Marty Oehme
6e4f19ac3f
Fixed the measures and directions collected to use Gini, Atkinson, .. measures or absolute employment, poverty, etc.
48 lines
2.8 KiB
YAML
48 lines
2.8 KiB
YAML
author: Adam, C., Bevan, D., & Gollin, D.
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year: 2018
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title: "Rural-urban linkages, public investment and transport costs: The case of tanzania"
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publisher: World Development
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uri: https://doi.org/10.1016/j.worlddev.2016.08.013
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pubtype: article
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discipline: development
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country: Tanzania
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period: 2001
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maxlength:
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targeting: explicit
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group: rural workers
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data: national Tanzania Social Accounting Matrix (SAM, 2001); national administrative survey Integrated Labor Force Survey (2001), Tanzania Agricultural Sample Census (2003)
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design: quasi-experimental
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method: general equilibrium model
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sample: 7
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unit: household
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representativeness: subnational, rural
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causal: 1 # 0 correlation / 1 causal
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theory: transport cost burden approach
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limitations: can not account for population change (e.g. pop growth); causality based on model only
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observation:
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- intervention: infrastructure
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institutional: 0
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structural: 1
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agency: 0
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inequality: spatial; income
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type: 1 # 0 vertical / 1 horizontal
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indicator: 0 # 0 absolute / 1 relative
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measures: real consumption wage differences
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findings: results depend on financing scheme, each financing scheme entails some households being worse off; rural households worse off when infrastructure is deficit-financed or paid through tariff revenue; rural households benefit most when financed through consumption taxes or by external aid
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channels: movement of rural workers out of quasi-subsistence agriculture to other locations and sectors
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direction: -1
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significance: 2 # 0 nsg / 1 msg / 2 sg
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notes: there can be spatial differences to how connected regions within a country are to markets purely due to transport costs
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annotation: |
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A study modeling the effects of transport infrastructure investments in Tanzania on rural income inequalities and household welfare inequalities, modeled through consumption indicators.
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Generally it finds that the results of public investment measures into transport infrastructure largely depend on the financing scheme used.
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Comparing four financing schemes when looking at the effects on rural households, it finds that they are generally worse off when the development is deficit-financed or paid through tariff revenues.
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On the other hand, rural households benefit through increased income from measures financed through consumption taxes, or by external aid.
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The general finding is that there is no pareto optimum for any of the investment measures for all locations,
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and that much of the increases in welfare are based on movement of rural workers out of quasi-subsistence agriculture to other locations and other sectors.
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The study creates causal inferences but is limited in its modeling approach representing a limited subset of empirical possibility spaces,
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as well as having to make the assumption of no population growth for measures to hold.
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