Opening the black box: structural factor models with large cross-sections

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 Classification: E0, C1Dynamic Factor Models, fundamentalness, Identification, structural VARs

The Generalized Dynamic Factor Model. One-Sided Estimation and Forecasting

This paper proposes a new forecasting method that exploits information from a largepanel of time series. The method is based on the generalized dynamic factor model proposedin Forni, Hallin, Lippi, and Reichlin (2000), and takes advantage of the information onthe dynamic covariance structure of the whole panel. We first use our previous method toobtain an estimation for the covariance matrices of common and idiosyncratic components.The generalized eigenvectors of this couple of matrices are then used to derive a consistentestimate of the optimal forecast. This two-step approach solves the end-of-sample problemscaused by two-sided filtering (as in our previous work), while retaining the advantages of anestimator based on dynamic information. The relative merits of our method and the oneproposed by Stock and Watson (2002) are discussed.Dynamic factor models,principal components, time series, large cross-sections, panel data, forecasting.

New Eurocoin: Tracking Economic Growth in Real Time

Removal of short-run dynamics from a stationary time series to isolate the medium to long-run component, can be obtained by a band-pass filter. However, band pass filters are infinite moving averages and can therefore deteriorate at the end of the sample. This is a well-known result in the literature isolating the business cycle in integrated series. We show that the same problem arises with our application to stationary time series. In this paper we develop a method to obtain smoothing of a stationary time series by using only contemporaneous values of a large dataset, so that no end-of-sample deterioration occurs. Our construction is based on a special version of Generalized Principal Components, which is designed to use leading variables in the dataset as proxies for missing future values in the variable of interest. Our method is applied to the construction of New Eurocoin, an indicator of economic activity for the euro area. New Eurocoin is an estimate, in real time, of the medium to long-run component of the euro area GDP growth, which performs equally well within and at the end of the sample. As our dataset is monthly and most of the series are updated with a short delay, we are able to produce a monthly, real-time indicator. An assessment of its performance as an approximation of the medium to long-run GDP growth, both in terms of fitting and turning-point signaling, is provided.Coincident Indicator, Band-pass Filter, Large-dataset Factor Models, Generalized Principal Components

New Eurocoin: Tracking Economic Growth in Real Time

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.coincident indicator, band-pass filter, large-dataset factor models, generalized principal components

When expectations of technological change in the economy are noisy signals

These expectations, or 'animal spirits', explain much of the volatility in investment, consumption and GDP, write Luca Sala, Luca Gambetti, Mario Forni and Marco Lipp

A real time coincident indicator of the euro area business cycle

This paper is the result of the Bank of Italy-CEPR project to construct a monthly coincident indicator of the business cycle of the euro area. The index is estimated on the basis of a harmonized data set of monthly statistics of the euro area (951 series) which we constructed from a variety of sources. We use the information of this large panel to obtain an indicator which has three characteristics: (i) it provides real time information on monthly coincident activity since it is updated as new information become available in a non-synchronous way; (ii) it is cleaned from noise originated from measurement error and idiosyncratic national and sectoral dynamics; (iii) it is cleaned from seasonal and short-run dynamics through a Þlter that requires very little revision at the end of the sample. Unlike other methods used in the literature, the procedure takes into consideration the cross-country as well as the within-country correlation structure and exploits all information on dynamic cross-correlations. As a byproduct of our analysis, we provide a characterization of the commonality and dynamic relations of the series in the data set with respect to the coincident indicator and a dating of the euro area cycle.business cycle, dynamic factor model

From red to blue shift: switching the binding affinity from the acceptor to the donor end by increasing the π-bridge in push–pull chromophores with coordinative ends

A series of homologous push–pull compounds, in which identical donor (a dimethylamino) and acceptor (a malonate ester) functionalities endcap crescent PPV fragments, exhibit striking differences in their supramolecular recognition of cations acting as Lewis acids. The shorter conjugated compound (one phenyl ring) coordinates a wide variety of lanthanide cations (Eu3+, Yb3+ and Er3+) in MeCN solutions to the 1,3-dicarbonyl acceptor end, resulting in an overall supramolecular polarization of the system (red shift of the intramolecular charge-transfer ICT band). With the “hard” cation Sc3+, recognition switches to the tertiary amine donor end, turning the conjugated system from D–π–A to A–π–A, and resulting in a blue shift of the ICT band upon complexation. Interestingly, increasing the conjugation by means of the insertion of sequential p-phenylenevinylene units into the ligand results in coordination to the donor end regardless of cation “hardness” (Sc3+, Eu3+ and Er3+), suggesting a relative change in the nucleophilicity of the two coordinating ends when increasing the length of the conjugated π-bridge. Such a hypothesis is supported by quantum chemical calculations on the ligands and subsequent atomic charges determination using two independent approaches (QTAIM and CHelpG). The characterization of the thermodynamic stabilities and the dimensionalities of the ligand–cation complexes in solution reveals striking differences from case to case, yet increasing affinities (from log Kav = 2.5 to log Kav = 4.9) are recorded with the increase of the π-conjugated bridge

Halogen bonding enhances nonlinear optical response in poled supramolecular polymers

We demonstrate that halogen bonding strongly enhances the nonlinear optical response of poled supramolecular polymer systems. We compare three nonlinear optical chromophores with similar electronic structures but different bond-donating units, and show that both the type and the strength of the noncovalent interaction between the chromophores and the polymer matrix play their own distinctive roles in the optical nonlinearity of the systems