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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.

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  • $\begingroup$ A cross-correlation analysis will help you to decide which lags to include. Related posts here and here. A more detailed description of the idea here. Another related post 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. $\endgroup$
    – javlacalle
    Oct 17, 2014 at 15:21

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