Cointegration in a MIDAS Regression
研究了混频数据采样（MIDAS）协整模型，从高频自回归分布滞后模型推导低频因变量的表示，提出协整检验并推导渐近零分布，通过蒙特卡洛模拟检验检验效果，并以美国年度耐用品消费与季度GDP为例说明。
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.