Nie ma wersji polskiej
Fabrizio Venditti
- 13 January 2006
- WORKING PAPER SERIES - No. 574Details
- Abstract
- We study the convergence properties of inflation rates among the countries of the European Monetary Union over the period 1980-2004. Given the Maastricht agreements and the adoption of the single currency, the sample can be naturally split into two parts, before and after the birth of the euro. We study convergence in the first sub-sample by means of univariate and multivariate unit root tests on inflation differentials, arguing that the power of the tests is considerably increased if the Dickey-Fuller regressions are run without an intercept term. Overall, we are able to accept the convergence hypothesis over the period 1980-1997. We then investigate whether the second sub-sample is characterized by stable inflation rates across the European countries. Using stationarity tests on inflation differentials, we find evidence of diverging behaviour. In particular, we can statistically detect two separate clusters, or or convergence clubs: a lower inflation group that comprises Germany, France, Belgium, Austria, Finland and a higher inflation one with Spain, Netherlands, Greece, Portugal and Ireland. Italy appears to form a cluster of its own, standing in between the other two.
- JEL Code
- C12 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Hypothesis Testing: General
C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
- 3 June 2008
- WORKING PAPER SERIES - No. 900Forecasting inflation and tracking monetary policy in the euro area: does national information help?Details
- Abstract
- The ECB objective is set in terms of year on year growth rate of the Euro area HICP. Nonetheless, a good deal of attention is given to national data by market analysts when they try to anticipate monetary policy moves. In this paper we use the Generalized Dynamic Factor model to develop a set of core inflation indicators that, combining national data with area wide information, allow us to answer two related questions. The first is whether country specific data actually bear any relevance for the future path of area wide price growth, over and above that already contained in area wide data. The second is whether in order to track ECB monetary policy decisions it is useful to take into account national information and not only area wide statistics. In both cases our findings point to the conclusion that, once area wide information is properly taken into account, there is little to be gained from considering national idiosyncratic developments.
- JEL Code
- C25 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Discrete Regression and Qualitative Choice Models, Discrete Regressors, Proportions
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
- 16 June 2010
- OCCASIONAL PAPER SERIES - No. 113Details
- Abstract
- This report aims to analyse euro area energy markets and the impact of energy price changes on the macroeconomy from a monetary policy perspective. The core task of the report is to analyse the impact of energy price developments on output and consumer prices. Nevertheless, understanding the link between energy price fluctuations, inflationary pressures and the role of monetary policy in reacting to such pressure requires a deeper look at the structure of the economy. Energy prices have presented a challenge for the Eurosystem, as the volatility of the energy component of consumer prices has been high since the creation of EMU. At the same time, a look back into the past may not necessarily be very informative for gauging the likely impact of energy price changes on overall inflation in the future. For instance, the reaction of HICP inflation to energy price fluctuations seems to have been more muted during the past decade than in earlier periods such as the 1970s.
- JEL Code
- E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy - Network
- Eurosystem Monetary Transmission Network
- 27 September 2018
- ECONOMIC BULLETIN - ARTICLEEconomic Bulletin Issue 6, 2018Details
- Abstract
- As financial markets became progressively more integrated internationally over the past decades, economists wondered to what extent policymakers can isolate domestic financial conditions from external factors. This article reviews the terms of this debate and provides fresh evidence on the co-movement in capital flows and stock prices across a panel of 50 advanced and emerging economies. In particular, the article focuses on the relative importance of global risk and US monetary policy for the global financial cycle and touches upon the implications for the exchange rate regime. Global risk aversion emerges as a significant driver of capital flows and stock returns and its impact is amplified by capital account openness, but not necessarily by the exchange rate regime, which matters only for asset prices, not for capital flows. The quantitative relevance of US monetary policy and the US dollar exchange rate seems to be episodic. In particular, the correlation between US interest rates and capital flows throughout the crisis is positive, rather than negative as the theory would predict, indicating the need for further empirical analysis of the role of US monetary policy as the driver of the global financial cycle. The article also finds that financial market tensions have been typically synchronised between the euro area and the United States but that financial conditions in the two areas have often decoupled. Overall, this confirms that the effectiveness of the ECB’s monetary policy has not been impaired by the global financial cycle.
