Orientador: João Francisco Escobedo / Banca: Roberto Vicente Calheiros / Banca: Jonas Teixeira Nery / Banca: Luci Hidalgo Nunes / Banca: Oswaldo Massambani / Resumo: Foi realizada uma análise para se obter a caracterização das tempestades sob o aspecto climatológico para a área central do Estado de São Paulo cujos parâmetros foram obtidos com o software TITAN, desenvolvido no NCAR e implementado nos computadores do IPMet. Os parâmetros que caracterizam as propriedades das tempestades tais como volume médio, área média, altura dos topos dos ecos, refletividade máxima e média bem como velocidade e deslocamento dos sistemas precipitantes foram determinados considerando o limiar de refletividade>30 dBZ, e volume>30 km3. A distribuição espacial de parâmetros tais como volume médio, área média, refletividade média e máxima mostrou, pela primeira vez para a área central do Estado de São Paulo, como os mesmos se distribuíram pela área monitorada pelo radar de Bauru e também a existência de regiões preferenciais onde se concentra a maior atividade convectiva, durante os verões analisados. Todas as varreduras observadas pelo radar de Bauru foram também processadas para se determinar as áreas de tempestades definidas pelo limiar de refletividade maior que 25 dBZ, para a partir daí obter a integração dessas áreas para o tempo de duração de cada tempestade e calcular a IAT, que é a integral área-tempo. O método da Integral-Área-Tempo (IAT), para se medir precipitação volumétrica baseada na informação de cobertura da precipitação em área foi aplicado aos dados de radar meteorológico de Bauru, para dois períodos de verão, o de 1998-1999 e 1999-2000. A premissa de que a porção crescente do conglomerado convectivo seria suficiente para calcular uma IAT que ainda seria altamente correlacionada com o volume total de chuva resultando, portanto numa técnica para o nowcasting é testada e verificada para os dois períodos analisados. Os resultados das análises mostraram que as células de tempestade...(Resumo completo, clicar acesso eletrônico abaixo) / Abstract: A climatological characterization of storm properties during two summer seasons, viz. 1998-1999 and 1999-2000, based on observations from the Bauru S-band Doppler radar, was obtained with the TITAN Software of NCAR, implemented at IPMet. Parameters, such as mean volume, mean area, mean and maximum echo tops, mean and maximum reflectivity, as well as speed and direction of precipitating systems were determined using the reflectivity> 30 dBZ and a volume> 30 km3 as a threshold for storm identification. The spatial distribution for parameters such as mean volume, mean area, mean and maximum reflectivity, mean and maximum echo top, etc, were determined for the first time in the central State of São Paulo, based on radar data information. It has shown some preferential areas where most of the convective activity was concentrated during the study period. The Area Time-Integration (ATI) method was then applied to these observations using the 25 dBZ thresholds, to determine the rainfall volume in the central area of the State of São Paulo, taking into account the entire lifetime of all observed storms that exceeded the threshold considered. Furthermore, it was also investigated, if it would be possible to estimate the ATIs only for the growth period of a convective storm and still obtain a good correlation. This method could then be applied to obtain the total rain volume of a convective system at the stage of its maximum development, which could be considered as a nowcasting tool to be explored in subsequent studies. The time span for the storms reaching their maximum area was found to be about 2 hours on average and this was reached within...(Complete abstract, click electronic access below) / Doutor

The explosion of information and user generated content made publicly available through the internet has made it possible to develop new ways of inferring interesting phenomena automatically. Some interesting examples are the spread of a contagious disease, earth quake occurrences, rainfall rates, box office results, stock market fluctuations and many many more. To this end a mathematical framework, based on theory from machine learning, has been employed to show how frequencies of relevant keywords in user generated content can estimate daily rainfall rates of different regions in Sweden using microblog data. Microblog data are collected using a microblog crawler. Properties of the data and data collection methods are both discussed extensively. In this thesis three different model types are studied for regression, linear and nonlinear parametric models as well as a nonparametric Gaussian process model. Using cross-validation and optimization the relevant parameters of each model are estimated and the model is evaluated on independent test data. All three models show promising results for nowcasting rainfall rates.

