This paper explores the country tables normally include data on a country’s exchange rates, IMF position, international liquidity, monetary statistics, interest rates, prices, production, labor, international transactions, government accounts, national accounts, and population. The International Financial Statistics (IFS) contains country tables for most IMF members, as well as for Anguilla, Aruba, the Central African Economic and Monetary Community (CEMAC), Curaçao, the currency union of Curaçao and Sint Maarten, the Eastern Caribbean Currency Union (ECCU), the euro area, Montserrat, the former Netherlands Antilles, Sint Maarten, the West African Economic Monetary Union (WAEMU), West Bank and Gaza, and some non-sovereign territorial entities for which statistics are provided internationally on a separate basis. Also, selected series are drawn from the country tables and published in area and world tables. Selected series, including data on IMF accounts, international reserves, and international trade, are drawn from the country tables and published in world tables as well.

During the past financial year, the IMF’s 189 member countries faced a number of pressing challenges. IMF work on these challenges - slower trade, declining productivity, gender inequality, inclusive growth, and debt management - is a central focus of this 2017 Annual Report.

International Financial Statistics, Database & Browser, August 2018

The 2007–09 international financial crisis underscored the importance of reliable and timely statistics on the general government and public sectors. Government finance statistics are a basis for fiscal analysis and they play a vital role in developing and monitoring sound fiscal programs and in conducting surveillance of economic policies. The Government Finance Statistics Manual 2014 represents a major step forward in clarifying the standards for compiling and presenting fiscal statistics and strengthens the worldwide effort to improve public sector reporting and transparency.

This monthly issue of International Financial Statistics (IFS) contains country tables for most IMF members, as well as for Anguilla, Aruba, the Central African Economic and Monetary Community, Curaçao, the currency union of Curaçao and Sint Maarten, the Eastern Caribbean Currency Union, the euro area, Montserrat, the former Netherlands Antilles, Sint Maarten, the West African Economic Monetary Union, West Bank and Gaza, and some non-sovereign territorial entities for which statistics are provided internationally on a separate basis. 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. The three categories are the market rate, describing an exchange rate determined largely by market forces; the official rate, describing an exchange rate determined by the authorities—sometimes in a flexible manner; and the principal, secondary, or tertiary rate, for countries maintaining multiple exchange arrangements.

An empirical investigation of financial crises during the last 800 years.

Introduction.Big data for twenty-first-century economic statistics: the future is now /Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro --Toward comprehensive use of big data in economic statistics.Reengineering key national economic indicators /Gabriel Ehrlich, John Haltiwanger, Ron S. Jarmin, David Johnson, and Matthew D. Shapiro ;Big data in the US consumer price index: experiences and plans /Crystal G. Konny, Brendan K. Williams, and David M. Friedman ;Improving retail trade data products using alternative data sources /Rebecca J. Hutchinson ;From transaction data to economic statistics: constructing real-time, high-frequency, geographic measures of consumer spending /Aditya Aladangady, Shifrah Aron-Dine, Wendy Dunn, Laura Feiveson, Paul Lengermann, and Claudia Sahm ;Improving the accuracy of economic measurement with multiple data sources: the case of payroll employment data /Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz --Uses of big data for classification.Transforming naturally occurring text data into economic statistics: the case of online job vacancy postings /Arthur Turrell, Bradley Speigner, Jyldyz Djumalieva, David Copple, and James Thurgood ;Automating response evaluation for franchising questions on the 2017 economic census /Joseph Staudt, Yifang Wei, Lisa Singh, Shawn Klimek, J. Bradford Jensen, and Andrew Baer ;Using public data to generate industrial classification codes /John Cuffe, Sudip Bhattacharjee, Ugochukwu Etudo, Justin C. Smith, Nevada Basdeo, Nathaniel Burbank, and Shawn R. Roberts --Uses of big data for sectoral measurement.Nowcasting the local economy: using Yelp data to measure economic activity /Edward L. Glaeser, Hyunjin Kim, and Michael Luca ;Unit values for import and export price indexes: a proof of concept /Don A. Fast and Susan E. Fleck ;Quantifying productivity growth in the delivery of important episodes of care within the Medicare program using insurance claims and administrative data /John A. Romley, Abe Dunn, Dana Goldman, and Neeraj Sood ;Valuing housing services in the era of big data: a user cost approach leveraging Zillow microdata /Marina Gindelsky, Jeremy G. Moulton, and Scott A. Wentland --Methodological challenges and advances.Off to the races: a comparison of machine learning and alternative data for predicting economic indicators /Jeffrey C. Chen, Abe Dunn, Kyle Hood, Alexander Driessen, and Andrea Batch ;A machine learning analysis of seasonal and cyclical sales in weekly scanner data /Rishab Guha and Serena Ng ;Estimating the benefits of new products /W. Erwin Diewert and Robert C. Feenstra.

The audited consolidated financial statements of the International Monetary Fund as of April 30, 2019 and 2018

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.

This publication contains the following four parts: A model Competent Authority Agreement (CAA) for the automatic exchange of CRS information; the Common Reporting Standard; the Commentaries on the CAA and the CRS; and the CRS XML Schema User Guide.