diff --git a/changelog_entry.yaml b/changelog_entry.yaml
index e69de29bb..37daeef19 100644
--- a/changelog_entry.yaml
+++ b/changelog_entry.yaml
@@ -0,0 +1,4 @@
+- bump: minor
+ changes:
+ added:
+ - Update National Insurance documentation
diff --git a/docs/book/_toc.yml b/docs/book/_toc.yml
index 615edf0e7..101ee4ffb 100644
--- a/docs/book/_toc.yml
+++ b/docs/book/_toc.yml
@@ -9,6 +9,7 @@ parts:
- caption: Programs
chapters:
- file: programs/gov/hmrc/child-benefit
+ - file: programs/gov/hmrc/national-insurance
- file: programs/gov/hmrc/fuel-duty
- file: programs/contrib/ubi-center/carbon-tax
- file: programs/gov/ofgem/energy-price-guarantee
diff --git a/docs/book/programs/gov/hmrc/national_insurance.ipynb b/docs/book/programs/gov/hmrc/national_insurance.ipynb
new file mode 100644
index 000000000..500a1346c
--- /dev/null
+++ b/docs/book/programs/gov/hmrc/national_insurance.ipynb
@@ -0,0 +1,4153 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "_gdKAFopTwuB"
+ },
+ "source": [
+ "# National Insurance"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "b3G5DBwhos_2"
+ },
+ "source": [
+ "National Insurance is a key component of the UK tax system. It primarily funds certain types of welfare and state benefits, including the State Pension. Here's an overview of National Insurance:\n",
+ "\n",
+ "**Purpose**:\\\n",
+ "The main purpose of National Insurance is to fund various state benefits such as the State Pension, unemployment benefits, maternity allowance, and sickness and disability allowances.\n",
+ "\n",
+ "**Types of National Insurance Contributions (NICs):**\\\n",
+ "**Class 1**: Paid by employees and their employers. This is based on the employee's earnings and is deducted directly from wages.\\\n",
+ "**Class 2**: Paid by self-employed people with profits above a certain threshold.\\\n",
+ "**Class 3**: Voluntary contributions, often made by people who want to fill gaps in their National Insurance record.\\\n",
+ "**Class 4**: Paid by self-employed people with profits above a certain threshold, in addition to Class 2 NICs."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "ie5U-X3ruXj3"
+ },
+ "source": [
+ "# Methodology\n",
+ "\n",
+ "The table outlines the methodology used by PolicyEngine UK to model Class 1, 2, and 4 National Insurance:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "cellView": "form",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "SfKRQHzBm1rQ",
+ "outputId": "ca2e1cc7-616a-433c-c1e3-6a0e95f48fbc"
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "+---------+------------------------------------------------------------------+---------------------------+-----------------------------+----------------------------------------------------------+\n",
+ "| Class | Methodology & Basis | Thresholds & Limits | Rate Application | Reference |\n",
+ "+=========+==================================================================+===========================+=============================+==========================================================+\n",
+ "| Class 1 | - Based on employment income. | - Primary Threshold | - Main and Additional rates | Social Security Contributions and Benefits Act 1992 s. 8 |\n",
+ "| | - Monthly and annual calculations. | - Upper Earnings Limit | | |\n",
+ "+---------+------------------------------------------------------------------+---------------------------+-----------------------------+----------------------------------------------------------+\n",
+ "| Class 2 | - Based on self-employment income. | - Small Profits Threshold | - Flat rate | Social Security and Benefits Act 1992 s. 11 |\n",
+ "| | - Weekly flat rate. | | | |\n",
+ "+---------+------------------------------------------------------------------+---------------------------+-----------------------------+----------------------------------------------------------+\n",
+ "| Class 4 | - Derived from self-employment income minus Class 1 employee NI. | - Lower Profits Limit | - Main and Additional rates | Social Security and Benefits Act 1992 s. 15 |\n",
+ "| | | - Upper Profits Limit | | |\n",
+ "+---------+------------------------------------------------------------------+---------------------------+-----------------------------+----------------------------------------------------------+\n"
+ ]
+ }
+ ],
+ "source": [