[ES] En la Era Digital, el creciente uso de Internet y de dispositivos digitales está transformando completamente la forma de interactuar en el contexto económico y social. Miles de personas, empresas y organismos públicos utilizan Internet en sus actividades diarias, generando de este modo una enorme cantidad de datos actualizados ("Big Data") accesibles principalmente a través de la World Wide Web (WWW), que se ha convertido en el mayor repositorio de información del mundo. Estas huellas digitales se pueden rastrear y, si se procesan y analizan de manera apropiada, podrían ayudar a monitorizar en tiempo real una infinidad de variables económicas. En este contexto, el objetivo principal de esta tesis doctoral es generar indicadores económicos, basados en datos web, que sean capaces de proveer regularmente de predicciones a corto plazo ("nowcasting") sobre varias actividades empresariales que son fundamentales para el crecimiento y desarrollo de las economías. Concretamente, tres indicadores económicos basados en la web han sido diseñados y evaluados: en primer lugar, un indicador de orientación exportadora, basado en un modelo que predice si una empresa es exportadora; en segundo lugar, un indicador de adopción de comercio electrónico, basado en un modelo que predice si una empresa ofrece la posibilidad de venta online; y en tercer lugar, un indicador de supervivencia empresarial, basado en dos modelos que indican la probabilidad de supervivencia de una empresa y su tasa de riesgo. Para crear estos indicadores, se han descargado una diversidad de datos de sitios web corporativos de forma manual y automática, que posteriormente se han procesado y analizado con técnicas de análisis Big Data. Los resultados muestran que los datos web seleccionados están altamente relacionados con las variables económicas objeto de estudio, y que los indicadores basados en la web que se han diseñado en esta tesis capturan en un alto grado los valores reales de dichas variables económicas, siendo por tanto válidos para su uso por parte del mundo académico, de las empresas y de los decisores políticos. Además, la naturaleza online y digital de los indicadores basados en la web hace posible proveer regularmente y de forma barata de predicciones a corto plazo. Así, estos indicadores son ventajosos con respecto a los indicadores tradicionales. Esta tesis doctoral ha contribuido a generar conocimiento sobre la viabilidad de producir indicadores económicos con datos online procedentes de sitios web corporativos. Los indicadores que se han diseñado pretenden contribuir a la modernización en la producción de estadísticas oficiales, así como ayudar a los decisores políticos y los gerentes de empresas a tomar decisiones informadas más rápidamente. / [CAT] A l'Era Digital, el creixent ús d'Internet i dels dispositius digitals està transformant completament la forma d'interactuar al context econòmic i social. Milers de persones, empreses i organismes públics utilitzen Internet a les seues activitats diàries, generant d'aquesta forma una enorme quantitat de dades actualitzades ("Big Data") accessibles principalment mitjançant la World Wide Web (WWW), que s'ha convertit en el major repositori d'informació del món. Aquestes empremtes digitals poden rastrejar-se i, si se processen i analitzen de forma apropiada, podrien ajudar a monitoritzar en temps real una infinitat de variables econòmiques. En aquest context, l'objectiu principal d'aquesta tesi doctoral és generar indicadors econòmics, basats en dades web, que siguen capaços de proveïr regularment de prediccions a curt termini ("nowcasting") sobre diverses activitats empresarials que són fonamentals per al creixement i desenvolupament de les economies. Concretament, tres indicadors econòmics basats en la web han sigut dissenyats i avaluats: en primer lloc, un indicador d'orientació exportadora, basat en un model que prediu si una empresa és exportadora; en segon lloc, un indicador d'adopció de comerç electrònic, basat en un model que prediu si una empresa ofereix la possibilitat de venda online; i en tercer lloc, un indicador de supervivència empresarial, basat en dos models que indiquen la probabilitat de supervivència d'una empresa i la seua tasa de risc. Per a crear aquestos indicadors, s'han descarregat una diversitat de dades de llocs web corporatius de forma manual i automàtica, que posteriorment s'han analitzat i processat amb tècniques d'anàlisi Big Data. Els resultats mostren que les dades web seleccionades estan altament relacionades amb les variables econòmiques objecte d'estudi, i que els indicadors basats en la web que s'han dissenyat en aquesta tesi capturen en un alt grau els valors reals d'aquestes variables econòmiques, sent per tant vàlids per al seu ús per part del món acadèmic, de les empreses i dels decisors polítics. A més, la naturalesa online i digital dels indicadors basats en la web fa possible proveïr regularment i de forma barata de prediccions a curt termini. D'aquesta forma, són avantatjosos en comparació als indicadors tradicionals. Aquesta tesi doctoral ha contribuït a generar coneixement sobre la viabilitat de produïr indicadors econòmics amb dades online procedents de llocs web corporatius. Els indicadors que s'han dissenyat pretenen contribuïr a la modernització en la producció d'estadístiques oficials, així com ajudar als decisors polítics i als gerents d'empreses a prendre decisions informades més ràpidament. / [EN] In the Digital Era, the increasing use of the Internet and digital devices is completely transforming the way of interacting in the economic and social framework. Myriad individuals, companies and public organizations use the Internet for their daily activities, generating a stream of fresh data ("Big Data") principally accessible through the World Wide Web (WWW), which has become the