Nonlinear Exchange Rate Adjustment in the Enlarged Euro zone. Evidence and Implications for Candidate Countries.

This paper sheds light on the importance of the validity of PPP hypothesis for the accessing process of the candidate countries towards EMU. The evidence of nonlinear adjustment in real exchange rates insists the estimation of a nonlinear SETAR model. While linear half-life estimates are biased upward (5 years on average), SETAR half-life estimates imply a faster reverting process (1.5 years on average). As a consequence, the evidence in favor of PPP hypothesis and the fast equilibrium adjustment of real exchange rates (setting Euro as the numeraire currency) imply that candidate countries follow a normal integration process towards EMU.EMU enlargement; PPP; Half-life; Nonlinearity; SETAR.

Purchasing Power Parity among developing countries and their trade-partners. Evidence from selected CEECs and Implications for their membership of EU.

The purpose of the paper is twofold. Firstly, we test the validity of the PPP hypothesis for selected CEEC (Czech Republic; Hungary; Poland and Slovak Republic). Secondly, we attempt to define those countries’ trade linkages between Euro Area; US and the rest of the world. By applying univariate unit root tests as well as a multivariate cointegration test, we find stronger evidence of PPP from the latter test. Moreover, any failure to accept PPP cannot be attributed to structural breaks, apart from one case (between Czech Republic and EU). In overall, there is evidence of strong-form PPP in 6 out of the 8 cases, while for the rest two, weak-form PPP is accepted. Thus, we confirm PPP as a long run equilibrium baseline for these exchange rates per EURO. Furthermore, the fact that PPP holds between these countries and Euro Area indicates absence of trade frictions and other barriers. The implied well-developed trade relations are consistent with those countries’ entry into EMU.PPP, Unit Root, Structural Breaks, Cointegration, Developing Countries

What causes exchange rate volatility? Evidence from selected EMU members and candidates for EMU membership countries

We allow for monetary, real, and financial variables to assess the relevant importance of each of the variables to exchange rate volatility in the case of selected EMU members and candidate countries. Ex-ante analysis shows that volatility in the Polish zloty/euro and the Hungarian forint/euro forex markets can be influenced by the monetary side of the economy. On the other hand, ex-post analysis shows that forex markets in France, Italy and Spain had been influenced, during the pre-EMU era, by monetary and real shocks. However, the Irish pound exchange rate per ECU had been affected by only real shocks.Exchange Rate Volatility; Bivariate GARCH; Volatility Spillover.

Testing for Efficiency in Selected Developing Foreign Exchange Markets: An Equilibrium-based Approach.

This paper proposes an alternative way of testing FOREX efficiency for developing countries. The FOREX market will be efficient if fully reflects all available information. If this holds, the actual exchange rate will not deviate significantly from its equilibrium rate. Moreover, the spot rate should deviate from its equilibrium rate by only transitory components (i.e. it should follow a white noise process). This test is applied to three Central & Eastern European Countries – members of the EU. Considering an LSTAR model we find no evidence of nonlinear adjustment in the misalignment series. So, linear unit root tests imply that the Poland/Euro FOREX market is efficient, the Czech/Euro FOREX market is not, while the Slovak/Euro FOREX market is quasi-efficient.FOREX efficiency; BEER; Linearity test; Unit Root.

Estimating the Equilibrium Effective Exchange Rate for Potential EMU members

In this study, we attempt to examine the possibility of emergence of significant fluctuations of the exchange rates in the future for the candidate EMU countries. In doing so, we estimate the equilibrium rate of the nominal effective exchange rate for Poland, Hungary, Slovak Republic and Malta through the BEER and PEER approaches. While the PEER-based estimation implies a large misalignment rate for the Hungarian forint, the BEER-based analysis shows that the present exchange rates of the countries considered do not deviate significantly from their equilibrium rates. As a consequence, based on BEER analysis, we do not expect large fluctuations in the effective exchange rates among the currencies considered. Hence, the relevant effective exchange rates are expected to be relatively stable. As a matter of fact, the entry of those countries into EMU is not expected to weaken the stability of Euro.Exchange rate - cointegration - BEER - PEER

Purchasing Power Parity among developing countries and their trade-partners. Evidence from selected CEECs and Implications for their membership of EU.

