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Disclosure of financial instruments: Practices and challenges of Latin American firms from the mining industry
Accepted Manuscript Title: Disclosure of financial instruments: Practices and challenges of latin american firms from the mining industry Authors: Rodrigo Fernandes Malaquias, Pablo Zambra PII: DOI: Reference:
S0275-5319(17)30235-0 http://dx.doi.org/doi:10.1016/j.ribaf.2017.07.144 RIBAF 834
To appear in:
Research in International Business and Finance
Received date: Accepted date:
4-4-2017 6-7-2017
Please cite this article as: Malaquias, Rodrigo Fernandes, Zambra, Pablo, Disclosure of financial instruments: Practices and challenges of latin american firms from the mining industry.Research in International Business and Finance http://dx.doi.org/10.1016/j.ribaf.2017.07.144 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Disclosure of Financial Instruments: Practices and Challenges of Latin American Firms from the Mining Industry
Authors: Rodrigo Fernandes Malaquias* is a Full Time Professor of Accounting at Universidade Federal de Uberlândia (UFU), Brazil. In 2012, he received his PhD in Business Administration from Escola de Administração de Empresas de São Paulo da Fundação Getulio Vargas (FGV-EAESP), Brazil. In 2015, he was a Visiting Research Scholar at DePaul University in Chicago, USA. His research includes finance, accounting, mobile banking, e-commerce, and cross-country studies. His papers have been published or accepted for publication by peer-reviewed journals, including Research in International Business and Finance, Accounting & Finance Review (USP), Computers in Human Behavior, Brazilian Review of Finance, Brazilian Business Review, Information Development, Information Technology for Development, Journal of Operations and Supply Chain Management, Technology and Disability, among others. Address: Avenida João Naves de Ávila, nº 2121, Bloco F, Sala 1F-215, Campus Santa Mônica, Uberlândia / Minas Gerais / Brazil. CEP (zip code): 38.400-902, Phone: +55 (34) 3239-4176. Email: [email protected] Research ID: A-7709-2017 (http://www.researcherid.com/rid/A-7709-2017) ORCID: 0000-0002-7126-1051 (http://orcid.org/0000-0002-7126-1051) * corresponding author.
Pablo Zambra is an Auditor, at Deloitte (Chile). His experience as auditor in Deloitte is mainly oriented to the mining sector of Chile. He has a specialization in International Financial Reporting Standard and experience as a part time professor of auditing and mining topics at the Universidad Católica del Norte (UCN), Chile. Currently, he is a Master’s degree student at Universidade Federal de Uberlânda, Brazil, in the area of Accounting, with emphasis on Financial Accounting. Address: Avenida João Naves de Ávila, nº 2121, Bloco F, Sala 1F-215, Campus Santa Mônica, Uberlândia / Minas Gerais / Brazil. CEP (zip code): 38.400-902. Email: [email protected]
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Abstract In this paper, we analyze the disclosure level of financial instruments provided by companies of the mining industry, located in Latin America region. The sample is comprised of 72 firms from Brazil, Chile, Peru and Mexico. The main results indicate that companies located in Mexico provide the higher levels of disclosure both for IFRS-07 and for IFRS-09 requirements. The size of firms is also a variable that affects disclosure. We also build a panorama regarding some challenges for firms to disclose full information following IFRS-09. Furthermore, the results of this paper indicate that companies should use the potential benefits of Internet and disclosure more information regarding financial instruments.
Key-words: IFRS 07; IFRS 09; Credit Risk; Derivatives; Internet.
1. Introduction Financial instruments play an important role for companies since firms can manage a set of risk factors with these contracts, especially through derivatives. Nevertheless, even though financial instruments allow companies to protect their financial income and cash flows, when managers use derivatives inadequately, they expose the company to a complex scenario of potential financial losses. In this regard, information about the use of financial instruments is relevant for external users of accounting reports. With complete information, investors can estimate the risk of investing more accurately in a particular firm. Although this is an important issue, disclosing information on financial instruments seems to not be a simple task for companies; furthermore, it is not a simple task for external auditors to audit this information. There is a more complex situation when we address disclosure of
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derivatives and information about hedge accounting. Different authors consider derivative financial instruments as a complex issue (Kawaller, 2004; Birt, Rankin & Song, 2013; Prorokowski, 2013; Chang, Donohoe & Sougiannis, 2016; Tessema, 2016). Lopes and Rodrigues (2007) studied the disclosure level of Portuguese-listed companies. They found that, on average, the disclosure level of companies was lower than 50% of the items available in their disclosure index (their disclosure index contains 54 items). “Accounting policies” was the category with more information disclosed by companies, and “credit risk” and “fair value and market value” were the categories with lower levels of disclosure. Firms’ characteristics such as size, listing status and economic sector presented a significant relationship with corporate disclosure on financial instruments (Lopes & Rodrigues, 2007). With Brazilian companies, Malaquias and Lemes (2013) found similar results, based on a disclosure index with 45 items, adopted from Lopes and Rodrigues (2007). Accounting standards about presentation, recognition, measurement and disclosure of financial instruments have existed for a couple of years, but revisions have been implemented periodically, as we have the case of IFRS 7 and, nowadays, the IFRS 9, which will be mandatory after 2018. One of the reasons to issue new standards on financial instruments rely on the changes and evolution of tools to measure and manage financial risks from these contracts, as well as new concepts and approaches currently accepted (IASB, 2016). These revisions indicate the relevance of new studies that analyze if companies meet the minimum information required of them. Some companies rely on financial instruments to develop their activities and manage their risks, which is the case of companies in the mining industry sector. The relationship between industries of natural resources extraction and the use of derivatives financial instruments was already documented in previous studies (Hassan, Percy & Stewart, 2006; Taylor et al., 2008;
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Taylor et al. 2010; Birt et al. 2013). For example, the sales of firms from the mining industry sector are very sensitive to the variations of commodities prices (Hassant et al., 2006), since their main product is sold by different economies worldwide. Firms can use derivatives (or a combination of financial instruments) to manage “interest rate, foreign currency, and commodity risk exposures” (Chalmers & Godfrei, 2000, p. 47). In the context of extractive firms, they have incentives to use derivatives in order to manage these kinds of risks (Birt et al., 2013). It is also important to note that extractive industries are also exposed to other risks, such as potential exploration and production risks (Hassant et al., 2006). The use of derivatives to protect their revenues from undesirable variations in fair values of commodities prices has a direct effect on their net income and free cash flow. Therefore, it represents primordial information for shareholders if these companies develop financial operations for hedging purposes. When presented properly and completely, this information mitigates the information asymmetry between management and external users of accounting reports. It is natural to expect that firms in the mining industry sector present adequate information for external users about their operations with financial instruments. Nevertheless, change in accounting standards and the complexity of disclosing detailed information about financial instruments may represent a negative effect on information that these companies report in their accounting statements. To the best of our knowledge, there is a gap on academic literature about disclosure of financial instruments in the mining sector, which motivated a new study in this field. In this context, the aim of this paper is to analyze the disclosure level of financial instruments provided by mining companies of Latin America. Previous studies have focused on financial instruments used by firms from the extraction industry (Hassan et al., 2006; Tower et al., 2008; Birt et al., 2013). Latin America is a region with abundance in natural resources and
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has countries with economies in the stage of growing (Martinez et al., 2015). Specifically, in the mining sector, the World Metals Statistics shows that countries of Latin America have high representativeness in the mining sector (Cochilco, 2015; 2016); on the other hand, there are few academic studies with firms of this region. The Latin American financial market has gained importance in the field of international finance, since investors from developed economies (such as the US) are investing in assets of foreign markets to diversify their portfolios and to participate in economic opportunities of growing economies. Therefore, detailed information represents an important issue in the evaluation of external users of financial reports (Etter, Lippincott & Reck, 2006; Camacho, 2016). The sample of this paper comprises companies from four Latin American countries, namely: Chile, Brazil, Mexico, and Peru. The inclusion of these countries in the sample is grounded in the relevance of them to Latin America. Furthermore, these countries have adopted international standards to change / improve their local accounting standards. Chile and Peru are mentioned in the study of Bolaños et al. (2015) for their dynamism in economic activities and their fund raising of foreign markets. Mexico has a higher impact in the Latin American integration and Brazil, with its stock exchange, is a representative economy in Latin American region. The disclosure index built to develop this study involves items from previous studies (Lopes & Rodrigues, 2007), current standards (which is the case of IFRS-07), and items from accounting standards that are not mandatory for the moment (which is the case of IFRS-09). Therefore, the results reported in this paper indicates not only a panorama regarding the disclosure practices of mining companies, but also the main challenges that these companies probably will face to disclose complete information during the next years.
