scholarly journals Cartographic Methods of Presentation the Average Transaction Prices of the Undeveloped Land

2018 ◽  
Vol 28 (2) ◽  
pp. 85-100 ◽  
Author(s):  
Marek Ogryzek ◽  
Mateusz Ciski
Keyword(s):  
Spatial Data ◽  
Selection Process ◽  
Real Estate Market ◽  
Regional Office ◽  
The Real Estate ◽  
Work Related ◽  
Transaction Prices ◽  
The Real Estate Market ◽  
Different Types ◽  
Potential Use

Abstract The article presents a description of basic cartographic methods used to visualize spatial data. Information on average transaction prices of the undeveloped land in Warmińsko-Mazurskie voivodeship, from The Agricultural Property Agency, Regional Office in Olsztyn, was the basis for map creation. Unified data allows the accurate presentation of information and highlights the differences in selected cartographic methods. The objective of this article is to describe the selection process of the best method for presenting spatial data by identifying the data structure and visualization purpose; as well as to describe the different types of data presentation for its potential use for work related to activities performed by professionals dealing with the real estate market and by individuals.

scholarly journals Evaluation of the Applicability of Statistical Methods in Studies on Price Dynamics on the Real Estate Market

2013 ◽  
Vol 21 (1) ◽  
pp. 49-58 ◽  
Author(s):  
Sebastian Kokot ◽  
Marcin Bas
Keyword(s):  
Real Estate ◽  
Traditional Approach ◽  
Real Estate Market ◽  
Price Dynamics ◽  
The Real ◽  
The Real Estate ◽  
Transaction Prices ◽  
Time Period ◽  
The Real Estate Market ◽  
Real Estate Prices

Abstract The specific character of the real estate market is the reason why observations of transaction prices seen as statistical variables are taken in a non-standard way. In the traditional approach each time period or specific moments of time are attributed with one observation of a studied variable per one object. In the case of the real estate market, this is not possible since transactions relate to different objects, i.e., properties, and occur at irregular, or even random, moments. This is why traditional methods used to examine the dynamics of economic phenomena must be adapted to specific conditions on the real estate market. Keeping that in mind, the aim of this paper is to adapt classical statistical examination methods of dynamics to specific conditions of the real estate market followed by the actual examination of the dynamics of real estate prices in three sub-segments of the housing market in Szczecin. On its basis, the authors evaluate various methods of examining real estate price dynamics in terms of their applicability in real estate appraisal procedures and, in a broader perspective, present characteristic phenomena that can be observed on the real estate market.

scholarly journals Use of Statistical Models for Simulating Transactions on the Real Estate Market

2015 ◽  
Vol 23 (2) ◽  
pp. 102-111 ◽  
Author(s):  
Radosław Cellmer ◽  
Katarzyna Szczepankowska
Keyword(s):  
Probability Distribution ◽  
Real Estate ◽  
Statistical Models ◽  
Real Estate Market ◽  
Model Parameters ◽  
The Real ◽  
The Real Estate ◽  
Transaction Prices ◽  
The Real Estate Market ◽  
Real Estate Prices

Abstract The regularities and relations between real estate prices and the factors that shape them may be presented in the form of statistical models, thanks to which the diagnosis and prediction of prices is possible. A formal description of empirical observation presented in the form of regressive models also offers a possibility for creating certain phenomena in a virtual dimension. Market phenomena cannot be fully described with the use of determinist models, which clarify only a part of price variation. The predicted price is, in this situation, a special case of implementing a random function. Assuming that other implementations are also possible, regressive models may constitute a basis for simulation, which results in the procurement of a future image of the market. Simulation may refer both to real estate prices and transaction prices. The basis for price simulation may be familiarity with the structure of the analyzed market data. Assuming that this structure has a static character, simulation of real estate prices is performed on the basis of familiarity with the probability distribution and a generator of random numbers. The basis for price simulation is familiarity with model parameters and probability distribution of the random factor. The study presents the core and theoretical description of a transaction simulation on the real estate market, as well as the results of an experiment regarding transaction prices of office real estate located within the area of the city of Olsztyn. The result of the study is a collection of virtual real properties with known features and simulated prices, constituting a reflection of market processes which may take place in the near future. Comparison between the simulated characteristic and actual transactions in turn allows the correctness of the description of reality by the model to be verified.

scholarly journals Diversified Price Dynamics in some Sub-Segments of the Housing Market

2015 ◽  
Vol 15 (1) ◽  
pp. 162-173
Author(s):  
Sebastian G. Kokot
Keyword(s):  
Real Estate ◽  
Price Index ◽  
Real Estate Market ◽  
Quality Of Data ◽  
The Real ◽  
The Real Estate ◽  
Transaction Prices ◽  
The Real Estate Market ◽  
Price Movements