- JEL Code
- E42 : Macroeconomics and Monetary Economics→Money and Interest Rates→Monetary Systems, Standards, Regimes, Government and the Monetary System, Payment Systems
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
F31 : International Economics→International Finance→Foreign Exchange
F36 : International Economics→International Finance→Financial Aspects of Economic Integration
F41 : International Economics→Macroeconomic Aspects of International Trade and Finance→Open Economy Macroeconomics
- 29 November 2018
- FINANCIAL STABILITY REVIEW - BOXFinancial Stability Review Issue 2, 2018Details
- Abstract
- This box describes a simple structural Bayesian vector autoregression (BVAR) model that uses sign restrictions to determine the relative importance of distinct economic and financial shocks in shaping the co-movement of key global financial variables. The model provides intuitive and economically plausible interpretations of gyrations in key US and global asset markets over the past six months. The model ascribes them to a multitude of factors, including strong nominal US demand, heightened investor risk aversion as well as the prospect of higher US inflation and tighter monetary conditions.
- 12 April 2019
- WORKING PAPER SERIES - No. 2261Details
- Abstract
- The paper proposes a framework for assessing the impact of system-wide and bank-level capital buffers. The assessment rests on a factor-augmented vector autoregression (FAVAR) model that relates individual bank adjustments to macroeconomic dynamics. We estimate FAVAR models individually for eleven euro area economies and identify structural shocks, which allow us to diagnose key vulnerabilities of national banking systems and estimate short-run economic costs of increasing banks’ capitalisation. On this basis, we run a fully-fledged cost-benefit assessment of an increase in capital buffers. The benefits are related to an increase in bank resilience to adverse shocks. Higher capitalisation allows banks to withstand negative shocks and moderates the reduction of credit to the real economy that ensues in adverse circumstances. The costs relate to transitory credit and output losses that are assessed both on an aggregate and bank level. An increase in capital ratios is shown to have a sharply different impact on credit and economic activity depending on the way banks adjust, i.e. via changes in assets or equity.
- JEL Code
- E51 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Money Supply, Credit, Money Multipliers
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
- 15 May 2019
- WORKING PAPER SERIES - No. 2280Details
- Abstract
- In this paper, we study the effects of structural shocks that influence global risk – the main factor behind a “global capital flows cycle” – and how risk, in turn, is transmitted to capital flows. Our results show that not all the risk shocks driving the global financial cycle have the same effects on capital flows. Changes in global risk caused by pure financial shocks have the largest impact on the global configuration of capital flows, followed by US monetary policy shocks. As regards the transmission of risk to capital flows, we uncover a traditional “trilemma”, as countries more financially open and adopting a strict peg are more sensitive to global risk. This “trilemma” is mainly driven by one category of cross-border flows, “other investment”, confirming the importance of cross-border banking loans in the narrative of the global financial cycle.
- JEL Code
- E42 : Macroeconomics and Monetary Economics→Money and Interest Rates→Monetary Systems, Standards, Regimes, Government and the Monetary System, Payment Systems
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
F31 : International Economics→International Finance→Foreign Exchange
F36 : International Economics→International Finance→Financial Aspects of Economic Integration
F41 : International Economics→Macroeconomic Aspects of International Trade and Finance→Open Economy Macroeconomics
- 7 January 2020
- WORKING PAPER SERIES - No. 2355Details
- Abstract
- We study what makes government bonds a safe asset. Building on a sample of monthly changes in government bond yields in 40 advanced and emerging countries, we analyse the sensitivity of yields to country specific fundamentals interacted with changes in global risk (VIX). We find that inertia (whether the bond behaved as a safe asset in the past) and good institutions foster a safe asset status, while the size of the debt market is also significant, reflecting the special role of the US. Within advanced and emerging markets, drivers are heterogeneous, with external sustainability in particular being relevant for the latter countries after the global financial crisis. Finally, the safe asset status does not appear to depend on whether the change in global risk is driven by financial shocks rather than by US monetary policy.
- JEL Code
- E42 : Macroeconomics and Monetary Economics→Money and Interest Rates→Monetary Systems, Standards, Regimes, Government and the Monetary System, Payment Systems
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
F31 : International Economics→International Finance→Foreign Exchange
F36 : International Economics→International Finance→Financial Aspects of Economic Integration
F41 : International Economics→Macroeconomic Aspects of International Trade and Finance→Open Economy Macroeconomics
- 30 January 2020
- WORKING PAPER SERIES - No. 2368Details
- Abstract
- In a simplified theoretical framework we model the strategic interactions between OPEC and non-OPEC producers and the implications for the global oil market. Depending on market conditions, OPEC may find it optimal to act either as a monopolist on the residual demand curve, to move supply in-tandem with non-OPEC, or to offset changes in non-OPEC supply. We evaluate the implications of the model through a Structural Vector Auto Regression (VAR) that separates non-OPEC and OPEC production and allows OPEC to respond to supply increases in non-OPEC countries. This is done by either increasing production (Market Share Targeting) or by reducing it (Price Targeting). We find that Price Targeting shocks absorb half of the fluctuations in oil prices, which have left unexplained by a simpler model (where strategic interactions are not taken into account). Price Targeting shocks, ignored by previous studies, explain around 10 percent of oil price fluctuations and are particularly relevant in the commodity price boom of the 2000s. We confirm that the fall in oil prices at the end of 2014 was triggered by an attempt of OPEC to re-gain market shares. We also find the OPEC elasticity of supply three times as high as that of non-OPEC producers.
