Marty Oehme
6e4f19ac3f
Fixed the measures and directions collected to use Gini, Atkinson, .. measures or absolute employment, poverty, etc.
47 lines
2.5 KiB
YAML
47 lines
2.5 KiB
YAML
author: Silveira Neto, R. D. M., & Azzoni, C. R.
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year: 2011
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title: Non-spatial government policies and regional income inequality in brazil
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publisher: Regional Studies
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uri: https://doi.org/10.1080/00343400903241485
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pubtype: article
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discipline: economics
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country: Brazil
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period: 1995-2005
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maxlength:
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targeting: implicit
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group: poor
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data: national administrative survey 'Pesquisa Nacional por Amostra de Domicılio' (PNAD)
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design: quasi-experimental
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method: beta convergence test
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sample: 27
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unit: region
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representativeness: national
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causal: 1 # 0 correlation / 1 causal
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theory:
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limitations: limited underlying data only allows estimation of Bolsa impact at endline; minimum wage had to be estimated from minimum-wage equal job incomes
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observation:
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- intervention: minimum wage; direct transfers (cash)
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institutional: 1
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structural: 0
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agency: 1
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inequality: spatial; income
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type: 1 # 0 vertical / 1 horizontal
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indicator: 1 # 0 absolute / 1 relative
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measures: Gini coeff
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findings: incomes have converged between regions after introduction of cash transfer and minimum wage with both accounting for 26.2% of effect; minimum wage contributed 16.6% to overall Gini reduction, transfers 9.6%
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channels: quasi-regional effects through predominant transfers to poorer regions
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direction: -1 # -1 neg / 0 none / 1 pos
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significance: 2 # 0 nsg / 1 msg / 2 sg
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notes:
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annotation: |
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A study on the impacts of minimum wage and direct cash transfers in Brazil on the country's income inequality but especially the way the policies interact with spatial inequalities.
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It finds that incomes between regions have converged during the time frame and overall the cash transfers under the 'Bolsa Familia' programme and minimum wage were accounting for 26.2% of the effect.
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Minimum wage contributed 16.6% of the effect to overall Gini reduction between the regions while cash transfers accounted for 9.6% of the effect.
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The authors argue that this highlights the way even non-spatial policies can have a positive (or, with worse targeting or selection, negative) influence on spatial inequalities,
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as transfers occuring predominantly to poorer regions and minimum wages having larger impacts in those regions created quasi-regional effects without being explictly adressed in the policies.
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Some limitations include limited underlying data only making it possible to estimate the cash transfer impacts for the analysis endline,
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and minimum wage effects having to be constructed from the effects wages equal to minimum-wage.
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