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Europe > Iceland

You are looking at 1 - 10 of 10 items for :

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Cover IMF Staff Country Reports
St. Kitts and Nevis: Selected Issues
International Monetary Fund. Western Hemisphere Dept.
This Selected Issues paper on St. Kitts and Nevis studies economic benefits from energy transition. Cheaper and more stable energy prices can support macroeconomic stability. In addition to the aforementioned effects, low and stable energy prices can mitigate the adverse impact from terms-of-trade shocks and reduce inflation volatility, thus contributing to smoothing out economic cycles. The energy landscape of St. Kitts and Nevis calls for energy reform. The two islands of St. Kitts and Nevis rely heavily on fossil fuels, primarily diesel, to power their grids without Interconnection. The analysis uses cross-country examples to examine the channels through which the adoption of renewable energy on a large scale can yield numerous long-term economic benefits. Transitioning to domestic renewable energy sources could stabilize domestic energy prices and reduce the volatility of inflation. A sharp reduction in energy costs in St. Kitts and Nevis could promote sectoral diversification. High-energy costs can prohibit economic diversification, particularly into energy intensive industries.
Keywords:
energy transition index; staff team of the International Monetary Fund; carbon capture in St. Kitts and Nevis; inflation volatility; copyright page; Renewable energy; Electricity; Energy prices; Non-renewable resources; Caribbean; Global
Cover IMF Staff Country Reports
Iceland: Financial Sector Assessment Program-Technical Note on Cyber and Operational Resilience, Supervision and Oversight
International Monetary Fund. Monetary and Capital Markets Department
This technical note focuses on cyber and operational resilience, supervision and oversight in Iceland. The Icelandic financial sector has not experienced seriously disruptive cyber-attacks or operational issues in recent years, but threats are growing. Iceland’s dependence on international connectivity for both debit and credit card systems introduces a significant vulnerability into the payment system. There is no dedicated cyber security strategy for the finance sector. Operational risk experts in the Central Bank of Iceland (CBI) are experienced and well regarded by financial institutions, but more resources are needed to provide adequate coverage of this increasingly important area. The supervision of financial institutions’ cybersecurity is highly dependent on self-assessments by the regulated entities themselves and independent reviews carried out by third parties. CBI should regularly revise the list of critical operations and critical service providers for internal use and for presentation to the Financial Stability Committee and Financial Stability Council. CBI is encouraged to enhance its incident dashboard by summarizing cyber incidents and examining trends.
Keywords:
C. supervision approach; payment services directive; markets authority; market infrastructure; cash payment; Cyber risk; Financial sector stability; Financial sector; Payment systems; Operational risk; Europe; Baltics; Global
Cover IMF Working Papers
Housing Boom and Headline Inflation: Insights from Machine Learning
Yang Liu
,
Di Yang
, and
Mr. Yunhui Zhao
Inflation has been rising during the pandemic against supply chain disruptions and a multi-year boom in global owner-occupied house prices. We present some stylized facts pointing to house prices as a leading indicator of headline inflation in the U.S. and eight other major economies with fast-rising house prices. We then apply machine learning methods to forecast inflation in two housing components (rent and owner-occupied housing cost) of the headline inflation and draw tentative inferences about inflationary impact. Our results suggest that for most of these countries, the housing components could have a relatively large and sustained contribution to headline inflation, as inflation is just starting to reflect the higher house prices. Methodologically, for the vast majority of countries we analyze, machine-learning models outperform the VAR model, suggesting some potential value for incorporating such models into inflation forecasting.
Keywords:
Housing Price Inflation; Rent; Owner-Occupied Housing; Machine Learning; Forecast; machine-learning model; machine learning method; housing boom; D. forecasting result; Inflation; Housing prices; Housing; Consumer price indexes; Global; Europe; Australia and New Zealand; North America; Caribbean; VAR model
Cover Policy Papers
2021 Comprehensive Surveillance Review— Background Paper on Traction
International Monetary Fund. Strategy, Policy, & Review Department
This paper presents traction as a multidimensional concept and discusses a comprehensive and complementary set of approaches to attempt to measure it based on the Fund’s value added to policy dialogue and formulation and public debate in member countries.
Keywords:
article IV advice; fund policy advice; fund advice; policy dialogue; IMF's transparency policy; COVID-19; Income; Financial Sector Assessment Program; Financial sector stability; Machine learning; Global
Cover IMF Staff Country Reports
Uruguay: Technical Assistance Report-Monetary and Financial Statistics Mission
International Monetary Fund. Statistics Dept.
At the request of the Central Bank of Uruguay (BCU), and with the support of the International Monetary Fund’s (IMF’s) Western Hemisphere Department (WHD), a monetary and financial statistics (MFS) technical assistance (TA) mission from the IMF’s Statistics Department (STA) visited Montevideo during February 3-14, 2020. The main objectives of the mission were to: (i) review available source data for other financial corporations (OFC); in particular, insurance corporations (IC), pension funds (PF), and credit administration companies (CAC); and (ii) compile standardized monetary statistics for OFC (report form SRF 4SR) in line with the 2016 Monetary and Financial Statistics Manual and Compilation Guide (MFSMCG). The officials met during the mission are listed in Appendix I.
