Impossible to find steady state in Ireland 2003

Dear professor,

I’m trying to find a steady state for Ireland 2003 model, however I get the following message:

“error: Impossible to find the steady state (the sum of square residuals of the static equations i s 29704268567552244.0000). Either the model doesn’t have a steady state, there are an infinity of steady states, or the guess values are too far from the solution”

Equation no. 8 has a bit larger sum of square residuals. I tried changing the state state values for variables in that equation, however, I can only decrease that sum of residuals by increasing other one.

If I don’t do exp(var) substitution, Dynare says that Blanchard-Kahn conditions aren’t met.

Many thanks

Model4.mod (1.9 KB)

  1. Only do the exp()-substitution once the model works.
  2. exp()-substitution cannot alter the BK-conditions. Therefore, check your timing. For example, the timing of capital in the production function is wrong.

Now the model with adjusted timing and in the non-exp form still says:

“error: Blanchard & Kahn conditions are not satisfied: indeterminacy.”

Is it possible that there is a problem with the notation? In the equations, I have the same variable in both steady-state form and in the form of relative deviations from the steady-state. For the latter I use normal variables x, y, z etc. and for the former I introduce new parameters with the values determined in the beginning.

I’m attaching the new model.

Model.mod (1.6 KB)

Hello again and thanks for reading my post to anyone in this community. I have corrected the time periods in the model equations, dropped exp(var) form and substituted the variables in the steady state form with the operator steady_state(var). Using this model in Dynare, I obtain the message:

error: Impossible to find the steady state (the sum of square residuals of the static equations is 188395631132217704448.0000). Either the model doesn’t have a steady state, there are an infinity of steady states, or the guess values are too far from the solution

Any suggestion is welcome.

Model.mod (1.7 KB)

You have various variables that must not be 0 in steady state. Thus, you need to set explicit initial values.


is missing the ln on the right.

Hello, I have set initial values for variables, according to the rule I describe below. I get the error message

“error: The steady state has NaNs or Inf.”

My sample includes data for Slovenia, Austria and Italy in 1991-2019. All estimates are on the annual basis.

x, a, v = 1, x is a shock to marginal efficiency of investment, a is IS shock and e is a money demand shock, values are assumed by Röhe (2012).
z, v = 0, z is a technological shock and v is a monetary policy shock. Values are assumed by Röhe (2012).
y = 26933 is the GDP p.c., average of the sample data for 3 countries in 28 years,
k=684000 is households’ capital supply, the data is average firm’s debt to depositary institutions for Slovenia 1991-2019
in=1946.8 are goods that are purchased by households and not consumed or investment, the data is the sample average for saving as a product of salary and savings rate
c=12567.3 is the consumption, the estimate is the sample average
d=2 is the nominal dividend, the estimate is average yield at DAX in 2020
m=735.1 is money brought from previous time period, the estimate is the sample average for money aggregate M3
w=14637.4 is the nominal wage, the estimate is the sample average
h=1834 is the number of hours worked, the estimate is average for Slovenia 1991-2019
r =8.8 is the gross nominal interest rate between time periods, the esitmate is the sample average
q=0.09 is the nominal rental rate for capital, the estimate is for the US in 2020, computed as sum of the equity risk premium (6.0 %) and the reaffirmed normalized risk-free rate (3.0 %)
n=14.7 is the GDP per hours worked (y/h)
*tau=0.0068 is the M3 growth rate, the estimate 0.68 % is the sample average
lambd=-0.41 is the marginal utility of additional euro of profits, estimated with the marginal utility of income, this estimate is for the US in 1991-1992
*ksi=0 this variable has no explicit meaning in Röhe (2012), it’s from firms’ Lagrangian optimization, the estimate I left 0
pi=79.1 is the inflation rate, the estimate is the sample average Model.mod (1.9 KB)

You cannot simply plug in data from the real world. That would require an appropriate scaling of most variables, e.g. via a productivity factor.