Self-Fulfilling Crises in the Eurozone: An Empirical Test. CEPS Working Document No. 366, 22 June 2012

This paper tests the hypothesis that government bond markets in the eurozone are more fragile and more susceptible to self-fulfilling liquidity crises than in stand-alone countries. We find evidence that a significant part of the surge in the spreads of the PIGS countries (Portugal, Ireland, Greece and Spain) in the eurozone during 2010-11 was disconnected from underlying increases in the debt-to-GDP ratios and fiscal space variables, and was the result of negative self-fulfilling market sentiments that became very strong since the end of 2010. We argue that this can drive member countries of the eurozone into bad equilibria. We also find evidence that after years of neglecting high government debt, investors became increasingly worried about this in the eurozone, and reacted by raising the spreads. No such worries developed in stand-alone countries despite the fact that debt-to-GDP ratios and fiscal space variables were equally high and increasing in these countries

Strong governments, weak banks. CEPS Policy Brief No. 305, 25 November 2013

Banks in the northern eurozone have capital ratios that are, on average, less than half of the capital ratios of banks in the eurozone’s periphery. The authors explain this by the fact that northern eurozone banks profit from the financial solidity of their governments and follow business strategies aimed at issuing too much subsidised debt. In doing so, they weaken their balance sheets and become more fragile – less able to withstand future shocks. Paradoxically, financially strong governments breed fragile banks. The opposite occurs in countries with financially weak governments. In these countries banks are forced to strengthen themselves because they are unable to rely on their governments. As a result they have significantly more capital and reserves than banks in the northern eurozone. Recommendations More than in the south, the governments of northern Europe should stand up and force the banks to issue more equity. This should go much further than what is foreseen in the Basel III accord. If the experience of the southern eurozone countries is any guide, banks in the north of the eurozone should at least double the capital and the reserves as a percentage of their balance sheets. Failure to do so risks destroying the financial solidity of the northern European governments when, in the future, negative shocks force these governments to come to the rescue of their undercapitalised banks. The new responsibilities entrusted to the European Central Bank as the single supervisor in the eurozone create a unique opportunity for that institution to change the regulatory and supervisory culture in the eurozone – one that has allowed the large banks to continue living dangerously, with insufficient capital

What Germany should fear most is its own fear: An analysis of Target2 and current account imbalances. CEPS Working Document No. 368, September 2012

This paper analyzes two claims that have been made about the Target2 payment system. The first one is that this system has been used to support unsustainable current account deficits of Southern European countries. The second one is that the large accumulation of Target2 claims by the Bundesbank represents an unacceptable risk for Germany if the eurozone were to break up. We argue that these claims are unfounded. They also lead to unnecessary fears in Germany that make a solution of the eurozone crisis more difficult. Ultimately, this fear increases the risk of a break-up of the eurozone. Or to paraphrase Franklin Roosevelt, what Germany should fear most is simply its own fear

Financing Direct Democracy: Revisiting the Research on Campaign Spending and Citizen Initiatives

The conventional view in the direct democracy literature is that spending against a measure is more effective than spending in favor of a measure, but the empirical results underlying this conclusion have been questioned by recent research. We argue that the conventional finding is driven by the endogenous nature of campaign spending: initiative proponents spend more when their ballot measure is likely to fail. We address this endogeneity by using an instrumental variables approach to analyze a comprehensive dataset of ballot propositions in California from 1976 to 2004. We find that both support and opposition spending on citizen initiatives have strong, statistically significant, and countervailing effects. We confirm this finding by looking at time series data from early polling on a subset of these measures. Both analyses show that spending in favor of citizen initiatives substantially increases their chances of passage, just as opposition spending decreases this likelihood

Revealing treacherous points for successful light-front phenomenological applications

Light-front dynamics(LFD) plays an important role in hadron phenomenology as evidenced from recent development of generalized parton distributions and other quantities involving hadrons. For successful LFD applications to hadron phenomenology, however, treacherous points such as zero-mode contributions should be taken into account. For a concrete example of zero-mode contribution, we present Standard Model analysis of vector anomaly in the CP-even form factors of W^{\pm} gauge bosons. Main distinguished features of LFD is discussed in comparison with other Hamiltonian dynamics. We also present a power counting method to correctly pin down which hadron form factors receive the zero-mode contribution and which ones do not. Indications from our analysis to hadron phenomenology are discussed.Comment: 6 pages; requires espcrc2.sty; to appear in the proceedings of Workshop on Light-Cone QCD and Nonperturbative Hadron Physics 2005 (LC 2005), Cairns, Queensland, Australia, 7-15 Jul 200

Feature and Region Selection for Visual Learning

Visual learning problems such as object classification and action recognition are typically approached using extensions of the popular bag-of-words (BoW) model. Despite its great success, it is unclear what visual features the BoW model is learning: Which regions in the image or video are used to discriminate among classes? Which are the most discriminative visual words? Answering these questions is fundamental for understanding existing BoW models and inspiring better models for visual recognition. To answer these questions, this paper presents a method for feature selection and region selection in the visual BoW model. This allows for an intermediate visualization of the features and regions that are important for visual learning. The main idea is to assign latent weights to the features or regions, and jointly optimize these latent variables with the parameters of a classifier (e.g., support vector machine). There are four main benefits of our approach: (1) Our approach accommodates non-linear additive kernels such as the popular $\chi^2$ and intersection kernel; (2) our approach is able to handle both regions in images and spatio-temporal regions in videos in a unified way; (3) the feature selection problem is convex, and both problems can be solved using a scalable reduced gradient method; (4) we point out strong connections with multiple kernel learning and multiple instance learning approaches. Experimental results in the PASCAL VOC 2007, MSR Action Dataset II and YouTube illustrate the benefits of our approach

Advances in Learning Bayesian Networks of Bounded Treewidth

This work presents novel algorithms for learning Bayesian network structures with bounded treewidth. Both exact and approximate methods are developed. The exact method combines mixed-integer linear programming formulations for structure learning and treewidth computation. The approximate method consists in uniformly sampling $k$-trees (maximal graphs of treewidth $k$), and subsequently selecting, exactly or approximately, the best structure whose moral graph is a subgraph of that $k$-tree. Some properties of these methods are discussed and proven. The approaches are empirically compared to each other and to a state-of-the-art method for learning bounded treewidth structures on a collection of public data sets with up to 100 variables. The experiments show that our exact algorithm outperforms the state of the art, and that the approximate approach is fairly accurate.Comment: 23 pages, 2 figures, 3 table

Parametric cooling of a degenerate Fermi gas in an optical trap

We demonstrate a novel technique for cooling a degenerate Fermi gas in a crossed-beam optical dipole trap, where high-energy atoms can be selectively removed from the trap by modulating the stiffness of the trapping potential with anharmonic trapping frequencies. We measure the dependence of the cooling effect on the frequency and amplitude of the parametric modulations. It is found that the large anharmonicity along the axial trapping potential allows to generate a degenerate Fermi gas with anisotropic energy distribution, in which the cloud energy in the axial direction can be reduced to the ground state value