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IMF Glossary : English-Chinese, Third edition.
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ISBN: 1455233765 Year: 2007 Publisher: Washington, D.C. : International Monetary Fund,

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Abstract

IMF Glossaries consists of terms, phraseological units, and institutional titles covering areas such as macroeconomics, money and banking, public finance, taxation, balance of payments, statistics, accounting, and economic development. They contain terminology relating to the IMF's organization and operations, as well as from the Articles of Agreement, By-Laws, Rules and Regulations, and other major IMF publications. Since the Glossaries are concept-based, synonyms are consolidated into one single entry. Cross- references refer to the main entry under which the various synonyms are listed ("see") and also draw the user's attention to terms that are related but not synonyms ("see also").


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IMF Glossary : English-French-Arabic, Third edition.
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ISBN: 145525696X 1452730172 Year: 2008 Publisher: Washington, D.C. : International Monetary Fund,

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The main body of the Glossary consists of terms, phraseological units, and institutional titles covering areas such as macroeconomics, money and banking, public finance, taxation, balance of payments, statistics, accounting, and economic development.


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What Do Monetary Contractions Do? Evidence From Large, Unanticipated Tightenings
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ISBN: 1484379462 Year: 2018 Publisher: Washington, D.C. : International Monetary Fund,

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As the “Volcker shock” is believed to have generated useful information on the effects of monetary policy, this paper develops a simple procedure to identify other unanticipated monetary contractions. The approach is applied to a panel data set spanning 162 countries (over the period 1970-2017), in which it identifies 147 large monetary contractions. The procedure selects episodes where a protracted period of loose monetary policy was suddenly followed by sizeable nominal interest rate increases. Focusing on contractions of significant size increases the signal-to-noise ratio, while they are unlikely to be accompanied by confounding “information effects” (markets interpreting a rate hike as the Central Bank being optimistic about the real side of the economy). A subsequent panel VAR analysis suggests that a 100-basis point rate hike reduces real GDP by 0.5 percent. This reduction in output seems to be persistent, pointing to a certain degree of hysteresis. The price level falls by 1.5 percent, indicating that the medium-/long-run impact of contractionary monetary shocks is not characterized by a neo-Fisherian response. Advanced economies appear to display more price stickiness than emerging/developing countries, as the former combine a more muted price response with a larger effect on output.


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How to Gain the Most from Structural Conditionality of IMF-Supported Programs
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Year: 2021 Publisher: Washington, D.C. : International Monetary Fund,

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Structural conditionality of IMF-supported programs is designed to support structural reforms by countries borrowing from the IMF. Taking stock of program conditions and their implementation, this paper finds that conditionality focuses on fiscal, monetary and financial issues—areas where IMF expertise is strong—and shies away from structural areas such as labor or product market reforms. Hence, tackling deep-rooted structural issues during IMF-supported programs often remained elusive. To ensure countries gain most from IMF conditionality, the paper outlines an evaluation matrix for prioritizing and designing structural reforms, and applies it to case studies.


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COVID-19 Containment Measures and Expected Stock Volatility: High-Frequency Evidence from Selected Advanced Economies
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Year: 2021 Publisher: Washington, D.C. : International Monetary Fund,

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We study the effect of COVID-19 containment measures on expected stock price volatility in some advanced economies, using event studies with hand-collected minute-level data and panel regressions with daily data. We find that six-month-ahead volatility indices dropped following announcements of initial or re-imposed lockdowns, and that they did not drop significantly following the easing of lockdowns. Such patterns are not as strong for three-month-ahead expected volatility and generally absent for one-month-ahead expected volatility. These results provide suggestive evidence for the existence of an intertemporal trade-off: although stringent containment measures cause short-term economic disruptions, they may reduce medium-term uncertainty (reflected in expected stock volatility) by boosting markets’ confidence that the outbreak would be under control more quickly.


