# Has mandating XBRL in the United Kingdom increased comparability of financial statements with other firms in the United States? (An empirical research)

01 May 2020    39 mins read.

Image Credits:Markus Spiske from Unsplash

## Abstract

This dissertation is an empirical analysis of whether comparability of financial statements increased, following the mandate of XBRL in the UK by the government in 2011. XBRL is an open standard for the exchange of financial information in digital form. It involves the application of computer-readable tags to business data, enabling the efficient and automatic processing of these data. Over the past decade, XBRL as a technology has been touted to be important for the future of digitisation in corporate reporting, prompting its adoption by regulators around the world. Furthermore, the thought pattern of present literature indicates that, XBRL will lead to higher levels of disaggregation and standardisation of financial reporting amongst industry peers for comparability. The literature nonetheless, currently lacks a comprehensive quantitative or qualitative research, that examines the impact of XBRL on comparability of financial statements. The study pairs and compares the financial statements of firms in the UK to the reports of firms in the US. Comparability scores for the paired firms are empirically calculated using De Franco et al’s. (2011) model. Two tests are conducted for a total of Sixty-four firms (or thirty-two pairs), and the experiment is performed over twenty-four quarters of data covering the period pre- and post- XBRL mandate. The results of the experiment from both tests point to a decrease in the comparability of financial statements, contradicting the hypothesis suggested by the literature. This raises the question as to whether this was due to the misuse of taxonomy or because of the novelty of the standard alluded to by some of the literature. The findings of this study should therefore, not be taken as a definitive answer to the research question but rather, used as evidence for further and wider studies.

## Section 1 – Introduction

### 1.2 - Aims and Objectives

The aims and objectives of this study is to research whether the comparability of financial statement for firms in the UK and US has increased, following the mandate by both countries in 2011. I focus on IFRS firms in the UK and contrast them to GAAP firms from the US. The approach for measuring this, is based on De Franco et al’s. (2011) empirical model for measuring comparability of Financial statements. This model was developed from the definition of Comparability in the IASB’s Conceptual Framework and is further explained in the methodology section later. Upon completion of this research, the question of whether comparability of financial statements for UK and US firms have increased post-XBRL mandate will hopefully be answered. This is an important question to answer as increase in the comparability of financial statements consequently lead to increase in the overall quality of Financial statements. Further implications of the findings are elaborated on, in the literature review section of this dissertation.

### 1.2 - Motivation

I was first introduced to XBRL during my placement year and was part of the team in charge of tagging the firm’s financial statement for submission to HMRC. My first-hand experience with the standard piqued my curiosity, leading to me exploring the impact it has had in the financial world thus far. Furthermore, its high relevance to the degree combination of ‘Accounting, Finance & Computer Science’ I am studying was another motivating factor for me.

### 1.4 - Guide to Study

In section 2 of this study, existing literatures on the topics of XBRL and comparability of financial statements will be reviewed and critically analysed. This will allow for an insight into the theoretical association of XBRL and comparability of financial statements leading to the motivation of this study. Section 3 will describe the methodology used to answer the research question. It would explain the rationale behind the choice of method chosen and evaluate alternative choices. The approach to answering the question is then outlined and any assumptions made during the study are explained. Finally, the data gathering, and sample selection process is described thus providing the steps necessary to replicate the tests. In Section 4, the findings of the tests will be commented on. Comparisons to other relevant studies will be made, providing a wider context. The limitations of the results will also be commented on. Section 5 will summarise the research and results found. The contributions of this dissertation to existing literature will be highlighted and potential future research will be suggested.

## Section 2 – Literature Review

### 2.1 - Introduction

In this section, literature on the topics of XBRL and comparability of financial statements will be reviewed and critically analysed. The literatures have been sourced from a mix of academic journals, reputable newspaper articles and government publications. Some papers from XBRL UK Limited, the UK jurisdiction of the XBRL International consortium have also been reviewed. It will begin by exploring what XBRL is and why it is important for reporting in the digital age. Then, it would explore the comparability of financial statements, including its importance, impact in the financial world and how international standards have helped improve this. This is followed by an elaboration on the theoretical association between XBRL and comparability of financial statements leading to the motivation of this research topic.

