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- Description of the replication files for "Fiscal Consolidation and Public Wages"
- by Juin-Jen Chang, Hsieh-Yu Lin, Nora Traum, and Shu-Chun S. Yang
- Journal of Money, Credit and Banking 
- Updated: June 14, 2019
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To produce the results based on the estimated models (sections 3-5 of the main paper):

1)	Run the file mainscript.m in the EstimatedModel folder.  This file will find the posterior mode, perform the Metropolis-Hastings algorithm, and save and report basic statistics about posterior draws.  Output from this file is used to construct table 2 of the main paper.


The above code calls a series of functions that are contained within the same EstimatedModel folder:

-	model: This code solves for the model steady-state and sets up the log-linearized model in the matrix system for Chris Sims, gensys program to solve the model.
-	declare_variable:  This code creates indices for all variables in the model.
-	prior: This code takes draws from the priors for parameters used in the model.
-       log_beta_pdf and log_gamma_pdf: These codes compute the parameters of a beta and gamma density respectively for a particular mean and standard deviation.
-	gensys, qzdiv, qzswitch: These codes solve the model. The files are from Sims (2002), solving Linear Rational Expectations Models, Computational Economics, and are available for public download at: http://sims.princeton.edu/yftp/gensys
-       MHalgorithm: This code performs Metropolis Hastings algorithm for the model.
-       get_posterior_multipliers_wgcut:  This code calculates present value multipliers at the posterior mean or for the entire set of posterior draws. Note that this file constructs results for table 3 of in the main paper.
-       get_posterior_irf_wgcut: This code computes impulse responses for the baseline model. Note that this code constructs results for figures 3-4 in the main paper.

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The folder Data contains an excel file with all the original, raw data series downloaded from the BEA, BLS, Federal Reserve Board and Federal Reserve Bank of St. Louis.  The excel file includes all data manipulations to construct the observable series for estimation.  Columns AI-AW contain the final data series that are contained in the data.mat file loaded into Matlab during estimation of the model (see folder mat_files inside EstimatedModel folder).  A description of these data series and the data manipulations is given in the Online Appendix of the paper, as well as contained within a data_readme file within this Data folder.  

