CHAPTER 1:<p>The default g-priors predominant in Bayesian Model Averaging tend to over-concentrate posterior mass on a tiny set of models - a feature we denote as 'supermodel effect'. To address it, we propose a 'hyper-g' prior specification, whose data-dependent shrinkage adapts posterior model distributions to data quality. We demonstrate the asymptotic consistency of the hyper-g prior, and its interpretation as a goodness-of-fit indicator. Moreover, we highlight the similarities between hyper-g and 'Empirical Bayes' priors, and introduce closed-form expressions essential to computationally feasibility. The robustness of the hyper-g prior is demonstrated via simulation analysis, and by comparing four vintages of economic growth data.<p><p>CHAPTER 2:<p>Ciccone and Jarocinski (2010) show that inference in Bayesian Model Averaging (BMA) can be highly sensitive to small data perturbations. In particular they demonstrate that the importance attributed to potential growth determinants varies tremendously over different revisions of international income data. They conclude that 'agnostic' priors appear too sensitive for this strand of growth empirics. In response, we show that the found instability owes much to a specific BMA set-up: First, comparing the same countries over data revisions improves robustness. Second, much of the remaining variation can be reduced by applying an evenly 'agnostic', but flexible prior.<p><p>CHAPTER 3:<p>This chapter explores the link between the leverage of the US financial sector, of households and of non-financial businesses, and real activity. We document that leverage is negatively correlated with the future growth of real activity, and positively linked to the conditional volatility of future real activity and of equity returns. <p>The joint information in sectoral leverage series is more relevant for predicting future real activity than the information contained in any individual leverage series. Using in-sample regressions and out-of sample forecasts, we show that the predictive power of leverage is roughly comparable to that of macro and financial predictors commonly used by forecasters. <p>Leverage information would not have allowed to predict the 'Great Recession' of 2008-2009 any better than conventional macro/financial predictors. <p><p>CHAPTER 4:<p>Model averaging has proven popular for inference with many potential predictors in small samples. However, it is frequently criticized for a lack of robustness with respect to prediction and inference. This chapter explores the reasons for such robustness problems and proposes to address them by transforming the subset of potential 'control' predictors into principal components in suitable datasets. A simulation analysis shows that this approach yields robustness advantages vs. both standard model averaging and principal component-augmented regression. Moreover, we devise a prior framework that extends model averaging to uncertainty over the set of principal components and show that it offers considerable improvements with respect to the robustness of estimates and inference about the importance of covariates. Finally, we empirically benchmark our approach with popular model averaging and PC-based techniques in evaluating financial indicators as alternatives to established macroeconomic predictors of real economic activity. / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished

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

This dissertation consists of three research papers dealing with selected issues relevant for central banks after the global financial crisis. The post-crisis world has seen a significant strengthening of the role of central banks with regard to the financial system as well as the real economy. Correspondingly, agendas of some central bankers have grown substantially, encompassing among others monetary policy, financial stability (macro- and microprudential policies) as well as resolution mechanisms. This dissertation thesis reflects the broad focus of some contemporary central banks in three original research articles that concern current unexplored issues for monetary policy and financial stability in the European Union, the Czech Republic, and the United States, potentially bringing policy implications for the relevant authorities. The first article analyzes inflation convergence in the whole European Union (EU) over 1999-2017 and provides comprehensive and robust evidence that the process of inflation convergence among the countries of the EU was not permanently disrupted during the global financial crisis, the European sovereign debt crisis, or the period of zero lower bound interest rates. Specifically, the convergence process did not noticeably weaken after the crisis and the occurrence of...

This thesis brings together two responses to the question ‘how can the law extend the timeframe for environmentally relevant decision-making?’ The first response is drawn from the context of institutional investment, and addresses the timeframe and breadth of environmental considerations in pension fund investment decision-making. The second response is related to the context of public environmental decision-making by legislators, the judiciary, and administrators. Three themes underlie and bind the thesis: the challenges to decision-making posed by the particular temporal and spatial characteristics of environmental problems, the existence and effects of short-termism in a variety of contexts, and the legal notion of the trust as a means for analysing and addressing problems of a long-term or intergenerational nature. These themes are borne out in each of the four substantive chapters. Chapter III sets out to demonstrate the theoretical potential of pension funds to drive the reduction of firms’ environmental impact, and, focusing particularly on the notion of fiduciary duty, explores the barriers that stand in their way. Chapter IV provides a practical application of the theoretical recommendations outlined in its predecessor. It provides a framework outlining how pension funds might implement a longer term, more sustainable approach to investing. The second half of the thesis, operating in the context of public environmental decision-making, is centred upon a particularly poignant legal notion with respect to the environment and time: the concept of intergenerational equity. Just as the first half of the thesis deals with the timeframes relevant to investment decision-making by pension funds within the bounds of fiduciary duty, largely a private law affair with public implications, the second half of the thesis is concerned with the principle of intergenerational equity as a means for extending the decision-making timeframe of legislative, judicial and administrative decision-makers. As previous analyses of the concept of intergenerational equity provide little insight into its practical implications when applied to particular factual situation, Chapter V sets out the structure of the principle of intergenerational equity as revealed by case law. Chapter VI brings together the issues from the first three papers by conceptualising intergenerational equity in resource management as an issue of long-term investment. Long-term environmental decision-making faces many obstacles. Individual behavioural biases, short-term financial incentive structures, the myopic pressures of the electoral cycle and the tendency of the common law to reinforce the (often shorttermist) status quo all present significant barriers to the capacity of both private and public decision-makers to act in ways that favour the longer term interests of the environment. Nonetheless, this thesis argues that there is reason for hope: drawing upon the three themes that underlie all of the substantive Chapters, it articulates potential legislative changes and recommends the adoption of particular governance structures to overcome barriers to long-term environmental decision-making.

The main aim of this dissertation is to analyze selected economic activities and economic relations occurring between the European Union and China. This dissertation is divided into four main chapters to ensure coherence and continuity throughout the research. The first chapter deals with the historical development of mutual cooperation between Europe and China. This chapter emphasizes recent events. The most extensive part of this work, the second section, addresses key areas of cooperation between the EU and China. Most of the research focus is devoted to trade economic relations and investment relations. Further, the second chapter addresses controversial areas within the mutual EU-China relations. In contrast with the second chapter, which looks at the mutual relations from the perspective of the whole EU, the third chapter distinguishes bilateral relations between two EU countries and China. The purpose of the third chapter is therefore to highlight the different approach of individual EU member countries. In the last chapter, I try to assess the growing influence of both the EU and China within the global economy. Finally, I outline the possible future development of the research topic.