Citizen participation and mobilization of local tax resources in Benin: case of built and unbuilt property taxes.

Last registered on December 18, 2019

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Pre-Trial

Trial Information

General Information

Title

Citizen participation and mobilization of local tax resources in Benin: case of built and unbuilt property taxes.

RCT ID

AEARCTR-0005060

Initial registration date

December 18, 2019

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published

December 18, 2019, 10:54 AM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Country

Benin

Region

Afrique de l'Ouest

Primary Investigator

Name

Damas HOUNSOUNON

Affiliation

Direction Générale des Impôts du Bénin

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Françoise HOUNKPEVI

PI Affiliation

Université d'Abomey-Calavi

Contact Investigator

PI Name

Balbine AHOMAGNON

PI Affiliation

Ministère des Travaux Publics et des Transports

Contact Investigator

PI Name

Jonas FASSINOU

PI Affiliation

CREP INTERNATIONAL - BENIN

Contact Investigator

Additional Trial Information

Status

On going

Start date

2019-07-01

End date

2021-03-31

Keywords

Other

Additional Keywords

Property tax, causal effect, performance, cluster randomization

JEL code(s)

Secondary IDs

Abstract

This research project aims to assess the causal impact of educating landowner’s taxpayers on the importance of paying the properties taxes (incentives and coercives measures) on the recovery level of properties tax in Benin. With the involvement of the tax administration and the local politico-administrative authorities, respectively persuasive and dissuasive information and sensitization sessions will be organized for two treatment groups, while a control group will be left in a situation of statuquo, that is to say without any information, neither of persuasion nor deterrence. A randomized experimental approach by clusters of 84 treatment villages (42 per treatment) and 42 villages controls based on data geo-localized with remote villages of at least 15 km will be adopted. The analysis of the results from our study will allow us to conclude on the policy option that would best contribute to the improvement of property tax mobilization performance in Benin.

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Ce projet d’étude a pour but d'évaluer l’impact causal de la sensibilisation des contribuables propriétaires terriens sur l'importance de payer les impôts fonciers (mesures incitatives et coercitives) sur le niveau de recouvrement de ces impôts au Bénin. Avec l’implication de l’administration fiscale et des autorités politico-administratives locales, des séances d’information et de sensibilisation de natures respectivement persuasive et dissuasive seront organisées à l’intention de deux groupes de traitement tandis qu'un groupe de contrôle sera laissé dans une situation de statuquo, c’est-à-dire sans aucune information, ni de persuasion, ni de dissuasion. Une approche expérimentale randomisée par clusters sur 84 villages de traitement (42 par traitement) et 42 villages de contrôles sur la base de données géo-localisées avec des villages distants d’au moins 15 km sera adoptée. L’analyse des résultats provenant de notre étude nous permettra de conclure sur l’option de politique qui contribuerait au mieux à l’amélioration de la performance de mobilisation des taxes foncières au Bénin.

External Link(s)

Registration Citation

Citation

AHOMAGNON, Balbine et al. 2019. "Citizen participation and mobilization of local tax resources in Benin: case of built and unbuilt property taxes.." AEA RCT Registry. December 18. https://doi.org/10.1257/rct.5060-1.0

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Experimental Details

Interventions

Intervention(s)

The proposed intervention is designed to assess the impact of taxpayer awareness on the importance of paying property taxes. Information and awareness sessions will be organized for a treatment group while a control group will be left in a situation of statuquo, that is to say without any information or persuasion, nor deterrence.

The assessment focuses on two types of intervention, and thus in turn two treatments:

(i) Sensitizing a first treatment group about what a property tax is and why it has to be paid. These are the incentives;
(ii) Informing (also information sessions) a second group of treatment on what a property tax is and the penalties that await them if they do not pay this tax

Intervention Start Date

2020-04-01

Intervention End Date

2020-06-30

Primary Outcomes

Primary Outcomes (end points)

The decision to pay or not the property taxes (binary qualitative variable)

Primary Outcomes (explanation)

It is a qualitative and binary variable which takes the value 1 when the landowner comes to pay his property taxes after receipt of the tax notice and 0 otherwise. Recall that the eligible owners are those who did not respond favorably to the tax notices distributed in 2019. These data will be easily collected from the administrative data available from the Center for Small and Medium Enterprises Taxes (CIPEs).

Secondary Outcomes

Secondary Outcomes (end points)

The property tax payment rate (ratio between the amount of the tax notice and the amount paid by the taxpayer)

Secondary Outcomes (explanation)

It expresses the relationship between the amount paid by the taxpayer and the amount of the tax notice. It is determined by the following formula:
TRF = (amount paid by the taxpayer) / (amount owed by the taxpayer)
It is therefore a quantitative variable that measures the rate of settlement of the property tax by the taxpayer on behalf of the year considered. This rate will be determined on the basis of administrative data collected from CIPEs from the list of landowners selected for our study.

Experimental Design

In this study, we are adopting a randomized approach by village. On the basis of the power calculations, a total number of 42 villages per commune subdivided into 3 subgroups including 2 treatment subgroups and a control subgroup of 14 villages each will be considered with a sample of 44 landowners (including including 12% attrition) chosen randomly from the lists of taxpayers who received tax notices in 2019 and who did not pay their taxes. This list is available in the Small and Medium Business Tax Centers (CIPEs). The villages were randomly chosen in the communes of Cotonou, Abomey-Calavi and Parakou which cover more than 80% of the 31 CIPEs unequally distributed over the entire extent of the national territory. Indeed, In all municipalities there is no Small Business Tax Center (CIPE) in which taxpayers must pay their property taxes. There are only 31 CIPEs unequally distributed in the 77 communes of Benin with a concentration in the departments of the Atlantic, Littoral and Borgou. To ensure the same chance for all taxpayers in our sample to have a CIPE nearby in which they can easily and freely pay their property taxes, we will choose these three municipalities above.
In addition, these 3 selected municipalities have approximately the same levels of development; which will allow us to ensure comparability of results.
Thus, 126 villages, that is to say 5,444 owners chosen at random will be concerned by the study, that is to say 1882 landowners will receive the first treatment (incentives), 1882 landowners will receive the second treatment (dissuasive measures) and 1680 for the control group. All the villages selected for this study are at least 10 km apart from each other in order to avoid contamination problems.

Experimental Design Details

Randomization Method

Randomization was carried out in two stages.
- We calculated from the list of all villages in Benin with their geographic coordinates obtained from the National Geography Institute (IGN), the distances between each of these villages in pairs via the STATA software. For the rest, we only selected the villages which are at least 10 km apart from each other; which brings the total workforce to 510 villages for the 3 municipalities considered.
- From these 510 villages, we carried out from STATA software the random assignment of villages for the three subgroups selected: the two treatment subgroups and the control subgroup.

Randomization Unit

The level of randomization used is the village. This is a randomized cluster approach for both of the treatments selected.

Was the treatment clustered?

Yes

Experiment Characteristics

Sample size: planned number of clusters

126 villages

Sample size: planned number of observations

5444 landowners.

Sample size (or number of clusters) by treatment arms

We retained a total of 42 villages for our first treatment (incentive measures); 42 for the second treatment (dissuasive measures) and 42 control villages.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

1,20

Supporting Documents and Materials

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