Value Relevance of Government Grants and Subsidies in Brazil

ABSTRACT

This study investigates whether Government Grants and Subsidies (GGS) hold incremental informational content relevant to the pricing of equity securities in the Brazilian capital market. This study is the first to examine whether GGS nature and its financial sum provide informational value relevant for the Brazilian capital market. Multiple linear regressions were estimated by using Ordinary Least Squares (OLS). The Ohlson model (1995) was used in empirical tests. The analysis is composed of 1.971 observations in the period between 2010 and 2020. Data were obtained from Explanatory Notes and Economatica®. Evidence demonstrates that it is not possible to reject the hypothesis that GGS assumes the role of “other information” in the evaluation process, affecting investor perception. Furthermore, it was observed that the GGS source and financial value denote informational value in the Brazilian market. This paper contributes to the literature by suggesting that executives’ proactiveness in obtaining GGS could have, in addition to effects on firms’ ownership structure, impacts on investors’ perception. Therefore, market players should monitor this information type and include it in the estimation models of future cash flows.

KEYWORDS:
Government grants; Political connections; Value relevance

RESUMO

Este estudo investiga se Subvenções e Assistências Governamentais (SAG) detêm conteúdo informacional incremental relevante para precificação de títulos acionários no mercado de capitais brasileiro. Este estudo é o primeiro a investigar se a natureza das SAG e seu montante financeiro dispõem de valor informativo relevante no mercado de capitais brasileiro. Foram estimadas regressões múltiplas lineares por Ordinary Least Squares (OLS). O modelo de Ohlson (1995) foi usado nos testes empíricos. A análise compõe 1.971 observações no período entre 2010 e 2020. Os dados foram obtidos nas Notas Explicativas e na Economatica®. As evidências demonstram que não é possível rejeitar hipótese de que as SAG assumem papel de “outras informações” no processo de avaliação, afetando a percepção dos investidores. Ademais, observou-se que a origem e o valor financeiro das SAG denotam valor informativo nesse mercado. Esta pesquisa contribui com a literatura ao sugerir que a proatividade dos executivos na obtenção de SAG pode ter, além de reflexos na estrutura patrimonial das firmas, impactos na percepção dos investidores. Logo, os players do mercado devem monitorar esse tipo de informação e incluí-lo nos modelos de estimação de fluxos futuros de caixa.

PALAVRAS-CHAVE:
Subsídios governamentais; Conexões políticas; Value-relevance

1 INTRODUCTION

This study investigates whether Governmental Grants and Subsidies (GGS) bear incremental informational content relevant to the pricing of equity securities in the Brazilian Capital Market. In the light of value relevance literature (Ball & Brown, 1968; Barth et al., 2001; Beaver, 2002; Ohlson, 1995), it is considered that value relevant information is affected significantly by a firm’s value, producing incremental effect on the production of equity securities in the capital market, signaling strong/weak performance in companies’ economic future. The main goal of this study is to understand how the market and investors price information which designates the state and the government participation in the company’s economy given that this action may tackle social goals, long-run investments, warranties, and political strategies.

GGS encompasses public government policies aimed at providing economic benefits to a firm or a group of firms under specific criteria. Therefore, they are government intervention instruments targeted at compensating for market imperfections, exploring economies of scale, and pursuing social policy goals (Schwartz & Clements, 1999). By rule, GGS acts, among other things, through direct payment to companies, tax reduction or loans at subsidized rates.

Three perspectives of GGS information are examined: (i) reception; (ii) source, and (iii) amount. That is because investors do not only react to information alone , but also to its announcement and its effects on companies (Beaver, 1968). This idea corresponds to Ohlson’s theory (1995), when proposing the existence of other relevant information which affects prices. Furthermore, it is admitted that profit is a set of heterogeneous components. (Ball & Brown, 1968).

In this study, data from 296 Brazilian companies listed on Brazil`s B3 S.A stock exchange in the period from 2010-2020 were analyzed, totaling, by restrictions of sampling, 1971 observations. The study used Ohlson’s (1995) residual income valuation (RIV). The methodological approach makes use of Ordinary Least Squares (OLS) multiple regression analysis. Results were consistent with expectations and suggest that GGS reception is value relevant for the decision-making process in investments. It was noted that the incremental effect produced by pricing information is positive, showing that the market is prone to prospect advantages and/or economic benefits between companies receiving government grants when compared to non-beneficiary firms. Additionally, an analysis was carried out to indicate the resource origins (federal, state and/or municipal) and the amount of GGS which reflects different perceptions by market participants on the capacity of cash flow generation.

In Brazil, the investigated economic context, the count of GGS and their disclosure are guided by the CPC 07 R1 (CPC, 2010). According to this normative device, GGSs, as extension of tax policy, came to be recognized as income in the Income Statement (DRE) in the period in which they occur, given that the previously established criteria are met. The alteration enabled distinguishing the firm’s operational results from those coming from GGSs, eliminating the distortion between companies’ performance. Indeed, Santos (2012) found out that the impact of GGS on Brazilian firms’ profit was on average 22.50 % between 2007 and 2008.

It is clear, thus, that GGS provokes an impact on companies’ results and that the GGS representative receipt can temporarily inflatethe subsidized firm’s performance and convert damage into profits rapidly (Lee et al., 2014). In spite of this, it is worth noting that this relationship is not necessarily consequent once it is subjected to the appropriate allocation of these resources (Einsweiller et al., 2020).

In addition to that, there is another question related to companies’ performance originating from GGS being affected by subsidy suspension (Yang et al., 2022). With that, these enterprises can become dependent on these resources. Therefore, the attribution of GGS benefits might signal economic and competitive (dis)advantage by the market. This scenario suggests, according to these arguments, that information upon GGS receipt can alter investors’ expectations around future generation of cash flow, making it reflect on stock prices.

It was expected that, in this study, GGS would prove relevant since they signal government support and protection as well as direct benefits capable of impacting companies’ cash flow. GGSs were projected as information able to generate differences in terms of evaluation between firms in the Brazilian capital market. This information, contained in the price of share securities, has a positive effect on the company’s evaluation, translating it into the expectations of participants in the market investigated.

Highlighting the contributions of this study, for companies, results suggest that the Brazilian capital market acknowledges information on GGS as capable of altering the investors’ expectations of future gains. Hence, managers and accountants should consider the GGS as a likely driver of the shareholder’s wealth maximization. From the academic perspective, it is shown that the value relevance model is effective at ratifying the consequences of GGS in the value of Brazilian companies.

Another important research contribution refers to the accounting regulatory bodies, as it was evidenced that GGS represent informational input which is important to the decisions of investment evaluation in the Brazilian market of capitals and, because of that, the disclosure of GGS must be complete and efficient. It is worth mentioning that, in 2010, the regulatory agency issued a review to the technical statement CPC 07 (CPC, 2008), reducing in more than half the number of disclosable items. Even so, literature shows that companies reached a low level of GGS disclosure (Loureiro et al., 2011; Souza et al., 2018).

It is underlined that this research helps to fill a considerable blank in the accounting literature considering that only one piece of work on this topic, using this approach, was ever found, belonging to Lee et al. (2014). The study investigated the GGS effect on the market value of Chinese firms. Until then, there were not identified any other works which exploited the value relevance of GGS in Brazil, even though some research has examined GGS economic effect on the creation of value (Einsweiller et al., 2020; Rezende et al., 2018). Thus, there is still little known about GGS value relevance, which reinforces the importance of this study

However, this research is not a mere replication, which is different from the study by Lee et al. (2014) in some aspects. The aforementioned study analyzed the Chinese economy, guided by the countries’ aggressive state participation in companies property. Despite the existence of public companies and government participation in many others, Brazil does not have such interventionist capitalism. This way, it is possible to establish comparisons between results in two countries with emergent and distinct models. Another point that should be highlighted is that the analysis in this study explores the diverse governmental origins of GGS excluding their effect on equity and profit, which was not observed by Lee et al. (2014).

