Real Estate as Investment Instruments in Poland Between 2020 and 2023
Bibliographic record
Abstract
Theoretical background: The article constitutes an analysis of the macroeconomic situation from 2020 to the first quarter of (Q1) in relation to real estate investments. Factors such as the COVID-19 pandemic, the influx of refugees to Poland, and rising inflation had a significant impact on investor behavior in the discussed market. The dynamic macroeconomic situation also led to changes in consumer and tenant preferences, while significantly affecting demand and supply. The years 2020–2023 (Q1) were characterized by a distinct specificity that accentuated the risks associated with real estate investments. This emphasized clear differences in various categories between real estate as investment assets and funds, securities, or other alternative investment methods. Purpose of the article: The aim of the article is to identify the risks associated with real estate investment in Poland during the period from 2020 to 2023 (Q1). It is also crucial to describe the macroeconomic aspects and their impact on the investment real estate market during the mentioned period. Research methods: The article presents the results of an empirical study aimed at identifying factors contributing to the increase in risk associated with real estate investment in the years 2020–2023 (Q1). Additionally, it was significant to verify the financing methods for the purchase of investment properties by the survey participants. The study was based on a survey questionnaire. A total of 250 respondents participated in the study, expressing their willingness to purchase their first or subsequent property for investment purposes during the years 2020–2023 (1Q). Respondents were asked 7 questions, including those related to factors influencing or hindering the completion of investment property transactions in the years 2020–2023 (Q1), as well as the method of financing the purchase and the reason why respondents utilized borrowed capital or relied solely on their own funds. Furthermore the article employed a research methodology that included critical analysis of secondary sources, as well as methods such as analysis, synthesis, description, deduction, induction, and reduction. The Polish and foreign literature related to investment and investment properties was subjected to analysis. Additionally, laws, resolutions, regulations, scientific works from other organizations, and reports were studied, serving as valuable sources of information about the real estate market situation from 2020 to 2023 (Q1). In formulating recommendations, a generalizing-synthesizing method was employed (deduction, reduction, induction). The inductive method aided in analyzing the significance and characteristics of investment properties. On the other hand, the deductive method was used to analyze the issue starting from the macroeconomic situation in Poland and delving into the changes in the investment real estate market. By making a critical analysis of the literature, the reduction technique was applied, thus, verifying the previously formulated hypotheses. Main findings: Based on the conducted analysis, it can be observed that the return on equity (ROE) from real estate investments takes on a negative value when investors partially use borrowed capital. This situation is influenced by high interest rates. However, alongside this factor, there is also a social element related to the high demand for property rentals. In the case of investors investing solely from their own sources, this leads to a return on equity ranging between 2.7% and 3.6% during the analyzed time period. The conducted analysis reveals that macroeconomic, social, and legal factors dynamically shape the demand and supply in the real estate market during the period from 2020 to 2023 (Q1). This is closely related to the decisions of investors aiming to invest their capital in investment properties.
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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 | 0.001 |
| 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) | 0.001 | 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".