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Record W2921902985

Economic Recession and Changing Consumption Patterns: Evidence from Lagos Metropolis.

2018· article· en· W2921902985 on OpenAlexaboutno aff
Suraju Abiodun Aminu, Oluwakemi Oludotun Oyefesobi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsRecessionConsumption (sociology)Purchasing powerQuarter (Canadian coin)Business cycleEconomicsConsumer spendingGross domestic productPurchasingEconomic indicatorDemographic economicsBusinessEconomic growthGeographyMacroeconomicsOperations management
DOInot available

Abstract

fetched live from OpenAlex

After two consecutive quarters of a negative growth rate in the Nigeria's gross domestic products (GDP), Nigeria was declared to be technically in a recession by the end of the second quarter of 2016. In addition to the review of the literature, a survey was also undertaken, involving 421 shoppers in the three outlets of Shoprite in Lagos metropolis, selected by a systematic sampling technique. Based on a dataset from the 421 respondents, the paper conducted a statistical analysis to detect the changes in the consumption patterns of the shoppers due to the current economic crisis in the country. Results of the correlation analysis showed that the current economic crisis in the country has significantly affected consumption patterns of majority of the respondents. The crisis has led a large number of respondents to substantially reduce consumption of luxury products and a simple majority to slightly reduce consumption of necessities. It was concluded that the recession has affected the purchasing power of consumers thus, leading to the changes in their consumption patterns. Both the policy and managerial implications of the finding were highlighted in the paper. Keywords: Business cycle, consumption patterns, consumers and economic recession.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.091
GPT teacher head0.309
Teacher spread0.219 · 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; both teacher heads agree on what is shown here.

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

Citations4
Published2018
Admission routes1
Has abstractyes

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