Submitted by Maicon Juliano Schmidt (maicons) on 2015-07-06T14:25:22Z No. of bitstreams: 1 Gustavo Jose Schuck.pdf: 1176134 bytes, checksum: 0a06b537ba55c68822649108c9e9d315 (MD5) / Made available in DSpace on 2015-07-06T14:25:23Z (GMT). No. of bitstreams: 1 Gustavo Jose Schuck.pdf: 1176134 bytes, checksum: 0a06b537ba55c68822649108c9e9d315 (MD5) Previous issue date: 2012-07-26 / Nenhuma / O interesse e, especialmente, a necessidade da atual economia global em entender o presente e antecipar o futuro, mesmo que no curto prazo, torna o estudo da previsão cíclica e, consequentemente, dos indicadores antecedentes de extrema importância. Dessa forma, este trabalho tem como objetivo a criação de três indicadores antecedentes compostos para a Produção Física da Agroindústria no Brasil, com horizonte de previsão entre 2 e 4 meses, 5 a 8 meses e 9 a 12 meses, respectivamente nomeados de Curto, Médio e Longo prazo. Para tanto, foi feito um levantamento do estado atual da arte, principalmente da produzida para o Brasil. Introdutoriamente, é apresentado o conceito de ciclo e indicadores antecedentes, como a justificativa e importância desse tema. Então, é feito um levantamento da literatura sobre ciclos, abordando publicações seminais, como Burns e Mitchell (1946), e a atual discussão entre ciclos econômicos e ciclos de crescimento. Após, abordo o conceito de indicadores antecedentes, sua origem, principais métodos utilizados e trabalhos atuais sobre o tema. Por fim, é construída uma metodologia, baseada no modelo proposto em OECD (2008) com adição de modelos VAR, Causalidade de Granger e Probit, sendo testada e avaliada para as informações mensais da Produção Física da Agroindústria no Brasil e outras 421 séries candidatas a antecedentes, no período entre janeiro de 1995 e dezembro de 2011. Conclui-se positivamente no que se refere à possibilidade de criação de indicadores antecedentes compostos, seja de curto, médio ou longo prazo, para Agroindústria brasileira. / The interest and especially the need of today's global economy to understand the present and anticipate the future, even in the short term, makes the study of cyclical forecasting and the leading indicators of extreme importance. Thus, this study aims to create three composite leading indicators for GDP of the Brazilian Agribusiness, with the forecast horizon between 2-4 months, 5-8 months and 9-12 months respectively named short, medium and long term. For this purpose, a survey was made of the current state of the art, mainly produced in Brazil. Introductorily, we present the concept of the cycle and leading indicators, as the justification and importance of this issue. Then, a survey of the literature on business cycles, addressing seminal publications such as Burns and Mitchell (1946), and the current discussion between business cycles and growth cycles. By then, it was mentioned the concept of leading indicators, its origin, the main methods used and current work on the subject. Finally, we built a methodology, based on the model proposed in OECD (2008) with addition of VAR models, Granger Causality and Probit. Being tested and evaluated, for the monthly information of physical production of Agribusiness in Brazil and other 421 series candidates as leading indicators, for period between January 1995 and December 2011. Completing positively to the possibility of creating composite leading indicators, whether short, medium or long term, for Brazilian Agribusiness.

La « Grande Récession » de 2008-2009 ou encore l'aggravation de la crise des dettes souveraines et de la dette publique dans la zone euro à l'été 2011, constituent de récents événements qui ont cristallisé les enjeux de l'analyse conjoncturelle, ceux relatifs notamment à la datation et à la prévision des inflexions cycliques de l'activité réelle. L'objet de cette thèse s'inscrit fondamentalement au sein de ces deux approches complémentaires du cycle économique.Le chapitre 1 dresse un portrait du cycle autour de trois conceptions distinctes de ses points de retournement : le cycle classique, le cycle de croissance et le cycle d'accélération. Nous discutons également de sa mesure eu égard aux diverses représentations possibles de l'activité agrégée d'un pays, ainsi qu'aux deux traditions existantes dans lesquelles s'inscrivent les modèles de datation. Nous mettons par ailleurs en lumière l'influence grandissante de l'environnement financier sur la dynamique cyclique des économies. Le chapitre 2 nous amène à développer deux algorithmes non-paramétriques dans le but de repérer les inflexions propres à chacun des cycles auparavant conceptualisés, mais aussipour en mesurer leurs principales caractéristiques. Le premier (resp. le second) algorithme repose sur une représentation univariée (resp. multivariée) de l'activité économique globale ; in fine, nous les appliquons aux données de la conjoncture française entre 1970 et 2010. Le chapitre 3 tire parti de nos résultats en matière de datation conjoncturelle afin de prévoir les récessions françaises depuis 1974. Au moyen de modèles probits, nous illustrons le rôle de variables financières et monétaires en tant qu'indicateurs avancés des fluctuations du cycle des affaires français. Nous montrons de plus que nos modèles prédictifs assurent uneparfaite détection des récessions pour un horizon égal à deux trimestres.Le chapitre 4 prolonge l'ensemble de l'analyse à plusieurs États membres de la zoneeuro, ces derniers étant observés depuis 1979. Nous construisons d'abord une chronologie de leurs cycles classiques respectifs puis, nous proposons un examen de leurs caractéristiques moyennes et de leur degré de synchronisation. Enfin, en s'appuyant sur des indicateurs financiers et monétaires dans le cadre d'un probit dynamique à effets fixes, nous parvenons à anticiper - jusqu'à un horizon de deux trimestres - les épisodes récessifs survenus dans les économies considérées. / The « Great Recession » of 2008-2009 and the sovereign and public debt crises which strengthened in the euro area in the summer of 2011 are recent events that have crystallized the challenges facing economic analysis, especially those related to dating and predicting cyclical inflections of real activity. The purpose of this thesis is to study these two complementary approaches to the economic cycle. Chapter 1 provides a portrait of the cycle using three distinct conceptions of its turning points: the classical cycle, the growth cycle and the acceleration cycle. We also discuss the measurement of the cycle with respect to various possible representations of aggregate activity of a country, as well as to two existing traditions which encompass dating models. Moreover, we highlight the growing influence of the financial environment over business cycle fluctuations.In chapter 2, we develop two non-parametric algorithms in order to identify theinflections that are particular to each of the previously conceptualized cycles, but also to measure their main characteristics. The first algorithm is based on a univariate representation of overall economic activity, the second on its ultivariate representation; ultimately, we apply the algorithms to the data of the French economy between 1970 and 2010. Chapter 3 builds on our results for cyclical dating to predict French recessions since 1974. Using probit models, we illustrate the role of monetary and financial variables as leading indicators of French business cycle fluctuations. In addition, we show that our models accurately detect recessions for a forecasting lag of two-quarters. Chapter 4 extends the entire analysis to several member states of the euro zone, with observations beginning in 1979. We first construct a chronology of their classical cycles, and then we propose an analysis of their main characteristics and their degree of synchronization.Finally, based on financial and monetary indicators in the context of a dynamic probit with fixed effects, we can anticipate the recessionary episodes which occurred in these economies with a horizon of two quarters.