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Scenario Analysis with the DD-PD Mapping Approach: Stock Market Shocks and U.S. Corporate Default Risk
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Year: 2021 Publisher: Washington, D.C. : International Monetary Fund,

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This paper introduces the quantile regression- based Distance-to-Default to Probability of Default (DD-PD) mapping, which links individual firms’ DD to their real world PD. Since changes in the DD depend on a handful of parameters, the mapping easily accommodates shocks arising from quantitative and narrative scenarios informed by expert judgment. At end-2020, risks from stock market corrections in the U.S. are concentrated in the energy, financial and technology sectors, and additional bank capital needs could be large. The paper concludes discussing uses of the mapping beyond PD valuation suitable for capital structure analysis, credit portfolio management, and long-term scenario planning analysis.


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Inclusivity in the Labor Market
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Year: 2021 Publisher: Washington, D.C. : International Monetary Fund,

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Labor earnings are the dominant income source for most individuals. Thus, an inclusive labor market is key for ensuring inclusive growth. In this paper we propose four principles that an inclusive labor market will embody: access, fairness, protection and voice. While measuring inclusivity presents challenges, we discuss how data can be used to shed light on the extent of inclusivity and document cross-country trends and stylized facts. We also discuss the role of policy in achieving an inclusive labor market, focusing on the need to rebalance growth; improve risk sharing; and fight discrimination. Several messages emerge. First, some policies entail a trade-off between the different dimensions of inclusivity. Second, it is important to view policies as a bundle, taking into account substitution and complementarities. Third, some policies are win-win, in the sense that they both increase inclusivity and improve overall efficiency.


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Predicting Fiscal Crises: A Machine Learning Approach
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Year: 2021 Publisher: Washington, D.C. : International Monetary Fund,

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In this paper I assess the ability of econometric and machine learning techniques to predict fiscal crises out of sample. I show that the econometric approaches used in many policy applications cannot outperform a simple heuristic rule of thumb. Machine learning techniques (elastic net, random forest, gradient boosted trees) deliver significant improvements in accuracy. Performance of machine learning techniques improves further, particularly for developing countries, when I expand the set of potential predictors and make use of algorithmic selection techniques instead of relying on a small set of variables deemed important by the literature. There is considerable agreement across learning algorithms in the set of selected predictors: Results confirm the importance of external sector stock and flow variables found in the literature but also point to demographics and the quality of governance as important predictors of fiscal crises. Fiscal variables appear to have less predictive value, and public debt matters only to the extent that it is owed to external creditors.


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What Drives Innovation? Lessons from COVID-19 R&D
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Year: 2021 Publisher: Washington, D.C. : International Monetary Fund,

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To examine the drivers of innovation, this paper studies the global R&D effort to fight the deadliest diseases and presents four results. We find: (1) global pharmaceutical R&D activity—measured by clinical trials—typically follows the ‘law of diminishing effort’: i.e. the elasticity of R&D effort with respect to market size is about ½ in the cross-section of diseases; (2) the R&D response to COVID-19 has been a major exception to this law, with the number of COVID-19 trials being 7 to 20 times greater than that implied by its market size; (3) the aggregate short-term elasticity of science and innovation can be very large, as demonstrated by aggregate flow of clinical trials increasing by 38% in 2020, with limited crowding out of trials for non-COVID diseases; and (4) public institutions and government-led incentives were a key driver of the COVID-19 R&D effort—with public research institutions accounting for 70 percent of all COVID-19 clinical trials globally and being 10 percentage points more likely to conduct a COVID-19 trial relative to private firms. Overall, while economists are naturally in favor of market size as a driving force for innovation (i.e.“if the market size is sufficiently large then innovation will happen”), our work suggests that scaling up global innovation may require a broader perspective on the drivers of innovation—including early-stage incentives, non-monetary incentives, and public institutions.


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Capital Income Taxation in the Netherlands
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Year: 2021 Publisher: Washington, D.C. : International Monetary Fund,

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This paper looks at capital income taxation in the Netherlands from an international and domestic perpective. The Netherlands is a major conduit country for FDI. Recent reforms taken by the Dutch authorities as well as public statements represent a strong move to address international tax avoidance, but it is too early to be able to detect the impact in the data, and measuring tax avoidance even in the past is fraught with difficulties. Domestically, the unique system, which for many financial assets effectively taxes wealth rather than capital income, leads to inequities and distortions. Owner-occupied housing is strongly tax-favored and in many cases effectively subsidized. Various reforms, not necessarily of a fundamental nature, would improve efficiency and equity.

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