Are bilateral real exchange rates stationary? Evidence from Lagrange multiplier unit root tests for India

The paper examines the stationarity of India’s real exchange rate vis-a` -vis 16 of its major trading partner countries for the period 1960–2000. Application of the conventional ADF unit root test, the Lagrange multiplier (LM) unit root test with one structural break, and the LM unit root test with two structural breaks provides evidence that India’s exchange rate vis-a` -vis 15 out of 16 countries is stationary, implying support for purchasing power parity.

The purchasing power parity revisited : new evidence for 16 OECD countries from panel unit root tests with structural breaks

In this paper, we apply a range of univariate unit root tests including the Lagrangian multiplier (LM) univariate and panel unit root tests to examine PPP for 16 OECD countries. In addition to incorporating structural breaks in the univariate exchange rate series, we also incorporate structural breaks in the panel exchange rate models. Our main finding from univariate tests, with and without structural breaks and panel LM test with one break, is that real exchange rates are not stationary, inconsistent with PPP hypothesis. However, when we incorporate two structural breaks in the univariate LM test, for most countries we find that real exchange rates are stationary. Moreover, we obtain overwhelming support for PPP when we apply panel LM unit root tests with two structural breaks.

New evidence on purchasing power parity from 17 OECD countries

There is a large literature that investigates whether or not real exchange rates are stationary in an attempt to unravel support for purchasing power parity (PPP). At best, the empirical results are mixed. This paper applies a unit root test that allows for a simultaneous structural break in the intercept and slope, shown by Sen (2003) to minimize power distortions, to examine PPP for 17 OECD countries. Our results on PPP are mixed. When the real exchange rate is based on the US dollar, evidence is found of PPP for only France, Portugal and Denmark. When the real exchange rate is based on the Deutschmark, we find evidence of PPP for Austria, Belgium, Norway, Spain, Netherlands, Switzerland, and Denmark.

Uplink power control via adaptive hmm estimation

Transmit power control is an important consideration in the cellular system design since it increases system capacity, improves QoS and reduces multi-user interference. In this paper, an adaptive power control design based on the identification of the underlying pathloss of the fading channel is presented. Making power control decisions based on the measured received power allows to model the fading channel pathloss dynamics with a Hidden Markov Model. Applying the online HMM identification algorithm enables accurate estimation of the real pathloss which ensures efficient performance of the suggested power control scheme.

Consolidation within the Australian real estate investment trust sector : an evaluation of the impact on unitholder returns

Mergers and acquisitions within the Australian-real estate investment trusts (A-REITs) sector have become a noticeable trend in the last decade. Utilising
event study methodology, 36 successful A-REIT mergers and acquisitions
between January 1995 and December 2008 were examined. Both target and
bidding shareholders experience positive excess returns of 4.27% and 0.54%
respectively over the 41 day event window [−20, +20]. Analysis indicates that the
cumulative abnormal returns (CARs) for bidding firms are considerably greater
than previous research suggests. This study finds higher bidder CARs when scrip
or a combination of scrip and cash is used to finance the acquisition. We also find
that the relative size or the size of the acquirer have a positive and significant
impact on the excess returns of bidding A-REITs. This suggests that the
synergistic benefits from the acquisition are a result of economies of scale and
increased market power. There is also some evidence that the relative size and
method of payment influence the CARs of target firms during the event window.

Locating the semiotic power of multimodality

This article reports research that attempts to characterize what is powerful about digital multimodal texts. Building from recent theoretical work on understanding the workings and implications of multimodal communication, the authors call for a continuing empirical investigation into the roles that digital multimodal texts play in real-world contexts, and they offer one example of how such investigations might be approached. Drawing on data from the practice of multimedia digital storytelling, specifically a piece titled “Lyfe-N-Rhyme,” created by Oakland, California, artist Randy Young (accessible at http://www.oaklanddusty.org/videos.php), the authors detail the method and results of a fine-grained multimodal analysis, revealing semiotic relationships between and among different, copresent modes. It is in these relationships, the authors argue, that the expressive power of multimodality resides.

