Collect General Government Spending Data based on COFOG Function classification

Contract

This is a UNV contract. More about UNV contracts.

We expect the Online Volunteers’ contributions through this task to support our organization’s efforts towards compiling a costing SDGs model. The model is a stochastic frontier model that uses translog functions, where the input data are government spending and efficiency term that covers FDI, ODA, and debts. The model will be run as panel data covering all countries from 2000 to 2022. The data collected by the Online Volunteers will be used as input for the model, which will help in understanding the relationships between government spending, efficiency terms, and the impact they have on achieving the SDGs. This will ultimately support our efforts towards achieving the SDGs.

For the collection of data on government finance statistics, in particular, general government spending, based on the classification of COFOG functions, we seek support from 5 Online Volunteers, under the guidance of Nour Barnat, chief of the methodology unit at UNCTAD statistics in the context of the SDGs costing project for the UN summit on SDGs progress in 2023, in particular, volunteers will:

• Discuss and define the objective and data collection methodology for compiling costing SDGs model, specifically related to government spending and other related variables
• Develop/identify a methodology tool for data collection, if required, and propose an implementation plan.
• Identify and screen for data sources related to government spending, FDI, ODA, and debts. Source of data can be international organisation, national agencies such as NSOs and ministries, as well as official government annual/quarterly/monthly reports and publications. The national sources can provide information in official languages only. Please refer to the section language to determine the language needed for these tasks.
• Conduct data collection using the defined methodology and tools from selected sources.
• Compare data between different data sources and fill the gaps by merging consistent data from different data sources.
• Double-check existing data and validate the final datasets to be used.
• Create/prepare a report capturing findings related to government spending, based on the classification of COFOG functions, for use in the stochastic frontier model.
• Prepare R reports or other tools reports that automatise the data collection for easy future updates.

T The Online Volunteers will be provided with other collected data and will be requested to fill the gaps and to update on new releases. The volunteers will be expected to keep all the data and supporting files provided confidential.

The ideal candidate for this task should possess a strong understanding of data collection concepts, with prior experience in conducting quantitative data collection and analysis. Advanced knowledge of government spending, national account, COFOG classification, SDGs, ODA, FDI or related areas is an advantage. A post-graduate degree in finance, economics, statistics or related fields is preferred. Additionally, the candidate should have advanced computer skills and proficiency in analytical software such as SAS, R, etc. Strong analytical and writing skills are essential, as the candidate will be expected to present data in a clear and concise manner.