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Testing for Noncausal Vector Autoregressive Representation

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  • Mehdi Hamidi Sahneh

    (UC3M)

Abstract

We propose a test for non-causal vector autoregressive representation generated by non-Gaussian shocks. We prove that in these models the Wold innovations are martingale difference if and only if the model is correctly specified. We propose a test based on a generalized spectral density to check for martingale difference property of the Wold innovations. Our approach does not require to identify and estimate the non-causal models. No specific estimation method is required, and the test has the appealing nuisance parameter free property. The test statistic uses all lags in the sample andit has a convenient asymptotic standard normal distribution under the null hypothesis. A Monte Carlo study is conducted to examine the finite-sample performance of our test.

Suggested Citation

  • Mehdi Hamidi Sahneh, 2015. "Testing for Noncausal Vector Autoregressive Representation," Proceedings of Economics and Finance Conferences 2204921, International Institute of Social and Economic Sciences.
    • Handle: RePEc:sek:iefpro:2204921
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    References listed on IDEAS

    as
    1. Yongmiao Hong & Yoon-Jin Lee, 2005. "Generalized Spectral Tests for Conditional Mean Models in Time Series with Conditional Heteroscedasticity of Unknown Form," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(2), pages 499-541.
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    8. Hamidi Sahneh, Mehdi, 2015. "Are the shocks obtained from SVAR fundamental?," MPRA Paper 65126, University Library of Munich, Germany.
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    More about this item

    Keywords

    Explosive Bubble; Identification; Non-causal Process; Vector Autoregressive.;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General

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