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. 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. An integer showing the precision of the technology matrix in digits. Default is NULL when no rounding is applied. 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. Defaults to NULL. Household column can be added with TRUE. 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.

Other indicator functions: direct_effects_create(), input_indicator_create()

## 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
#> 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