I have a set of models I am creating in which the target variable I am forecasting is sampled at a high frequency (daily) but the predictors are all Federal Reserve Macroeconomic variables which are sampled at a low frequency (Monthly at best weekly). What are the best practice approaches for combining mixed frequency data into a model in which the target is sampled at a higher frequency? I am building my forecast model using Python packages.


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