## Issue

I’m trying to run the code below but I get a `NameError`

when running the code. The issue is that `q`

seems not to be defined but this should not be true.

```
class SimpleNamespace():
pass
#Question 1
#i)
#Defining the parameters using SimpleNameSpace. par = Parameters
par = SimpleNamespace()
par.y = 1 #assets
par.p = 0.2 #probability
par.theta = -2 #elasticity
#Defining utility function for agent
def utility(z,par):
return (z**(1+par.theta))/(1+par.theta)
#Defining premium
def premium(q,par):
return par.p*q
#Defining expected value
#Note that z_1, z_2 represents first and second part of the objective function - just in a compressed version
def exp_value (i,q,par):
z_1 = par.y-i+q-premium(q,par)
z_2 = par.y-premium(q,par)
return par.p*utility(z_1,par)+(1-par.p)*utility(z_2,par)
def opt_q(i,q,par):
obj = lambda q: -exp_value(i,q,par) #defining the objective function
solution = optimize.minimize_scalar(obj, bounds=(0,0.9), method="bounded") #bounded solution within [0.01, 0.9]
q = solution.x
return q
for i in np.linspace(0.01,0.9,num=100):
res = opt_q(i,q,par)
print(res)
```

## Solution

You are getting the `NameError`

because you are not passing the `q`

to `opt_q`

in the last for-loop. Since it is already defined inside `opt_q`

just remove `q`

from its arguments and don’t pass it in the for-loop as well as follows:

```
def opt_q(i,par):
obj = lambda q: -exp_value(i,q,par) #defining the objective function
solution = minimize_scalar(obj, bounds=(0,0.9), method="bounded") #bounded solution within [0.01, 0.9]
q = solution.x
return q
for i in np.linspace(0.01,0.9,num=100):
res = opt_q(i,par)
print(res)
```

This resolves your issue.

Answered By – Muhammad Mohsin Khan

Answer Checked By – Mary Flores (BugsFixing Volunteer)