Regime switches, Agents’ Beliefs, and Post-World War II U.S. Macroeconomic Dynamics

The evolution of inflation and output over the last 50 years is examined through the lens of a micro-founded model that allows for changes in the behavior of the Federal Reserve and in the volatility of structural shocks. Agents are aware of the possibility of regime changes and their beliefs have an impact on the law of motion underlying the macroeconomy. The results support the view that there were regime switches in the conduct of monetary policy. However, the behavior of the Federal Reserve is identified by repeated fluctuations between a Hawk- and a Dove- regime, instead of by the traditional pre- and post- Volcker structure. Counterfactual simulations show that if agents had anticipated the appointment of an extremely conservative Chairman, inflation would not have reached the peaks of the late `70s and the inflation-output trade-off would have been less severe. These "beliefs counterfactuals" are new in the literature. Finally, the paper provides a Bayesian algorithm to handle the technical difficulties that arise in a rational expectations model with Markov-switching regimes.Beliefs, Markov-switching, DSGE, Monetary Policy, Bayesian

Identifying e-Commerce in Enterprises by means of Text Mining and Classification Algorithms

Monitoring specific features of the enterprises, for example, the adoption of e-commerce, is an important and basic task for several economic activities. This type of information is usually obtained by means of surveys, which are costly due to the amount of personnel involved in the task. An automatic detection of this information would allow consistent savings. This can actually be performed by relying on computer engineering, since in general this information is publicly available on-line through the corporate websites. This work describes how to convert the detection of e-commerce into a supervised classification problem, where each record is obtained from the automatic analysis of one corporate website, and the class is the presence or the absence of e-commerce facilities. The automatic generation of similar data records requires the use of several Text Mining phases; in particular we compare six strategies based on the selection of best words and best n-grams. After this, we classify the obtained dataset by means of four classification algorithms: Support Vector Machines; Random Forest; Statistical and Logical Analysis of Data; Logistic Classifier. This turns out to be a difficult case of classification problem. However, after a careful design and set-up of the whole procedure, the results on a practical case of Italian enterprises are encouraging

Analisi e ottimizzazione di un sistema produttivo mediante tecniche euristiche e strumenti di simulazione

Il presente lavoro di tesi, svolto presso l'azienda Mikron SA,è incentrato sulla analisi di un sistema produttivo organizzato per celle, per il quale è stato necessario valutare una serie di soluzioni alternative per la gestione della produzione. In particolare, mediante tecniche euristiche (algoritmi genetici) e strumenti di simulazione, si è confrontato la situazione iniziale con due metodologie ritenute più idonee per il tipo di produzione in questione: l'm-Conwip e il Polca. A questa fase è stata affiancata una parte più pratica volta a ottimizzare e standardizzare le procedure dell'azienda nell'ambito della logistica interna. Infine, dati i riscontri positivi dell'analisi fatta, è presentato anche una studio preliminare sulla applicabilità delle tecniche sopracitate alle fase di assemblaggio di uno dei prodotti dell'azienda

MoCA: A Monte Carlo code for Comptonisation in Astrophysics. I. Description of the code and first results

We present a new Monte Carlo code for Comptonisation in Astrophysics (MoCA). To our knowledge MoCA is the first code that uses a single photon approach in a full special relativity scenario, and including also Klein-Nishina effects as well as polarisation. In this paper we describe in detail how the code works, and show first results from the case of extended coronae in accreting sources Comptonising the accretion disc thermal emission. We explored both a slab and a spherical geometry, to make comparison with public analytical codes more easy. Our spectra are in good agreement with those from analytical codes for low/moderate optical depths, but differ significantly, as expected, for optical depths larger than a few. Klein-Nishina effects become relevant above 100 keV depending on the optical thickness and thermal energy of the corona. We also calculated the polarisation properties for the two geometries, which show that X-ray polarimetry is a very useful tool to discriminate between them.Comment: 16 pages, 20 figure

The ABACOC Algorithm: a Novel Approach for Nonparametric Classification of Data Streams

Stream mining poses unique challenges to machine learning: predictive models are required to be scalable, incrementally trainable, must remain bounded in size (even when the data stream is arbitrarily long), and be nonparametric in order to achieve high accuracy even in complex and dynamic environments. Moreover, the learning system must be parameterless ---traditional tuning methods are problematic in streaming settings--- and avoid requiring prior knowledge of the number of distinct class labels occurring in the stream. In this paper, we introduce a new algorithmic approach for nonparametric learning in data streams. Our approach addresses all above mentioned challenges by learning a model that covers the input space using simple local classifiers. The distribution of these classifiers dynamically adapts to the local (unknown) complexity of the classification problem, thus achieving a good balance between model complexity and predictive accuracy. We design four variants of our approach of increasing adaptivity. By means of an extensive empirical evaluation against standard nonparametric baselines, we show state-of-the-art results in terms of accuracy versus model size. For the variant that imposes a strict bound on the model size, we show better performance against all other methods measured at the same model size value. Our empirical analysis is complemented by a theoretical performance guarantee which does not rely on any stochastic assumption on the source generating the stream

A dyadic model on a tree

We study an infinite system of non-linear differential equations coupled in a tree-like structure. This system was previously introduced in the literature and it is the model from which the dyadic shell model of turbulence was derived. It mimics 3d Euler and Navier-Stokes equations in a rough approximation of a wavelet decomposition. We prove existence of finite energy solutions, anomalous dissipation in the inviscid unforced case, existence and uniqueness of stationary solutions (either conservative or not) in the forced case

The NuSTAR view of the Seyfert Galaxy HE 0436-4717

We present the multi epoch spectral analysis of HE 0436-4717, a bright Seyfert 1 galaxy serendipitously observed by the high energy satellite NuSTAR four times between December 2014 and December 2015. The source flux shows modest variability within each pointing and among the four observations. Spectra are well modelled in terms of a weakly variable primary power law with constant photon index ($\Gamma$=2.01$\pm$0.08). A constant narrow \ion{Fe} K$\alpha$ emission line suggests that this feature has an origin far from the central black hole, while a broad relativistic component is not required by the data. The Compton reflection component is also constant in flux with a corresponding reflection fraction R=0.7$^{+0.2}_{-0.3}$. The iron abundance is compatible with being Solar (A$_{Fe}$=1.2$^{+1.4}_{-0.4}$), and a lower limit for the high energy cut-off E$_c$>280 keV is obtained. Adopting a self-consistent model accounting for a primary Comptonized continuum, we obtain a lower limit for the hot corona electron temperature kT$_e$>65 keV and a corresponding upper limit for the coronal optical depth of $\tau_e$<1.3. The results of the present analysis are consistent with the locus of local Seyfert galaxies in the kT$_e$-$\tau_e$ and temperature-compactness diagrams.Comment: accepted for publication in A&