Error using beta_specification

Estimation ML/Bayesian estimation
1

Dear all,
I am building a DSGE model about macroeconomic policy however,
Error using beta_specification (line 63)
Beta prior (for beta). Given the declared prior expectation, prior lower and upper bounds, the prior std. has to be
smaller than 0.044677.

Error in set_prior (line 171)
[bayestopt_.p6(k(i)), bayestopt_.p7(k(i))] = beta_specification(bayestopt_.p1(k(i)), bayestopt_.p2(k(i))^2,
bayestopt_.p3(k(i)), bayestopt_.p4(k(i)), bayestopt_.name{k(i)});

Error in dynare_estimation_init (line 152)
[xparam1,estim_params_,bayestopt_,lb,ub,M_] = set_prior(estim_params_,M_,options_);

Error in dynare_estimation_1 (line 115)
[dataset_, dataset_info, xparam1, hh, M_, options_, oo_, estim_params_, bayestopt_, bounds] = …

Error in dynare_estimation (line 105)
dynare_estimation_1(var_list,dname);

Error in Untitled (line 989)
oo_recursive_=dynare_estimation(var_list_);

Error in dynare (line 223)
evalin(‘base’,fname) ;Untitled.mod (10.9 KB)
labor_data.m (26.7 KB)

2

Looks like some of your beta priors, for example,
BETA_PDF, 0.998, 0.1;
do not make sense to dynare.
Hence, the comment
''Given the declared prior expectation, prior lower and upper bounds, the prior std. has to be

smaller than 0.044677.’

Reuben

3

Indeed. The beta distribution is bounded between 0 and 1. Given the location of the mean almost at the upper bound, you cannot move sufficient mass to the left to achieve the desired standard deviation while still keeping the mean at the upper bound. Thus, either move the mean or reduce the standard deviation.

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