Is There a Real Estate Bubble in the Czech Republic?

Real estate prices more than doubled in many countries of Central and Eastern Europe from 2003 to 2008. In this paper, I provide one of the first assessments of whether housing prices in this region correspond to rents, i.e. to cash-flows related to an apartment purchase. State-of-the-art panel data stationarity and Granger causality techniques are employed to test the implications of the standard present value model using regional data from the Czech Republic. Apartment prices are only slightly overvalued. In addition, changes in prices are helpful in predicting changes in rents and vice versa.Central and Eastern Europe, Czech Republic, panel data, unit root, bubble, house prices, rents

Simple Signal Extension Method for Discrete Wavelet Transform

Discrete wavelet transform of finite-length signals must necessarily handle the signal boundaries. The state-of-the-art approaches treat such boundaries in a complicated and inflexible way, using special prolog or epilog phases. This holds true in particular for images decomposed into a number of scales, exemplary in JPEG 2000 coding system. In this paper, the state-of-the-art approaches are extended to perform the treatment using a compact streaming core, possibly in multi-scale fashion. We present the core focused on CDF 5/3 wavelet and the symmetric border extension method, both employed in the JPEG 2000. As a result of our work, every input sample is visited only once, while the results are produced immediately, i.e. without buffering.Comment: preprint; presented on ICSIP 201

Mossbauer spectroscopy of iron in the Luna 20 regolith

Results of the Mossbauer effect measurements on Fe-57 in the average sample of the Luna 20 regolith, and their comparison with similar measurements of the Luna 16 samples are presented. Room temperature measurements of the nonmagnetic as well as magnetic components of the spectra were performed. By careful least-squares analysis, six quadrupole doublets in the inner parts of spectra were resolved. According to their splittings, they were interpreted as four types of iron in silicates (olivine, two inequivalent pyroxene sites, and a glassy fraction) and two types of nonmagnetic iron-titanium oxides (ilmenite and a spinel). Velocity-window measurements, were used to determine the average nickel content of (2.01 plus or minus 0.84) wt. %. These results are discussed in terms of distribution of iron among different phases. In comparison with the Luna 16 sample, the Luna 20 sample contains more olivine and less ilmenite as well as metal with a slightly higher nickel content

Moving wheels, heels, and hearts: A look at dance therapy and Down syndrome

Moving Wheels and Heels is a Dance Therapy workshop in White Planes, New York for adults with physical and/or cognitive disabilities. Following a daily schedule, the dancers led by Sabatino Verlezza, Barbara Verlezza, and Nancy Lushington take part in May O\u27Donnell dance technique classes and choreograph themed pieces for the final performance at the end of the week-long workshop. One of the participants is a dancer with Down syndrome and inspired further research into the benefits of dancing for persons with Down syndrome. Dancing works to target and improve genetic, structural and muscular weaknesses, masks the task with an enjoyable activity, and increases social and emotional experiences and feelings. Materials provided include: description of fieldwork as an intern for Moving Wheels and Heels, gathered research on Down syndrome and Dance Therapy, and an interview with Barbara Verlezza

Tests for Differing Sensitivity Among Asset Returns

When comparing assets, differences in sensitivity to economic variables are highly relevant, yet tests for such differences are absent from traditional studies. We therefore examine a range of tests for parameter differences across regression equations of asset returns. Simplistic approaches, which ignore conditional heteroskedasticity and/or serial correlation, suffer test distortions in simulations calibrated to asset returns, and more ‘robust’ methods also distort, for different reasons, but among these are the best methods. The tests suggest dramatic and time-varying differences between small and large firm sensitivity to market risk, the default premium and the term structure

The Parallel Algorithm for the 2-D Discrete Wavelet Transform

The discrete wavelet transform can be found at the heart of many image-processing algorithms. Until now, the transform on general-purpose processors (CPUs) was mostly computed using a separable lifting scheme. As the lifting scheme consists of a small number of operations, it is preferred for processing using single-core CPUs. However, considering a parallel processing using multi-core processors, this scheme is inappropriate due to a large number of steps. On such architectures, the number of steps corresponds to the number of points that represent the exchange of data. Consequently, these points often form a performance bottleneck. Our approach appropriately rearranges calculations inside the transform, and thereby reduces the number of steps. In other words, we propose a new scheme that is friendly to parallel environments. When evaluating on multi-core CPUs, we consistently overcome the original lifting scheme. The evaluation was performed on 61-core Intel Xeon Phi and 8-core Intel Xeon processors.Comment: accepted for publication at ICGIP 201

Who’s Afraid of Reduced-Rank Parameterizations of Multivariate Models? Theory and Example

Reduced-rank restrictions can add useful parsimony to coefficient matrices of multivariate models, but their use is limited by the daunting complexity of the methods and their theory. The present work takes the easy road, focusing on unifying themes and simplified methods. For Gaussian and non-Gaussian (GLM, GAM, etc.) multivariate models, the present work gives a unified, explicit theory for the general asymptotic (normal) distribution of maximum likelihood estimators (mle). MLE can be complex and computationally hard, but we show a strong asymptotic equivalence between mle and a relatively simple minimum (Mahalanobis) distance estimator. The latter method yields particularly simple tests of rank, and we describe its asymptotic behavior in detail. We also examine the method’s peformance in simulation and via analytical and empirical examples

Simple Tests for Reduced Rank in Multivariate Regression

The present work proposes tests for reduced rank in multivariate regression coefficient matrices, under rather general conditions. A heuristic approach is to first estimate the regressions via standard methods, then compare the coefficient matrix rows (or columns) to assess their redundancy. A formal version of this approach utilizes the distance between an unrestricted coefficient matrix estimate and an estimate restricted by reduced rank. Two distance minimization problems emerge, based on equivalent formulations of the null hypothesis. For each method we derive estimators and tests, and their asymptotic distributions. We examine test performance in simulation, and give some numerical examples