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2. Hypotheses of the study Size and disclosure Research available in academic literature regarding the disclosure level provided by companies on their financial reports indicates that detailed information reduces information asymmetry (Lopes & Rodrigues 2007; Malaquias & Lemes 2013; Birt et al., 2013; Aznan & Nelson, 2014). In this context, there is also a consideration that firms’ size affects disclosure. For example, larger companies may disclose more information than smaller companies due their internal information systems; therefore, to generate accounting reports with detailed information is less costly for them, so they tend to present higher levels of disclosure (Lopes e Rodrigues, 2007). The positive relationship between size and disclosure was also documented in other studies (Chalmers & Godfrey 2004; Taylor et al., 2008; Hassan et al., 2008; Taylor et al., 2010; Birt et al., 2013; Malaquias & Lemes, 2013; Mohammadi & Mardini, 2016). Therefore, the first variable we include in the quantitative model is size, and the first hypothesis of the study is: H1: The disclosure of financial instruments is positively associated with firms’ size.
Leverage and disclosure Grounded on the exposition that firms have when they obtain external financing, leveraged companies should be more motivated to disclose more information of financial instruments (Taylor; Tower; Van Der Zahn & Neilson, 2008). Birt et al. (2013) point out that firms with higher levels of leverage tend to be more exposed to financial risk; also, these firms tend to use more derivatives and are motivated to disclose more information regarding these contracts. Some studies have included this variable in the empirical analysis (Chalmers & Godfrey, 2004; Lopes & Rodrigues, 2007), and some of them found a significant relationship
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between leverage and disclosure of financial instruments (Taylor et al., 2008; Hassan et al., 2008; Taylor et al., 2010; Birt et al., 2013). Therefore, the second hypothesis of this study is: H2: The disclosure of financial instruments is positively associated with firms’ leverage.
Listing status and disclosure Listing status of firms also has presented a useful variable to understand the level of disclosure in accounting reports. Listed companies, especially those companies listed in foreign markets, tend to present higher levels of disclosure. Since investors are not familiar with domestic rules of foreign companies, when these companies are listed in foreign markets, they need to attend the minimum requirements of disclosure. This figure is necessary to improve the understanding of their financial reports by local investors of foreign markets (Lopes & Rodrigues, 2007). Malaquias and Lemes (2013) observed a positive relationship between financial instruments disclosure and the experience of Brazilian companies listed at the New York Stock Exchange (NYSE). They called this effect as a learning process. Therefore, in this paper, we expect that firms listed at NYSE will present higher levels of disclosure than those counterparts will. The level of American requirements of firms should incentive these companies in engage in a more detailed content on their financial reports. Considering this scenario, we present the third hypothesis of the study: H3: The disclosure of financial instruments is positively associated with firms’ listing status at NYSE.
Firm’s profitability and disclosure The profitability of the firms represents a variable included in previous studies and the motivation is related with managers’ behavior. Managers of profitable firms have additional
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incentives to disclose more information (Xiao et al., 2004; Kelton & Yang, 2008). We can consider that firms with higher profitability indexes are more willing to disclose detailed information to investors (Lopes & Alencar, 2010). Garay et al. (2013) included in their study Latin American firms, and they observed that disclosure index and ROA (Return on Assets) was positively associated. Four of the seven countries considered in the study of Garay et al. (2013) are the same of the sample of this paper. Therefore, we present the fourth hypothesis: H4: The disclosure of financial instruments is positively associated with firms’ profitability.
Auditor type and disclosure Among the variables considered to study the disclosure level, we can identify the auditor type. The relevance of this variable can be explained considering: i) the role of these professionals to reduce information asymmetry (Jensen & Meckling, 1976; Scott, 2009); and their participation as external referees regarding the compliance with accounting standards. Aznan and Nelson (2014), with a sample of Malaysian firms, found a positive relationship among these variables; nevertheless, in the multivariate regression, this effect was not statistically significant. Nevertheless, there are other studies that have documented a positive effect of the auditor type on disclosure (Lopes & Rodrigues 2007; Birt et al., 2013). Therefore, we include this variable in our quantitative model, and we present the following research hypothesis: H5: The disclosure of financial instruments is positively associated with type of auditor of the firm.
Country infrastructure and disclosure Observing the study of Buhr and Freddman (2001), cultural, institutional and conjectural factors of countries can present an effect on the disclosure level. Countries’ infrastructure affect
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the levels of investments, for example, due governmental incentives (Lee & Fisher, 2004; Kartasheva, 2012); in order to attract more investments, companies could disclose more (and detailed) information. Private investors have interest in infrastructure projects and these opportunities are consolidated in developed countries; on the other hand, these opportunities in developing economies can motivate foreign investors that seek to diversify their portfolios (Peng & Newell, 2007; Torrance, 2009; Gemson et al., 2012). This situation is presumed to work as an indirect incentive to local firms disclose more information in emerging economies. Furthermore, physical and institutional infrastructure factors of a given country also affect the option do adopt the Internet Financial Report (IFR), which contributes to improvements on transparency, market efficiency, disclosure practices and financial information levels (Ojah & Mokoaleli-Mokoteli, 2008). Considering these arguments, and the fact that country’s infrastructure can support the information demands of external investors, we present the sixth study hypothesis: H6: The disclosure of financial instruments is positively associated with country’s infrastructure, where the firm is located.
Internet access and disclosure Firms can reduce information asymmetry through voluntary disclosure. Furthermore, they can use Internet resources to disclose financial reports and to disseminate more information to external users. Using Internet, firms have a flexible way to present and disclose information, improve transparency, reach immediate communication, widely and with low cost (Xiao et al., 2004; Kelton & Yang, 2008; Trabelsia et al., 2008; Gandía et al., 2012; Ojah & MokoaleliMokoteli, 2012).
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The Internet also expands the borders of accounting reports, since these reports can be quickly available worldwide (Xiao et al., 2004). “Indeed, the Internet could be treated as an information media, along with other traditional paper-based media” (Gajewskyi & Li, 2015, p. 7). Therefore, Internet based disclosure can reduce information asymmetry (Gajewskyi & Li, 2015) and contribute with the transparency level of companies. The growth of Internet use also increases the demand of corporate/financial information of companies (Alai & Romero, 2012), and some factors such as size, the number of analysts following the firm and return on equity affect the extent of additional Internet financial reporting voluntary disclosure (Trabelsi et al., 2008). Firms in the mining industry tend to disclose higher levels of voluntary information when compared with other industries, using the Internet as a tool to improve their image and minimize the environmental effects from their activities (Alai & Romero, 2012). Therefore, based on these arguments and evidences, we expect that countries with higher levels of Internet access will present a natural demand for firms to disclose more information. Thus, we present the seventh hypothesis of this study: H7: The disclosure of financial instruments is positively associated with country’s Internet access, where the firm is located.
3. Method and data The annual accounting reports are the main source of information to develop this paper. Our sample is comprised of 72 companies in the extractive sector or mining industry, located in Brasil, Chile, Mexico or Peru. The annual reports were accessed at the official website of the regulatory body of each country; when necessary, the website of each company was consulted to
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search for its respective annual report. Figure 1 contains the names of the regulatory bodies of each country of this research.
In Brazil, the companies included in the sample participate of the mining extraction industry or of the oil and gas industry (09 companies with complete data for analysis). To select companies from Chile, we choose those affected by the specific tax of the mining activity, which resulted in 32 companies with complete data for analysis. Additionally, we included in the sample the Corporación Nacional del Cobre de Chile (CODELCO), because it is the main mining company of the country and it is classified as a public company (Law n. 20285). Regarding the companies from Mexico, we consulted the Dirección General de Desarrollo Minero and we found 15 companies of the metallic mining industry with complete data for analysis in this paper. In Peru, we also selected 15 companies (with complete data) which are regulated by SMV (Superintendencia del Mercado de Valores) and contain in their names one of this words: minera, copper, or mina. After selecting the firms, we collected their annual accounting report of the year of 2015, since it was the more current information available during the data collection. The year of 2015 represents a period after IFRS adoption and a year before IFRS-09 requirements are mandatory. Therefore, our results indicate a panorama regarding: i) the disclosure practices of financial instruments disclosure considering what is required by IASB (IFRS-07); and ii) the disclosure practices of what will be mandatory for companies after 2018 (IFRS-09). To estimate the disclosure level of each firm, we used the disclosure index, available in Appendix A of this research. This questionnaire was developed considering previous studies (Lopes & Rodrigues, 2007; Chang et al., 2016) and the requirements of IFRS-07 and IFRS-09.
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All the questions are equally weighted, and a given company receives the score 1 if it discloses the item, and 0 in the absence of the required information. The average of these scores, multiplied by 100, represents the disclosure index (therefore, it varies from 0% to 100%). We employed multivariate regression analysis to test the seven hypotheses of the study. To avoid heteroscedasticity problems, we used robust standards errors to report the p-values of each coefficient. We also observed the VIF (Variance Inflation Factor) indexes to analyze if multicollinearity is a concern in each quantitative model.
