Do countries “graduate” from crises? Some historical perspective

The widespread banking crises since 2007 among advanced economies and the “near” default of Greece in 2010 dashed the popular notion that rich countries have outgrown severe financial crises. Record or near-record declines in output accompanying these events signaled the end of the short-lived “great moderation era.” In fact, graduation from recurring sovereign external debt crises is a very tortuous process that sometimes takes a century or more. For banking crises, we simply do not know what it takes to graduate; it is unclear whether any country has managed it.financial crisis, debt, default, banking, reversals, duration

ESSAYS ON GRADUATION

This dissertation attempts to address the elusive concept of "graduation", that is the emergence from frequent crisis suffering status. It contains two chapters. The first uses a data set covering over two hundred years of sovereign debt, banking and inflation crises to explore the question of how long does it take a country to "graduate" from the typical pattern of serial crises that most emerging markets experience. We find that for default and inflation crises, twenty years is a significant period, but the distribution of recidivism has extremely fat tails. In the case of banking crises, it is unclear whether countries ever graduate. We also examine the more recent phenomenon of IMF programs, which sometimes result in "near misses" but sometimes end in default even after a program is instituted. The second chapter investigates the impact of countries' institutions on their likelihood of sovereign default from both an empirical and theoretical perspective. By employing a dataset of more than 80 countries, two facts emerge: 1) high institutional quality is associated with a low frequency of sovereign default crisis, and 2) in particular, polarized governments tend to default more often. To explain these facts, we developed a model that establishes a link between institutions, government polarization and sovereign default crises. Countries that lack rules and institutional settings to limit the pressure of powerful groups on a central government's policies default more often than countries that do have good institutions. Given that there are no barriers to limit the influence of powerful groups, a more polarized government defaults more because groups do not coordinate, giving rise to a negative externality. Simulations of the model succeed in matching the cross-country differences in sovereign default frequencies, given their institutional quality and degree of government polarization in the data

Molecular genetic studies of acetyl-CoA carboxylase and 3-methylcrotonyl-CoA carboxylase in plants

Similar reverse-genetics approach is applied to investigate the function of two biotin-containing enzymes at the interface between catabolism and anabolism: acetyl-CoA carboxylase (ACCase) and 3-methylcrotonyl-CoA carboxylase (MCCase).;Plastidic ACCase catalyzes the first committed step of de novo fatty acid biosynthesis. Antisense Arabidopsis expressing antisense RNA of CAC1-A, which encodes the biotin carboxyl carrier protein (BCCP) of plastidic ACCase under the direction of CaMV 35S promoter, have been obtained. CAC1-A antisense plants with reduced BCCP possess different degrees of similar morphological changes. These include slow growth, smaller plant size, and crinkly and variegated-yellow vegetative and cauline leaves eventually leading to premature cell death. The severity of the morphological change is correlated with the magnitude of the reduction of BCCP protein. Reduced BCCP expression does not alter mRNA and protein abundance of the other three subunits of ACCase, nor does it change fatty acid composition, but it reduces fatty acid content in each CAC1-A antisense plant. Reduced BCCP expression also causes cellular and subcellular abnormalities and expression changes in genes involved in transcription and translation, anti-oxidation, pathogen and other stress responses, cell division control, and cellular structure.;MCCase is involved in mitochondrial Leu catabolism and several interconnected metabolic pathways: the mevalonate shunt and isoprenoid catabolism. Antisense Arabidopsis expressing antisense RNA of MCC-A, which encodes the biotin-containing subunit of MCCase under the direction of CaMV 35S promoter, have been generated. MCC-A antisense plants express various levels of MCC-A. In some lines, MCC-A mRNA, MCC-A protein, and MCCase activity are all below detection. No morphological changes have been observed in MCC-A antisense plants. Moreover, MCC-A antisense plants accumulate more 14C-propionyl-CoA, an intermediate metabolite of peroxisomal Leu catabolic pathway, than wild type plants, after feeding plants with 14C-Leu. Searching Arabidopsis cDNA library identifies putative branched-chain amino acid aminotransferase in mitochondria, peroxisomes, chloroplasts and cytoplasm, but not putative branched-chain 2-ketoacid dehydrogenase genes in peroxisomes. Expression patterns of genes of potential interest over time in the dark are investigated using Affymetrix microarray. Our study provides evidence supporting the existence of the peroxisomal Leu catabolic pathway, but the establishment of a detailed pathway needs more investigation

Representation Learning with Fine-grained Patterns

With the development of computational power and techniques for data collection, deep learning demonstrates a superior performance over most of existing algorithms on benchmark data sets. Many efforts have been devoted to studying the mechanism of deep learning. One important observation is that deep learning can learn the discriminative patterns from raw materials directly in a task-dependent manner. Therefore, the representations obtained by deep learning outperform hand-crafted features significantly. However, those patterns are often learned from super-class labels due to a limited availability of fine-grained labels, while fine-grained patterns are desired in many real-world applications such as visual search in online shopping. To mitigate the challenge, we propose an algorithm to learn the fine-grained patterns sufficiently when only super-class labels are available. The effectiveness of our method can be guaranteed with the theoretical analysis. Extensive experiments on real-world data sets demonstrate that the proposed method can significantly improve the performance on target tasks corresponding to fine-grained classes, when only super-class information is available for training