This October 2016 issue of International Financial Statistics (IFS) is a standard source of statistics on all aspects of international and domestic finance. This issue presents countries newly reporting monetary data for Rwanda using the standardized report forms. Exchange rates in IFS are classified into three broad categories, reflecting the role of the authorities in determining the rates and/or the multiplicity of the exchange rates in a country. Although the method of calculating the US dollar/SDR exchange rate has remained the same, the currencies’ number and weight have changed over time. Their amount in the SDR basket is reviewed every five years. When a country joins the IMF, it is assigned a quota that fits into the structure of existing quotas. Quotas are considered in the light of the member’s economic characteristics and considering quotas of similar countries.

This paper describes the compilation of the Global Debt Database (GDD), a cutting-edge dataset covering private and public debt for virtually the entire world (190 countries) dating back to the 1950s. The GDD is the result of a multiyear investigative process that started with the October 2016 Fiscal Monitor, which pioneered the expansion of private debt series to a global sample. It differs from existing datasets in three major ways. First, it takes a fundamentally new approach to compiling historical data. Where most debt datasets either provide long series with a narrow and changing definition of debt or comprehensive debt concepts over a short period, the GDD adopts a multidimensional approach by offering multiple debt series with different coverages, thus ensuring consistency across time. Second, it more than doubles the cross-sectional dimension of existing private debt datasets. Finally, the integrity of the data has been checked through bilateral consultations with officials and IMF country desks of all countries in the sample, setting a higher data quality standard.

IMF Financial Operations 2018 provides a broad introduction to how the IMF fulfills its mission through its financial activities. It covers the financial structure and operations of the IMF and provides background detail on the financial statements. It reviews the IMF's three main activities: lending, surveillance, and technical assistance.

Risks to macroeconomic stability posed by excessive private leverage are significantly amplified by tax distortions. ‘Debt bias’ (tax provisions favoring finance by debt rather than equity) has increased leverage in both the household and corporate sectors, and is now widely recognized as a significant macroeconomic concern. This paper presents new evidence of the extent of debt bias, including estimates for banks and non-bank financial institutions both before and after the global financial crisis. It presents policy options to alleviate debt bias, and assesses their effectiveness. The paper finds that thin capitalization rules restricting interest deductibility have only partially been able to address debt bias, but that an allowance for corporate equity has generally proved effective. The paper concludes that debt bias should feature prominently in countries’ tax reform plans in the coming years.

This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.

This edition of Monetary and Financial Statistics Manual and Compilation Guide (Manual) updates and merges into one volume methodological and practical aspects of the compilation process of monetary statistics. The Manual is aimed at compilers and users of monetary data, offering guidance for the collection and analytical presentation of monetary statistics. The Manual includes standardized report forms, providing countries with a tool for compiling and reporting harmonized data for the central bank, other depository corporations, and other financial corporations.

The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data. To make use of this data, the powerful methods in this book for working with quantitative information, particularly about volatility and risks, are essential. Strengths of this fully-revised edition include major additions to the R code and the advanced topics covered. Individual chapters cover, among other topics, multivariate distributions, copulas, Bayesian computations, risk management, and cointegration. Suggested prerequisites are basic knowledge of statistics and probability, matrices and linear algebra, and calculus. There is an appendix on probability, statistics and linear algebra. Practicing financial engineers will also find this book of interest.

The AREAER provides a description of the foreign exchange arrangements, exchange and trade systems, and capital controls of all IMF Member countries.

This paper evaluates the risks and vulnerabilities of the German financial system and reviews both the German regulatory and supervisory framework and implementation of the common European framework insofar as it is relevant for Germany. The country is home to two global systemically important financial institutions, Deutsche Bank AG and Allianz SE. The system is also very heterogeneous, with a range of business models and a large number of smaller banks and insurers. The regulatory landscape has changed profoundly with strengthened solvency and liquidity regulations for banks (the EU Capital Requirements Regulation and Directive IV), and the introduction of macroprudential tools.

The October 2017 Global Financial Stability Report finds that the global financial system continues to strengthen in response to extraordinary policy support, regulatory enhancements, and the cyclical upturn in growth. It also includes a chapter that examines the short- and medium-term implications for economic growth and financial stability of the past decades’ rise in household debt. It documents large differences in household debt-to-GDP ratios across countries but a common increasing trajectory that was moderated but not reversed by the global financial crisis. Another chapter develops a new macroeconomic measure of financial stability by linking financial conditions to the probability distribution of future GDP growth and applies it to a set of 20 major advanced and emerging market economies. The chapter shows that changes in financial conditions shift the whole distribution of future GDP growth.