A Time Series Analysis of District-wise Government Spending
Submitted by Gaurav Godhwani (@gggodhwani) on Saturday, 31 March 2018
Section: Full talk Technical level: Beginner
About District Treasuries: District Treasuries are the nodal offices for all financial transactions of the Government within the district, managing both payment and receipts. They also monitors the activities of various sub-treasuries which work as an extension of the Treasuries at the Tehsil/Taluka level. Each district has various Drawing & Disbursing Officers who are authorised to draw money can present their claims in the Treasury which are then accounted by concerned authorities. Various states in India have developed Integrated Financial Management System which publishes detailed information of daily transactions happening at district treasuries within a state.
About Time Series Analysis & Inferences: The detailed information of daily transactions at district treasury can helps us perform near real-time tracking of flow and utilisation of funds. This can be used to track expenditure on various schemes and social sectors, anomalies in fund disbursement, understanding near real-time alerts and predicting timely utilization of budgets. In this talk, we will explore how we can harness time-series modelling and analysis to better understand functioning of various district treasuries in India.
The session will be organized as:
- Setting the scene
- Getting the District Treasuries Data
- Exploratory Data Analysis of the District Fund Flow
- Evaluation of various Time Series Algorithms
- Visualizing trends and the big picture
- Scaling Up
- How you can contribute
Gaurav Godhwani is working as the technical lead with Centre for Budget and Governance Accountability, majorly focussing on Open Budgets India initiative. He has served as co-founder and chapter leader for DataKind Bangalore, building a team of pro-bono data scientists to help nonprofits start projects addressing critical humanitarian problems and explore how data science can be applied to solve these challenges. He has previously led data projects at Goibibo and PromptCloud, later focusing his work towards data-for-good ecosystem. He is a passionate open data and open source contributor.