International Transmission under Floating Exchange Rates

International Transmission under Floating Exchange Rates

Equity Returns and Inflation: The Puzzlingly Long Lags

This paper examines data for stock prices and price levels of 14 developed countries during the post-WWII era and compares their behavior in that sample with behavior over the past two centuries in the UK and the US. Contrary to much of the literature of the past several decades, we find that nominal equity prices do, in fact, keep pace with movements in the overall price level. Our results suggest, however, that this is only the case over long periods. The puzzle therefore is not that equities fail the test as inflation hedges, as had been quite widely believed, but that they take so long to pass.Stock prices, inflation, Fisher effect, neutrality, cointegration,Equity Returns,Inflation ,Long Lags

Real Exchange Rate Behavior Under Floating and Fixed Regimes

In this paper we examine the stability of the real exchange rate and the macroeconomic effects of alternative exchange-rate regimes, including currency union, on real exchange-rate behaviour. We focus on the Irish punt in order to exploit its diversity of experience over different nominal exchange rate regimes. We make both temporal and cross-country comparisons of real-exchange-rate stability for the Irish punt with sterling, the US dollar and the German mark. We reach two conclusions on the basis of our results. The first is that for Ireland, as for most other countries, purchasing power parity provides a reasonably good description of actual exchange rate behaviour over the long run. Our second principal conclusion concerns regime effects. Currency union appears to matter. The real exchange rates we analyse are unambiguously less variable under currency union than under alternative exchange-rate systems. Otherwise, however, we find no clear-cut differences in behaviour across regimes.Exchange Rates, purchasing power parity, exchange-rate regimes, currency union

Currency Union and Real Exchange Rate Behavior

In this paper we study the behavior of the real exchange rate of three North American currencies vis-a-vis the U.S. dollar: the Canadian dollar the Mexican peso, and the Panamanian Balboa. Our principal object is to design an experiment in which meaningful comparisons of behavior across regimes would be possible. In the main we were unable to find any. The allegation of problems created due to aggregating data across regimes therefore receives no support at all in these data. A second criterion for choosing the countries in our sample was differences in level of economic development. The object here was to provide ample leeway for real variables to operate. For Mexico such factors do not appear to matter. For Panama they might be of some importance, but a modified form of PPP nevertheless continues to perform well.Real exchange rates, purchasing power parity, exchange rate regimes, currency unions.

Observation of dipole-mode vector solitons

We report on the first experimental observation of a novel type of optical vector soliton, a {\em dipole-mode soliton}, recently predicted theoretically. We show that these vector solitons can be generated in a photorefractive medium employing two different processes: a phase imprinting, and a symmetry-breaking instability of a vortex-mode vector soliton. The experimental results display remarkable agreement with the theory, and confirm the robust nature of these radially asymmetric two-component solitary waves.Comment: 4 pages, 8 figures; pictures in the PRL version are better qualit

Discovery of Sexual Dimorphisms in Metabolic and Genetic Biomarkers

Metabolomic profiling and the integration of whole-genome genetic association data has proven to be a powerful tool to comprehensively explore gene regulatory networks and to investigate the effects of genetic variation at the molecular level. Serum metabolite concentrations allow a direct readout of biological processes, and association of specific metabolomic signatures with complex diseases such as Alzheimer's disease and cardiovascular and metabolic disorders has been shown. There are well-known correlations between sex and the incidence, prevalence, age of onset, symptoms, and severity of a disease, as well as the reaction to drugs. However, most of the studies published so far did not consider the role of sexual dimorphism and did not analyse their data stratified by gender. This study investigated sex-specific differences of serum metabolite concentrations and their underlying genetic determination. For discovery and replication we used more than 3,300 independent individuals from KORA F3 and F4 with metabolite measurements of 131 metabolites, including amino acids, phosphatidylcholines, sphingomyelins, acylcarnitines, and C6-sugars. A linear regression approach revealed significant concentration differences between males and females for 102 out of 131 metabolites (p-values<3.8 x 10(-4); Bonferroni-corrected threshold). Sex-specific genome-wide association studies (GWAS) showed genome-wide significant differences in beta-estimates for SNPs in the CPS1 locus (carbamoyl-phosphate synthase 1, significance level: p<3.8 x 10(-10); Bonferroni-corrected threshold) for glycine. We showed that the metabolite profiles of males and females are significantly different and, furthermore, that specific genetic variants in metabolism-related genes depict sexual dimorphism. Our study provides new important insights into sex-specific differences of cell regulatory processes and underscores that studies should consider sex-specific effects in design and interpretation

A Methodological Perspective on Genetic Risk Prediction Studies in Type 2 Diabetes: Recommendations for Future Research

Fueled by the successes of genome-wide association studies, numerous studies have investigated the predictive ability of genetic risk models in type 2 diabetes. In this paper, we review these studies from a methodological perspective, focusing on the variables included in the risk models as well as the study designs and populations investigated. We argue and show that differences in study design and characteristics of the study population have an impact on the observed predictive ability of risk models. This observation emphasizes that genetic risk prediction studies should be conducted in those populations in which the prediction models will ultimately be applied, if proven useful. Of all genetic risk prediction studies to date, only a few were conducted in populations that might be relevant for targeting preventive interventions

Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche.

Age at menarche is a marker of timing of puberty in females. It varies widely between individuals, is a heritable trait and is associated with risks for obesity, type 2 diabetes, cardiovascular disease, breast cancer and all-cause mortality. Studies of rare human disorders of puberty and animal models point to a complex hypothalamic-pituitary-hormonal regulation, but the mechanisms that determine pubertal timing and underlie its links to disease risk remain unclear. Here, using genome-wide and custom-genotyping arrays in up to 182,416 women of European descent from 57 studies, we found robust evidence (P < 5 × 10(-8)) for 123 signals at 106 genomic loci associated with age at menarche. Many loci were associated with other pubertal traits in both sexes, and there was substantial overlap with genes implicated in body mass index and various diseases, including rare disorders of puberty. Menarche signals were enriched in imprinted regions, with three loci (DLK1-WDR25, MKRN3-MAGEL2 and KCNK9) demonstrating parent-of-origin-specific associations concordant with known parental expression patterns. Pathway analyses implicated nuclear hormone receptors, particularly retinoic acid and γ-aminobutyric acid-B2 receptor signalling, among novel mechanisms that regulate pubertal timing in humans. Our findings suggest a genetic architecture involving at least hundreds of common variants in the coordinated timing of the pubertal transition

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.