The International Financial Reporting Standards and Their Implementation into the US Accounting System

This paper examines the differences between the International Financial Reporting Standards (IFRS) and Generally Accepted Accounting Principles (GAAP). The areas closely examined are the differences inrevenue recognition and reporting of intangibles. By investigating the differences in the two sets of standards I put into context the changes that would be necessary for domestic companies adopting the IFRS. The differences between these two standards are important because the implementation of IFRS into the U.S. is a current issue for domestic companies. It is important to note how the new standards will affect different companies in different ways. Depending on the size and industry, some companies will have a harder time transitioning to the new standards. However, once these companies make the transition to IFRS they will have better recognition and reporting of revenues and intangibles.

A Bootstrap-Regression Procedure to Capture Unit Specific Effects in Data Envelopment Analysis

The Data Envelopment Analysis (DEA) efficiency score obtained for an individual firm is a point estimate without any confidence interval around it. In recent years, researchers have resorted to bootstrapping in order to generate empirical distributions of efficiency scores. This procedure assumes that all firms have the same probability of getting an efficiency score from any specified interval within the [0,1] range. We propose a bootstrap procedure that empirically generates the conditional distribution of efficiency for each individual firm given systematic factors that influence its efficiency. Instead of resampling directly from the pooled DEA scores, we first regress these scores on a set of explanatory variables not included at the DEA stage and bootstrap the residuals from this regression. These pseudo-efficiency scores incorporate the systematic effects of unit-specific factors along with the contribution of the randomly drawn residual. Data from the U.S. airline industry are utilized in an empirical application.