Real and nominal stochastic convergence: Are the new EU members ready to join the Euro zone?

Cataloged from PDF version of article.A key requirement for the new members to join the European Economic and Monetary Union (EMU) is real and financial convergence to European Union (EU) levels. This paper expands the analysis in [Kocenda, E., Macroeconomic convergence in transition economies, Journal of Comparative Economics 29 (2001) 1-23] and [Kutan, A., Yigit, T., Nominal and real stochastic convergence of transition economies, Journal of Comparative Economics 32 (2004) 23-36] by investigating the convergence of the new EU members to these standards. Using panel unit root techniques, we find strong evidence of real stochastic convergence for all new members, which indicates that they adjust to Euro-area output shocks. However, the degree of nominal convergence is idiosyncratic. The Baltic states exhibit the strongest monetary policy and price-level convergence, suggesting that they are ready to adopt the Euro. However, Central and East European countries should address the reasons for their lack of convergence before adopting the Euro. (c) 2005 Association for Comparative Economic Studies. Published by Elsevier Inc. All rights reserved

European Integration, Productivity Growth and Real Convergence

Cataloged from PDF version of article.This paper derives a stochastic endogenous growth model to investigate the impact of European Union (EU) integration on convergence and productivity growth. The theoretical model implies both temporary and permanent positive effects of the integration process. The empirical part of the analysis uses structural break tests and data envelopment analysis to examine the accession process of five recent members to the EU15. The results show (i) endogenously identified accession dates as structural breaks, (ii) improved rates of productivity growth after accession over and above the Union benchmark level, and (iii) increased pace of overall growth due to capital accumulation as a result of institutional features of the Union such as Structural and Cohesion Funds. These findings support the theoretical model, implying that economic integration is beneficial for member countries, especially from a long-run perspective, and Cohesion and Structural funds help the new members catch up with the core-EU members' standard of living. (c) 2006 Elsevier B.V. All rights reserved

Nominal and real stochastic convergence of transition economies

Cataloged from PDF version of article.To investigate the sensitivity of real and nominal economic convergence of transition economies to model specification and restrictions, we extend the work of Kocenda [J. Compar. Econ. 29 (2001) 1] by considering a more stable, post-1993 period and by adopting a more recent panel estimation approach. This new technique involves less restrictive assumptions than previous panel unit root techniques by allowing heterogeneity in convergence rates. Our results show less nominal and real economic convergence than those of Kocenda

Pilgrims to the Eurozone: How far, how fast?

Cataloged from PDF version of article.In our analysis, we re-examine the nominal and real convergence of all recent 10 European Union (EU) members to EU standards. Testing for monetary convergence has significant implications for interim optimal exchange rate and monetary policies before a formal and permanent link to the euro, while real convergence is the ultimate objective of economic integration. Novel features of the paper include broader measures of real convergence in both euro as well as local currencies, an examination of inflation and interest rate convergence with respect to the Maastricht benchmarks, and employment of more appropriate tests of convergence allowing for structural breaks. The results indicate slow but steady per-capita real income convergence towards EU standards. On the other hand, evidence indicates significant strong inflation and interest rate convergence. Policy implications of the paper are also discussed. © 2006 Elsevier B.V. All rights reserved

A molecular-based fast method to determine the extent of DNA damages in higher plants and fungi

Comet assay also called ‘single cell gel electrophoresis is a technique for the detection of DNA damage and repair at the level of single cells, which is one of the most advanced techniques introduced to theagricultural sciences in recent years. The assay is one of the most popular tests of DNA damage detection (e.g. single and double-strand breaks, oxidative-induced base damage and DNA-DNA/DNAproteincross linking) by electrophoresis. The assay is very sensitive, rapid, easy to handle, noninvasive, visual and inexpensive compared to most conventional techniques to detect DNA damage, there is also little amount of cell samples required and it is applicable for most eukaryotic cells, thus, it has rapidly gained importance in the fields of genetic toxicology, medicine, environmental studies and agriculture. Isolated DNA from cells are embedded in a thin agarose gel on a microscope slide and unwound in a suitable buffer and exposed to a weak electric field to attract broken, negatively-charged DNA towards the anode. After electrophoresis, migrated DNA fragments stained with a fluorescent dye would resemble a shape of a comet observed by a fluorescence microscopy. The extent of comet-like shapes would indicate the level of DNA damage in cells. The intensity of comet tail relative to the head would also reflect the extent of DNA damage in numerical

