61 research outputs found

    Do Surveys Help in Macroeconomic Variables Disaggregation and Estimation?

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    This paper explores the potential of Business Survey data for the estimation and disaggregation of macroeconomic variables at higher frequency. We propose a multivariate approach which is an extension of the Stock and Watson (1991) dynamic factor model, considering more than one common factor and low-frequency cycles. The multivariate model is cast in State Space Form and the temporal aggregation constraint is converted into a problem of missing values. An application in real time for the value added of the Industry sector in the Euro area is presented.Temporal Disaggregation. Multivariate State Space Models. Dynamic factor

    FaMIDAS: A Mixed Frequency Factor Model with MIDAS structure

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    In this paper a dynamic factor model with mixed frequency is proposed (FaMIDAS), where the past observations of high frequency indicators are used following the MIDAS approach. This structure is able to represent with richer dynamics the information content of the economic indicators and produces smoothed factors and forecasts. In addition, the Kalman filter is applied, which is particularly suited for dealing with unbalanced data set and revisions in the preliminary data. In the empirical application for the Italian quarterly GDP the short-term forecasting performance is evaluated against other mixed frequency models in a pseudo-real time experiment, also allowing for pooled forecast from factor models.mixed frequency models, dynamic factor models, MIDAS,forecasting.

    FaMIDAS: A Mixed Frequency Factor Model with MIDAS structure

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    In this paper a dynamic factor model with mixed frequency is proposed (FaMIDAS), where the past observations of high frequency indicators are used following the MIDAS approach. This structure is able to represent with richer dynamics the information content of the economic indicators and produces smoothed factors and forecasts. In addition, it is particularly suited for real time forecast as it reduces the problem of the unbalanced data set and of the revisions in preliminary data. In the empirical application we specify and estimate a FaMIDAS to forecast Italian quarterly GDP. The short-term forecasting performance is evaluated against other mixed frequency models in a pseudo-real time experiment, also allowing for pooled forecast from factor models.Mixed frequency models, Dynamic factor Models, MIDAS, Forecasting

    La storia dei Templari e l'apporto delle nuove scoperte

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    Identifying Comedy: The Linguistic Properties of Humor

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    This dissertation is a method to label comedy with a linguistic model. Comedy is defined via an audience\u27s laughter. The first part presents anecdotal evidence and certain factors of comedy. Time and Cultural awareness play into the understanding of comedy. Time can situate the humor in a piece of writing. Cultural understanding can unlock the laughter in a joke. The second section breaks down comedy into a linguistic model. Expression, meaning, and context are the different parts of comedy. Each part has impact on humor. An audience understanding these three parts is critical to the concept of comedy equals a laughing audience

    Do Privatizations Boost Household Shareholding? Evidence from Italy

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    It is believed that privatizations substantially contributed to boost stock markets through the 1980s and 1990s. However, trough which channels did that materialize? We test whether privatizations –improving households’ acquaintance with the risk and return characteristics of stocks through the massive accompanying advertising campaigns– boosted demand for stocks by enlarging the set of households willing to invest in shares. We use a unique micro-data set collected for a large sample of Italian households on Public Offerings (PO) during 1995-99, the climax of privatizations in Italy. We show that advertising increased the notoriety of the incoming PO at households, and through this furthered households’ propensity to subscribe that PO. Furthermore, the propensity to subscribe the incoming PO also increased as households became better informed about past privatizations. Thus, privatizations expanded households’ share participation in Italy.Household portfolio choice, Information, Privatizations

    A Monthly Indicator of the Euro Area GDP

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    A continuous monitoring of the evolution of the economy is fundamental for the decisions of public and private decision makers. This paper proposes a new monthly indicator of the euro area real Gross Domestic Product (GDP), with several original features. First, it considers both the output side (six branches of the NACE classification) and the expenditure side (the main GDP components) and combines the two estimates with optimal weights reflecting their relative precision. Second, the indicator is based on information at both the monthly and quarterly level, modelled with a dynamic factor specification cast in state-space form. Third, since estimation of the multivariate dynamic factor model can be numerically complex, computational efficiency is achieved by implementing univariate filtering and smoothing procedures. Finally, special attention is paid to chain-linking and its implications, via a multistep procedure that exploits the additivity of the volume measures expressed at the prices of the previous year.Temporal Disaggregation, Multivariate State Space Models, Dynamic factor Models, Kalman filter and smoother, Chain-linking

    Survey Data as Coicident or Leading Indicators

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    In this paper we propose a monthly measure for the euro area Gross Domestic Product (GDP) based on a small scale factor model for mixed frequency data, featuring two factors: the first is driven by hard data, whereas the second captures the contribution of survey variables as coincident indicators. Within this framework we evaluate both the in-sample contribution of the second survey-based factor, and the short term forecasting performance of the model in a pseudo-real time experiment. We find that the survey-based factor plays a significant role for two components of GDP: Industrial Value Added and Exports. Moreover, the two factor model outperforms in terms of out of sample forecasting accuracy the traditional autoregressive distributed lags (ADL) specifications and the single factor model, with few exceptions for Exports and in growth rates.Survey data, Temporal Disaggregation. Multivariate State Space Models. Dynamic factor Models. Kalman filter and smoother. Chain-linking

    Engasjert og Myndiggjort — En kvalitativ undersøkelse av hvordan konsumentene opplever 360° nyheter

