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Review of Accounting Studies

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21.11.2016

The impact of the institutional environment on the value relevance of fair values

verfasst von: Peter Fiechter, Zoltán Novotny-Farkas

Erschienen in: Review of Accounting Studies | Ausgabe 1/2017

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Abstract

Most prior studies attribute valuation discounts on certain fair valued assets to measurement error or bias. We argue that institutional differences across countries (e.g., information environment or market sophistication) affect investors’ ability to process and impound fair value information in their valuation. We predict that the impact of the institutional environment on value relevance is particularly pronounced for reported fair values of assets designated at fair value through profit or loss (hereafter, “FVO assets”), for which investor experience is lowest and complexity is highest. Using a global sample of IFRS banks, we find that FVO assets are generally less value relevant than held-for-trading assets (HFT) and available-for-sale assets (AFS). By partitioning countries into market- and bank-based economies to proxy for institutional differences, we find that the valuation discount on FVO assets is more pronounced in bank-based economies. Additional tests suggest that this valuation discount is attenuated by a richer firm-level information environment and the presence of institutional investors with fair value experience.

Vorheriger Artikel The effects of audit partner pre-client and client-specific experience on audit quality and on perceptions of audit quality

Nächster Artikel Voluntary fair value disclosures beyond SFAS 157’s three-level estimates

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We focus on FVO assets rather than FVO liabilities because the interpretation of coefficient estimates for FVO liabilities is difficult, as it is not clear whether and how investors impound own credit risk (OCR) adjustments. In addition, our descriptive statistics (see Section 4.2) suggest that the FVO is selected less frequently for liabilities than for assets. However, for completeness and comparability, we also include financial liabilities in our empirical analyses, and the results for liabilities are consistent with our main inferences.

During the standard setting process, 9%, 15%, and 18% of the comment letters explicitly expressed concerns that the application intent underlying the FVO is unclear, that economically identical transactions can be differently accounted for under the FVO, and that the FVO might be applied inappropriately, respectively. In the second round, 28% of all comment letters argued that the FVO is simply too complex (source: own data analysis of comment letters to revision of IAS 39 in 2002 and 2004).

The FVO (in its revised and thus internationally comparable version) is applicable for annual periods on or after January 1, 2006. Therefore, the earliest data on the FVO was available as of December 31, 2006.

For an extensive review of the IFRS literature on fair value accounting, see Section 9.1 in the survey of De George et al. (2016).

The FVO can be elected if one of the following three criteria is satisfied (IASB 2006): (1) the application of the FVO eliminates or significantly reduces accounting mismatches; or (2) a group of financial instruments is managed and its performance is evaluated on a fair value basis; or (3) a financial instrument contains one or more substantive embedded derivatives. Under IAS 39, there are no transition provisions for the application of the FVO such as under FAS 159 (FASB 2007) so that only newly recognized positions are eligible for the FVO. Therefore, strategical election of the FVO as shown by Song (2008) is not possible.

We do not use the Ball et al. (2000) dichotomous classification of countries into code law versus common law systems, because all countries in our sample apply IFRS. We also do not classify countries into outsider and insider economies (Leuz et al. 2003), because relevant data are missing for numerous countries in our sample.

Indirect evidence of professional information intermediaries having more comfort in using and processing fair values is provided in Bischof et al. (2014), who show that analysts specifically demand fair value information during conference calls, particularly during the crisis period and when fair value related disclosure is weak.

The data can be downloaded at: http://econ.worldbank.org/WBSITE/EXTERNAL/EXTDEC/EXTRESEARCH/0,contentMDK:20,696,167~pagePK:64,214,825~piPK:64,214,943~theSitePK:469,382,00.html. We use the November 2013 version of the dataset.

Following Beck and Levine (2002), we average the data over a 10-year period. We use a 10-year period that ends just before the worldwide introduction of IFRS; we thereby create an ex ante classification of countries that is neither affected by macroeconomic effects of IFRS adoption nor influenced by the financial crisis. However, our inferences hold when we use alternative, more recent periods to calculate Structure_Aggregate.

We partition the sample instead of using interaction terms, as we use both sample partitions and interaction terms for the additional tests on the role of the firm-specific information environment and institutional investors. However, our main inferences hold when we use interaction terms between Financial_Structure and FVO_PS, HFTA_PS, and AFS_PS, respectively (see also Section V).

We do not use share prices later than March 31, as new information in connection with the first quarter earnings announcements may be available to investors.

When using standard errors clustered by country, our inferences remain similar, although this clustering changes the significance levels of some coefficients.

The regression results remain virtually constant when we control for differences in bank business models (i.e., regional, savings and loans, money center, and investment banks). In addition, the findings hold when we exclude investment banks from the sample.

Following the design of Song et al. (2010), we interact High_Info only with the variables of interest (i.e., FVOA_PS, HFTA_PS, and AFS_PS) to mitigate multicollinearity issues.

Prior literature finds that these variables are associated with stronger information environments (e.g., Leuz and Verrecchia 2000; Maffett 2012).

These banks do typically not distinguish between FVO and HFT assets despite the requirements of IFRS 7 (IASB 2007, para. 8).

Data on institutional shareholders are from SNL Financial. Because of missing data on the percentage of shares held by institutional investors in SNL Financial, the sample is reduced to 688 observations in that analysis.

To reduce heterogeneity in institutional factors (e.g., legal environment, political order, and culture), we conduct additional tests for a subsample of European banks (627 observations) for which heterogeneity between countries is likely smaller than in the worldwide sample. The findings from the European subsample confirm our main inferences.

