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CES in TPI
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Jason DeBacker committed Mar 22, 2017
1 parent 62bf77b commit 6284d1e
Showing 1 changed file with 33 additions and 21 deletions.
54 changes: 33 additions & 21 deletions Python/ogusa/TPI.py
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Original file line number Diff line number Diff line change
Expand Up @@ -95,6 +95,7 @@ def create_tpi_params(**sim_params):

tpi_params = [sim_params['J'], sim_params['S'], sim_params['T'], sim_params['BW'],
sim_params['beta'], sim_params['sigma'], sim_params['alpha'],
sim_params['gamma'], sim_params['epsilon'],
sim_params['Z'], sim_params['delta'], sim_params['ltilde'],
sim_params['nu'], sim_params['g_y'], sim_params['g_n_vector'],
sim_params['tau_payroll'], sim_params['tau_bq'], sim_params['rho'], sim_params['omega'], N_tilde,
Expand All @@ -104,7 +105,7 @@ def create_tpi_params(**sim_params):
small_open_params = [sim_params['small_open'], sim_params['tpi_firm_r'], sim_params['tpi_hh_r']]


J, S, T, BW, beta, sigma, alpha, Z, delta, ltilde, nu, g_y,\
J, S, T, BW, beta, sigma, alpha, gamma, epsilon, Z, delta, ltilde, nu, g_y,\
g_n_vector, tau_payroll, tau_bq, rho, omega, N_tilde, lambdas, imm_rates, e, retire, mean_income_data,\
factor, h_wealth, p_wealth, m_wealth, b_ellipse, upsilon, chi_b, chi_n, theta = tpi_params

Expand Down Expand Up @@ -183,7 +184,7 @@ def firstdoughnutring(guesses, r, w, b, BQ, T_H, j, params):
# unpack tuples of parameters
income_tax_params, tpi_params, initial_b = params
analytical_mtrs, etr_params, mtrx_params, mtry_params = income_tax_params
J, S, T, BW, beta, sigma, alpha, Z, delta, ltilde, nu, g_y,\
J, S, T, BW, beta, sigma, alpha, gamma, epsilon, Z, delta, ltilde, nu, g_y,\
g_n_vector, tau_payroll, tau_bq, rho, omega, N_tilde, lambdas, imm_rates, e, retire, mean_income_data,\
factor, h_wealth, p_wealth, m_wealth, b_ellipse, upsilon, chi_b, chi_n, theta = tpi_params

Expand Down Expand Up @@ -260,7 +261,7 @@ def twist_doughnut(guesses, r, w, BQ, T_H, j, s, t, params):

income_tax_params, tpi_params, initial_b = params
analytical_mtrs, etr_params, mtrx_params, mtry_params = income_tax_params
J, S, T, BW, beta, sigma, alpha, Z, delta, ltilde, nu, g_y,\
J, S, T, BW, beta, sigma, alpha, gamma, epsilon, Z, delta, ltilde, nu, g_y,\
g_n_vector, tau_payroll, tau_bq, rho, omega, N_tilde, lambdas, imm_rates, e, retire, mean_income_data,\
factor, h_wealth, p_wealth, m_wealth, b_ellipse, upsilon, chi_b, chi_n, theta = tpi_params

Expand Down Expand Up @@ -375,7 +376,7 @@ def inner_loop(guesses, outer_loop_vars, params):
#unpack variables and parameters pass to function
income_tax_params, tpi_params, initial_values, ind = params
analytical_mtrs, etr_params, mtrx_params, mtry_params = income_tax_params
J, S, T, BW, beta, sigma, alpha, Z, delta, ltilde, nu, g_y,\
J, S, T, BW, beta, sigma, alpha, gamma, epsilon, Z, delta, ltilde, nu, g_y,\
g_n_vector, tau_payroll, tau_bq, rho, omega, N_tilde, lambdas, imm_rates, e, retire, mean_income_data,\
factor, h_wealth, p_wealth, m_wealth, b_ellipse, upsilon, chi_b, chi_n, theta = tpi_params
K0, b_sinit, b_splus1init, factor, initial_b, initial_n, omega_S_preTP, initial_debt = initial_values
Expand Down Expand Up @@ -458,7 +459,7 @@ def inner_loop(guesses, outer_loop_vars, params):

return euler_errors, b_mat, n_mat

def initial_GDP_level(y_guess, alpha, Z, initial_debt, B, L):
def initial_GDP_level(y_guess, gamma, epsilon, Z, initial_debt, B, L):
# Solve for first-period output given debt ratio, wealth, labor input, and production function.
# The solution arises from a 3-unknown, 3-equation system that is simplified below.
# (1) initial_debt = D/Y by assumption.
Expand All @@ -467,8 +468,16 @@ def initial_GDP_level(y_guess, alpha, Z, initial_debt, B, L):
# This could easily be modified to allow for an initial level of foreign bondholding.
# Salim Furth, 12/28/2016