### 2.3 - The need for XBRL

According to Horgan (2019), from the insight centre for Data analytics, we create 1 exabyte of data every six hours. For reference, an exabyte of data is greater than all the text content and digital collection of the library of congress; - the largest library in the world (Johnston, 2012). This sheer volume of data, much of it irrelevant to a given user’s present needs, may hinder that user’s acquisition of relevant data for decision making. The data processing abilities of humans are simply limited, and as Hirshleifer and Teoh (2003) would argue, this may force a user to make decisions based on incomplete information. Using the interactive tags found within the XBRL format of a financial report, a user can easily find relevant information for decision making (Yoon, Zo and Ciganek, 2011). This assumption was initially asserted by Hodge, Kennedy and Maines (2004), who found that users, even non-professional financial report users, are more likely to acquire decision- relevant information using XBRL-enabled search engines. The ease of acquisition for financial analysis tasks obtained from financial statements using XBRL is also argued by Janvrin, Pinsker and Mascha (2013), in addition to increase in information transparency. Furthermore, results from the study of ‘XBRL and qualitative characteristics of useful financial information’ by Birt, Muthusamy and Bir (2017), reveal that XBRL users of tagged information, find XBRL to be more relevant compared to PDF users in their profit-forecasting decisions. Overall, literature indicates that XBRL-enabled filings will enable users to search and obtain relevant information more quickly and efficiently, thus potentially solving the problem of navigating vast amounts of data. Nevertheless, a company’s financial statement information is often not analysed in isolation. On the contrary, it is frequently compared to its peers and as such, there is a degree of importance to its comparability. To gain a better understanding of the impact of comparability in financial statement reporting, related literature will be examined in the next section.

### 2.4 - Comparability of financial statements

Comparability of financial statements is often positively correlated to the quality of disclosures and resolution of investor uncertainty, partially motivating the mandatory adoption of IFRS in most countries worldwide including the UK and US (Tarca, 2018). According to the IASB’s Conceptual Framework, comparability is described as the qualitative characteristic that enables users to identify and understand similarities and differences among at least two items (IASB, 2015, CF2.24). Additionally, information contained within the financial report of an entity is considered to be useful if it can be compared to similar information about other entities or itself over time (IASB, 2015). The general consensus provided by the literature on comparability of financial statements is positive. A study conducted by Li (2016) for instance, analysed the economic consequences of comparability through the examination of its effect on investment efficiency, and found that a higher level of comparability can mitigate investment inefficiency. Furthermore, it is argued that financial statement comparability lowers the cost of acquiring information and increases the overall quantity and quality of information available to analysts about the firm (De Franco, Kothari and Verdi, 2011). If comparability helps investors understand firm- specific information, then surely, it would be useful to investors in evaluating alternative investments. Other stakeholders of financial statements such as auditors also benefit from increased comparability. Kang et al., (2014) conducted a research on a sample of firms maintaining a certain level of audit quality, where they investigated whether financial statement comparability reduces audit hours. They found that comparability is negatively associated with audit hours meaning a higher level of comparability resulted in less hours spent auditing an account. Comparability of financial statements has previously been improved through the mandatory adoption of IFRS as similar things look more alike without making different things look less different. Additionally, accounting convergence and higher quality information under IFRS were likely drivers of its improvement (Yip and Young, 2012). In the next section, literature on the theoretical association between XBRL and comparability of financial statements will be reviewed.

