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Estimation of MIDAS Regressions with Errors-in-the-Variables

Author

Listed:
  • Sukhbir Kaur
  • Sukhbir Singh
  • Kanchan Jain
  • Pooja Soni

Abstract

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.

Suggested Citation

  • Sukhbir Kaur & Sukhbir Singh & Kanchan Jain & Pooja Soni, 2026. "Estimation of MIDAS Regressions with Errors-in-the-Variables," Papers 2604.23469, arXiv.org.
    • Handle: RePEc:arx:papers:2604.23469
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    File URL: http://arxiv.org/pdf/2604.23469
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