The thesis, entitled "Essays on macroeconometrics and short-term forecasting",<p>is composed of three chapters. The first two chapters are on nowcasting,<p>a topic that has received an increasing attention both among practitioners and<p>the academics especially in conjunction and in the aftermath of the 2008-2009<p>economic crisis. At the heart of the two chapters is the idea of exploiting the<p>information from data published at a higher frequency for obtaining early estimates<p>of the macroeconomic variable of interest. The models used to compute<p>the nowcasts are dynamic models conceived for handling in an efficient way<p>the characteristics of the data used in a real-time context, like the fact that due to the different frequencies and the non-synchronicity of the releases<p>the time series have in general missing data at the end of the sample. While<p>the first chapter uses a small model like a VAR for nowcasting Italian GDP,<p>the second one makes use of a dynamic factor model, more suitable to handle<p>medium-large data sets, for providing early estimates of the employment in<p>the euro area. The third chapter develops a topic only marginally touched<p>by the second chapter, i.e. the estimation of dynamic factor models on data characterized by block-structures.<p>The firrst chapter assesses the accuracy of the Italian GDP nowcasts based<p>on a small information set consisting of GDP itself, the industrial production<p>index and the Economic Sentiment Indicator. The task is carried out by using<p>real-time vintages of data in an out-of-sample exercise over rolling windows<p>of data. Beside using real-time data, the real-time setting of the exercise is<p>also guaranteed by updating the nowcasts according to the historical release calendar. The model used to compute the nowcasts is a mixed-frequency Vector<p>Autoregressive (VAR) model, cast in state-space form and estimated by<p>maximum likelihood. The results show that the model can provide quite accurate<p>early estimates of the Italian GDP growth rates not only with respect<p>to a naive benchmark but also with respect to a bridge model based on the<p>same information set and a mixed-frequency VAR with only GDP and the industrial production index.<p>The chapter also analyzes with some attention the role of the Economic Sentiment<p>Indicator, and of soft information in general. The comparison of our<p>mixed-frequency VAR with one with only GDP and the industrial production<p>index clearly shows that using soft information helps obtaining more accurate<p>early estimates. Evidence is also found that the advantage from using soft<p>information goes beyond its timeliness.<p>In the second chapter we focus on nowcasting the quarterly national account<p>employment of the euro area making use of both country-specific and<p>area wide information. The relevance of anticipating Eurostat estimates of<p>employment rests on the fact that, despite it represents an important macroeconomic<p>variable, euro area employment is measured at a relatively low frequency<p>(quarterly) and published with a considerable delay (approximately<p>two months and a half). Obtaining an early estimate of this variable is possible<p>thanks to the fact that several Member States publish employment data and<p>employment-related statistics in advance with respect to the Eurostat release<p>of the euro area employment. Data availability represents, nevertheless, a<p>major limit as country-level time series are in general non homogeneous, have<p>different starting periods and, in some cases, are very short. We construct a<p>data set of monthly and quarterly time series consisting of both aggregate and<p>country-level data on Quarterly National Account employment, employment<p>expectations from business surveys and Labour Force Survey employment and<p>unemployment. In order to perform a real time out-of-sample exercise simulating<p>the (pseudo) real-time availability of the data, we construct an artificial<p>calendar of data releases based on the effective calendar observed during the first quarter of 2012. The model used to compute the nowcasts is a dynamic<p>factor model allowing for mixed-frequency data, missing data at the beginning<p>of the sample and ragged edges typical of non synchronous data releases. Our<p>results show that using country-specific information as soon as it is available<p>allows to obtain reasonably accurate estimates of the employment of the euro<p>area about fifteen days before the end of the quarter.<p>We also look at the nowcasts of employment of the four largest Member<p>States. We find that (with the exception of France) augmenting the dynamic<p>factor model with country-specific factors provides better results than those<p>obtained with the model without country-specific factors.<p>The third chapter of the thesis deals with dynamic factor models on data<p>characterized by local cross-correlation due to the presence of block-structures.<p>The latter is modeled by introducing block-specific factors, i.e. factors that<p>are specific to blocks of time series. We propose an algorithm to estimate the model by (quasi) maximum likelihood and use it to run Monte Carlo<p>simulations to evaluate the effects of modeling or not the block-structure on<p>the estimates of common factors. We find two main results: first, that in finite samples modeling the block-structure, beside being interesting per se, can help<p>reducing the model miss-specification and getting more accurate estimates<p>of the common factors; second, that imposing a wrong block-structure or<p>imposing a block-structure when it is not present does not have negative<p>effects on the estimates of the common factors. These two results allow us<p>to conclude that it is always recommendable to model the block-structure<p>especially if the characteristics of the data suggest that there is one. / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished

Tableau d’honneur de la Faculté des études supérieures et postdoctorales, 2010-2011 / Cette étude tente de comprendre, de documenter et d'expliquer les impacts des restructurations des firmes et de l'évolution de leurs stratégies de profit sur les relations du travail à travers l'héritage historique (c. 1973-2007) du secteur automobile et la crise de 2008-09. Plus précisément, elle tente d'analyser de façon historique et comparative l'impact et l'influence des conditions politico-économiques sur les modèles productifs des firmes de l'automobile et sur les négociations collectives passées et récentes. Elle se concentre principalement sur les cas de G.M. et de Chrysler ainsi que sur les syndicats nord-américains de l'automobile, les T.C.A. et les T.U.A. Le cas canadien est analysé dans le contexte de la plus récente crise. Cette étude souligne l'influence marquée des conditions politico-économiques, l'introduction de nouveaux standards sectoriels et le blocage de l'action syndicale. À la fois dépendante de l'héritage historique, mais singulière dans sa résultante, cette crise reste un point tournant sectoriel.

La crise financière et économique, qui a entraîné en 2008 un ralentissement de l'activité économique mondiale, a eu des impacts variés sur l'économie des pays en voie de développement. Selon la structure de leurs économies initiales et de leur intégration dans le système financier mondial, ils furent affectés plus ou moins fortement. Cette crise a touché ces pays au travers de plusieurs canaux : les flux des échanges commerciaux de biens et surtout de leurs prix (Commerce extérieur), les investissements directs étrangers, les transferts de fonds privés et l'aide publique au développement. L'analyse de la vulnérabilité de ces pays à la Crise financière internationale nécessite donc une approche macroéconomique qui peut être complétée par une vision plus microéconomique en vu d'évaluer les impacts sur le niveau de pauvreté des ménages. Notre approche dans ce mémoire s'inscrit dans le cadre macroéconomique et notre analyse se fait à l'aide d'un modèle d'équilibre général calculable appliqué à la Côte d'Ivoire. En effet la modélisation en équilibre générale, qui a la particularité de tenir compte des aspects structurels de l'économie et de capturer les interactions entre les secteurs et les agents économiques aussi bien que les effets directs et indirects des chocs macroéconomiques, offre un cadre d'analyse adéquat pour évaluer les effets de la crise sur l'économie ivoirienne. Dans un premier temps, nous ferons un bref historique des faits marquants dans l'évolution de la jeune économie ivoirienne, suivie d'une description de la structure économique du pays. Ensuite, nous ferons une description des mécanismes de transmission de la crise aux pays d'Afrique Subsaharienne. Enfin, après avoir décrit les spécificités du modèle Ivoire, nous analyserons les résultats de nos simulations basés sur les canaux de transmission de la crise aux pays en développement.