On the search for spillovers from foreign direct investment (FDI) with spatial dependency

This paper examines various specifications that are used within the literature to test for spillovers from foreign direct investment (FDI). Analysis provides significant evidence of externalities from inward FDI, but it shows that these externalities are more localized than has previously been believed. Further, the results demonstrate that the econometric treatment of issues such as agglomeration, contiguity and spatial dependence significantly changes the conclusions regarding local and national spillovers from FDI, and productivity growth more generally.

The accuracy of parameter estimation from noisy data, with application to resonance peak estimation in distributed Brillouin sensing

Distributed Brillouin sensing of strain and temperature works by making spatially resolved measurements of the position of the measurand-dependent extremum of the resonance curve associated with the scattering process in the weakly nonlinear regime. Typically, measurements of backscattered Stokes intensity (the dependent variable) are made at a number of predetermined fixed frequencies covering the design measurand range of the apparatus and combined to yield an estimate of the position of the extremum. The measurand can then be found because its relationship to the position of the extremum is assumed known. We present analytical expressions relating the relative error in the extremum position to experimental errors in the dependent variable. This is done for two cases: (i) a simple non-parametric estimate of the mean based on moments and (ii) the case in which a least squares technique is used to fit a Lorentzian to the data. The question of statistical bias in the estimates is discussed and in the second case we go further and present for the first time a general method by which the probability density function (PDF) of errors in the fitted parameters can be obtained in closed form in terms of the PDFs of the errors in the noisy data.

Financial constraints in investment:panel data results from Estonia, 1995–1999

To investigate investment behaviour the present study applies panel data techniques, in particular the Arellano-Bond (1991) GMM estimator, based on data on Estonian manufacturing firms from the period 1995-1999. We employ the model of optimal capital accumulation in the presence of convex adjustment costs. The main research findings are that domestic companies seem to be financially more constrained than those where foreign investors are present, and also, smaller firms are more constrained than their larger counterparts.

The accuracy of parameter estimation from noisy data, with application to resonance peak estimation in distributed Brillouin sensing

Distributed Brillouin sensing of strain and temperature works by making spatially resolved measurements of the position of the measurand-dependent extremum of the resonance curve associated with the scattering process in the weakly nonlinear regime. Typically, measurements of backscattered Stokes intensity (the dependent variable) are made at a number of predetermined fixed frequencies covering the design measurand range of the apparatus and combined to yield an estimate of the position of the extremum. The measurand can then be found because its relationship to the position of the extremum is assumed known. We present analytical expressions relating the relative error in the extremum position to experimental errors in the dependent variable. This is done for two cases: (i) a simple non-parametric estimate of the mean based on moments and (ii) the case in which a least squares technique is used to fit a Lorentzian to the data. The question of statistical bias in the estimates is discussed and in the second case we go further and present for the first time a general method by which the probability density function (PDF) of errors in the fitted parameters can be obtained in closed form in terms of the PDFs of the errors in the noisy data.

Visualisation of heterogeneous data with the generalised generative topographic mapping

Heterogeneous and incomplete datasets are common in many real-world visualisation applications. The probabilistic nature of the Generative Topographic Mapping (GTM), which was originally developed for complete continuous data, can be extended to model heterogeneous (i.e. containing both continuous and discrete values) and missing data. This paper describes and assesses the resulting model on both synthetic and real-world heterogeneous data with missing values.

Visualisation of heterogeneous data with simultaneous feature saliency using Generalised Generative Topographic Mapping

Most machine-learning algorithms are designed for datasets with features of a single type whereas very little attention has been given to datasets with mixed-type features. We recently proposed a model to handle mixed types with a probabilistic latent variable formalism. This proposed model describes the data by type-specific distributions that are conditionally independent given the latent space and is called generalised generative topographic mapping (GGTM). It has often been observed that visualisations of high-dimensional datasets can be poor in the presence of noisy features. In this paper we therefore propose to extend the GGTM to estimate feature saliency values (GGTMFS) as an integrated part of the parameter learning process with an expectation-maximisation (EM) algorithm. The efficacy of the proposed GGTMFS model is demonstrated both for synthetic and real datasets.