Parameterizing Gravity Waves and Understanding Their Impacts on Venus' Upper Atmosphere

The complexity of Venus upper atmospheric circulation is still being investigated. Simulations of Venus upper atmosphere largely depend on the utility of Rayleigh Friction (RF) as a driver and necessary process to reproduce observations (i.e. temperature, density, nightglow emission). Currently, there are additional observations which provide more constraints to help characterize the driver(s) of the circulation. This work will largely focus on the impact parameterized gravity waves have on Venus upper atmosphere circulation within a three dimensional hydrodynamic model (Venus Thermospheric General Circulation Model)

Effect of micronized zeolite addition to lamb concentrate feeds on growth performance and some blood chemistry and metabolites

This study was conducted to determine the effects of the addition of micronized zeolite (MZ) on the fattening performance, blood parameters, faecal ash and nitrogen levels of lambs fed concentrate feeds intensively. For two months 25 four-month-old Merino x Ile de France crossbred male lambs (21.1 ± 1.32 kg live weight) were fed 100 g alfalfa hay and a mixed concentrate diet containing 0%, 1%, 2% or 3% additional MZ. At the end of the study, bodyweight gain and feed consumption were not affected by the treatments. Similarly, the addition of up to 2% MZ to the diet did not affect slaughter weight, hot carcass or cold carcass weights, but they decreased at 3% MZ inclusion. No differences were observed between the groups in terms of blood urea nitrogen, plasma glucose, serum creatinine, triglyceride, sodium, potassium and chlorine concentration. However, serum total protein, calcium and phosphorus concentrations were affected by MZ supplementation. The addition of MZ to the ration did not affect the faecal dry matter content and total nitrogen level, yet it increased the ash content of the faeces. Consequently, it was demonstrated that the addition of up to 2% MZ to lamb grower feed does not have a negative impact on performance and carcass yield of the animals, but affects serum total protein, calcium and phosphorus concentrations

Investigating the ability of high-rate GNSS-PPP for determining the vibration modes of engineering structures: small scale model experiment

This study evaluates the performance of the Precise Point Positioning method using Global Navigation Satellite System measurements (GNSS-PPP) for monitoring vibration modes of shear type buildings excited by harmonic ground motions and hammer tests. For experimental testing, the shear type lumped-mass building system is represented by a specially designed metal frame model, resembling a three story building, which was excited on a small scale shaking table. The excitation protocols applied were harmonic motions with different frequencies and amplitudes. The metal model has special deformation plates at the column tips to prevent the nonlinear rotations and out-of-plane motions for the entire system. The fundamental vibration periods of the model structure were computed by a Finite Element Mathematical (FEM) model, which were compared with the position variations determined by GNSS-PPP. Two GNSS receivers were mounted on top of the model structure on the line perpendicular to the motion axis to measure the rotation motion. The GNSS data comprised dual-frequency observations with a 10 Hz sampling rate. GNSS-derived positioning was obtained by processing the data using a post-mission kinematic PPP method with fixed phase ambiguities. Analysis of the characteristics of the vibration frequencies showed that the high-rate GNSS PPP method can capture the frequencies of first motion mode of shear type structural response when compared with the FEM output. Results demonstrate the efficiency of the high-rate GNSS PPP method in monitoring first motion mode of a natural frequency

A new curve fitting based rating prediction algorithm for recommender systems

summary:The most algorithms for Recommender Systems (RSs) are based on a Collaborative Filtering (CF) approach, in particular on the Probabilistic Matrix Factorization (PMF) method. It is known that the PMF method is quite successful for the rating prediction. In this study, we consider the problem of rating prediction in RSs. We propose a new algorithm which is also in the CF framework; however, it is completely different from the PMF-based algorithms. There are studies in the literature that can increase the accuracy of rating prediction by using additional information. However, we seek the answer to the question that if the input data does not contain additional information, how we can increase the accuracy of rating prediction. In the proposed algorithm, we construct a curve (a low-degree polynomial) for each user using the sparse input data and by this curve, we predict the unknown ratings of items. The proposed algorithm is easy to implement. The main advantage of the algorithm is that the running time is polynomial, namely it is $\theta(n^2)$, for sparse matrices. Moreover, in the experiments we get slightly more accurate results compared to the known rating prediction algorithms