Direct method for optimal power management in hybrid electric vehicles

Hybrid electric vehicles are powered by an electric system and an internal combustion engine. The components of a hybrid electric vehicle need to be coordinated in an optimal manner to deliver the desired performance. This paper presents an approach based on direct method for optimal power management in hybrid electric vehicles with inequality constraints. The approach consists of reducing the optimal control problem to a set of algebraic equations by approximating the state variable which is the energy of electric storage, and the control variable which is the power of fuel consumption. This approximation uses orthogonal functions with unknown coefficients. In addition, the inequality constraints are converted to equal constraints. The advantage of the developed method is that its computational complexity is less than that of dynamic and non-linear programming approaches. Also, to use dynamic or non-linear programming, the problem should be discretized resulting in the loss of optimization accuracy. The propsed method, on the other hand, does not require the discretization of the problem producing more accurate results. An example is solved to demonstrate the accuracy of the proposed approach. The results of Haar wavelets, and Chebyshev and Legendre polynomials are presented and discussed. © 2011 The Korean Society of Automotive Engineers and Springer-Verlag Berlin Heidelberg.

Fine-scale effects of habitat loss and fragmentation despite large-scale gene flow for some regionally declining woodland bird species

Habitat loss and associated fragmentation effects are well-recognised threats to biodiversity. Loss of functional connectivity (mobility, gene flow and demographic continuity) could result in population decline in altered habitat, because smaller, isolated populations are more vulnerable to extinction. We tested whether substantial habitat reduction plus fragmentation is associated with reduced gene flow in three 'decliner' woodland-dependent bird species (eastern yellow robin, weebill and spotted pardalote) identified in earlier work to have declined disproportionately in heavily fragmented landscapes in the Box-Ironbark forest region in north-central Victoria, Australia. For these three decliners, and one 'tolerant' species (striated pardalote), we compared patterns of genetic diversity, relatedness, effective population size, sex-ratios and genic (allele frequency) differentiation among landscapes of different total tree cover, identified population subdivision at the regional scale, and explored fine-scale genotypic (individual-based genetic signature) structure. Unexpectedly high genetic connectivity across the study region was detected for 'decliner' and 'tolerant' species. Power analysis simulations suggest that moderate reductions in gene flow should have been detectable. However, there was evidence of local negative effects of reduced habitat extent and structural connectivity: slightly lower effective population sizes, lower genetic diversity, higher within-site relatedness and altered sex-ratios (for weebill and eastern yellow robin) in 10 x 10 km 'landscapes' with low vegetation cover. We conclude that reduced structural connectivity in the Box-Ironbark ecosystem may still allow sufficient gene flow to avoid the harmful effects of inbreeding in our study species. Although there may still be negative consequences of fragmentation for demographic connectivity, the high genetic connectivity of mobile bird species in this system suggests that reconnecting isolated habitat patches may be less important than increasing habitat extent and/or quality if these need to be traded off.

Power penalty assessment of OXADM device model - analytical analysis

This OXADM are located in the nodes, which have more than two switching directions in ring networks. The function of OXADM is to flexibility switch the wavelengths among the different input and output ports. Because of the OXADM's imperfect performance, the insertion loss and crosstalk are induced in the system. Analytical modeling method is using to analyze the OXADM structure in crosstalk or power leakage that lead to the power penalty. To overcome this problem, power penalty is needed to be supplied. The insertion of this power penalty depends on few parameters. The parameters that we going to investigate here will be in term of number of operating wavelengths and number of input/output ports as well as the Q factor. The variation of this parameters will affects the amount of the desired power penalty. Simulation results in higher crosstalk or higher power penalty needed as the number of OXADM increases. As the sum of the wavelength and the number of input/output for each OXADM increases, the power penalty will increased as well. Investigation on the maximum Q factors is 6 to get the minimum power penalty at the lowest BER for most of the combination of the sum of the wavelength and the number of input/output for each OXADM.

