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Detecting irrelevant variables in possible proxies for the latent factors in macroeconomics and finance

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  • Wu, Jianhong

Abstract

This paper focuses on evaluating the observed and latent factors in macroeconomics and finance from a new angle. The null hypothesis is that some observed time series is not correlated with each latent factor. This issue is interesting since it can help us to detect irrelevant variables in possible proxies for the latent factors in the macroeconomics and finance field. In this sense, this paper can be seen as the preliminary work of Bai and Ng (2006b) or one of its supplements. Under the null hypothesis and some mild assumptions, the proposed statistic is asymptotically chi-squared distributed. Monte Carlo simulation study shows that the new method has desired performance. A real example is analyzed for illustration.

Suggested Citation

  • Wu, Jianhong, 2019. "Detecting irrelevant variables in possible proxies for the latent factors in macroeconomics and finance," Economics Letters, Elsevier, vol. 176(C), pages 60-63.
    • Handle: RePEc:eee:ecolet:v:176:y:2019:i:c:p:60-63
    DOI: 10.1016/j.econlet.2018.12.012
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    References listed on IDEAS

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    More about this item

    Keywords

    Factor analysis; Large dimensional panel; Latent factor; Macroeconomics and finance;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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