z Rozporządzeniami Zmieniającymi. Available online: https://eur-lex.europa.eu/legal-content/PL/TXT/?uri=celex%3A32008R1126 (accessed on 15 April 2022).
  9. Rówińska, M. Cechy jakościowe sprawozdania finansowego jednostek gospodarczych. Finans. Rynki Finans. Ubezpieczenia 2013, 58, 375–382. [Google Scholar]
  10. Tokarski, M. Sprawozdanie finansowe—Niedoskonałe źródło informacji o sytuacji finansowej przedsiębiorstwa. Przedsiębiorczość Eduk. 2009, 5, 176–186. [Google Scholar] [CrossRef]
  11. Bednarski, L. Analiza Finansowa w Przedsiębiorstwie; PWE: Warszawa, Poland, 2007; pp. 18–22. [Google Scholar]
  12. Szczęsny, W. Finanse Zarys Wykładu; Difin: Warszawa, Poland, 2010; p. 218. [Google Scholar]
  13. Pomykalska, B.; Pomykalski, P. Analiza Finansowa Przedsiębiorstwa; PWN: Warszawa, Poland, 2017; p. 32. [Google Scholar]
  14. Dang, H.T. Determinants of Liquidity of Listed Enterprises: Evidence from Vietnam. J. Asian Financ. Econ. Bus. 2020, 7, 67–73. [Google Scholar] [CrossRef]
  15. Enqvist, J.; Graham, M.; Nikkinen, J. The impact of working capital management on firm profitability in different business cycles: Evidence from Finland. Res. Int. Bus. Financ. 2014, 32, 36–49. [Google Scholar] [CrossRef]
  16. Hosaka, T. Bankruptcy prediction using imaged financial ratios and convolutional neural networks. Expert Syst. Appl. 2019, 117, 287–299. [Google Scholar] [CrossRef]
  17. Bolek, M.; Wiliński, W. The influence of liquidity on profitability of polish construction sector companies. Financ. Internet Q. 2012, 8, 38–52. [Google Scholar]
  18. Eljelly, A.M.A. Liquidity-profitability trade-off: An empirical investigation in an emerging market. Int. J. Commer. Manag. 2004, 14, 48–61. [Google Scholar] [CrossRef]
  19. Kobika, R. Liquidity management and profitability: A case study analysis of listed manufacturing companies in Sri Lanka. Glob. Sci. J. 2018, 6, 484–494. [Google Scholar]
  20. Ajanthan, A. A nexus between liquidity and profitability: A study of trading companies in Sri Lanka. Eur. J. Bus. Manag. 2014, 5, 221–237. [Google Scholar]
  21. Ding, S.; Guariglia, A.; Knight, J. Investment and financing constraints in China: Does working capital management make a difference? J. Bank. Financ. 2013, 37, 1490–1507. [Google Scholar] [CrossRef]
  22. Lind, L.; Pirttila, T.; Viskari, S.; Schupp, F.; Karri, T. Working capital management in the automotive industry: Financial value chain analysis. J. Purch. Supply Manag. 2012, 18, 92–100. [Google Scholar] [CrossRef]
  23. Deloof, M. Does working capital management affect profitability of Belgian firms? J. Bus. Financ. Account. 2003, 30, 373–587. [Google Scholar] [CrossRef]
  24. Lazaridis, I.; Tryfonidis, D. The relationship between working capital management and profitability of listed companies in the Athens Stock Exchange. J. Financ. Manag. Anal. 2006, 19, 26–35. [Google Scholar]
  25. Gołaś, Z. Impact of working capital management on business profitability: Evidence from the Polish dairy industry. Agric. J. 2020, 66, 278–285. [Google Scholar] [CrossRef]
  26. Czerwińska-Kayzer, D.; Florek, J.; Staniszewski, R.; Kayzer, D. Application of Canonical Variate Analysis to Compare Different Groups of Food Industry Companies in Terms of Financial Liquidity and Profitability. Energies 2021, 14, 4701. [Google Scholar] [CrossRef]
  27. Antczak, J.; Horzela, I.; Nowakowska-Krystman, A. Influence of Financial Liquidity on the Competitiveness of Defence Industry Enterprises. Eur. Res. Stud. J. 2021, XXIV, 257–273. [Google Scholar] [CrossRef]
