%To run in parallel: % dynare test_small_base.mod conffile='/Applications/Dynare/4.4.2/dynare_parallel.txt' parallel %To test parallel configuration % dynare test_small_base.mod conffile='/Applications/Dynare/4.4.2/dynare_parallel.txt' parallel_test % Model in real terms: investment and capital-asset ratio adjustment cost, % consumption habits, sticky prices via Rotemberg % with indexation to both past and steady state inflation % Equation Blocks 1) households 2) capital producers % 3) entrepreneurs 4) banks 5) retailers % 6) aggregation 7) monetary policy %Version: January 5th, 2015 global I_SS; var %Households c_h d l_h lam_h w %Retailers J_R x %Capital Producers I q_k %Entrepreneurs c_e k b y lam_e s_e r_k %Banks r_d r_b r_ib K_b J_B leverage eps_r_cb %Aggregation C %Monetary Policy r_cb %Shocks A_e %Measurement data_I data_rCB %Prices pie pie_w ; varexo e_A_e e_r_cb; %e_sig e_q_e; parameters %Households and Entrepreneurs beta_p beta_e m_e alpha eps_l gamma phi %Banks eps_d eps_b delta_kb vi kappa_kb z M sig %Retailers kappa_p ind_p delta_e eps_y %Capital Producers kappa_i deltak %Prices piss %Aggregation S %Shocks rho_A_e rho_r_cb sig_ss r_cb_ss %Monetary Policy rho_ib phi_pie phi_y %Measurement I_SS ; % ********************* % Calibrated Parameters % ********************* %Discount factors beta_p = 0.9943; beta_e = 0.975; %Loan-to-value ratio entrepreneurs m_e = 0.35 ; %Capital share in the production function alpha = 0.250; %Elast. of subst. of deposits and loans eps_d = -1.1402; %-1.46025; eps_b = 2.2987; %2.932806; %Elast. of subst. of goods and labor eps_y = 6; %Depreciation rate for physical capital deltak = 0.025; %Steady state gross inflation rate piss = 1; %Steady state gross nominal interest rate r_cb_ss = (piss/beta_p-1)* (eps_d-1)/eps_d ; %Capital-asset ratio (Basel II) vi = 0.09; %Depreciation rate of bank capital delta_kb = 0.153661; %Estimated Parameters %Inverse Frisch elasticity of labor supply %phi = 0.9167; %Cofficient of Relative Risk Aversioin %gamma = 1.3589; %Adjustment cost parameter for prices, investment, and capital-asset ratio %kappa_p = 20.2155; %kappa_i = 2.6804; %kappa_kb = 23.8727; %Monetary policy response to lagged interest rate, inflation, output %rho_ib = 0.8305; %phi_pie = 2.2018; %phi_y = -0.0664; %Indexation to lagged and steady state inflation %ind_p = 0.4414; %AR(1) coefficients on shocks %rho_A_e = 0.5855; %rho_r_cb = 0.8094; %Steady States for Measurement Variables I_SS = -1.75257; %------------------------------------------------------------ % Model equations %------------------------------------------------------------ model; %1) Houshold ********************************************************6 exp(c_h)^(-gamma) = exp(lam_h); // CON rescaling exp(lam_h) = beta_p * exp(lam_h(+1)) * (1+exp(r_d))/exp(pie(+1)); // exp(l_h)^phi = exp(lam_h)*exp(w); exp(pie_w) = exp(w) / exp(w(-1)) * exp(pie); exp(c_h) + exp(d) = exp(w) * exp(l_h)+ (1+exp(r_d(-1)))*exp(d(-1))/exp(pie) ; // %2) Capital Producers ***************************************************** exp(k) = (1-deltak) * exp(k(-1)) + ( 1 - kappa_i/2 * (exp(I)/exp(I(-1)) - 1)^2 ) * exp(I) ; 1 = exp(q_k) * ( 1 - kappa_i/2 * (exp(I)/exp(I(-1)) - 1)^2 - kappa_i * (exp(I)/exp(I(-1)) - 