870 resultados para Time varying coefficients


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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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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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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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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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A characterization of observability for linear time-varying descriptor systemsE(t)x(t)+F(t)x(t)=B(t)u(t), y(t)=C(t)x(t) was recently developed. NeitherE norC were required to have constant rank. This paper defines a dual system, and a type of controllability so that observability of the original system is equivalent to controllability of the dual system. Criteria for observability and controllability are given in terms of arrays of derivatives of the original coefficients. In addition, the duality results of this paper lead to an improvement on a previous fundamental structure result for solvable systems of the formE(t)x(t)+F(t)x(t)=f(tt).

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This paper is a theoretica1 and empirica1 study of the re1ationship between indexing po1icy and feedback mechanisms in the inflationary adjustment process in Brazil. The focus of our study is on two policy issues: (1) did the Brazilian system of indexing of interest rates, the exchange rate, and wages make inflation so dependent on its own past values that it created a significant feedback process and inertia in the behaviour of inflation in and (2) was the feedback effect of past inf1ation upon itself so strong that dominated the effect of monetary/fiscal variables upon current inflation? This paper develops a simple model designed to capture several "stylized facts" of Brazi1ian indexing po1icy. Separate ru1es of "backward indexing" for interest rates, the exchange rate, and wages, reflecting the evolution of po1icy changes in Brazil, are incorporated in a two-sector model of industrial and agricultural prices. A transfer function derived irom this mode1 shows inflation depending on three factors: (1) past values of inflation, (2) monetary and fiscal variables, and (3) supply- .shock variables. The indexing rules for interest rates, the exchange rate, and wages place restrictions on the coefficients of the transfer function. Variations in the policy-determined parameters of the indexing rules imply changes in the coefficients of the transfer function for inflation. One implication of this model, in contrast to previous results derived in analytically simpler models of indexing, is that a higher degree of indexing does not make current inflation more responsive to current monetary shocks. The empirical section of this paper studies the central hypotheses of this model through estimation of the inflation transfer function with time-varying parameters. The results show a systematic non-random variation of the transfer function coefficients closely synchronized with changes in the observed values of the wage-indexing parameters. Non-parametric tests show the variation of the transfer function coefficients to be statistically significant at the time of the changes in wage indexing rules in Brazil. As the degree of indexing increased, the inflation feadback coefficients increased, while the effect of external price and agricultura shocs progressively increased and monetary effects progressively decreased.

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This paper studies semistability of the recursive Kalman filter in the context of linear time-varying (LTV), possibly nondetectable systems with incorrect noise information. Semistability is a key property, as it ensures that the actual estimation error does not diverge exponentially. We explore structural properties of the filter to obtain a necessary and sufficient condition for the filter to be semistable. The condition does not involve limiting gains nor the solution of Riccati equations, as they can be difficult to obtain numerically and may not exist. We also compare semistability with the notions of stability and stability w.r.t. the initial error covariance, and we show that semistability in a sense makes no distinction between persistent and nonpersistent incorrect noise models, as opposed to stability. In the linear time invariant scenario we obtain algebraic, easy to test conditions for semistability and stability, which complement results available in the context of detectable systems. Illustrative examples are included.

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This work summarizes some results about static state feedback linearization for time-varying systems. Three different necessary and sufficient conditions are stated in this paper. The first condition is the one by [Sluis, W. M. (1993). A necessary condition for dynamic feedback linearization. Systems & Control Letters, 21, 277-283]. The second and the third are the generalizations of known results due respectively to [Aranda-Bricaire, E., Moog, C. H., Pomet, J. B. (1995). A linear algebraic framework for dynamic feedback linearization. IEEE Transactions on Automatic Control, 40, 127-132] and to [Jakubczyk, B., Respondek, W. (1980). On linearization of control systems. Bulletin del` Academie Polonaise des Sciences. Serie des Sciences Mathematiques, 28, 517-522]. The proofs of the second and third conditions are established by showing the equivalence between these three conditions. The results are re-stated in the infinite dimensional geometric approach of [Fliess, M., Levine J., Martin, P., Rouchon, P. (1999). A Lie-Backlund approach to equivalence and flatness of nonlinear systems. IEEE Transactions on Automatic Control, 44(5), 922-937]. (C) 2008 Elsevier Ltd. All rights reserved.

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This work considers a nonlinear time-varying system described by a state representation, with input u and state x. A given set of functions v, which is not necessarily the original input u of the system, is the (new) input candidate. The main result provides necessary and sufficient conditions for the existence of a local classical state space representation with input v. These conditions rely on integrability tests that are based on a derived flag. As a byproduct, one obtains a sufficient condition of differential flatness of nonlinear systems. (C) 2009 Elsevier Ltd. All rights reserved.

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When linear equality constraints are invariant through time they can be incorporated into estimation by restricted least squares. If, however, the constraints are time-varying, this standard methodology cannot be applied. In this paper we show how to incorporate linear time-varying constraints into the estimation of econometric models. The method involves the augmentation of the observation equation of a state-space model prior to estimation by the Kalman filter. Numerical optimisation routines are used for the estimation. A simple example drawn from demand analysis is used to illustrate the method and its application.

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Applied econometricians often fail to impose economic regularity constraints in the exact form economic theory prescribes. We show how the Singular Value Decomposition (SVD) Theorem and Markov Chain Monte Carlo (MCMC) methods can be used to rigorously impose time- and firm-varying equality and inequality constraints. To illustrate the technique we estimate a system of translog input demand functions subject to all the constraints implied by economic theory, including observation-varying symmetry and concavity constraints. Results are presented in the form of characteristics of the estimated posterior distributions of functions of the parameters. Copyright (C) 2001 John Wiley Sons, Ltd.

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Forecasting category or industry sales is a vital component of a company's planning and control activities. Sales for most mature durable product categories are dominated by replacement purchases. Previous sales models which explicitly incorporate a component of sales due to replacement assume there is an age distribution for replacements of existing units which remains constant over time. However, there is evidence that changes in factors such as product reliability/durability, price, repair costs, scrapping values, styling and economic conditions will result in changes in the mean replacement age of units. This paper develops a model for such time-varying replacement behaviour and empirically tests it in the Australian automotive industry. Both longitudinal census data and the empirical analysis of the replacement sales model confirm that there has been a substantial increase in the average aggregate replacement age for motor vehicles over the past 20 years. Further, much of this variation could be explained by real price increases and a linear temporal trend. Consequently, the time-varying model significantly outperformed previous models both in terms of fitting and forecasting the sales data. Copyright (C) 2001 John Wiley & Sons, Ltd.

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Proceedings of the Information Technology Applications in Biomedicine, Ioannina - Epirus, Greece, October 26-28, 2006