SIMULATION after Estimation Flawed

[peisenha]

There is not role for randomenss?

` def simulate_outcomes_estimation(init_dict, X, Z): """The function simulates the outcome Y, the resulting treatment dummy."""

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coeffs_untreated = init_dict['UNTREATED']['all']
coeffs_treated = init_dict['TREATED']['all']
coeffs_cost = init_dict['COST']['all']

# Calculate potential outcomes and costs
Y_1 = np.dot(coeffs_treated, X.T)
Y_0 = np.dot(coeffs_untreated, X.T)
C = np.dot(coeffs_cost, Z.T)

# Calculate expected benefit and the resulting treatment dummy
D = np.array((Y_1 - Y_0 - C > 0).astype(int))

# Observed outcomes
Y = D * Y_1 + (1 - D) * Y_0

return Y, D, Y_1, Y_0

`

[peisenha]

• Simulated sample after estimation has same size as estimation sample
• use obserables of estimation sample
• integration tests comparing estimation and simulation sample at starting values, need to be identical