4. Results In the studies of Camfferman (2015) and Novotny-Farkas (2016), there is a discussion on the estimated credit losses, comparing IFRS-09 versus IAS-39. Considering the results of this paper, firms of the sample still do not disclose fully and detailed information as required by IFRS-09 (as we can see in Table 1); firms from Mexico are those that presented the higher levels of disclosure for both subset of questions (financial instruments and IFRS-09 requirements). It is important to note that the requirements from IFRS-09 are not mandatory for the accounting reports of 2015; nevertheless, those requirements to disclose information regarding financial instruments are mandatory, but firms do not meet them adequately (none of the firms in the sample disclosed 100% of information of the disclosure index, as Table 1 indicates).
We also observed that IFRS-09 requirements are not fully disclosed by extractive firms in the sample of this study. One point that should be highlighted is the information regarding expected credit losses, which received low scores in the disclosure index and it represents an
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issue that has been discussed in different papers (Camfferman, 2015; Novotny-Farkas, 2016), since it is complex to establish the inputs to estimate these losses and develop the calculations. During the analysis of results, we observed that some companies have disclosed information about hedge accounting, such as accounting policies, and these companies attended partially or fully to the disclosure index requirements (of hedge accounting). Nevertheless, the analysis of their financial statements indicates that these companies did not use hedge accounting in such period. This result would be an evidence that some companies keep information from previous reports to elaborate new accounting statements. We observe this fact in companies of the four countries of the sample. Therefore, the percentage of disclosure of hedge policies is higher than the number of companies that used this accounting choice effectively.
As Table 2 shows, we also created two dummy variables to represent the variables: Internet users and country infrastructure. These variables received 1 for two countries and 0 for the other two, respectively. The disclosure level of IFRS-09 items is lower than the disclosure level of financial instruments, as we can see in Table 2 (24.074 and 47.817, respectively). In Table 3 we report the results of the comparison, among countries, of the disclosure level estimated to each firm. The results of this table indicate that, despite the disclosure level is different in the four countries (as Table 1 indicates), these indexes are statistically equivalent among Brazil, Chile and Peru. Companies from Mexico registered the higher levels of information regarding financial instruments, but not necessarily of IFRS-09 requirements. Table 4 contains the results for the analysis of the following hypotheses: H1, H2, H3, H4 and H5.
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Regarding the results in Table 4, it is important to note that we tested different models since there are different measures for leverage (lev-tot; lev-st; lev-lt) and profitability (prof-ni; prof-oi). Furthermore, after performing the Variance Inflation Test (VIF) in the first model, we observed the presence of multicollinearity between the proxies to leverage and profitability. Therefore, we run the regressions with these variables separately, to avoid some problems with the interpretation of the beta coefficients. Table 5 contains equivalent content, but the dependent variable is the disclosure index of IFRS-09 items (see Appendix A). The countries’ characteristics available in Figure 2 were used to create the dummy variables, as we explained before. Therefore, we can test the other two hypotheses: H6 and H7. The results are available in Table 6, and Table 7 summarizes the results of the hypotheses testing.
There is a consensus that large firms can present a more detailed level of disclosure when compared with small firms. This result is consistent with the empirical analysis made in this paper, in a cross-country study, because size and disclosure were positively associated. This result is in accordance with H1, and with previous research in this field (Chalmers & Godfrey 2004; Taylor et al., 2008; Hassan et al., 2008; Taylor et al., 2010; Birt et al., 2013; Malaquias & Lemes, 2013; Mohammadi & Mardini, 2016). It is also important to highlight that larger companies seem to be able to anticipate IFRS-09 requirements too; therefore, they are presumed to provide a more complete and detailed level of information to their investors and external users.
The relationship between disclosure and leverage (H2) was partially supported because it was significant for the entire level of disclosure, but not significant when we considered IFRS-09
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requirements. Therefore, there results of this paper do not support that leveraged firms have additional motivation to disclose more detailed information on financial instruments. The auditor type (H5) did not present a significant effect on credit risk disclosure and on disclosure of financial instruments. A potential explanation is that this information (from IFRS-09), as a voluntary content, is not subject of auditing by external auditors during the accounting reports analysis. For the other three hypotheses (H3, H4 and H6), the relationship was not significant, both for the disclosure level of financial instruments (general) and for the disclosure level of credit risk (grounded on IFRS-09). Regarding the last hypothesis (H7), it was rejected. Following the theoretical review, we expected a positive relationship between countries’ Internet access and disclosure, but the empirical analysis indicated a negative relationship between these variables. As presented in the theoretical framework, Internet enables firms to present information in a flexible way and with low cost (Xiao et al., 2004; Kelton & Yang, 2008; Trabelsia et al., 2008; Gandía et al., 2012; Ojah & Mokoaleli-Mokoteli, 2012). Therefore, we highlight that companies have an important tool to disseminate information, but they do not necessarily use this channel to improve their interaction with shareholders / stakeholders and reduce information asymmetry. This result is more critical when we observe that firms of the mining sector naturally demand the use of derivatives to reduce their exposure to external risk factors. Complete information regarding the use of derivative contracts represents a challenge for these companies, regardless of where they are in Latin America.
5. Final Remarks Considering the complexity exposed by various users of financial information and other interested parties in this kind of report, as well as in its interpretation and effective use, the FASB
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and the IASB had some initiatives to improve and simplify these requirements; the result is IFRS-09 (IASB, 2016). IFRS-09 brings more relevance to financial reports and contribute with transparency and market efficiency (Novotny-Farkas, 2016). Investors from developed economies have already evaluated positively this new standard (Onali & Ginesti, 2014). New requirements, such as expected credit loss instead of only incurred credit loss, improve the way of presentation of financial statements (Novotny-Farkas, 2016), which represent benefits of this statement. Nevertheless, even considering the relevance of this kind of information, the analysis of this paper indicates that companies from the sample study (of the four countries) have not anticipate this information yet, at least in its fully format. Some companies of the sample study are evaluating the effects of these standards. IFRS-09 requirements will be mandatory in 2018; therefore, a debate about the disclosure of these items by firms of the extractive industry is a major issue to be considered both in the academic studies and in practice. The results of this paper indicate a panorama not only about the disclosure of financial instruments by mining firms of Latin America, but we also indicate some challenges related with the implementation of IFRS-09 requirements to generate a more complete information to investors. We also report that these challenges will be higher for small firms, and for firms situated in countries with higher levels of Internet access, since Internet represents a channel that companies can use to facilitate their interaction with shareholders. Some limitations are present in this study, and the main one is that the disclosure level is affected by a set of variables; our quantitative model considers only seven factors to explain the disclosure index. Therefore, new research is needed to analyze IFRS-09 requirements with other determinants. The second limitation is the number of companies of each country, because this quantity may not represent the disclosure practices of the other companies. A third limitation is
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related with the countries of the study, since there are other economies in Latin America; nevertheless, we selected those countries with more representation in the mining industry sector, and we used this this data to build a panorama regarding some challenges that could be faced by companies to provide complete information to their shareholders.
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Torrance M (2009) The Rise of a Global Infrastructure Market through Relational Investing. Journal Economic Geography, 85: 75-97.
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Trabelsia S, Labelle R, Dumontier P (2008) Incremental voluntary disclosure on corporate Websites, Determinants and Consequences. Journal of Contemporary Accounting & Economics, 4(2): 120-155.
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Appendix A Disclosure Index #
Item / Category (Source) Credit Risk (Lopes & Rodrigues, 2007; IFRS-07)
1
Counterparties identification
2
Maximum amount of credit risk exposure
3
Significant concentration of credit risk
4
Credit Risk (IFRS-09) Method to determine credit losses
5
Quantitative and qualitative information on expected credit losses
6
Credit risk exposure and evaluation methods (reduction / increase)
7
Credit losses (twelve months)
8
Credit losses, incurred (twelve months or more)
9
Levels of credit risk
Derivatives - Accounting Policie (Lopes & Rodrigues, 2007; IFRS-07) 10 Risk management policy, including hedging policy 11 Objectives of holding or issuing derivatives 12 Accounting policies and methods adopted 13 Monitoring and controlling policy 14 Financial controls Derivatives - Financial Instruments (IFRS-07; IFRS-09)
24 15 Fair value of derivatives 16 Precedure embedded derivated 17 Level - fair values Derivatives - Risks (Lopes & Rodrigues, 2007; IFRS-07) 18 Segregation by risk categories 19 Principal, stated value, face value, notional value maturity 20 Weighted average/effective interest rate Hedge Accounting (IFRS-07; IFRS-09) 21 Strategy of risk management 22 How hedge activities can affect future cash flows 23 Effects of hedge accounting on income and on equity 24 Fair value hedge 25 Cash flow hedge 26 Net investment hedge Risk Management (IFRS-07; IFRS-09) 27 Emmergence of each risk 28 Management of each risk 29 Exposure to each risk 30 Instrument used to manage the risk 31 Efficacy of the risk management (method) 32 Method used to estimate the coverage ratio and inefficiencies Risk Management - Hedge with Derivatives (Chang et al., 2016; IFRS-07; IFRS-09) 33 Interest rates risk 34 Foreign exchange rate risk 35 Price risk (commodities) 36 Price risk (raw materials) 37 Liquidity risk 38 Credit risk Risk Management - Different of Credit Risk (IFRS-07; IFRS-09) 39 Other types of risk (beyond credit risk) 40 Sensivity analysis 41 Segregation of the effects (Income x Equity) Note: Each company receives a score = 1 for each item disclosed.