Rumba Clave Blen Blen Blen: Film Screening and Panel Discussion with Director Arístides Falcón Paradí

This flyer promotes the event "Rumba Clave Blen Blen Blen: Film Screening and Panel Discussion with Director Arístides Falcón Paradí".

Geometric inequalities for initial data with symmetries

We consider a class of initial data sets (Σ,h,K) for the Einstein constraint equations which we define to be generalized Brill (GB) data. This class of data is simply connected, U(1)²-invariant, maximal, and four-dimensional with two asymptotic ends. We study the properties of GB data and in particular the topology of Σ. The GB initial data sets have applications in geometric inequalities in general relativity. We construct a mass functional M for GB initial data sets and we show:(i) the mass of any GB data is greater than or equals M, (ii) it is a non-negative functional for a broad subclass of GB data, (iii) it evaluates to the ADM mass of reduced t − φi symmetric data set, (iv) its critical points are stationary U(1)²-invariant vacuum solutions to the Einstein equations. Then we use this mass functional and prove two geometric inequalities: (1) a positive mass theorem for subclass of GB initial data which includes Myers-Perry black holes, (2) a class of local mass-angular momenta inequalities for U(1)²-invariant black holes. Finally, we construct a one-parameter family of initial data sets which we show can be seen as small deformations of the extreme Myers- Perry black hole which preserve the horizon geometry and angular momenta but have strictly greater energy.

Association of anticholinergic burden with adverse effects in older people with intellectual disabilities:an observational cross-sectional study

BACKGROUND: No studies to date have investigated cumulative anticholinergic exposure and its effects in adults with intellectual disabilities. AIMS: To determine the cumulative exposure to anticholinergics and the factors associated with high exposure. METHOD: A modified Anticholinergic Cognitive Burden (ACB) scale score was calculated for a representative cohort of 736 people over 40 years old with intellectual disabilities, and associations with demographic and clinical factors assessed. RESULTS: Age over 65 years was associated with higher exposure (ACB 1-4 odds ratio (OR) = 3.28, 95% CI 1.49-7.28, ACB 5+ OR = 3.08, 95% CI 1.20-7.63), as was a mental health condition (ACB 1-4 OR = 9.79, 95% CI 5.63-17.02, ACB 5+ OR = 23.74, 95% CI 12.29-45.83). Daytime drowsiness was associated with higher ACB (P<0.001) and chronic constipation reported more frequently (26.6% ACB 5+ v. 7.5% ACB 0, P<0.001). CONCLUSIONS: Older people with intellectual disabilities and with mental health conditions were exposed to high anticholinergic burden. This was associated with daytime dozing and constipation.

The study of correlation between sea surface temperature (SST) by using the NOAA-AVHRR data and compare this data with temperature measurement in the Caspian Sea

The changes in time and location of surface temperature from a water body has an important effect on climate activities, marine biology, sea currents, salinity and other characteristics of the seas and lakes water. Traditional measurement of temperature is costly and time consumer due to its dispersion and instability. In recent years the use of satellite technology and remote sensing sciences for data acquiring and parameter and lysis of climatology and oceanography is well developed. In this research we used the NOAA’s Satellite images from its AVHRR system to compare the field surface temperature data with the satellite images information. Ten satellite images were used in this project. These images were calibrated with the field data at the exact time of satellite pass above the area. The result was a significant relation between surface temperatures from satellite data with the field work. As the relative error less than %40 between these two data is acceptable, therefore in our observation the maximum error is %21.2 that can be considered it as acceptable. In all stations the result of satellite measurements is usually less than field data that cores ponds with the global result too. As this sea has a vast latitude, therefore the different in the temperature is natural. But we know this factor is not the only cause for surface currents. The information of all satellites were images extracted by ERDAS software, and the “Surfer” software is used to plot the isotherm lines.