Therefore, it is necessary to establish that these differences have an impact on important practical results and consequences that deserve to be explored in the Brazilian market and in other markets. Evidence suggests that in emerging markets, mentioning China and Brazil, GGS magnitudes reveal that this kind of one-off relationship between companies and state and its governments can be exploited as one economic advantage with positive reflections in future cash flows. However, among the reasons from which this research emphasizes and advances towards what is present in the literature, the evidence that involves a demonstration that market players already price the mere existence of this relationship is highlighted. In countries like Brazil and China, this study and the work by Lee et al. (2014) show that economic costs relating to receiving GGSs do not surpass benefits. In fact, values received as GGS should work as a signal of expectations already priced by the market as a result of GGS receipt and their origins. Although subtle, this difference allows investors to make profits by monitoring this information in the market and in the reports presented by companies.

2 LITERATURE REVIEW AND HYPOTHESIS

2.1 Value relevance

Accounting has the goal of providing useful information for economic decision making, and for the investors’ and lenders’ evaluations, as exposed by the Technical Statement CPC 00 R2 - Conceptual Framework for Financial Report, approved in 2019 (CPC, 2019). This end is met when accounting figures indicate trustworthy, fair representation of the company’s financial position, performance, and cash flow. To be useful, accounting information must be relevant in terms of value and this means making a difference in the decision-making process of investors, reflected in the price/return of shares (Barth et al., 2001; Beaver, 2002).

According to Lo (2010), it is the potential change of expectations which determines, at first, whether an item is relevant, regardless of their monetary value. Therefore, if an item can be anticipated, its report does only confirm expectations, not alter them. In turn, value relevance is one of the qualitative characteristics of accounting data. Beaver (1968) claims that relevant financial data induce changes in the perception of the investors’ evaluation with respect to probability of future returns (or prices), thus, modifying the equilibrium value of the current market price. Barth et al. (2023) argue that accounting profit has lost relevance over the years due to the fact that other information not completely captured by conservative accounting generates differences in terms of evaluation.

Intangible resources, growth opportunities, and alternative metrics used to measure companies’ performance are amongst some aspects which can help explain firms’ value, besides accounting profit (Barth et al., 2023). In this sense, an expressive part of the literature has approached the inputs-to-equity-valuation. Thus, it is sought to provide information on which inputs are determining and, therefore, useful in the models of evaluation and for the pricing of assets by investors. Studies in this nature are framed as of incremental association once they seek to identify that “other types of information” disclose relevant information in addition to accounting figures (Holthausen & Watts, 2001).

Francis and Schipper (1999) present empirical evidence of relevance reduction of accounting figures through time. The downfall could be explained in front of the necessity to consider “other pieces of information” which would justify changes in share prices. Ohlson (1995) developed the Residual Income Valuation (RIV) model defending this premise, since the accounting numbers might not encompass the whole informational content absorbed by the market due to conservatism, characteristics of its own, accounting policies or informational restrictions. His model allows testing empirically whether such “other information”, originating from relevant events, can aggregate future residual profits and, by doing so, affect current firms’ value (Ohlson, 1995). Despite its importance, the body of research done on the Brazilian stock market can tend to give more attention to investigating the role of other information as elements that complement basic accounting figures and improve firms’ evaluation (Coelho & Aguiar, 2008; Coelho et al., 2011).

Ohlson’s model (1995) proposes that the firm value is a function of equity and abnormal earnings-basic numbers with a basis in accounting. Nevertheless, because of imperfections and market inefficiencies, such aggregates are not sufficient to explain the total variation in the firm’s value. What is lacking might be explained by new future cash flow captured by “other relevant information”; however, not necessarily or not yet completely incorporated by accounting. In this research, GGS value relevance is explored, an uninvestigated topic through this viewpoint in literature.

2.2 Hypothesis development

In this study, GGSs are defined as government actions aimed at providing companies, or groups of companies, economic benefits which fulfill previously established criteria. Evidence suggests the existence of GGS-based benefits in regards to performance improvement, value unlock and cash generation boost (Almeida & Pereira, 2019; Lee et al., 2014; Rezende et al., 2018). Additionally, GGS can supply increments of financial and operational efficiency (Hu et al., 2019), something which would accentuate the gap between companies which do and which do not receive GGSs.

It is argued, in this study, that the receipt of GGS produces incremental informational content capable of changing investors’ perception about the subsidized firm’s value. This argument is sustained mainly due to two theoretical constructions. In the first place, GGSs receipt might signal to the capital market, at first an advantage derived from political connections. This sign of politically associated connection would be relevant because of the stock price synchronicity effect. Hou and Yang (2021) highlight that stock price synchronicity -the magnitude of information about the company reflected on its value -is larger in companies with explicit signs of support to politicians and political parties.

This evidence may be associated with benefits from political connections, which include preference in receiving GGS, even for companies with low performance and financial difficulties (Chaney et al., 2011; Tao et al., 2017). In addition,, companies are favored through a softer application of law (Blau et al., 2013; Correia, 2014), reduction of the probability of audit review (Batta et al., 2014) and a higher chance of the obtention of public contracts (Goldman et al., 2013). Indirectly, enterprises might still benefit from reduction in the cost of finance training (Claessens et al., 2008; Leuz & Oberholzer-Gee, 2006) and with reduction of effective tax rate (Adhikari et al., 2006).

GGSs obtained preferably through political relationships may suggest a market directed management. Hillman (2005) argues that companies benefit from their connections for being capable of understanding the process of public policies, gaining direct access to politicians, bureaucrats, and decision makers, influencing political decisions which legitimize and confer reputation and status on firms. Perception of benefits may still be more relevant in emerging markets, with higher levels of corruption and lower levels of transparency (Boubakri et al., 2012; Faccio, 2006).

Due to that fact, this study considers Brazil as an opportune economic context for driving an investigation on GGS value relevance once, in spite of being an emerging economy, it shows its capital market in a maturation state. To corroborate this, Einsweiller et al. (2020) demonstrate evidence that politically connected companies in Brazil have more access to tax benefits as well as government subsidies, which contribute in the generation of added value. These results point to the market that subsidized firms have good perspectives and lower uncertainty with respect to generation of future cash flow since they count on support and protection from the government (Lee et al., 2014).

The GGSs represent an outstanding instrument of government actions in Brazil. In 2022, between January and November, the expenditure item for subsidies and grants (4.3.15) amounted to R$14,128.5 million. In 2023, this amount escalated to R$ 17.297.4 million, a nominal increase of 22,4 %. Data can be found on National Treasury Results Bulletin, volume 29, number 11, published on December 27, 2023. In November, the month with the most recent disclosed data, spendings on grants and subsidies was R$ 357.4 million in 2022 against R$ 975.10 million in 2023, a nominal addition of 172.8 %. This figure corresponds to 3.11 % of other compulsory union expenditures. This item includes expenses on allowances and unemployment insurance, the Fund for the Maintenance and Development of Basic Education and Valorization of Education Professionals (FUNDEB), and payments of court judgments and writs of payment. These values, therefore, represent the size of participation of these incentives for economies of companies, including only the federal context.

In this sense, the market monitors and assesses the large flow of funds, thus contributing to the pricing and adjustment of values in the future. Not every company will have access to the GGS, which is an aspect that differentiates the value of firms. It should also be noted that companies with access to the GGS must comply with the requirements and obligations for the concession of these grants. The data from the National Treasury Results Bulletin (2023) helps us understand that investors would be motivated to monitor the performance of companies in relation to whether or not they receive the GGS. Considering the GGS as a political cost or benefit, it is interesting for the market to monitor, by means of accounting information, the effect of these grants on future cash flow. There is also an agency relationship between government and companies, as the latter need to prove that the objectives of the principal ( the state) are being met in order to benefit from the SAG (Costa et al., 2022).

