857 resultados para Environments with time-varying ocean currents
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In this paper we develop methods for estimation and forecasting in large timevarying parameter vector autoregressive models (TVP-VARs). To overcome computational constraints with likelihood-based estimation of large systems, we rely on Kalman filter estimation with forgetting factors. We also draw on ideas from the dynamic model averaging literature and extend the TVP-VAR so that its dimension can change over time. A final extension lies in the development of a new method for estimating, in a time-varying manner, the parameter(s) of the shrinkage priors commonly-used with large VARs. These extensions are operationalized through the use of forgetting factor methods and are, thus, computationally simple. An empirical application involving forecasting inflation, real output, and interest rates demonstrates the feasibility and usefulness of our approach.
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This paper provides a method to estimate time varying coefficients structuralVARs which are non-recursive and potentially overidentified. The procedureallows for linear and non-linear restrictions on the parameters, maintainsthe multi-move structure of standard algorithms and can be used toestimate structural models with different identification restrictions. We studythe transmission of monetary policy shocks and compare the results with thoseobtained with traditional methods.
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The main objective of this study is to investigate whether the Finnish investors’ country-specific strategy concentrating on emerging markets provides diversification benefits. We also analyze whether the benefits of international diversification has been diminished after periods of high volatility caused by different market crisis. The objective is investigated with three methods: Correlation coefficients, rolling correlations added with OLS trend-lines and Box’s M statistic. All the empirical tests are analyzed and calculated with logarithmic returns of weekly time series data from Friday closing values between January 1995 and December 2007. The number of weekly observations is 678. The data type is total return indices of different countries. Data is collected from DataStream and provided by Datastream Financial. Countries investigated are Finland, Argentina, Brazil, Chile, China, India, Mexico, Poland, Russia, South Africa, South Korea, Thailand and Turkey. The current data is quoted both in U.S. Dollars and local currencies. The empirical results of this thesis show that the correlation coefficients are time-varying across Finland and 12 emerging market countries. Although the correlations have risen from 1995 to 2007, there can be found sub-periods where the correlation has declined from earlier period. The results also indicate that a Finnish investor constructing a portfolio of emerging market countries cannot rely on the correlation coefficients estimated from historical data because of the instability of correlation matrices.
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This paper provides a generalisation of the structural time series version of the Almost Ideal Demand System (AIDS) that allows for time-varying coefficients (TVC/AIDS) in the presence of cross-equation constraints. An empirical appraisal of the TVC/AIDS is made using a dynamic AIDS with trending intercept as the baseline model with a data set from the Italian Household Budget Survey (1986-2001). The assessment is based on four criteria: adherence to theoretical constraints, statistical diagnostics on residuals, forecasting performance and economic meaningfulness. No clear evidence is found for superior performance of the TVC/AIDS, apart from improved short-term forecasts.
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Numerous studies have documented the failure of the static and conditional capital asset pricing models to explain the difference in returns between value and growth stocks. This paper examines the post-1963 value premium by employing a model that captures the time-varying total risk of the value-minus-growth portfolios. Our results show that the time-series of value premia is strongly and positively correlated with its volatility. This conclusion is robust to the criterion used to sort stocks into value and growth portfolios and to the country under review (the US and the UK). Our paper is consistent with evidence on the possible role of idiosyncratic risk in explaining equity returns, and also with a separate strand of literature concerning the relative lack of reversibility of value firms' investment decisions.
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This paper investigates the degree of return volatility persistence and the time-varying behaviour of systematic risk (beta) for 31 market segments in the UK real estate market. The findings suggest that different property types exhibit differences in volatility persistence and time variability. There is also evidence that the volatility persistence of each market segment and its systematic risk are significantly positively related. Thus, the systematic risks of different property types tend to move in different directions during periods of increased market volatility. Finally, the market segments with systematic risks less than one tend to show negative time variability, while market segments with systematic risk greater than one generally show positive time variability, indicating a positive relationship between the volatility of the market and the systematic risk of individual market segments. Consequently safer and riskier market segments are affected differently by increases in market volatility.
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This paper presents a novel mobile sink area allocation scheme for consumer based mobile robotic devices with a proven application to robotic vacuum cleaners. In the home or office environment, rooms are physically separated by walls and an automated robotic cleaner cannot make a decision about which room to move to and perform the cleaning task. Likewise, state of the art cleaning robots do not move to other rooms without direct human interference. In a smart home monitoring system, sensor nodes may be deployed to monitor each separate room. In this work, a quad tree based data gathering scheme is proposed whereby the mobile sink physically moves through every room and logically links all separated sub-networks together. The proposed scheme sequentially collects data from the monitoring environment and transmits the information back to a base station. According to the sensor nodes information, the base station can command a cleaning robot to move to a specific location in the home environment. The quad tree based data gathering scheme minimizes the data gathering tour length and time through the efficient allocation of data gathering areas. A calculated shortest path data gathering tour can efficiently be allocated to the robotic cleaner to complete the cleaning task within a minimum time period. Simulation results show that the proposed scheme can effectively allocate and control the cleaning area to the robot vacuum cleaner without any direct interference from the consumer. The performance of the proposed scheme is then validated with a set of practical sequential data gathering tours in a typical office/home environment.
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This Thesis is the result of my Master Degree studies at the Graduate School of Economics, Getúlio Vargas Foundation, from January 2004 to August 2006. am indebted to my Thesis Advisor, Professor Luiz Renato Lima, who introduced me to the Econometrics' world. In this Thesis, we study time-varying quantile process and we develop two applications, which are presented here as Part and Part II. Each of these parts was transformed in paper. Both papers were submitted. Part shows that asymmetric persistence induces ARCH effects, but the LMARCH test has power against it. On the other hand, the test for asymmetric dynamics proposed by Koenker and Xiao (2004) has correct size under the presence of ARCH errors. These results suggest that the LM-ARCH and the Koenker-Xiao tests may be used in applied research as complementary tools. In the Part II, we compare four different Value-at-Risk (VaR) methodologies through Monte Cario experiments. Our results indicate that the method based on quantile regression with ARCH effect dominates other methods that require distributional assumption. In particular, we show that the non-robust method ologies have higher probability to predict VaRs with too many violations. We illustrate our findings with an empirical exercise in which we estimate VaR for returns of São Paulo stock exchange index, IBOVESPA, during periods of market turmoil. Our results indicate that the robust method based on quantile regression presents the least number of violations.
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This paper investigates economic growth’s pattern of variation across and within countries using a Time-Varying Transition Matrix Markov-Switching Approach. The model developed follows the approach of Pritchett (2003) and explains the dynamics of growth based on a collection of different states, each of which has a sub-model and a growth pattern, by which countries oscillate over time. The transition matrix among the different states varies over time, depending on the conditioning variables of each country, with a linear dynamic for each state. We develop a generalization of the Diebold’s EM Algorithm and estimate an example model in a panel with a transition matrix conditioned on the quality of the institutions and the level of investment. We found three states of growth: stable growth, miraculous growth, and stagnation. The results show that the quality of the institutions is an important determinant of long-term growth, whereas the level of investment has varying roles in that it contributes positively in countries with high-quality institutions but is of little relevance in countries with medium- or poor-quality institutions.
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Many studies show environmental enrichment is correlated with benefits to captive animals; however, one should not always assume this positive relationship given that enrichment increases the amount of resources that a territorial animal must defend and possibly affects its aggressive dynamics. In this study, we tested if environmental enrichment affects aggressive interactions in the aggressive fish Nile tilapia (Oreochromis niloticus). We compared fights staged between pairs of male tilapia of similar size (= matched in resource holding potential) in a novel arena that was either barren or enriched, to examine whether enrichment enhances territory value in line with theoretical predictions, with the potential for compromised welfare. We evaluated time elapsed until the first attack (latency), frequency of aggressive interactions and fight duration. We detected fight dynamic differences at the pair level. Higher resource value generated increased aggression but had no effect on fight duration or latency. This conclusion is in line with game theory predictions concerning resource value and contradicts the theory that enrichment of the environment will serve welfare purposes. (C) 2010 Elsevier GmbH. All rights reserved.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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The atomic tunneling between two tunnel-coupled Bose-Einstein condensates (BECs) in a double-well time-dependent trap was studied. For the slowly varying trap, synchronization of oscillations of the trap with oscillations of the relative population was predicted. Using the Melnikov approach, the appearance of the chaotic oscillations in the tunneling phenomena between the condensates was confirmed.
