This paper investigates whether the inherent non-stationarity of macroeconomic time series is entirely due to a random walk or also to non-linear components. Applying the numerical tools of the analysis of dynamical systems to long time series for the US, we reject the hypothesis that these series are generated solely by a linear stochastic process. Contrary to the Real Business Cycle theory that attributes the irregular behavior of the system to exogenous random factors, we maintain that the fluctuations in the time series we examined cannot be explained only by means of external shocks plugged into linear autoregressive models. A dynamical and non-linear explanation may be useful for the double aim of describing and forecasting more accurately the evolution of the system. Linear growth models that find empirical verification on linear econometric analysis, are therefore seriously called in question. Conversely non-linear dynamical models may enable us to achieve a more complete information about economic phenomena from the same data sets used in the empirical analysis which are in support of Real Business Cycle Theory. We conclude that Real Business Cycle theory and more in general the unit root autoregressive models are an inadequate device for a satisfactory understanding of economic time series. A theoretical approach grounded on non-linear metric methods, may however allow to identify non-linear structures that endogenously generate fluctuations in macroeconomic time series. (authors' abstract) / Series: Working Papers Series "Growth and Employment in Europe: Sustainability and Competitiveness"

Nickel based alloys have been developed as a material offering superior general and localized corrosion resistance compared to the more traditionally used in chemical and oil plant in the most aggressive environment such as hydrochloric acid and ferric chloride. Hence the addition of Cr and Mo to Ni creates alloys with exceptional corrosion resistance in a diverse range of environments. This study examines the roles of Cr and Mo in the corrosion behavior of Ni alloys. The performance of three nickel-base alloys IN600, IN601 and C22 was examined in increasing saline solution severity of sodium chloride, concentrated hydrochloric acid and ferric chloride solution at pH = 0.0. The passive corrosion and breakdown behavior of these alloys suggests that Cr is the primary element influencing general corrosion resistance, while the repassivation potential is strongly dependent on the Mo content. This indicates that Cr plays a strong role in maintaining the passivity of the alloy, while Mo acts to stabilize the passive film after a localized breakdown event. Corrosion fatigue test results indicate that fatigue life of IN600, IN601 and C22 specimens tested in 3.5 % sodium chloride solution are essentially the same as for specimens tested in air. Test results also showed that for IN600, IN601 and C22 alloys, the number of cycles to failure was highest in air and sodium chloride solution, followed by specimens fatigued in hydrochloric acid, and was least in specimens fatigued in ferric chloride solution. No evidence of surface pitting was found on C22 specimens in all three solutions whereas IN600 and IN601 were both pitted. However, pits were generally larger in IN600 likely due to lower Cr content than in IN601.

Nickel based alloys have been developed as a material offering superior general and localized corrosion resistance compared to the more traditionally used in chemical and oil plant in the most aggressive environment such as hydrochloric acid and ferric chloride. Hence the addition of Cr and Mo to Ni creates alloys with exceptional corrosion resistance in a diverse range of environments. This study examines the roles of Cr and Mo in the corrosion behavior of Ni alloys. The performance of three nickel-base alloys IN600, IN601 and C22 was examined in increasing saline solution severity of sodium chloride, concentrated hydrochloric acid and ferric chloride solution at pH = 0.0. The passive corrosion and breakdown behavior of these alloys suggests that Cr is the primary element influencing general corrosion resistance, while the repassivation potential is strongly dependent on the Mo content. This indicates that Cr plays a strong role in maintaining the passivity of the alloy, while Mo acts to stabilize the passive film after a localized breakdown event. Corrosion fatigue test results indicate that fatigue life of IN600, IN601 and C22 specimens tested in 3.5 % sodium chloride solution are essentially the same as for specimens tested in air. Test results also showed that for IN600, IN601 and C22 alloys, the number of cycles to failure was highest in air and sodium chloride solution, followed by specimens fatigued in hydrochloric acid, and was least in specimens fatigued in ferric chloride solution. No evidence of surface pitting was found on C22 specimens in all three solutions whereas IN600 and IN601 were both pitted. However, pits were generally larger in IN600 likely due to lower Cr content than in IN601.

Maned wolves are endangered carnivores endemic to Brazil. This research aimed to compare the attitudes of interest groups towards the conservation of the maned wolf in urban and rural areas; to investigate how such attitudes may influence the maned wolf's status and conservation; and to recommend ways to incorporate such knowledge into strategies to conserve both wolf and habitat. The methodology used questionnaires and interviews. Questionnaires targeted people living in the neighbourhood of conservation areas, staff and students (year 8 and sixth-form) of local schools; staff and visitors to conservation areas and zoos in three main research locations: Greater São Paulo, the Low Mogiana region and São Carlos city. Other conservation areas and zoos within the São Paulo state contributed further data. The relationship between socio-demographic factors and attitudes towards the maned wolf conservation was also investigated to identify the most positive and negative profiles of respondents. Overall, results indicate a lack of antagonism between urban and rural populations. Results suggest that negative attitudes towards the maned wolf related to: misconceptions about feeding habits and to a lack of clear differentiation between the maned wolf and Canis lupus; perceptions of threat connected to the presence of the maned wolf on people's properties; and possibly values undermining local wildlife. Results, however, consistently indicated local people's tolerance towards the species and towards occasional predation events. Results also indicate discrepancies existing between bio/education professionals' expectations of local people's attitudes and the actual attitudes displayed by the latter. Recommendations addressed misconceptions and values regarding the maned wolf, inclusion of the local community and their issues, and relationships between interest groups for the benefit of maned wolf conservation. The positive attitudes of a majority towards the maned wolf suggest they may support actions favourable to the species and maintain their position in case of conflict. However, further investigation is advised into local people's awareness of the causes of the decline of the maned wolf and of how their behaviour may affect populations of wolves.

The classical approach to testing for structural change employs retrospective tests using a historical data set of a given length. Here we consider a wide array of fluctuation-type tests in a monitoring situation - given a history period for which a regression relationship is known to be stable, we test whether incoming data are consistent with the previously established relationship. Procedures based on estimates of the regression coefficients are extended in three directions: we introduce (a) procedures based on OLS residuals, (b) rescaled statistics and (c) alternative asymptotic boundaries. Compared to the existing tests our extensions offer better power against certain alternatives, improved size in finite samples for dynamic models and ease of computation respectively. We apply our methods to two data sets, German M1 money demand and U.S. labor productivity. / Series: Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science"

Argentina ha tenido, a lo largo de su historia, distintos procesos de crecimiento en los que las expansiones y las contracciones de su economía, en apariencia, parecen corresponder a distintos senderos de crecimiento. Si bien han sido analizados por diversos autores, el análisis se encuentra en el marco de historia económica o descripción de políticas públicas, salvo en Avila (1998), quien analiza el potencial de crecimiento económico argentino basándose en el cumplimiento de la hipótesis de convergencia; a pesar de ello, hasta la actualidad no se ha encarado un análisis empírico que contemple estos aspectos en los patrones de crecimiento de la economía Argentina. El objetivo de este trabajo es estudiar estos procesos de crecimiento dentro de un contexto de modelización no lineal en el cual se determine un umbral que delimite estas fases de crecimiento y, a partir de ello, poder caracterizar cada fase.

We analyze by simulation the properties of two time domain and two frequency domain estimators for low order autoregressive fractionally integrated moving average Gaussian models, ARFIMA (p,d,q). The estimators considered are the exact maximum likelihood for demeaned data, EML, the associated modified profile likelihood, MPL, and the Whittle estimator with, WLT, and without tapered data, WL. Length of the series is 100. The estimators are compared in terms of pile-up effect, mean square error, bias, and empirical confidence level. The tapered version of the Whittle likelihood turns out to be a reliable estimator for ARMA and ARFIMA models. Its small losses in performance in case of ``well-behaved" models are compensated sufficiently in more ``difficult" models. The modified profile likelihood is an alternative to the WLT but is computationally more demanding. It is either equivalent to the EML or more favorable than the EML. For fractionally integrated models, particularly, it dominates clearly the EML. The WL has serious deficiencies for large ranges of parameters, and so cannot be recommended in general. The EML, on the other hand, should only be used with care for fractionally integrated models due to its potential large negative bias of the fractional integration parameter. In general, one should proceed with caution for ARMA(1,1) models with almost canceling roots, and, in particular, in case of the EML and the MPL for inference in the vicinity of a moving average root of +1. (author's abstract) / Series: Preprint Series / Department of Applied Statistics and Data Processing

The paper analyses the degree of output persistence in GDP in order to empirically discriminate between the Solow growth model, the perfect competition endogenous growth model, the imperfect competition endogenous growth model, and the subcase of a multiple equilibria model of endogenous growth for the case of Austria. We find that a temporary shock in the growth rate of output induces a permanent and larger effect on the level of GDP. This leads us to refute the Solow growth model and the perfect competition model. We find strong empirical support for the imperfect competition growth model, but cannot fully rule out the possibility of multiple equilibria growth rates. / Series: Department of Economics Working Paper Series

This thesis investigates the nature of joint dividend-and-earnings signalling in announcements to the New Zealand Stock Exchange in the 1990s. Initially the Market Model is used to compute expected returns, and the abnormal returns derived from these are subjected to restricted least squares regressions to separate out a putative dividend signal from the concurrent earnings signal. But with the Market Model, the zero-value company returns associated with an absence of trading in thinly traded stocks are over-represented in returns distributions leading to problems of bias. New models are developed that explicitly exploit zero returns. The first alternative methodology entails friction modelling, which uses a maximum likelihood estimation procedure to find the relationship coefficients and the range of returns that should be considered as zero, and then proceeds to treat them as a separate category. The second alternative methodology is that of state asset models, which take a fresh new look at investor perceptions of the connection between movements in company returns and those of the concurrent underlying market. Zero-value company returns cease to be zero in value, where a state model is rotated, or alternatively they can be modelled as an extra state. All three methodologies furnish some evidence of dividend signalling; but this evidence is highly dependent on small changes within the given methodology.

This paper proposes a large Bayesian Vector Autoregressive (BVAR) model with common stochastic volatility to forecast global equity indices. Using a dataset consisting of monthly data on global stock indices the BVAR model inherently incorporates co-movements in the stock markets. The time-varying specification of the covariance structure moreover accounts for sudden shifts in the level of volatility. In an out-of-sample forecasting application we show that the BVAR model with stochastic volatility significantly outperforms the random walk both in terms of root mean squared errors as well as Bayesian log predictive scores. The BVAR model without stochastic volatility, on the other hand, underperforms relative to the random walk. In a portfolio allocation exercise we moreover show that it is possible to use the forecasts obtained from our BVAR model with common stochastic volatility to set up simple investment strategies. Our results indicate that these simple investment schemes outperform a naive buy-and-hold strategy. (authors' abstract) / Series: Department of Economics Working Paper Series