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In 2001, the US moved to regulate internal control reporting by management and auditors. While some jurisdictions have followed the lead of the US, many others have not. An important question, therefore, is the relevance of internal control to stakeholders. The more specific issue of the benefits of US-style regulation of internal control reporting is also topical. We review studies on the determinants of internal control quality and its economic consequences for stakeholders including investors, creditors, managers, auditors and financial analysts. We extend previous reviews by focusing on US studies published since 2013 as well as all non-US studies investigating IC quality including countries regulating IC disclosure as well as unregulated settings and both developed and developing economies. In doing so, we identify research questions where evidence remains mixed and new directions in which there are research opportunities.

Three main insights arise from our analysis. First, evidence on the economic consequences of internal control quality suggests that the quality of internal control can have a significant effect on decision making by users of financial information. Second, the results of research on the empirical association between ownership structure, certain board characteristics and internal control quality is generally mixed. Empirical evidence concerning the association between audit committee characteristics and internal control quality generally supports a positive and significant association. Finally, while studies in non-US jurisdictions are increasing, opportunities remain to explore the determinants and consequences of internal control in other jurisdictions. Our review provides evidence for policy makers of whether there are benefits from requiring management and auditors to report on internal control over financial reporting.

This paper provides a wide-ranging and up-to-date (1997–2016) review of the archival empirical risk-reporting literature. The reviewed papers are classified into two principal themes: the incentives for and/or informativeness of risk reporting. Our review demonstrates areas of significant divergence in the literature specifically: mandatory versus voluntary risk reporting, manual versus automated content analysis, within-country versus cross-country variations in risk reporting, and risk reporting in financial versus non-financial firms. Our paper identifies a number of issues which require further research. In particular we draw attention to two: first, a lack of clarity and consistency around the conceptualization of risk; and second, the potential costs and benefits of standard-setters’ involvement.

This paper reviews academic literature related to the consequences that outside directors and boards may face in the wake of earnings restatements and suggests directions for future research. We examine loss of board seats; recruitment of new directors; proxy recommendations and shareholder support; pre-emptive director departures; director wealth effects; director reputation, litigation, and sanction risks; international evidence; and legal proposals for reform. The overall picture that emerges from the literature is that directors’ primary risk in the wake of earnings restatements is loss of board seats, in part through adverse proxy advisor recommendations and reduced shareholder support. Directors typically face little risk of legal liability or SEC sanctions, and some directors pre-emptively leave a problem company’s board and reduce their loss of interlocked board seats. Some legal scholars have called for director liability to be increased so as to promote more vigilant board oversight. Companies often focus on increasing the independence of the board in the wake of a restatement in an effort to repair organizational reputation. While researchers have revealed a host of important findings to date, much more can be learned about the effects of restatements on outside directors and boards.

This synthesis covers academic research on the use of valuation, tax, information technology (IT), and forensic specialists on audit engagements. The importance and role of specialists on audit engagements have recently increased, and specialist use has garnered significant attention from regulators and academics. Given the PCAOB’s (2017b) recent proposal to revise auditing standards regarding specialists’ involvement, it is important to review the specialist literature as a whole. By integrating research across these four domains, I identify commonalities and differences related to: (1) factors associated with the use of specialists on audit engagements (including the nature, timing, and extent of use); (2) factors impacting auditors’ interactions with specialists (including specialists contracted by the auditor or management); and (3) outcomes associated with the use of specialists. This integrated analysis of the specialist literatures shows variation in the use of specialists, and various factors affecting both if and how they are involved and whether auditors use specialists internal or external to the audit firm. Additionally, research has sometimes (but not always) linked specialist involvement to higher audit quality. The commonalities and areas of variation identified are informative to audit research and practice, particularly as regulators and audit firms look to improve the quality of audits using specialists. Throughout the synthesis, I also provide a number of directions for future research.

This chapter proposes semiparametric estimation of the relationship between growth rate of GDP per capita, growth rates of physical and human capital, labor as well as other covariates and common trends for a panel of 23 OECD countries observed over the period 1971–2015. The observed differentiated behaviors by country reveal strong heterogeneity. This is the motivation behind using a mixed fixed- and random coefficients model to estimate this relationship. In particular, this chapter uses a semiparametric specification with random intercepts and slopes coefficients. Motivated by Lee and Wand (2016), the authors estimate a mean field variational Bayes semiparametric model with random coefficients for this panel of countries. Results reveal nonparametric specifications for the common trends. The use of this flexible methodology may enrich the empirical growth literature underlining a large diversity of responses across variables and countries.

Vector Autoregression (VAR) has been a standard empirical tool used in macroeconomics and finance. In this paper we discuss how to compare alternative VAR models after they are estimated by Bayesian MCMC methods. In particular we apply a robust version of deviance information criterion (RDIC) recently developed in Li, Zeng, and Yu (2014b) to determine the best candidate model. RDIC is a better information criterion than the widely used deviance information criterion (DIC) when latent variables are involved in candidate models. Empirical analysis using US data shows that the optimal model selected by RDIC can be different from that by DIC.

Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.

Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.

The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.

By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.