"/home/jrodriguez/NH_HC/results/model_v2/aux_model/moments_vector.csv"
).values
#This is the var cov matrix of aux estimates
var_cov = pd.read_csv(
"/home/jrodriguez/NH_HC/results/model_v2/aux_model/var_cov.csv").values
#The W matrix in Wald metric
#Using diagonal of Var-Cov matrix of simulated moments
#w_matrix = np.linalg.inv(var_cov)
w_matrix = np.zeros((var_cov.shape[0], var_cov.shape[0]))
for i in range(var_cov.shape[0]):
w_matrix[i, i] = var_cov[i, i]**(-1)
#Creating a grid for the emax computation
dict_grid = gridemax.grid(800)
#For montercarlo integration
D = 25
#For II procedure
M = 10
#How many hours is part- and full-time work
hours_p = 15
hours_f = 40
#Indicate if model includes a work requirement (wr),
#and child care subsidy (cs) and a wage subsidy (ws)
wr = 1
cs = 1
###Auxiliary estimates###
moments_vector = pd.read_csv(
"/home/jrodriguez/NH_HC/results/model_v2/aux_model/moments_vector.csv"
).values
#This is the var cov matrix of aux estimates
var_cov = pd.read_csv(
"/home/jrodriguez/NH_HC/results/model_v2/aux_model/var_cov.csv").values
#The vector of aux standard errors
#Using diagonal of Var-Cov matrix of simulated moments
se_vector = np.sqrt(np.diagonal(var_cov))
#Creating a grid for the emax computation
dict_grid = gridemax.grid()
#For montercarlo integration
D = 50
#Number of samples to produce
M = 1000
#How many hours is part- and full-time work
hours_p = 15
hours_f = 40
#Indicate if model includes a work requirement (wr),
#and child care subsidy (cs) and a wage subsidy (ws)
wr = 1
cs = 1
).values
#This is the var cov matrix of aux estimates
var_cov = pd.read_csv(
"/home/jrodriguez/NH_HC/results/model_v2/aux_model/var_cov.csv").values
#The W matrix in Wald metric
#Using inverse of diagonal of Var-Cov matrix of simulated moments
w_matrix = np.zeros((var_cov.shape[0], var_cov.shape[0]))
for i in range(var_cov.shape[0]):
w_matrix[i, i] = var_cov[i, i]**(-1)
#w_matrix = np.linalg.inv(var_cov)
#Creating a grid for the emax computation
dict_grid = gridemax.grid(500)
#For montercarlo integration
D = 25
#Number of samples to produce
M = 10
#How many hours is part- and full-time work
hours_p = 15
hours_f = 40
#Indicate if model includes a work requirement (wr),
#and child care subsidy (cs) and a wage subsidy (ws)
wr = 1
cs = 1