## Section 3 – Methodology

### 3.1 - Introduction

To answer the research question raised from the literature review earlier, an empirical analysis of quantitative data to measure comparability of financial statements, originally developed by De Franco et al. (2011) will be used. Whilst comparability in financial reporting is not a directly measurable phenomenon as a result of it not being a well-defined concept (Barth et al., 2014), various empirical methods to measuring it have been developed and these will be discussed in this section. An empirical approach to measuring comparability will be used for this study because it is output-based and firm-specific. Additionally, it can be calculated using widely available company financial statement and data. In contrast, the alternative use of qualitative input- based definitions of comparability such as business activities or accounting methods can be challenging, as one must decide which accounting choices to use, how to account for variation in their implementation and how to weigh them. Moreover, other complications linked to differing accounting standards could arise, given this research’s aim to analyse the financial statement of firms using two different standards (GAAP in US and IFRS in the UK). Another advantage of using the chosen empirical approach to measure comparability during this research is that it does not require all firms to follow the same standard. Comparability of financial statements has been of significant interest to empirical financial accounting research (Gross and Perotti, 2017). The empirical methods developed by various researchers (Lang, Maffett and Owens, 2010; Jayaraman and Verdi, 2014), involve looking at the similarity of correlations between accounting data for different firms. Increase in similarity of correlations is taken to be evidence of an increase in comparability and vice versa. Underlying these correlation studies is the idea that accounting is an attempt to portray economic reality. Therefore, it is helpful to see how some independent measure of economic reality compares with accounting measures. Shareholders’ equity and cash flows are frequently taken to be examples of such independent measures within the studies. As such, the Correlations between a firms’ earnings (or other accounting measure) and one of these aforementioned independent measures is first calculated. The correlations show how accounting measurements portray economic reality for the companies in question (ICAEW, 2015). The figures obtained are then compared to the same correlations for other sets of firms. As a great similarity between the correlations, indicates a great similarity between the way two companies’ financial statement data map to economic reality, it is therefore assumed that the financial reporting for those two firms have greater comparability.

### 3.2 - Analysis of the empirical model used

As alluded to earlier, the empirical research model used in this dissertation is based on the model developed by De Franco et al. (2011) in their study; “The Benefits of Financial Statement Comparability”. It is arguably the most influential paper on empirical financial accounting research of comparability in recent years (Gross and Perotti, 2017). Their comparability measure is based on the theory that ‘for a given set of economic events, two firms have comparable accounting systems if they produce similar financial statements’ (De Franco et al., 2011). In order to employ this concept of measuring similarity through earnings, De Franco et al. (2011) use earnings as a proxy for the financial statement output. To control and account for economic events, they use stock return as proxy for economic events. Consequently, a linear function of earnings to returns is assumed and they estimate the parameters of this function through firm-specific time-series regressions. By holding the economic events for two firms under observation constant, a pairwise comparability score that is not biased by any economic dissimilarity of these firms is yielded. The yielded score between a firm and its benchmarks in the same industry are then aggregated into a firm-year-specific summary measures, which are calculated as the mean or median of the company’s comparability. Whilst there are numerous benefits to using this model as discussed, there are a couple of limitations that come with using it. First, De Franco et al.’s (2011) empirical method for measuring comparability requires the use of stock returns. This means that only publicly listed companies can be observed as the measure is inapplicable to unlisted entities. Nevertheless, this limiting effect has little repercussions on the scope of this research as I intend to use publicly available data of listed companies in the UK and the US. Secondly, the differences in stock price efficiency across peer firms can affect return comparability (Gross and Perotti, 2017), thereby influencing the measure. As such, it will be assumed during the research, that peer firms have similar stock price efficiency. Finally, DeFranco et al. (2011) implicitly assume that firms belonging to the same industry have the same economic comparability. This may not always be the case as differences in economic comparability may exist for firms within an industry in the same accounting period. (Gross and Perotti, 2017).

### 3.3 - Approach

The Accounting system comparability model will be replicated. This is represented as: $$𝐹𝑆_i = 𝑓_i(𝐸𝐸_i)$$ Where;

• $$𝑓_i()$$: represents the Accounting function of firm i,
• $$𝐸𝐸_𝑖$$: represents the Economic events of firm i, and
• $$𝐹𝑆_𝑖$$: represents the Financial statements of firm i