+ "# @title\n",
+ "import pandas as pd\n",
+ "from tabulate import tabulate\n",
+ "\n",
+ "\n",
+ "data = {\n",
+ " \"Class\": [\"Class 1\", \"Class 2\", \"Class 4\"],\n",
+ " \"Methodology & Basis\": [\n",
+ " \"- Based on employment income. \\n- Monthly and annual calculations.\",\n",
+ " \"- Based on self-employment income. \\n- Weekly flat rate.\",\n",
+ " \"- Derived from self-employment income minus Class 1 employee NI.\"\n",
+ " ],\n",
+ " \"Thresholds & Limits\": [\n",
+ " \"- Primary Threshold \\n- Upper Earnings Limit\",\n",
+ " \"- Small Profits Threshold\",\n",
+ " \"- Lower Profits Limit \\n- Upper Profits Limit\"\n",
+ " ],\n",
+ " \"Rate Application\": [\n",
+ " \"- Main and Additional rates\",\n",
+ " \"- Flat rate\",\n",
+ " \"- Main and Additional rates\"\n",
+ " ],\n",
+ " \"Reference\": [\n",
+ " \"Social Security Contributions and Benefits Act 1992 s. 8\",\n",
+ " \"Social Security and Benefits Act 1992 s. 11\",\n",
+ " \"Social Security and Benefits Act 1992 s. 15\"\n",
+ " ]\n",
+ "}\n",
+ "\n",
+ "df = pd.DataFrame(data)\n",
+ "\n",
+ "# Print the table without the index column\n",
+ "print(tabulate(df, headers='keys', tablefmt='grid', showindex=False))\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "bxQD7vfe1t2n"
+ },
+ "source": [
+ "# Appendix:\n",
+ "**- Class 1 National Insurance Rates:**\\\n",
+ "This table displays the parameter values for the Class 1 National Insurance rates for employees (both main and additional) and employers."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "cellView": "form",
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+ },
+ "id": "Qk95U6v2XqHR",
+ "outputId": "8551c5df-1844-4299-d52b-288e33dfd39a"
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " Date Class 1 Employee Main Rates Class 1 Employee Additional Rates Class 1 Employer Rates\n",
+ "2015-06-01 12.00% 2.00% 13.80%\n",
+ "2022-04-01 13.25% 3.25% \n",
+ "2022-11-06 12.00% \n"
+ ]
+ }
+ ],
+ "source": [
+ "# @title\n",
+ "\n",
+ "main_dates = [\"2015-06-01\", \"2022-04-01\", \"2022-11-06\"]\n",
+ "main_rates = [0.12, 0.1325, 0.12]\n",
+ "\n",
+ "additional_dates = [\"2015-06-01\", \"2022-04-01\"]\n",
+ "additional_rates = [0.02, 0.0325]\n",
+ "\n",
+ "employer_dates = [\"2015-06-01\"]\n",
+ "employer_rates = [0.138]\n",
+ "\n",
+ "all_dates = sorted(set(main_dates + additional_dates + employer_dates))\n",
+ "\n",
+ "df = pd.DataFrame({'Date': all_dates})\n",
+ "df['Class 1 Employee Main Rates'] = df['Date'].map(dict(zip(main_dates, main_rates)))\n",
+ "df['Class 1 Employee Additional Rates'] = df['Date'].map(dict(zip(additional_dates, additional_rates)))\n",
+ "df['Class 1 Employer Rates'] = df['Date'].map(dict(zip(employer_dates, employer_rates)))\n",
+ "\n",
+ "df['Class 1 Employee Main Rates'] = df['Class 1 Employee Main Rates'].apply(lambda x: f\"{x*100:.2f}%\" if pd.notnull(x) else \"\")\n",
+ "df['Class 1 Employee Additional Rates'] = df['Class 1 Employee Additional Rates'].apply(lambda x: f\"{x*100:.2f}%\" if pd.notnull(x) else \"\")\n",
+ "df['Class 1 Employer Rates'] = df['Class 1 Employer Rates'].apply(lambda x: f\"{x*100:.2f}%\" if pd.notnull(x) else \"\")\n",
+ "\n",
+ "print(df.to_string(index=False))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "sWgDc7c_2iVp"
+ },
+ "source": [
+ "**- Class 1 National Insurance Thresholds:**\n"
+ ]
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+ "import plotly.express as px\n",
+ "\n",
+ "dates = ['2015-04-06', '2016-04-06', '2017-04-06', '2018-04-06', '2019-04-06', '2020-04-06', '2021-04-06', '2022-04-06']\n",
+ "\n",
+ "lower_earnings = [112, 112, 113, 116, 118, 120, 120, 123]\n",
+ "primary_threshold = [155, 155, 157, 162, 166, 183, 184, 190]\n",
+ "secondary_threshold = [155, 155, 157, 162, 166, 169, 170, 175]\n",
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+ "\n",
+ "df = pd.DataFrame({\n",
+ " 'Dates': dates,\n",
+ " 'Lower Earnings Limit': lower_earnings,\n",
+ " 'Primary Threshold': primary_threshold,\n",
+ " 'Secondary Threshold': secondary_threshold,\n",
+ " 'Upper Earnings Limit': upper_earnings\n",
+ "})\n",
+ "\n",
+ "fig = px.line(df, x='Dates', y=df.columns[1:],\n",
+ " title='Class 1 National Insurance Thresholds Over Time',\n",
+ " labels={'value': 'Thresholds (GBP)', 'variable': 'Thresholds', 'Dates': 'Dates'})\n",
