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The Effects of Mortgage Rate Regulation in the Russian Federation

2022· article· en· W4389254827 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBaikal Research Journal · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicRegional Socio-Economic Development Trends
Canadian institutionsnot available
Fundersnot available
KeywordsRussian federationReal estatePopulationSalaryQuarter (Canadian coin)EconomicsInterest rateMonetary policyEconomic policyBusinessFinanceMonetary economicsMarket economyGeography

Abstract

fetched live from OpenAlex

The main purpose of the present research is to define the impact of changes that took place in the monetary and credit policy of the Russian Federation. The changes touched upon the regulatory issues of mortgage lending which have influenced some aspects of life of the population, including the affordability factor of square meter housing prices in the Russian Federation. The article analyzes the money incomes of the population in the RF, including the main source of average salary, rates, volume and number of credits granted in the period from 2019 to the third quarter of 2021. This period reflects the current situation and takes into account the factor of economic consequences occurred during the pandemics, that is characterized by crisis in the economy. The research describes general trends in mortgage lending in the Russian Federation with the account of some factors. It also provides some solutions for the problems encountered, including the increase in the demand for housing and consequently growing real estate prices. The reduction in rates was aimed to increase affordability of housing, but in practice it had the opposite effect, when the rate cut led to increase in real estate prices. Based on the research findings, we can conclude that money and credit policy in the Russian Federation has failed in terms of mortgage rate regulation and that it is necessary to review the rate in the short-term.

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.

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)0.022
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.641
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.064
GPT teacher head0.406
Teacher spread0.342 · 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