Regression Models with Variables of Different Frequencies: The Case of a Fixed Frequency Ratio*
研究了如何构建和估计变量观测频率不同的回归模型，通过蒙特卡洛实验和实证例子说明传统固定聚合方法可能不一致且精度较差。
An increasing variety of data frequencies available in economics, finance, etc. gives rise to a question how to build and estimate a regression model with variables observed at different frequencies. In a unifying framework of (m,d)-aggregation we consider various approaches by discussing some potential and limitations. A Monte Carlo experiment and an empirical example illustrate that the traditional fixed aggregation approach, widely used in applied economics, might be inconsistent with data and highly inferior in terms of model precision.