largest repository of information in the world. These digital footprints can be tracked and, if properly processed and analyzed, could help to monitor in real time a wide range of economic variables. In this context, the main goal of this PhD thesis is to generate economic indicators, based on web data, which are able to provide regular, short-term predictions ("nowcasting") about some business activities that are basic for the growth and development of an economy. Concretely, three web-based economic indicators have been designed and evaluated: first, an indicator of firms' export orientation, which is based on a model that predicts if a firm is an exporter; second, an indicator of firms' engagement in e-commerce, which is based on a model that predicts if a firm offers e-commerce facilities in its website; and third, an indicator of firms' survival, which is based on two models that indicate the probability of survival of a firm and its hazard rate. To build these indicators, a variety of data from corporate websites have been retrieved manually and automatically, and subsequently have been processed and analyzed with Big Data analysis techniques. Results show that the selected web data are highly related to the economic variables under study, and the web-based indicators designed in this thesis are capturing to a great extent their real values, thus being valid for their use by the academia, firms and policy-makers. Additionally, the digital and online nature of web-based indicators makes it possible to provide timely, inexpensive predictions about the economy. This way, they are advantageous with respect to traditional indicators. This PhD thesis has contributed to generating knowledge about the viability of producing economic indicators with data coming from corporate websites. The indicators that have been designed are expected to contribute to the modernization of official statistics and to help in making earlier, more informed decisions to policy-makers and business managers. / Blázquez Soriano, MD. (2019). Design and Evaluation of Web-Based Economic Indicators: A Big Data Analysis Approach [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/116836 / TESIS

Deep neural networks (DNNs) based on satellite and radar data have shown promising results for precipitation nowcasting, beating physical models and optical flow for time horizons up to 8 hours. “MetNet”, developed by Google AI, is a 225 million parameter DNN combining three different types of architectures that was trained on satellite and radar data over the United States. They claim to be the first machine learning model to outperform physical models at such a scale. In this work, we implemented a similar but simplified model trained on radar-only Swedish data, with the aim to perform precipitation nowcasting for up to 2 hours into the future. Furthermore, we compare the model to another, simpler model that omits the spatial aggregator of the DNN architecture which is a state-of-the-art vision transformer. Our results show that, although the adopted training dataset was too small to prevent overfitting, the model is still able to outperform the persistence benchmark for lead times longer than 30 minutes with a threshold of 0.2mm/h precipitation. Our simplified model, perhaps unsurprisingly, is outperformed by MetNet because of having too few training data samples or variances in the models’ implementation. We show, nonetheless, that the adopted spatial aggregator fulfills a vital role as expected, aggregating global information into spatial and temporal contexts.  Due to the limitations imposed by the reduced size of the model, we cannot, unfortunately, draw definitive conclusions on whether a radar-only model could yield similar forecast skills as MetNet. To improve on these results, more training data is certainly needed. This would require that more robust computation resources are available, but pre-training the model on a larger dataset — or even implementing a model that takes in different geographical locations for training — can naturally lead to significant improvements in the predictions. / Djupa neurala nätverk (DNN) baserade på satellit och radar data har gett bra resultat för korta nederbördsprognoser och kan slå fysikaliska modeller och optical flow f ̈or prognoser upp till 8 timmar i framtiden. “MetNet” ̈ar ett 225 million DNN publicerat av Google som kombinerar tre olika typer av djupa arkitekturer, det är tränat på satellit och radar data över USA och är enligt dom den första maskininlärningsmodellen som presterar bättre än fysikaliska modeller. I denna uppsats har vi konstruerat en modell som liknar deras på ett nedskalat problem. Vi har färre parametrar, lägre upplöst data, endast 2 timmar prognostisering och använder bara radar data över Sverige för att träna modellen. Vi använder F1-score för att evaluera modellens prestanda och jämför prognosen mot persistens som referens. Vidare undersöker vi en mindre komplicerad modell där den tredje arkitekturen inte används för att se vilken roll vision transformern har. Våra resultat visar att datasetet vi tränat på är för litet och modellen överanpassas men modellen lyckas ändå slå persistens referensen för prognoser 30–120 minuter när en 0.2mm/h regntröskel tillämpas. Resultaten är sämre än MetNet av Google och vi kan inte dra några slutsatser huruvida en modell med endast radar-data skulle kunna ge liknande resultat eller inte, eftersom modellen inte tränats till dess fulla potential. Vi visar att den tredje arkitekturen, vision transformern, är en viktig del av nätverket och aggregerar global information till lokala kontexter över tid och rum. För att förbättra våra resultat skulle vi pröva att låta modellen träna på det amerikanska datasetet använt av Google och implementera en modell vars input varierar geografisk position.