  28. Aktas, N.; Croci, E.; Petmezas, D. Is working capital management value-enhancing? Evidence from firm performance and investment. J. Corp. Financ. 2015, 30, 98–113. [Google Scholar] [CrossRef]
  29. Zimon, G. Financial liquidity management strategies in Polish energy companies. Int. J. Energy Econ. Policy 2020, 10, 365–368. [Google Scholar] [CrossRef]
  30. Abad, C.; Laffarga, J.; Garcia-Borbolla, A.; Larran, M.; Pinero, J.M.; Garrod, N. An evaluation of the value relevance of consolidated versus unconsolidated accounting information: Evidence from quoted Spanish firms. J. Int. Financ. Manag. Account. 2000, 11, 156–177. [Google Scholar] [CrossRef]
  31. Larran, M.; Rees, W. Private Disclosure in the Spanish capital market: Evidence from financial analysts and investor relations directors. Span. J. Financ. Account. 2003, 115, 116–152. [Google Scholar] [CrossRef]
  32. Niskanen, J.; Kinnunen, J.; Kasanen, E. A note on the information content of parent company versus consolidated earnings in Finland. Eur. Account. Rev. 1998, 7, 31–40. [Google Scholar] [CrossRef]
  33. Muller, V.-O. Value relevance of consolidated versus parent company financial statements: Evidence from the largest three European capital markets. Account. Manag. Inf. Syst. 2011, 10, 326–350. [Google Scholar]
  34. Goncharov, I.; Werner, J.R.; Zimmermann, J. Legislative demands and economic realities: Company and group accounts compared. Int. J. Account. 2009, 44, 334–362. [Google Scholar] [CrossRef]
  35. Harris, T.S.; Lang, M.; Moller, H.P. The Value Relevance of German Accounting Measures: An Empirical Analysis. J. Account. Res. 1994, 32, 187–209. [Google Scholar] [CrossRef]
  36. Choi, F.D.S.; Mueller, G.G. International Accounting; Prentice-Hall: Hoboken, NJ, USA, 1992. [Google Scholar]
  37. Delvaille, P.; Ebbers, G.; Saccon, C. International Financial Reporting Convergence: Evidence from Three Continental European Countries. Account. Eur. 2005, 2, 137–164. [Google Scholar] [CrossRef]
  38. Lamb, M.; Nobes, C.; Roberts, A. International Variations in the Connection between Tax and Financial Reporting. Account. Bus. Res. 1998, 28, 173–188. [Google Scholar] [CrossRef]
  39. Macías, M.; Mui-o, F. Examining dual accounting systems in Europe. Int. J. Account. 2011, 46, 51–78. [Google Scholar] [CrossRef]
  40. Nobes, C. Towards a general model of the reasons for international differences in financial reporting. Abacus 1998, 34, 162–187. [Google Scholar] [CrossRef]
  41. Oliveras, E.; Puig, X. The Changing Relationship between Tax and Financial Reporting in Spain. EBSCOhost. Account. Eur. 2005, 2, 195–207. [Google Scholar] [CrossRef]
  42. Busari, K.; Bagudo, M.M. Comparing the Value Relevance of Selected Accounting Information in Consolidated and Separate Financial Statements: The Case of Nigerian Listed Financial Service Firms. Available online: https://ssrn.com/abstract=3936540 (accessed on 31 July 2021). [CrossRef]
  43. Sotti, F. The value relevance of consolidated and separate financial statements: Are non-controlling interests relevant? Afr. J. Bus. Manag. 2018, 12, 329–337. [Google Scholar]
  44. Shamki, D.; Abdulrahman, A. Net Income, Book Value and Cash Flows: The Value Relevance in Jordanian Economic Sectors. Int. J. Bus. Soc. Res. 2011, 1, 123–135. [Google Scholar]
  45. Carini, C.; Teodori, C. Making Financial Sustainability Measurement More Relevant: An Analysis of Consolidated Financial Statements. In Financial Sustainability of Public Sector Entities; Caruana, J., Brusca, I., Caperchione, E., Cohen, S., Manes Rossi, F., Eds.; Public Sector Financial Management; Palgrave Macmillan: Cham, Switzerland, 2019. [Google Scholar] [CrossRef]
