Determination of inflationary behavior: A comparative analysis
Bibliographic record
Abstract
Standard theory of consumer behavior stands on the maxim of utility maximization. Optimizing behavior of consumer is achieved by maximization of utility subject to budget constraint. An increase in inflation that is not accompanied by proportionate increase in income can leave a consumer worse off. Therefore, it is imperative for consumers to have right assessment about inflation which in turn requires appropriate modelling of inflationary behavior. This study assesses efficacies of different versions of new Keynesian Phillips curve for capturing dynamics of CPI inflation. Estimation of different formulations of this curve is achieved by employing generalized method of moments. This choice of estimation technique is made to handle potential problem of endogeneity. Countries with different resource and market structures are included to evaluate and compare fitness of different formulations for different economies. Economies of Pakistan and Turkey represent developing economies, economy of South-Korea is incorporated for emerging market economy and economies of Canada, UK and US are included for developed economies. The results of this study reveal that internal as well as external factors are crucial for explaining inflationary behavior of developing economies. Whereas, dynamics of domestic inflation for advanced economies are mostly explained by internal factors.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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".