Weather radar imagery is important for several remote sensing applications including tracking of storm fronts and radar echo classification. In particular, tracking of precipitation events is useful for both forecasting and classification of rain/non-rain events since non-rain events usually appear to be static compared to rain events. Recent weather radar imaging-based forecasting approaches [3] consider that precipitation events can be modeled as a combination of localized functions using Radial Basis Function Neural Networks (RBFNNs). Tracking of rain events can be performed by tracking the parameters of these localized functions. The RBFNN-based techniques used in forecasting are not only computationally expensive, but also moderately effective in modeling small size precipitation events. In this thesis, an existing RBFNN technique [3] was implemented to verify its computational efficiency and forecasting effectiveness. The feasibility of modeling precipitation events using RBFNN effectively was evaluated, and several modifications to the existing technique have been proposed.

Considerando a importância de uma medida de alta frequência para o PIB do Rio Grande do Sul, o principal indicador de atividade econômica do estado, este trabalho foi dividido em três objetivos. O primeiro foi a estimação de uma série com frequência mensal para o PIB real do Rio Grande do Sul entre janeiro de 2002 e março de 2017, dado que o mesmo só é contabilizado em frequência trimestral. Para tanto, foi utilizado um modelo em espaço de estados que permite a estimação e nowcast do PIB mensal, utilizando séries coincidentes como fonte de informação para a interpolação dos dados trimestrais do PIB, em linha com Bernanke, Gertler e Watson (1997), Mönch e Uhlig (2005) e Issler e Notini (2016). O segundo objetivo foi comparar a série estimada com um indicador de atividade calculado pelo Banco Central do Brasil para o estado, o Índice de Atividade Econômica Regional (IBCR-RS), tanto em termos metodológicos como na capacidade em antecipar as variações do PIB trimestral antes de sua divulgação (nowcasting). O terceiro objetivo foi estabelecer a cronologia dos ciclos de expansão e recessão da economia gaúcha com o uso do algoritmo de Bry e Boschan (1971). Após a etapa de seleção das séries coincidentes e da estimação de diversos modelos de interpolação, foi escolhido para gerar a série mensal do PIB o modelo que utiliza somente a produção industrial como variável auxiliar, tendo este apresentado o melhor ajuste. A comparação do PIB mensal interpolado com o IBCR-RS mostrou que, além da vantagem computacional a favor do método proposto neste trabalho, a imposição da disciplina de que as variações do PIB mensal estimado devem ser exatamente iguais às do PIB trimestral faz com que a dinâmica de curto e longo prazo das variáveis sejam idênticas, o que não ocorre com o IBCR-RS. A cronologia dos pontos de inflexão da atividade econômica apontou três períodos recessivos na economia gaúcha desde janeiro de 2002: jun/2003 a abr/2005 (23 meses e queda acumulada de 8,79%); abr/2011 a abr/2012 (13 meses e queda acumulada de 9,47%); e jun/2013 a nov/2016 (42 meses e queda acumulada de 10,41%), sendo o encerramento deste último apontado somente com a inclusão dos resultados estimados pelo modelo para o segundo trimestre de 2017. Finalmente, os resultados do exercício de nowcasting do PIB mostraram desempenho superior do método proposto frente ao IBCR-RS em termos de antecipação do resultado do PIB de um trimestre a frente, tomando como base as medidas de MAE (erro absoluto médio, em inglês) e MSE (erro quadrático médio, em inglês), comumente usadas nesse intuito. / Giving the importance of a high frequency measure for Rio Grande do Sul’s GDP, the main indicator of economic activity of the state, this work was divided into three objectives. The first one was the estimation of monthly frequency series for Rio Grande do Sul’s real GDP between January/2002 and March/2017, since it is only accounted in quarterly basis. Therefore, we used a State-Space model that enables to estimate and nowcast the monthly GDP, using coincident series as a source of information for the interpolation of quarterly GDP data, in line with Bernanke, Gertler e Watson (1997), Mönch e Uhlig (2005) and Issler e Notini (2016). The second objective was to compare the estimated series with an activity indicator calculated by the Central Bank of Brazil for the state, the Regional Economic Activity Index (IBCR-RS), both in methodological terms