Despite these aspects concerning political connections, there is another possibility. Receiving GGSs can convey a message to investors about the heavy burden of politics instead of the support or funding (Yang et al., 2022). In this context, the GGSs can be deemed as a sign of a recessionary guarantee endorsed by the government (Yan & Li, 2018). Subsidized companies can count on GGSs and gradually lose their competence in the market over the long term (Liu et al., 2019). Therefore, the GGS-originated benefits may even ease companies’ financial constraints in the short run but also lose the capacity to generate value over long-term intervals.

In the second place, the receipt of GGSs has an impact on the company’s results and can therefore be deterministic of the share price. GGS functions as an instrument of economic intervention used by governments to compensate for market imperfections, exploring economies of scale and seeking objectives of social politics (Schwartz & Clements, 1999). According to the legal framework in force in Brazil, GGSs must be recognized as income in the period in which they occur, provided that all the obligations required for the benefit to be enjoyed are met. They are usually presented in the form of reducing tax rates or granting loans at subsidized rates. Before that, Lee et al. (2014) explain that a large volume of GGS can temporarily increase the subsidized company’s performance and even convert damage into profit in a short period (Lee et al., 2014). It stands out, however, that this financial performance may be unsustainable when these incentives are discontinued (Yang et al., 2022).

The GGSs must be reversed into important financial incentives which, if correctly applied, can increase the company’s wealth generation (Einsweiller et al., 2020). This way, when the government increases public spendings, an effect called crowding out can occur -GGS helping with the expansion of the economy. Nevertheless, such an effect might be neutralized with the elevation of the tax rate and the reduction of private investments. Evidence suggests subsidized companies with higher levels of investments yet a lower efficiency of allocated resources (Hu et al., 2019). As a consequence, there might not be any significant performance improvement in the long term due to the management of GGS originated funding (Chen et al., 2008).

The literature does not demonstrate consensus as to the economic effects produced by the GGSs. Research suggests that GGS can improve a company’s financial performance in addition to increasing its value. (Dvouletý et al., 2021; Lee et al., 2014). Another favorable point is reducing the restrictions of capital imposed on companies (Claro, 2006). However, another line of investigation points out that GGS results in super production or even loss of efficiency (Hu et al., 2019), reducing levels of effectiveness of investments in innovation (Hong et al., 2016) and favoring companies with greater competitive advantage (Neary, 1994).

The studies measuring GGS effects on the Brazilian stock market are still scarce. In Brazil, the literature shows that the GGSs are capable of creating value for both shareholders and companies (Einsweiller et al., 2020; Rezende et al., 2018). On the other hand, a major part of research concentrates on the level of information disclosure on GGS (Loureiro et al., 2011; Souza et al., 2018). This study is innovative by exploring the effect of GGS on the market value of Brazilian companies.

At the time this study was carried out, only Lee et al. (2014) explored the information relevance of GGS, focusing on the Chinese stock market between 2002 and 2008. Based on Ohlson’s (1999) model of relevance, the results found suggest that not only are GGSs value relevant but that they also have an incremental effect on the abnormal earnings and the net equity of Chinese companies. The authors highlight that this finding relates to the fact that analysts (more sophisticated users of accounting information) would consider GGS as information aggregates relevant to forecasting profits, determining target prices of assets, and recommending shares.

This finding shows that the receipt of GGS by firms active in emerging markets, such as Brazil and China, deserve attention. Investors and other parties interested in accounting information who are able to signal advantages and future economic costs would evaluate GGS and this could be reflected as an increase or a discount in the firm’s price. The case exposed by Lee et al. (2014) expresses that GGS would be evaluated by the incremental power of the subsidized company’s cash flow and/or reduction of the cost of capital, resulting in a lower discount rate for future cash flows and increment of the company’s value. It is worth noting that China is an economy with strong action and intervention by its government.

It is highlighted that the effect provoked by GGS on companies’ results demand attention. In Brazil, in the transition stage to the International Financial Reporting Standards (IFRS), Santos (2012) identified that GGS reflex (then registered directly as paid-in capital) in companies’ profit was 24 % (2007) and 21 % (2008). The change in GGS accounting treatment eliminated an eventual distortion in the entity’s performance. Companies which benefit from GGS registered expenses on tax as though they were effectively paid, and, as a result, the credit goes directly to equity.

In spite of acknowledging that political cost (Yang et al., 2022) can be incorporated to the company’s value, this research aims to attribute to GGS an incremental positive effect and significant value to companies, following part of the literature (Claro, 2006; Dvouletý et al., 2021; Einsweiller et al., 2020; Lee et al., 2014). It is assumed that the investor would consider GGS as information signaling more economic advantages originating from political connections than costs, and this would lead to improvement in future cash flows. If evidence allowing hypothesis rejection is gathered, this would mean that the accounting figures, per se, do not explain all the variability in companies’ price. This way, the existence of other information, such as GGS, would add up and change evaluation.

Under the light of the previous discussion, it is considered that GGS assumes an information role which has the capacity to alter economic expectations of the participants in the Brazilian capital market and influence companies’ stock prices. The following hypothesis is sustained:

H_1: GGS are positively value relevant in the perception of investors in the evaluation of companies in the Brazilian capital market

The proposition of the H 1 hypothesis presents consistency with the literature, grounded in the idea that the value relevance approach provides a structure which enables us to understand different evaluation paths from the past that, in turn, contain alteration in the profits (Lo & Lys, 2000). Ohlson’s theory (1995) and contributions by Feltham and Ohlson (1995) are amongst the most relevant investigations on the market of capitals once they have demonstrated that there is a strong relationship between accounting numbers and enterprise value. GGS can assume the role of other information, according to theory, in as much as this accounting recognition promotes change in the company’s earnings in future time spans and periods in force.

Feltham and Ohlson (1995) seek to demonstrate this perspective by suggesting disaggregating the results into financial and operational components (Bernard, 1995). The breakdown of result items and net worth through the value relevant approach is common in the literature (Beisland, 2014; Burke & Wieland, 2017; Franzen & Radhakrishnan, 2009; Han & Manry, 2004; Macedo et al., 2011; Oliveira et al., 2010; Santos et al., 2024). Specifically, Beisland (2014) did not observe informational relevance of resulting financial items, onlyof operational.

3 METHODOLOGICAL PROCEDURES

3.1 Population and sample

The population in this study encompasses all Brazilian companies which stocks traded on the Brazilian Stock Exchange (Brasil, Bolsa, Balcão - B3) in the period between 2010 and 2020. To make the sample, companies with a canceled status (or inactive register) were disregarded. It is important to acknowledge that excluding companies for this reason can introduce a survival bias in the analysis because the companies that stopped trading on B3 during the study period were not disregarded. Thus, the study conclusions must be interpreted considering this limitation.

Furthermore, companies with missing data which were necessary to the analysis were excluded alongside those with a negative net equity. The application of these filters consolidated the samples of 296 examined companies and a total of 1.971 observations. The selection and composition process of the sample is presented in Table 1. Given the characteristics of the collection process, the data is an 11-year longitudinal unbalanced panel study because these companies did not have data throughout the period covered by the study.

Table 1
Sampling process and sample distribution

Panel A - Sample composition and selection procedures
Procedure description	Companies	Observations
Beginning population between 2010 and 2020	855	9.405
(-) companies with canceled status on B3	(450)	(4.950)
(-) companies with missing data and negative net equity	(109)	(2.484)
= Final sample	296	1.971
Panel B - Sample distribution by GGS
Receipt (RGGS)	Observations	Percentage
Did not receive GGS	1.010	51,24 %
Received GGS	961	48,76 %
Source: Federal (FGGS)	623	64,83 %
Source: State (EGGS)	142	14,78 %
Source: Municipal (MGGS)	0	0,0 %
Source: Federal and State (FEGGS)	182	18,94 %
Source: State and Municipal (EMGGS)	1	0,10 %
Source: Federal, State and Municipal (FEMGGS)	13	1,35 %
Amount (MGGS)	Observations	Percentage
Did not inform received amount	1.046	56,3 %
Informed the received amount	925	43,7 %

• Source: Elaborated by the authors.

