In most developing countries, tax collection capacity remains inadequately low. Nowhere is the lack of tax collection capacity more apparent than in local governments, which collect a negligible fraction of local income in taxes (Gordon, 2010). As a result, local governments provide inadequately low levels of public goods - such as roads, schools and electricity - which are crucial inputs in order for developing countries to achieve structural change and economic growth.
The goal of this project is to identify the key constraints on local government tax collection capacity. We focus on the case of Ghana, which is one of the most developed countries in Sub-Saharan Africa, and a stable democracy, and yet which collects less than two percent of GDP in local tax revenues (Government of Ghana, District Assemblies Common Fund, 2014). Moreover, the low levels of local taxation are widely acknowledged to be a constraint on growth and development by the Ghanian government, and policymakers do not agree on how best to promote greater revenue collections (Government of Ghana, Ministry of Finance and Ministry of Local Government and Rural Development, 2015).
This project consists of two basic stages. In Stage I, we will build the most comprehensive database in existence of local taxation capacity in Ghana. To do so, we will begin by digitising complete records of revenues by source, such as property taxes and business licenses, as well as collection costs and administrative costs of revenue collection. We will then design a new survey instrument about tax collection practices and technologies used for identifying revenue sources, valuation of properties, enforcement of payments and tax collection strategies more broadly. We will use this survey to interview the main government officials in each of Ghana's 216 district governments, and quantify their capacity on each of the key metrics. Our surveys will build on the firm surveys of Bloom and Van Reenen (2007), and the surveys of central government civil servants in Ghana of Rasul, Rogger and Williams (2016), which have led to a great interest among both academics and policymakers.
We will use our database to characterise "best practice" among local governments on several main dimensions: identification of revenue sources, tax collection technology usage, tax enforcement strategies, property valuation techniques, and openness to improvements in tax collection capacity and new technologies. The surveys will help inform which constraints most binding for local governments in terms of revenue collections, and which interventions will be most effective in raising local tax collections.
In Stage II of the project, we will use our findings from Stage I to conduct a randomised controlled trial on local governments, introducing a combination of new technologies and new tax collection methods, and assessing the impact on district revenue collections. The current proposal covers Stage I; we describe Stage I and II in more detail below.