Determining the Impact of Multiple Consecutive Years of Financial Reporting Quality Issues on Investment Efficiency

Abstract

Prior research recognizes that there is a positive relation between financial reporting quality and investment efficiency. The primary object of this dissertation is to examine how financial reporting quality in multiple consecutive years impacts investment efficiency. I use material weaknesses in internal control (MW) as a proxy for poor financial reporting quality and I examine the impact of poor financial reporting quality in multiple consecutive years using an OLS regression model. The results indicate there is a progressively negative impact on investment efficiency tied to the number of consecutive years in which firms report MW. Additionally, I examine whether investment specific financial reporting quality issues have a greater impact on investment efficiency than all other types of financial reporting quality issues. My results suggest that investment specific financial reporting quality issues are driving the negative impact on investment efficiency. These results imply that managers can reduce investment inefficiency by focusing their resources on remediating (correcting) financial reporting quality issues (MW) associated with investment.

Current internal control research identifies firms as having either strong or weak internal control dependent upon (1) the presence or absence of MW or (2) the number of MW. This research essentially treats each MW as being of equal importance, Thus, as a secondary objective of this dissertation, in Appendix B, I develop a metric for internal control using the Analytic Hierarchy Process (AHP) to provide a weighting scheme for the different types of MW. Based on Audit Analytics (which separates MW into 21 different categories), I engage 18 participants in an AHP exercise to determine which types of MW have the greatest impact on the financial statements. The results indicate that auditors and managers find MW related to Personnel Weaknesses have the greatest impact on the financial statements. AHP results in weights that are then applied to the 21 different categories of MW. These weights are applied to firms based upon the types of MW reported and the sum of the weights is the measure used for the internal control metric. I then perform a simple OLS regression to test the relation between the internal control metric and stock market returns (Appendix C). I find that a positive relation exists between strong internal controls (as measured by the newly constructed metric) and stock market returns.