Abstract:The proposed evaluation scheme is a uni-equation model to evaluate properties of Mass Appraisal (MA) in terms of widespread availability of sample data. It all allows the use of statistical models and in the opposite conditions of the absence of data of comparable properties, the functions of similar market areas are known as well as the ones near to those for which you want to estimate the function. Of course, the accuracy of the evaluation increases with the amount of available data, with other equal conditions and evaluations carried out without data (but in the presence of other market information). It requires extra-statistical appraisal procedures involving a complete knowledge of the real estate market. However, such knowledge is also required in the MA performed by quantitative models with regard to the data sampling and performance monitoring process. The model considers micro-level characteristics of the properties and macro-level parameters of the real estate market segments. The appraisal model defines the prediction function with both the statistical models and estimation procedures. For this purpose, the model considers four specific situations: the construction of a statistical model operating with a sufficiently large sample of market prices; the construction of a prediction function operating with a very few number of market prices samples; in this situation, the appraisal function of market value is defined by using a sample of market prices referred to comparable properties, and these are few for statistical use but perfectly suitable to the appraisal process; the construction of a prediction function operating with only one market price; the construction of a prediction function operating in the absence of real estate data but with similar functions of market areas with other estimated proprieties. The presented model provides a uniform method of estimating the market value of properties (and fees), through the modular functions. The model studied is able to operate also with reduced information, considering the practical circumstances, the boundary conditions, the application precautions and the significance of the results.
This study proposes an innovative methodology, named Repeat Appraised Price Model (RAV), useful for determining the price index numbers for real estate markets and the corresponding index numbers of hedonic prices of main real estate characteristics in the case of a lack of data. The methodological approach proposed in this paper aims to appraise the time series of price index numbers. It integrates the principles of the method of repeat sales with the peculiarities of the Hedonic Price Method, overcoming the problem of an almost total absence of repeat sales for the same property in a given time range; on the other hand, the technique aims to overcome the limitation of the repeat sales technique concerning the inability to take into account the characteristics of individual properties.
Appraisals are based on regression models. Its major application limits are all in situations in which the real estate market doesn't offer a sufficient number of comparables to implement statistical tools. In low-transaction real estate markets, the most effective appraisal method is the market comparison approach (MCA). The application limits of MCA depend on the degree of similarity between the properties' characteristics and the reliability of the prices of comparables. In this paper, we introduce some rational measurements in order to guarantee a scientific approach to MCA is associated with the correct prices. Our method is able to restore appraisals of the market value of any type of property, even in situations in which the comparables are limited or when the reliability of the buying and selling prices could be better.The International Valuation Standards (IVS) are internationally recognized appraisal methods used in the market-oriented approach, the income approach, and the cost approach. When a real estate market is active and all necessary market data are available, the market comparison approach (MCA) is the most direct, probative, and documented method used to appraise real estate market values (Simonotti, 2006); in particular, the MCA is the most important method and is comparable to the marketoriented approach. The MCA is known by several different names in the appraisal literature. In some of the older literature it is called the market data approach, while elsewhere it is referred to as the grid adjustment technique.There are many appraisal procedures that can be used in the logic application of the MCA. These procedures are grouped into two categories: (1) quantitative techniques based on detection of objective markets data (paired data analysis, graphic analysis, trend analysis, secondary data analysis, adjustment grid method, etc.); and (2) qualitative techniques based on the analyst's subjective judgment (relative comparison analysis, personal interviews, etc.).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.