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    Master in digital communication and culture, 2017.English: News producers are looking to new media technologies like 360-degree video to capture the imagination of the consumers and re-engage them in news. The last two years have seen a growing number of media outlets use spherical (360-degree) video in their work. A leader in the field is the New York Times, which released its first 360 production, “The Displaced,” in November 2015. As with all 360 works, “The Displaced” can be viewed on a mobile – with or with a virtual reality headset. It also can be viewed on other mobile devices like a computer or an iPad. Spherical (360-degree) video often is described as the “gateway to virtual reality.” The technology allows viewers to navigate the scene by moving their mobile around or, if they are using a virtual reality headset, by swinging their head from side to side. Those viewing the work on a computer, however, must click and grab onto the screen to navigate. The advocates of 360 video point to the technology´s inherent ability to allow viewers to experience the news firsthand hand by placing them on site. But is this really the case and if so, is this reason enough to use 360 technology in news? The news producers think so but there is little research available that addresses the consumers´ thoughts on the matter. This master´s thesis is an attempt to redress the issue. The overall aim of this research is to present the consumers´ perspective of 360 news. A basic qualitative study, which is exploratory in nature, was conducted to obtain the information needed to understand and conceptualize the consumers´ experience and their thoughts about the media´s use of 360 technology. The study bases its empirical findings on in-depth interviews and the analysis of viewers´ comments posted on the Internet. Nine participants took part in this study. Each were asked to watch a 360 report and to discuss the experience. The results of the research indicate that watching the news in 360 engaged and empowered the viewer. The participants in this study indicated that they did not just observe the action. They took part in it. They felt as if they were there and that they had control over their viewing experience. Their ability to obtain the information firsthand, they say, gave them a deeper understanding of the issue – one that they would not have received from traditional media. The use of 360 technology also made the work more engaging and transparent.Norsk: Nyhetsprodusenter er hele tiden på leting etter ny teknologi for å fange publikums interesse og fantasi. Flere mediebedrifter har funnet at 360-grader (sfærisk) video engasjerer publikum og representerer noe helt nytt innen mediadistribusjon. De siste to årene har blitt sett et økende antall 360-grader videoer distribuert via mobiltelefonteknologi. New York Times var blant de første som tok i bruk 360-video i reportasjene sine. De produserte “The Displaced” i november 2015. Som alle 360-grader produksjoner, kan “The Displaced” vises på mobil – med eller uten brukt av VR-briller. Den også kan bli sett på ved bruk av datamaskin. Sfærisk (360-grader) video beskrives ofte som “inngangsporten til virtuell virkelighet.” Teknologien gjør det mulig for publikum å navigere på “innsiden” av reportasjene ved å bevege mobilen opp og ned eller til siden. De som bruker VR-briller navigerer ved å bevege hodet. De som ser på reportasjen på en datamaskin må imidlertid bruke PC mus eller tastatur til å navigere på innsiden av reportasjen. Tilhengere av 360-video peker på teknologiens iboende evne til å la publikum oppleve førstehåndsnyheter og reportasjer ved å plassere dem på innsiden av reportasjen. Men er dette virkelig tilfelle, og er det i så fall grunn nok til å bruke 360-teknologi i nyheter? Nyhetsprodusenter er sikre, men det er gjort lite forskning på området og lite har blitt gjort med tanke på hvordan publikum opplever bruken av 360-video. Denne masteroppgaven er et forsøk på å belyse dette. Mitt overordnede mål med denne oppgaven er å presentere publikumsperspektiv på 360-video. Jeg tok i bruk kvalitativ metode gjennom utforskende, individuelle dybdeintervjuer. Jeg har også analysert kommentarer om 360-video som har blitt lagt ut på kommentarfeltet på Internett. Ni informanter er med i denne studien. De ble bedt om å se på en 4-11 minutters 360-videoreportasje og deretter forklare hva de opplevde. Mitt hovedmål er å forstå og konseptualisere publikums opplevelse av 360-video. Resultatene av forskningen min viser at informantene blir engasjert og myndiggjort ved å se nyheter i 360 grader. De ni informantene indikerte at de ikke bare observerte reportasjene, men de deltok i dem. De ble en del av handlingen, samtidig som de kunne kontrollere opplevelsen sin. Informantene får førstehåndsinformasjon som gir dem en dypere forståelse av problemet – noe som de ikke ville ha fått gjennom tradisjonelle medier som TV og avis. Bruken av 360-teknologi gjorde også reportasjen mer engasjerende og gjennomsiktig, ifølge informantene

    EuroMInd-C: a Disaggregate Monthly Indicator of Economic Activity for the Euro Area and member countries

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    The paper deals with the estimation of monthly indicators of economic activity for the Euro area and its largest member countries that possess the following attributes: relevance, representativeness and timeliness. Relevance is determined by comparing our monthly indicators to the gross domestic product at chained volumes, as the most important measure of the level of economic activity. Representativeness is achieved by considering a very large number of (timely) time series of monthly indicators relating to the level of economic activity, providing a more or less complete coverage. The indicators are modelled using a large-scale parametric factor model. We discuss its specification and provide details of the statistical treatment. Computational efficiency is crucial for the estimation of large-scale parametric factor models of the dimension used in our application (considering about 170 series). To achieve it, we apply state-of-the-art state space methods that can handle temporal aggregation, and any pattern of missing values
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