A randomised sequential procedure to determine the number of factors

This paper proposes a procedure to estimate the number of common factors k in a static approximate factor model. The building block of the analysis is the fact that the first k eigenvalues of the covariance matrix of the data diverge, whilst the others stay bounded. On the grounds of this, we propose a test for the null that the i-th eigenvalue diverges, using a randomised test statistic based directly on the estimated eigenvalue. The test only requires minimal assumptions on the data, and no assumptions are required on factors, loadings or idiosyncratic errors. The randomised tests are then employed in a sequential procedure to determine k

Testing for Exogeneity in Cointegrated Panels

This paper proposes a test for the null that, in a cointegrated panel, the long-run correlation between the regressors and the error term is different from zero. As is well known, in such case the OLS estimator is T-consistent, whereas it is NT-consistent when there is no endogeneity. Other estimators can be employed, such as the FM-OLS, that are NT-consistent irrespective of whether exogeneity is present or not. Using the difference between the former and the latter estimator, we construct a test statistic which diverges at a rate N under the null of endogeneity, whilst it is bounded under the alternative of exogeneity, and employ a randomization approach to carry out the test. Monte Carlo evidence shows that the test has the correct size and good power

Micro versus macro cointegration in heterogeneous panels

We consider the issue of cross-sectional aggregation in nonstationary and heterogeneous panels where each unit cointegrates. We derive asymptotic properties of the aggregate estimate, and necessary and sufficient conditions for cointegration to hold in the aggregate relationship. We then analyze the case when cointegration does not carry through the aggregation process, and we investigate whether the violation of the formal conditions for perfect aggregation can still lead to an aggregate equation that is observationally equivalent to a cointegrated relationship. We derive a measure of the degree of noncointegration of the aggregate relationship and we explore its asymptotic properties. We propose a valid bootstrap approximation of the test. A Monte Carlo exercise evaluates size and power properties of the bootstrap test

Detection of the ultranarrow temporal correlation of twin beams via sum-frequency generation

We demonstrate the ultranarrow temporal correlation (6 fs full width half maximum) of twin beams generated by parametric down-conversion, by using the inverse process of sum-frequency generation. The result relies on an achromatic imaging of a huge bandwith of twin beams and on a careful control of their spatial degrees of freedom. The detrimental effects of spatial filtering and of imperfect imaging are shown toghether with the theoretical model used to describe the results

Quantum spatial correlations in high-gain parametric down-conversion measured by means of a CCD camera

We consider travelling-wave parametric down-conversion in the high-gain regime and present the experimental demonstration of the quantum character of the spatial fluctuations in the system. In addition to showing the presence of sub-shot noise fluctuations in the intensity difference, we demonstrate that the peak value of the normalized spatial correlations between signal and idler lies well above the line marking the boundary between the classical and the quantum domain. This effect is equivalent to the apparent violation of the Cauchy-Schwartz inequality, predicted by some of us years ago, which represents a spatial analogue of photon antibunching in time. Finally, we analyse numerically the transition from the quantum to the classical regime when the gain is increased and we emphasize the role of the inaccuracy in the determination of the symmetry center of the signal/idler pattern in the far-field plane.Comment: 21 pages, 11 figures, submitted to J. Mod. Opt. special issue on Quantum Imagin

Common stochastic trends and aggregation in heterogeneous panels

In nonstationary heterogeneous panels where the number of units is finite and where each unit cointegrates, a large number of conditions needs to be satisfied for cointegration to be preserved in the aggregate relationship. In reality, the conditions most likely will not hold. This paper takes a closer look at what happens when the conditions are violated. In this case, the question of whether an aggregate relationship is observationally equivalent to a cointegrating equation is of particular interest. We derive a measure of the degree of noncointegration of the aggregate estimates, and we explore its asymptotic properties

Testing for instability in covariance structures

We propose a test for the stability over time of the covariance matrix of multivariate time series. The analysis is extended to the eigensystem to ascertain changes due to instability in the eigenvalues and/or eigenvectors. Using strong Invariance Principles and Law of Large Numbers, we normalise the CUSUM-type statistics to calculate their supremum over the whole sample. The power properties of the test versus alternative hypotheses, including also the case of breaks close to the beginning/end of sample are investigated theoretically and via simulation. We extend our theory to test for the stability of the covariance matrix of a multivariate regression model. The testing procedures are illustrated by studying the stability of the principal components of the term structure of 18 US interest rates

