Time Series Data with both Daily and Monthly Variables

Dear all,

I have daily data on how many people entered a certain shopping center, and the weather on that day (temperature). I wish to find out if there is a relation between the weather and the number of people who entered the shopping center.

In addition, I have covariates such as the average income in that region.

The problem is, the covariates, such as mean income, are monthly, not daily. So for my main dependent and independent variables, I have a daily time series, while the covariates are monthly.

How should I handle this situation ?

I thought of several options, not sure which is best:

1. Aggregate the daily variables using means, to make them monthly - I will lose information
2. Make the monthly data daily, i.e., for each day in this month, the income will be the same. This will lead to a model with random effect, won't it ?

How would you handle this problem and which model would you use ? (regression, time series, mixed model)

Thank you in advance !