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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.

Sweden

International Monetary Fund. Monetary and Capital Markets Department

Published: 2016-11-17

Total Pages: 61


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This paper discusses the findings of the Financial System Stability Assessment for Sweden. The Swedish financial system is large and highly interconnected, putting a premium on the accompanying policy framework. Relative to the size of the domestic economy, the financial system is among Europe’s largest. It features complex domestic and international linkages, reflecting Sweden’s role as a regional financial hub. However, the macrofinancial risks have grown since 2011, for example the rising share of highly indebted households. Stress tests also suggest that banks and nonbanks are largely resilient to solvency shocks, but concerns persist about the ability of bank models to capture unexpected losses.
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.
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.
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.