Non disponibile in italiano
Lucia Alessi
- 19 October 2021
- MACROPRUDENTIAL BULLETIN - ARTICLE - No. 15Details
- Abstract
- This article estimates the “greenness” of euro area investors and the impact that the EU taxonomy could have on the markets by redirecting financial resources towards sustainable economic activities and by contributing to fill the investment gap in the relevant sectors.
- JEL Code
- G2 : Financial Economics→Financial Institutions and Services
G3 : Financial Economics→Corporate Finance and Governance
Q54 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Climate, Natural Disasters, Global Warming
- 30 September 2016
- WORKING PAPER SERIES - No. 1967Details
- Abstract
- Mainstream macroeconomic theory predicts a rapid response of asset prices to monetary policy shocks, which conventional empirical models are unable to reproduce. We argue that this is due to a deficient information set: Forward-looking economic agents observe vastly more information than the handful of variables included in standard VAR models. Thus, small-scale VARs are likely to suffer from nonfundamentalness and yield biased results. We tackle this problem by estimating a Structural Factor Model for a large euro area dataset. We find quicker and larger effects of monetary policy shocks, consistent with mainstream theory and the observed large swings in asset prices. Our results point to stronger financial stability consequences of an exogenous monetary policy tightening, also in the form of a quicker than expected unwinding of QE, than commonly thought.
- JEL Code
- C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
E43 : Macroeconomics and Monetary Economics→Money and Interest Rates→Interest Rates: Determination, Term Structure, and Effects
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
- 21 August 2014
- WORKING PAPER SERIES - No. 1723Details
- Abstract
- This paper aims at providing policymakers with a set of early warning indicators helpful in guiding decisions on when to activate macroprudential tools targeting excessive credit growth and leverage. To robustly select the key indicators we apply the
- JEL Code
- C40 : Mathematical and Quantitative Methods→Econometric and Statistical Methods: Special Topics→General
G01 : Financial Economics→General→Financial Crises
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E61 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook→Policy Objectives, Policy Designs and Consistency, Policy Coordination
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages - Network
- Macroprudential Research Network
- 10 July 2014
- WORKING PAPER SERIES - No. 1688Details
- Abstract
- This paper documents macroeconomic forecasting during the global financial crisis by two key central banks: the European Central Bank and the Federal Reserve Bank of New York. The paper is the result of a collaborative effort between staff at the two institutions, allowing us to study the time-stamped forecasts as they were made throughout the crisis. The analysis does not exclusively focuses on point forecast performance. It also examines methodological contributions, including how financial market data could have been incorporated into the forecasting process.
- JEL Code
- 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
- 28 May 2014
- FINANCIAL STABILITY REVIEW - ARTICLEFinancial Stability Review Issue 1, 2014Details
- Abstract
- Excessive credit growth has often been associated with the build-up of systemic risks to financial stability. With the entry into force of a new macro-prudential policy framework in the EU on 1 January 2014, a set of policy instruments has been made available to regulators to address such risks by curbing excessive leverage and/or imposing capital buffers which increase the resilience of the system against potential future losses. This special feature presents an early warning system designed to support macro-prudential policy decisions. Drawing on the historical experience of EU countries, the model aims to assess whether observed leverage dynamics might justify the activation of macro-prudential tools such as the counter-cyclical capital buffer proposed by the Basel Committee on Banking Supervision. The early warning indicators are based on aggregate credit-related, macroeconomic, market and real-estate variables, while the early warning thresholds are derived by considering conditional relationships between individual indicators in a unitary framework.
- JEL Code
- G00 : Financial Economics→General→General
- 16 November 2009
- WORKING PAPER SERIES - No. 1115Details
- Abstract
- We propose a new method for multivariate forecasting which combines Dynamic Factor and multivariate GARCH models. The information contained in large datasets is captured by few dynamic common factors, which we assume being conditionally heteroskedastic. After presenting the model, we propose a multi-step estimation technique which combines asymptotic principal components and multivariate GARCH. We also prove consistency of the estimated conditional covariances. We present simulation results in order to assess the finite sample properties of the estimation technique. Finally, we carry out two empirical applications respectively on macroeconomic series, with a particular focus on different measures of inflation, and on financial asset returns. Our model outperforms the benchmarks in fore-casting the inflation level, its conditional variance and the volatility of returns. Moreover, we are able to predict all the conditional covariances among the observable series.