Abstract The observation of price movements on the real estate market is an extremely difficult task as we have to face problems belonging to two spheres. The first of them is the specific nature of real estate as marketable objects and of the real estate market itself. The second one is the character and quality of data on real estate transaction prices. In this article the author, based on an empirical study, attempts to prove that even in a single segment of a local real estate market the prices in individual sub-segments can fluctuate with different intensity. The range of price movements can be so vast that it seems pointless to apply a single averaged price index for the whole segment, and usually that is what analysts do.

scholarly journals A GRID-Based Spatial Interpolation Method as a Tool Supporting Real Estate Market Analyses

2020 ◽  
Vol 9 (1) ◽  
pp. 39 ◽  
Author(s):  
Agnieszka Szczepańska ◽  
Dariusz Gościewski ◽  
Małgorzata Gerus-Gościewska
Keyword(s):  
Spatial Distribution ◽  
Real Estate ◽  
Spatial Data ◽  
Interpolation Method ◽  
Real Estate Market ◽  
Grid Structure ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market ◽  
Spatial Interpolation Method

The spatial distribution of prices is closely linked with the urban real estate market. Property prices are one of the key indicators of economic activity because they influence economic decisions. Decision-makers and consumers often need information about the spatial distribution of prices, but spatial-temporal analyses of the real estate market are based on the prices quoted in different locations across years (epochs). Due to this idiosyncrasy, the resulting datasets are dispersed (different across years) and difficult to compare. For this reason, the existing interpolation methods are not always effective in analyses of the real estate market. A different approach to interpolating real estate prices that supports the generation of continuous interpolated surfaces while maintaining the values of measurement points is thus needed. This paper proposes a method for replacing dispersed spatial data with a regular GRID structure. The GRID structure covers the measured object with a regular network of nodes, which supports uniform interpolation at every point of the analyzed space and a comparison of interpolation models in successive epochs (years). The proposed method was tested on a selected object. The results indicate that the GRID structure can be used in analyses of highly complex real estate markets where input data are incomplete, irregular and dispersed.

scholarly journals Identifying local differences with fused-MCP: an apartment rental market case study on geographical segmentation detection

2020 ◽  
Vol 3 (1) ◽  
pp. 183-214 ◽  
Author(s):  
Ryo Inoue ◽  
Rihoko Ishiyama ◽  
Ayako Sugiura
Keyword(s):  
Spatial Autocorrelation ◽  
Spatial Data ◽  
Real Estate Market ◽  
Spatial Analyses ◽  
The Real Estate ◽  
Local Characteristics ◽  
Estimated Parameters ◽  
The Real Estate Market

AbstractAs the variety and quality of spatial data increase in recent times, the potential to analyze local characteristics based on spatial data is getting stronger. Previous spatial analysis methods structuralize the spatial autocorrelation of data by the distances between data observation points and the contiguity of the data-observed regions. It is significant for the estimation of global characteristics of spatial data. However, these approaches are not suitable for identifying local differences from the data since they assume a smooth spatial autocorrelation structure. Generalized fused lasso, which can detect local differences in spatial data, has been proposed in machine learning studies. Its limitation is that the estimated parameters are biased toward zero; however, methods that overcome the limitation have also been proposed. Fused-MCP is one of those methods and is expected to be useful in spatial analyses. This study applies fused-MCP to spatial analyses. As an example of spatial analyses based on fused-MCP, this study analyzes the structure of geographical segmentation of the real estate market in central Tokyo. Fused-MCP is utilized to extract areas where the valuation standard is the same. The results reveal that the geographical segmentation displays hierarchal patterns. Specifically, the market is divided by municipalities, railway lines and stations, and neighborhoods. The case study confirmed the applicability of fused-MCP to spatial analyses.

scholarly journals The Use of the Geographically Weighted Regression for the Real Estate Market Analysis

2012 ◽  
Vol 11 (1) ◽  
pp. 19-32 ◽  
Author(s):  
Radosław Cellmer
Keyword(s):  
Real Estate ◽  
Geographically Weighted Regression ◽  
Real Estate Market ◽  
Weighted Regression ◽  
The Real ◽  
The Real Estate ◽  
Transaction Prices ◽  
The Real Estate Market ◽  
Market Transaction ◽  
Grading Scale

Abstract The article presents a method for developing geographically weighted regression models for analyzing real estate market transaction prices and evaluating the effect of selected property attributes on the prices and value of real estate. The property attributes were evaluated on a grading scale to determine the relative (percentage) indicators characterizing the relationships on the real estate market. The market data were analyzed to evaluate the influence of infrastructure availability on the prices of land in Olsztyn. The results were used to assess the effect of every utility service on the property transaction prices.