The companies chosen had their Explanatory Notes (EN) examined, with the goal of identifying the critical information analyzed. It was verified that 48.76 % of the sample (961 observations) pointed to the receipt of GGS in the period. However, of these, there are firms which did not inform the received value in the EN (3.75 %). A representative part of the GGSs comes from federal resources. In an isolated way, or alongside the state resources, they amount to 83.77 % of the observations which informed that they received GGS.

Data referring to GGS was collected manually after the reading of the Explanatory Notes, on which all the information integrating the company’s Financial Statements are reported. This search was carried out in 1.971 Explanatory Notes throughout the period between 2010 and 2020, starting on November 8, 2021 and ending on June 19, 2022. Three systematic steps were followed to minimize the margin of error in the GGS data collection, as shown in Table 2.

Table 2
Systematic data collection on GGS in the Explanatory Notes

Step 1: In the first place, the existence of a mention or a statement on the receipt of GGS by the company was certified. In a positive scenario, 1 (one) was attributed; on the contrary, 0 (zero). This way, the first variable of the study is a dummy, designated RSAG. To identify it, keywords were sought, which included “subsides”, “benefits”, “grants”, “assistance”, “tax incentives”, “donations”, “awards”, and “CPC 07”. These terminologies were highlighted in the Brazilian studies (Loureiro et al., 2011; Souza et al., 2018).

Step 2: Afterwards, in companies which informed receiving GGS (RSAG = 1), the origin of the resources in the public sphere was explored. It was identified that resources received by these companies originated from the federal government, be it in an isolated or cumulative way. In this sense, this variable also has a dummy attribute to the extent that it conferred 1 (one) to the origin of the received GGS (F, E, M) and, in opposite cases 0 (zero).

Step 3: In the third place, a structured reading of documents was resorted to examine the content of the information on GGS presented by companies. It is noteworthy that even though these bits of information are expected on the CPC 07 (R1) (2010), they do not follow any disclosure patterns by the firms and, consequently, demand considerable effort for their grant. The content analysis allowed us to identify the types of subsidies received by the companies and their respective amounts.

• Source: Elaborated by the authors.

Regarding the purpose of this research, only monetary information was collected, which - disposed in different measurement units (billion, million, thousands and units) - were standardized to billions. The collection of the GGS amount, in relation to its nature, was carried out by at least two researchers and verified by a third one.

3.2 Variables and data collection

Two approaches are considered for the analysis of GGS value relevance: receipt and value. This evaluation is consistent provided that the first demonstrates the condition of which benefiting from GGS changes investors’ expectations. The second approach highlights whether, among the companies who are recipient of GGS, the amount generates incremental informational content relevant to decision-making. Thus, the variables of interest are RGGS (receipt) and MGGS, represented by the monetary values recognized by the companies in the EN.

Regarding the MGGS variable, it is assumed that the relevant effect of GGS-received values mainly encompasses more than one period or business year. The guideline to acknowledge the result, ending as part of the equity, derives from three different aspects: (i) shareholders are not those who apply resources and GGS originates in acts of management. (ii) the firm receives GGS, but it is necessary to give back, which reflect expenses and cost in the result; (iii) taxes are expenses that must be presented in the results, this way GGSs are put as a tax policy extension (CPC 07 R1, 2010). Even if they occur in only one period, their reflection should endure more and the market, according to Beaver (1968), monitors accounting profit as essential information. In addition to that, Lo (2010) reinforces that materiality is not an attribute connected only with the item value, but also with the potential to change investors’ expectations and their capacity of anticipating and forecasting.

The other variables of the study, which were linked to the value relevance model weremarket value (MV), net equity (NE) and net profit (NP) andwere collected in the Economatica® database. Information on the sector and the activity of each company was also accessed in this base. The B3 sector classification is used.

3.3 Econometric models

To study the presumed value relevance of GGSs, the Ohlson’s model (1995) was adopted-a designated residual income valuation model (RIV). A linear model in which the company’s market value is a function of the shareholders’ equity, abnormal earnings and “other information”. There is evidence of its application in the Brazilian and foreign stock markets (Coelho et al., 2011; Lee et al., 2014; Madeira & Costa Júnior, 2015; Santos & Coelho, 2018). The model is displayed in Equation 1:

$$P_t={\alpha }_0+{{\alpha }_{1}y}_t+{\alpha }_2{x}_t^a+{\alpha }_3{v}_t^a+{\epsilon }_t$$ (1)

Where: P_t is the firm’s value; y_t is the shareholders’ equity; $x_t^a$ are abnormal earnings; $v_t^a$ corresponds to other information, which, in this study, is the variable of interest (GGS); a₀ is the intercept; a₁, a₂ and a₃ are the slopes; and ${\epsilon }_{it}$is the error term. This way, if GGSs are not value relevant, 𝛼 3 is statistically null.

As exposed by Ohlson (1995), the abnormal earnings ( $x_t^a$ ) are estimated in accordance with the expression: $x_t^a={NP}_t-{(NE}_{t-1}\times i_t)$. In which: 𝑖 𝑡 is the proxy for the risk-free rate for the period. This is the basic pay for the company’s endeavors in reaching the market in terms of returns. To estimate abnormal earnings, a rate was used, from the Special Settlement and Custody System (SELIC) , applied by Madeira and Costa Júnior (2015) and Santos and Coelho (2018). The Selic rate was obtained in the Central Bank of Brazil (BCB) website, in the Time Series Management System (SGS) , code 11. Other studies used the cost of capital, but this is an ad hoc procedure since the cost of one’s own capital has a risk (Cardoso & Martins, 2012). Ohlson (1995) does not specify the discount rate of the future dividend flow in the development of their evaluation model, but it assumes risk neutrality and market homogeneous expectations. This way, as suggested by Lopes et al. (2007), the Selic rate is an adequate simplification to determine abnormal earnings. In their study, Lopes et al. (2007) employed the return on savings, which is based on the Selic rate.

On the role of the GGSs as other information, it is important to note that Feltham and Ohlson (1995) proposed the disaggregation of accounting components to reveal which items would be capable of explaining the variability of the company’s value. According to Feltham and Ohlson (1995), if accounting is conservative, meaning, on the whole, the anticipating oflosses and the postponement of earnings, this disaggregation is more informative. Therefore, from that, it can be considered that alterations in investors’ expectations are reflected on the main accounting aggregates, but the identification of their components can be relevant and explain change in future cash flow in a clearer way.

Regarding the argument which sustains the inclusion of GGSs and their effect on the firm’s value in the Ohlson’s model (1995), Bernard (1995) reinforces that, in the fundamentalist analysis, informational aspects on the perspective of companies’ value, which involves a study of their activities, should be considered. In conclusion, it is assumed that companies receiving GGS, and the values received by them, can mean material change in the firms’ expectations even when this information is known to the market even though it requires compromise on the part of the company in the future. This perspective clarifies the relationship between accounting data and firm value, as explained by Bernard (1995), when discussing empirical implications in the model of Feltham and Ohlson (1995).

Consistently with what Feltham and Ohlson (1995) suggest, Bernard (1995) points out that an advantage of establishing the earnings forecast as an objective is being able to explain the company's current value based on its subsequent performance. What is relevant in this exercise is that the decomposition of results appears to be an advantage for company valuation, since decomposition reveals information on how and why an event or piece of data (in this study, it is the GGS) becomes useful in explaining the company's value (Bernard, 1995).