Figure 1:
25 Regulatory bodies of the countries studied Country
Regulatory board
Brazil
Comissão de Valores Mobiliados (CVM)
Chile
Superintendecia de Valores y Seguros (SVS)
Mexico
Comisión Nacional Bancaria y de Valores (CNBV)
Peru
Superintendencia del Mercado de Valores (SMV)
Figure 2: Countries’ characteristics regarding internet and quality of infrastructure 200
3.4
150
3.2
100
3.0
50
2.8 2.6
0
BR Internet Users
CH
PE
MX
Secure Internet Servers
BR
CH
PE
MX
Logistic Performance Index
Notes: Internet Users = Internet Users by 100 people; Secure Internet Servers = Secure Internet Servers per 1 million people; Logistic Performance Index = Logistic Performance Index. Source: Compiled from the database of The World Bank (2016).
Table 1: Descriptive statistics of the disclosure level, by country
26
Country
Discl. Fin. Instr.
Discl. IFRS 09
Mean
S.D.
Min.
Max.
Mean
S.D.
Min.
Max.
Brazil
44.762
25.951
14.286
85.714
27.778
11.785
16.667
50.000
Chile
43.636
21.217
8.571
82.857
19.697
14.704
0.000
50.000
Mexico
61.524
22.364
20.000
85.714
31.111
10.666
16.667
50.000
Peru
45.143
25.787
8.571
82.857
24.445
12.387
0.000
50.000
Table 2: Descriptive statistics of the variables in the sample Variables
Obs
Mean
S.D.
Min.
Max.
intaccess
72
57.336
8.940
40.900
64.289
intaccessdm
72
0.583
0.496
0.000
1.000
infrast
72
3.104
0.169
2.841
3.256
ifrastrdm
72
0.667
0.475
0.000
1.000
lnatuss
72
13.660
2.239
4.625
19.256
lev-tot
72
1.293
3.959
0.019
24.755
lev-st
72
0.686
2.802
0.000
21.280
lev-lt
72
0.607
1.647
0.000
13.647
prof-ni
72
-0.188
0.750
-4.946
0.410
prof-oi
72
-0.122
0.723
-4.946
0.637
audit
72
0.861
0.348
0.000
1.000
nyse
72
0.111
0.316
0.000
1.000
ifrs9
72
24.074
13.672
0.000
50.000
discl
72
47.817
23.643
8.571
85.714
Notes: intaccess = it represents the number of Internet users by 100 people of each country (source: The World Bank, 2016); intaccessdm = it is a dummy variable, and it receives 1 for firms from countries with higher Internet users index and 0 for the other cases; infrast = it represents the logistic performance index (overall, 1=low to 5=high) of each country (source: The World Bank, 2016); infrastdm = it is a dummy variable, and it receives 1 for firms from countries with higher logistic performance indexes and 0 for the other cases; lnatuss = it is the natural logarithm of Total Assets of each company, in US Dollars; lev-tot = it is the ratio between total liabilities and total assets; lev-st = short term leverage; lev-lt = long term leverage; prof-ni = the ratio between net income and total assets; prof-oi = the ratio between operational income and total assets; audit = it is a dummy variable, and it receives 1 for firms audited by one of the big four auditing companies and 0 for the other cases; nyse = it is a dummy variable, and it receives 1 for firms listed at the New York Stock Exchange; ifrs9 = it represents the disclosure index based only in the items from IFRS 09 (see also Appendix A); discl = it represents the disclosure index (see also Appendix A) based on the following sources: IAS 39, IFRS 07 and Lopes & Rodrigues (2007). Table 3: Regression analysis between disclosure and dummy variables for countries Variables Brazil Chile Mexico constant
Discl. Fin. Instr. Coef. P>t -0.381 0.972 -1.507 0.844 16.381 0.066 45.143 0.000 r2 = 9.04%
Discl. IFRS 09 Coef. P>t 3.333 0.504 -4.747 0.251 6.667 0.117 24.444 0.000 r2 = 11.31%
27 Notes: Brazil = it represents a dummy variable, where firms from Brazil receives 1 and the other cases receive 0; Chile = it represents a dummy variable, where firms from Chile receives 1 and the other cases receive 0; Mexico = it represents a dummy variable, where firms from Mexico receives 1 and the other cases receive 0; Peru = it represents a dummy variable, where firms from Peru receives 1 and the other cases receive 0. The variable “Peru” was omitted of this regression analysis to avoid perfect multicollinearity. Table 4: Regression analysis between disclosure of financial instruments and its determinants Variables Coef. P>t Brazil -11.909 0.113 Chile -13.680 0.062 Mexico 4.226 0.541 lnatuss 6.191 0.000 lev-tot 2.799 0.011 lev-st lev-lt prof-ni 11.345 0.038 prof-oi audit 10.743 0.218 nyse 1.248 0.829 constant -40.754 0.005 r2 = 43.67%
Coef. -9.996 -13.065 4.312 5.591
P>t 0.167 0.072 0.551 0.000
Coef. -9.946 -12.950 4.549 5.561
P>t 0.168 0.075 0.532 0.000
Coef. -10.387 -13.346 3.690 5.886 0.741
P>t 0.154 0.065 0.605 0.000 0.051
Coef. -9.640 -12.665 4.838 5.675
P>t 0.194 0.081 0.501 0.000
Coef. -11.652 -14.349 2.473 5.951
P>t 0.122 0.058 0.751 0.000
0.838 0.081 1.627 0.133 -1.936 0.316 10.539 0.221 2.009 0.745 -31.876 0.026 r2 = 41.59%
-1.858 0.333 10.394 0.225 1.960 0.753 -31.311 0.027 r2 = 41.56%
11.779 0.171 1.730 0.774 -37.239 0.011 r2 = 42.36%
11.209 0.199 1.701 0.780 -34.122 0.014 r2 = 42.07%
10.878 0.188 2.066 0.731 -36.541 0.019 r2 = 42.15%
Notes: the VIF statistic indicated a multicollinearity between the variables leverage and profitability (VIF = 10.69). Therefore, we estimate the models considering the effects of these variables separately.
Table 5: Regression analysis between disclosure (IFRS 09) and its determinants Variables Brazil Chile Mexico lnatuss lev-tot lev-st lev-lt prof-ni prof-oi audit nyse constant
Coef. 0.980 -8.978 3.539 2.100 -0.060
P>t 0.831 0.038 0.429 0.012 0.933
Coef. 0.939 -8.991 3.537 2.113
P>t 0.836 0.036 0.425 0.007
Coef. 0.981 -8.968 3.516 2.128
P>t 0.829 0.036 0.421 0.006
Coef. 0.878 -9.001 3.574 2.121 0.078
P>t 0.847 0.036 0.418 0.009 0.784
Coef. 0.969 -8.923 3.689 2.105
P>t 0.832 0.037 0.396 0.006
Coef. 0.813 -9.042 3.562 2.104
P>t 0.861 0.040 0.460 0.017
0.109 0.715 0.098 0.917 -0.757 0.830
-0.474 0.744
4.488 0.348 -5.048 0.178 -4.733 0.652 r2 = 24.82%
4.492 0.345 -5.064 0.169 -4.922 0.617 r2 = 24.82%
-0.750 0.597 4.665 0.314 -5.099 0.167 -5.280 0.581 r2 = 24.89%
4.419 0.348 -5.080 0.167 -4.967 0.633 r2 = 24.80%
4.413 0.341 -5.093 0.167 -4.793 0.616 r2 = 24.81%
Notes: we used the same quantitative models available on Table 4 to construct this table. Table 6: Regression analysis between disclosure and countries’ characteristics
4.244 0.358 -5.043 0.172 -4.522 0.683 r2 = 24.78%
28
Variables lnatuss lev-tot audit nyse intaccessdm infrastdm constant
Discl. Fin. Instr. Coef. P>t 6.018 0.000 0.786 0.062 11.319 0.181 3.029 0.601 -14.637 0.001 0.440 0.925 -37.245 0.011 r2 = 42.01%
Discl. IFRS 09 Coef. P>t 2.387 0.006 0.167 0.664 3.487 0.515 -2.451 0.505 -7.720 0.013 -3.001 0.392 -4.978 0.657 r2 = 20.46%
Table 7: Expected signs versus observed signs in the hypotheses testing Variables Size Leverage Listing Status Profitability Auditor (Big four) Infraestructure Internet Access
Hypotheses H1 H2 H3 H4 H5 H6 H7
Expected Sign + + + + + + +
Observed Sign + ; + + ; n.s. n.s. ; n.s. n.s. ; n.s. n.s. ; n.s. n.s. ; n.s. − ; −
Notes: + : indicates a positive and statistically significant relationship; − : indicates a negative and statistically significant relationship; n.s.: indicates a relationship not significant between the variables.
