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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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    File URL: https://iises.net/proceedings/4th-economics-finance-conference-london/table-of-content/detail?cid=22&iid=019&rid=4921
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    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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