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Record W2475015460 · doi:10.5539/ass.v12n8p110

Is Access to Agribank Credit an Effective Tool in Improving Household Income? Evidence from the Northern Mountainous Region of Vietnam

2016· article· en· W2475015460 on OpenAlexvenueno aff
Đỗ Xuân Luận, Nguyen Thanh Vu, Kieu Thi Thu Huong, Duong Thi Thu Hang, Siegfried Bauer

Bibliographic record

VenueAsian Social Science · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsnot available
Fundersnot available
KeywordsLoanHousehold incomePovertyPopulationEconomicsPer capita incomePropensity score matchingDemographic economicsBusinessEconomic growthGeographyFinanceDemography

Abstract

fetched live from OpenAlex

<p class="a"><span lang="EN-US">Access to credit has been thought to be a key factor in rural development and poverty reduction. In Vietnam, the Vietnam Bank for Agriculture and Rural Development (Agribank) emerged from the mono-tier banking system in 1988 and performs as a profit-oriented commercial bank sustaining the development of rural areas. During the last two decades, the bank has clearly expanded its share of credit outstanding in total rural credit market volume and this process is in line with the trending development of the national economy. The aim of this study is to examine whether Agribank credit improves household income in the Northern Mountains of Vietnam, where the poor and ethnic minorities are overrepresented in the population. In order to create robust estimates, a joint consideration of all four matching algorithms (</span><span lang="EN-US">nearest-neighbor matching, radius matching, Kernel matching and stratification matching) </span><span lang="EN-US">is applied to the Propensity Score Matching. The study found that access to extension services, ethnicity, and total savings emerged as reliable predictors of credit access among household endowments. Loan volumes increase with total value of household assets. In addition, the impact of credit lies in the range increase of 14.56% to 43.78% of total income, 12.09% to 51.83% of per capita income and 43.64% to 111.60% of nonfarm income of household with credit access. The agricultural bank credit has contributed in improving household income in the Northern Mountains of Vietnam. Results in this study provide further support for the hypothesis that the remarkable progress in poverty reduction in the last two decades in Vietnam is partly attributed to the development of Agribank credit. Experiences of the Agribank in lending to rural areas could be worthwhile for intermediary financial institutions to support rural development in Vietnam.</span></p>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score0.837

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.268
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2016
Admission routes1
Has abstractyes

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