and in the capability to anticipate the quarterly GDP release (nowcasting). The third objective was to establish the chronology of the cycles of expansion and recession of the economy of Rio Grande do Sul using the algorithm of Bry e Boschan (1971). After the selection of the coincident series and the estimation of several interpolation models, the chosen model to generate the monthly GDP series uses only the industrial production as an auxiliary variable, and this one presented the best fit. The comparison of the monthly GDP interpolated with the IBCR-RS showed that, in addition to the computational advantage in favor of the method proposed in this work, the imposition of the discipline that the estimated monthly GDP changes must be exactly the same as the quarterly GDP makes the short-term and long-term dynamics of the variables are identical, which is not the case with IBCR-RS. The chronology of the turning points of the economic activity pointed to three recessive periods in the economy of Rio Grande do Sul since January 2002: June/2003 to April/2005 (23 months and accumulated drop of 8.79%); April/2011 to April/2012 (13 months and accumulated fall of 9.47%); and June/2013 to November/2016 (42 months and 10.41% accumulated decrease), with the latter one closing only with the inclusion of the results estimated by the model for the second quarter of 2017. Finally, results for GDP’s nowcasting showed superior performance of the proposed method compared to the IBCR-RS in terms of anticipating quarter-to-quarter GDP results, based on the measures of MAE (absolute mean error) and MSE (mean square error), commonly used for this purpose.

L'objectif de cette thèse était d'apporter une approche géophysique non linéaire à l'hydrologie urbaine. Elle a visé l'étude de la mise à l'échelle et de l'intermittence de la non-linéarité des précipitations, la réalisation d'une méthode de prévision stochastique à très court terme ("nowcast"), ainsi que son application aux processus hydrologiques dans les environnements (semi-) urbains. La partie modélisation hydrologique globale concerne la vallée de la Bièvre, zone semi-urbanisée de 110 km2 dans le sud-ouest de la région parisienne. Par conséquent, trois études différentes ont été réalisées dans cette zone à l'aide de deux modèles hydrologiques : le modèle conceptuel semi-distribué InfoWorks CS appliqué sur tout le bassin versant de Bièvre ; et le modèle physique complètement distribué Multi-Hydro, développé à l'École des Ponts ParisTech, appliqué sur deux sous-bassins versants de la Bièvre. Les principaux objectifs étaient de mieux comprendre les impacts de la variabilité spatio-temporelle des données pluviométriques en utilisant deux produits (les données radar bande-C de Météo-France avec une résolution de 1 km x 1 km x 5 min, et les données radar DPSRI band-X de l'ENPC à une résolution de 250 m x 250 m x 3.41 min) comme entrées pour les modèles, et d'identifier les capacités de chaque modèle pour traiter des données à une meilleur résolution, telles que la bande-X. Ensuite, les résultats obtenus démontrent que la fiabilité des simulations hydrologiques dépend intrinsèquement des caractéristiques des données pluviométriques. De plus, les données du radar bande-X pourraient mesurer des pics de précipitations plus élevés et le modèle complètement distribué était plus sensible à une meilleure résolution des données pluviométriques. Par la suite, des données de pluie provenant des radars météorologiques situés à des endroits complètement différents (Brésil, France, Japon) ont été analysées et comparées statistiquement afin d'améliorer la compréhension générale du comportement scalant des précipitations. De plus, le théorème d'intersection a été appliqué pour mettre en évidence les impacts de la variabilité spatiale d'un réseau virtuel de pluviomètres, qui a été généré en considérant l'emplacement des centres de masse de chaque sous-bassin versant de la vallée de la Bièvre. Ainsi, il a été possible d'identifier que la fractalité du réseau virtuel a conduit à une perte d'information importante des champs de pluie, biaisant leurs statistiques. Cela indique que le processus commun (largement retrouvé dans la littérature) de calibration des données radar à l'aide de pluviomètres devrait correctement prendre en compte cette fractalité. Enfin, une nouvelle approche de prévision stochastique immédiate a été proposée, à l'aide du modèle des multifractals universels (UM) en cascades continues. Cette méthode a été appliquée aux données