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This paper is concerned with the controllability and stabilizability problem for control systems described by a time-varyinglinear abstract differential equation with distributed delay in the state variables. An approximate controllability propertyis established, and for periodic systems, the stabilization problem is studied. Assuming that the semigroup of operatorsassociated with the uncontrolled and non delayed equation is compact, and using the characterization of the asymptoticstability in terms of the spectrum of the monodromy operator of the uncontrolled system, it is shown that the approximatecontrollability property is a sufficient condition for the existence of a periodic feedback control law that stabilizes thesystem. The result is extended to include some systems which are asymptotically periodic. Copyright © 2014 John Wiley &Sons, Ltd.
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In environmental epidemiology, exposure X and health outcome Y vary in space and time. We present a method to diagnose the possible influence of unmeasured confounders U on the estimated effect of X on Y and to propose several approaches to robust estimation. The idea is to use space and time as proxy measures for the unmeasured factors U. We start with the time series case where X and Y are continuous variables at equally-spaced times and assume a linear model. We define matching estimator b(u)s that correspond to pairs of observations with specific lag u. Controlling for a smooth function of time, St, using a kernel estimator is roughly equivalent to estimating the association with a linear combination of the b(u)s with weights that involve two components: the assumptions about the smoothness of St and the normalized variogram of the X process. When an unmeasured confounder U exists, but the model otherwise correctly controls for measured confounders, the excess variation in b(u)s is evidence of confounding by U. We use the plot of b(u)s versus lag u, lagged-estimator-plot (LEP), to diagnose the influence of U on the effect of X on Y. We use appropriate linear combination of b(u)s or extrapolate to b(0) to obtain novel estimators that are more robust to the influence of smooth U. The methods are extended to time series log-linear models and to spatial analyses. The LEP plot gives us a direct view of the magnitude of the estimators for each lag u and provides evidence when models did not adequately describe the data.
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It has been suggested that the shape of the normalized time-varying elastance curve [E(n)(t(n))] is conserved in different cardiac pathologies. We hypothesize, however, that the E(n)(t(n)) differs quantitatively after myocardial infarction (MI). Sprague-Dawley rats (n = 9) were anesthetized, and the left anterior descending coronary artery was ligated to provoke the MI. A sham-operated control group (CTRL) (n = 10) was treated without the MI. Two months later, a conductance catheter was inserted into the left ventricle (LV). The LV pressure and volume were measured and the E(n)(t(n)) derived. Slopes of E(n)(t(n)) during the preejection period (alpha(PEP)), ejection period (alpha(EP)), and their ratio (beta = alpha(EP)/alpha(PEP)) were calculated, together with the characteristic decay time during isovolumic relaxation (tau) and the normalized elastance at end diastole (E(min)(n)). MI provoked significant LV chamber dilatation, thus a loss in cardiac output (-33%), ejection fraction (-40%), and stroke volume (-30%) (P < 0.05). Also, it caused significant calcium increase (17-fold), fibrosis (2-fold), and LV hypertrophy. End-systolic elastance dropped from 0.66 +/- 0.31 mmHg/microl (CTRL) to 0.34 +/- 0.11 mmHg/microl (MI) (P < 0.05). Normalized elastance was significantly reduced in the MI group during the preejection, ejection, and diastolic periods (P < 0.05). The slope of E(n)(t(n)) during the alpha(PEP) and beta were significantly altered after MI (P < 0.05). Furthermore, tau and end-diastolic E(min)(n) were both significantly augmented in the MI group. We conclude that the E(n)(t(n)) differs quantitatively in all phases of the heart cycle, between normal and hearts post-MI. This should be considered when utilizing the single-beat concept.