This research explores different perspectives for analyzing GGS. Firstly, it tests the conjecture that information about the receipt of GGS explains the value of firms, indicating that this information has relevant content for the market in valuation. Equation 2 allows us to verify the research hypothesis (H1).

$${MV}_{it+4}={\beta }_0+{\beta }_1{NE}_{it}+{\beta }_2{AE}_{it}+{\beta }_3{RGGS}_{it}+{\delta }_t+{\gamma }_s+{\epsilon }_{it}$$ (2)

Where ${MV}_{it+4}$ is the company’s market value 𝑖 four months after the end of the year t, as performed by Macedo et al. (2011), Rezende (2005), Santos et al. (2024). National studies in the field of value relevance conventionally use this approach since there are legal requirements from the Securities and Exchange Commission (CVM) (e.g. Instruction 480/09, Resolution 80/2022) and corporate law which leads companies to disclose demonstrations ending on December 31st of a financial year by the end of the month of April. Beyond that, it is worth mentioning that value relevance studies document that accounting demonstration disclosure impacts the company’s value, admitting certain efficiency in the Brazilian capital market once bookkeeping information can be incorporated into stock prices and this allows the conduction of comparative studies (Macedo et al., 2011). Studies like those of Burke and Wieland (2017) and Oliveira et al. (2010) make three-month estimates. To give robustness to the results, in this study, estimations were processed with ${MV}_{it+3}$ , with results similar to those of the originally proposed estimation; NE_it: company’s net worth i at the end of the year t; AE_it: company’s abnormal earnings i at the end of the year t; RGGS_it: receipt of GGS i at the end of the year t; ${\delta }_t$: time fixed effects; y_s: sector fixed effects; ${\epsilon }_{it}$: regression error term, assuming normality of the residuals, i.e. $~N\left(0,{\sigma }^2\right)$ .

Additionally, this research explores the value relevance of the origin and the magnitude of the GGSs in Brazilian companies. It is conjectured that the resource origin might also be value relevant and different when compared among Brazilian federal entities. In Brazil, the GGSs have distinct origins-federal, state and municipal-and these subsidies aim to stimulate the increase of new electric alternative energy sources (Law nº 10.973/2004), encourage regional development (e.g. The Northeast Development Fund - FNDE , Law nº 12.712/2012), and develop social projects, which include incentives to education (Law nº 11.096/2005), culture (Law nº 8.313/1991) and youth (Law nº 8.069/1990).

Empirical evidence reveals that Brazilian companies with shares traded on B3 S.A. mostly received GGSs originating from the federal sphere, followed by the state and municipal ones (Gonçalves et al., 2016; Loureiro et al., 2011; Rezende et al., 2018; Souza et al., 2018). Although these pieces of research did not show the resource distribution by government level, the objective here is to explore whether there is a value relevance distinction taking the GGS origin into account.

To do so, the variable RSAG_it was segmented from the origin, as highlighted by Table 1 (Panel B). Considering the sample distribution, it was opted to estimate only the models which presented adequate quantitative for their carryout, namely: (FGGS_it), state (EGGS_it), federal and state (FEGGS_it) and federal, state and municipal (FEMGGS_it). The econometric model is presented according to Equation 3.

$${MV}_{it+4}={\beta }_0+{\beta }_1{NE}_{it}+{\beta }_2{AE}_{it}+{\beta }_3{FGGS}_{it}+{\delta }_t+{\gamma }_s+{\epsilon }_{it}$$ (3a)

$${MV}_{it+4}={\beta }_0+{\beta }_1{NE}_{it}+{\beta }_2{AE}_{it}+{\beta }_3{EGGS}_{it}+{\delta }_t+{\gamma }_s+{\epsilon }_{it}$$ (3b)

$${MV}_{it+4}={\beta }_0+{\beta }_1{NE}_{it}+{\beta }_2{AE}_{it}+{\beta }_3{FEGGS}_{it}+{\delta }_t+{\gamma }_s+{\epsilon }_{it}$$ (3c)

$${MV}_{it+4}={\beta }_0+{\beta }_1{NE}_{it}+{\beta }_2{AE}_{it}+{\beta }_3{FEMGGS}_{it}+{\delta }_t+{\gamma }_s+{\epsilon }_{it}$$ (3d)

This way, to verify if the resource origin is value relevant, the statistical significance of the coefficient ${\beta }_3$ is examined, as well as the R² of regressions of the models derived from Equation 3. It is thus expected that the coefficients ${\beta }_3$ are positive and statistically significant and the cumulative receipt of resources from different sources are more representative (FEMGGS_it > FEGGS_it > FGGS_it and EGGS_it)

To test if the magnitude of the GGSs in the firm’s asset structure is value relevant in the investors’ perception, the econometric model was estimated including the monetary value of the GGS_it between the regressors, done by the representative variable adjustment in the NE_it and NP_it by the exclusion of the effects of the variables of interest (GGS_it), assuming the following expressions:

$${MV}_{it+4}={\beta }_0+{\beta }_1{NE}_{it}+{\beta }_2{{(AE}_{it}-{MGGS}_{it})}_{it}+{\beta }_3{MGGS}_{it}+{\delta }_t+{\gamma }_s+{\epsilon }_{it}$$ (4a)

$${MV}_{it+4}={\beta }_0+{\beta }_1{AE}_{it}+{\beta }_2{{(NE}_{it}-{MGGS}_{it})}_{it}+{\beta }_3{MGGS}_{it}+{\delta }_t+{\gamma }_s+{\epsilon }_{it}$$ (4b)

Where: (AE_it - MGGS_it): difference between the amount of abnormal earnings and the amount of 𝑆𝐴𝐺 𝑖𝑡 of the company 𝑖 at the end of the year t; (NE_it - MGGS_it): difference between the amount of net worth and the amount of GGS_it of the company 𝑖 at the end of the year 𝑡.

It is worth highlighting that AE_it and NE_it need to be adjusted so the model can isolate and capture the informative value of the GGS_it amount. The procedure is equally adopted by Santos et al. (2024) and Franzen and Radhakrishnan (2009)-expenses/revenue used as other relevant information; Han and Manry (2004) and Oliveira et al. (2010)-capitalized or activated values as other relevant information; and Burke and Wieland (2017)-cash flow. This occurs since accounting profit is a component which aggregates diverse non-homogeneous components (Ball & Brown, 1968), whereas net worth reflects the associate’s residual patrimony through the difference between amounts recognized in assets minus the liabilities owed to non-members (third party capital)

In Oliveira et al.’s study (2010), net worth is adjusted according to the intangible assets; Santos et al. (2024) add environmental cost to the accounting profit because spending effectively reduces the company’s results; Burke and Wieland (2017) separate cash flow and accruals in profit. With this procedure, it can eventually be identified if these figures prove any relevance to investors in their respective markets. The Ohlson’s model (1995) might be applied to non-financial and financial information, not solely to strict accounting informational aggregates. Amir and Lev’s (1996) study supports this and indicates that investigations should be conducted by using two types of information given that investors evaluate which other information are complementary to the shareholders’ equity and to the profit in the assessment.

In this study, it is expected that the coefficient of the variable of interest MSAG_it shows a positive, significant effect, which is the same expected for ${\beta }_1$ and ${\beta }_2$ . This way, the sum of SAG_it would present incremental informational value in companies’ evaluation in the Brazilian stock market. If ${\beta }_1$ and ${\beta }_2$ affect the value, then accounting is informative. The relationship between variables were estimated using the ordinary least squares-OLS -with control of fixed effects per year and sector, which allows controlling companies’ time effects and particular attributes. The models were estimated with robust errors for heteroscedasticity. All the models were also estimated with logarithmic transformation of variables, leading to the reduction of the sample base. Results of estimations did not show any significant alteration of the coefficients in relation to the originally previewed model, denoting larger robustness of the carried-out analyses.

4 RESULTS AND DISCUSSION

4.1 GGSs value relevance

Initially, a descriptive statistics is presented of the analyzed continuous variables and the results of the Jonckheere-Terpstra test which examines the tendency of variables included in the value relevance model and the GGSs throughout the analysis period.

