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Record W4319710301 · doi:10.58886/jfi.v12i1.2295

Is Renting Better? A Review of the Home Ownership Decision amid Increasing Risk

2013· review· en· W4319710301 on OpenAlexaff
Rob Wolf, Dale L. Domian

Bibliographic record

VenueJournal of Finance Issues · 2013
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsYork University
Fundersnot available
KeywordsRentingEconomic rentReal estateValuation (finance)BusinessLeaseEquity (law)Cash flowActuarial scienceEconomicsCapitalization rateFinanceReal estate investment trustMicroeconomics

Abstract

fetched live from OpenAlex

There has always been an avid debate on the merits of owning versus renting a residence. There is a commonly accepted sentiment that owning a home is a wise investment. However, this sentiment is often unproven or supported with non-substantial evidence. The scholarly literature on the buy versus rent decision has conflicting results. Further, recent events in the US residential real estate market suggest increased asset riskiness which may have a dramatic effect on home ownership. Our research uses a capital budgeting model, similar to the lease versus buy analysis, with the output being the present value of buying instead of renting. The present value model includes the difference in cash flows between buying and renting for two standardized holding periods. A key contribution of the paper is a more accurate estimate of required return on equity, the discount rate in our present value model. As real estate values have recently demonstrated greater risk and the capital structure of homeowners may be highly leveraged, the cost of equity is higher than often suggested. The benchmark model uses point estimates for each variable with subsequent models including scenario analysis for key variables. The results suggest buying is better, in the benchmark model as well as scenarios allowing rents, home appreciation, mortgage rates and required return to vary. However, most scenarios show negative present values are possible, which contrasts the historic view that home ownership always has a positive return.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.971
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.069
GPT teacher head0.300
Teacher spread0.231 · 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; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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

Citations1
Published2013
Admission routes1
Has abstractyes

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