This article proposes an alternative methodology to estimate impulse response functions without imposing parametric restrictions. The impulse responses are estimated by regressing the series of interest on estimated innovations, which are the residuals obtained from a prior-stage "long autoregression." We establish the consistency and asymptotic normality of the proposed estimator. Copyright Royal Economic Society 2007
This paper establishes the asymptotic distributions of the impulse response functions in panel vecto...
In this paper the author uses iterative multiple regression and backward elimination process to dete...
This thesis proposes practical solutions to address three challenges of local projections (LPs). Fir...
We show that the standard procedure for estimating long-run identified vector autoregressions uses a...
This paper analyzes impulse response functions of vector autoregression models for variables that ar...
This paper analyzes the impulse response function of vector autoregression models for variables that...
This paper introduces methods for computing impulse response functions that do not require specifica...
Poor identification of individual impulse response coefficients does not necessarily mean that an im...
In this paper, we consider residual-based bootstrap methods à la GonÇalves and Perron (2014) to cons...
this paper was carried out within Sonderforschungsbereich 373 at the Humboldt University Berlin and ...
Abstract. Existing methods for constructing confidence bands for multi-variate impulse response func...
The statistical reliability of estimated VAR impulse responses is an important concern in applied wo...
Impulse response functions are one of the major analytic concepts in modern macroeconomics. However,...
The problem of estimation of a stochastic linear system has been a matter of active research for the...
Abstract _ This paper describes a Bayesian analysis of impulse response functions. We show how many ...
This paper establishes the asymptotic distributions of the impulse response functions in panel vecto...
In this paper the author uses iterative multiple regression and backward elimination process to dete...
This thesis proposes practical solutions to address three challenges of local projections (LPs). Fir...
We show that the standard procedure for estimating long-run identified vector autoregressions uses a...
This paper analyzes impulse response functions of vector autoregression models for variables that ar...
This paper analyzes the impulse response function of vector autoregression models for variables that...
This paper introduces methods for computing impulse response functions that do not require specifica...
Poor identification of individual impulse response coefficients does not necessarily mean that an im...
In this paper, we consider residual-based bootstrap methods à la GonÇalves and Perron (2014) to cons...
this paper was carried out within Sonderforschungsbereich 373 at the Humboldt University Berlin and ...
Abstract. Existing methods for constructing confidence bands for multi-variate impulse response func...
The statistical reliability of estimated VAR impulse responses is an important concern in applied wo...
Impulse response functions are one of the major analytic concepts in modern macroeconomics. However,...
The problem of estimation of a stochastic linear system has been a matter of active research for the...
Abstract _ This paper describes a Bayesian analysis of impulse response functions. We show how many ...
This paper establishes the asymptotic distributions of the impulse response functions in panel vecto...
In this paper the author uses iterative multiple regression and backward elimination process to dete...
This thesis proposes practical solutions to address three challenges of local projections (LPs). Fir...