Similarly to Mukai (2017), net income before income taxes will be used as a proxy for the financial statement output because it is generally used as an indicator of key performance. More specifically, the ratio of quarterly net income before extraordinary items to the beginning-of-period total assets (Earnings) as a proxy for Financial Statement will be used. For Economic Events, I will be using stock return as proxy. As these economic events could be either unique to the firm or due to economy or industry-wide shock, I will also be using cash flows from operating activities as proxy. It is arguable that where cash flow is used as a measure of economic reality based on a one-to-one correspondence between accounting income and cash flow, it is implied that accrual accounting is no longer being used. Whilst this point is correct, as long as firms use accrual accounting it purely raises a hypothetical possibility (ICAEW, 2015). As such, the empirical tests are conducted for two cases; 1) Where stock return is used as proxy and 2) where cashflow is used as proxy. Information comparability is subsequently analysed stepwise. For each firm, I will first estimate its accounting functions using 8 quarters of data pre and post XBRL adoption separately. Reporting in XBRL was mandated in the UK for companies from the 1st April 2011 (Financial Times, 2010) and in the US from the 25th of June 2011. Nevertheless, I will be using the cut-off date of 30th June 2011 as this will make analysis a little less intricate whilst having minimal effect. As such, quarterly data for companies up-till 30th June 2011 will be considered pre XBRL and quarterly data for companies on or after the 1st July 2011 will be considered post XBRL. The Equation used to estimate the accounting functions are as follow:

$$𝐸𝑎𝑟𝑛𝑖𝑛𝑔𝑠_{𝑖𝑡} = 𝛼_𝑖 + 𝛽_𝑖 𝐸𝐸_{𝑖𝑡} + 𝜀_{𝑖𝑡}$$ $$𝐸𝑎𝑟𝑛𝑖𝑛𝑔𝑠_{𝑗𝑡} = 𝛼_𝑗 +𝛽_𝑗 𝐸𝐸_{𝑗𝑡} +𝜀_{𝑗𝑡}$$

For ‘Earnings’, the proxy for Financial Statement (quarterly net income before extraordinary items) mentioned earlier is used. For ‘EE’, the stock price return during the quarter is used for the first case test and Cash flow during the quarter is used for the second case test. $$\ 𝛼_𝑖 \$$ & $$\ 𝛽_𝑖 \$$ (equation 2) proxy for the accounting function 𝑓(•) under the framework in equation (1). Similarly, the accounting function for paired firm J is proxied by $$\ 𝛼_𝑗\$$ & $$\ 𝛽_𝑗\$$ (equation 3) and estimated using earnings, and return or cash flow for firm J. The comparability between two firms is represented by the closeness of the functions between these two firms. To estimate the distance between functions so as to consequently measure comparability, De Franco et al. (2011) invoke one implication: “if two firms have experienced the same set of economic events, the more comparable the accounting between the firms, the more similar their financial statements”. As such, the next step will be to calculate the predicted earnings for firm I and paired firm j using the estimated accounting function from the earlier step. More precisely; the estimated accounting functions for each firm is used with the economic events of a single firm. By using only one firm’s return in both predictions, the variations in economic events is held at a constant and thus accounted for. Therefore, we calculate:

$$𝐸(𝐸𝑎𝑟𝑛𝑖𝑛𝑔𝑠_{𝑖𝑖𝑡}) = 𝛼_𝑖 + 𝛽_𝑖 𝐸𝐸_{𝑖𝑡}$$ $$𝐸(𝐸𝑎𝑟𝑛𝑖𝑛𝑔𝑠_{𝑖𝑗𝑡}) = 𝛼_𝑗 + 𝛽_𝑗 𝐸𝐸_{𝑖𝑡}$$

