In order to promote scientific research reproducibility I share in this page the codes and (treated) datasets used for my research work. In general, I prefer free software and languages (R, Python, Julia) over proprietary one (Matlab, Stata).
Moreover, additional material might be accessible at this GitHub repository. It hosts the main script I use to gather, harmonise and update data. The script requires a working installation of R, it will install required packages upon the first execution.
In general, GitHub is a fantastic place to share programs and routines. Among the most interesting project is QuantEcon, led by T. Sargent and J. Stachurski: it is massive set of lectures on (mainly) macroeconomics illustrated with codes and notebooks in Python and Julia.
External code repositories:
Chris Sims' website for basically everything in macro
Ambrogio Cesa-Bianchi's VARs toolbox, gets you hit the ground running
Fabio Canova's material for his classes at EUI
John Cochrane's list of works includes used programs
Nick Huntington-Klein maintains a wonderful open repo for data related tasks from manipulation to regression