Cool, despite Julia replacing matlab here, it looks like the biggest loser to Julia's rise might be Octave.<p>Matlab will always have its proponents, that will use it no matter what, but if Julia keeps encroaching on this territory, I'm not sure where that leaves Ocatve.<p>To the model discussed in this paper, check out this series of blog posts for more information:<p><a href="http://libertystreeteconomics.newyorkfed.org/2014/09/forecasting-with-the-frbny-dsge-model.html#.VRnNb1bdIeE" rel="nofollow">http://libertystreeteconomics.newyorkfed.org/2014/09/forecas...</a><p>Essentially the model is a work in progress that is continually updated each quarter. It attempts to model at a macro economic level, the interactions between Banks, consumers, Companies, Governments and households.<p>Once the model has solved for the general equilibrium of how those 5 agencies interact the model can then be used to "shock" a particular factor, such as interest rates, to determine how this might affect the interaction between these agents.<p>Its a fairly well respected model, and the fact that the US is one of the few countries to release such a large amount of financial data is one reason why the US is still a leader in economic theory.
I'm always found Julia performance claims [1] to be misleading in comparison to LuaJit [2].<p>Because Julia claims to be much faster than LuaJIT, yet continually - people find that LuaJIT (not Julia) is much faster in real world test [3].<p>Does anyone else have experience in Julia vs LuaJIT?<p>[1] <a href="http://julialang.org/#high-performance-jit-compiler" rel="nofollow">http://julialang.org/#high-performance-jit-compiler</a><p>[2] <a href="http://luajit.org/performance_x86.html" rel="nofollow">http://luajit.org/performance_x86.html</a><p>[3] <a href="http://bayesanalytic.com/lua_jit_faster_than_julia_stock_prediction/" rel="nofollow">http://bayesanalytic.com/lua_jit_faster_than_julia_stock_pre...</a>
Even more interesting is the document on Github with technical details about the port:<p><a href="https://github.com/FRBNY-DSGE/DSGE.jl/blob/master/doc/MatlabToJuliaTransition.md" rel="nofollow">https://github.com/FRBNY-DSGE/DSGE.jl/blob/master/doc/Matlab...</a>
The real news here is not the move to Julia (although that is likely to be the reason for most of the attention). The important thing is the move to open - an open language, movement to Github, nice explanation of the details.
For those of you in this field...how influential is the NYFed trying out (and apparently being satisfied with) Julia to other government agencies, computational economists, and/or academics? Is it "OS X is Unix/BSD-based" influential, or "Whitehouse.gov uses Drupal [1]" influential?<p>[1] <a href="http://buytaert.net/whitehouse-gov-using-drupal" rel="nofollow">http://buytaert.net/whitehouse-gov-using-drupal</a>
How's the probabilistic programming use case in Julia now?<p>I don't like Python as a language that much (I prefer Lisps or MLs), but I reckon its libraries are fantastic: PyMC, Theano, NumPy... And loads of general-purpose stuff.
I like the use of the Greek alphabet in the code base.<p>Examples<p><a href="https://github.com/FRBNY-DSGE/DSGE.jl/blob/master/src/solve/gensys.jl#L92" rel="nofollow">https://github.com/FRBNY-DSGE/DSGE.jl/blob/master/src/solve/...</a><p><a href="https://github.com/FRBNY-DSGE/DSGE.jl/blob/master/src/solve/gensys.jl#L170" rel="nofollow">https://github.com/FRBNY-DSGE/DSGE.jl/blob/master/src/solve/...</a>
I've never written a line of Julia in my life, and I'm usually somewhat adept at figuring out what is going on when I read the source of unfamiliar languages. But I'm am having one helluva time trying to differentiate comments and code.<p>EDIT: downvotes? wtf?