des radars pluviométriques de la région amazonienne brésilienne et de Paris. Bien qu'il soit encore en développement et nécessite quelques améliorations, les premiers résultats obtenus avec ce modèle de prévision présenté ici sont vraiment encourageants et corroborent une fois de plus le besoin de données à haute résolution spatio-temporelle pour faire face aux crues soudaines / The focus of this thesis was to bring a nonlinear geophysical approach to urban hydrology. It aimed the study of rainfall non-linearity scaling and intermittency, achieving a stochastic very short-range forecast (nowcast) method, as well as its application to hydrological processes in (semi-) urban environments. The overall hydrological modelling part concerned the Bièvre Valley, which is a 110 km2 semi-urbanized area in the southwest of Paris region. Therefore, three different studies were performed within this area using two hydrological models: the conceptually-based semi-distributed model InfoWorks CS over the total Bièvre catchment, and the physically-based fully-distributed model developed at École des Ponts ParisTech called Multi-Hydro over two sub-catchments. The main goals were to better understand the impacts of spatio-temporal variability of rainfall data by using two products (the Météo-France C-band radar data with a resolution of 1 km x 1 km x 5 min; and the ENPC DPSRI X-band radar data at a 250 m x 250 m x 3.41 min resolution) as input to the models, and to identify the capacities of each model to deal with better resolution data, such as the X-band one. Then, the obtained results demonstrate that the reliability of the hydrological simulations are intrinsically dependent on rainfall data features. Moreover, the X-band radar data could measure higher peaks of rainfall rates and the fully-distributed model was more sensitive to better resolution rainfall data. Afterwards, different weather rainfall radar data from completely different sites (Brazil, France, Japan) were statistically analysed and compared in order to improve the general comprehension of rainfall scaling behaviour. In addition, the Intersection Theorem was applied to highlight the impacts of spatial variability of a virtual rain gauge network. The latter was generated by considering the location of each Bièvre Valley sub-catchment mass centre. Thus, it was possible to identify that the fractality of the virtual network led to an important information loss of the rainfall fields, biasing their statistics. This indicates that the common process (largely found in literature) of radar data calibration using rain gauges should be properly take into account this fractality. Finally, a new stochastic nowcast approach was proposed, using the continuous in scale cascade Universal Multifractals (UM) model. This method was applied to weather rainfall radar data from the Brazilian Amazon region and Paris. Although it is still under development and needs some improvements, the first results obtained with this forecast model presented here in this thesis are really encouraging and once more corroborate to the need of high spatio-temporal resolution data to cope flash floods

Submitted by Fernando Ferreira da Luz Barbosa (fernando.luz@outlook.com) on 2015-07-20T19:07:10Z No. of bitstreams: 1 Fernando Ferreira da Luz Barbosa.pdf: 927554 bytes, checksum: e29a7f5ad6e3cdd15bb6adafc98a4cb6 (MD5) / Approved for entry into archive by BRUNA BARROS (bruna.barros@fgv.br) on 2015-07-21T12:46:06Z (GMT) No. of bitstreams: 1 Fernando Ferreira da Luz Barbosa.pdf: 927554 bytes, checksum: e29a7f5ad6e3cdd15bb6adafc98a4cb6 (MD5) / Approved for entry into archive by Maria Almeida (maria.socorro@fgv.br) on 2015-07-30T19:08:34Z (GMT) No. of bitstreams: 1 Fernando Ferreira da Luz Barbosa.pdf: 927554 bytes, checksum: e29a7f5ad6e3cdd15bb6adafc98a4cb6 (MD5) / Made available in DSpace on 2015-07-30T19:08:57Z (GMT). No. of bitstreams: 1 Fernando Ferreira da Luz Barbosa.pdf: 927554 bytes, checksum: e29a7f5ad6e3cdd15bb6adafc98a4cb6 (MD5) Previous issue date: 2015-04-27 / Disagreement between economists is a well know fact. However, it took a long time for this concept to be incorporated in economic models. In this survey, we review the consequences and insights provided by recent models. Since disagreement between market agents can be generated through different hypotheses, the main differences between them are highlighted. Finally, this work concludes with a short review of nowcasting using google trends, emphasizing advances connecting both literatures.

