Impossible to find steady state in Ireland 2003

Steady state
#1

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)

#2
  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.
#3

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)

#4

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)

#5

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

ln(x)=rhox*x(-1)+epsilonx;
ln(a)=rhoa*a(-1)+epsilona;
ln(e)=rhoe*e(-1)+epsilone;
ln(z)=rhoz*z(-1)+epsilonz;
ln(v)=rhov*v(-1)+epsilonv;

is missing the ln on the right.

#6

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)

#7

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.