Health Tax Initial Modelling

Contract

This is a UNV contract. More about UNV contracts.

UNDP, together with national governments and other partners, have collaborated to conduct health tax analyses in various low- and middle-income countries. These provide countries with estimates of the additional government revenue expected from increases in health tax rates and the associated decreases in consumption of the taxed products. These tax briefs are used as advocacy pieces for policymakers, as well as for the Ministry of Finance and Ministry of Health to present to other policymakers.

The Online Volunteer will contribute to the modelling of expected tax revenues from increases in the rates or structure of taxes on health-harming products. This will include research into the markets of these goods (the demand, supply information, leading brands’ prices, market share data) and tax rates and structures of tobacco, alcohol and sugar-sweetened beverages, all of which need to be inserted into an Excel-based model. The Online Volunteer will be assigned to a specific country and will need to familiarize themselves well with UNDP's Excel template to input the data necessary for health tax modelling. The Online Volunteer may additionally be involved in other data collection and modelling tasks, such as problem solving the model, in the case of unexpected results, or other health economic modelling. The UNDP Health and Development Unit will provide the required information, guidance and supervision. Upon completion, the online volunteer will be given due credit and receive a Certificate of Appreciation for their contribution. No financial compensation is provided for this online volunteering opportunity.

The Online Volunteers are expected to be proficient in Microsoft Excel. At a minimum, a bachelor's degree or equivalent in statistics, economics, public health, finance or a relevant field is needed to perform this task. Experience in and understanding of health taxation is considered an asset, as is quantitative modelling and forecasting.