FBR uses buoyancy-based model to estimate FY27 tax collection

The Federal Board of Revenue (FBR) has used a buoyancy-based forecasting framework to estimate tax collections for FY2026-27, according to a report on tax estimates issued on Thursday.

The report said buoyancy coefficients were recalibrated using the latest available FBR revenue data along with National Accounts statistics.

The macroeconomic dataset includes GDP, Large-Scale Manufacturing (LSM) and imports over a 20-year period from FY2005-06 to FY2024.

According to the FBR, the use of long-term data strengthens the reliability of estimates by capturing different economic cycles, structural changes and policy phases.

The report said buoyancy for each major tax head was estimated through a log-linear regression framework implemented in Excel.

The method measures how tax revenues respond to changes in underlying macroeconomic indicators.

The FBR said the approach provides transparency, replicability and practical value for institutional revenue forecasting.

After estimating buoyancy coefficients, projected growth rates of GDP, LSM and imports were applied to the relevant tax-specific buoyancy parameters.

This produced the autonomous growth rate for each tax category, showing the expected increase in revenue from economic activity under unchanged policy conditions.

The report said the model separates structural revenue growth from revenue expected through discretionary policy measures.

The calculated autonomous growth rates were then applied to projected base-year collections for FY2025-26 to estimate additional revenue for FY2026-27.

The incremental revenue was added to base-year collections to arrive at final baseline projections.

The FBR said these projections exclude the impact of any new taxation measures, rate changes or policy reforms that may be introduced during the FY2026-27 budget process.

The report said the approach ensures methodological consistency and policy neutrality in baseline revenue forecasting.