Table 3
Descriptive statistics and tendency test

Variables	Obs.	DP	CV	Minimum	Average	Median	Maximum	JT test
MV	1.971	40,23	2,13	0,01	14,22	2,77	559,36	6,37***
NE	1.971	25,77	3,33	0,00	7,74	1,54	347,94	5,80***
AE	1.971	2,03	4,61	-15,22	0,44	0,04	24,78	8,11***
MGGS	925	0,18	2,57	0,00	0,07	0,02	2,11	3,18***
NE - MGGS	925	18,42	2,61	-0,06	7,06	1,80	184,60	2,89***
AE - MGGS	925	1,90	5,94	-15,43	0,32	0,04	23,59	6,53***

• Notes: MV: market value; NE: net equity; AE: abnormal earnings; MGGS: GGS amount; NE - MGGS: difference between net equity and amount of GGS (SAG); AE - MGGS: difference between abnormal earnings and amount of GGS (SAG). Values in billions (R$). *** it represents a level of significance to 1 %. The Jonckheere-Terpstra test was carried out to check tendency per year.
• Source: Research data.

It can be realized from Table 3 that abnormal earnings are the measure with one of the highest dispersions, with a variance coefficient of 461 %. There is high volatility in the GGS values, with a variance coefficient of 257 %. The Banco Mercantil S.A. (BMIN4) has the lowest value of SAG, R$1.000,00 (2017), referring to the tax incentive of cultural and artistic sponsorship. The company Vale S.A. (VALE3) registered the highest value, of R$ 2.112.000.000,00 (2018), value allusive to tax incentives from the Superintendence for the Development of the Amazon (SADAM).

Analysis of tendency results show that, apart from companies’ MV and NE, the GGS grew between 2010 and 2020. For the variable of interest, GGS, the compound yearly growth was 5.17 %. In the meantime, throughout the same period, these companies’ net profit percentage was -0.08 %.

Table 4 demonstrates the results of estimations based on the value relevance model proposed by Ohlson (1995), including, gradually, information on the receipt of GGS and the origin of resource by entity

Table 4
Accounting information relevance - Receipt and origin of GGS (SAG)

Eq. 1: ${MV}_{it}={\beta }_0+{\beta }_1{NE}_{it}+{\beta }_2{AE}_{it}+{\delta }_t+{\gamma }_s+{\epsilon }_{it}$
Eq. 2: ${VM}_{it}={\beta }_0+{\beta }_1{NE}_{it}+{\beta }_2{AE}_{it}+{\beta }_3{RGGS}_{it}+{\delta }_t+{\gamma }_s+{\epsilon }_{it}$
Eq. 3a: ${MV}_{it}={\beta }_0+{\beta }_1{NE}_{it}+{\beta }_2{AE}_{it}+{\beta }_3{FGGS}_{it}+{\delta }_t+{\gamma }_s+{\epsilon }_{it}$
Eq. 3b: ${MV}_{it}={\beta }_0+{\beta }_1{NE}_{it}+{\beta }_2{AE}_{it}+{\beta }_3{EGGS}_{it}+{\delta }_t+{\gamma }_s+{\epsilon }_{it}$
Eq. 3c: ${MV}_{it}={\beta }_0+{\beta }_1{NE}_{it}+{\beta }_2{AE}_{it}+{\beta }_3{FEGGS}_{it}+{\delta }_t+{\gamma }_s+{\epsilon }_{it}$
Eq. 4c: ${MV}_{it}={\beta }_0+{\beta }_1{NE}_{it}+{\beta }_2{AE}_{it}+{\beta }_3{FEMGGS}_{it}+{\delta }_t+{\gamma }_s+{\epsilon }_{it}$
Variables	Expec.	Eq. 1	Eq. 2	Eq. 1	Eq. 3a	Eq. 3b	Eq. 3c	Eq. 3d
$\left({\beta }_0\right)Constante$	?	1,42	0,46	1,61	-0,91	-0,93	0,49	-1,59
		(1,49)	(0,44)	(1,00)	(-0,51)	(-0,50)	(0,27)	(-1,44)
$\left({\beta }_1\right){NE}_{it}$	+	1,00***	1,00***	1,36***	1,36***	1,38***	1,38***	1,36***
		(15,62)	(15,75)	(13,90)	(13,96)	(13,80)	(13,86)	(13,89)
$\left({\beta }_2\right){AE}_{it}$	+	7,21***	7,23***	7,11***	7,10***	7,06***	7,02***	7,07***
		(6,78)	(6,80)	(4,97)	(4,97)	(4,97)	(4,97)	(4,96)
${\left({\beta }_3\right)RGGS}_{it}$	+		2,79
			(3,12)
${\left({\beta }_3\right)FGGS}_{it}$	+				3,41***
					(2,70)
${\left({\beta }_3\right)EGGS}_{it}$	+					4,63***
						(2,60)
${\left({\beta }_3\right)FEGGS}_{it}$	+						7,62***
							(2,70)
${\left({\beta }_3\right)FEMGGS}_{it}$	+							22,97***
								(2,59)
Year		Yes	Yes	Yes	Yes	Yes	Yes	Yes
Sector		Yes	Yes	Yes	Yes	Yes	Yes	Yes
F Test		42,78***	41,34***	23,40***	22,48***	21,66***	21,37***	27,30***
$R^2\left(\%\right)$		78,05	78,16	74,93	75,02	75,15	75,38	75,34
VIF Max		1,46	1,46	1,52	1,52	1,54	1,53	1,52
Obs.		1.971	1.971	961	961	961	961	961

• Notes: The models were estimated with robust standard errors, showing coefficients and the t-statistics (between parentheses). For each company i at the end of the year t, the dependent variable is the market value (MV_it); NE_it: net equity; AE_it: abnormal earnings; RGGS_it: receipt of GGS (SAG); z: receipt of GGS (SAG) from federal, state, federal and state and federal, state and municipal, in this order. VIF (maximum) is the variance inflation factor for multicollinearity. ***represents the level of significance to 1 %. The augmented Dickey-Fuller unit root test was carried out for all the variables in the study and the results indicated that the null hypothesis that all the panels contain unit roots was rejected. The null hypothesis that the residuals are normally distributed was rejected. However, according to Brooks (2014) and Wooldridge (2011), it is accepted that the errors reflect the sum of many unobserved factors affecting the dependent variable, and it is possible to invoke the central limit theorem because the analyses cover a large number of observations (Obs. > 900). In addition, some values cannot be negative and, strictly speaking, it is more feasible to achieve a distribution close to normal, as empirical evidence indicates that this hypothesis is not suitable for certain variables, relaxing the assumption (Brooks, 2014; Wooldridge, 2011).
• Source: Research data (2022).

According to Equation 1, the study results confirm the proposition of the relevance model by evidencing that the NE and the AE exert an effect over the company’s MV. Besides, it is noted that the abnormal earning has informational content higher than the equity (${\beta }_1<{\beta }_2$). Madeira and Costa Júnior (2015) and Santos and Coelho’s (2018) research, grounded on the Brazilian economic context, pointed to results similar to this study, indicating that the accounting profit is more informative than the net profit. The arrangement of the results converge with Ohlson’s (1995) expectation given that through profit a larger assertiveness in relation to the future benefit flow such as cash flow or cost reduction can be made possible. In turn, in economies known to be evolving in their markets, investors may attribute less relevance to profit thanks to the potential risks of interventions (politics, crises and instability, and share concentration are amongst some of the aspects that might be pondered).

Afterwards, in Equation 2, the RGGS_it exposed coefficient statistically different than 0 (zero), which pinpoints the existence of informational relevance of subsidies received by companies. Therefore, the research hypothesis (H₁) that the GGS (SAG) are value relevant for the investor’s perception in the process of evaluating companies cannot be rejected. This result corroborates the study belonging to Lee et al. (2014). The introduction of the variable RGGS_it elevated the determination coefficient, indicating that GGS would have a higher surprise effect among the investors compared to the firm’s net wealth value.

