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Escaping from poverty trap: a choice between government transfer payments and public services

Overview of attention for article published in Global Health Research and Policy, June 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (56th percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

twitter
4 tweeters

Citations

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1 Dimensions

Readers on

mendeley
17 Mendeley
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Title
Escaping from poverty trap: a choice between government transfer payments and public services
Published in
Global Health Research and Policy, June 2017
DOI 10.1186/s41256-017-0035-x
Pubmed ID
Authors

Sixia Chen, Jianjun Li, Shengfeng Lu, Bo Xiong

Abstract

Anti-poverty has always been an important issue to be settled. What policies should be selected to help individuals escaping from the poverty trap: by directly offering transfer payments or indirectly providing public services? This paper is among the first to explore the effects of public anti-poverty programs system in China. We Using unbalanced panel data of China Health and Nutrition Survey (CHNS) from 1989 to 2009, we demonstrate how the individual poverty status is determined through a four-staged simultaneous model. We choose the 3SLS (Three Staged Linear Squared) methodology to do the estimation. GTPs (Government Transfer Payments) don't have positive effects on poverty reductions. The results demonstrate that GTPs increasing by 10% makes private transfer payments decrease by 3.9%. Meanwhile, GTPs increasing by 10% makes the household income decreased by 27.1%. However, public services (such as medical insurance, health services, hygiene protection etc.) have significantly positive impacts on poverty reduction. Public services share a part of living cost of the poor, and are conducive for people to gain higher household income. GTPs given by governments are not effective in reducing the poverty, as a result of "crowd-out effect" and "inductive effect". However, public services are suggested to be adopted by governments to help the poor out of the poverty trap.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 24%
Student > Doctoral Student 3 18%
Student > Ph. D. Student 2 12%
Professor > Associate Professor 2 12%
Student > Master 1 6%
Other 2 12%
Unknown 3 18%
Readers by discipline Count As %
Social Sciences 5 29%
Economics, Econometrics and Finance 5 29%
Nursing and Health Professions 1 6%
Business, Management and Accounting 1 6%
Environmental Science 1 6%
Other 1 6%
Unknown 3 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 December 2017.
All research outputs
#6,615,161
of 12,253,439 outputs
Outputs from Global Health Research and Policy
#36
of 62 outputs
Outputs of similar age
#143,510
of 341,979 outputs
Outputs of similar age from Global Health Research and Policy
#2
of 6 outputs
Altmetric has tracked 12,253,439 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 62 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 40th percentile – i.e., 40% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 341,979 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.