Abstract:
There are huge expectations that Tanzania’s current natural gas discoveries and extraction would provide significant growth in the economy. However, there are no empirical studies conducted to provide the understanding of the potential and efficient resource extraction paths, shadow prices, cost components and behavior of gas extracting firms, whether firm’s are operating in a manner predicted by Hotelling’s theory and its dynamic optimality condition. We use panel Feasible Generalized Least Squares (FGLS) method to estimate the extraction costs, test the Hotelling’s principle and estimate the shadow price. Furthermore, we use Excel Solver spreadsheet to simulate dynamic optimal cost path at range of discount rates. The result shows that the marginal cost is inversely related with the quantities extracted as stock of gas reserves diminishes. Similarly, taxes are inversely related to firm’s cost of extraction. The average shadow price estimated is $ 6.33 per million BTU which is closer to actual domestic price of natural gas. Hotelling’s principle is rejected given the range of discount rates and it suggests that natural gas firms in Tanzania are operating at sub-optimal level and the resource is not extracted in a manner predicted by the theory. We also found that the optimal cost path is decreasing with increasing quantities extracted for Songo Songo and Mnazi Bay natural gas fields. However, the cost path is not economical when higher discount rates are simulated. The study recommends on reviewing and examining other factors that affects extraction cost which might limit the attainment of dynamic optimal paths in gas operating firms. This should not be the choice of discount rates and tax levels only, but also issues like transfer pricing should be re-assessed. They might increase natural gas extraction costs and limit optimal extraction path in the country.
Keywords: Tanzania, natural gas extraction, Hotelling‟s principle, shadow price, optimal path, FGLS, excel solver.
