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Record W2974597808 · doi:10.5539/ibr.v12n10p75

The Growth Conundrum: Paul Romer’s Endogenous Growth

2019· article· en· W2974597808 on OpenAlexvenueno aff
Daniele Schilirò

Bibliographic record

VenueInternational Business Research · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Productivity
Canadian institutionsnot available
Fundersnot available
KeywordsRomerEconomicsEndogenous growth theoryEndogeneityTechnological changeExternalityIncentiveNeoclassical economicsProductivityPer capitaHuman capitalEconomic systemMicroeconomicsMarket economyEconomic growthMacroeconomicsSociology

Abstract

fetched live from OpenAlex

The explanation and causes of economic growth, the problem of convergence of per capita income among different economies, the low productivity growth in many advanced economies, and the presence of disrupting technological innovations remain at the center of the debate among economists. The present contribution analyzes the endogenous growth theory of Paul Romer and discusses its features and content through Romer’s main works on the topic. This study on Romer’s work highlights the existence and importance of increasing returns in the process of growth, the key role of knowledge, the ideas as non-rival goods, the existence of externalities, the endogeneity of technological change, and the primary role of human capital, especially in research activity. Institutions, such as property rights are important as well. The state also has a decisive role in education and the research sector. Another relevant aspect is that economic growth and technological change are closely interconnected; they cannot be separated. Romer’s theory of endogenous technological change ties the development of new ideas and economic growth to the number of people working in the knowledge sector. New ideas, being non-rival and partially excludable, are fundamental for growth since they make everyone producing physical goods and services more productive. Finally, Romer’s endogenous growth highlights the factors that provide incentives for knowledge creation; thus, his theory can also be considered a significant contribution to the theory of the knowledge-based economy.

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)0.002
metaresearch head score (Gemma)0.001
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.417
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.010

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 head0.104
GPT teacher head0.292
Teacher spread0.188 · 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 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

Citations21
Published2019
Admission routes1
Has abstractyes

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