  46. Kargin, S. The impact of IFRS on the value relevance of accounting information: Evidence from Turkish firms. Int. J. Econ. Financ. 2013, 5, 71–80. [Google Scholar] [CrossRef]
  47. Okafor, O.N.; Anderson, M.; Warsame, H. IFRS and value relevance; Evidence based on Canadian adoption. Int. J. Manag. Financ. 2016, 12, 136–160. [Google Scholar]
  48. Zulu, M.; Dde Klerk, M.; Oberholster, J.G.I. A comparison of the value relevance of interim and annual financial statements. S. Afr. J. Econ. Manag. Sci. 2017, 20, 1–11. [Google Scholar] [CrossRef]
  49. Chen, Z.; Lu, A. A market-based funding liquidity measure. Rev. Asset Pricing Stud. 2019, 9, 356–393. [Google Scholar] [CrossRef]
  50. Lagos, R.; Rocheteau, G.; Wright, R. Liquidity: A new monetarist perspective. J. Econ. Lit. 2017, 55, 371–440. [Google Scholar] [CrossRef]
  51. Fong, K.Y.; Holden, C.W.; Trzcinka, C.A. What are the best liquidity proxies for global research? Rev. Financ. 2017, 21, 1355–1401. [Google Scholar] [CrossRef]
  52. Castiglionesi, F.; Feriozzi, F.; Lorenzoni, G. Financial Integration and Liquidity Crises (No. w23359). Natl. Bur. Econ. Res. 2019, 65, 955–975. [Google Scholar]
  53. Schwarz, K. Mind the Gap: Disentangling Credit and Liquidity in Risk Spreads. 2017. Available online: https://repository.upenn.edu/fnce_papers/19 (accessed on 20 April 2022).
  54. Olagunju, A.; David, A.O.; Samuel, O.O. Liquidity Management and Commercial Banks’ Profitability in Nigeria. Res. J. Financ. Account. 2012, 2, 24–38. [Google Scholar]
  55. Sierpińska, M.; Jachna, T. Ocena Przedsiębiorstwa Według Standardów Światowych; PWN: Warszawa, Poland, 2006; p. 79. [Google Scholar]
  56. Guerrieri, V.; Lorenzoni, G. Credit crises, precautionary savings, and the liquidity trap. Q. J. Econ. 2017, 132, 1427–1467. [Google Scholar] [CrossRef]
  57. Bolek, M.; Wolski, R. Profitability or liquidity: Influencing the market value-The case of Poland. Int. J. Econ. Financ. 2012, 4, 182. [Google Scholar] [CrossRef]
  58. Boudoukh, J.; Whitelaw, R.F. Liquidity as a choice variable: A lesson from the Japanese government bond market. Rev. Financ. Stud. 1993, 6, 265–292. [Google Scholar] [CrossRef]
  59. Chang, B. Adverse selection and liquidity distortion. Rev. Econ. Stud. 2017, 85, 275–306. [Google Scholar] [CrossRef]
  60. Białas, K. Rola Dynamicznych Wskaźników Płynności Finansowej w Zarządzaniu Przedsiębiorstwem, Finanse i Prawo Finansowe; Uniwersytet Łódzki: Łódź, Poland, 2017; pp. 9–10. [Google Scholar]
  61. Ustawa z dnia 10 Kwietnia 1997 r.—Prawo Energetyczne (Dz. U. 2020 r. poz. 833 z późn. zm.). Available online: https://isap.sejm.gov.pl/isap.nsf/download.xsp/WDU19970540348/U/D19970348Lj.pdf (accessed on 15 April 2022).
  62. Available online: https://raportzintegrowany2017.gkpge.pl/zasady-zarzadzania/struktura-wlascicielska-i-operacyjna.html (accessed on 25 April 2022).
  63. Available online: https://grupa.energa.pl/grupa-energa/historia (accessed on 25 April 2022).
  64. Available online: https://www.tauron.pl/tauron/bip/bip-historiastannadzień (accessed on 25 April 2022).
  65. Available online: https://www.tauron.pl/tauron/relacje-inwestorskie/raporty-biezace/raport-biezacy?id=8074896 (accessed on 11 May 2022).
  66. Available online: https://www.energetyka24.com/grupa-enea-zanotowala-227-mld-zl-straty-w-roku-2020 (accessed on 11 May 2022).
