Add files via upload

Script and functions required to run the analysis - data is available at:  https://ielab.info/resources/111

AUS_RoW_disaggregation.m

@@ -0,0 +1,86 @@
+function [Dis_T,All_DIMs_Eora,Total_RoW] = AUS_RoW_disaggregation(T_Eora,Q,VA,Eora_labels,T_IElab)
+%ADDS an RoW block to form a two-region AUS-RoW MRIO - can add more regions
+%if desired by adding more countries
+% % *AIM:* Adds RoW region 
+% *Authors:* Michalis Hadjikakou (Deakin University, Australia)
+% *Last updated:* 09/11/2017
+% *Data inputs:* 
+% * n : number of sectors for RoW
+% * labels : Country name labels from Eora 26-sector full MRIO
+% * T_Eora : Eora full transaction matrix with all countries
+% * T_IElab : IElab full transaction matrix for Australia
+% *Function outputs: *Transaction matrix with disaggregated RoW region
+% (with n sectors)
+
+% Initialising 
+
+currency_rate = 0.967915; % US$/AU$ for 2013 - modify depending on year of interest
+n = 26; % number of sectors for each country - this is used for indexing purposes (code remains flexible to changed MRIO sector resolution)
+AUS_RoW_conc = zeros(2*n+1,length(T_Eora)); % Dimensions are compatible with 2 region plus residual rest of RoW column
+
+% Converting from 1000 USD to million AUD
+
+T_Eora = (T_Eora/currency_rate)/1000;
+Q = (Q/currency_rate)/1000;
+VA = (VA/currency_rate)/1000;
+
+% Locating countries
+
+Index_AUS = find(not(cellfun('isempty', strfind(Eora_labels, 'Australia')))); % Finding positions of Australian sectors in original matrix
+%Index_USA = find(not(cellfun('isempty', strfind(Eora_labels, 'USA')))); % Finding positions of Australian sectors in original matrix
+%Index_CHN = find(not(cellfun('isempty', strfind(Eora_labels, 'China')))); % Finding positions of Australian sectors in original matrix
+AUS_RoW_conc(1:n,Index_AUS) = eye(n); % Filling in Australian sector positions with ones
+%AUS_USA_CHN_RoW_conc(n+1:2*n,Index_USA) = eye(n); % Filling in USA sector positions with ones
+%AUS_USA_CHN_RoW_conc(2*n+1:3*n,Index_CHN) = eye(n); % Filling in China sector positions with ones
+
+RoW_before_Australia = (1:Index_AUS(1)-1)'; % Index of all countries before Australia 
+RoW_after_Australia = ((Index_AUS(end)+1):length(T_Eora)-1)'; % Index of all countries after Australia 
+
+AUS_RoW_conc(1:n,Index_AUS(1):Index_AUS(end)) = eye(n); % Australia sector aggregation
+AUS_RoW_conc(n+1:2*n,1:Index_AUS(1)-1) = repmat(eye(n),1,(Index_AUS(1)-1)/n); % Aggregating all RoW countries before Australia (alphabetically)
+AUS_RoW_conc(n+1:2*n,Index_AUS(end)+1:length(T_Eora)-1) = repmat(eye(n),1,length(RoW_after_Australia)/n); % Aggregating all RoW countries between USA and RoW 
+AUS_RoW_conc(end,end) = 1; % RoW kept as one row in concordance but this can later be removed as rest of RoW is negligible 
+
+Eora_26_simplified = AUS_RoW_conc*T_Eora*AUS_RoW_conc'; % Creating aggregated MRIO
+Eora_26_simplified(end,:) = []; % Deleting last row as all inputs have now been absorbed into a single RoW region
+Eora_26_simplified(:,end) = []; % Deleting last column as all exports to rest of RoW have now been absorbed into a single RoW region
+
+%RoW_input_shares = Eora_26_simplified(3*n+1:4*n,1:4*n)./repmat(sum(Eora_26_simplified(3*n+1:4*n,1:4*n)),n,1); % Determining RoW input shares from rest of RoW
+%RoW_inputs_rest_of_RoW = repmat(Eora_26_simplified(end,1:end-1),n,1).*RoW_input_shares; % Calculating rest of RoW inputs to be added to RoW inputs
+%RoW_corrected = Eora_26_simplified(3*n+1:4*n,1:4*n)+RoW_inputs_rest_of_RoW; % Correcting RoW inputs to include all rest of RoW
+%Eora_26_simplified(3*n+1:4*n,1:4*n)= RoW_corrected; % Indexing original matrix and correcting inputs
+%Eora_26_simplified(end,:) = []; % Deleting last row as all inputs have now been absorbed into a single RoW region
+
+%RoW_output_shares = Eora_26_simplified(1:4*n,3*n+1:4*n)./repmat(sum(Eora_26_simplified(1:4*n,3*n+1:4*n),2),1,n); % Determining RoW input shares from rest of RoW
+%RoW_outputs_rest_of_RoW = repmat(Eora_26_simplified(1:end,end),1,n).*RoW_output_shares;% Calculating rest of RoW exports to be added to RoW inputs
+%RoW_exports_corrected = Eora_26_simplified(1:4*n,3*n+1:4*n)+RoW_outputs_rest_of_RoW;% Correcting RoW exports to include all rest of RoW 
+%Eora_26_simplified(1:4*n,3*n+1:4*n)= RoW_exports_corrected;% Indexing original matrix and correcting 
+%Eora_26_simplified(:,end) = []; % Deleting last column as all exports to rest of RoW have now been absorbed into a single RoW region
+
+Output_totals_RoW = sum(Eora_26_simplified(n+1:2*n,:),2); % Calculating row sums of all RoW exports and domestic production - these will act as weights for initial disaggregation
+Output_weights_RoW = Output_totals_RoW'/sum(Output_totals_RoW); % Calculating weights 
+Dis_T = disaggregate_USE(T_IElab,length(T_IElab),Output_weights_RoW); % Disaggregating using Hadjikakou's disaggregate function (see working directory)
+Dis_T(length(Dis_T)-25:length(Dis_T),length(Dis_T)-25:length(Dis_T)) = Eora_26_simplified(n+1:2*n,n+1:2*n);% Setting RoW to be equal to RoW in Eora 
+
+%New_T_label = [Eora_MRIO.Tlabels xlsread([datapath 'Eora_26/' 'labels_T.xlsx'],'labels_T','D1:D16')]; % !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
+
+% 2.3 Disaggregating RoW environmental extensions, VA and calculating DIMs
+Ext_RoW = zeros(size(Q,1),size(AUS_RoW_conc,1)); % Empty matrix where aggregated extensions are to be saved
+
+for ext = 1:size(Q,1)
+ Ext_RoW(ext,:) = AUS_RoW_conc*Q(ext,:)'; % Looping through each extension in Q matrix and multiplying by concordance matrix
+end
+
+VA_agg = AUS_RoW_conc*VA'; % Aggregating original final demand
+%VA_weights_RoW = VA_agg(3*n+1:end-1,:)./repmat(sum(VA_agg(3*n+1:end-1,:)),size(VA_agg(3*n+1:end-1,:),1),1); % Calculating VA weights for RoW
+
+Sum_VA = sum(VA_agg,2); % Calculating sum of Value Added
+
+Total_RoW = sum(Eora_26_simplified(n+1:2*n,n+1:2*n),1)+Sum_VA(end-n+1:end)'; % Sum of RoW T matrix plus RoW VA
+
+All_DIMs_Eora = Ext_RoW(:,end-n:end-1)./repmat(Total_RoW,length(Ext_RoW),1); % Calculating direct impact multipliers for RoW that can be used later on in the disaggregated model
+
+% Y_agg = AUS_USA_CHN_RoW_conc*FD;
+
+end
+