Industry Effects on Firm and Segment Profitability Forecasting

Academics and practitioners have long recognized the importance of a firm’s industry membership in explaining its financial performance. Yet, contrary to conventional wisdom, recent research shows that industry-specific profitability forecasting models are not better than economy-wide models. The objective of this paper is to further explore this result and to provide insights into when and why industry-specific profitability forecasting models are useful. We show that industry-specific forecasts are significantly more accurate in predicting profitability for single-segment firms and, to some extent, for business segments. For multiple-segment firms, the aggregation of segment-level data for external reporting of firm-level financials obliterates the industry effects of their segments

Multi-material spectral photon-counting micro-CT with minimum residual decomposition and self-supervised deep denoising

Spectral micro-CT imaging with direct-detection energy discriminating photon counting detectors having small pixel size (< 100×100 μm2) is mainly hampered by: i) the limited energy resolution of the imaging device due to charge sharing effects and ii) the unavoidable noise amplification in the images resulting from basis material decomposition. In this work, we present a cone-beam micro-CT setup that includes a CdTe photon counting detector implementing a charge summing hardware solution to correct for the charge-sharing issue and an innovative image processing pipeline based on accurate modeling of the spectral response of the imaging system, an improved basis material decomposition (BMD) algorithm named minimum-residual BMD (MR-BMD), and self-supervised deep convolutional denoising. Experimental tomographic projections having a pixel size of 45×45 μm2 of a plastinated mouse sample including I, Ba, and Gd small cuvettes were acquired. Results demonstrate the capability of the combined hardware and software tools to sharply discriminate even between materials having their K-Edge separated by a few keV, such as e.g., I and Ba. By evaluating the quality of the reconstructed decomposed images (water, bone, I, Ba, and Gd), the quantitative performances of the spectral system are here assessed and discusse

La dimensione territoriale nell\u2019approccio dei living labs. Verso i territorial living labs per il sostegno alle citt\ue0 e alle regioni\u2018smart\u2019

Le politiche comunitarie di sostegno alla pianificazione spaziale centrate sul policentrismo hanno cercato di innestare dinamiche di cambiamento della situazione di stallo economico e sociale delle regioni periferiche a nord e a sud dell\u2019area centrale del continente europeo. Il policentrismo allude alla possibilit\ue0 di generazione di nuove centralit\ue0 in aree deboli come contrasto al declino tendenziale e per rafforzare la coesione territoriale che si affianca alla coesione sociale ed economica nelle principali politiche della UE. Una prosecuzione di queste politiche avviate con l\u2019Esdp e sviluppate in termini di analisi con Espon, \ue8 data dai programmi comunitari sulle ICT che coinvolgono direttamente anche le imprese private specializzate del settore. Il tema quindi \ue8 la creazione di nuove centralit\ue0 in regioni dove i fenomeni urbani non riescono o non possono strutturalmente far parte dei sistemi metropolitani mondiali di accumulazione di capitali prevalentemente finanziari che, a loro volta, sono travolti da una crisi che sembra assumere i caratterini di un declino sistemico e strutturale. Le ICT costituiscono un ambito riflessivo e di elaborazione di politiche che possono cambiare le citt\ue0, non solo di quelle che fanno parte delle aree forti e centrali del continente europeo, ma anche nelle aree deboli dove il concetto di \u2018sviluppo\u2019 sembra essere superato in favore di volont\ue0 diverse e pi\uf9 centrate a fornire risposte autocentrate alla domanda sociale. E\u2019 su quest\u2019ultima che pu\uf2 attestarsi e concentrarsi l\u2019offerta di tecnologia ed \ue8 sulla innovazione sociale che l\u2019avanzamento tecnologico e la creazione di nuovi mercati potrebbero avere una spinta decisiva a livello locale e sovra locale. Il contributo presenta una sintesi dei risultati dell\u2019avvio del progetto Peripheria che riguarda il supporto ad alcune Smart City e Living Labs per sperimentare modi innovativi condivisi in reti di produzione territoriale