Uplink power control via adaptive Hidden-Markov-Model-Based pathloss estimation

Dynamic variations in channel behavior is considered in transmission power control design for cellular radio systems. It is well known that power control increases system capacity, improves Quality of Service (QoS), and reduces multiuser interference. In this paper, an adaptive power control design based on the identification of the underlying pathloss dynamics of the fading channel is presented. Formulating power control decisions based on the measured received power levels allows modeling the fading channel pathloss dynamics in terms of a Hidden Markov Model (HMM). Applying the online HMM identification algorithm enables accurate estimation of the real pathloss ensuring efficient performance of the suggested power control scheme.

Development and delivery of the appropriate assessments items for power systems related PBL subjects

Problem Based Learning (PBL) as a teaching method has been around for many years. It is one of the most effective ways of learning and teaching. It uses real world problems as a learning method and encourages learners to learn independently while a mentoring support is provided by the academic. However, various academic institutions develop the assessments items in many ways; the implementation and delivery become a challenge in ensuring the right assessment and implementation. This paper discusses some of the practical experiences of the development and delivery of the appropriate assessment items for power systems related PBL subjects.

Hybrid prediction method for solar power using different computational intelligence algorithms

Computational Intelligence (CI) holds the key to the development of smart grid to overcome the challenges of planning and optimization through accurate prediction of Renewable Energy Sources (RES). This paper presents an architectural framework for the construction of hybrid intelligent predictor for solar power. This research investigates the applicabil- ity of heterogeneous regression algorithms for 6 hour ahead solar power availability forecasting using historical data from Rockhampton, Australia. Real life solar radiation data is collected across six years with hourly resolution from 2005 to 2010. We observe that the hybrid prediction method is suitable for a reliable smart grid energy management. Prediction reliability of the proposed hybrid prediction method is carried out in terms of prediction error performance based on statistical and graphical methods. The experimental results show that the proposed hybrid method achieved acceptable prediction accuracy. This potential hybrid model is applicable as a local predictor for any proposed hybrid method in real life application for 6 hours in advance prediction to ensure constant solar power supply in the smart grid operation.

International power transitions, critical realism, and the rise of China

This thesis employs the philosophy of critical realism to develop an innovative theory and methodology for the study of international power transitions. The theory is then applied in a future-oriented case analysis to enrich explanation and understanding of a major real world policy challenge - the rise of China.

A sequential purchasing power parity test for panels of large cross-sections and implications for investors

In this paper we use monthly time series data for not less than 64 countries and a new sequential approach to test for purchasing power parity (PPP). The results are strong in that the evidence in favor of PPP is very weak. In fact, for the US-dollar-based exchange rates the evidence is basically non-existent. In order to eliminate the effect of the base currency, we also apply the sequential PPP test to all pairs of exchange rates, and find similarly weak evidence of PPP. However, for those rates where evidence is found, using a technical trading rule, we find evidence of significant profits. The predictability of the stationary pairs is therefore important for investors. © 2014 © 2014 Taylor & Francis.

A modified fuzzy min-max neural network for data clustering and its application to power quality monitoring

When no prior knowledge is available, clustering is a useful technique for categorizing data into meaningful groups or clusters. In this paper, a modified fuzzy min-max (MFMM) clustering neural network is proposed. Its efficacy for tackling power quality monitoring tasks is demonstrated. A literature review on various clustering techniques is first presented. To evaluate the proposed MFMM model, a performance comparison study using benchmark data sets pertaining to clustering problems is conducted. The results obtained are comparable with those reported in the literature. Then, a real-world case study on power quality monitoring tasks is performed. The results are compared with those from the fuzzy c-means and k-means clustering methods. The experimental outcome positively indicates the potential of MFMM in undertaking data clustering tasks and its applicability to the power systems domain.