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Record W3114763750 · doi:10.1080/19186444.2020.1858676

Effect of domestic and foreign private investment on economic growth of Pakistan

2020· article· en· W3114763750 on OpenAlexvenueno aff
Malik Shahzad Shabbir, Misbah Bashir, Hina Munir Abbasi, Ghulam Yahya, Bilal Ahmed Abbasi

Bibliographic record

VenueTransnational Corporation Review · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsnot available
Fundersnot available
KeywordsDisequilibriumForeign direct investmentEconomicsInvestment (military)Error correction modelDeveloping countryMonetary economicsTime seriesCointegrationMacroeconomicsInternational economicsEconometricsEconomic growthStatistics

Abstract

fetched live from OpenAlex

The foreign and domestic investments have a significant contribution towards economic development for developing and developed economies especially for underdeveloped economies. The primary objective of this study is to investigate the causal connection between domestic and foreign private investment along with its impact on economic growth of Pakistan. Moreover, time-series data has been used from 1980 to 2017 and autoregressive distributed lags (ARDL) method is implied for the data analysis perspective. The long-run findings indicate that foreign private investment has a negative and insignificant impact on economic growth, whereas, domestic investment shows a statistical significance but positive impact on Pakistan economy. The short-run dynamic designates that both domestic and foreign private investment is significantly and positively associated with the growth rate. Whereas, error correction term (ECT) is correcting the disequilibrium of data 42.7% on annual basis. Finally, F-test shows that the overall model of this study is statistically significant.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.036
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.265
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 source (direct Gemma or distilled Codex), 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

Citations102
Published2020
Admission routes1
Has abstractno

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