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Lucrezia Reichlin

23 March 2006
WORKING PAPER SERIES - No. 595
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Abstract
The paper analyses output dynamics in Euro area countries in the last thirty years. It establishes robust stylized facts on output differentials within the union, on the synchronization of recessions within the area countries and on similarities and differences with respect to the US case. Finally, it provides estimates of changes in the degree of risk sharing since the early nineties. The paper finds that, since 1970, within the Euro area, gaps in levels of income per capita have been persistent. This implies that it is difficult to distinguish convergence patterns from persistent fluctuations around different means. However, these gaps are small and business cycle characteristics, when measured by levels of output, have been very similar across countries. Output variance, the paper finds, is mainly explained by common shocks with similar propagation mechanisms while idiosyncratic shocks, although persistent, are small. These characteristics are in line with what found for US regions. An implication of this result is that policy should be concerned with the common characteristic of the European cycle. The next step of the analysis is then to compare the characteristics of the Euro area cycle with the US cycle. It is found that the two cycles are driven by a common world shock, but that the propagation of the shock differs across the two areas: the Euro Area lags the US and its cycle is more persistent, but less volatile. Low growth, persistence of shocks and low volatility are common characteristics of the Euro area and the gap with respect to the US has been stable over the last thirty years. Facing these historical characteristics, the process of European integration, has however helped to smooth the cross-sectional correlation of consumption conditional on output. This finding supports the hypothesis that, since the early nineties, risk sharing has increased within the Euro Area.
JEL Code
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
F2 : International Economics→International Factor Movements and International Business
F43 : International Economics→Macroeconomic Aspects of International Trade and Finance→Economic Growth of Open Economies
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Proceedings of June 2005 workshop on what effects is EMU having on the euro area and its member countries?
26 May 2006
WORKING PAPER SERIES - No. 633
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Abstract
This paper formalizes the process of updating the nowcast and forecast on output and inflation as new releases of data become available. The marginal contribution of a particular release for the value of the signal and its precision is evaluated by computing "news" on the basis of an evolving conditioning information set. The marginal contribution is then split into what is due to timeliness of information and what is due to economic content. We find that the Federal Reserve Bank of Philadelphia surveys have a large marginal impact on the nowcast of both inflation variables and real variables and this effect is larger than that of the Employment Report. When we control for timeliness of the releases, the effect of hard data becomes sizeable. Prices and quantities affect the precision of the estimates of inflation while GDP is only affected by real variables and interest rates.
JEL Code
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
26 May 2006
WORKING PAPER SERIES - No. 632
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Abstract
This paper asks two questions. First, can we detect empirically whether the shocks recovered from the estimates of a structural VAR are truly structural Second, can the problem of nonfundamentalness be solved by considering additional information? The answer to the first question is "yes" and that to the second is "under some conditions".
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
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
E00 : Macroeconomics and Monetary Economics→General→General
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
O3 : Economic Development, Technological Change, and Growth→Technological Change, Research and Development, Intellectual Property Rights
11 September 2006
WORKING PAPER SERIES - No. 674
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Abstract
This paper considers quasi-maximum likelihood estimations of a dynamic approximate factor model when the panel of time series is large. Maximum likelihood is analyzed under different sources of misspecification: omitted serial correlation of the observations and cross-sectional correlation of the idiosyncratic components. It is shown that the effects of misspecification on the estimation of the common factors is negligible for large sample size (T) and the cross sectional dimension (n). The estimator is feasible when n is large and easily implementable using the Kalman smoother and the EM algorithm as in traditional factor analysis. Simulation results illustrate what are the empirical conditions in which we can expect improvement with respect to simple principle components considered by Bai (2003), Bai and Ng (2002), Forni, Hallin, Lippi, and Reichlin (2000, 2005b), Stock and Watson (2002a,b).
JEL Code
C51 : Mathematical and Quantitative Methods→Econometric Modeling→Model Construction and Estimation
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
20 December 2006
WORKING PAPER SERIES - No. 700
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Abstract
This paper considers Bayesian regression with normal and double exponential priors as forecasting methods based on large panels of time series. We show that, empirically, these forecasts are highly correlated with principal component forecasts and that they perform equally well for a wide range of prior choices. Moreover, we study the asymptotic properties of the Bayesian regression under Gaussian prior under the assumption that data are quasi collinear to establish a criterion for setting parameters in a large cross-section.
JEL Code
C11 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Bayesian Analysis: General
C13 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Estimation: General
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
16 January 2007
WORKING PAPER SERIES - No. 712
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Abstract
This paper shows how large-dimensional dynamic factor models are suitable for structural analysis. We establish sufficient conditions for identification of the structural shocks and the associated impulse response functions. In particular, we argue that, if the data follow an approximate factor structure, the “problem of fundamentalness”, which is intractable in structural VARs, can be solved provided that the impulse responses are sufficiently heterogeneous. Finally, we propose a consistent method (and n, T rates of convergence) to estimate the impulse-response functions, as well as a bootstrapping procedure for statistical inference.
JEL Code
E0 : Macroeconomics and Monetary Economics→General
C1 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General
23 February 2008
WORKING PAPER SERIES - No. 865
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Abstract
This paper shows that the explanation of the decline in the volatility of GDP growth since the mid-eighties is not the decline in the volatility of exogenous shocks but rather a change in their propagation mechanism.
JEL Code
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
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
28 October 2008
WORKING PAPER SERIES - No. 949
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Abstract
Global financial integration unlocks a huge potential for international risk sharing. We examine the degree to which international equity holdings act as a risk sharing device in industrial and emerging economies. We split equity returns into investment income (dividend distribution) and capital gains to investigate which of the two channels delivers the largest potential for risk sharing. Our evidence suggests that net capital gains are a more potent channel of risk sharing. They behave in a countercyclical way, that is they tend to be positive (negative) when the domestic economy is growing more slowly (rapidly) than the rest of the world. Countries with more countercyclical net capital gains experience improved consumption risk sharing. The empirical analysis furthermore suggests that these risk sharing properties of net capital gains have increased through time, in particular in the 1990s and early-2000s, on the back of a declining equity home bias and financial market deepening.
JEL Code
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
14 November 2008
WORKING PAPER SERIES - No. 966
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Abstract
This paper shows that Vector Autoregression with Bayesian shrinkage is an appropriate tool for large dynamic models. We build on the results by De Mol, Giannone, and Reichlin (2008) and show that, when the degree of shrinkage is set in relation to the cross-sectional dimension, the forecasting performance of small monetary VARs can be improved by adding additional macroeconomic variables and sectoral information. In addition, we show that large VARs with shrinkage produce credible impulse responses and are suitable for structural analysis.
JEL Code
C11 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Bayesian Analysis: General
C13 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Estimation: General
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
19 February 2009
WORKING PAPER SERIES - No. 1010
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Abstract
This paper shows that the EMU has not affected historical characteristics of member countries' business cycles and their cross-correlations. Member countries which had similar levels of GDP per-capita in the seventies have also experienced similar business cycles since then and no significant change associated with the EMU can be detected. For the other countries, volatility has been historically higher and this has not changed in the last ten years. We also find that the aggregate euro area per-capita GDP growth since 1999 has been lower than what could have been predicted on the basis of historical experience and US observed developments. The gap between US and euro area GDP per capita level has been 30% on average since 1970 and there is no sign of catching up or of further widening.
JEL Code
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E3 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles
C5 : Mathematical and Quantitative Methods→Econometric Modeling
F2 : International Economics→International Factor Movements and International Business
F43 : International Economics→Macroeconomic Aspects of International Trade and Finance→Economic Growth of Open Economies
1 October 2010
WORKING PAPER SERIES - No. 1253
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Abstract
This paper describes the response of three central banks to the 2007-09 financial crisis: the European Central Bank, the Federal Reserve and the Bank of England. In particular, the paper discusses the design, implementation and impact of so-called "non-standard" monetary policy measures focusing on those introduced in the euro area in the aftermath of the failure of Lehman Brothers in September 2008. Having established the impact of these measures on various observable money market spreads, we propose an empirical exercise intended to quantify the macroeconomic impact of non-standard monetary policy measures insofar as it has been transmitted via these spreads. The results suggest that non-standard measures have played a quantitatively significant role in stabilising the financial sector and economy after the collapse of Lehman Bros., even if insufficient to avoid a significant fall in economic and financial activity.
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
8 December 2010
WORKING PAPER SERIES - No. 1275
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Abstract
We define nowcasting as the prediction of the present, the very near future and the very recent past. Crucial in this process is to use timely monthly information in order to nowcast key economic variables, such as e.g. GDP, that are typically collected at low frequency and published with long delays. Until recently, nowcasting had received very little attention by the academic literature, although it was routinely conducted in policy institutions either through a judgemental process or on the basis of simple models. We argue that the nowcasting process goes beyond the simple production of an early estimate as it essentially requires the assessment of the impact of new data on the subsequent forecast revisions for the target variable. We design a statistical model which produces a sequence of nowcasts in relation to the real time releases of various economic data. The methodology allows to process a large amount of information, as it is traditionally done by practitioners using judgement, but it does it in a fully automatic way. In particular, it provides an explicit link between the news in consecutive data releases and the resulting forecast revisions. To illustrate our ideas, we study the nowcast of euro area GDP in the fourth quarter of 2008.
JEL Code
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
14 January 2011
WORKING PAPER SERIES - No. 1290
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Abstract
Standard accounts of the Great Depression attribute an important causal role to monetary policy errors in accounting for the catastrophic collapse in economic activity observed in the early 1930s. While views vary on the relative importance of money versus credit contraction in the propagation of this policy error to the wider economy and ultimately price developments, a broad consensus exists in the economics profession around the view that the collapse in financial intermediation was a crucial intermediary step. What lessons have monetary policy makers taken from this episode? And how have they informed the conduct of monetary policy by leading central banks in recent times? This paper sets out to address these questions, in the context of the financial crisis of 2008-09 and with application to the euro area. It concludes that the Eurosystem’s non-standard monetary policy measures have supported monetary policy transmission and avoided the calamity of the 1930s.
JEL Code
E5 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit
E4 : Macroeconomics and Monetary Economics→Money and Interest Rates
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
21 November 2012
WORKING PAPER SERIES - No. 1496
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Abstract
We analyse the impact on the euro area economy of the ECB’s non-standard monetary policy measures by studying the effect of the expansion of intermediation of interbank transactions across the central bank balance sheet. We exploit data drawn from the aggregated Monetary and Financial Institutions (MFI) balance sheet, which allows us to construct a measure of the ‘policy shock’ represented by the ECB’s increasing role as a financial intermediary. We find small but significant effects both on loans and real economic activity.
JEL Code
E5 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
9 July 2013
WORKING PAPER SERIES - No. 1564
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Abstract
The term now-casting is a contraction for now and forecasting and has been used for a long-time in meteorology and recently also in economics. In this paper we survey recent developments in economic now-casting with special focus on those models that formalize key features of how market participants and policy makers read macroeconomic data releases in real time, which involves: monitoring many data, forming expectations about them and revising the assessment on the state of the economy whenever realizations diverge sizeably from those expectations. (Prepared for G. Elliott and A. Timmermann, eds., Handbook of Economic Forecasting, Volume 2, Elsevier-North Holland).
JEL Code
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
C01 : Mathematical and Quantitative Methods→General→Econometrics
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
25 January 2019
WORKING PAPER SERIES - No. 2226
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Abstract
This paper studies the relationship between the business cycle and financial intermediation in the euro area. We establish stylized facts and study their stability during the global financial crisis and the European sovereign debt crisis. Long-term interest rates have been exceptionally high and long-term loans and deposits exceptionally low since the Lehman collapse. Instead, short-term interest rates and short-term loans and deposits did not show abnormal dynamics in the course of the financial and sovereign debt crisis.
JEL Code
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E51 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Money Supply, Credit, Money Multipliers
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
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