The decline in the U.S. personal saving rate: is it real and is it a puzzle?

Since the mid-1990s, the national income and product accounts personal saving rate for the United States has been trending down, dropping into negative territory for three months during the past two years. This paper examines measurement problems surrounding two of the standard definitions of the personal saving rate. The authors conclude that, despite these measurement problems, the recent decline of the U.S. personal saving rate to low levels seems to be a real economic phenomenon and may be a cause for concern for several reasons. After examining several possible explanations for the trend advanced in the recent literature, the authors conclude that none of them provides a compelling explanation for the steep decline and negative levels of the U.S. personal saving rate.Consumer behavior ; Saving and investment

Bubbling (or just frothy) house prices?

Housing

Computing Higher Leray–Serre Spectral Sequences of Towers of Fibrations

The higher Leray–Serre spectral sequence associated with a tower of fibrations represents a generalization of the classical Leray–Serre spectral sequence of a fibration. In this work, we present algorithms to compute higher Leray–Serre spectral sequences leveraging the effective homology technique, which allows to perform computations involving chain complexes of infinite type associated with interesting objects in algebraic topology. In order to develop the programs, implemented as a new module for the Computer Algebra system Kenzo, we translated the original construction of the higher Leray–Serre spectral sequence in a simplicial framework and studied some of its fundamental properties

Fracionamento de diferentes classes de compostos químicos por cromatografia líquida em coluna.

Resumo

2,4-Dimethoxy­benzaldehyde azine

The title mol­ecule, C18H20N2O4, is located on a crystallographic centre of symmetry. The meth­oxy groups are coplanar with the benzene ring [interplanar angles of 14.4 (2) and 3.1 (3)°], indicating a conjugation effect

Recombinant expression of Streptococcus pneumoniae capsular polysaccharides in Escherichia coli.

Currently, Streptococcus pneumoniae is responsible for over 14 million cases of pneumonia worldwide annually, and over 1 million deaths, the majority of them children. The major determinant for pathogenesis is a polysaccharide capsule that is variable and is used to distinguish strains based on their serotype. The capsule forms the basis of the pneumococcal polysaccharide vaccine (PPV23) that contains purified capsular polysaccharide from 23 serotypes, and the pneumococcal conjugate vaccine (PCV13), containing 13 common serotypes conjugated to CRM197 (mutant diphtheria toxin). Purified capsule from S. pneumoniae is required for pneumococcal conjugate vaccine production, and costs can be prohibitively high, limiting accessibility of the vaccine in low-income countries. In this study, we demonstrate the recombinant expression of the capsule-encoding locus from four different serotypes of S. pneumoniae within Escherichia coli. Furthermore, we attempt to identify the minimum set of genes necessary to reliably and efficiently express these capsules heterologously. These E. coli strains could be used to produce a supply of S. pneumoniae serotype-specific capsules without the need to culture pathogenic bacteria. Additionally, these strains could be applied to synthetic glycobiological applications: recombinant vaccine production using E. coli outer membrane vesicles or coupling to proteins using protein glycan coupling technology

ITS-rDNA phylogeny of Colletotrichum spp. causal agent of apple glomerella leaf spot.

Several diseases have affected apple production, among them there is Glomerella leaf spot (GLS) caused by Colletotrichum spp. The first report of this disease in apple was in plants nearby citrus orchards in São Paulo State, Brazil. The origin of this disease is still not clear, and studies based on the molecular phylogeny could relate the organisms evolutionarily and characterize possible mechanisms of divergent evolution. The amplification of 5.8S-ITS (Internal Transcribed Spacer) of rDNA of 51 pathogenic Colletotrichum spp. isolates from apples, pineapple guava and citrus produced one fragment of approximately 600 bases pairs (bp) for all the isolates analyzed. The amplified fragments were cleaved with restriction enzymes, and fragments from 90 to 500bp were obtained. The sequencing of this region allowed the generation of a phylogenetic tree, regardless of their hosts, and 5 isolated groups were obtained. From the "in silico" comparison, it was possible to verify a variation from 93 to 100% of similarity between the sequences studied and the Genbank data base. The causal agent of GLS is nearly related (clustered) to isolates of pineapple guava and to the citrus isolates used as control

Linear predictability vs. bull and bear market models in strategic asset allocation decisions: evidence from UK data

Most papers in the portfolio choice literature have examined linear predictability frameworks based on the idea that simple but flexible Vector Autoregressive (VAR) models can be expanded to produce portfolio allocations that hedge against the bull and bear dynamics typical of financial markets through careful selection of predictor variables that capture business cycles and market sentiment. Yet, a distinct literature exists that shows that non-linear econometric frameworks, such as Markov switching, are also natural tools to compute optimal portfolios arising from the existence of good and bad market states. This paper examines whether and how simple VARs can produce portfolio rules similar to those obtained under a simple Markov switching, by studying the effects of expanding both the order of the VAR and the number/selection of predictor variables included. In a typical stock-bond strategic asset allocation problem for UK data, we compute the out-of-sample certainty equivalent returns for a wide range of VARs and compare these measures of performance with those of non-linear models. We conclude that most VARs cannot produce portfolio rules, hedging demands or (net of transaction costs) out-of-sample performances that approximate those obtained from simple non-linear frameworks

Linear Predictability vs. Bull and Bear Market Models in Strategic Asset Allocation Decisions: Evidence from UK Data

Most papers in the portfolio choice literature have examined linear predictability frameworks based on the idea that simple but flexible Vector Autoregressive (VAR) models can be expanded to produce portfolio allocations that hedge against the bull and bear dynamics typical of financial markets through careful selection of predictor variables that capture business cycles and market sentiment. Yet, a distinct literature exists that shows that nonlinear econometric frameworks, such as Markov switching, are also natural tools to compute optimal portfolios arising from the existence of good and bad market states. This paper examines whether and how simple VARs can produce portfolio rules similar to those obtained under a simple Markov switching, by studying the effects of expanding both the order of the VAR and the number/selection of predictor variables included. In a typical stock-bond strategic asset allocation problem for U.K. data, we compute the out-of-sample certainty equivalent returns for a wide range of VARs and compare these measures of performance with those of nonlinear models. We conclude that most VARs cannot produce portfolio rules, hedging demands, or (net of transaction costs) out-of-sample performances that approximate those obtained from equally simple nonlinear frameworks