Poverty Impacts of Government Expenditure from Natural Resource Revenues
This study analyzes the effects on poverty incidence and other economic variables resulting from government expenditures associated with natural resource revenues, using the Nam Theun II hydroelectric power project in the Lao People’s Democratic Republic (Lao PDR) as a case study. The analysis uses a multi-sector/multi-household general equilibrium model of the economy of Lao PDR. The conceptual framework distinguishes between official and marginal expenditures financed by project revenues, recognizing that some of the former still might have been undertaken without the new revenues generated... Mehr ...
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Dokumenttyp: | doc-type:workingPaper |
Erscheinungsdatum: | 2010 |
Verlag/Hrsg.: |
Manila: Asian Development Bank (ADB)
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Schlagwörter: | ddc:330 / D58 / I32 / Q25 / Poverty incidence / general equilibrium / natural resource revenues / Dutch disease / Lao PDR |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-29048984 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | http://hdl.handle.net/10419/109563 |
This study analyzes the effects on poverty incidence and other economic variables resulting from government expenditures associated with natural resource revenues, using the Nam Theun II hydroelectric power project in the Lao People’s Democratic Republic (Lao PDR) as a case study. The analysis uses a multi-sector/multi-household general equilibrium model of the economy of Lao PDR. The conceptual framework distinguishes between official and marginal expenditures financed by project revenues, recognizing that some of the former still might have been undertaken without the new revenues generated by the project. A range of assumptions is considered regarding the direct distributional impact of the marginal expenditures. The analysis also incorporates the project’s indirect distributional effects, operating through the "Dutch disease" mechanism. We find that poverty incidence declines under the entire range of distributional assumptions considered. Nevertheless, the most important determinant of poverty impact is the degree of rural bias. Even the most regressive of the pro-rural distributions reduces poverty incidence by seven times as much as the most progressive of the pro-urban distributions.