Cointegration in a MIDAS Regression

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Authors: H. Peter Boswijk, Ph.H.B.F. Franses
Cited by: 1
References: 13

Abstract

ABSTRACT Mixed data sampling (MIDAS) cointegration models are used to analyse variables observed at different frequencies. In this paper, we start from an assumed autoregressive distributed lag (ADL) model for high‐frequency observations, and derive the resulting representation when the dependent variable is only observed at a lower frequency. We propose a test for cointegration, exploiting knowledge of the implied moving average process in the MIDAS model, and derive its asymptotic null distribution. We study the size and power of the test using Monte Carlo simulations, and illustrate our method using the US annual durables consumption as a function of quarterly GDP.

Fields of Study & Subjects

Monetary Policy and Economic Impact Italy: Economic History and Contemporary Issues Financial Risk and Volatility Modeling

Publication details

Journal / source
Oxford Bulletin of Economics and Statistics
Publisher
Wiley
Volume
88
Issue
4
Pages
712–725
Publication date
15 April 2026
Language
EN