Error using resol

Too many output arguments.

Error in RBC_q1.driver (line 981)

[dr,~,M,~,oo] = resol(0,M_,options_,oo_);

Error in dynare (line 278)

evalin(‘base’,[fname ‘.driver’]);

Hi I am getting above error in relation to resol function in dynare 5.4 while trying to replicate codes which could have use dynare version 4.5 or 4.6. Please help me fixing this error. Thanks

You need to use

```
[dr, ~, M, oo]= resol(0,M_,options_,oo_);
```

Thank you Dr. Pfeifer, resol function worked but still I have other issues with Smult_ and evalin given below.

Error in simult_ (line 37)

iter = size(ex_,1);

Error in RBC_q1.driver (line 986)

y0 = simult_(oo.dr.ys,dr,ee,1)';

Error in dynare (line 278)

evalin(‘base’,[fname ‘.driver’]);

Is it due to dynare version difference?

Hi I am not able to upload mod file. below is the link of codes from the paper!

It should now be

```
y0=simult_(M_,options_,oo.dr.ys,dr,ee,1)';
```

Thank you so much. simult_ function is fixed. still am getting this

Error in dynare (line 278)

evalin(‘base’,[fname ‘.driver’]);

**and new error below:**

Error using eval

Argument must be a text scalar.

Error in RBC_q1.driver (line 1004)

eval([deblank(M_.endo_names(i1,:)) '*ss = ’ num2str(oo*.dr.ys(i1)) ‘;’]) ;

Sorry couldn’t upload the codes here but have given links of the codes from paper by Gallic & Vermandel below:

Thank you so much!

Then you need to explain which codes you are trying to run and what you already changed.

Hello!

thank you. I have changed only only resol and simul_ function based on your comments in mod file of RBC_q1, this is main file.

If I am not wrong, is it due to due to version change? As we fix one problem, new errors turn up. Since I am using dynare 5.4 against initial version used by author is around dynare 4.5

Try

RBC_q1.mod (21.1 KB)

climate_IRF.m (2.2 KB)

Great!.. Thank you so much. It is working now.

Dear Professor Pfeifer,

Given in your guidebook, is it correct to equate my log difference observed variable yt to model variables in following way given that model is not log-linear:

yt_obs=log(yt/yt-1)+ut…where ut used as one of the parameter values calculated from the data as mean of log of trend of yt over yt-1.

Thank you in advance!

Yes, but most of the time it is preferable to work with demeaned growth rates and not have a constant in the observation equation.

Thank you so much Professor. I truly appreciate your help.

Dear Professor Pfeifer,

Why it is taking quite long time or not at all completing my estimation when i use ‘moments_varendo’ in the estimation command and displaying message given below.

Estimation::compute_moments_varendo: I’m computing endogenous moments (this may take a while)

I use this estimation command for mode finding.

estimation(datafile=‘data_file.m’, mh_replic=100000, mode_file=model_mode_file,mode_compute=6,moments_varendo)

Thank you

Particularly in large models this is a very time intensive step.

Thank you. Is there simplest way out to get variance decomposition using ‘moments_varendo’ in estimation command.

Thanks