scholarly journals MICROECONOMICS OF ARCHITECTURE: BETWEEN MARKET AND PUBLIC

2020 ◽  
Vol Vol. 36 (No. 2) ◽  
pp. 85-90
Author(s):  
Valentinas Navickas ◽  
Tomas Skripkiunas
Keyword(s):  
Literature Review ◽  
Real Estate ◽  
Public Goods ◽  
Market Value ◽  
Real Estate Market ◽  
The Real ◽  
The Real Estate ◽  
Nonmarket Goods ◽  
The Real Estate Market ◽  
Different Types

The position of architecture between market goods and public goods is addressed in this study. A transition of architectural objects of built environment from market goods towards public or nonmarket goods is presented in literature review. The real estate market value is highly influenced by concepts of externalities and public goods, therefore being highly spatially dependent and making the process of the real estate valuation more complex. The internalization of these externalities and public goods is impossible because of the nature of public space in the city. The concept of value and different types of value, like exchange, use, image, social, environmental, cultural value, are also presented in literature review. These different types of value are transferred to value in exchange when estimating market value. The aim of research is to calculate the amount of the real estate market value that is influenced by externalities, public or nonmarket goods. The process of value transfers between market and public is also discussed in this study. In the research part prices of similar apartments measure the coefficient of variance. Newly constructed apartment buildings with partial finishing interior within city boundaries are selected expecting their price to vary only because of different amount of externalities and public goods available inside district/region of selected building or provided by the actual building itself. The results show that up to 29% of the real estate market value is influenced by public or nonmarket goods. Implications of further research suggest controlling for market segmentation and architectural quality variables

scholarly journals The Use of Indicator Kriging for Analyzing Prices in the Real Estate Market

2016 ◽  
Vol 24 (4) ◽  
pp. 5-15
Author(s):  
Katarzyna Kobylińska ◽  
Radosław Cellmer
Keyword(s):  
Real Estate ◽  
Spatial Information ◽  
Real Estate Market ◽  
Indicator Kriging ◽  
Geostatistical Simulation ◽  
The Real ◽  
The Real Estate ◽  
Geostatistical Methods ◽  
Transaction Prices ◽  
The Real Estate Market

Abstract The patterns and relations between real estate prices and the factors which shape them can be presented, among others, in the form of traditional statistical models, as well as by means of geostatistical methods. In the case of research involving the diagnosis and prediction of transaction prices, the key role is played by the spatial aspect, hence the particular significance of geostatistical methods using spatial information. The main goal of the conducted research is to determine the probability of the occurrence of a price in a given location in space by means of geostatistical simulation - indicator kriging. Indicator kriging does not use the entirety of information included in a dataset, and can, therefore, be useful in situations when the assumptions involving the spatial stationarity of the examined phenomenon are not fulfilled by an entire dataset, but are fulfilled by a certain part of the set. The maps of the probability with which a regionalized variable (price) takes on particular values, limited by arbitrarily selected cutoff values, were prepared by means of indicator kriging. An alternative approach to the preparation of price probability maps is the determination of the spatial distribution of areas in which, with the assumed probability, the value of the price falls within the predetermined ranges. The paper presents both the essence as well as a theoretical description of the geostatistical simulation of a transaction on the real estate market, as well as the results of an experiment involving the transaction prices of real properties located in the north-western part of the city of Olsztyn. The result of the research is a set of virtual information about the places in which the transactions have occurred and about the prices of real estate, constituting a reflection of the market processes which may take place in the near future.

scholarly journals Urban Greenery as a Component of Real Estate Value

2016 ◽  
Vol 24 (4) ◽  
pp. 79-87 ◽  
Author(s):  
Agnieszka Szczepańska ◽  
Iwona Krzywnicka ◽  
Grzegorz Lemański
Keyword(s):  
Real Estate ◽  
Real Estate Market ◽  
Urban Environments ◽  
Market Prices ◽  
The Real Estate ◽  
Transaction Prices ◽  
Urban Greenery ◽  
The Real Estate Market ◽  
Green Areas ◽  
Questionnaire Studies

Abstract Due to the specific characteristics of cities, such as the intensity of the use of space, the supply of green areas is limited. These areas are subjected to constant pressure (demand for new transportation or construction functions), which usually results in their reduction. As a consequence of this, green areas have become a limited asset in urban environments. City dwellers, seeking a high quality of life in the urban environment, pay attention to the proximity of greenery to their place of residence. This is, therefore, a factor that greatly influences market prices of residential real estate. In the study, the dependency of transaction prices of residential premises on the vicinity of urban greenery was subjected to analysis. Additionally, questionnaire studies were conducted with respect to the evaluation of the significance of environmental factors when choosing a place to live, which translates over to the decisions made by consumers on the real estate market.

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