S0275-5319(17)30235-0 http://dx.doi.org/doi:10.1016/j.ribaf.2017.07.144 RIBAF 834
To appear in:
Research in International Business and Finance
Received date: Accepted date:
4-4-2017 6-7-2017
Please cite this article as: Malaquias, Rodrigo Fernandes, Zambra, Pablo, Disclosure of financial instruments: Practices and challenges of latin american firms from the mining industry.Research in International Business and Finance http://dx.doi.org/10.1016/j.ribaf.2017.07.144 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Disclosure of Financial Instruments: Practices and Challenges of Latin American Firms from the Mining Industry
Authors: Rodrigo Fernandes Malaquias* is a Full Time Professor of Accounting at Universidade Federal de Uberlândia (UFU), Brazil. In 2012, he received his PhD in Business Administration from Escola de Administração de Empresas de São Paulo da Fundação Getulio Vargas (FGV-EAESP), Brazil. In 2015, he was a Visiting Research Scholar at DePaul University in Chicago, USA. His research includes finance, accounting, mobile banking, e-commerce, and cross-country studies. His papers have been published or accepted for publication by peer-reviewed journals, including Research in International Business and Finance, Accounting & Finance Review (USP), Computers in Human Behavior, Brazilian Review of Finance, Brazilian Business Review, Information Development, Information Technology for Development, Journal of Operations and Supply Chain Management, Technology and Disability, among others. Address: Avenida João Naves de Ávila, nº 2121, Bloco F, Sala 1F-215, Campus Santa Mônica, Uberlândia / Minas Gerais / Brazil. CEP (zip code): 38.400-902, Phone: +55 (34) 3239-4176. Email: [email protected] Research ID: A-7709-2017 (http://www.researcherid.com/rid/A-7709-2017) ORCID: 0000-0002-7126-1051 (http://orcid.org/0000-0002-7126-1051) * corresponding author.
Pablo Zambra is an Auditor, at Deloitte (Chile). His experience as auditor in Deloitte is mainly oriented to the mining sector of Chile. He has a specialization in International Financial Reporting Standard and experience as a part time professor of auditing and mining topics at the Universidad Católica del Norte (UCN), Chile. Currently, he is a Master’s degree student at Universidade Federal de Uberlânda, Brazil, in the area of Accounting, with emphasis on Financial Accounting. Address: Avenida João Naves de Ávila, nº 2121, Bloco F, Sala 1F-215, Campus Santa Mônica, Uberlândia / Minas Gerais / Brazil. CEP (zip code): 38.400-902. Email: [email protected]
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Abstract In this paper, we analyze the disclosure level of financial instruments provided by companies of the mining industry, located in Latin America region. The sample is comprised of 72 firms from Brazil, Chile, Peru and Mexico. The main results indicate that companies located in Mexico provide the higher levels of disclosure both for IFRS-07 and for IFRS-09 requirements. The size of firms is also a variable that affects disclosure. We also build a panorama regarding some challenges for firms to disclose full information following IFRS-09. Furthermore, the results of this paper indicate that companies should use the potential benefits of Internet and disclosure more information regarding financial instruments.
Key-words: IFRS 07; IFRS 09; Credit Risk; Derivatives; Internet.
1. Introduction Financial instruments play an important role for companies since firms can manage a set of risk factors with these contracts, especially through derivatives. Nevertheless, even though financial instruments allow companies to protect their financial income and cash flows, when managers use derivatives inadequately, they expose the company to a complex scenario of potential financial losses. In this regard, information about the use of financial instruments is relevant for external users of accounting reports. With complete information, investors can estimate the risk of investing more accurately in a particular firm. Although this is an important issue, disclosing information on financial instruments seems to not be a simple task for companies; furthermore, it is not a simple task for external auditors to audit this information. There is a more complex situation when we address disclosure of
3
derivatives and information about hedge accounting. Different authors consider derivative financial instruments as a complex issue (Kawaller, 2004; Birt, Rankin & Song, 2013; Prorokowski, 2013; Chang, Donohoe & Sougiannis, 2016; Tessema, 2016). Lopes and Rodrigues (2007) studied the disclosure level of Portuguese-listed companies. They found that, on average, the disclosure level of companies was lower than 50% of the items available in their disclosure index (their disclosure index contains 54 items). “Accounting policies” was the category with more information disclosed by companies, and “credit risk” and “fair value and market value” were the categories with lower levels of disclosure. Firms’ characteristics such as size, listing status and economic sector presented a significant relationship with corporate disclosure on financial instruments (Lopes & Rodrigues, 2007). With Brazilian companies, Malaquias and Lemes (2013) found similar results, based on a disclosure index with 45 items, adopted from Lopes and Rodrigues (2007). Accounting standards about presentation, recognition, measurement and disclosure of financial instruments have existed for a couple of years, but revisions have been implemented periodically, as we have the case of IFRS 7 and, nowadays, the IFRS 9, which will be mandatory after 2018. One of the reasons to issue new standards on financial instruments rely on the changes and evolution of tools to measure and manage financial risks from these contracts, as well as new concepts and approaches currently accepted (IASB, 2016). These revisions indicate the relevance of new studies that analyze if companies meet the minimum information required of them. Some companies rely on financial instruments to develop their activities and manage their risks, which is the case of companies in the mining industry sector. The relationship between industries of natural resources extraction and the use of derivatives financial instruments was already documented in previous studies (Hassan, Percy & Stewart, 2006; Taylor et al., 2008;
4
Taylor et al. 2010; Birt et al. 2013). For example, the sales of firms from the mining industry sector are very sensitive to the variations of commodities prices (Hassant et al., 2006), since their main product is sold by different economies worldwide. Firms can use derivatives (or a combination of financial instruments) to manage “interest rate, foreign currency, and commodity risk exposures” (Chalmers & Godfrei, 2000, p. 47). In the context of extractive firms, they have incentives to use derivatives in order to manage these kinds of risks (Birt et al., 2013). It is also important to note that extractive industries are also exposed to other risks, such as potential exploration and production risks (Hassant et al., 2006). The use of derivatives to protect their revenues from undesirable variations in fair values of commodities prices has a direct effect on their net income and free cash flow. Therefore, it represents primordial information for shareholders if these companies develop financial operations for hedging purposes. When presented properly and completely, this information mitigates the information asymmetry between management and external users of accounting reports. It is natural to expect that firms in the mining industry sector present adequate information for external users about their operations with financial instruments. Nevertheless, change in accounting standards and the complexity of disclosing detailed information about financial instruments may represent a negative effect on information that these companies report in their accounting statements. To the best of our knowledge, there is a gap on academic literature about disclosure of financial instruments in the mining sector, which motivated a new study in this field. In this context, the aim of this paper is to analyze the disclosure level of financial instruments provided by mining companies of Latin America. Previous studies have focused on financial instruments used by firms from the extraction industry (Hassan et al., 2006; Tower et al., 2008; Birt et al., 2013). Latin America is a region with abundance in natural resources and
5
has countries with economies in the stage of growing (Martinez et al., 2015). Specifically, in the mining sector, the World Metals Statistics shows that countries of Latin America have high representativeness in the mining sector (Cochilco, 2015; 2016); on the other hand, there are few academic studies with firms of this region. The Latin American financial market has gained importance in the field of international finance, since investors from developed economies (such as the US) are investing in assets of foreign markets to diversify their portfolios and to participate in economic opportunities of growing economies. Therefore, detailed information represents an important issue in the evaluation of external users of financial reports (Etter, Lippincott & Reck, 2006; Camacho, 2016). The sample of this paper comprises companies from four Latin American countries, namely: Chile, Brazil, Mexico, and Peru. The inclusion of these countries in the sample is grounded in the relevance of them to Latin America. Furthermore, these countries have adopted international standards to change / improve their local accounting standards. Chile and Peru are mentioned in the study of Bolaños et al. (2015) for their dynamism in economic activities and their fund raising of foreign markets. Mexico has a higher impact in the Latin American integration and Brazil, with its stock exchange, is a representative economy in Latin American region. The disclosure index built to develop this study involves items from previous studies (Lopes & Rodrigues, 2007), current standards (which is the case of IFRS-07), and items from accounting standards that are not mandatory for the moment (which is the case of IFRS-09). Therefore, the results reported in this paper indicates not only a panorama regarding the disclosure practices of mining companies, but also the main challenges that these companies probably will face to disclose complete information during the next years.