$$\ 𝐸(𝐸𝑎𝑟𝑛𝑖𝑛𝑔𝑠)_{𝑖𝑖𝑡} \$$ in equation 4 is the predicted earnings for firm I given its function ($$\ 𝛼_𝑖 + 𝛽_𝑖 \$$) and return in period t. And $$\ 𝐸(𝐸𝑎𝑟𝑛𝑖𝑛𝑔𝑠)_{𝑖𝑗𝑡} \$$ in equation 5 is the predicted earnings for paired firm j given its own function ($$\ 𝛼_𝑗 + 𝛽_𝑗 \$$) and the return of firm i in period t. In the third step, I calculate the comparability between firm I and paired firm j as the negative value of the average absolute differences between the predicted earnings using the accounting functions of both firms. Hence: $$𝐶𝑜𝑚𝑝𝐴𝑐𝑐𝑡_{𝑖𝑗𝑡} = −1 \times 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 | (𝐸(𝐸𝑎𝑟𝑛𝑖𝑛𝑔𝑠_{𝑖𝑖𝑡}) − 𝐸(𝐸𝑎𝑟𝑛𝑖𝑛𝑔𝑠_{𝑖𝑗𝑡}) |$$ For each pair of firms, the comparability scores are measured before XBRL mandate using respective financial statement data before 30th June 2011, and after XBRL mandate using respective financial statement data on or after 1st July 2011. Thus: $$𝑃𝑟𝑒𝐶𝑜𝑚𝑝𝐴𝑐𝑐𝑡_{𝑖𝑗𝑡} = −1 \times 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 |( 𝐸(𝐸𝑎𝑟𝑛𝑖𝑛𝑔𝑠_{𝑖it,pre}) − 𝐸(𝐸𝑎𝑟𝑛𝑖𝑛𝑔𝑠_{𝑖𝑗𝑡,𝑝𝑟𝑒}) |$$ $$𝑃𝑜𝑠𝑡𝐶𝑜𝑚𝑝𝐴𝑐𝑐𝑡_{𝑖𝑗𝑡} = −1 \times 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 | (𝐸(𝐸𝑎𝑟𝑛𝑖𝑛𝑔𝑠_{𝑖𝑖𝑡,𝑝𝑜𝑠𝑡}) − 𝐸(𝐸𝑎𝑟𝑛𝑖𝑛𝑔𝑠_{𝑖𝑗𝑡,𝑝𝑜𝑠𝑡} ) |$$

In the final step, the comparability measures are compared for the pre-XBRL period and the post-XBRL period. If $$\ 𝑃𝑜𝑠𝑡𝐶𝑜𝑚𝑝𝐴𝑐𝑐𝑡_{𝑖𝑗𝑡}\$$ is greater than $$\ 𝑃𝑟𝑒𝐶𝑜𝑚𝑝𝐴𝑐𝑐𝑡_{𝑖𝑗𝑡}\$$ then this is evidence that the information comparability between firm I and paired firm j increased after XBRL adoption. If the opposite occurs, $$\ (𝑃𝑟𝑒𝐶𝑜𝑚𝑝𝐴𝑐𝑐𝑡_{𝑖𝑗𝑡}\$$ is greater than $$\ 𝑃𝑜𝑠𝑡𝐶𝑜𝑚𝑝𝐴𝑐𝑐𝑡_{𝑖𝑗𝑡}\$$ ) then this is an indication of a decrease in comparability after XBRL adoption.

### 3.4 - Sample selection

The data used will be sourced from Osiris, a database of publicly listed companies worldwide. Osiris is maintained by ‘Bureau Van Dijk’, a Moody’s analytics company and as a result is reliable. The sourced open and freely accessible data to the public, can also be found on the websites of the respective governments (UK and US). For the UK at: http://download.companieshouse.gov.uk/en_accountsdata.html and for the US at: https://www.sec.gov/dera/data/financial-statement-data-sets.html. As I am comparing the financial statements of firms using IFRS (in the UK) to those using GAAP (in the US), an equal number of firms is sourced from both listings. I focus only on firms in the Consumer Staples industry firstly because of feasibility, given the breadth and scope of this research and secondly because of their relatively low volatility (Menton, 2019). Only those firms whose fiscal year end in March, June, September, and December are also sourced. The firms are then paired based on their peer group number, Global Industry Classification Standard (GICS) code and Operating revenue. Additionally, the figures being used in the data are the ones from the XBRL filings. Afterall, the goal of the research is to find whether XBRL mandate has had an effect on comparability and in doing so, track the impact of potential incorrect use of taxonomies mentioned earlier in the literature. After this extensive exercise of sifting through a significant number of financial statements, I ended up with a total of Sixty-four firms (or Thirty-two pairs). For each of the firms, twenty- four(24) quarters of data is gathered, covering the time period 2009 to 2014. Alteryx, a data blending and analytic software is used in the experiment in order to facilitate the calculation and processing of data. A copy of the workflow built as a result of this research has been uploaded online for public accessibility and future re-use at: https://github.com/inimaga/XBRL-ComparabilityDA.