  67. Available online: https://strefainwestorow.pl/wiadomosci/20200528/energa-miala-w-2019-r-204-mld-zl-ebitda-wobec-188-mld-zl-rok-wczesniej-opis (accessed on 11 May 2022).
  68. Available online: https://www.energetyka24.com/energa-podsumowuje-wyniki-za-2020-strata-mniejsza-niz-w-2019 (accessed on 11 May 2022).
  69. Available online: https://www.wnp.pl/energetyka/grupa-pge-ze-strata-netto-3-9-mld-zl-za-2019-rok,383740.html (accessed on 11 May 2022).
Table 1. Indicators for assessing the financial liquidity of companies (name and structure).
Table 1. Indicators for assessing the financial liquidity of companies (name and structure).
IndicatorCounting Method
Static liquidity ratios
Current liquidity ratio (safe index value: 1.2–2.0)current assets/short-term liabilities
Increased liquidity ratio (safe indicator value: 0.8–1.5)current assets–inventories/short-term liabilities
Cash liquidity ratio (safe indicator value: 0.1–0.2)cash and cash equivalents/short-term liabilities
Dynamic liquidity ratios—cash adequacy ratios (desired values—the higher the better)
Operating cash adequacy ratio for total debt repaymentcash from operating activities/total liabilities
Operating cash adequacy ratio for repayment of long-term liabilitiescash from operating activities/total long-term liabilities
Operating cash adequacy ratio for repayment of current liabilitiescash from operating activities/current liabilities (short-term)
Dynamic liquidity ratios—cash efficiency ratios (desired values—positive, the higher the better)
Cash efficiency ratio of salescash from operating activities/operating sales
Cash efficiency ratio of assetscash from operating activities/average assets
Cash flow rate ratiocash from operating activities/operating profit
Source: own work based on [27].
Table 2. Characterization of operational sizes of researched entities in 2021.
Table 2. Characterization of operational sizes of researched entities in 2021.
Comparison ParameterPGEEnergaEneaTauron
Year of group formation2007200620022006
Dominant unit debut on the GPW2009201320082010
Installed capacity17.78 GWe1.39 GWe6.3 GWe4.5 GWe
Installed renewable energy capacity2 331 MWe1 439 GW443 MWe533 MWe
Retail energy and fuel sales42.91 TWh18.6 TWh24.5 TWh33.4 TWh
Energy production57.4 TWh4.1 TWh26.4 TWh14.3 TWh
Number of energy customers5.3 mln3.2 mln2.7 mln5.7 mln
Share in the coal energy market91% *-23%29%
Length of power lines297 thou. km193 thou. km121 thou. km-
* Refers to the share in the brown coal market. Source: reports on the activity of the examined capital groups for the year 2021 (18 February 2023).
Table 3. Liquidity ratios of the examined entities for the years 2018–2021.
Table 3. Liquidity ratios of the examined entities for the years 2018–2021.
EntityIndicator2018201920202021
IFRCFRIFRCFRIFRCFRIFRCFR
ENEACRF1.42.21.41.41.21.11.1
QR1.81.12.11.01.30.71.01.0
CSHR0.70.10.90.40.20.30.20.4
ENERGACR2.61.70.80.90.80.70.60.6
QR2.61.70.80.80.80.60.60.6
CSHR1.21.00.30.30.00.10.00.1
PGECR0.90.72.81.12.51.02.31.0
QR0.90.52.80.62.50.72.30.6
CSHR1.20.10.30.10.00.30.00.1
TAURONCR0.40.60.70.90.90.90.50.6
QR0.30.50.70.60.80.80.50.6
CSHR0.10.10.20.20.10.10.00.1
Source: own analysis based on individual and consolidated financial statements of the examined capital groups from 2019 and 2021.
Table 4. The repayment capacity indicator of the surveyed entities for the years 2018–2021.
Table 4. The repayment capacity indicator of the surveyed entities for the years 2018–2021.
