Nuestra respuesta a la pandemia de coronavirus
El BCE ha adoptado una serie de medidas de política monetaria y de supervisión bancaria para mitigar el impacto de la pandemia de coronavirus en la economía de la zona del euro y apoyar a los ciudadanos europeos.
Nuestras medidas para respaldar la economía de la zona del euro
Ir por delante de la curva de aprendizaje
¿Dónde encontrar la información más reciente sobre el coronavirus?
- 21 January 2021
- Christine Lagarde, Luis de Guindos: Introductory statement to the press conference (with Q&A)Christine Lagarde, President of the ECB, Luis de Guindos, Vice-President of the ECB, Frankfurt am Main, 21 January 2021
- 12 January 2021
- Isabel Schnabel: Interview with Der StandardInterview with Isabel Schnabel, Member of the Executive Board of the ECB, conducted by Andras Szigètvari on 7 January 2021 und published on 12 January 2021
- No. 2510
11 January 2021
- Nowcasting in a pandemic using non-parametric mixed frequency VARs
C11 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Bayesian Analysis: General
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
This paper develops Bayesian econometric methods for posterior inference in non-parametric mixed frequency VARs using additive regression trees. We argue that regression tree models are ideally suited for macroeconomic nowcasting in the face of extreme observations, for instance those produced by the COVID-19 pandemic of 2020. This is due to their flexibility and ability to model outliers. In an application involving four major euro area countries, we find substantial improvements in nowcasting performance relative to a linear mixed frequency VAR.
- No. 2507
18 December 2020
- The Covid-19 crisis and consumption: survey evidence from six EU countries
D12 : Microeconomics→Household Behavior and Family Economics→Consumer Economics: Empirical Analysis
D81 : Microeconomics→Information, Knowledge, and Uncertainty→Criteria for Decision-Making under Risk and Uncertainty
E21 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Consumption, Saving, Wealth
G51 : Financial Economics
H31 : Public Economics→Fiscal Policies and Behavior of Economic Agents→Household
Using new panel data from a representative survey of households in the six largest euro area economies, the paper estimates the impact of the Covid-19 crisis on consumption. The panel provides, each month, household-specific indicators of the concern about finances due to Covid-19 from the first peak of the pandemic until October 2020. The results show that this concern causes a significant reduction in non-durable consumption. The paper also explores the potential impact on consumption of government interventions and of another wave of Covid-19, using household-level consumption adjustments to scenarios that involve positive and negative income shocks. Fears of the financial consequences of the pandemic induce a significant reduction in the marginal propensity to consume, an effect consistent with models of precautionary saving and liquidity constraints. The results are robust to endogeneity concerns through use of panel fixed effects and partial identification methods, which account also for time-varying unobservable variables, and provide informative identification regions of the average treatment effect of the concern for Covid-19 under weak assumptions.
- No. 2505
17 December 2020
- Daily tracker of global economic activity: a close-up of the COVID-19 pandemic
F44 : International Economics→Macroeconomic Aspects of International Trade and Finance→International Business Cycles
G17 : Financial Economics→General Financial Markets→Financial Forecasting and Simulation
Q02 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→General→Global Commodity Markets
This paper develops a novel indicator of global economic activity, the GEA Tracker, which is based on commodity prices selected recursively through a genetic algorithm. The GEA Tracker allows for daily real-time knowledge of international business conditions using a minimum amount of information. We find that the GEA Tracker outperforms its competitors in forecasting stock returns, especially in emerging markets, and in predicting standard indicators of international business conditions. We show that an investor would have inexorably profited from using the forecasts provided by the GEA Tracker to weight a portfolio. Finally, the GEA Tracker allows us to present the daily evolution of global economic activity during the COVID-19 pandemic.
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