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_getfunction.- 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
NULLwhen no rounding is applied.- remove_empty
Defaults to
TRUE. If you want to keep empty primary input rows, chooseFALSE. 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 withTRUE.- 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