Overview
The MATLAB code in this package constructs Monte Carlo experiments presented in the paper. Third-party software Dynare(http://www.dynare.org) is executed inside. Three folders contain the main program, the functions, and dataset needed for replication of tables and diagrams.

Software Used
	MATLAB (R2020b and R2022a)
	Dynare 4.6.2
	Dynare 5.1
	Dynare executes inside MATLAB

Appendix B
Part B.1-Small-scale New Keynesian model
	-All files used for this part of simulation study are saved in folder "small model".
	-Model citation: Guerron-Quintana, P., A. Inoue, and L. Kilian (2017). Impulse response matching estimators for dsge models. Journal of Econometrics 196 (1), 144 – 155.
	-Data Generation: 'data.m' executing 'dgp.mod' and 'dgp_MIS.mod'.
	-Dataset Used: 'sampledataT100.mat', 'sampledataT232.mat', 'MIS_t4_sampledataT232', and 'MIS_t20_sampledataT232'.
	-Programs in 'irfplot.m' generates Figure 1.
	-Programs in 'SMAS_opt.m' generates Table 1-4 in this section. Estimation results are saved in 
		'T232p2H20_opt', 'T232p4H20_opt', 'T232p6H20_opt' (Table 1), 
		'T232p4H80_opt', 'T232p6H80_opt' (Table 2), 
		'T232p2H2_opt', 'T232p2H8_opt'(Table 3), 
		'T100p2H20_opt', 'T100p2H80_opt'(Table 4),
		'T232p2H20_opt_MIS_t4', 'T232p2H80_opt_MIS_t4',
		'T232p2H20_opt_MIS_t20', and 'T232p2H80_opt_MIS_t20' (Table 5).
		Partial results are saved in 'T232p2H80_opt.xlsx' (Table 2). 
	-Dynare programs called: 'dgptest.mod'
	-Programs in 'histcompare.m' generates Figure 2 and Figure 3.

Part B.2-Medium-scale New Keynesian model
	-All files used for this part of simulation study are saved in folder "medium model".
	-Model citation: Smets, F. and F.Wouters (2007). Shocks and frictions in us business cycles: A bayesian 		dsge approach. American Economic Review 97 (3), 586–606.
	-Data Generation: 'syndata.m' executing 'sw_dgp'.
	-Data Used: 'sampledata_sub_236.mat', 'sampledata_sub_236_2.mat' and 'sampledata_sub_944.mat'.
	-Programs in 'sw_p2_single_opt.m' generates Table 7 in this section.
	-Programs in 'sw_2param_opt.m' generates Table 8 in this section.
	-Partial results are saved in 'single_p2_opt_T236.xlsx', 'single_p2_opt_T944.xlsx' (Table 7), and 'two 		param_opt.xlsx' (Table 8).

Part B.3-Infeasible New Keynesian model
	-All files used for this part of simulation study are saved in folder "baseline model".
	-Model citation: Fernandez-Villaverde, J., J. Rubio-Ramirez, and F. Schorfheide (2016). Solution and 		estimation methods for dsge models. Handbook of Macroeconomics 2, 527–724.
	-Programs in 'baseline_opt.m' generates Table 10 in this section. 
	-Partial estimation results are saved in 'Infeasible SMAS_opt.xlsx' (Table 10).

Supplementary Appendix
Part S.3-Medium-scale New Keynesian model
	-All files used for this part of simulation study are saved in folder "medium model".
	-Model citation: Smets, F. and F.Wouters (2007). Shocks and frictions in us business cycles: A bayesian 		dsge approach. American Economic Review 97 (3), 586–606.
	-Data Generation: 'syndata.m' executing 'sw_dgp' and 'sw_dgp_MIS'.
	-Data Used: 'sampledata_sub_236.mat', 'sampledata_sub_236_2.mat', 'sampledata_sub_236_t4.mat', 
		    'sampledata_sub_236_t20.mat', 'sampledata_sub_944_t4.mat', and 'sampledata_sub_944_t20.mat'.
	-Programs in 'sw_p1_single_opt.m' generates Table 11 in this section.
	 Programs in 'sw_p2_single_opt.m' generates Table 12 in this section.
	-Partial results are saved in 'single_p1_opt_T236.xlsx' (Table 11) 
		    and 'medium NK_student t results.xlsx' (Table 12).
Part S.4-Estimation of the asymptotic variance
	-All files used for this part of simulation study are saved in folder "asympt var".
	-The suggested method explores the finite-sample properties' convergence towards their asymptotic equivalents.
	-Dataset Used: 'sampledataT464.mat'.
	-Programs in 'main.m' generates results depending on estimates from the experiments in Part B.1 (Table 13).

References
	-Stéphane Adjemian, Houtan Bastani, Michel Juillard, Frédéric Karamé, Junior Maih, Ferhat Mihoubi, 		George Perendia, Johannes Pfeifer, Marco Ratto and Sébastien Villemot (2011), “Dynare: Reference 		Manual, Version 4,” Dynare Working Papers, 1, CEPREMAP
	-Mutschler, W. (2018). Higher-order statistics for DSGE models. Econometrics and Statistics 6, 44–56.
	-Dynare programs on Smets and Wouters(2007): 
		Nicola Viegi (http://www.nviegi.net/teaching/master/monmas.htm),
		Johannes Pfeifer (https://github.com/JohannesPfeifer/DSGE_mod/tree/master/Smets_Wouters_2007), 
		and Willi Mutschler (https://github.com/wmutschl/ReplicationDSGEHOS)
	-Matlab code for computing bias-adjusted impulse response confidence intervals for structural VAR models 		with intercept(https://drive.google.com/file/d/1Hdz7oQmmHDFt6bUzF5Rw-ny29VXY3MCe/view).
	-Matlab code for Bertille Antoine, Lynda Khalaf, Maral Kichian & Zhenjiang Lin (2022) Identification-		Robust Inference With Simulation-Based Pseudo-Matching, Journal of Business & Economic 		Statistics, DOI: 10.1080/07350015.2021.2019046