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Record W2906224885

An Analysis On China’S Economical Growth Perspectives

2016· article· en· W2906224885 on OpenAlexaboutno aff
Larisa Luchian, Irina Ionescu

Bibliographic record

VenueAnnals of Faculty of Economics · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsnot available
Fundersnot available
KeywordsChinaEconomicsPer capitaPosition (finance)Gross domestic productOrder (exchange)Quantitative analysis (chemistry)Real gross domestic productEconometric analysisMacroeconomicsEconomyGeographyFinance
DOInot available

Abstract

fetched live from OpenAlex

The current paper aims to give an overview upon the evolution of the Chinese economical growth over the past two decades. By combining two types of analyses, the paper would also like to look on China’s economical growth perspectives in the past two decades. Thus, in the first part of our study we illustrate the results of a descriptive, critical, subjective and qualitative analyses on the main macroeconomic indexes used in determining the economic performance of a country (GDP, GDP per capita, imports and exports). The second part of the paper consists of a quantitative analysis of China’s economical growth, which combines the results of a time series econometric modulation for the GDP macroeconomic variable, and the resulted forecast based on the previously determined pattern. We based our study on a period of time dating from 1990 to 2014, suggesting that China registered a positive evolution both in terms of GDP and GDP per capita, as well as in terms of commercial exchanges, as a result of an economic reform gradually applied. Moreover, in order to determine China’s position within the current hierarchy of power centers, the G7 states (USA, Japan, Great Britain, France, Germany, Canada and Italy) were also introduced in the analysis. In terms of GDP, the United States was an absolute global leader until 2014 when it was outrun by China. As for the quantitative analysis, the period of time taken into consideration was also between the first trimester of 1990 and the third trimester of 2014, the observed values having a trimestral frequency. The final part of the study shows the results of the GDP forecast based on the previously determined ARMA pattern, as well as the forecasts given by the main international organizations (IMF and OECD), claiming China’s worldwide supremacy in terms of GDP, both on a short term (until 2020 - IMF), as well as on a long term and a very long term (until 2045, when Canada will swipe first places - OECD). The main conclusions which can be drawn by this study claim that, despite the slowing down of the GDP increase rate, China became a worldwide leader. Nonetheless, in order for China to keep its status, it must continue its ascending path from the past few decades and reorient to improve its global competitiveness and to ensure its economic sustainability.

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 categoriesMeta-epidemiology (narrow)
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 score0.462
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
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 head0.088
GPT teacher head0.296
Teacher spread0.208 · 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.

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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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