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The MIDAS Touch: Mixed Data Sampling Regression Models

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  • Ghysels, Eric
  • Santa-Clara, Pedro
  • Valkanov, Rossen

Abstract

We introduce Mixed Data Sampling (henceforth MIDAS) regression models. The regressions involve time series data sampled at different frequencies. Technically speaking MIDAS models specify conditional expectations as a distributed lag of regressors recorded at some higher sampling frequencies. We examine the asymptotic properties of MIDAS regression estimation and compare it with traditional distributed lag models. MIDAS regressions have wide applicability in macroeconomics and �nance.

Suggested Citation

  • Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," University of California at Los Angeles, Anderson Graduate School of Management qt9mf223rs, Anderson Graduate School of Management, UCLA.
  • Handle: RePEc:cdl:anderf:qt9mf223rs
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    References listed on IDEAS

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