Exploring Auditors’ Perceptions of the Usage and Importance of Audit Information Technology

This study provides novel evidence on the extent to which auditors perceive the usage and importance of audit technology in an emerging market. It explores the types of audit technology tools used and factors influencing the use of these; it tests the association between the perceived use and importance of the tools and firm-specific/ auditor-specific characteristics. Using interviews and questionnaires from auditors at Big 4 and international non-Big 4 audit firms, the findings reflect the highly perceived importance of using audit technology in technical and administrative procedures, specifically to assess risk. We find that the perceived use and importance of audit technology is relatively higher for those in Big 4 firms, with less years of auditor experience and higher auditor technology expertise, and those in management positions. The results provide policy makers with guidance on the opportunities and challenges of using information technology in the audit process.

Macroeconomic information, structural change, and the prediction of fiscal aggregates

Previous research on the prediction of fiscal aggregates has shown evidence that simple autoregressive models often provide better forecasts of fiscal variables than multivariate specifications. We argue that the multivariate models considered by previous studies are small-scale, probably burdened by overparameterization, and not robust to structural changes. Bayesian Vector Autoregressions (BVARs), on the other hand, allow the information contained in a large data set to be summarized efficiently, and can also allow for time variation in both the coefficients and the volatilities. In this paper we explore the performance of BVARs with constant and drifting coefficients for forecasting key fiscal variables such as government revenues, expenditures, and interest payments on the outstanding debt. We focus on both point and density forecasting, as assessments of a country’s fiscal stability and overall credit risk should typically be based on the specification of a whole probability distribution for the future state of the economy. Using data from the US and the largest European countries, we show that both the adoption of a large system and the introduction of time variation help in forecasting, with the former playing a relatively more important role in point forecasting, and the latter being more important for density forecasting.