D?viz kuru ve ekonomik b?y?me ekseninde Krugman 45 Derece Kural?'n?n ge?erlili?i: K?resel bir analiz
Bibliographic record
Abstract
?lkeler aras? b?y?me oranlar? fark?n?n, ?lkelerin toplam talebindeki b?y?me farkl?l?klar?ndan kaynakland??? savunulmaktad?r. D??a a??k bir ekonomide b?y?meyi k?s?tlayan temel fakt?r d?? ?demeler dengesidir. Krugman (1988) ?lkeler aras? toplam ?retim kapasitelerinde ?nemli farkl?l?klar olmas?na ra?men, reel kur de?erlerinin de?i?memesinin teoriye uymamas? kar??s?ndaki eksikli?i ifade etmi?tir. Krugman'a g?re ?lkelerin b?y?me oranlar? ile d?? ticaretin gelir esnekli?i, ancak kavramlar aras?nda sistematik bir ili?ki varsa ba?da?t?r?labilir. Krugman ihracat ile ithalat talebinin gelir esnekli?i ve b?y?me oranlar? aras?ndaki ili?kiyi ortaya koymu?, bu yakla??ma da ?45 Derece Kural?? ad?n? vermi?tir. ?hracat talebinin gelir esnekli?inin, ithalat talebinin gelir esnekli?e oran? ile ?lkelerin b?y?me oran? aras?nda do?rusal bir ili?ki bulunmaktad?r. Bu ?al??mada, Krugman 45 Derece Kural?'n?n ge?erlili?inin test edilmesi amac?yla panel veri analizi uygulanm??t?r. Analize konu olan 14 ?lke (Avusturalya, Avusturya, Bel?ika, Brezilya, Kanada, ?in, Fransa, Almanya, ?talya, Japonya, Hollanda, T?rkiye, ?ngiltere ve Amerika) G20 ?lkeleri aras?ndan se?ilmi?tir. ?ncelikle paneli olu?turan serilerin dura?anl??? incelenmi?, ard?ndan ortak ili?kili etkiler modeli (common correlated effects model) yard?m?yla ampirik sonu?lar elde edilmi?tir. Elde edilen bulgulara g?re, s?z konusu 14 ?lke i?in Krugman 45 Derece Kural?'n?n ge?erli?i oldu?u sonucuna ula??lm??t?r. ?lkelerin b?y?me oranlar? ile ihracat ve ithalat talebinin gelir esnekli?i aras?nda sistematik bir ili?ki vard?r. It is argued that the difference of the growth rates between countries is based on the growth diversity of aggregate demand of the countries. The main factor that restricts economic growth in an open economy is the balance of international payments. Krugman (1988) stated that, although there are significant differences between countries? total production capacities, the real exchange rates remain the same which does not fit the theory. According to Krugman, countries? growth rate and the income elasticity of foreign trade can be reconciled if only there is a systematic relation between the two concepts. Krugman introduced the relation between the income elasticity of export and import demands and growth rate, and later named this approach as ?45 Degree Rule?. There is a linear relation between the rate of income elasticities of export demand over import demand and countries? growth rates. In this study, panel data analysis is applied to test the validity of Krugman?s 45 Degree Rule. The 14 countries (Australia, Austria, Belgium, Brazil, Canada, China, France, Germany, Italy, Japan, Holland, Turkey, England and United States of America) participated in this analysis are chosen from the G20 countries. Primarily, stationarity of the series, which generate the panel data, is analyzed with panel unit root tests. Afterwards, empirical results are obtained by the help of common correlated effects model. According to the empirical findings, Krugman?s 45 Degree Rule is valid for those 14 countries and there is a systematic relationship between these countries? growth rate and income elasticities of export and import demand.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.005 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".