Create a coefficient matrix from a Symmetric Input-Output Table. The coefficient matrix is related by default to output, but you can change this to total supply or other total aggregate if it exists in your table.

coefficient_matrix_create(data_table, total = "output", digits = NULL,
  remove_empty = TRUE, households = FALSE, return_part = NULL)

Arguments

data_table

A symmetric input-output table, a use table, a margins or tax table retrieved by the iotable_get function.

total

Usually an output vector with a key column, defaults to "output" which equals "P1" or "output_bp". You can use other rows for comparison, for example "TS_BP" if it exists in the matrix.

digits

An integer showing the precision of the technology matrix in digits. Default is NULL when no rounding is applied.

remove_empty

Defaults to TRUE. If you want to keep empty primary input rows, choose FALSE. Empty product/industry rows are always removed to avoid division by zero error in the analytical functions.

households

Defaults to NULL. Household column can be added with TRUE.

return_part

Defaults to NULL. You can choose "product" or "industry" to return an input coefficient matrix or "primary_inputs" to get only the total intermediate use and proportional primary inputs.

Value

A data.frame that contains the matrix of data_table divided by total with a key column. Optionally the results are rounded to given digits.

References

See United Kingdom Input-Output Analytical Tables 2010 for explanation on the use of the Coefficient matrix.

Examples

coefficient_matrix_create ( data_table = iotable_get ( source = "germany_1990"), total = "output", digits = 4 )
#> iotables_row agriculture_group industry_group construction #> 1 agriculture_group 0.0258 0.0236 0.0000 #> 2 industry_group 0.1806 0.2822 0.2613 #> 3 construction 0.0097 0.0068 0.0158 #> 4 trade_group 0.0811 0.0674 0.0578 #> 5 business_services_group 0.0828 0.0890 0.1263 #> 6 other_services_group 0.0353 0.0139 0.0071 #> 7 total 0.4153 0.4829 0.4683 #> 8 imports 0.0667 0.1452 0.0547 #> 9 intermediate_consumption 0.5066 0.6341 0.5292 #> 10 compensation_employees 0.2137 0.2746 0.3209 #> 11 net_tax_production -0.0458 0.0013 0.0039 #> 12 consumption_fixed_capital 0.1793 0.0591 0.0239 #> 13 os_mixed_income_net 0.1463 0.0309 0.1221 #> 14 gva 0.4934 0.3659 0.4708 #> 15 output 1.0000 1.0000 1.0000 #> 16 net_tax_products 0.0247 0.0060 0.0063 #> 17 employment_wage_salary 0.0110 0.0074 0.0118 #> 18 employment_self_employed 0.0140 0.0003 0.0014 #> 19 employment_domestic_total 0.0250 0.0078 0.0132 #> trade_group business_services_group other_services_group #> 1 0.0011 0.0010 0.0015 #> 2 0.0761 0.0173 0.0597 #> 3 0.0098 0.0339 0.0180 #> 4 0.1378 0.0156 0.0413 #> 5 0.1218 0.2790 0.0672 #> 6 0.0208 0.0217 0.0434 #> 7 0.3673 0.3686 0.2310 #> 8 0.0406 0.0193 0.0271 #> 9 0.4234 0.4001 0.2828 #> 10 0.3971 0.1802 0.5364 #> 11 0.0051 0.0086 -0.0169 #> 12 0.0761 0.1424 0.0968 #> 13 0.0983 0.2687 0.1010 #> 14 0.5766 0.5999 0.7172 #> 15 1.0000 1.0000 1.0000 #> 16 0.0155 0.0122 0.0247 #> 17 0.0148 0.0053 0.0188 #> 18 0.0024 0.0009 0.0013 #> 19 0.0171 0.0061 0.0201