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YADA Examples

 

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YADA is distributed with ten examples that allow you to start playing with DSGE models directly. The examples are given by the models studied by:

1.An and Schorfheide (2007) - link to Econometric Reviews article. The data for this example has been simulated with the model. The model is also available in two dynare model file variants, one already log-linearized and another that requires linearization by dynare. Both cases, as well as full log-linearization is supported by YADA's dynare parser.
2.Lubik and Schorfheide (2007) - link to Journal of Monetary Economics article. The data for this example has also been simulated with the model.
3.Smets and Wouters (2007) - link to American Economic Review article. This example has the actual data from the article.
4.Fagan, Lothian and McNelis (2013) - link to Journal of Applied Econometrics article. The actual data from the article is included.
5.Galí, Smets and Wouters (2012) - link to NBER Macroeconomics Annual article. The euro area version of this model from Smets, Warne and Wouters (2014) is included in the YADA distribution, along with actual data.
6.Del Negro and Schorfheide (2013) - link to Handbook of Economic Forecasting article, along with the actual data.
7.Small-scale version of the Smets and Wouters (2007) model in Del Negro and Schorfheide (2013) - link to Handbook of Economic Forecasting article. Actual US data is included.
8.Herbst and Schorfheide (2016) - link to Frank Schorfheide's homepage. More information about the book is available from Frank Schorfheide's homepage. The YADA-based model is the same as the in An and Schorfheide example, but here it has actual US data available online from FRED at the Federal Reserve Bank of St Louis. The construction of the data is described in Appendix B of the book by Herbst and Schorfheide.
9.Leeper, Plante and Traum (2010) - link to Journal of Econometrics article.
10.Slobodyan and Wouters (2012) - link to American Economic Journal: Macroeconomics article.

It is straightforward to setup these examples in the YADA environment since all input files have already been constructed. A guide for the An and Schorfheide example is provided in the FAQ.

The GUI, or Graphical User Interface, for YADA has three basic objects: menus, a toolbar, and tabs for various settings and options. All the main functions in YADA are hidden below the menu items. Some of the most important functions, such as opening this help file, are also located on the toolbar.

NOTE: The minimum system requirement for running YADA are:

MS-Windows operating system with Matlab version 5.3 or later. For Matlab versions prior to 7, make sure that it is permitted to run the file aimparser.exe, located in the bin directory of YADA.
UNIX or Macintosh OS X with Matlab version 7 or later.

 

Additional Information

If you are looking for the mathematical details behind the computations made by YADA, the first place to look is the document YADA Manual - Computational Details which is distributed with YADA.
If you are looking for details about how to entend YADA, a place to start is Extending YADA - A Guide to The User Interface, The Controls and The Data Structures, which is also distributed with YADA.
YADA has been developed in connection with the New Area-Wide Model (NAWM) project at the ECB. A working paper describing the NAWM (Christoffel, Coenen and Warne, 2008) is available for download from the website of the ECB, a working paper  of the latest version called NAWM II (Coenen, Karadi, Schmidt and Warne, 2018) and a working paper describing forecasting with DSGE models (Christoffel, Coenen and Warne, 2010) are also available for download from the same site.
YADA relies on some external code. In particular, it uses some functions and ideas developed by Mattias Villani. Moreover, it relies on AiM (developed by Anderson and  Moore at the Federal Reserve) to parse and (optionally) to solve the DSGE model. It also includes csminwel (for optimization) and gensys (for solving a DSGE model) by Christopher Sims, as well as code from Stixbox by Anders Holtsberg, from the Lightspeed Toolbox by Tom Minka, from Dynare by Michel Juillard and Stephane Adjemian, from the Kernel Density Estimation Toolbox by Christian Beardah, and kde2d for bivariate kernel density estimation by Zdravko Botev.
One of YADA's model solvers uses the Klein (2000) QZ decomposition based algorithm. The code in YADA has here been inspired by Paul Klein's own solab code. The latter code is available from his website for Matlab as well as for Gauss and Fortran.

 

 


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