Savings Income Tax Base Vs. OBR Estimates: A Discrepancy?

In the realm of economic modeling, accuracy is paramount. When discrepancies arise between different models, it's crucial to delve into the root causes and identify potential solutions. This article explores a significant difference between PolicyEngine's savings income tax yield and the estimates provided by the Office for Budget Responsibility (OBR). Specifically, we'll examine why PolicyEngine's calculations for a 2 percentage point increase in the savings income tax rate are substantially lower than the OBR's projections. Understanding this gap is vital for ensuring the reliability of economic forecasts and policy recommendations. Our discussion will cover the observed discrepancies, the underlying reasons for these differences, potential solutions, and the overall impact on policy analysis.

The Discrepancy: A Significant Gap in Savings Income Tax Yield Estimates

The core issue lies in the stark contrast between PolicyEngine's savings income tax yield and the OBR's estimates. A 2 percentage point (2pp) increase in the savings income tax rate, as calculated by PolicyEngine, yields approximately £0.02 billion. In sharp contrast, the OBR's November 2025 Economic and Fiscal Outlook (EFO) projects a yield of £0.5 billion from the same 2pp increase. This OBR estimate comprises a £0.6 billion static yield minus a £0.1 billion behavioral adjustment. This thirty-fold difference raises critical questions about the underlying assumptions and data used by each model. Understanding the magnitude of this discrepancy is the first step towards reconciling these differing viewpoints and improving the accuracy of future projections.

Diving Deeper: Comparing Taxable Savings Income Bases

To pinpoint the cause of this discrepancy, we need to examine the taxable savings income base used by each model. PolicyEngine estimates the total savings interest income at £4.3 billion, with a taxable portion of £2.9 billion. At a 20% savings income tax rate, this translates to £0.33 billion in savings income tax. This calculation results in an effective tax base of £1.66 billion. However, the OBR's £0.5 billion yield from a 2pp increase implies a much larger tax base of approximately £25 billion (0.5/0.02). This reveals a significant gap: PolicyEngine's effective tax base is considerably smaller than what the OBR's estimates suggest. The disparity in the tax base is the primary driver of the difference in projected tax yields. This significant difference in effective tax base highlights the critical need to understand the data sources and methodologies used by each organization.

Key Metrics Compared: PolicyEngine vs. OBR Implied

The table above clearly illustrates the discrepancy. While PolicyEngine estimates an effective tax base of £1.66 billion, the OBR's projections imply a tax base of around £25 billion. This difference underscores the magnitude of the issue and the importance of identifying the correct savings income figures. The sheer scale of the difference in the effective tax base highlights the critical need for further investigation into the data and methodologies employed by both PolicyEngine and the OBR.

Root Cause Analysis: Identifying the Source of the Discrepancy

The fundamental reason for the disparity lies in the taxable savings income base used by PolicyEngine, which appears to be significantly smaller than what the OBR utilizes in its calculations. This difference in the tax base directly impacts the projected revenue from any changes to the savings income tax rate. To effectively address this issue, it is crucial to pinpoint the specific factors contributing to this underestimation within PolicyEngine's model.

Data Source Inconsistencies: A Closer Look at Savings Income Reporting

The HMRC statistics documentation sheds light on a potential cause: incomplete coverage of savings income in the sample data drawn from NPS (National Personal Savings) prior to 2018-2019. The documentation notes that a significant portion of Income Tax payers with savings income do not report it to HMRC. This underreporting can lead to an underestimation of the total taxable savings income base. Understanding the limitations of the data is critical for improving the accuracy of economic models. This limitation in data reporting could be a significant factor contributing to the discrepancy between PolicyEngine's estimates and the OBR's projections.

Distinguishing This Issue from Previous Concerns

It's essential to differentiate this issue from a previously identified problem (Issue #218) where projections were 2.5 times higher than SPI (Survey of Personal Incomes) targets. While Issue #218 focused on the projections exceeding SPI targets, the current concern centers on the SPI targets themselves being insufficient to match OBR savings tax revenue estimates. This distinction highlights that the problem is not merely an overestimation relative to SPI data, but a fundamental difference in the underlying savings income figures compared to the OBR's data. Clarifying this difference is crucial for targeting the correct solutions. This distinction emphasizes the importance of addressing the core issue of data accuracy rather than simply focusing on projection methodologies.

Potential Solutions: Bridging the Gap Between Estimates

To reconcile the discrepancy between PolicyEngine's and the OBR's savings income tax yield estimates, several solutions can be explored. These solutions range from identifying better data sources to calibrating the model against existing tax revenue data.

1. Finding a Better Savings Income Calibration Source

One potential solution involves seeking out more accurate data sources for savings income. The OBR or the Bank of England may possess better estimates of the total UK savings income subject to tax. These organizations often have access to comprehensive financial data and sophisticated modeling techniques, which could provide a more reliable basis for calibration. Accessing more robust data is crucial for refining economic models. Exploring data sources from these institutions could provide a more accurate representation of the savings income landscape in the UK.

2. Calibrating to Savings Income Tax Revenue

Another approach involves calibrating PolicyEngine to actual savings income tax revenue data. HMRC self-assessment data on savings tax paid can be used to back out the implied tax base. This method leverages real-world tax revenue figures to align the model's projections with actual outcomes. By using historical tax data, the model can be adjusted to better reflect the true savings income tax base. This is a practical approach to improving the model's accuracy. This method ensures that the model's outputs are grounded in real-world financial data, enhancing its reliability.

3. Using OBR Costing as a Calibration Target

A third solution involves directly using the OBR's costing as a calibration target. This would entail scaling savings income within PolicyEngine so that a 2pp increase in the savings income tax rate yields approximately £0.5 billion, matching the OBR's estimate. This approach directly aligns PolicyEngine's projections with the OBR's benchmark, ensuring consistency in policy analysis. Adopting the OBR costing as a target provides a clear benchmark for calibration. While this method ensures alignment with the OBR's estimates, it's important to continuously evaluate the underlying data and assumptions.

Impact: Implications for Policy Analysis

The discrepancy in savings income tax yield estimates has significant implications for policy analysis, particularly for dashboards and projections related to tax reforms. In the specific case of the UK Autumn Budget 2025 dashboard, the estimates for the