Standard bootstrap method is used to generate confidence intervals (CIs) of impulse response functions of VAR and SVAR models in the pork sector. In the VAR model, the bootstrap method does not produce significant different results from Monte Carlo simulations. In the SVAR analysis, on the other hand, the bootstrap CIs are significantly different from Monte Carlo CIs after a six period forecast intervals. This suggests that the choice of method used to measure reliability of IRFs is not trivial. Furthermore, bootstrap CIs in SVAR model seem to be more stable than MC CIs, which tend to be wider in the longer horizons
Proxy structural vector autoregressions (SVARs)identify structural shocks in vector autoregressions ...
Three different bootstrap confidence intervals (CIs) for coefficient omega were investigated. The CI...
We study the construction of confidence intervals for efficiency levels of individual firms in stoch...
Standard bootstrap method is used to generate confidence intervals (CIs) of impulse response functio...
In this paper, we consider residual-based bootstrap methods à la GonÇalves and Perron (2014) to cons...
We propose a new bootstrap algorithm for inference for impulse responses in structural vector autore...
Constructing bootstrap confidence intervals for impulse response functions (IRFs) from structural ve...
The article demonstrates how the distribution-free method of bootstrapping can be applied to the con...
It is common to conduct bootstrap inference in vector autoregressive (VAR) models based on the assum...
Two new methods for improving prediction regions in the context of vector autoregressive (VAR) model...
The problem of forecasting from vector autoregressive models has attracted considerable attention in...
We propose a new bootstrap algorithm for inference for impulse responses in structural vector autore...
textabstractIn this paper we introduce a bootstrap procedure to test parameter restrictions in vecto...
It is argued that standard impulse response analysis based on vector autoregressive models has a num...
This paper investigates the finite sample properties of confidence intervals for structural vector e...
Proxy structural vector autoregressions (SVARs)identify structural shocks in vector autoregressions ...
Three different bootstrap confidence intervals (CIs) for coefficient omega were investigated. The CI...
We study the construction of confidence intervals for efficiency levels of individual firms in stoch...
Standard bootstrap method is used to generate confidence intervals (CIs) of impulse response functio...
In this paper, we consider residual-based bootstrap methods à la GonÇalves and Perron (2014) to cons...
We propose a new bootstrap algorithm for inference for impulse responses in structural vector autore...
Constructing bootstrap confidence intervals for impulse response functions (IRFs) from structural ve...
The article demonstrates how the distribution-free method of bootstrapping can be applied to the con...
It is common to conduct bootstrap inference in vector autoregressive (VAR) models based on the assum...
Two new methods for improving prediction regions in the context of vector autoregressive (VAR) model...
The problem of forecasting from vector autoregressive models has attracted considerable attention in...
We propose a new bootstrap algorithm for inference for impulse responses in structural vector autore...
textabstractIn this paper we introduce a bootstrap procedure to test parameter restrictions in vecto...
It is argued that standard impulse response analysis based on vector autoregressive models has a num...
This paper investigates the finite sample properties of confidence intervals for structural vector e...
Proxy structural vector autoregressions (SVARs)identify structural shocks in vector autoregressions ...
Three different bootstrap confidence intervals (CIs) for coefficient omega were investigated. The CI...
We study the construction of confidence intervals for efficiency levels of individual firms in stoch...