Residential Real Estate as a Potential Hedge of Capital Against Inflation
Bibliographic record
Abstract
ABSTRACT There is a belief among investors that real estate is an excellent way to protect capital from depreciation due to inflation. Research does not provide a clear answer as to whether this investors’ belief is correct, but some approaches indicate that simple econometric methods are not able, especially in the short term, to clearly indicate the existence of a relationship between inflation and property prices (Fogler, 1984). The purpose of the study –was to find the relationship between residential real estate prices and inflation in the Polish economic conditions. Methodology of the study - the study used cointegration analysis with the Engle - Granger test. The research was carried out in the period from the first quarter of 2009 to the fourth quarter of 2021. The real estate hedonic indices calculated by NBP (National Bank of Poland) and the actual and forecasted inflation rates published by the GUS (Central Statistical Office) and the NBP (National Bank of Poland) were used in the research. The result - the analysis led to a negative verification of the research hypothesis, as it could not be proved that real estate prices were related to the level of inflation during the researched period. Originality/value - the study fills a gap in the Polish market regarding the analysis of the possibility of using real estate as a hedge against inflation. The research concerned only the Polish market, but this issue has not been taken up for years, also in mature economies.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".