6
2. Hypotheses of the study Size and disclosure Research available in academic literature regarding the disclosure level provided by companies on their financial reports indicates that detailed information reduces information asymmetry (Lopes & Rodrigues 2007; Malaquias & Lemes 2013; Birt et al., 2013; Aznan & Nelson, 2014). In this context, there is also a consideration that firms’ size affects disclosure. For example, larger companies may disclose more information than smaller companies due their internal information systems; therefore, to generate accounting reports with detailed information is less costly for them, so they tend to present higher levels of disclosure (Lopes e Rodrigues, 2007). The positive relationship between size and disclosure was also documented in other studies (Chalmers & Godfrey 2004; Taylor et al., 2008; Hassan et al., 2008; Taylor et al., 2010; Birt et al., 2013; Malaquias & Lemes, 2013; Mohammadi & Mardini, 2016). Therefore, the first variable we include in the quantitative model is size, and the first hypothesis of the study is: H1: The disclosure of financial instruments is positively associated with firms’ size.
Leverage and disclosure Grounded on the exposition that firms have when they obtain external financing, leveraged companies should be more motivated to disclose more information of financial instruments (Taylor; Tower; Van Der Zahn & Neilson, 2008). Birt et al. (2013) point out that firms with higher levels of leverage tend to be more exposed to financial risk; also, these firms tend to use more derivatives and are motivated to disclose more information regarding these contracts. Some studies have included this variable in the empirical analysis (Chalmers & Godfrey, 2004; Lopes & Rodrigues, 2007), and some of them found a significant relationship
7
between leverage and disclosure of financial instruments (Taylor et al., 2008; Hassan et al., 2008; Taylor et al., 2010; Birt et al., 2013). Therefore, the second hypothesis of this study is: H2: The disclosure of financial instruments is positively associated with firms’ leverage.
Listing status and disclosure Listing status of firms also has presented a useful variable to understand the level of disclosure in accounting reports. Listed companies, especially those companies listed in foreign markets, tend to present higher levels of disclosure. Since investors are not familiar with domestic rules of foreign companies, when these companies are listed in foreign markets, they need to attend the minimum requirements of disclosure. This figure is necessary to improve the understanding of their financial reports by local investors of foreign markets (Lopes & Rodrigues, 2007). Malaquias and Lemes (2013) observed a positive relationship between financial instruments disclosure and the experience of Brazilian companies listed at the New York Stock Exchange (NYSE). They called this effect as a learning process. Therefore, in this paper, we expect that firms listed at NYSE will present higher levels of disclosure than those counterparts will. The level of American requirements of firms should incentive these companies in engage in a more detailed content on their financial reports. Considering this scenario, we present the third hypothesis of the study: H3: The disclosure of financial instruments is positively associated with firms’ listing status at NYSE.
Firm’s profitability and disclosure The profitability of the firms represents a variable included in previous studies and the motivation is related with managers’ behavior. Managers of profitable firms have additional
8
incentives to disclose more information (Xiao et al., 2004; Kelton & Yang, 2008). We can consider that firms with higher profitability indexes are more willing to disclose detailed information to investors (Lopes & Alencar, 2010). Garay et al. (2013) included in their study Latin American firms, and they observed that disclosure index and ROA (Return on Assets) was positively associated. Four of the seven countries considered in the study of Garay et al. (2013) are the same of the sample of this paper. Therefore, we present the fourth hypothesis: H4: The disclosure of financial instruments is positively associated with firms’ profitability.
Auditor type and disclosure Among the variables considered to study the disclosure level, we can identify the auditor type. The relevance of this variable can be explained considering: i) the role of these professionals to reduce information asymmetry (Jensen & Meckling, 1976; Scott, 2009); and their participation as external referees regarding the compliance with accounting standards. Aznan and Nelson (2014), with a sample of Malaysian firms, found a positive relationship among these variables; nevertheless, in the multivariate regression, this effect was not statistically significant. Nevertheless, there are other studies that have documented a positive effect of the auditor type on disclosure (Lopes & Rodrigues 2007; Birt et al., 2013). Therefore, we include this variable in our quantitative model, and we present the following research hypothesis: H5: The disclosure of financial instruments is positively associated with type of auditor of the firm.
Country infrastructure and disclosure Observing the study of Buhr and Freddman (2001), cultural, institutional and conjectural factors of countries can present an effect on the disclosure level. Countries’ infrastructure affect
9
the levels of investments, for example, due governmental incentives (Lee & Fisher, 2004; Kartasheva, 2012); in order to attract more investments, companies could disclose more (and detailed) information. Private investors have interest in infrastructure projects and these opportunities are consolidated in developed countries; on the other hand, these opportunities in developing economies can motivate foreign investors that seek to diversify their portfolios (Peng & Newell, 2007; Torrance, 2009; Gemson et al., 2012). This situation is presumed to work as an indirect incentive to local firms disclose more information in emerging economies. Furthermore, physical and institutional infrastructure factors of a given country also affect the option do adopt the Internet Financial Report (IFR), which contributes to improvements on transparency, market efficiency, disclosure practices and financial information levels (Ojah & Mokoaleli-Mokoteli, 2008). Considering these arguments, and the fact that country’s infrastructure can support the information demands of external investors, we present the sixth study hypothesis: H6: The disclosure of financial instruments is positively associated with country’s infrastructure, where the firm is located.
Internet access and disclosure Firms can reduce information asymmetry through voluntary disclosure. Furthermore, they can use Internet resources to disclose financial reports and to disseminate more information to external users. Using Internet, firms have a flexible way to present and disclose information, improve transparency, reach immediate communication, widely and with low cost (Xiao et al., 2004; Kelton & Yang, 2008; Trabelsia et al., 2008; Gandía et al., 2012; Ojah & MokoaleliMokoteli, 2012).
10
The Internet also expands the borders of accounting reports, since these reports can be quickly available worldwide (Xiao et al., 2004). “Indeed, the Internet could be treated as an information media, along with other traditional paper-based media” (Gajewskyi & Li, 2015, p. 7). Therefore, Internet based disclosure can reduce information asymmetry (Gajewskyi & Li, 2015) and contribute with the transparency level of companies. The growth of Internet use also increases the demand of corporate/financial information of companies (Alai & Romero, 2012), and some factors such as size, the number of analysts following the firm and return on equity affect the extent of additional Internet financial reporting voluntary disclosure (Trabelsi et al., 2008). Firms in the mining industry tend to disclose higher levels of voluntary information when compared with other industries, using the Internet as a tool to improve their image and minimize the environmental effects from their activities (Alai & Romero, 2012). Therefore, based on these arguments and evidences, we expect that countries with higher levels of Internet access will present a natural demand for firms to disclose more information. Thus, we present the seventh hypothesis of this study: H7: The disclosure of financial instruments is positively associated with country’s Internet access, where the firm is located.
3. Method and data The annual accounting reports are the main source of information to develop this paper. Our sample is comprised of 72 companies in the extractive sector or mining industry, located in Brasil, Chile, Mexico or Peru. The annual reports were accessed at the official website of the regulatory body of each country; when necessary, the website of each company was consulted to
11
search for its respective annual report. Figure 1 contains the names of the regulatory bodies of each country of this research.
In Brazil, the companies included in the sample participate of the mining extraction industry or of the oil and gas industry (09 companies with complete data for analysis). To select companies from Chile, we choose those affected by the specific tax of the mining activity, which resulted in 32 companies with complete data for analysis. Additionally, we included in the sample the Corporación Nacional del Cobre de Chile (CODELCO), because it is the main mining company of the country and it is classified as a public company (Law n. 20285). Regarding the companies from Mexico, we consulted the Dirección General de Desarrollo Minero and we found 15 companies of the metallic mining industry with complete data for analysis in this paper. In Peru, we also selected 15 companies (with complete data) which are regulated by SMV (Superintendencia del Mercado de Valores) and contain in their names one of this words: minera, copper, or mina. After selecting the firms, we collected their annual accounting report of the year of 2015, since it was the more current information available during the data collection. The year of 2015 represents a period after IFRS adoption and a year before IFRS-09 requirements are mandatory. Therefore, our results indicate a panorama regarding: i) the disclosure practices of financial instruments disclosure considering what is required by IASB (IFRS-07); and ii) the disclosure practices of what will be mandatory for companies after 2018 (IFRS-09). To estimate the disclosure level of each firm, we used the disclosure index, available in Appendix A of this research. This questionnaire was developed considering previous studies (Lopes & Rodrigues, 2007; Chang et al., 2016) and the requirements of IFRS-07 and IFRS-09.
12
All the questions are equally weighted, and a given company receives the score 1 if it discloses the item, and 0 in the absence of the required information. The average of these scores, multiplied by 100, represents the disclosure index (therefore, it varies from 0% to 100%). We employed multivariate regression analysis to test the seven hypotheses of the study. To avoid heteroscedasticity problems, we used robust standards errors to report the p-values of each coefficient. We also observed the VIF (Variance Inflation Factor) indexes to analyze if multicollinearity is a concern in each quantitative model.
