Mixed causal–noncausal autoregressions with exogenous regressors

B-Tier
Journal: Journal of Applied Econometrics
Year: 2020
Volume: 35
Issue: 3
Pages: 328-343

Score contribution per author:

0.670 = (α=2.01 / 3 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

Mixed causal–noncausal autoregressive (MAR) models have been proposed to model time series exhibiting nonlinear dynamics. Possible exogenous regressors are typically substituted into the error term to maintain the MAR structure of the dependent variable. We introduce a representation including these covariates called MARX to study their direct impact. The asymptotic distribution of the MARX parameters is derived for a class of non‐Gaussian densities. For a Student t likelihood, closed‐form standard errors are provided. By simulations, we evaluate the MARX model selection procedure using information criteria. We examine the influence of the exchange rate and industrial production index on commodity prices.

Technical Details

RePEc Handle
repec:wly:japmet:v:35:y:2020:i:3:p:328-343
Journal Field
Econometrics
Author Count
3
Added to Database
2026-01-29