Keywords:
IMF's Statistics Department; administration company; staff team of the International Monetary Fund; Statistics Department of the IMF; CAC assets; Nonbank financial institutions; Offshore financial centers; Financial statements; Financial soundness indicators; Collective action clauses; Global
Cover IMF Working Papers
UnFEAR: Unsupervised Feature Extraction Clustering with an Application to Crisis Regimes Classification
Mr. Jorge A Chan-Lau
We introduce unFEAR, Unsupervised Feature Extraction Clustering, to identify economic crisis regimes. Given labeled crisis and non-crisis episodes and the corresponding features values, unFEAR uses unsupervised representation learning and a novel mode contrastive autoencoder to group episodes into time-invariant non-overlapping clusters, each of which could be identified with a different regime. The likelihood that a country may experience an econmic crisis could be set equal to its cluster crisis frequency. Moreover, unFEAR could serve as a first step towards developing cluster-specific crisis prediction models tailored to each crisis regime.
Keywords:
clustering; unsupervised feature extraction; autoencoder; deep learning; biased label problem; crisis prediction; WP; crisis frequency; crisis observation; crisis risk; crisis data points; machine learning; Early warning systems; Global
Cover IMF Working Papers
The More the Merrier? A Machine Learning Algorithm for Optimal Pooling of Panel Data
Marijn A. Bolhuis
and
Brett Rayner
We leverage insights from machine learning to optimize the tradeoff between bias and variance when estimating economic models using pooled datasets. Specifically, we develop a simple algorithm that estimates the similarity of economic structures across countries and selects the optimal pool of countries to maximize out-of-sample prediction accuracy of a model. We apply the new alogrithm by nowcasting output growth with a panel of 102 countries and are able to significantly improve forecast accuracy relative to alternative pools. The algortihm improves nowcast performance for advanced economies, as well as emerging market and developing economies, suggesting that machine learning techniques using pooled data could be an important macro tool for many countries.
Keywords:
WP; country; algorithm; Machine learning; GDP growth; forecasts; panel data; pooling; proximate country; machine learning method; example country; macroeconomic aggregate; bias-variance tradeoff; country of interest; Production growth; Eastern Europe
Cover IMF Working Papers
The Role of Risk and Information for International Capital Flows: New Evidence from the SDDS
Ms. Yuko Hashimoto
and
Mr. Konstantin Wacker
In this paper we investigate whether better information about the macroeconomic environment of an economy has a positive impact on its capital inflows, namely portfolio and foreign direct investment (FDI). The purpose of our study is to explicitly quantify information asymmetries by compliance with the IMF's Special Data Dissemination Standard (SDDS). For FDI, we find statistically significant and robust support for this hypothesis: SDDS subscription increased inflows by an economically relevant magnitude of about 60 percent. We also find evidence of aversion against political and macroeconomic risk as determinants of portfolio and FDI flows anduse a non-parametric test for spatial correlation in the residual of capital flows.
Keywords:
WP; FDI inflow; interest rate; emerging market; FDI flow; determinants of capital flows; information; panel data; risk; SDDS; IMF; FDI; portfolio investment; spatial econometrics; FDI-agglomeration literature; FDI literature; SDDS subscription; portfolio flow; Foreign direct investment; Special Data Dissemination Standard (SDDS); Capital flows; Exchange rates; Global
Cover IMF Staff Country Reports
Iceland: Report on the Observance of Standards and Codes (ROSC)—Data Module
International Monetary Fund
This Report on the Observance of Standards and Codes on Data Module for Iceland highlights Data Module, response by the authorities, and detailed assessments using the data quality assessment framework. Iceland’s macroeconomic statistics are generally of high quality and are adequate to conduct effective surveillance. There is a high degree of quality awareness among Iceland’s statistical managers. There are some deficiencies in the periodicity and timeliness of the producer price index, and in the timeliness of central government finance statistics.
Keywords:
ISCR; CR; central bank; sc; central government; staff resource; balance of payments; ROSC exercise; ROSC recommendation; commitment to confidentiality; Consumer price indexes; Balance of payments statistics; Producer price indexes; Monetary statistics; Data collection; Europe
Cover IMF Staff Papers
IMF Staff papers: Volume 37 No. 4
International Monetary Fund. Research Dept.
The transition strategy from administratively set interest rates to market rates is discussed. Despite worldwide trends toward financial liberalization, few monetary authorities are prepared to accept as reasonable any interest rate level that is market determined. The paper suggests some helpful indicators to assess the adequacy of interest rates and discusses factors that contribute to a smooth liberalization process. The main conclusion is that interest rate liberalization is not synonymous with laissez-faire policies, but requires the replacement of the administratively set interest rates by indirect monetary management techniques that operate through the market.
Keywords:
SP; interest rate equation; interest rate; deficit; deficit variable; expenditure competition strategy; yield differential; effects of deficit; Demand for money; Consumption; Exchange rates; Interest rate policy; Labor markets; Europe; Sub-Saharan Africa