U.S. and U.K. Inflation: Evidence on Structural Change in the Order of Integration

We employ smooth transition models to test the null hypothesis of a unit root in time series on U.S. and U.K. monthly inflation beginning in 1957. Under the alternative hypothesis the test allows for structural change from level-stationarity to difference stationarity. For both countries the hypothesis of a unit root is rejected and it is estimated that rapid structural change began in 1970:6 in U.K. inflation and 1973:6 in U.S. inflation.

U.S. and U.K. Interest Rates 1890 - 1934: New Evidence on Structural Breaks

This paper presents econometric evidence on whether the founding of the Federal Reserve in 1914 caused a structural change from level-stationarity to difference-stationarity in U.S. and U.K. short-term nominal interest rates. We develop new econometric tests that allow for parameter transitions to test for a break of this kind and undertake a grid search analysis of dates and speeds for the change. We find that U.S. nominal interest rates most likely evolved rapidly to difference-stationarity in June 1917. For the U.K. we fail to reject the null that U.K. interest rate series follow a difference stationary process over the entire period 1890-1934. Our analysis differs from previous research on this topic in that we take care to explore statistical uncertainty around parameter estimates, and incorporate higher order dynamics into our econometric analysis.

Characterisation of the TBR1 interactome: variants associated with neurodevelopmental disorders disrupt novel protein interactions

TBR1 is a neuron-specific transcription factor involved in brain development and implicated in a neurodevelopmental disorder (NDD) combining features of autism spectrum disorder (ASD), intellectual disability (ID) and speech delay. TBR1 has been previously shown to interact with a small number of transcription factors and co-factors also involved in NDDs (including CASK, FOXP1/2/4 and BCL11A), suggesting that the wider TBR1 interactome may have a significant bearing on normal and abnormal brain development. Here we have identified approximately 250 putative TBR1-interaction partners by affinity purification coupled to mass spectrometry. As well as known TBR1-interactors such as CASK, the identified partners include transcription factors and chromatin modifiers, along with ASD- and ID-related proteins. Five interaction candidates were independently validated using bioluminescence resonance energy transfer assays. We went on to test the interaction of these candidates with TBR1 protein variants implicated in cases of NDD. The assays uncovered disturbed interactions for NDD-associated variants and identified two distinct protein-binding domains of TBR1 that have essential roles in protein–protein interaction

Pairwise tests of purchasing power parity

Given nominal exchange rates and price data on N + 1 countries indexed by i = 0,1,2,…, N, the standard procedure for testing purchasing power parity (PPP) is to apply unit root or stationarity tests to N real exchange rates all measured relative to a base country, 0, often taken to be the U.S. Such a procedure is sensitive to the choice of base country, ignores the information in all the other cross-rates and is subject to a high degree of cross-section dependence which has adverse effects on estimation and inference. In this article, we conduct a variety of unit root tests on all possible N(N + 1)/2 real rates between pairs of the N + 1 countries and estimate the proportion of the pairs that are stationary. This proportion can be consistently estimated even in the presence of cross-section dependence. We estimate this proportion using quarterly data on the real exchange rate for 50 countries over the period 1957-2001. The main substantive conclusion is that to reject the null of no adjustment to PPP requires sufficiently large disequilibria to move the real rate out of the band of inaction set by trade costs. In such cases, one can reject the null of no adjustment to PPP up to 90% of the time as compared to around 40% in the whole sample using a linear alternative and almost 60% using a nonlinear alternative

Point-of-Care Tests to Strengthen Health Systems and Save Newborn Lives: The Case of Syphilis

Rosanna Peeling and colleagues describe their experience of introducing point-of-care testing to screen for syphilis in pregnant women living in low- and middle-income countries

The Ontology of Biological Attributes (OBA)-computational traits for the life sciences.

Existing phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for the annotation of genome-wide association studies (GWAS), Quantitative Trait Loci (QTL) mappings or any population-focussed measurable trait data. The integration of trait and biological attribute information with an ever increasing body of chemical, environmental and biological data greatly facilitates computational analyses and it is also highly relevant to biomedical and clinical applications. The Ontology of Biological Attributes (OBA) is a formalised, species-independent collection of interoperable phenotypic trait categories that is intended to fulfil a data integration role. OBA is a standardised representational framework for observable attributes that are characteristics of biological entities, organisms, or parts of organisms. OBA has a modular design which provides several benefits for users and data integrators, including an automated and meaningful classification of trait terms computed on the basis of logical inferences drawn from domain-specific ontologies for cells, anatomical and other relevant entities. The logical axioms in OBA also provide a previously missing bridge that can computationally link Mendelian phenotypes with GWAS and quantitative traits. The term components in OBA provide semantic links and enable knowledge and data integration across specialised research community boundaries, thereby breaking silos

Asymmetric adjustment and smooth transitions: a combination of some unit root tests

Conventional Dickey–Fuller unit root tests have been generalized to allow for nonlinearity under the alternative hypothesis by Enders and Granger [Journal of Business Economics and Statistics, 16 (1998) 304] (EG) and Leybourne, Newbold and Vougas [Journal of Time Series Analysis, 19 (1998) 83] (LNV). EG focus on the case of asymmetric adjustment modelled as threshold autoregression, while LNV extend the concept of trend stationarity to that of stationarity around a smooth transition between deterministic linear trends. In this study, the EG and LNV methodologies are combined to develop tests of the null hypothesis of a unit root, that under the alternative hypothesis allow for stationary asymmetric adjustment around a smooth transition between deterministic linear trends. The empirical power of the combined tests is briefly investigated and an empirical application to time series on aggregate industrial production in the UK and the US is considered