Private school rerun (#971)

* Adjust private school factor upwards to 0.85 (from 0.77)

* Versioning

CHANGELOG.md

@@ -5,6 +5,12 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), 
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [2.8.0] - 2024-10-21 13:04:20
+
+### Fixed
+
+- Adjusted private school attendance factor to 0.85.
+
 ## [2.7.0] - 2024-10-21 10:09:01
 
 ### Added
@@ -1524,6 +1530,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 
 
+[2.8.0]: https://github.com/PolicyEngine/openfisca-uk/compare/2.7.0...2.8.0
 [2.7.0]: https://github.com/PolicyEngine/openfisca-uk/compare/2.6.0...2.7.0
 [2.6.0]: https://github.com/PolicyEngine/openfisca-uk/compare/2.5.0...2.6.0
 [2.5.0]: https://github.com/PolicyEngine/openfisca-uk/compare/2.4.0...2.5.0

changelog.yaml

@@ -1279,3 +1279,8 @@
     added:
     - Automatic allocation of post-employee-incidence employee to households (consumers/capital).
   date: 2024-10-21 10:09:01
+- bump: minor
+  changes:
+    fixed:
+    - Adjusted private school attendance factor to 0.85.
+  date: 2024-10-21 13:04:20

policyengine_uk/parameters/gov/simulation/private_school_vat/private_school_factor.yaml

@@ -1,6 +1,6 @@
 description: student polulation adjustment factor, tested by Vahid
 values:
-  2010-01-01: 0.77
+  2010-01-01: 0.85
 metadata:
   unit: /1
   label: student polulation adjustment factor

policyengine_uk/utils/solve_private_school_attendance_factor.py

@@ -1,12 +1,13 @@
 from policyengine_uk import Microsimulation
 from policyengine_core.reforms import Reform
+from tqdm import tqdm
 
 # Initialize variables to track the best private_school_factor and its result
 best_factor = None
 smallest_difference = float("inf")
 
 # Loop over values of private_school_factor from 0.7 to 0.8 in steps of 0.01
-for factor in [round(x * 0.01, 2) for x in range(70, 81)]:
+for factor in tqdm([round(x * 0.01, 2) for x in range(70, 91)]):
     # Define the reform with the current private_school_factor value
     reform = Reform.from_dict(
         {
@@ -22,6 +23,7 @@
 
     # Run the reformed microsimulation
     reformed = Microsimulation(reform=reform)
+    reformed.get_holder("attends_private_school").delete_arrays()
 
     # Calculate the number of students attending private school in thousands
     private_school_attendance = (

setup.py

@@ -4,7 +4,7 @@
 
 setup(
     name="PolicyEngine-UK",
-    version="2.7.0",
+    version="2.8.0",
     author="PolicyEngine",
     author_email="nikhil@policyengine.org",
     classifiers=[