This project uses multiple sources of publicly accessible remotely sensed satellite data as the primary source for estimating Pakistan’s Gross Domestic Product (GDP) at the city level. In the absence of a formal System of Regional Accounts (SRA) which requires repeat economic censuses, the Regional Domestic Product (RDP) can be a sufficient statistic for tracking economic growth and development at lower administrative levels where identification and preparation (PC-I) of development projects takes place. The study intends to build a unique panel dataset of RDP estimates for Pakistan from 2010, using satellite imagery on night-time luminosity, Phyto mass growth, and machine learning algorithms. In addition to empowering local governance, this dataset can be leveraged to causally evaluate the allocative efficiency gains of public funds.
City Development Product (Cdp): Data Architecture For Sustained Economic Development In Pakistan
MR. MOHAMMAD AHMAD
The Fletcher School of Tufts University, United States of America