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Autori principali: Kaur, Sukhbir, Singh, Sukhbir, Jain, Kanchan, Soni, Pooja
Natura: Preprint
Pubblicazione: 2026
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Accesso online:https://arxiv.org/abs/2604.23469
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author Kaur, Sukhbir
Singh, Sukhbir
Jain, Kanchan
Soni, Pooja
author_facet Kaur, Sukhbir
Singh, Sukhbir
Jain, Kanchan
Soni, Pooja
contents In this paper, a Mixed Data Sampling (MIDAS) model is studied when both low and high frequency variables are contaminated with measurement error. It is shown that the profile likelihood estimator becomes inconsistent in the presence of measurement error. Using the corrected score approach along with profile likelihood approach, a consistent estimator for parameters of MIDAS Measurement Error model is proposed. Small and large sample properties of the estimator are examined by performing a monte carlo simulation study and considering the effect of sample size, number of lags and profiling parameter.
format Preprint
id arxiv_https___arxiv_org_abs_2604_23469
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Estimation of MIDAS Regressions with Errors-in-the-Variables
Kaur, Sukhbir
Singh, Sukhbir
Jain, Kanchan
Soni, Pooja
Methodology
Econometrics
In this paper, a Mixed Data Sampling (MIDAS) model is studied when both low and high frequency variables are contaminated with measurement error. It is shown that the profile likelihood estimator becomes inconsistent in the presence of measurement error. Using the corrected score approach along with profile likelihood approach, a consistent estimator for parameters of MIDAS Measurement Error model is proposed. Small and large sample properties of the estimator are examined by performing a monte carlo simulation study and considering the effect of sample size, number of lags and profiling parameter.
title Estimation of MIDAS Regressions with Errors-in-the-Variables
topic Methodology
Econometrics
url https://arxiv.org/abs/2604.23469