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I highly recommend this econometrics text for getting started with statistics: https://www.amazon.com/Principles-Econometrics-5th-Carter-Hi...

For modeling I found Wooldridge's panel and cross-section data book very useful: https://www.amazon.com/Econometric-Analysis-Cross-Section-Pa...

Greene is a really useful reference text: https://www.amazon.com/Econometric-Analysis-8th-William-Gree...

For advanced stats theory, I recommend Casella and Berger https://www.amazon.com/Statistical-Inference-George-Casella/...

Hope that helps!

The more specific a model can be made to the problem at hand, the better it'll perform. Supervised ML models are great starting / baseline models.




I second Wooldridge. Greene I found to be much denser without providing much additional insight. It is a popular MS/PhD entry text though.

I add any of Ken Train's work to this mix, especially on estimating discrete choice theory.




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