Calculate_multipliers_modified.m

@@ -0,0 +1,41 @@
+function [All_TIMs] = Calculate_multipliers_modified(Total_output,Q,T)
+%CALCULATES TOTAL IMPACT MULTIPLIERS FOR ANY NUMBER OF INDICATORS 
+% % *AIM:* Standard total impact multipliers function - allows simplification of script 
+% *Authors:* Michalis Hadjikakou (Deakin University, Australia),
+% m.hadjikakou@unsw.edu.au
+% *Last updated:* 11/09/2017
+% *Data inputs: Total output, Q, T
+% * Total output : Total output as row vector
+% * Q : DIMs as column vector 
+% * T : Transaction matrix 
+% *Function outputs: *Total impact multipliers for any number of indicators
+% (All_TIMs)
+
+ Total_output = Total_output .* (Total_output>1); % set small and negative values to zero;
+ % this is necessary to prevent negative and huge DIMs (check with and without). 
+ All_indicators = Q'; % Ensures that script can be used with many different indicators - Basically DIMs have already been calculated
+
+ DIMs = All_indicators; % can be done for several rows of DIMs - Columns become rows to ensure compatibility 
+
+ DIMs(isinf(DIMs))=0 ; % Set inf in DIMs to zero
+ DIMs(isnan(DIMs))=0 ; % Set nan in DIMs to zero
+ DIMs = DIMs .* (DIMs>0); % set negative values to zero!
+
+ A = T ./ repmat(Total_output,length(Total_output),1); % This is identical to A = T * inv(diag(TotalIn));
+ A(isinf(A))=0 ; % Set inf in matrix A to zero
+ A(isnan(A))=0 ; % Set nan in matrix A to zero
+
+ I = eye(size(A));
+ L = inv(I-A);
+
+ for indnum = 1:size(All_indicators,1)% Loop through indicator rows
+
+ TIMs = DIMs(indnum,:) * L; % Calculating total impact multipliers for each indicator
+ TIMs = TIMs .* (TIMs>0); % set negative values to zero!
+ All_TIMs(indnum,:) = TIMs; % Saving TIMs in matrix
+
+ end
+
+
+end
+