- JEL Code
- C52 : Mathematical and Quantitative Methods→Econometric Modeling→Model Evaluation, Validation, and Selection
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
- 16 June 2009
- WORKING PAPER SERIES - No. 1061Details
- Abstract
- This paper explores the statistical properties of house-hold consumption-expenditure budget share distributions
- JEL Code
- D3 : Microeconomics→Distribution
D12 : Microeconomics→Household Behavior and Family Economics→Consumer Economics: Empirical Analysis
C12 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Hypothesis Testing: General
- 31 March 2009
- WORKING PAPER SERIES - No. 1039Details
- Abstract
- We test the performance of a host of real and financial variables as early warning indicators for costly aggregate asset price boom/bust cycles, using data for 18 OECD countries between 1970 and 2007. A signalling approach is used to predict asset price booms that have relatively serious real economy consequences. We use a loss function to rank the tested indicators given policy makers' relative preferences with respect to missed crises and false alarms. The paper analyzes the suitability of various indicators as well as the relative performance of financial versus real, global versus domestic and money versus credit based liquidity indicators. We find that global measures of liquidity are among the best performing indicators and display forecasting records, which provide useful information for policy makers interested in timely reactions to growing financial imbalances, as long as aversion against type I and type II errors is not too unbalanced. Furthermore, we explore out-of-sample whether the most recent wave of asset price booms (2005-2007) would be predicted to be followed by a serious economic downturn.
- JEL Code
- E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E51 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Money Supply, Credit, Money Multipliers
- 31 July 2008
- WORKING PAPER SERIES - No. 922Details
- Abstract
- We review, under a historical perspective, the development of the problem of nonfundamentalness of Moving Average (MA) representations of economic models. Nonfundamentalness typically arises when agents’ information space is larger than the econometrician’s one. Therefore it is impossible for the latter to use standard econometric techniques, as Vector AutoRegression (VAR), to estimate economic models. We restate the conditions under which it is possible to invert an MA representation in order to get an ordinary VAR and identify the shocks, which in a VAR are fundamental by construction. By reviewing the work by Lippi and Reichlin [1993] we show that nonfundamental shocks may be very different from fundamental shocks. Therefore, nonfundamental representations should not be ruled out by assumption and indeed methods to detect nonfundamentalness have been recently proposed in the literature. Moreover, Structural VAR (SVAR) can be legitimately used for assessing the validity of Dynamic Stochastic General Equilibrium models only if the representation associated with the economic model is fundamental. Factor models can be an alternative to SVAR for validation purposes as they do not have to deal with the problem of nonfundamentalness.
- JEL Code
- C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
C51 : Mathematical and Quantitative Methods→Econometric Modeling→Model Construction and Estimation
C52 : Mathematical and Quantitative Methods→Econometric Modeling→Model Evaluation, Validation, and Selection
- 20 May 2008
- WORKING PAPER SERIES - No. 903Details
- Abstract
- We propose a refinement of the criterion by Bai and Ng [2002] for determining the number of static factors in factor models with large datasets. It consists in multi-plying the penalty function by a constant which tunes the penalizing power of the function itself as in the Hallin and Liška [2007] criterion for the number of dynamic factors. By iteratively evaluating the criterion for different values of this constant, we achieve more robust results than in the case of fixed penalty function. This is shown by means of Monte Carlo simulations on seven data generating processes, including heteroskedastic processes, on samples of different size. Two empirical applications are carried out on a macroeconomic and a financial dataset.
- JEL Code
- C52 : Mathematical and Quantitative Methods→Econometric Modeling→Model Evaluation, Validation, and Selection