Submitted by Douglas Minoru Kagohara (douglasminoru@yahoo.com.br) on 2015-09-08T23:43:17Z No. of bitstreams: 1 Douglas_Kagohara.pdf: 418440 bytes, checksum: d272546247d30d373e0cdd3e2fbc6e4b (MD5) / Rejected by Renata de Souza Nascimento (renata.souza@fgv.br), reason: Anderson, Coloque a numeração das páginas no canto direito, não interfere se for acima e abaixo. Mas não pode estar centralizado na página. Grata, on 2015-09-08T23:56:47Z (GMT) / Submitted by Douglas Minoru Kagohara (douglasminoru@yahoo.com.br) on 2015-09-09T00:30:41Z No. of bitstreams: 2 Douglas_Kagohara.pdf: 418440 bytes, checksum: d272546247d30d373e0cdd3e2fbc6e4b (MD5) Douglas_Kagohara_v1.pdf: 433398 bytes, checksum: 16753d95c519f1a652cf186aa37895a5 (MD5) / Approved for entry into archive by Renata de Souza Nascimento (renata.souza@fgv.br) on 2015-09-09T00:40:10Z (GMT) No. of bitstreams: 2 Douglas_Kagohara.pdf: 418440 bytes, checksum: d272546247d30d373e0cdd3e2fbc6e4b (MD5) Douglas_Kagohara_v1.pdf: 433398 bytes, checksum: 16753d95c519f1a652cf186aa37895a5 (MD5) / Made available in DSpace on 2015-09-09T13:00:08Z (GMT). No. of bitstreams: 2 Douglas_Kagohara.pdf: 418440 bytes, checksum: d272546247d30d373e0cdd3e2fbc6e4b (MD5) Douglas_Kagohara_v1.pdf: 433398 bytes, checksum: 16753d95c519f1a652cf186aa37895a5 (MD5) Previous issue date: 2015-08-13 / The aim of this work is to apply and evaluate the performance of nowcasting techniques for prediction of an important macroeconomic variable of gross domestic product (GDP). In recent years, new techniques have been proposed and improved. We will compare different models of nowcasting against a benchmark, evaluating the variables are relevant from Autometrics, which was developed by Doornik (2011). The proposal is to bring together various economic indicators of the Brazilian economy that might to a greater or lesser extent anticipate GDP growth. It will be used the technique of dummy variables with saturation (proposed by Johansen et. Al.) to control possible breaks and outliers. This approach is suitable under an unstable economic environment with constant change over time. / O objetivo deste trabalho é aplicar e avaliar o desempenho do conceito de técnicas de nowcasting para previsão de uma importante variável macroeconômica do Produto Interno Bruto (PIB) brasileiro. Nos últimos anos, novas técnicas vêm sendo propostas e aprimoradas. Comparam-se diferentes modelos de nowcasting frente a um benchmarking, avaliando a relevância das variáveis a partir do Autometrics, que foi desenvolvido por Doornik (2011). A proposta é reunir diversos indicadores econômicos da economia brasileira que possam em maior ou menor grau antecipar a variação do PIB. Será utilizada a técnica de variáveis dummies com saturação (proposta por Johansen et. al.) para controlar possíveis quebras e outliers. Esta abordagem é adequada para um ambiente econômico instável, com constantes mudanças ao longo do tempo.