With regard to the complementary analysis, the results show that federal (FGGS_it) and state (EGGS_it) GGS are relevant and increase the value of the firm, as can be seen from the coefficient of determination of Equations 3a and 3b in relation to Equation 1. The results indicate that the firm subsidized by federal and state resources (FEGGS_it), cumulatively, and federal, state, and municipal resources (FEMGGS_it), cumulatively, signal to the market greater economic and/or political advantages, which translates into the effect of the variable on value. The market seems to consider active management in obtaining public funds from different sources to be value relevant.

As an extension of the analysis, Table 5 shows the effect of the magnitude of the GGS (SAG) (financial impact) on the market value of Brazilian firms.

Table 5
Relevance of accounting information - GGS amount

Eq. 1:${MV}_{it+4}={\beta }_0+{\beta }_1{NE}_{it}+{\beta }_2{AE}_{it}+{\delta }_t+{\gamma }_s+{\epsilon }_{it}$
Eq. 4a: ${MV}_{it+4}={\beta }_0+{\beta }_1{NE}_{it}+{\beta }_2{{(AE}_{it}-{MGGS}_{it})}_{it}+{\beta }_3{MGGS}_{it}+{\delta }_t+{\gamma }_s+{\epsilon }_{it}$
Eq. 4b: ${MV}_{it+4}={\beta }_0+{\beta }_1{AE}_{it}+{\beta }_2{{(NE}_{it}-{MGGS}_{it})}_{it}+{\beta }_3{MGGS}_{it}+{\delta }_t+{\gamma }_s+{\epsilon }_{it}$
Variables	Expectations	Eq. 1	Eq. 4a	Eq. 4b
$\left({\beta }_0\right)Constante$	?	1,66	2,14	2,14
		(1,01)	(1,28)	(1,28)
$\left({\beta }_1\right){NE}_{it}$	+	1,36***	1,12***
		(13,83)	(9,26)
$\left({\beta }_1\right){AE}_{it}$	+	7,16***		5,60***
		(4,99)		(3,75)
$\left({\beta }_2\right){{NE}_{it}-MGGS}_{it}$	+			1,12***
				(9,26)
$\left({\beta }_2\right){{AE}_{it}-MGGS}_{it}$	+		5,60***
			(3,75)
$\left({\beta }_3\right){MGGS}_{it}$	+		58,26***	53,78***
			(3,06)	(2,78)
Year		Yes	Yes	Yes
Sector		Yes	Yes	Yes
F Test		22,74***	22,71***	22,71***
$R^2\left(\%\right)$		75,56	78,24	78,24
VIF Max		1,52	2,04	2,13
Obs.		925	925	925

• Notes: The models have been estimated with robust standard errors, showing the coefficients and t-statistics (in brackets). For each company i at the end of year t, the dependent variable is the market value 𝑀𝑉 𝑖𝑡 ; 𝑁𝐸 𝑖𝑡 : shareholders' equity; 𝑁𝐸 𝑖𝑡 − 𝑀𝐺𝐺𝑆 𝑖𝑡 : shareholders' equity minus GGS; 𝐴𝐸 𝑖𝑡 − 𝑀𝐺𝐺𝑆 𝑖𝑡 : abnormal profits minus GGS; 𝐴𝐸 𝑖?? : abnormal profits; 𝑀𝐺𝐺𝑆 𝑖𝑡 : amount of GGS; 𝑉𝐼𝐹 (maximum) is the variance inflation factor for multicollinearity. *** represents a 1 % significance level. The augmented Dickey-Fuller unit root test was carried out for all the variables in the study and the results indicated the rejection of the null hypothesis that all the panels contain unit roots. The null hypothesis that the residuals are normally distributed was rejected. However, according to Brooks (2014) and Wooldridge (2011), it is accepted that the errors reflect the sum of many unobserved factors affecting the dependent variable, and it is possible to invoke the central limit theorem because the analyses cover a large number of observations (Obs. > 900). In addition, some values cannot be negative and, strictly speaking, it is more feasible to achieve a distribution close to normal, as empirical evidence indicates that this hypothesis is not suitable for certain variables, relaxing the assumption (Brooks, 2014; Wooldridge, 2011).
• Source: Research data (2022).

Equations 4a and 4b show that the magnitude of the GGS ( 𝑀𝐺𝐺𝑆 𝑖𝑡 ) is value relevant. In all estimations, 𝑀𝐺𝐺𝑆 𝑖𝑡 shows incremental informational content. The values, which are significant at the 1 % level, indicate that the market considers not only the receipt of GGSs, but also the materiality of the incentives, perhaps as a measure of quantifying the prospective economic advantages. The variation in 𝑅 2 is 2.68 %. The results indicate that the amount of incentives received from the government has an effect on market value. This finding is consistent with the literature, as the receipt of subsidies implies a direct economic impact on companies' cash flows (Lee et al., 2014; Santos, 2012).

As a sensitivity analysis, quantile regression analysis was also applied to assess the informational relevance of the GGS value ( 𝑀𝐺𝐺𝑆 𝑖𝑡 ) at different percentiles. A dummy variable was also created, in which 1 (one) was assigned if the GGS value ( 𝐷𝐺𝐺𝑆 𝑖𝑡 ) exceeded the median of the values; otherwise, 0 (zero). The latter was estimated via 𝑂𝐿𝑆. The results of this analysis are shown in Table 6.

Table 6
Relevance of accounting information - GGS amount (Quantile Regression)

	Percentile 10	Percentile 25	Percentile 50	Percentile 75	Percentile 90
Variables	Eq. 1: ${MV}_{it+4}={\beta }_0+{\beta }_1{NE}_{it}+{\beta }_2{AE}_{it}+{\delta }_t+{\gamma }_s+{\epsilon }_{it}$
$\left({\beta }_0\right)Constante$	0,03	0,08	0,16	0,20	0,06
	(0,03)	(0,09)	(0,12)	(0,11)	(0,01)
$\left({\beta }_1\right){NE}_{it}$	0,69***	1,02***	1,30***	1,80***	2,56***
	(51,35)	(72,79)	(65,46)	(66,87)	(36,97)
$\left({\beta }_2\right){AE}_{it}$	3,07***	3,27***	5,45***	10,16***	17,52***
	(25,87)	(26,48)	(31,03)	(42,92)	(28,71)
Year	Yes	Yes	Yes	Yes	Yes
Sector	Yes	Yes	Yes	Yes	Yes
$Pseud{R}^2$	32,39	42,49	53,20	64,54	74,65
Obs.	925	925	925	925	925
Variables	Eq. 4a: ${MV}_{it+4}={\beta }_0+{\beta }_1{NE}_{it}+{\beta }_2{{(AE}_{it}-{MGGS}_{it})}_{it}+{\beta }_3{MGGS}_{it}+{\delta }_t+{\gamma }_s+{\epsilon }_{it}$
$\left({\beta }_0\right)Constante$	-0,01	0,02	0,12	0,02	0,54
	(-0,01)	(0,02)	(0,10)	(0,01)	(0,20)
$\left({\beta }_1\right){NE}_{it}$	0,67***	0,99***	1,21***	1,77***	2,20***
	(40,99)	(68,83)	(57,47)	(39,27)	(48,20)
$\left({\beta }_2\right){{AE}_{it}-MGGS}_{it}$	3,11***	3,15***	5,26***	10,02***	14,26***
	(22,90)	(26,30)	(29,98)	(26,65)	(37,51)
$\left({\beta }_3\right){MGGS}_{it}$	8,48***	15,73***	15,70***	16,31***	66,22***
	(5,04)	(10,59)	(7,21)	(3,50)	(14,03)
Year	Yes	Yes	Yes	Yes	Yes
Sector	Yes	Yes	Yes	Yes	Yes
$Pseud{R}^2$	32,83	43,72	53,83	64,59	76,17
Obs.	925	925	925	925	925
Variables	Eq. 4b: ${MV}_{it+4}={\beta }_0+{\beta }_1{AE}_{it}+{\beta }_2{{(NE}_{it}-{MGGS}_{it})}_{it}+{\beta }_3{MGGS}_{it}+{\delta }_t+{\gamma }_s+{\epsilon }_{it}$
$\left({\beta }_0\right)Constante$	-0,01	0,02	0,12	0,02	0,54
	(-0,01)	(0,02)	(0,10)	(0,01)	(0,20)
$\left({\beta }_1\right){AE}_{it}$	3,11***	3,15***	5,26***	10,02***	14,26***
	(22,90)	(26,30)	(29,98)	(26,65)	(37,51)
$\left({\beta }_2\right){{NE}_{it}-MGGS}_{it}$	0,67***	0,99***	1,21***	1,77***	2,20***
	(40,99)	(68,83)	(57,47)	(39,27)	(48,20)
$\left({\beta }_3\right){MGGS}_{it}$	6,05***	13,57***	11,65***	8,07***	54,16***
	(3,51)	(8,93)	(5,23)	(1,69)	(11,22)
Year	Yes	Yes	Yes	Yes	Yes
Sector	Yes	Yes	Yes	Yes	Yes
$Pseud{R}^2$	32,83	43,72	53,83	64,59	76,17
Obs.	925	925	925	925	925

