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.
Chris Sims' website for basically everything in macro
Koop's and Korobilis's websites, mainly for Bayesian VARs
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
Jesus Fernandez-Villaverde curates an open repository for his class on computational methods
Alisdair McKay also shares the material for solving heterogenous-agent models
Ben Moll's site also offers codes and lecture materials