For more details on the data and alteryx workflow, please see appendix section.

## Section 4 – Findings and interpretations of findings

...

## Section 5 – Conclusions

### 5.1 - Summary

Two main tests were conducted in this study in an attempt to empirically answer the question of whether the 2011 mandate of XBRL in the UK by HMRC, and in the US by the SEC, improved comparability of financial statements. An equal number of company data from both countries were sourced. The consumer staples industry was chosen as the focus of the study due to its relatively low volatility. The sourced firms are paired based on their peer group, Global Industry Classification Standard (GICS) code and Operating revenue. The comparability scores for the paired firms were then empirically calculated using De Franco et al’s. (2011) model as a framework. This model involves looking at the similarity of correlations between accounting data for a paired set of comparable firms. Increase in similarity of correlations is taken to be evidence of an increase in comparability and vice versa. Underlying the correlation study is the idea that accounting is an attempt to portray economic reality. For the first test, the shareholders’ equity or return is used as a proxy for economic events and the comparability scores for each firm is computed based on 24 quarters of data. The achieved scores in the period pre-XBRL mandate are averaged then compared to the achieved scores post-XBRL. Upon examination of the obtained results, it is observed that the comparability levels for the financial statements of UK and US firms declined following XBRL mandate. In the second test, the same exercise is repeated but this time, cash flow is used as a proxy for economic events. Upon computation of the comparability scores, again based on 24 quarters of data, the achieved scores indicated a bigger decline post-XBRL mandate. Nevertheless, the average scores of comparability levels when broken down by years, showed a stable recovery pattern, after initially declining in 2011, the year XBRL was mandated. The results of the experiment from both tests point to a decrease in the comparability of financial statements for UK and US firms following XBRL mandate in 2011. These contradict the views of Vasarhelyi, Chan and Krahel (2012) who argued that “XBRL will lead to higher levels of disaggregation and standardization of financial reporting data among industry peers for comparability and consistency”. A potential reason for the observed decline could be attributed to the improper use of taxonomies highlighted by the research/study of Debreceny et al., (2010). Perhaps, it is why Dhole et al. (2015), in their study found that US firms extensively used extensions for 10-K and 10-Q reports in the initial years following the XBRL mandate by the Securities and Exchange Commission (SEC). Although this research is limited by the use of reported earnings as a key financial metric, the use of a single financial statement item allowed the analysis to be both tractable and parsimonious. The sample size of observable firm used in this research together with the time frame is another limiting factor of this study. Nevertheless, for the criteria the tests were conducted under, this study has shown that the mandate of XBRL led to a decline in comparability of financial statements, at least in the initial years. This is not to say that, this would continue to be the case as the novelty of the standard might be responsible for this. As such, the findings of this study should not be taken as a definitive answer to the research question but rather, it should be used as evidence for further and wider studies.

### 5.2 - Implications, Contributions and Recommendations for future Studies

The implications from the results found in this study are that the adoption of XBRL, following its mandate in both the UK and US, led to a decline in the comparability of financial statements. This raises the question as to whether this was due to the misuse of taxonomy or because of the novelty of the standard. To address the limitations of this study, it is recommended that the tests in this study be repeated again using a larger and more diverse sample set. The experiment should also be carried out over a longer time period post XBRL to get a wider and more appreciative picture of what happened. Additionally, the use of taxonomy should be examined in parallel to the conducted tests. This should hopefully answer the question of whether the mismatch was due to taxonomy usage and give a much higher level of credibility to the findings. It is also recommended that the research be repeated using a qualitative methodology to measure comparability. This would allow for the capture of some omitted variables out of the scope of this research, and thus lead to a more practical answer. This dissertation contributes to the current literature in the following three main ways. First, it examined how XBRL technology can lead to increase in the comparability of financial statements amongst firms and consequently, the improvement in quality of information. Secondly, it empirically evaluated whether the mandate of XBRL in the UK by HMRC, and in the US by the SEC, improved comparability of financial statements. Finally, it speculated on the reasons for the achieved result and proposed further areas of study and research.

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## Appendices

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