#alpha, Z, initial_debt, B, L = y_inputs
error = y_guess - Z * ((B - initial_debt*y_guess) ** alpha) * (L ** (1 - alpha))
#alpha, gamma, epsilon, Z, initial_debt, B, L = y_inputs
# error = y_guess - Z * ((B - initial_debt*y_guess) ** alpha) * (L ** (1 - alpha))
if epsilon == 1:
error = y_guess - Z*((B - initial_debt*y_guess)**gamma)*(L**(1-gamma))
elif epsilon == 0:
error = y_guess - Z*(gamma*(B - initial_debt*y_guess) + (1-gamma)*L)
else:
error = y_guess - (Z * (((gamma**(1/epsilon))*((B - initial_debt*y_guess)**((epsilon-1)/epsilon))) +
(((1-gamma)**(1/epsilon))*(L**((epsilon-1)/epsilon))))**(epsilon/(epsilon-1)))

return error


Expand All @@ -477,7 +486,7 @@ def run_TPI(income_tax_params, tpi_params, iterative_params, small_open_params,
# unpack tuples of parameters
analytical_mtrs, etr_params, mtrx_params, mtry_params = income_tax_params
maxiter, mindist_SS, mindist_TPI = iterative_params
J, S, T, BW, beta, sigma, alpha, Z, delta, ltilde, nu, g_y,\
J, S, T, BW, beta, sigma, alpha, gamma, epsilon, Z, delta, ltilde, nu, g_y,\
g_n_vector, tau_payroll, tau_bq, rho, omega, N_tilde, lambdas, imm_rates, e, retire, mean_income_data,\
factor, h_wealth, p_wealth, m_wealth, b_ellipse, upsilon, chi_b, chi_n, theta = tpi_params
# K0, b_sinit, b_splus1init, L0, Y0,\
Expand Down Expand Up @@ -525,7 +534,7 @@ def run_TPI(income_tax_params, tpi_params, iterative_params, small_open_params,
# B_init = K_init
K_init = B_init
else:
# Y_params = (alpha, Z)
# Y_params = (Z, gamma, epsilon)
# y_guess = firm.get_Y((3-initial_debt/3)*B0,L_init[0],Y_params)
# y_inputs = (alpha,Z,initial_debt, B0, L_init[0])
# [Y0, infodict, ier, message] = opt.fsolve(initial_GDP_level, y_guess, args=y_inputs, xtol=mindist_TPI, full_output=True)
Expand All @@ -540,18 +549,19 @@ def run_TPI(income_tax_params, tpi_params, iterative_params, small_open_params,
# K_init[0] = K0
K_init = B_init * Kss/Bss
else:
K_params = (alpha, delta, Z)
K_params = (Z, gamma, epsilon, delta)
K_init = firm.get_K(L_init, tpi_firm_r, K_params)


K = K_init
L = L_init
B = B_init
Y_params = (alpha, Z)
Y_params = (Z, gamma, epsilon)
Y = firm.get_Y(K, L, Y_params)
w = firm.get_w(Y, L, alpha)
w_params = (Z, gamma, epsilon)
w = firm.get_w(Y, L, w_params)
if small_open == False:
r_params = (alpha, delta)
r_params = (Z, gamma, epsilon, delta)
r = firm.get_r(Y, K, r_params)
else:
r = tpi_hh_r
Expand Down Expand Up @@ -676,13 +686,14 @@ def run_TPI(income_tax_params, tpi_params, iterative_params, small_open_params,
print 'K has negative elements. Setting them positive to prevent NAN.'
K[:T] = np.fmax(K[:T], 0.05*B[:T])
else:
# K_params previously set to = (alpha, delta, Z)
# K_params previously set to = (Z, gamma, epsilon, delta)
K[:T] = firm.get_K(L[:T], tpi_firm_r[:T], K_params)
Y_params = (alpha, Z)
Y_params = (Z, gamma, epsilon)
Ynew = firm.get_Y(K[:T], L[:T], Y_params)
wnew = firm.get_w(Ynew[:T], L[:T], alpha)
w_params = (Z, gamma, epsilon)
wnew = firm.get_w(Ynew[:T], L[:T], w_params)
if small_open == False:
r_params = (alpha, delta)
r_params = (Z, gamma, epsilon, delta)
rnew = firm.get_r(Ynew[:T], K[:T], r_params)
else:
rnew = r
Expand Down Expand Up @@ -773,19 +784,20 @@ def run_TPI(income_tax_params, tpi_params, iterative_params, small_open_params,
if small_open == False:
K[:T] = B[:T] - D[:T]
else:
# K_params previously set to = (alpha, delta, Z)
# K_params previously set to = (Z, gamma, epsilon, delta)
K[:T] = firm.get_K(L[:T], tpi_firm_r[:T], K_params)
# Y_params previously set to = (alpha, Z)
# Y_params previously set to = (Z, gamma, epsilon)
Ynew = firm.get_Y(K[:T], L[:T], Y_params)

# testing for change in Y
ydiff = Ynew[:T] - Y[:T]
ydiff_max = np.amax(np.abs(ydiff))
print 'ydiff_max = ', ydiff_max

wnew = firm.get_w(Ynew[:T], L[:T], alpha)
w_params = (Z, gamma, epsilon)
wnew = firm.get_w(Ynew[:T], L[:T], w_params)
if small_open == False:
# r_params previously set to = (alpha,delta)
# r_params previously set to = (Z, gamma, epsilon, delta)
rnew = firm.get_r(Ynew[:T], K[:T], r_params)
else:
rnew = r
Expand Down

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