EntityRepayment Capacity Indicator2018201920202021
IFRCFRIFRCFRIFRCFRIFRCFR
ENEAoverall0.000.160.000.120.000.190.000.28
long-term0.000.240.000.200.000.320.000.70
short term0.000.510.000.330.000.470.000.47
ENERGAoverall0.000.170.000.110.000.170.000.32
long-term0.000.220.000.180.000.270.000.55
short-term0.000.660.000.260.000.460.000.78
PGEoverall0.040.180.000.200.140.270.060.18
long-term0.100.330.000.300.230.440.120.39
short-term0.080.410.000.580.340.680.110.34
TAURONoverall0.000.120.000.090.000.180.050.21
short-term0.000.200.000.140.000.260.090.37
long-term0.000.310.000.260.000.550.100.50
Source: own elaboration based on individual and consolidated financial statements of the researched capital groups from 2019 and 2021.
Table 5. Cash performance ratio indicator of the researched entities for the years 2018–2021.
Table 5. Cash performance ratio indicator of the researched entities for the years 2018–2021.
EntityCash Performance Indicator2018201920202021
IFRCFRIFRCFRIFRCFRIFRCFR
ENEAsale−0.070.19−0.010.13−0.070.17−0.030.26
assets−0.010.080.000.07−0.020.11−0.010.16
EBIT profitn/d2.35n/d1.16n/d−1.85n/d2.65
ENERGAsale−0.340.18−0.710.11−0.200.15−0.590.26
assets0.000.090.000.060.000.100.000.17
EBIT profitn/d1.58n/d2.73n/d2.82n/d2.86
PGEsale0.050.20−0.020.180.070.220.030.14
assets0.010.07−0.010.090.040.130.020.08
EBIT profit1.102.06−0.42−1.632.867.281.591.46
TAURONsale−0.010.12−0.050.10−0.020.200.050.20
assets0.000.06−0.020.05−0.010.100.030.12
EBIT profit−5.432.81−4.936.89n/d−2.6320.135.46
Source: own analysis based on individual and consolidated financial statements of the examined capital groups from 2019 and 2021.
Table 6. Revenue from sales and net profit of the surveyed entities in the years 2018–2021 (in million EUR *).
Table 6. Revenue from sales and net profit of the surveyed entities in the years 2018–2021 (in million EUR *).
EntityFinancial
Size
2018201920202021
IFRCFRIFRCFRIFRCFRIFRCFR
ENEARevenue10002696121234901317387115764513
EBIT−24221−31395−41−363−63440
net results15515360115−723−47598380
ENERGArevenue192199182442192659142913
EBIT−15250−1898−23141−17272
net results105158−80−213−42−9445200
PGErevenue243655203223800658609737764211,219
EBIT108528166−8881513001281090
net results−43321−268−83637131369839
TAURONrevenue18343856227341612413433338765450
EBIT51682163−194−32710195
net results−36944−99−2486−692−4625582
* Data recalculated at the exchange rate of EUR 1 = PLN 4.7. Source: own elaboration based on unit and consolidated financial statements of the surveyed capital groups from 2019 and 2021.
Table 7. Operating income of the researched companies in the years 2018–2021 (in million EUR *).
Table 7. Operating income of the researched companies in the years 2018–2021 (in million EUR *).
Cash Flows from
Operating Activities
2018201920202021
IFRCFRIFRCFRIFRCFRIFRCFR
ENEA−66518−8456−87672−511167
ENERGA−6509−13414−4551−8779
PGE1191086−70145143321822031586
TAURON−27473−106433−538601931064
* Data converted at the exchange rate of EUR 1 = PLN 4.7. Source: own calculations based on individual and consolidated financial statements of examined capital groups from 2019 and 2021.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Borowiec, L.; Kacprzak, M.; Król, A. Information Value of Individual and Consolidated Financial Statements for Indicative Liquidity Assessment of Polish Energy Groups in 2018–2021. Energies 2023, 16, 3670. https://doi.org/10.3390/en16093670

AMA Style

Borowiec L, Kacprzak M, Król A. Information Value of Individual and Consolidated Financial Statements for Indicative Liquidity Assessment of Polish Energy Groups in 2018–2021. Energies. 2023; 16(9):3670. https://doi.org/10.3390/en16093670

Chicago/Turabian Style

Borowiec, Leszek, Marzena Kacprzak, and Agnieszka Król. 2023. "Information Value of Individual and Consolidated Financial Statements for Indicative Liquidity Assessment of Polish Energy Groups in 2018–2021" Energies 16, no. 9: 3670. https://doi.org/10.3390/en16093670

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop