Mario Forni
Center for Economic and Policy Research
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Featured researches published by Mario Forni.
The Review of Economics and Statistics | 2000
Mario Forni; Marc Hallin; Marco Lippi; Lucrezia Reichlin
This paper proposes a factor model with infinite dynamics and nonorthogonal idiosyncratic components. The model, which we call the generalized dynamic-factor model, is novel to the literature and generalizes the static approximate factor model of Chamberlain and Rothschild (1983), as well as the exact factor model la Sargent and Sims (1977). We provide identification conditions, propose an estimator of the common components, prove convergence as both time and cross-sectional size go to infinity at appropriate rates, and present simulation results. We use our model to construct a coincident index for the European Union. Such index is defined as the common component of real GDP within a model including several macroeconomic variables for each European country.
Journal of the American Statistical Association | 2005
Mario Forni; Marc Hallin; Marco Lippi; Lucrezia Reichlin
This article proposes a new forecasting method that makes use of information from a large panel of time series. Like earlier methods, our method is based on a dynamic factor model. We argue that our method improves on a standard principal component predictor in that it fully exploits all the dynamic covariance structure of the panel and also weights the variables according to their estimated signal-to-noise ratio. We provide asymptotic results for our optimal forecast estimator and show that in finite samples, our forecast outperforms the standard principal components predictor.
Econometric Theory | 2009
Mario Forni; Domenico Giannone; Marco Lippi; Lucrezia Reichlin
This paper shows how large-dimensional dynamic factor models are suitable for structural analysis. We argue that all identification schemes employed in SVAR analysis can be easily adapted in dynamic factor models. Moreover, the “problem of fundamentalness”, which is intractable in structural VARs, can be solved, provided that the impulse-response functions are sufficiently heterogeneous. We provide consistent stimators for the impulse-response functions, as well as (n, T) rates of convergence. An exercise with US macroeconomic data shows that our solution of the fundamentalness problem may have important empirical consequences.
The Review of Economics and Statistics | 2001
Christophe Croux; Mario Forni; Lucrezia Reichlin
This paper proposes a measure of dynamic comovement between (possibly many) time series and names it cohesion. The measure is defined in the frequency domain and is appropriate for processes that are costationary, possibly after suitable transformations. In the bivariate case, the measure reduces to dynamic correlation and is related, but not equal, to the well known quantities of coherence and coherency. Dynamic correlation on a frequency band equals (static) correlation of bandpass-filtered series. Moreover, long-run correlation and cohesion relate in a simple way to co-integration. Cohesion is useful to study problems of business-cycle synchronization, to investigate short-run and long-run dynamic properties of multiple time series, and to identify dynamic clusters. We use state income data for the United States and GDP data for European nations to provide an empirical illustration that is focused on the geographical aspects of business-cycle fluctuations.
S.Co.2007. | 2007
Filippo Altissimo; Riccardo Cristadoro; Mario Forni; Marco Lippi; Giovanni Veronese
This paper presents ideas and methods underlying the construction of an indicator that tracks the euro area GDP growth, but, unlike GDP growth, (i) is updated monthly and almost in real time; (ii) is free from hort-run dynamics. Removal of short-run dynamics from a time series, to isolate the mediumlong-run component, can be obtained by a band-pass filter. However, it is well known that band-pass filters, being two-sided, perform very poorly at the end of the sample. New Eurocoin is an estimator of the medium- long-run component of the GDP that only uses contemporaneous values of a large panel of macroeconomic time series, so that no end-of-sample deterioration occurs. Moreover, as our dataset is monthly, New Eurocoin can be updated each month and with a very short delay. Our method is based on generalized principal components that are designed to use leading variables in the dataset as proxies for future values of the GDP growth. As the medium- long-run component of the GDP is observable, although with delay, the performance of New Eurocoin at the end of the sample can be measured.
Journal of Monetary Economics | 2003
Mario Forni; Marc Hallin; Marco Lippi; Lucrezia Reichlin
The Paper uses a large data set, consisting of 447 monthly macroeconomic time series concerning the main countries of the Euro area to simulate out-of-sample predictions of the Euro area industrial production and the harmonized inflation index and to evaluate the role of financial variables in forecasting. We considered two models which allow forecasting based on large panels of time series: Forni, Hallin, Lippi, and Reichlin (2000, 2001c) and Stock and Watson (1999). Performance of both models was compared to that of a simple univariate AR model. Results show that multivariate methods outperform univariate methods for forecasting inflation at one, three, six, and twelve months and industrial production at one and three months. We find that financial variables do help forecasting inflation, but do not help forecasting industrial production. (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.)
Journal of Econometrics | 2004
Mario Forni; Marc Hallin; Marco Lippi; Lucrezia Reichlin
Abstract A factor model generalizing those proposed by Geweke (in: D.J. Aigner and A.S. Goldberger, Latent Variables in Socio-Economic Models, North-Holland, Amsterdam, 1977), Sargent and Sims (New Methods in Business Research, Federal Reserve Bank of Minneapolis, Minneapolis, 1977), Engle and Watson (J. Amer. Statist. Assoc. 76 (1981) 774) and Stock and Watson (J. Business. Econom. Statist. 20 (2002) 147) has been introduced in Forni et al. (Rev. Econ. Statist. 80 (2000) 540), where consistent (as the number n of series and the number T of observations both tend to infinity along appropriate paths (n,T(n))) estimation methods for the common component are proposed. Rates of convergence associated with these methods are obtained here as functions of the paths (n,T(n)) along which n and T go to infinity. These results show that, under suitable assumptions, consistency requires T(n) to be at least of the same order as n, whereas an optimal rate of n is reached for T(n) of the order of n2. If convergence to the space of common components is considered, consistency holds irrespective of the path (T(n) thus can be arbitrarily slow); the optimal rate is still n , but only requires T(n) to be of the order of n.
The Economic Journal | 2001
Mario Forni; Marc Hallin; Marco Lippi; Lucrezia Reichlin
This paper proposes a new way to compute a coincident and a leading indicator of economic activity. Our methodology, based on Forni, Hallin, Lippi and Reichlin (2000), reconciles dynamic principal components analysis with dynamic factor analysis. It allows us to extract indicators from a large panel of economic variables (many variables for many countries). The procedure is used to estimate coincident and leading indicators for the EURO area. Unlike other methods used in the literature, the procedure takes into consideration the cross-country as well as the within-country correlation structure and exploit all information on dynamic cross-correlation.(This abstract was borrowed from another version of this item.)
European Economic Review | 2001
Mario Forni; Lucrezia Reichlin
Abstract This paper establishes stylized facts on regional output fluctuations in Europe and the US. Moreover, it proposes a measure of the potential output target of the future European central bank, estimates the potential variance stabilization of a fiscal federation and constructs a regional map of the potential beneficiaries of monetary and fiscal federal policies. The econometric model is an extention of the dynamic factor model a la Sargent and Sims (1977. In: Sims, C.A. (Ed.), New Methods in Business Research. Federal Reserve Bank of Minneapolis) where we introduce an intermediate-level shock, which is common to all regions (counties) in each country (state), but it is not common to Europe (US) as a whole. We build on Forni and Reichlin 1996. Empirical Economics, Long-Run Economic Growth (special issue) 21 (1996) 27–42. Review of Economic Studies 65 (1998) 453–473 to propose an estimation method which exploits the large cross-sectional dimension of our data set. Our analysis shows that (i) Europe has a level of integration similar to that of the US and that national shocks are not a sizeable source of fluctuations: around 75% of output variance is explained by global and purely local dynamics; (ii) Europe, unlike the US, has no traditional business cycle; (iii) the core of the most integrated regions in Europe does not have national boundaries; (iv) the future European Central Bank has a potential stabilization target of about 18% of total output fluctuations; (v) a fiscal federation, if implemented, could have a smoothing effect on output in addition to what done by national fiscal policy, which accounts also for about 18% of total output fluctuations.
The Economic Journal | 2014
Mario Forni; Luca Gambetti; Luca Sala
This paper uses a structural, large dimensional factor model to evaluate the role of ‘news’ shocks (shocks with a delayed eect on productivity) in generating the business cycle.