A comparison of linear forecasting models and neural networks:an application to Euro inflation and Euro Divisia

Linear models reach their limitations in applications with nonlinearities in the data. In this paper new empirical evidence is provided on the relative Euro inflation forecasting performance of linear and non-linear models. The well established and widely used univariate ARIMA and multivariate VAR models are used as linear forecasting models whereas neural networks (NN) are used as non-linear forecasting models. It is endeavoured to keep the level of subjectivity in the NN building process to a minimum in an attempt to exploit the full potentials of the NN. It is also investigated whether the historically poor performance of the theoretically superior measure of the monetary services flow, Divisia, relative to the traditional Simple Sum measure could be attributed to a certain extent to the evaluation of these indices within a linear framework. Results obtained suggest that non-linear models provide better within-sample and out-of-sample forecasts and linear models are simply a subset of them. The Divisia index also outperforms the Simple Sum index when evaluated in a non-linear framework. © 2005 Taylor & Francis Group Ltd.

A composite leading indicator of the inflation cycle for the Euro area

We evaluate the performance of composite leading indicators of turning points of inflation in the Euro area, constructed by combining the techniques of Fourier analysis and Kalman filters with the National Bureau of Economic Research methodology. In addition, the study compares the empirical performance of Euro Simple Sum and Divisia monetary aggregates and provides a tentative answer to the issue of whether or not the UK should join the Euro area. Our findings suggest that, first, the cyclical pattern of the different composite leading indicators very closely reflect that of the inflation cycle for the Euro area; second, the empirical performance of the Euro Divisia is better than its Simple Sum counterpart and third, the UK is better out of the Euro area. © 2005 Taylor & Francis Group Ltd.

Non-curliation of Escherichia coli O78:K80 isolates associated with IS1 insertion in csgB and reduced persistence in poultry infection

The elaboration of curli fimbriae by Escherichia coli is associated with the development of a lacy colony morphology when grown on colonisation factor antigen agar at 25 degrees C. Avian colisepticaemia E. coli isolates screened for curliation by this culture technique showed lacy and smooth colonial morphologies and the genetic basis of the non-curliated smooth colonial phenotype was analysed. Two smooth E. coli O78:K80 isolates possessed about 40 copies of the IS1 element within their respective genomes of which one copy insertionally inactivated the csgB gene, the nucleator gene for curli fibril formation. One of these two isolates also possessed a defective rpoS gene which is a known regulator of curli expression. In the day-old chick model, both smooth isolates were as invasive as a known virulent O78:K80 isolate as determined by extent of liver and spleen colonisation post oral inoculation but were less persistent in terms of caecal colonisation.

Dehydration at the lens surface:surface energy and surfactant persistence

Purpose: Most published surface wettability data are based on hydrated materials and are dominated by the air-water interface. Water soluble species with hydrophobic domains (such as surfactants) interact directly with the hydrophobic domains in the lens polymer. Characterisation of relative polar and non-polar fractions of the dehydrated material provides an additional approach to surface analysis. Method: Probe liquids (water and diiodomethane) were used to characterise polar and dispersive components of surface energies of dehydrated lenses using the method of Owens and Wendt. A range of conventional and silicone hydrogel soft lenses was studied. The polar fraction (i.e. polar/total) of surface energy was used as a basis for the study of the structural effects that influence surfactant persistence on the lens surface. Results: When plotted against water content of the hydrated lens, polar fraction of surface energy (PFSE) values of the dehydrated lenses fell into two rectilinear bands. One of these bands covered PFSE values ranging from 0.4 to 0.8 and contained only conventional hydrogels, with two notable additions: the plasma coated silicone hydrogels lotrafilcon A and B. The second band covered PFSE values ranging from 0.04 to 0.28 and contained only silicone hydrogels. Significantly, the silicone hydrogel lenses with lowest PFSE values (p<0.15) are found to be prone to lipid deposition duringwear. Additionally, more hydrophobic surfactants were found to be more persistent on lenses with lower PFSE values. Conclusions: Measurement of polar fraction of surface energy provides an importantmechanistic insight into surface interactions of silicone hydrogels.

Persistence in a random bond ising model of socio-econo dynamics

We study the persistence phenomenon in a socio-econo dynamics model using computer simulations at a nite temperature on hypercubic lattices in dimensions up to ve. The model includes a \social" local eld which contains the magnetization at time t. The nearest neighbour quenched interactions are drawn from a binary distribution which is a function of the bond concentration, p. The decay of the persistence probability in the model depends on both the spatial dimension and p. We nd no evidence of \blocking" in this model. We also discuss the implications of our results for possible applications in the social and economic elds. It is suggested that the absence, or otherwise, of blocking could be used as a criterion to decide on the validity of a given model in dierent scenarios.

Does money matter in inflation forecasting

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. In our forecasting experiment we use two non-linear techniques, namely, recurrent neural networks and kernel recursive least squares regression - techniques that are new to macroeconomics. Recurrent neural networks operate with potentially unbounded input memory, while the kernel regression technique is a finite memory predictor. The two methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a naive random walk model. The best models were non-linear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation.

Early marketing matters:a time-varying parameter approach to persistence modeling

Are persistent marketing effects most likely to appear right after the introduction of a product? The authors give an affirmative answer to this question by developing a model that explicitly reports how persistent and transient marketing effects evolve over time. The proposed model provides managers with a valuable tool to evaluate their allocation of marketing expenditures over time. An application of the model to many pharmaceutical products, estimated through (exact initial) Kalman filtering, indicates that both persistent and transient effects occur predominantly immediately after a brand's introduction. Subsequently, the size of the effects declines. The authors theoretically and empirically compare their methodology with methodology based on unit root testing and demonstrate that the need for unit root tests creates difficulties in applying conventional persistence modeling. The authors recommend that marketing models should either accommodate persistent effects that change over time or be applied to mature brands or limited time windows only.