For comparison, in Beck and Levine (2002), the variable Structure_Aggregate indicates that these countries are bank-based. Although Beck and Levine (2002) also use data from the World Bank, they calculate Structure_Aggregate by using data averaged from 1980 to 1989, whereas our reference period is from 1995 to 2004. The change in classification of France, Italy, and Spain suggests that these countries have experienced a larger growth in their stock markets relative to their banking systems over the past two decades.

Because of the short holding period for HFT assets, fair values are likely close to their amortized cost. In addition, unrealized gains and losses are likely offset by internally hedged positions in the trading portfolio. Thus our interpretation of these findings relies on the assumption that fair values of HFT assets differ from their amortized cost. Given our sample period, which includes the 2008 financial crisis, this assumption appears valid.

We test for differences in coefficients across subsamples with seemingly unrelated regressions using Wald Chi-square tests.

Consistent with our findings for FVO assets, the value relevance of FVO liabilities (FVOL_PS = −0.620) is lower than that of HFT liabilities (HFTL_PS = −1.079) in bank-based economies (F-stat = 14.90) but not in market-based economies (F-stat = 0.34).

Another concern is that relatively few banks have non-zero FVO assets: 58.3% and 42.6% in market- and bank-based economies, respectively. To test whether our inferences are driven by different proportions of banks applying the FVO, we exclude banks with zero FVO assets. The results are consistent with our main findings. While FVO assets are less value relevant in bank-based economies (coefficient = 0.260, t-stat = 0.89) than in market-based economies (coefficient = 0.863, t-stat = 9.53), HFT and AFS assets are value relevant in both institutional environments.

In addition, the untabulated interaction term between FVOL_PS and market-based economies of −0.242 (t-stat = −2.15) and the stand-alone coefficient of −0.691 (t-stat = −5.71) indicate a higher value relevance of FVO liabilities in market-based economies.

Because the proxy for firm-level information environment is positively correlated with firm size, we test whether our inferences are driven by differences in bank size. Following Song et al. (2010), we distinguish between large and small banks. We define banks as large (small) if the total assets denominated in USD are above (below) the sample median. For all samples, we find no significant differences between the valuation coefficients (not reported) for large and small banks. Specifically, FVO assets are substantially less value relevant in bank-based economies, consistent with our main findings. In addition, inferences remain when using interaction terms between above median size and fair value categories.

Somewhat unexpected are the negative interaction terms HFTA_PS*INST_Nordic and AFS_PS*INST_Nordic in the full sample and the market-based subsample, respectively. However, the joint coefficients HFTA_PS + HFTA_PS*INST_Nordic and AFS_PS + AFS_PS*INST_Nordic are not significantly different from 1 (F-stat = 0.32 and 0.96, respectively).

Our tests implicitly assume that the definition of Level 1 does not systematically vary across institutions. For example, if the definition of “active market” is less strict in bank-based than in market-based economies, Level 1 fair values in bank-based economies contain generally more measurement error. However, because Level 1 is defined as unadjusted market prices, measurement error or bias should be minimal. We also run robustness analyses focusing on asset types for which the definition is unlikely to vary across institutions (e.g., debt securities vs. equity securities). Inferences from the asset type regressions confirm our findings.

The sample size in Panel A is substantially reduced to 140 observations because (a) disclosure of the valuation hierarchy is required only for periods beginning on or after January 1, 2009 (IASB 2009, para. 44G); (b) even under the revised IFRS 7, disclosure of valuation inputs across IAS 39 categories is not mandatory; and (c) to compare fair value measurement inputs across categories, we require observations to have non-zero HFT, AFS, and FVO assets. The sample size in Panel B of Table 8 is larger, as we do not apply restriction (c) to the value relevance tests.

However, this test might lack statistical power. We also run a pooled regression with a three-way interaction term between FVO_INC, Persistent, and Bank_Based to examine whether the ability of fair values to reflect the persistence of underlying cash flows is different across institutional regimes. Our untabulated results show that this interaction term is positive, but statistically insignificant. In addition, untabulated findings do not indicate a statistical difference in the persistence of income from FVO assets between market- and bank-based economies.

Because we also find that FVO assets contain relatively more loans (15.6% and 7.7% for market-based and bank-based economies, respectively) than HFT or AFS assets, we test whether our inferences are driven by investors perceiving fair valued loans as less value relevant. We interact FVOA_PS with a dummy variable LOAN that equals 1 if the bank applies the FVO to loans (among other asset classes), and 0 otherwise. Untabulated results show that, in market-based economies, the interaction term is significantly negative, indicating that investors perceive FVO assets as less value relevant if also applied to loans. However, in bank-based economies, the coefficient on the interaction term is insignificant, and thus our main inferences are not driven by fair valued loans.

We define a bank as low capitalized when the difference between total regulatory capital ratio (BCBS 2006b) and the minimum capital requirement of the bank’s country of domicile is below the 25th percentile (i.e., 2.2%). Inferences do not change when we alternatively define banks as low capitalized when the difference between the regulatory capital ratio and the minimum capital requirement is below the 10th percentile (i.e., 1.1%).

We define mortgage-backed securities, Alt-A investments, collateralized debt obligations, and leveraged finance products as crisis-sensitive investments (see, e.g., Financial Stability Forum 2008).

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Titel: The impact of the institutional environment on the value relevance of fair values
verfasst von: Peter Fiechter
Zoltán Novotny-Farkas
Publikationsdatum: 21.11.2016
Verlag: Springer US
Erschienen in: Review of Accounting Studies / Ausgabe 1/2017
Print ISSN: 1380-6653
Elektronische ISSN: 1573-7136
DOI: https://doi.org/10.1007/s11142-016-9378-7

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