Economic restructuring in New York State

When economic activity slows down, labor markets may undergo extensive structural change-the permanent reallocation of workers across industries. Job losses can be heavy, and creating new jobs and retraining displaced workers to fill them can take time. A high degree of restructuring may help to explain why New York State's most recent downturn persisted for well over two years. Subseries: Second District Highlights.Employment - New York (State) ; Labor market - New York (State) ; Industries - New York (State) ; Federal Reserve District, 2nd

The Averaged Periodogram Estimator for a Power Law in Coherency

We prove the consistency of the averaged periodogram estimator (APE) in two new cases. First, we prove that the APE is consistent for negative memory parameters, after suitable tapering. Second, we prove that the APE is consistent for a power law in the cross-spectrum and therefore for a power law in the coherency, provided that sufficiently many frequencies are used in estimation. Simulation evidence suggests that the lower bound on the number of frequencies is a necessary condition for consistency. For a Taylor series approximation to the estimator of the power law in the cross-spectrum, we consider the rate of convergence, and obtain a central limit theorem under suitable regularity conditions.J.P. Morgan Chase and Co. and New York UniversityStatistics Working Papers Serie

Computationally Efficient Gaussian Maximum Likelihood Methods for Vector ARFIMA Models

In this paper, we discuss two distinct multivariate time series models that extend the univariate ARFIMA model. We describe algorithms for computing the covariances of each model, for computing the quadratic form and approximating the determinant for maximum likelihood estimation, and for simulating from each model. We compare the speed and accuracy of each algorithm to existing methods and measure the performance of the maximum likelihood estimator compared to existing methods. We also fit models to data on unemployment and inflation in the United States, to data on goods and services inflation in the United States, and to data about precipitation in the Great Lakes.Statistics Working Papers Serie

RE-EM Trees: A New Data Mining Approach for Longitudinal Data

Longitudinal data refer to the situation where repeated observations are available for each sampled individual. Methodologies that take this structure into account allow for systematic differences between individuals that are not related to covariates. A standard methodology in the statistics literature for this type of data is the random effects model, where these differences between individuals are represented by so-called “effects” that are estimated from the data. This paper presents a methodology that combines the flexibility of tree-based estimation methods with the structure of random effects models for longitudinal data. We apply the resulting estimation method, called the RE-EM tree, to pricing in online transactions, showing that the RE-EM tree is less sensitive to parametric assumptions and provides improved predictive power compared to linear models with random effects and regression trees without random effects. We also perform extensive simulation experiments to show that the estimator improves predictive performance relative to regression trees without random effects and is comparable or superior to using linear models with random effects in more general situations.Statistics Group, Information, Operations, and Management Science Department, Stern School of Business, New York UniversityStatistics Working Papers Serie

The Averaged Periodogram Estimator for a Power Law in Coherency

We prove the consistency of the averaged periodogram estimator (APE) in two new cases. First, we prove that the APE is consistent for negative memory parameters, after suitable tapering. Second, we prove that the APE is consistent for a power law in the cross-spectrum and therefore for a power law in the coherency, provided that sufficiently many frequencies are used in estimation. Simulation evidence suggests that the lower bound on the number of frequencies is a necessary condition for consistency. For a Taylor series approximation to the estimator of the power law in the cross-spectrum, we consider the rate of convergence, and obtain a central limit theorem under suitable regularity conditions.J.P. Morgan Chase and Co. and New York UniversityStatistics Working Papers Serie

Computationally Efficient Gaussian Maximum Likelihood Methods for Vector ARFIMA Models

In this paper, we discuss two distinct multivariate time series models that extend the univariate ARFIMA model. We describe algorithms for computing the covariances of each model, for computing the quadratic form and approximating the determinant for maximum likelihood estimation, and for simulating from each model. We compare the speed and accuracy of each algorithm to existing methods and measure the performance of the maximum likelihood estimator compared to existing methods. We also fit models to data on unemployment and inflation in the United States, to data on goods and services inflation in the United States, and to data about precipitation in the Great Lakes.Statistics Working Papers Serie

Targeted sequencing for high-resolution evolutionary analyses following genome duplication in salmonid fish:Proof of concept for key components of the insulin-like growth factor axis

Acknowledgements This study was funded by a Natural Environment Research Council grant (NERC, project code: NBAF704). FML is funded by a NERC Doctoral Training Grant (Project Reference: NE/L50175X/1). RLS was an undergraduate student at the University of Aberdeen and benefitted from financial support from the School of Biological Sciences. DJM is indebted to Dr. Steven Weiss (University of Graz, Austria), Dr. Takashi Yada (National Research Institute of Fisheries Science, Japan), Dr. Robert Devlin (Fisheries and Oceans Canada, Canada), Prof. Samuel Martin (University of Aberdeen, UK), Mr. Neil Lincoln (Environment Agency, UK) and Prof. Colin Adams/Mr. Stuart Wilson (University of Glasgow, UK) for providing salmonid material or assisting with its sampling. We are grateful to staff at the Centre for Genomics Research (University of Liverpool, UK) (i.e. NERC Biomolecular Analysis Facility – Liverpool; NBAF-Liverpool) for performing sequence capture/Illumina sequencing and providing us with details on associated methods that were incorporated into the manuscript. Finally, we are grateful to the organizers of the Society of Experimental Biology Satellite meeting 'Genome-powered perspectives in integrative physiology and evolutionary biology' (held in Prague, July 2015) for inviting us to contribute to this special edition of Marine Genomics and hosting a really stimulating meeting.Peer reviewedPublisher PD

DAN (NBL1) promotes collective neural crest migration by restraining uncontrolled invasion

Neural crest cells are both highly migratory and significant to vertebrate organogenesis. However, the signals that regulate neural crest cell migration remain unclear. Here, we test the function of DAN, a BMP antagonist we detected by analysis of chick cranial mesoderm. Our analysis shows that, prior to neural crest cell exit from the hindbrain, DAN is expressed in the mesoderm, then it becomes absent along cell migratory pathways. Cranial neural crest and metastatic melanoma cells avoid DAN protein stripes in vitro. Addition of DAN reduces the speed of migrating cells, in vivo and in vitro respectively. In vivo loss-of-function of DAN results in enhanced neural crest cell migration by increasing speed and directionality. Computer model simulations support the hypothesis that DAN restrains cell migration by regulating cell speed. Taken together, our results identify DAN as a novel factor that inhibits uncontrolled neural crest and metastatic melanoma invasion and promotes collective migration in a manner consistent with inhibition of BMP signaling