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Record W2095131522 · doi:10.5539/ass.v9n9p270

Effect of Macroeconomic Variables on the FDI inflows: The Moderating Role of Political Stability: An Evidence from Pakistan

2013· article· en· W2095131522 on OpenAlexvenueno aff
Arfan Shahzad, Abdullah Kaid Al‐Swidi

Bibliographic record

VenueAsian Social Science · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsnot available
Fundersnot available
KeywordsForeign direct investmentBalance of paymentsEconomicsInflation (cosmology)Political stabilityMonetary economicsModerationStatistical softwarePoliticsInvestment (military)PaymentInflation rateRegression analysisInternational economicsAugmented Dickey–Fuller testEconometricsMacroeconomicsInterest rateStatisticsMathematicsFinanceCointegration

Abstract

fetched live from OpenAlex

This study has examined the moderating role of Political Stability (PS) on the relationships between macroeconomic variables and the Foreign Direct Investment (FDI) inflows in Pakistan. For that purpose, this study used the authentic annual data for the period 1991 to 2011. The empirical analysis involved using the ADF test to check the stationary of the data, the EViews software and hierarchal regression using SPSS 19.0 statistical software package. The results of the study confirmed that that GDP growth rate, exports, imports and balance of payment have positive significant effects on FDI inflows in Pakistan. On the other hand, the inflation rate was not significant in determining the FDI inflows in the country. However, the GDP growth rate and Balance of Payment tends to be a significant determinant of FDI inflows when the moderating effect of the Political stability is accounted for. Based on the findings of this study, it is strongly suggested that political stability is crucial for the country’s domestic and foreign investment expansion in the future course of direction.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.735
Threshold uncertainty score0.997

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 studies0.0000.001
Scholarly communication0.0000.001
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 head0.014
GPT teacher head0.269
Teacher spread0.254 · 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 designTheoretical or conceptual
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

Citations45
Published2013
Admission routes1
Has abstractyes

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