While technically possible webscraping or numerical analysis in Stata is hell - if you need that for your work don’t use it. Also the offer of time series models is quite low and programming your own is painful.

For example Stata can’t handle if you have quarters that are expressed in date format it will think you have gaps in your time series and won’t let you run basic time series commands until you create new time series variable. If you look for easy to use program for time series analysis it would be EViews. Stata is clunky with time series analysis. You will be routinely forced to run for example panel LR heteroskedasticity test on random subsamples even with the most expensive edition.Ĭreating beautiful graphics in Stata is nearly impossible - now don’t get me wrong you can make some decent graphics in Stata but it pales in contrast to what you can do with Python or R. Stata has some serious limitations on matrix sixes even in the most expensive edition the max mat size is 11000 which is serious limit when you work with panel data and have to run some iterative model with large number of variables. Stata is a program not a language so if you want to create a new complex function you need to separately get and learn Mata (statas programming language). If you can get it for free from uni then you probably don’t care about that but still it’s something to keep in mind. Stata is not a freeware and i don’t think that the price tag is justified given that it’s inferior product compared to free ware programs like R and Python. To be honest I don’t like stata for several reasons: When it comes to Stata I use it only for a educational purposes (I teach econometric tutorials at university). I always recommend to people around me to learn both Python and R - the difference between them is not that big and with R you don’t really need to invest heavily into programming skills but just basics and then use packages.Īlso, Jupyter Notebooks that can accommodate both R and Python make using both of them easier.

Also, I prefer to use Python when I need to set up my own program as programming in Python is more natural (if that makes any sense) than in R, unless the program can be build easily from ready made functions from various packages. However, Python is far superior for web-scraping, numerical analysis and sentiment text analysis (although R has some good packages for that as well). I find also producing nice standard statistics graphics with R easier (but for maps I prefer Python). For that reason for most econometric analysis I usually default to R. Python can do everything that R can do and R can do everything that Python does, but I must say R is superior to Python when it comes to the packages.

Speed compare stata 14 vs 15