4. Results In the studies of Camfferman (2015) and Novotny-Farkas (2016), there is a discussion on the estimated credit losses, comparing IFRS-09 versus IAS-39. Considering the results of this paper, firms of the sample still do not disclose fully and detailed information as required by IFRS-09 (as we can see in Table 1); firms from Mexico are those that presented the higher levels of disclosure for both subset of questions (financial instruments and IFRS-09 requirements). It is important to note that the requirements from IFRS-09 are not mandatory for the accounting reports of 2015; nevertheless, those requirements to disclose information regarding financial instruments are mandatory, but firms do not meet them adequately (none of the firms in the sample disclosed 100% of information of the disclosure index, as Table 1 indicates).
We also observed that IFRS-09 requirements are not fully disclosed by extractive firms in the sample of this study. One point that should be highlighted is the information regarding expected credit losses, which received low scores in the disclosure index and it represents an
13
issue that has been discussed in different papers (Camfferman, 2015; Novotny-Farkas, 2016), since it is complex to establish the inputs to estimate these losses and develop the calculations. During the analysis of results, we observed that some companies have disclosed information about hedge accounting, such as accounting policies, and these companies attended partially or fully to the disclosure index requirements (of hedge accounting). Nevertheless, the analysis of their financial statements indicates that these companies did not use hedge accounting in such period. This result would be an evidence that some companies keep information from previous reports to elaborate new accounting statements. We observe this fact in companies of the four countries of the sample. Therefore, the percentage of disclosure of hedge policies is higher than the number of companies that used this accounting choice effectively.
As Table 2 shows, we also created two dummy variables to represent the variables: Internet users and country infrastructure. These variables received 1 for two countries and 0 for the other two, respectively. The disclosure level of IFRS-09 items is lower than the disclosure level of financial instruments, as we can see in Table 2 (24.074 and 47.817, respectively). In Table 3 we report the results of the comparison, among countries, of the disclosure level estimated to each firm. The results of this table indicate that, despite the disclosure level is different in the four countries (as Table 1 indicates), these indexes are statistically equivalent among Brazil, Chile and Peru. Companies from Mexico registered the higher levels of information regarding financial instruments, but not necessarily of IFRS-09 requirements. Table 4 contains the results for the analysis of the following hypotheses: H1, H2, H3, H4 and H5.
14
Regarding the results in Table 4, it is important to note that we tested different models since there are different measures for leverage (lev-tot; lev-st; lev-lt) and profitability (prof-ni; prof-oi). Furthermore, after performing the Variance Inflation Test (VIF) in the first model, we observed the presence of multicollinearity between the proxies to leverage and profitability. Therefore, we run the regressions with these variables separately, to avoid some problems with the interpretation of the beta coefficients. Table 5 contains equivalent content, but the dependent variable is the disclosure index of IFRS-09 items (see Appendix A). The countries’ characteristics available in Figure 2 were used to create the dummy variables, as we explained before. Therefore, we can test the other two hypotheses: H6 and H7. The results are available in Table 6, and Table 7 summarizes the results of the hypotheses testing.
There is a consensus that large firms can present a more detailed level of disclosure when compared with small firms. This result is consistent with the empirical analysis made in this paper, in a cross-country study, because size and disclosure were positively associated. This result is in accordance with H1, and with previous research in this field (Chalmers & Godfrey 2004; Taylor et al., 2008; Hassan et al., 2008; Taylor et al., 2010; Birt et al., 2013; Malaquias & Lemes, 2013; Mohammadi & Mardini, 2016). It is also important to highlight that larger companies seem to be able to anticipate IFRS-09 requirements too; therefore, they are presumed to provide a more complete and detailed level of information to their investors and external users.
The relationship between disclosure and leverage (H2) was partially supported because it was significant for the entire level of disclosure, but not significant when we considered IFRS-09
15
requirements. Therefore, there results of this paper do not support that leveraged firms have additional motivation to disclose more detailed information on financial instruments. The auditor type (H5) did not present a significant effect on credit risk disclosure and on disclosure of financial instruments. A potential explanation is that this information (from IFRS-09), as a voluntary content, is not subject of auditing by external auditors during the accounting reports analysis. For the other three hypotheses (H3, H4 and H6), the relationship was not significant, both for the disclosure level of financial instruments (general) and for the disclosure level of credit risk (grounded on IFRS-09). Regarding the last hypothesis (H7), it was rejected. Following the theoretical review, we expected a positive relationship between countries’ Internet access and disclosure, but the empirical analysis indicated a negative relationship between these variables. As presented in the theoretical framework, Internet enables firms to present information in a flexible way and with low cost (Xiao et al., 2004; Kelton & Yang, 2008; Trabelsia et al., 2008; Gandía et al., 2012; Ojah & Mokoaleli-Mokoteli, 2012). Therefore, we highlight that companies have an important tool to disseminate information, but they do not necessarily use this channel to improve their interaction with shareholders / stakeholders and reduce information asymmetry. This result is more critical when we observe that firms of the mining sector naturally demand the use of derivatives to reduce their exposure to external risk factors. Complete information regarding the use of derivative contracts represents a challenge for these companies, regardless of where they are in Latin America.
5. Final Remarks Considering the complexity exposed by various users of financial information and other interested parties in this kind of report, as well as in its interpretation and effective use, the FASB
16
and the IASB had some initiatives to improve and simplify these requirements; the result is IFRS-09 (IASB, 2016). IFRS-09 brings more relevance to financial reports and contribute with transparency and market efficiency (Novotny-Farkas, 2016). Investors from developed economies have already evaluated positively this new standard (Onali & Ginesti, 2014). New requirements, such as expected credit loss instead of only incurred credit loss, improve the way of presentation of financial statements (Novotny-Farkas, 2016), which represent benefits of this statement. Nevertheless, even considering the relevance of this kind of information, the analysis of this paper indicates that companies from the sample study (of the four countries) have not anticipate this information yet, at least in its fully format. Some companies of the sample study are evaluating the effects of these standards. IFRS-09 requirements will be mandatory in 2018; therefore, a debate about the disclosure of these items by firms of the extractive industry is a major issue to be considered both in the academic studies and in practice. The results of this paper indicate a panorama not only about the disclosure of financial instruments by mining firms of Latin America, but we also indicate some challenges related with the implementation of IFRS-09 requirements to generate a more complete information to investors. We also report that these challenges will be higher for small firms, and for firms situated in countries with higher levels of Internet access, since Internet represents a channel that companies can use to facilitate their interaction with shareholders. Some limitations are present in this study, and the main one is that the disclosure level is affected by a set of variables; our quantitative model considers only seven factors to explain the disclosure index. Therefore, new research is needed to analyze IFRS-09 requirements with other determinants. The second limitation is the number of companies of each country, because this quantity may not represent the disclosure practices of the other companies. A third limitation is
17
related with the countries of the study, since there are other economies in Latin America; nevertheless, we selected those countries with more representation in the mining industry sector, and we used this this data to build a panorama regarding some challenges that could be faced by companies to provide complete information to their shareholders.
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Appendix A Disclosure Index #
Item / Category (Source) Credit Risk (Lopes & Rodrigues, 2007; IFRS-07)
1
Counterparties identification
2
Maximum amount of credit risk exposure
3
Significant concentration of credit risk
4
Credit Risk (IFRS-09) Method to determine credit losses
5
Quantitative and qualitative information on expected credit losses
6
Credit risk exposure and evaluation methods (reduction / increase)
7
Credit losses (twelve months)
8
Credit losses, incurred (twelve months or more)
9
Levels of credit risk
Derivatives - Accounting Policie (Lopes & Rodrigues, 2007; IFRS-07) 10 Risk management policy, including hedging policy 11 Objectives of holding or issuing derivatives 12 Accounting policies and methods adopted 13 Monitoring and controlling policy 14 Financial controls Derivatives - Financial Instruments (IFRS-07; IFRS-09)
24 15 Fair value of derivatives 16 Precedure embedded derivated 17 Level - fair values Derivatives - Risks (Lopes & Rodrigues, 2007; IFRS-07) 18 Segregation by risk categories 19 Principal, stated value, face value, notional value maturity 20 Weighted average/effective interest rate Hedge Accounting (IFRS-07; IFRS-09) 21 Strategy of risk management 22 How hedge activities can affect future cash flows 23 Effects of hedge accounting on income and on equity 24 Fair value hedge 25 Cash flow hedge 26 Net investment hedge Risk Management (IFRS-07; IFRS-09) 27 Emmergence of each risk 28 Management of each risk 29 Exposure to each risk 30 Instrument used to manage the risk 31 Efficacy of the risk management (method) 32 Method used to estimate the coverage ratio and inefficiencies Risk Management - Hedge with Derivatives (Chang et al., 2016; IFRS-07; IFRS-09) 33 Interest rates risk 34 Foreign exchange rate risk 35 Price risk (commodities) 36 Price risk (raw materials) 37 Liquidity risk 38 Credit risk Risk Management - Different of Credit Risk (IFRS-07; IFRS-09) 39 Other types of risk (beyond credit risk) 40 Sensivity analysis 41 Segregation of the effects (Income x Equity) Note: Each company receives a score = 1 for each item disclosed.
