Raveh, Ohad (2011): The Natural Resource Curse, Fiscal Decentralization, and Agglomeration Economies.
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Natural resource abundance is a blessing for some countries, yet is a curse for others. The degree of fiscal decentralization may account for this divergent outcome. Resources tend to locate in remote, non-agglomerated, and sparsely populated areas; a high degree of fiscal decentralization gives a resource abundant region an advantage in the inter-regional tax competition over capital so that it attracts some capital from agglomerated and densely populated regions. Given a sufficiently high agglomeration level, any such movement of capital would bring a loss of output in the agglomerated region that outweighs the sum of gains from resource income and increased output in the remote region – so that aggregate product in the economy drops. This theory is empirically tested -and confirmed- building on Sachs and Warner’s influential works on the resource curse, employing the World Bank’s Fiscal Decentralization Indicators, and taking the United States as a case study.
|Item Type:||MPRA Paper|
|Original Title:||The Natural Resource Curse, Fiscal Decentralization, and Agglomeration Economies|
|Keywords:||Natural Resources, Economic Growth, Resource Curse, Fiscal Decentralization, Agglomeration Economies, Tax Competition|
|Subjects:||O - Economic Development, Innovation, Technological Change, and Growth > O1 - Economic Development > O18 - Urban, Rural, Regional, and Transportation Analysis ; Housing ; Infrastructure
O - Economic Development, Innovation, Technological Change, and Growth > O5 - Economywide Country Studies > O57 - Comparative Studies of Countries
O - Economic Development, Innovation, Technological Change, and Growth > O1 - Economic Development > O13 - Agriculture ; Natural Resources ; Energy ; Environment ; Other Primary Products
Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q3 - Nonrenewable Resources and Conservation > Q33 - Resource Booms
C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C21 - Cross-Sectional Models ; Spatial Models ; Treatment Effect Models ; Quantile Regressions
|Depositing User:||Ohad Raveh|
|Date Deposited:||19. Mar 2011 19:06|
|Last Modified:||11. Mar 2015 10:05|
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