+ "\n",
+ "fig.show()\n"
+ ]
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+ "**- Class 2 National Insurance Rates:**"
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+ "dates_flat_rate = ['2015-06-01', '2017-06-01', '2018-06-01', '2019-06-01', '2020-06-01', '2022-04-06']\n",
+ "flat_rate_values = [2.80, 2.85, 2.95, 3.00, 3.05, 3.15]\n",
+ "df_flat_rate = pd.DataFrame({'Dates': dates_flat_rate, 'Flat rate': flat_rate_values})\n",
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+ "dates_small_profits = ['2015-04-06', '2017-04-06', '2018-04-06', '2019-04-06', '2020-04-06', '2021-04-06', '2022-04-06']\n",
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+ "df_small_profits = pd.DataFrame({'Dates': dates_small_profits, 'Small profits threshold': small_profits_values})\n",
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+ "fig_flat_rate = px.line(df_flat_rate, x='Dates', y='Flat rate',\n",
+ " title='Class 2 National Insurance: Flat rate',\n",
+ " labels={'Dates': 'Dates', 'Flat rate': 'Flat rate (GBP)'},\n",
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+ "fig_small_profits = px.line(df_small_profits, x='Dates', y='Small profits threshold',\n",
+ " title='Class 2 National Insurance: Small profits threshold',\n",
+ " labels={'Dates': 'Dates', 'Small profits threshold': 'Small profits threshold (GBP)'},\n",
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+ "**- Class 4 National Insurance Rates:**\\\n",
+ "This table displays the parameter values for the Class 4 National Insurance rates (both main and additional).\n"
+ ]
+ },
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+ "text": [
+ " Date Class 4 Main Rate Class 4 Additional Rate\n",
+ "2015-06-01 9.00% 2.00%\n",
+ "2022-04-01 10.25% 3.50%\n",
+ "2022-11-06 9.00% \n"
+ ]
+ }
+ ],
+ "source": [
+ "# @title\n",
+ "\n",
+ "main_dates = [\"2015-06-01\", \"2022-04-01\", \"2022-11-06\"]\n",
+ "main_rates = [0.09, 0.1025, 0.09]\n",
+ "\n",
+ "additional_dates = [\"2015-06-01\", \"2022-04-01\"]\n",
+ "additional_rates = [0.02, 0.035]\n",
+ "\n",
+ "all_dates = sorted(set(main_dates + additional_dates))\n",
+ "\n",
+ "df = pd.DataFrame({'Date': all_dates})\n",
+ "df['Class 4 Main Rate'] = df['Date'].map(dict(zip(main_dates, main_rates)))\n",
+ "df['Class 4 Additional Rate'] = df['Date'].map(dict(zip(additional_dates, additional_rates)))\n",
+ "\n",
+ "df['Class 4 Main Rate'] = df['Class 4 Main Rate'].apply(lambda x: f\"{x*100:.2f}%\" if pd.notnull(x) else \"\")\n",
+ "df['Class 4 Additional Rate'] = df['Class 4 Additional Rate'].apply(lambda x: f\"{x*100:.2f}%\" if pd.notnull(x) else \"\")\n",
+ "\n",
+ "print(df.to_string(index=False))\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "qFtjkiGq4JHW"
+ },
+ "source": [
+ "**- Class 4 National Insurance Thresholds:**"
+ ]
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+ "# @title\n",
+ "\n",
+ "dates_lower_profits_limit = [\"2015-04-06\", \"2017-04-06\", \"2018-04-06\", \"2019-04-06\", \"2020-04-06\", \"2021-04-06\", \"2022-04-06\", \"2026-04-06\"]\n",
+ "values_lower_profits_limit = [8060, 8164, 8424, 8632, 9500, 9568, 11908, 12570]\n",
+ "\n",
+ "dates_upper_profits_limit = [\"2015-04-06\", \"2015-06-05\", \"2017-04-06\", \"2018-04-06\", \"2019-04-06\", \"2020-04-06\", \"2021-04-06\", \"2026-04-06\"]\n",
+ "values_upper_profits_limit = [42386, 43000, 45000, 46350, 50000, 50000, 50270, 50270]\n",
+ "\n",
+ "df_lower = pd.DataFrame({'Dates': dates_lower_profits_limit, 'Values': values_lower_profits_limit, 'Label': 'Lower Profits Limit'})\n",
+ "df_upper = pd.DataFrame({'Dates': dates_upper_profits_limit, 'Values': values_upper_profits_limit, 'Label': 'Upper Profits Limit'})\n",
+ "df = pd.concat([df_lower, df_upper])\n",
+ "\n",
+ "fig = px.line(df, x='Dates', y='Values', color='Label', title='Class 4 National Insurance Thresholds Over Time', markers=True)\n",
+ "\n",
+ "fig.update_layout(\n",
+ " xaxis_title=\"Dates\",\n",
+ " yaxis_title=\"Thresholds (GBP)\",\n",
+ " legend_title_text='Threshold Type',\n",
+ " legend=dict(orientation=\"h\", yanchor=\"bottom\", y=1.02, xanchor=\"left\", x=0.05)\n",
+ ")\n",
+ "\n",
+ "fig.show()\n"
+ ]
+ }
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+ "pygments_lexer": "ipython3",
+ "version": "3.9.7"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}