1) * exp(I)/exp(I(-1)) ) + beta_e * exp(lam_e(+1)) / exp(lam_e) * exp(q_k(+1)) * kappa_i * (exp(I(+1))/exp(I) - 1) * (exp(I(+1))/exp(I))^2 ; // 13 // 15 %3) Entrepreneurs ********************************************************* exp(c_e)^(-gamma) = exp(lam_e); // CON rescaling exp(s_e) * m_e * exp(q_k(+1)) * exp(pie(+1)) * (1-deltak) + beta_e * exp(lam_e(+1)) * ( exp(q_k(+1))*(1-deltak) + exp(r_k(+1))) = exp(lam_e) * exp(q_k) ; // exp(w) = (1-alpha) * exp(y) / ( exp(l_h)*exp(x) ); exp(lam_e) - exp(s_e) * (1+exp(r_b)) = beta_e * exp(lam_e(+1)) * (1+exp(r_b)) / exp(pie(+1)); // exp(c_e) + ((1+exp(r_b(-1))) * exp(b(-1)) / exp(pie) ) + (exp(w)*exp(l_h)) + exp(q_k) * exp(k) = exp(y) / exp(x) + exp(b) + exp(q_k) * (1-deltak) * exp(k(-1)) + exp(J_R) ; exp(y) = exp(A_e) * (exp(k(-1)))^(alpha) * ( exp(l_h) ) ^ (1-alpha); (1+exp(r_b)) * exp(b) = m_e * exp(q_k(+1)) *exp(pie(+1)) * exp(k) * (1-deltak); exp(r_k) = alpha * exp(A_e) * exp(k(-1))^(alpha-1) * ( exp(l_h)) ^ (1-alpha)/exp(x); %4) Banks **************************************************************** exp(r_ib) = - kappa_kb * (exp(K_b)/(exp(b)) - vi ) * (exp(K_b)/(exp(b))) ^2 + exp(r_cb) ; exp(K_b) = (1-delta_kb) * exp(K_b(-1)) + exp(J_B(-1)) ; %exp(K_b)/(exp(b))=vi; exp(b) = exp(d) + exp(K_b); - 1 + eps_d - eps_d * exp(r_cb)/exp(r_d); + 1 - eps_b + eps_b * exp(r_ib)/exp(r_b); exp(J_B) = + exp(r_b) * exp(b) - exp(r_d) * exp(d) - kappa_kb/2 * ( (exp(K_b) / (exp(b)) - vi ) ^2) * exp(K_b); exp(leverage)=(exp(b))/exp(K_b); %5) Retailers ************************************************************** exp(J_R) = exp(y)*(1 - 1/exp(x) - (kappa_p/2) * (exp(pie) - exp(pie(-1)) ^ ind_p * piss ^ (1-ind_p) )^2 ) ; 1 - eps_y + eps_y/exp(x) - kappa_p * (exp(pie) - exp(pie(-1)) ^ ind_p * piss ^ (1-ind_p) ) * exp(pie) + beta_p*(exp(lam_e(+1))/exp(lam_e))* kappa_p * (exp(pie(+1)) - exp(pie) ^ ind_p * piss ^ (1-ind_p) ) * exp(pie(+1)) * (exp(y(+1))/exp(y)) = 0; %6) Aggregation ************************************************ exp(C) = exp(c_h) + exp(c_e); %7) Monetary Policy ***************************************************** (1+exp(r_cb)) = (1+r_cb_ss)^(1 - rho_ib ) * (1+exp(r_cb(-1)))^rho_ib * (( exp(pie) / piss ) ^phi_pie * (exp(y)/exp(y(-1)))^phi_y ) ^ ( 1 - rho_ib ) * exp(eps_r_cb) ; %8) Shocks ****************************************************12 exp(A_e) = (1 - rho_A_e) * 1 + rho_A_e * exp(A_e(-1)) + e_A_e; exp(eps_r_cb) = (1 - rho_r_cb) * 1 + rho_r_cb * exp(eps_r_cb(-1)) + e_r_cb; %9) Measurement Equations ******************************12 data_I = I-I_SS; data_rCB = exp(r_cb) - r_cb_ss; end; %------------------------------------------------------------ % Initial Values %------------------------------------------------------------ initval; c_h = 0.0192946; d = 0.747995; l_h = -0.00897527; lam_h = -0.0268194; w = 0.0163184; J_R = -1.31441; x = 0.182322; I = -1.75257; q_k = 0; c_e = -0.949657; k = 1.93631; b = 0.842306; y = 0.477347; lam_e = 1.32002; s_e = -3.74563; r_k = -3.02758; r_d = -5.16157; r_b = -3.96089; r_ib = -4.53188; K_b = -1.56564; J_B = -3.43865; leverage = 2.40795; eps_r_cb = 0; C = 0.341002; r_cb = -4.53188; A_e = 0; data_I = 0; data_rCB = 0; pie = 0; pie_w = 0; end; %------------------------------------------------------------ % Bayesian Estimation %------------------------------------------------------------ %Defining which dataseries are used in estimation varobs data_I data_rCB; %load Model.txt; % load dataseries from file filename = 'Model.txt'; delimiter = '\t'; startRow = 2; %% Format string for each line of text: % column1: double (%f) % column2: double (%f) % column3: double (%f) % column4: double (%f) % column5: double (%f) % column6: double (%f) % column7: double (%f) % column8: double (%f) % column9: double (%f) % column10: double (%f) % column11: double (%f) % column12: double (%f) % column13: double (%f) % column14: double (%f) % column15: double (%f) % column16: double (%f) % For more information, see the TEXTSCAN documentation. formatSpec = '%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%[^\n\r]'; %% Open the text file. fileID = fopen(filename,'r'); %% Read columns of data according to format string. % This call is based on the structure of the file used to generate this % code. If an error occurs for a different file, try regenerating the code % from the Import Tool. dataArray = textscan(fileID, formatSpec, 'Delimiter', delimiter, 'HeaderLines' ,startRow-1, 'ReturnOnError', false); %% Close the text file. fclose(fileID); %% Post processing for unimportable data. % No unimportable data rules were applied during the import, so no post % processing code is included. To generate code which works for % unimportable data, select unimportable cells in a file and regenerate the % script. %% Allocate imported array to column variable names Year = dataArray{:, 1}; Quarter = dataArray{:, 2}; Investment = dataArray{:, 4}; FedFundsRate = dataArray{:, 9}; %% Clear temporary variables clearvars filename delimiter startRow formatSpec fileID dataArray ans; Dates=horzcat(Year, Quarter); save('Model_small.mat', 'Dates', 'FedFundsRate', 'Investment') BEG_OBS = 1; % 1997:Q2 END_OBS = length(Dates); % 2007:Q4 43 quarterly observations DATES = Dates(BEG_OBS:END_OBS,:); datadescr.DATES = DATES; datadescr.MODEL = M_.fname; % give the dataseries the names listed in the 'varobs' command ... dataseries.data_I = Investment (BEG_OBS:END_OBS); datadescr.data_I = 'Real Investment'; dataseries.data_rCB = FedFundsRate (BEG_OBS:END_OBS) - mean(FedFundsRate (BEG_OBS:END_OBS)); datadescr.data_rCB = 'Short-term dinterest rate'; %Saving the renamed series for Dynare save ('DYNARE_estimdata','-STRUCT','dataseries') estimated_params ; %Variable Prior Shape Mean Std. Dev. stderr e_A_e, inv_gamma_pdf, 0.0100, 0.05; stderr e_r_cb, inv_gamma_pdf, 0.0100, 0.05; rho_A_e, beta_pdf, 0.80, 0.10; rho_r_cb, beta_pdf, 0.80, 0.10; kappa_p, gamma_pdf, 50, 20; kappa_i, gamma_pdf, 2.5, 1.0; kappa_kb, gamma_pdf, 10.0, 5.0; phi_pie, gamma_pdf, 2.0, 0.5; rho_ib, beta_pdf, 0.75, 0.10; phi_y, normal_pdf, 0.10, 0.15; ind_p, beta_pdf, 0.50, 0.15; gamma, gamma_pdf, 1.0, 0.5; phi, gamma_pdf, 1.0, 0.5; end; %options_.parallel = struct('Local', 1, 'PcName','', 'CPUnbr', [0:3], 'user','','passwd','','RemoteDrive', '', 'RemoteFolder',''); estimation(datafile=DYNARE_estimdata ,mode_compute = 6 ,mh_jscale = 0.30 ,presample = 0 ,prefilter = 0 ,prior_trunc = 1e-14 ,mh_replic = 100000 ,mh_nblocks = 10 ,mode_check ,lik_init = 1 ,order = 1 ) C I y r_cb r_b r_d pie b d J_B K_b;