L
Lina Salanauskaite
Researcher at University of Antwerp
Publications - 11
Citations - 260
Lina Salanauskaite is an academic researcher from University of Antwerp. The author has contributed to research in topics: Poverty & Euromod. The author has an hindex of 7, co-authored 11 publications receiving 234 citations.
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GINI DP 82: The paradox of redistribution revisited: and that it may rest in peace?
TL;DR: This article showed that the relationship between the extent of targeting and redistributive impact over a broad set of empirical specifications, country selections and data sources has in fact become a very weak one.
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The paradox of redistribution revisited: and that it may rest in peace?
TL;DR: The relationship between the extent of targeting and redistributive impact over a broad set of empirical specifications, country selections and data sources has in fact become a very weak one as mentioned in this paper.
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For the Poor, but Not Only the Poor: On Optimal Pro-Poorness in Redistributive Policies
TL;DR: In this paper, a detailed disaggregated analysis reveals that most redistributive systems do contain subsystems that are strongly targeted to the poor by intent and by design, and they also show that a disaggregation over the function of social transfers is very relevant: old-age benefits are an important driver of the weak overall association.
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Is the neighbour’s grass greener? Comparing family support in Lithuania and four other New Member States
TL;DR: In this article, the authors disentangle the importance of each of these two factors, focusing on the family support system in Lithuania and comparing it with four other new member states, namely Estonia, Hungary, Slovenia and the Czech Republic, and employ the EUROMOD microsimulation tax-benefit model to test whether size or design has greater effects on child poverty reduction in Lithuania.
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Testing the statistical significance of microsimulation results : a plea
TL;DR: In this article, the authors argue that it is undesirable and unnecessary to test the statistical significance of results in the microsimulation literature, and they argue that simple statistical tests can be sufficient.