Estimating Conditional Value-at-Risk with Nonstationary Quantile Predictive Regression Models

Author:

Christis Katsouris

Keyword:

Economics, Econometrics, Econometrics (econ.EM)

journal:

date:

2023-11-14 00:00:00

Abstract

This paper develops an asymptotic distribution theory for a two-stage instrumentation estimation approach in quantile predictive regressions when both generated covariates and persistent predictors are used. The generated covariates are obtained from an auxiliary quantile regression model and our main interest is the robust estimation and inference of the primary quantile predictive regression in which this generated covariate is added to the set of nonstationary regressors. We find that the proposed doubly IVX estimator is robust to the abstract degree of persistence regardless of the presence of generated regressor obtained from the first stage procedure. The asymptotic properties of the two-stage IVX estimator such as mixed Gaussianity are established while the asymptotic covariance matrix is adjusted to account for the first-step estimation error.

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