Do ethics imply persistence? The case of Islamic and socially responsible funds

We analyse the performance persistence of Islamic and Socially Responsible Investment (SRI) mutual funds. We adopt a multi-stage strategy in which, in the first stage, partial frontiers’ approaches are considered to measure the performance of the different funds in the sample. In the second stage, the results yielded by the partial frontiers are plugged into different investment strategies based on a recursive estimation methodology whose persistence performance is evaluated in the third stage of the analysis. Results indicate that, for both types of funds, performance persistence actually exists, but only for the worst and, most notably, best funds. This result is robust not only across methods (and different choices of tuning parameters within each method) but also across both SRI and Islamic funds—although in the case of the latter persistence was stronger for the best funds. The persistence of SRI and Islamic funds represents an important result for investors and the market, since it provides information on both which funds to invest in and which funds to avoid. Last but not least, the use of the aforementioned techniques in the context of mutual funds could also be of interest for the non-conclusive literature.

Persistence of apoptotic cells without autoimmune disease or inflammation in CD14-/- mice

Interaction of macrophages with apoptotic cells involves multiple steps including recognition, tethering, phagocytosis, and anti-inflammatory macrophage responses. Defective apoptotic cell clearance is associated with pathogenesis of autoimmune disease. CD14 is a surface receptor that functions in vitro in the removal of apoptotic cells by human and murine macrophages, but its mechanism of action has not been defined. Here, we demonstrate that CD14 functions as a macrophage tethering receptor for apoptotic cells.Significantly, CD14-/- macrophages in vivo are defective in clearing apoptotic cells in multiple tissues, suggesting a broad role for CD14 in the clearance process. However, the resultant persistence of apoptotic cells does not lead to inflammation or increased autoantibody production, most likely because, as we show, CD14-/- macrophages retain the ability to generate anti-inflammatory signals in response to apoptotic cells. We conclude that CD14 plays a broad tethering role in apoptotic cell clearance in vivo and that apoptotic cells can persist in the absence of proinflammatory consequences.

Evolution, recurrency and kernels in learning to model inflation

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. We use non-linear, artificial intelligence techniques, namely, recurrent neural networks, evolution strategies and kernel methods in our forecasting experiment. In the experiment, these three methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a naive random walk model. The best models were non-linear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation. There is evidence in the literature that evolutionary methods can be used to evolve kernels hence our future work should combine the evolutionary and kernel methods to get the benefits of both.

Cardiocentric neurophysiology:the persistence of a delusion

Aristotle is well known to have taught that the brain was a mere coolant apparatus for overheated blood and to have located the hegemonikon in the heart. This teaching was hotly disputed by his immediate successors in the Alexandrian Museum, who showed that the brain played the central role in psychophysiology. This was accepted and developed by the last great biomedical figure of classical antiquity - Claudius Galen. However, Aristotle's cardiocentric theory did not entirely disappear and this article traces its influence through the Arabic physicians of the Islamic ascendancy, into the European Middle Ages where Albertus Magnus' attempt to reconcile cardiocentric and cerebrocentric physiology was particularly influential. It shows how cardiocentricity was sufficiently accepted to attract the attention of, and require refutation by, many of the great names of the Renaissance, including Vesalius, Fernel, and Descartes, and was still taken seriously by luminaries such as William Harvey in the mid-seventeenth century. The article, in rehearsing this history, shows the difficulty of separating the first-person perspective of introspective psychology and the third-person perspective of natural science. It also outlines an interesting case of conflict between philosophy and physiology. © 2013 Copyright Taylor & Francis Group, LLC.

Inflation convergence in Europe

Convergence has been a popular theme in applied economics since the seminal papers of Barro (1991) and Barro and Sala-i-Martin (1992). The very notion of convergence quickly becomes problematic from an academic viewpoint however when we try and formalise a framework to think about these issues. In the light of the abundance of available convergence concepts, it would be useful to have a more universal framework that encompassed existing concepts as special cases. Moreover, much of the convergence literature has treated the issue as a zero-one outcome. We argue that it is more sensible and useful for policy decision makers and academic researchers to consider also ongoing convergence over time. Assessing the progress of ongoing convergence is one interesting and important means of evaluating whether the Eastern European New Member Countries (NMC) of the European Union (EU) are getting closer to being deemed “ready” to join the European Monetary Union (EMU), that is, fulfilling the Maastricht convergence criteria.

Inflation forecasting, relative price variability and skewness

This article presents out-of-sample inflation forecasting results based on relative price variability and skewness. It is demonstrated that forecasts on long horizons of 1.5-2 years are significantly improved if the forecast equation is augmented with skewness. © 2010 Taylor & Francis.

Does money matter in inflation forecasting?

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. In our forecasting experiment we use two nonlinear techniques, namely, recurrent neural networks and kernel recursive least squares regressiontechniques that are new to macroeconomics. Recurrent neural networks operate with potentially unbounded input memory, while the kernel regression technique is a finite memory predictor. The two methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a nave random walk model. The best models were nonlinear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation. Beyond its economic findings, our study is in the tradition of physicists' long-standing interest in the interconnections among statistical mechanics, neural networks, and related nonparametric statistical methods, and suggests potential avenues of extension for such studies. © 2010 Elsevier B.V. All rights reserved.