feat(data): Extract SilveiraNeto2011

02-data/processed/relevant/SilveiraNeto2011.yml

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+author: Silveira Neto, R. D. M., & Azzoni, C. R.
+year: 2011
+title: Non-spatial government policies and regional income inequality in brazil
+publisher: Regional Studies
+uri: https://doi.org/10.1080/00343400903241485
+discipline: economics
+
+country: Brazil
+period: 1995-2005
+maxlength:
+targeting: implicit
+group: poor
+data: national administrative survey 'Pesquisa Nacional por Amostra de Domicılio' (PNAD)
+
+design: quasi-experimental
+method: beta convergence test; using Gini coefficient
+sample: 27
+unit: region
+representativeness: national
+causal: 1 # 0 correlation / 1 causal
+
+theory:
+limitations: limited underlying data only allows estimation of Bolsa impact at endline; minimum wage had to be estimated from minimum-wage equal job incomes
+observation:
+  - intervention: minimum wage; direct transfers (cash)
+    institutional: 1
+    structural: 0
+    agency: 1
+    inequality: spatial; income
+    type: 1 # 0 vertical / 1 horizontal
+    indicator: 1 # 0 absolute / 1 relative
+    measures: income
+    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%
+    channels: quasi-regional effects through predominant transfers to poorer regions
+    direction: 1 # -1 neg / 0 none / 1 pos
+    significance: 1 # 0 nsg / 1 msg / 2 sg
+
+notes:
+annotation: |
+  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.
+  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.
+  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.
+  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,
+  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.
+  Some limitations include limited underlying data only making it possible to estimate the cash transfer impacts for the analysis endline, 
+  and minimum wage effects having to be constructed from the effects wages equal to minimum-wage.