Thesis (Ph.D.) - Cairo University - Faculty of Economics and Political Science - Department of Economics

This thesis presents Nighttime Light (NTL) as a potential instrument for estimating and predict-ing GDP for Egypt at the national and sub-national levels, when data are not very consistent. NTL involves a remote sensing technique, reflecting artificial human lighting and human eco-nomic activity on Earth. To the best of the author{u2019}s knowledge, the study is the first to compute regional GDP dataset for Egyptian governorates over an extending period of time FY08-FY13. Using this dataset, the study is also the first to estimate the association between NTL and real regional GDP in Egypt. The thesis uses regional GDP and NTL for 27 governorates over the pe-riod FY08-FY13, and estimates log-log equations using the panel-error corrected model. The study found that NTL is significantly correlated with regional GDP and can predict GDP at the national and sub-national levels in Egypt, which affirms most previous research findings. The study is divided into four chapters, in addition to introduction, conclusion, references and appendices. Chapter II explains the NTL data source and nature, and NTL literature. Chapter III explains how GGP is computed and how NTL data are extracted and processed. Chapter IV ana-lyses the performance of GGP and NTL, and shows both measures interaction in Egypt and within Egypt. The fifth chapter examines empirically the relation between NTL and GGP for the 27 Egyptian governorates over the period FY08-FY13

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