Dear Dynare users,

I’m having a problem in interpreting global sensitivity analysis outputs and Smirnov tests results

I searched for Ratto’s paper (2008) treating the issue, but unfortunately I couldn’t have access to it.

How can I interpret these results ?

Is the p-value is interpreted as being inferior to the significance threshold, and therefore we reject null hypotesis, which is that those parameters’ cdf is similar to acceptable behavior parameters’ cdf ?

how about those driving indeterminacy and instability ?

Thank you

Smirnov statistics in driving acceptable behaviour

delta_2 d-stat = 0.522 p-value = 0.000

rho_inf d-stat = 0.416 p-value = 0.000

Smirnov statistics in driving indeterminacy

alppha d-stat = 0.171 p-value = 0.000

delta_2 d-stat = 0.307 p-value = 0.000

mu d-stat = 0.132 p-value = 0.000

rho_inf d-stat = 0.302 p-value = 0.000

Smirnov statistics in driving instability

alppha d-stat = 0.323 p-value = 0.000

delta_2 d-stat = 0.315 p-value = 0.000

mu d-stat = 0.264 p-value = 0.000

rho_R d-stat = 0.131 p-value = 0.000

rho_inf d-stat = 0.142 p-value = 0.000

Starting bivariate analysis:

Correlation analysis for prior_stable

[alppha,rho_R]: corrcoef = 0.111

[delta_2,rho_inf]: corrcoef = 0.205

Correlation analysis for prior_unacceptable

[alppha,rho_R]: corrcoef = -0.160

[delta_2,rho_inf]: corrcoef = -0.585

[rho_is,rho_rstar]: corrcoef = -0.127

Correlation analysis for prior_indeterm

[alppha,delta_2]: corrcoef = -0.231

[alppha,rho_inf]: corrcoef = 0.196

[delta_2,rho_R]: corrcoef = 0.142

[delta_2,rho_inf]: corrcoef = -0.573

[mu,rho_inf]: corrcoef = -0.161

[rho_R,rho_inf]: corrcoef = -0.347

Correlation analysis for prior_unstable

[alppha,delta_2]: corrcoef = 0.279

[alppha,mu]: corrcoef = -0.357

[alppha,rho_R]: corrcoef = -0.247

[alppha,rho_inf]: corrcoef = -0.406

[delta_2,mu]: corrcoef = -0.426

[delta_2,rho_R]: corrcoef = -0.257

[delta_2,rho_inf]: corrcoef = -0.614

[mu,rho_inf]: corrcoef = 0.422

[rho_R,rho_inf]: corrcoef = 0.507