The purpose of the paper is twofold. Firstly, we test the validity of the PPP hypothesis for selected CEEC (Czech Republic; Hungary; Poland and Slovak Republic). Secondly, we attempt to define those countries’ trade linkages between Euro Area; US and the rest of the world. By applying both univariate unit root and a multivariate cointegration test, we find stronger evidence of PPP from the latter test. Moreover, any failure to accept PPP cannot be attributed to structural breaks, apart from one case (between Czech Republic and EU). In overall, there is evidence of strong-form PPP in 6 out of the 8 cases, while for the rest two, weak-form PPP is accepted. Thus, we confirm PPP as a long run equilibrium baseline for these exchange rates per EURO. Furthermore, the fact that PPP holds between these countries and Euro Area indicates absence of trade frictions and other barriers. The implied well-developed trade relations are consistent with those countries’ entry into EMU.PPP, Unit Root, Structural Breaks, Cointegration, Developing Countries

The Integration of the Word Processor into a Process Writing Lesson

The present paper delves into the creation of a computer-based lesson via the effective exploitation of the word processor. After the author presents the teaching situation, he discusses the rationale for the use of the word processor in a process writing lesson based on the relevant literature. Moreover, the relevant teaching materials are described and placed in appendices and the teaching procedure is justified in relation to the pedagogical framework. Keywords: TEFL, teaching methodology, word processor, process writing, writing skill DOI: 10.7176/JEP/10-22-14 Publication date: August 31st 201

Task Based Learning and Strategy Based Instruction in Teaching English as a Foreign Language

In the present paper the author discusses the innovative methodological approaches of the Task Based Learning (TBL) and the Strategy Based Instruction (SBI) in the field of teaching English as a Foreign Language (TEFL). Based on the relevant literature, after the author has identified the aims of a suggested Speaking lesson, he creates the original lesson as an example of implementing TBL and SBI and provides the tasks grading and sequencing criteria. Keywords: TEFL, TBL, SBI, teaching methodology, speaking skil

Understanding cellular differentiation by modelling of single-cell gene expression data

Over the course of the last decade single-cell RNA sequencing (scRNA-seq) has revolutionized the study of cellular heterogeneity, as one experiment routinely covers the expression of thousands of genes in tens or hundreds of thousands of cells. By quantifying differences between the single cell transcriptomes it is possible to reconstruct the process that gives rise to different cell fates from a progenitor population and gain access to trajectories of gene expression over developmental time. Tree reconstruction algorithms must deal with the high levels of noise, the high dimensionality of gene expression space, and strong non-linear dependencies between genes. In this thesis we address three aspects of working with scRNA-seq data: (1) lineage tree reconstruction, where we propose MERLoT, a novel trajectory inference method, (2) method comparison, where we propose PROSSTT, a novel algorithm that simulates scRNA-seq count data of complex differentiation trajectories, and (3) noise modelling, where we propose a novel probabilistic description of count data, a statistically motivated local averaging strategy, and an adaptation of the cross validation approach for the evaluation of gene expression imputation strategies. While statistical modelling of the data was our primary motivation, due to time constraints we did not manage to fully realize our plans for it. Increasingly complex processes like whole-organism development are being studied by single-cell transcriptomics, producing large amounts of data. Methods for trajectory inference must therefore efficiently reconstruct \textit{a priori} unknown lineage trees with many cell fates. We propose MERLoT, a method that can reconstruct trees in sub-quadratic time by utilizing a local averaging strategy, scaling very well on large datasets. MERLoT compares favorably to the state of the art, both on real data and a large synthetic benchmark. The absence of data with known complex underlying topologies makes it challenging to quantitatively compare tree reconstruction methods to each other. PROSSTT is a novel algorithm that simulates count data from complex differentiation processes, facilitating comparisons between algorithms. We created the largest synthetic dataset to-date, and the first to contain simulations with up to 12 cell fates. Additionally, PROSSTT can learn simulation parameters from reconstructed lineage trees and produce cells with expression profiles similar to the real data. Quantifying similarity between single-cell transcriptomes is crucial for clustering scRNA-seq profiles to cell types or inferring developmental trajectories, and appropriate statistical modelling of the data should improve such similarity calculations. We propose a Gaussian mixture of negative binomial distributions where gene expression variance depends on the square of the average expression. The model hyperparameters can be learned via the hybrid Monte Carlo algorithm, and a good initialization of average expression and variance parameters can be obtained by trajectory inference. A way to limit noise in the data is to apply local averaging, using the nearest neighbours of each cell to recover expression of non-captured mRNA. Our proposal, nearest neighbour smoothing with optimal bias-variance trade-off, optimizes the k-nearest neighbours approach by reducing the contribution of inappropriate neighbours. We also propose a way to assess the quality of gene expression imputation. After reconstructing a trajectory with imputed data, each cell can be projected to the trajectory using non-overlapping subsets of genes. The robustness of these assignments over multiple partitions of the genes is a novel estimator of imputation performance. Finally, I was involved in the planning and initial stages of a mouse ovary cell atlas as a collaboration