Submitted by Pedro Montero Mattos (pmattos90@gmail.com) on 2017-09-05T14:09:34Z No. of bitstreams: 1 nowcasting-brazilian-gdp-ficha.pdf: 808279 bytes, checksum: 3b790fa6a2be106b618a354ab1f18650 (MD5) / Rejected by Joana Martorini (joana.martorini@fgv.br), reason: Prezado Pedro, boa noite, Seu trabalho não condiz com as normas necessárias para aprovação. Favor corrigir para que possamos aceitar o arquivo. Na capa faltou o nome completo da Escola, e ao identificar o local, na parte inferior da página, colocar somente o nome da cidade e o ano, retirar páginas em branco. Dissertação, banca examinadora, data da aprovação, campo de conhecimento devem estar ao lado inferior direito da página e deve haver um resumo em português. No link abaixo, a partir da página 11, tem o modelo dos requisitos necessários que podem auxiliá-lo: http://sistema.bibliotecas-sp.fgv.br/sites/bibliotecas.fgv.br/files/bibnormas1.pdf Se preferir, entre em contato pelo telefone: Thais Oliveira Cursos de Pós-Graduação (55 11) 3799-7764 SRA - Secretaria de Registros Acadêmicos on 2017-09-05T22:51:54Z (GMT) / Submitted by Pedro Montero Mattos (pmattos90@gmail.com) on 2017-09-06T18:29:03Z No. of bitstreams: 1 nowcasting-brazilian-gdp-final.pdf: 2797146 bytes, checksum: bc06f3221f99621eef79ac27ea0570ed (MD5) / Rejected by Joana Martorini (joana.martorini@fgv.br), reason: Prezado, boa tarde. Seu trabalho foi rejeitado pelo seguintes motivos: - O título na capa, contracapa e dissertação devem ser em negrito; - A numeração de páginas começa a partir da Introdução; - As Dissertações, Data da Aprovação e Banca Examinadora devem estar ao lado direito da página. Favor fazer a correção para que possamos aprovar o item. Qualquer dúvida entrar em contato no mestradoprofissional@fgv.br ou ligue 3799-7764 Att. on 2017-09-11T17:59:58Z (GMT) / Submitted by Pedro Montero Mattos (pmattos90@gmail.com) on 2017-09-11T20:14:04Z No. of bitstreams: 1 nowcasting-brazilian-gdp-final.pdf: 1435677 bytes, checksum: f7158565f421de4eacc385ee98d3348b (MD5) / Rejected by Joana Martorini (joana.martorini@fgv.br), reason: Prezado Pedro, boa noite. O trabalho está correto, exceto pela numeração de páginas, começa a partir da "Introdução", mas com o número de páginas certo, que no caso do seu arquivo seria "14" contando a partir da folha de rosto. Favor fazer a correção para que possamos aprovar o item. Grata. on 2017-09-11T21:34:20Z (GMT) / Submitted by Pedro Montero Mattos (pmattos90@gmail.com) on 2017-09-11T21:53:46Z No. of bitstreams: 1 nowcasting-brazilian-gdp-final.pdf: 1436704 bytes, checksum: 65555fa1bc7c021e54edc92cf70d35f2 (MD5) / Approved for entry into archive by Joana Martorini (joana.martorini@fgv.br) on 2017-09-11T22:28:54Z (GMT) No. of bitstreams: 1 nowcasting-brazilian-gdp-final.pdf: 1436704 bytes, checksum: 65555fa1bc7c021e54edc92cf70d35f2 (MD5) / Made available in DSpace on 2017-09-12T17:16:25Z (GMT). No. of bitstreams: 1 nowcasting-brazilian-gdp-final.pdf: 1436704 bytes, checksum: 65555fa1bc7c021e54edc92cf70d35f2 (MD5) Previous issue date: 2017-08-16 / Based on recent surveys on nowcasting methods, we apply the one-step estimation of dynamic factor models to the Brazilian case. Such methodology copes well with the problems of mixed-frequency series, ragged edges, timeliness and high dimensionality of data sets. We use the daily expectation published by the Brazilian Central Bank as a benchmark for our model and we do not find enough evidence to reject that both models have equal predictive accuracy, under non-distressed circumstances. / Baseado em recentes pesquisas em métodos de Nowcasting, foi aplicada a estimação de modelos de fatores dinâmicos em um passo ao caso brasileiro. Esta metodologia lida com os problemas de frequências mistas, amostras recortadas, horizonte temporal e alta dimensão da amostra. Foram utilizadas as expectativas diárias do PIB publicadas pelo Banco Central como um benchmark do modelo. Não foram encontradas evidências que rejeitam a hipótese de igual poder preditivo, para circunstâncias econômicas não estressadas.