Skip to contents

Create a coefficient matrix from a Symmetric Input-Output Table.

Usage

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 analytic 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.

Details

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.

References

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

See also

Other indicator functions: direct_effects_create(), input_indicator_create()

Examples

coefficient_matrix_create(data_table = iotable_get(source = "germany_1995"), 
                          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