Alain Hecq
João Victor Issler
Sean Telg

mixed causal–noncausal autoregressions with exogenous regressors (replication data)

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 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.

Data and Resources

Suggested Citation

Hecq, Alain; Issler, João Victor; Telg, Sean (2020): Mixed causal–noncausal autoregressions with exogenous regressors (replication data). Version: 1. Journal of Applied Econometrics. Dataset.