ESTIMATING CORE INFLATION IN NORWAY

Central banks are continually considering the problem of how to identify which price changes should be considered permanent and which entirely temporary. Indeed, due to the delayed effect that monetary policy uses to put its choices into action, a wrong valuation of the type of inflation can prove extremely costly for the economy and does not produce the desired results. Since price indexes (as CPI) deliver a distorted picture of underlying inflation, it is necessary to devise a more appropriate target for monetary policy. The need to find a good measure for the latter variable becomes more marked when the central bank adopts price stability as the overriding aim of monetary policy. In this paper we apply the Quah and Vahey (1995) methodology to Norway, oil producing OECD country, and derive measures of core inflation by imposing restrictions from economic theory within the context of a multivariate econometric analysis. To estimate long-term movements of inflation, we present two models that enable the distinction between core and non-core inflation and also between domestic and imported inflation. We conclude that in all the models presented core inflation is a �prime mover� of inflation.Core inflation, Monetary Policy, Norway

Macroeconomic Modelling and the Effects of Policy Reforms: an Assessment for Italy using ITEM and

In this paper we compare the dynamic properties of the Italian Treasury Econometric Model (ITEM) with those of QUEST III, the endogenous growth model of the European Commission (DG ECFIN) in the version calibrated for Italy. We consider an array of shocks often examined in policy simulations and investigate their implications on macro variables. In doing so, we analyse the main transmission channels in the two models and provide a comparative assessment of the magnitude and the persistence of the effects, trying to ascertain whether the responses to shocks are consistent with the predictions of economic theory. We show that, despite substantial differences between the two models, the responses of the key variables are qualitatively similar when we consider competition enhancing policies and labour productivity improvements. On the other hand, we observe quantitative disparities between the two models, mainly due to the forward-looking behaviour and the endogenous growth mechanism incorporated into the QUEST model but not in ITEM. The simulation results show that Quest III is a powerful tool to capture the effects of structural economic reforms, like competitionenhancing policies or innovation-promoting policies. On the other hand, owing to the breakdown of fiscal variables in a large number of components, ITEM is arguably more suitable for the quantitative evaluation of fiscal policy and the study of the impact of reforms on the public sector balance sheet.Economic Modelling, DSGE, Structural Reforms, Italy

Wind pattern analysis applied Tokyo 2020 Olympic Game

The following master thesis is the product of the work carried out during the Erasmus exchange of the year 2017-2018 that involved the author, exchange student from the University of Bologna, the Universitat Politècnica de Catalunya , TriM, an italian company with a strong knowledge of weather data and forecasting, and Meteocat, the public meteorological company of Catalonia in a collaboration aimed to find new methodologies for the processing of meteorological data. The reason that motivated this work is dictated by the increasing amount of weather data available today, that necessarily drives the weather forecasting in a more automated procedure that reduces the time needed to generate a forecast and the intervention of a human, in the figure of a meteorologist, in the analysis of the data. This allows to process more data and thus having predictions that take advantages of the usage of many information that could result in improved forecasting. The development in the field of machine learning allows today to treat a vast amount of information in an automatic way, leaving the analysis process to the machines, freeing the user of this time-consuming task. And unsupervised learning is the branch that can process data that are not labelled nor preprocessed, speeding up the data mining. The goal of this thesis is to apply unsupervised learning techniques to this scope, taking inspiration from the available literature that experimented in this field and combining different solutions into a new technique that aims to reduce the human decision in the process of the recognition of wind patterns and improve the automationof the whole process

A stochastic estimated version of the Italian dynamic General Equilibrium Model (IGEM)

We estimate with Bayesian techniques the Italian dynamic General Equilibrium Model (IGEM), which has been developed at the Italian Treasury Department, Ministry of Economy and Finance, to assess the effects of alter-native policy interventions. We analyze and discuss the estimated effects of various shocks on the Italian economy. Compared to the calibrated version used for policy analysis, we find a lower wage rigidity and higher adjustment costs. The degree of prices and wages indexation to past inflation is much smaller than the indexation level assumed in the calibrated model. No substantial difference is found in the estimated monetary parameters. Estimated fiscal multipliers are slightly smaller than those obtained from the calibrated version of the model

Brain imaging in Kufs disease type B. case reports

The clinical traits of Kufs disease (KD) type B (CLN13), an adult-onset neuronal ceroid lipofuscinosis (NCL), are well established according to the neurological features of the cases reported with mutations in CTSF. The neuroradiological characteristics of this uncommon disease have not yet been outlined

Business Model in Accounting: An Overview

Despite the interest in business model (BM), the academic debate in the accounting field seems still in the early stage. We investigate the use of BM in accounting through a literature review and discuss the findings considering management and banking research. Specific streams and areas of improvement are identified

Project selection in project portfolio management: an artificial neural network model based on critical success factors

While a growing body of literature focuses in detecting and analyzing the main reasons affecting project success, the use of these results in project portfolio management is still under investigation. Project critical success factors (CSFs) can serve as the fundamental criteria to prevent possible causes of failures with an effective project selection process, taking into account company strategic objectives, project manager’s experience and the competitive environment. This research proposes an innovative methodology to help managers in assessing projects during the selection phase. The paper describes the design, development and testing stages of a decision support system to predict project performances. An artificial neural network (ANN), scalable to any set of CSFs, classifies the level of project’s riskiness by extracting the experience of project managers from a set of past successful and unsuccessful projects

Introductory editorial: drug-eluting stents or drug-eluting grafts? Insights from proteomic analysis

No abstract available

Neophobia in food consumption: An empirical application of the FTNS scale in southern Italy

Through the Food Technology Neophobia Scale (FTNS) proposed by Cox and Evans (2008) this work investigates the role of consumer attitudes to food technology in determining the probability of purchasing innovative products by using a set of commonly purchased food. Six food categories with different processing levels were analyzed. Consumer choices were empirically modeled through a simultaneous system of three equations. The results confirm the strength of the FTNS scale, reflecting the dichotomy between neophobia and neophilia attitudes even in southern Italy, characterized by a very different socio-cultural context from that analyzed by Cox and Evans. The model highlights the role of both consumer attitudes to technology and socio-demographic characteristics in determining the probability of buying innovative products, providing some initial elements to define ideal customer profiles for the products considered