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The MIDAS Touch: Mixed Data Sampling Regression Models

Eric Ghysels (), Pedro Santa-Clara and Rossen Valkanov

CIRANO Working Papers from CIRANO

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 finance. Nous introduisons des modèles de régression MIDAS (Mixed Data Sampling). Ce sont des modèles de régression avec des séries temporelles échantillonées à différentes fréquences. Nous analysons les liens avec les modèles à retards échelonnés.

Keywords: distributed log models; aliasing; discretization bias; retards échelonnés; aliasing; biais de discrétisation (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-fin
Date: 2004-05-01
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Persistent link: https://EconPapers.repec.org/RePEc:cir:cirwor:2004s-20

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