Tax Avoidance and Tax Disclosures in Corporate Social Responsibility Reports in the United Kingdom

This study examines how a firm’s tax disclosures in a CSR report are influenced by its tax avoidance behavior. Using a sample of public U.K. firms, our empirical analysis reveals that firms engaging in higher levels of tax avoidance are more likely to provide tax-specific disclosures in their CSR reports. In addition, the tax disclosures tend to be longer, contain more justification words, and contain more soft claims than hard information. Further cross-sectional analyses suggest that the positive association between tax avoidance and tax disclosures is attenuated when firms exhibit better CSR performance as well as stronger corporate governance. Collectively, our findings provide evidence that firms appear to legitimize their tax avoidance behavior by providing more tax disclosures in their communications with stakeholders.

Strategic Nondisclosure in Takeovers

We examine takeover auctions when an informed bidder has better information about the target value than a rival and target shareholders. The informed bidder’s information is either hard or soft, and only hard information can be credibly disclosed. We show that withholding information creates a winner’s curse, thereby serving as a preemption device that deters the rival’s participation. In turn, an endogenous dis- closure cost arises that induces the informed bidder to optimally withhold favorable information to minimize the acquisition price—breaking down the standard unraveling result, even if his information is always hard. Perhaps surprisingly, stronger competition from the uninformed bidder can reduce the target shareholders’ payoff and increase the payoff of the informed bidder while unambiguously improving social welfare. Moreover, “hardened” information can reduce the gains to trade, decreasing welfare but increasing shareholders’ payoff. Our results provide a cautionary note to promoting more competition and more disclosure.

Soft and hard information in equity crowdfunding: network effects in the digitalization of entrepreneurial finance

As a digital financial innovation, equity crowdfunding (ECF) allows investors to exploit the complementarity of information provision and network effects in a reduced transaction cost environment. We build on the underlying distinction between soft and hard information and show that ECF platforms create an environment of greater information pooling that benefits from network externalities. We test our hypotheses using a unique proprietary dataset and find that soft information has a greater impact than hard on the likelihood that a financing pitch will be successful. Moreover, the effects of soft information are amplified by the size of the investor network on the platform and network size also positively moderates the effect of information on the amount invested during each pitch. We conclude that ECF platforms can successfully exploit low transaction costs of the digital environment and bring network externalities to bear on investor decisions. Taken together that these increase the supply of funds to entrepreneurs.

Tax aggressiveness and the proportion of quantitative information in income tax footnotes

Purpose This paper aims to analyse the determinants of the proportion of quantitative data in financial statement footnote disclosures. Quantitative data represents “hard” information and has been considered to be more persuasive than qualitative data. The primary focus is on income tax footnotes because revenue agents use them as a reference in tax audits, and citizen groups use them to analyse tax inequalities. This study posits that firms with lower effective tax rates (“tax aggressive” firms) disclose less quantitative data in their income tax footnotes. Design/methodology/approach The multivariate analysis uses data from the contents of income tax footnotes extracted from 10-K filings in eXtensible Business Reporting Language (XBRL). It uses the alphanumeric characters identified in the income tax footnotes to calculate the proportion of quantitative data relative to the entire footnote disclosure as the dependent variable in a multivariate regression analysis. Findings The findings show that firms which avoid more taxes disclose less quantitative data in income tax footnotes after controlling for the readability of the income tax footnotes and the entire annual report. Therefore, firms seem to reduce the publication of measurable data accessible to revenue agencies and citizen groups. Originality/value This analysis provides evidence that firms weigh the financial reporting requirements and tax audit risks when they disclose quantitative income tax data. Also, it supports the Financial Accounting Standards Board’s (FASB’s) proposal to require more disaggregated income tax disclosure. To the researcher’s knowledge, this is the first analysis that focuses on the determinants of disclosing quantitative data in income tax footnotes.

Selecting Applicants

A firm selects applicants to hire based on hard information, such as a test result, and soft information, such as a manager's evaluation of an interview. The contract that the firm offers to the manager can be thought of as a restriction on acceptance rates as a function of test results. I characterize optimal acceptance rate functions both when the firm knows the manager's mix of information and biases and when the firm is uncertain. These contracts may admit a simple implementation in which the manager can accept any set of applicants with a sufficiently high average test score.

Fintech Borrowers: Lax Screening or Cream-Skimming?

We study the personal credit market using unique individual-level data covering fintech and traditional lenders. We show that fintech lenders acquire market share by lending first to higher-risk borrowers and then to safer borrowers, and rely mainly on hard information to make credit decisions. Fintech borrowers are significantly more likely to default than neighbor individuals with the same characteristics borrowing from traditional financial institutions. Furthermore, they tend to experience a short-lived reduction in the cost of credit, because their indebtedness increases more than non-fintech borrowers after loan origination. However, fintech lenders’ pricing strategies are likely to take this into account.

Financial Intermediation and Technology

We study the effects of technological change on financial intermediation, distinguishing between innovations in information (data collection and processing) and communication (relationships and distribution). Both follow historic trends towards an increased use of hard information and less in-person interaction, which are accelerating rapidly. We point to more recent innovations, such as the combination of data abundance and artificial intelligence, and the rise of digital platforms. We argue that in particular the rise of new communication channels can lead to the vertical and horizontal disintegration of the traditional bank business model. Specialized providers of financial services can chip away activities that do not rely on access to balance sheets, while platforms can interject themselves between banks and customers. We discuss limitations to these challenges, and the resulting policy implications.

Costs of Job Rotation: Evidence from Mandatory Loan Officer Rotation

Job rotation inside an organization creates two conflicting effects. It disciplines agents by creating the fear that their successors may discover and report their hidden information. Thus, the agent takes actions that align with the principal’s objective. However, job rotation can create a moral hazard problem. If information is soft and therefore, nonverifiable, the principal cannot attribute blame to the agent or the successor. Agents shirk, thereby hurting performance. Thus, the importance of disciplining versus moral hazard effects depends on the availability of hard information. Using unique loan-level data, we show that job rotation hinders performance when the information is soft. This paper was accepted by Giesecke Kay, finance.

Improving assessment capability for accounts receivable pool financiers

Purpose The accounts receivable pool (ARP) is an e-invoice management system that provides suppliers with easy access to financial service. The purpose of this paper is to focus on the strength and weakness of ARP mechanism and suggest efficient methods to identify creditworthy borrowers. Design/methodology/approach By decomposing the sales records of 348 ARP borrowers and predicting the occurrence of overdue incidences, this study first portrays the creditworthy borrowers by sales features. Then, content analysis was applied to measure the loadings of soft and hard information, and examined the effectiveness of different information structures in creditworthiness assessment. Findings For ARP borrowers, upward trend and low volatility reveal their creditworthiness. In order to identify creditworthy borrowers beforehand, ARP financiers who have elaborated more soft information and less hard information can perform better. Originality/value This study first discussed ARP finance from a critical perspective and underlines borrower assessment to eliminate the defect of loose recourse. The empirical evidence presents the sales features of creditworthy borrowers. Moreover, the results suggest an efficient approach for ARP financiers to conduct better assessment.