America’s unreported economy: measuring the size, growth and determinants of income tax evasion in the U.S.

Abstract This study empirically investigates the extent of noncompliance with the tax code and examines the determinants of federal income tax evasion in the U.S. Employing a refined version of Feige’s (1986; 1989) General Currency Ratio (GCR) model to estimate a time series of unreported income as our measure of tax evasion, we find that 18-23 % of total reportable income may not properly be reported to the IRS. This gives rise to a 2009 “tax gap” in the range of $390-$537 billion. As regards the determinants of tax noncompliance, we find that federal income tax evasion is an increasing function of the average effective federal income tax rate, the unemployment rate, the nominal interest rate, and per capita real GDP, and a decreasing function of the IRS audit rate. Despite important refinements of the traditional currency ratio approach for estimating the aggregate size and growth of unreported economies, we conclude that the sensitivity of the results to different benchmarks, imperfect data sources and alternative specifying assumptions precludes obtaining results of sufficient accuracy and reliability to serve as effective policy guides.Unreported economy; Underground economy; tax evasion; tax gap; noncompliance; income tax evasion; currency demand approach, currency ratio models

Pastoral role expectations in the local church

https://place.asburyseminary.edu/ecommonsatsdissertations/1030/thumbnail.jp

The legal challenges facing selected African countries with regard to the implementation of the Rome Statute of the International Criminal Court

Public, Constitutional and International LawLL. M

Multi-criteria decision-making in whole process design

PhD ThesisIn recent years, the chemical and pharmaceutical industries have faced increased development times and costs with fewer novel chemicals being discovered. This has resulted in many companies focusing on innovative research and development as they consider this key to business success. In particular, a number of leading industrial organisations have adopted the principles of Whole Process Design (WPD). WPD considers the optimisation of the entire product development process, from raw materials to end product, rather than focusing on each individual unit operation. The complexity involved in the implementation of WPD requires rationalised decision-making, often with limited or uncertain information. This thesis assesses the most widely applied methods in Multi-Criteria Decision Analysis (MCDA) in conjunction with the results of two interviews and two questionnaires that identified the industrial requirements for decision-making during WPD. From the findings of this work, a novel decision-making methodology was proposed, the outcome of which allows a decision-maker to visually interpret their decision results with associated levels of uncertainty. To validate the proposed methodology, a software framework was developed that incorporates two other decision-making approaches, the Analytical Hierarchy Process (AHP) and ELimination Et Choix Traduisant la REalité trois (ELECTRE III). The framework was then applied to a number of industrial case studies to validate the application of the proposed methodology.Engineering and Physical Sciences Research Council (EPSRC) and Chemistry Innovatio