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leximpact
Simulateur socio-fiscal
Budget
leximpact-survey-scenario
Commits
5000ce4c
Commit
5000ce4c
authored
2 months ago
by
BENOIT MICHAUD
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Plain Diff
ajoute les sources des taux de non recours retenus et la gestion du cas de non-recours à 100%
parent
ec4a6345
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1 merge request
!49
Non recours
Pipeline
#21529
failed
2 months ago
Stage: init
Stage: check
Stage: test
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1
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1
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1 changed file
leximpact_survey_scenario/leximpact_tax_and_benefit_system.py
+19
-2
19 additions, 2 deletions
...mpact_survey_scenario/leximpact_tax_and_benefit_system.py
with
19 additions
and
2 deletions
leximpact_survey_scenario/leximpact_tax_and_benefit_system.py
+
19
−
2
View file @
5000ce4c
...
...
@@ -593,6 +593,14 @@ def create_leximpact_tbs(projected_variables=projected_variables):
)
poids
=
famille
(
"
weight_familles
"
,
period
.
this_year
)
taux_non_recours
=
0.34
# source : https://drees.solidarites-sante.gouv.fr/publications-communique-de-presse/les-dossiers-de-la-drees/mesurer-regulierement-le-non-recours-au
if
taux_non_recours
==
0
:
return
(
non_calculable
==
TypesRSANonCalculable
.
calculable
)
*
montant
df_rsa
=
pd
.
DataFrame
(
{
"
somme_totale_annee
"
:
somme_totale_annee_rsa
,
...
...
@@ -609,7 +617,7 @@ def create_leximpact_tbs(projected_variables=projected_variables):
)
seuil_recours
=
df_eligibles
.
somme_totale_annee
[
df_eligibles
.
cumsum_weight
<=
0.3
df_eligibles
.
cumsum_weight
<=
taux_non_recours
].
max
()
return
(
...
...
@@ -658,6 +666,15 @@ def create_leximpact_tbs(projected_variables=projected_variables):
somme_totale_annee
=
famille
(
"
ppa_montant_n_1
"
,
period
)
poids
=
famille
(
"
weight_familles
"
,
period
.
this_year
)
taux_non_recours
=
0
# source : https://www.caf.fr/allocataires/actualites/actualites-nationales/prime-d-activite-campagne-d-acces-aux-droits
if
taux_non_recours
==
0
:
montant
=
np
.
where
(
departement_experimentation_rsa
,
experimentation
,
normal
)
return
montant
df
=
pd
.
DataFrame
(
{
"
somme_totale_annee
"
:
somme_totale_annee
,
...
...
@@ -674,7 +691,7 @@ def create_leximpact_tbs(projected_variables=projected_variables):
)
seuil_recours
=
df_eligibles
.
somme_totale_annee
[
df_eligibles
.
cumsum_weight
<=
0.4
df_eligibles
.
cumsum_weight
<=
taux_non_recours
].
max
()
montant
=
np
.
where
(
...
...
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