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Consistent Specification Test of the Quantile Autoregression

Anthoulla Phella

arXiv 8 Oct 2020 · Econometrics · publishedENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (2020)

arXiv:2010.03898 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper proposes a test for the joint hypothesis of correct dynamic specification and no omitted latent factors for the Quantile Autoregression. If the composite null is rejected we proceed to disentangle the cause of rejection, i.e., dynamic misspecification or an omitted variable. We establish the asymptotic distribution of the test statistics under fairly weak conditions and show that factor estimation error is negligible. A Monte Carlo study shows that the suggested tests have good finite sample properties. Finally, we undertake an empirical illustration of modelling GDP growth and CPI inflation in the United Kingdom, where we find evidence that factor augmented models are correctly specified in contrast with their non-augmented counterparts when it comes to GDP growth, while also exploring the asymmetric behaviour of the growth and inflation distributions.

Citation extraction

29
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56
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29
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appendix boundary found by appendix_titled_section at “Appendix A” · 53% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Escanciano, Juan Carlos, & Velasco, Carlos (2010) Specification tests of parametric dynamic conditional quantiles0.8558462%
2Bierens, Herman J (1990) A Consistent Conditional Moment Test of Functional Form0.84333100%
3Stock, James H, & Watson, Mark W (2002) Forecasting using principal components from a large number of predictors0.84333100%
4Adrian, Tobias, Boyarchenko, Nina, & Giannone, Domenico (2019) Vulnerable Growth0.81142100%
5Koenker, Roger, & Xiao, Zhijie (2006) Quantile autoregression0.73732100%
6Bai, Jushan, & Ng, Serena (2002) Determining the Number of Factors in Approximate Factor Models0.6936333%
7Angeloni, Ignazio, Aucremanne, Luc, Ehrmann, Michael, Galí, Jordi, L… (2006) New evidence on inflation persistence and price stickiness in the euro area: implications for macro modeling0.64422100%
8Bernanke, Ben S., Boivin, Jean, & Eliasz, Piotr (2005) Measuring the effects of monetary policy: a factor-augmented vector autoregressive (FAVAR) approach0.64422100%
9Bierens, Herman J (1982) Consistent model specification tests0.64422100%
10Corradi, Valentina, Fernandez, Andres, & Swanson, Norman R (2009) Information in the Revision Process of Real-Time Datasets0.64422100%

Showing the top 10 of 29 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Forecasting With Factor-Augmented Quantile Autoregressions: A Model Averaging Approach0.73732