• Notes: The quantile models have been estimated showing the coefficients and t-statistics (in brackets). For each company 𝑖 at the end of year 𝑡, the dependent variable is the market value (MV_it); PL_it: shareholders' equity; (NE_it - MGGS_it): shareholders' equity minus GGS; (AE_it - MGGS_it): abnormal profits minus GGS; AE_it: abnormal profits; MGGS_it: amount of GGS. * and *** represent significance levels of 10 % and 1 %. The augmented Dickey-Fuller unit root test was carried out for all the variables in the study and the results indicated the rejection of the null hypothesis that all the panels contain unit roots. The null hypothesis that the residuals are normally distributed was rejected. However, according to Books (2014) and Wooldridge (2011), it is accepted that the errors reflect the sum of many unobserved factors affecting the dependent variable, and it is possible to invoke the central limit theorem because the analyses cover a large number of observations (Obs. > 900). In addition, some values cannot be negative and, strictly speaking, it is more feasible to achieve a distribution close to normal, as empirical evidence indicates that this hypothesis is not suitable for certain variables, relaxing the assumption (Brooks, 2014; Wooldridge, 2011).
• Source: Research data (2022).

The results were statistically significant in all the percentiles analyzed. The result found for the dummy variable confirms the informational relevance of MGGS_it, showing a positive and significant effect on the market value of Brazilian companies' shares ( 𝛽 3 = 3,48 ∗∗∗ ). Thus, there is an increase in the value relevance of GGS in relation to the value received, and this informational gain seems to accompany the growth in GGS values.

4.2 Discussion of results

The findings reinforce that GGSs are welcomed by investors in the process of evaluating companies, including corroborating that this information is used by more sophisticated users-such as market analysts-when forecasting profits, determining target prices and recommending shares (Lee et al., 2014). At first, the receipt of GGS, specifically in emerging contexts, can signal implicit advantages, which include those related to political connections.

In this sense, empirical evidence shows that politically connected Brazilian companies are more likely to receive GGS (Einsweiller et al., 2020). This context suggests that subsidized firms-by understanding the public policy process, which encompasses GGS-can gain direct access to statesmen, having the potential to celebrate decisions with government officials that favor them (Hillman, 2005). This perception of benefits may be even greater in Brazil, an emerging market with higher levels of corruption (Boubakri, et al., 2012; Faccio, 2006).

Therefore, GGSs signal to the market that subsidized companies have the support and protection of the government agent (Lee et al., 2014). As the results suggest here, there does not seem to be the “heavy burden” of the reputation of the political context on the company (Yang et al., 2022), nor does it signal a loss of competence in the market in the long term (Liu et al., 2019), given that the findings illustrate the positive effect of the GGS on the value of companies between 2010 and 2020. If there is a perception of this “damage”, the individual nature of the GGS may favor the company over others and other competitors, which is one justification for the positive effect on value.

The literature shows that GGSs contribute directly to financial performance, value creation, and cash generation (Almeida & Pereira, 2019; Lee et al., 2014; Rezende et al., 2018). At first, the effect of GGS on the firm’s cash flows may seem logical, however, if not allocated correctly, these resources will not be able to generate wealth for the company (Einsweiller et al., 2020). Thus, the value relevance of the GGS found in this study may indicate that managers are managing these resources properly. Or, more likely, that the market prices the supposed efficiency of managers in relation to incentives.

It can be seen that the origin of the GGS denotes different, but converging, investor perceptions of future cash generation, attributing informational utility to the joint receipt of funds from the federal, state and municipal governments. This result could make it clear to the Brazilian capital market that the company's management is focused on obtaining all the opportunities available in the market. The results presented here reinforce that the changes in accounting-that GGSs should be recognized as income in the period in which they occur as long as all the obligations required for the benefit to be enjoyed are met-may have generated gains in information transparency, as well as the extent of the impacts of GGSs on company results, as established by Santos (2012).

5 CONCLUSION

This study achieved its objective, which was to examine the informational relevance attributed to GGS in Brazilian companies listed on B3 S.A. between 2010 and 2020, using OLS regression techniques. The results support the hypothesis presented: GGS are positively relevant in the perception of investors in the process of evaluating companies in Brazil. The motivations for investigating the relevance of GGS stem from the set of advantages that these subsidies can provide for companies, indirectly through government protection, or directly through the effects on future cash flows.

The results of the research are favorable to the proposition that GGSs take on the role of “other information” that has relevant informational content in the process of attributing value to companies in the Brazilian capital market. In addition, data is provided indicating that the origin of the GGS is also relevant, although it consolidates different perceptions of the value of companies. Finally, it is set out to assess how the magnitude of the GGS was associated with the price and what was presented was evidence that, in addition to the receipt (existence) and origin of the GGS, the amount received caused differences in terms of valuation.

It was concluded that GGSs constitute relevant information for the investment decision-making process among investors in the Brazilian market. The results are in line with the evidence of Lee et al. (2014), who investigated the relevance of subsidies in firms in China using Ohlson’s (1999) model. Here, the findings are robust and support the relevance of GGSs, according to Ohlson’s model (1995).

The research contributes to the literature by investigating how the GGS - the extent of the government's fiscal policy - and firm value may be related in the Brazilian stock market. This research provides support for questioning the process of attributing value in decision-making based on GGS and its management in organizations. Therefore, the results presented here help managers, investors, and regulators to observe the relevance of accounting and disclosure of GGS, considered a determining factor in maximizing the value of the firm.

As a limitation, we should clarify that we are not investigating the informational relevance of specific GGS public policies, such as incentives for technological innovation, clean energy production, and regional development. Each policy is aimed at a specific purpose and has specific criteria for its adoption. Future studies could assess whether the different types of GGS are value relevant. For example, investigating whether the incentives for technological innovation introduced by Law 10.973/2004 have an effect on abnormal profits and whether this information is perceived by the market as relevant. In addition, further research could consider the value of each company on the date of publication of the financial statements and thus capture the individualized effects of the accounting figures and information per unit of analysis. Regarding the valuation model, it is suggested that the cost of capital and other rates be used to estimate the abnormal profit. There are models that use the simplification of net profit as a measure, without considering the abnormal profit of the original model (Collins, Pincus, & Xie, 1999). Finally, future research could explore the impact of survival bias on the results by means of sensitivity analyses, incorporating data from inactive companies or considering different inclusion criteria in the sample.

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• DATA AVAILABILITY STATEMENT
  The dataset related to this article can be obtained from the Economatica database and the companies' explanatory notes.

Edited by

• EDITOR-IN-CHIEF
  Márcia D’Angelo

• ASSOCIATE EDITOR
  Veronica Santana

Data availability

The dataset related to this article can be obtained from the Economatica database and the companies' explanatory notes.

Publication Dates

• Publication in this collection
  27 July 2026
• Date of issue
  2026

History

• Received
  06 Sept 2023
• Reviewed
  28 May 2024
• Accepted
  16 Aug 2024