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Forecasting with Julia

Author

Listed:
  • Marco Del Negro
  • Marc Giannoni
  • Abhi Gupta
  • Pearl Li
  • Erica Moszkowski

Abstract

A little more than a year ago, in this post, we announced DSGE.jl?a package for working with dynamic stochastic general equilibrium (DSGE) models using Julia, the open-source computing language. At that time, DSGE.jl contained only the code required to specify, solve, and estimate such models using Bayesian methods. Now, we have extended the package to provide the additional code needed to produce economic forecasts, counterfactual simulations, and inference on unobservable variables, such as the natural rate of interest or the output gap. The old, pre-Julia version of the code, which was written in MATLAB and is posted here on Github, a public repository hosting service, also performed some of these functions, but not quite as fast.

Suggested Citation

  • Marco Del Negro & Marc Giannoni & Abhi Gupta & Pearl Li & Erica Moszkowski, 2017. "Forecasting with Julia," Liberty Street Economics 20170508, Federal Reserve Bank of New York.
  • Handle: RePEc:fip:fednls:87192
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    More about this item

    Keywords

    State Space Models; DSGE; Julia;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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