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I am making a model (multiple regression) that predicts credit growth. Many of the independent variables are leading indicators and should therefore be lagged. How do I choose the optimal number of lags for my independent variables to explain credit growth?

Thank you.

user58710
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  • A cross-correlation analysis will help you to decide which lags to include. Related posts [here](http://stats.stackexchange.com/questions/109122) and [here](http://stats.stackexchange.com/questions/108876/). A more detailed description of the idea [here](https://onlinecourses.science.psu.edu/stat510/node/75). Another related [post](http://stats.stackexchange.com/questions/109152/) gives an example of the interpretation of the cross-correlation function. Some technical details for the implementation of this approach are discussed in this [post](http://stats.stackexchange.com/questions/109024/). – javlacalle Oct 17 '14 at 15:21

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