- JEL Code
- Q41 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Energy→Demand and Supply, Prices
Q43 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Energy→Energy and the Macroeconomy
- 3 February 2020
- WORKING PAPER SERIES - No. 2369Details
- Abstract
- In this paper we develop a general framework to analyze state space models with time-varying system matrices where time variation is driven by the score of the conditional likelihood. We derive a new filter that allows for the simultaneous estimation of the state vector and of the time-varying parameters. We use this method to study the time-varying relationship between the price dividend ratio, expected stock returns and expected dividend growth in the US since 1880. We find a significant increase in the long-run equilibrium value of the price dividend ratio over time, associated with a fall in the long-run expected rate of return on stocks. The latter can be attributed mainly to a decrease in the natural rate of interest, as the long-run risk premium has only slightly fallen.
- JEL Code
- C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
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
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
- 11 August 2020
- WORKING PAPER SERIES - No. 2451Details
- Abstract
- In this paper we assess the merits of financial condition indices constructed using simple averages versus a more sophisticated alternative that uses factor models with time varying parameters. Our analysis is based on data for 18 advanced and emerging economies at a monthly frequency covering about 70% of the world’s GDP. We use four criteria to assess the performance of these indicators, namely quantile regressions, Structural Vector Autoregressions, the ability of the indices to predict banking crises and their response to US monetary policy shocks. We find that averaging across the indicators of interest, using judgemental but intuitive weights, produces financial condition indices that are not inferior to, and actually perform better than, those constructed with more sophisticated statistical methods.
- JEL Code
- E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
C11 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Bayesian Analysis: General
C55 : Mathematical and Quantitative Methods→Econometric Modeling→Modeling with Large Data Sets?
- 14 September 2020
- WORKING PAPER SERIES - No. 2467Details
- Abstract
- Between January 2017 and March 2020 a coalition of oil producers led by OPEC and Russia (known as OPEC+) cut oil production in an attempt to raise the price of crude oil. In March 2020 the corona virus shock led to a collapse of this coalition, as members did not agree on keeping the oil market tight in the face of a large negative demand shock. Yet, was OPEC+ actually effective in sustaining the price of oil? Between 2017 and early 2020 when the OPEC+ strategy was in place, oil inventories fell substantially and the price of oil reached a peak of around 80 USD per barrel, from a minimum of 30 USD in 2016. This suggests that the OPEC+ strategy had a significant impact on the global oil market. Yet, to what extent did crude prices actually reflect OPEC+ production cuts rather than other factors, like swings in demand for oil? How would the price of oil have evolved had OPEC+ not cut supply? This paper provides an answer to these questions through a counterfactual analysis based on two structural models of the global oil market. We find the impact of OPEC+ on the market was overall quite limited, owing to significant deviations from the assigned quotas. On average, without the OPEC+ cuts, the price of oil would have been 6 percent (4 USD) lower.
- JEL Code
- Q43 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Energy→Energy and the Macroeconomy
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
- 29 September 2020
- WORKING PAPER SERIES - No. 2472Details
- Abstract
- The role that the price of oil plays in economic analysis in central banks as well as in financial markets has evolved over time. Oil is not seen anymore just as a input to production but also as a barometer of global economic activity as well as a financial asset. A high frequency structural decomposition of the price of oil can therefore inform on the state of the global business cycle as well as on global financial market sentiment. In this paper we develop a method to identify structural sources of oil price fluctuations at the daily frequency and in real time. The identification strategy blends sign, narrative restrictions and instrumental variable techniques. By using data on asset prices, oil production and global economic activity we account for the double nature of oil: a financial asset as well as a physical commodity. The model offers novel insights on the relationship between the price of oil and asset prices. We also illustrate how the model could have been used in real time to interpret oil price movements in periods of high geopolitical tensions between the US and Iran and to read the drop of crude prices due to fears related to the Corona virus.
- JEL Code
- Q43 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Energy→Energy and the Macroeconomy
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods