Results 231 to 240 of about 98,361 (266)
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2006
Abstract The purpose of this chapter is to introduce the non-stationary VAR model and show that the presence of unit roots (i.e. stochastic trends) leads to a reduced rank condition on the long-run matrix .
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Abstract The purpose of this chapter is to introduce the non-stationary VAR model and show that the presence of unit roots (i.e. stochastic trends) leads to a reduced rank condition on the long-run matrix .
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A spectral decomposition for structural VAR models
Empirical Economics, 1996Based on structural VARs, this paper proposes a spectral decomposition which allows to infer the effects of changes in one variable on the other variables in the frequency domain. It is shown that there is a close relationship between this concept and conventional forecast error variance decomposition techniques for VARs.
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VaR Modelling on Long Run Horizons
Automation and Remote Control, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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1995
In the minds of some economic theorists and traditional econometricians, the vector autoregressive (VAR) approach to time-series data is unscientific, obscure, confusing, or simply wrong. Since the publication of Sims’s original contributions (1972, 1980a, 1980b, 1982), the methodology has spurred endless debates. Critics claim that the methodology has
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In the minds of some economic theorists and traditional econometricians, the vector autoregressive (VAR) approach to time-series data is unscientific, obscure, confusing, or simply wrong. Since the publication of Sims’s original contributions (1972, 1980a, 1980b, 1982), the methodology has spurred endless debates. Critics claim that the methodology has
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Model Reduction in Cointegrated VAR Models
2004Cointegrated vector autoregressive models have become a standard modeling tool in applied econometric time series analysis during the last decade. Therefore, in this chapter we explore the possibilities to extend the model selection strategies suggested in Chapter 2 to cointegrated VAR models.
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VAR modelling and Haavelmo's probability approach to macroeconomic modelling
Empirical Economics, 1993Some recent developments in the macroeconometric analysis of time series are discussed in the light of Haavelmo (1944). Experimental design in econometrics is discussed and related to the case of passive observation. The general ideas are illustrated with a analysis of the long-run and short-run structure in Danish monetary data.
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Panel VAR models with spatial dependence [PDF]
, 2002 I consider a panel vector-autoregressive model with cross-sectional dependence of the disturbances characterized by a spatial autoregressive process. I propose a three-step estimation procedure. Its first step is an instrumental variable estimation that ignores the spatial correlation.
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Consistent estimation of global VAR models [PDF]
, 2009 In this paper, I propose an instrumental variable (IV) estimation procedure to estimate global VAR (GVAR) models and show that it leads to consistent and asymptotically normal estimates of the parameters. I also provide computationally simple conditions that guarantee that the GVAR model is stable.
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