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Asymptotic distributions of impulse response functions and forecast error variance decompositions of vector autoregressive models
Lütkepohl, Helmut - In: The review of economics and statistics 72 (1990) 1, pp. 116-125
Persistent link: https://www.econbiz.de/10001085596
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Asymptotic distribution of the moving average coefficients of an estimated vector autoregressive process
Lütkepohl, Helmut - In: Econometric theory 4 (1988) 1, pp. 77-85
Persistent link: https://www.econbiz.de/10001049386
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Comparison of predictors for temporally and contemporaneously aggregated time series
Lütkepohl, Helmut - In: International journal of forecasting 2 (1986) 4, pp. 461-475
Persistent link: https://www.econbiz.de/10001036216
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Forecasting cointegrated VARMA processes
Lütkepohl, Helmut - 1999
Persistent link: https://www.econbiz.de/10001413243
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The sources of the US money demand instability
Lütkepohl, Helmut - In: Empirical economics : a journal of the Institute for … 18 (1993) 4, pp. 729-743
Persistent link: https://www.econbiz.de/10001331523
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Prediction tests for structural stability of multiple time series
Lütkepohl, Helmut - In: Journal of business & economic statistics : JBES ; a … 7 (1989) 1, pp. 129-135
Persistent link: https://www.econbiz.de/10001090220
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Forecasting aggregated vector ARMA processes
Lütkepohl, Helmut - 1987
Persistent link: https://www.econbiz.de/10013277996
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Structural vector autoregressive models with more shocks than variables identified via heteroskedasticity
Lütkepohl, Helmut - In: Economics letters 195 (2020), pp. 1-4
Persistent link: https://www.econbiz.de/10012509991
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Vector autoregressive models
Lütkepohl, Helmut - In: Handbook of research methods and applications in …, (pp. 139-164). 2013
Persistent link: https://www.econbiz.de/10010206841
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Structural vector autoregressive models with more shocks than variables identified via heteroskedasticity
Lütkepohl, Helmut - 2020
In conventional structural vector autoregressive (VAR) models it is assumed that there are at most as many structural shocks as there are variables in the model. It is pointed out that heteroskedasticity can be used to identify more shocks than variables. However, even if there is...
Persistent link: https://www.econbiz.de/10012223488