frPropose a project
Impact results

Optimizing land resource
management in Senegal


Research teamJustine KnebelmannVictor PouliquenBassirou Sarr

The Project for the Improvement of Property Tax Management (PAGCF) in Senegal is led by a research team in collaboration with the Directorate General of Taxes and Domains (DGID). The aim is to pilot a new model of land taxation, using a digital platform that centralizes land registry data and automatically issues tax notices. This information is based on digital real estate surveys and the systematic geolocation of properties, as well as a more accurate and equitable formula for valuing real estate. The end goal is to provide tax authorities with a more effective tax collection system which can then be used to finance other essential services for Senegalese taxpayers.

Key impact results

The impact evaluation carried out between 2022 and 2025 demonstrated that this digital platform has expanded the tax base of the Senegalese tax authorities, while improving the system for issuing tax notices and collecting property tax. The platform has also facilitated the scale-up of property registration and taxation schemes.

  • 92%


    of properties registered, representing an increase of 73%.

  • 70%


    of properties issued a tax notice, representing an increase of 50.9%.

  • 5 624


    additional taxpayers, representing an increase of 15%.

  • +1,67


    millions in additional tax revenue.

Impact study methodology

Between 2022 and 2025, FID supported an impact evaluation based on a randomized controlled trial (RCT) covering 194 cadastral sections and 80,000 plots of land, which were randomly assigned to 97 treatment sections and 97 similar sections as a comparison group. These findings were supported by a data analysis of the self-reported surveys conducted from July to August 2025.

The impact evaluation addressed three research questions

  • 01
    How effective is the program in terms of collecting tax revenue?

    • The more reliable land registry database and automated system for issuing tax notices have significantly improved property tax collection.

      The initiative has improved every stage of property tax administration, from registration to the issuing of tax notices. As a result of the geolocated property survey, 92% of properties (38,900) are now registered in the new database and 86% have been identified as taxable, compared with less than 20% under the previous system. A tax notice was issued for 73% of these properties (26,412), thereby doubling the likelihood of a property being matched to a notice. These improvements stem from a more accurate database, which corrects the vast amount of obsolete information (property owners, addresses, etc.) that made collecting tax more difficult in the past. The evaluation has also shown that, because of these changes, there has been a significant increase in the tax revenue collected. On account of the program, 18,465 additional tax notices were issued (rising from 10% to 60.9%), 5,624 additional payments were recorded (with the compliance rate increasing from 9% to 24.5%) and 10 billion CFA francs (€1.67 million) in additional revenue was collected across the study area.

  • 02
    Does using a formula to assess property values make the tax system more reliable and fairer?

    • Using an algorithm to value real estate helps reduce unequal treatment among taxpayers.

      The formula estimates market rental values more objectively, while also making tax estimates more equitable. The findings show that the discretionary valuation method previously used by tax authorities resulted in real estate values being substantially underestimated, particularly high-value properties, leading to potential revenue losses and significant inequities. This method also reduces horizontal inequity, as similar properties are much more likely to be taxed at similar amounts.

  • 03
    How do taxpayers view the new system, and does it affect compliance?

    • The more reliable and transparent system for property tax management has improved taxpayers' perceptions and willingness to file their tax returns and pay taxes.

      The final survey, which was self-reported and conducted among a representative sample of nearly 4,000 property owners in the Dakar region, 1,600 tenants and 200 neighborhood representatives, supported the findings from the administrative data: the probability of being issued a tax notice rose from 16% to 48%, and the likelihood of paying from 21% to 36%. Taxpayers also have a better understanding of how property tax works, with awareness that it goes toward funding local authorities rising from 30% to 34%. They also now consider the system more transparent: the proportion of those who stated that informal payments are common practice fell from 10% to 7%.

      These findings prompted the Senegalese Ministry of the Economy and Finance to scale-up the scheme nationwide with the support of a Proof of Impact and Public Policy (PIPP) from FID for 2026-2028.

Find out more

  • Research

    • Knebelmann, Justine ; Pouliquen, Victor ; Sarr, Bassirou (2024).

      "Discretion versus Algorithms: Bureaucrats and Tax Equity in Senegal".

      Working Paper.

    • Knebelmann, Justine (2023).

      “Adopting an algorithm improves tax equity when bureaucrats undervalue the wealth of the richest”.

      Guest blog by Justine Knebelmann. World bank blogs.

    • Knebelmann, Justine (2019).

      “Taxing property owners in Dakar”.

      Policy Brief, International Growth center.

  • Media

    • “La taxe foncière, un levier stratégique pour le Sénégal”.

      Le Soleil, july 2025.