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Corporate Income Tax Gap Estimation by Using Bottom-Up Techniques in Selected Countries
This technical note describes bottom-up CIT gap estimation techniques applied by revenue administrations in the following highly experienced countries in this approach: Australia, Brazil, Canada, Denmark, Sweden, the United Kingdom, and the United States. The main topics included in the descriptions are techniques applied, CIT gap results, advantages and disadvantages of different available options, and future developments and recommendations for any revenue administration interested in starting bottom-up CIT gap estimation programs having no prior experience.
Gender and Revenue Administration
This technical note provides an overview of current issues and ideas that revenue administrations can consider regarding gender equality. It discusses the interactions between revenue administrations and gender equality and explores how revenue administrations can administer gender-sensitive tax laws effectively and apply a gender lens when administering tax or trade laws with a view to reducing barriers for women’s employment, entrepreneurship, and trade. It also provides practical considerations for a revenue administration in building gender perspectives in reform plans and shares several examples that highlight targeted measures that have led to positive outcomes in several countries.
Women in Air War
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Belgium
This report presents the results of applying the RA-GAP VAT gap estimation methodology to Belgium for the period 2011-2021. The Revenue Administration Gap Analysis Program (RAGAP) methodology employs a top-down approach for estimating the potential Value-Added Tax (VAT) base, using statistical data on value-added generated in each sector. There are two main components to this methodology for estimating the VAT gap: 1) estimate the potential VAT collections for a given period; and 2) determine the accrued VAT collections for that period. The difference between the two values is the VAT gap.
Russian Opera and the Symbolist Movement
An aesthetic, historical, and theoretical study of four scores, Russian Opera and the Symbolist Movement is a groundbreaking and imaginative treatment of the important yet neglected topic of Russian opera in the Silver Age. Spanning the gap between the supernatural Russian music of the nineteenth century and the compositions of Prokofiev and Stravinsky, this exceptionally insightful and well-researched book explores how Russian symbolist poets interpreted opera and prompted operatic innovation. Simon Morrison shows how these works, though stylistically and technically different, reveal the extent to which the operatic representation of the miraculous can be translated into its enactment. Mor...
The Russian Urban Sustainability Puzzle
This book provides comprehensive analysis of the social-environmental situation and sustainability issues in Russian megacities based on a large-scale mixed method original empirical research conducted in 2015–2019.
The Revenue Administration Gap Analysis Program
It is generally difficult to measure revenue not collected due to noncompliance, but a growing number of countries now regularly produce and publish estimated revenue losses. Good tax gap analysis enables the detection of changes in taxpayer behavior by consistent estimates over time. This Technical Note sets out the theoretical concepts for personal income tax (PIT) gap estimation, the different measurement approaches available, and their implications for the scope and presentation of statistics. The note also focuses on the practical steps for measuring the PIT gap by establishing a random audit program to collect data, and how to scale findings from the sample to the population.
Articulate Flesh
Discusses the themes of the male body, war, and homosexual love in poetry, and analyzes the poetry of D.H. Lawrence, Hart Crane, W.H. Auden, Allen Ginsberg, and Thom Gunn.
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. ...