Figure 1:
25 Regulatory bodies of the countries studied Country
Regulatory board
Brazil
Comissão de Valores Mobiliados (CVM)
Chile
Superintendecia de Valores y Seguros (SVS)
Mexico
Comisión Nacional Bancaria y de Valores (CNBV)
Peru
Superintendencia del Mercado de Valores (SMV)
Figure 2: Countries’ characteristics regarding internet and quality of infrastructure 200
3.4
150
3.2
100
3.0
50
2.8 2.6
0
BR Internet Users
CH
PE
MX
Secure Internet Servers
BR
CH
PE
MX
Logistic Performance Index
Notes: Internet Users = Internet Users by 100 people; Secure Internet Servers = Secure Internet Servers per 1 million people; Logistic Performance Index = Logistic Performance Index. Source: Compiled from the database of The World Bank (2016).
Table 1: Descriptive statistics of the disclosure level, by country
26
Country
Discl. Fin. Instr.
Discl. IFRS 09
Mean
S.D.
Min.
Max.
Mean
S.D.
Min.
Max.
Brazil
44.762
25.951
14.286
85.714
27.778
11.785
16.667
50.000
Chile
43.636
21.217
8.571
82.857
19.697
14.704
0.000
50.000
Mexico
61.524
22.364
20.000
85.714
31.111
10.666
16.667
50.000
Peru
45.143
25.787
8.571
82.857
24.445
12.387
0.000
50.000
Table 2: Descriptive statistics of the variables in the sample Variables
Obs
Mean
S.D.
Min.
Max.
intaccess
72
57.336
8.940
40.900
64.289
intaccessdm
72
0.583
0.496
0.000
1.000
infrast
72
3.104
0.169
2.841
3.256
ifrastrdm
72
0.667
0.475
0.000
1.000
lnatuss
72
13.660
2.239
4.625
19.256
lev-tot
72
1.293
3.959
0.019
24.755
lev-st
72
0.686
2.802
0.000
21.280
lev-lt
72
0.607
1.647
0.000
13.647
prof-ni
72
-0.188
0.750
-4.946
0.410
prof-oi
72
-0.122
0.723
-4.946
0.637
audit
72
0.861
0.348
0.000
1.000
nyse
72
0.111
0.316
0.000
1.000
ifrs9
72
24.074
13.672
0.000
50.000
discl
72
47.817
23.643
8.571
85.714
Notes: intaccess = it represents the number of Internet users by 100 people of each country (source: The World Bank, 2016); intaccessdm = it is a dummy variable, and it receives 1 for firms from countries with higher Internet users index and 0 for the other cases; infrast = it represents the logistic performance index (overall, 1=low to 5=high) of each country (source: The World Bank, 2016); infrastdm = it is a dummy variable, and it receives 1 for firms from countries with higher logistic performance indexes and 0 for the other cases; lnatuss = it is the natural logarithm of Total Assets of each company, in US Dollars; lev-tot = it is the ratio between total liabilities and total assets; lev-st = short term leverage; lev-lt = long term leverage; prof-ni = the ratio between net income and total assets; prof-oi = the ratio between operational income and total assets; audit = it is a dummy variable, and it receives 1 for firms audited by one of the big four auditing companies and 0 for the other cases; nyse = it is a dummy variable, and it receives 1 for firms listed at the New York Stock Exchange; ifrs9 = it represents the disclosure index based only in the items from IFRS 09 (see also Appendix A); discl = it represents the disclosure index (see also Appendix A) based on the following sources: IAS 39, IFRS 07 and Lopes & Rodrigues (2007). Table 3: Regression analysis between disclosure and dummy variables for countries Variables Brazil Chile Mexico constant
Discl. Fin. Instr. Coef. P>t -0.381 0.972 -1.507 0.844 16.381 0.066 45.143 0.000 r2 = 9.04%
Discl. IFRS 09 Coef. P>t 3.333 0.504 -4.747 0.251 6.667 0.117 24.444 0.000 r2 = 11.31%
27 Notes: Brazil = it represents a dummy variable, where firms from Brazil receives 1 and the other cases receive 0; Chile = it represents a dummy variable, where firms from Chile receives 1 and the other cases receive 0; Mexico = it represents a dummy variable, where firms from Mexico receives 1 and the other cases receive 0; Peru = it represents a dummy variable, where firms from Peru receives 1 and the other cases receive 0. The variable “Peru” was omitted of this regression analysis to avoid perfect multicollinearity. Table 4: Regression analysis between disclosure of financial instruments and its determinants Variables Coef. P>t Brazil -11.909 0.113 Chile -13.680 0.062 Mexico 4.226 0.541 lnatuss 6.191 0.000 lev-tot 2.799 0.011 lev-st lev-lt prof-ni 11.345 0.038 prof-oi audit 10.743 0.218 nyse 1.248 0.829 constant -40.754 0.005 r2 = 43.67%
Coef. -9.996 -13.065 4.312 5.591
P>t 0.167 0.072 0.551 0.000
Coef. -9.946 -12.950 4.549 5.561
P>t 0.168 0.075 0.532 0.000
Coef. -10.387 -13.346 3.690 5.886 0.741
P>t 0.154 0.065 0.605 0.000 0.051
Coef. -9.640 -12.665 4.838 5.675
P>t 0.194 0.081 0.501 0.000
Coef. -11.652 -14.349 2.473 5.951
P>t 0.122 0.058 0.751 0.000
0.838 0.081 1.627 0.133 -1.936 0.316 10.539 0.221 2.009 0.745 -31.876 0.026 r2 = 41.59%
-1.858 0.333 10.394 0.225 1.960 0.753 -31.311 0.027 r2 = 41.56%
11.779 0.171 1.730 0.774 -37.239 0.011 r2 = 42.36%
11.209 0.199 1.701 0.780 -34.122 0.014 r2 = 42.07%
10.878 0.188 2.066 0.731 -36.541 0.019 r2 = 42.15%
Notes: the VIF statistic indicated a multicollinearity between the variables leverage and profitability (VIF = 10.69). Therefore, we estimate the models considering the effects of these variables separately.
Table 5: Regression analysis between disclosure (IFRS 09) and its determinants Variables Brazil Chile Mexico lnatuss lev-tot lev-st lev-lt prof-ni prof-oi audit nyse constant
Coef. 0.980 -8.978 3.539 2.100 -0.060
P>t 0.831 0.038 0.429 0.012 0.933
Coef. 0.939 -8.991 3.537 2.113
P>t 0.836 0.036 0.425 0.007
Coef. 0.981 -8.968 3.516 2.128
P>t 0.829 0.036 0.421 0.006
Coef. 0.878 -9.001 3.574 2.121 0.078
P>t 0.847 0.036 0.418 0.009 0.784
Coef. 0.969 -8.923 3.689 2.105
P>t 0.832 0.037 0.396 0.006
Coef. 0.813 -9.042 3.562 2.104
P>t 0.861 0.040 0.460 0.017
0.109 0.715 0.098 0.917 -0.757 0.830
-0.474 0.744
4.488 0.348 -5.048 0.178 -4.733 0.652 r2 = 24.82%
4.492 0.345 -5.064 0.169 -4.922 0.617 r2 = 24.82%
-0.750 0.597 4.665 0.314 -5.099 0.167 -5.280 0.581 r2 = 24.89%
4.419 0.348 -5.080 0.167 -4.967 0.633 r2 = 24.80%
4.413 0.341 -5.093 0.167 -4.793 0.616 r2 = 24.81%
Notes: we used the same quantitative models available on Table 4 to construct this table. Table 6: Regression analysis between disclosure and countries’ characteristics
4.244 0.358 -5.043 0.172 -4.522 0.683 r2 = 24.78%
28
Variables lnatuss lev-tot audit nyse intaccessdm infrastdm constant
Discl. Fin. Instr. Coef. P>t 6.018 0.000 0.786 0.062 11.319 0.181 3.029 0.601 -14.637 0.001 0.440 0.925 -37.245 0.011 r2 = 42.01%
Discl. IFRS 09 Coef. P>t 2.387 0.006 0.167 0.664 3.487 0.515 -2.451 0.505 -7.720 0.013 -3.001 0.392 -4.978 0.657 r2 = 20.46%
Table 7: Expected signs versus observed signs in the hypotheses testing Variables Size Leverage Listing Status Profitability Auditor (Big four) Infraestructure Internet Access
Hypotheses H1 H2 H3 H4 H5 H6 H7
Expected Sign + + + + + + +
Observed Sign + ; + + ; n.s. n.s. ; n.s. n.s. ; n.s. n.s. ; n.s. n.s. ; n.s. − ; −
Notes: + : indicates a positive and statistically significant relationship; − : indicates a negative and statistically significant relationship; n.s.: indicates a relationship not significant between the variables.