# A Mass Appraisal Model Based on Market Segment Parameters

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## Abstract

**:**

## 1. Introduction

## 2. Literature Review

## 3. Base of the Valuation

## 4. Market Area

## 5. Appraisal Function

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- the first situation, construction of a statistical model operating with a sufficiently large sample of market prices;
- -
- the second situation, construction of a prediction function operating with a very few number of market prices samples;
- -
- the third situation, construction of a prediction function operating with only one market price;
- -
- the fourth situation, construction of a prediction function operating in the absence of real estate data but with similar functions of market areas with other estimated proprieties [2].

_{0}is the constant term (euro); b

_{f}is the coefficient of the generic real estate characteristic f (with f = 1, 2, ..., n); B

_{g}is the coefficient of the generic market segment parameter g (with g = 1, 2, ..., m); x

_{jf}is the generic real estate characteristic; and X

_{jg}is the generic market segment parameter with e

_{j}the stochastic error.

_{0}the constant term; p

_{f}is the marginal price of the generic real estate characteristic; q

_{g}is the marginal price of the generic market segment parameter; x

_{f}is the generic real estate characteristic and X

_{g}is the generic market segment parameter.

_{0}and b

_{0}) and in marginal prices of real estate characteristics (p

_{f}and b

_{f}) and in marginal prices of the parameters (q

_{g}and B

_{g}).

_{0}), is estimated by using numerous market data, sufficient for the construction of a statistical model. Once the prices related to the market area, the real estate characteristics and the market segment parameters are known, the multiple linear regression equation Formula (2) is interpolated to the market value:

_{0f}is the generic real estate characteristic of the property assessed and X

_{0g}is the generic segment parameter of the property assessed. The appraisal function is able to estimate individually by interpolation all the properties of the market area.

_{j}(with j = 1, 2, …, k) of a market area, the real estate characteristics and the market segment parameters, the appraisal function is developed as a compound k system in which each one of the equations is based on the appraisal function of the Formula (2):

_{0}according to the Formula (6) is equal to:

_{j}, the real estate characteristics and the market segment parameters of the contracted property, the appraisal function is:

_{0A}of market area A and the locational factor L

_{0B}of market area B, are:

## 6. Prototypes

_{0}), is estimated by using numerous market data, sufficient for the construction of a statistical model.

_{0}, b

_{1}, …, b

_{4}, of the regression model are the constant term and the marginal prices of the characteristics and parameters:

_{0}related to the location and other characteristics and parameters. The constant term is calculated as from (17):

_{0}related to the location and other characteristics and parameters. The constant term is calculated by setting a comparison equation between the subject and the comparable property, as from [21]:

_{0A}of market area A (second situation) and locational factor L

_{0B}of market area B (third situation), equal to:

## 7. Conclusions

## Author Contributions

## Conflicts of Interest

## References

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Sales Price (Euro) PRS | Size (Square Feet) SIZ | Balconies (Square Feet) BAL | Floor Level (Floor Number) LEV | Typology (0–1) TYP |
---|---|---|---|---|

90,000.00 | 93.00 | 6.00 | 4.00 | 0.00 |

45,000.00 | 60.00 | 6.00 | 1.00 | 0.00 |

60,000.00 | 60.00 | 8.00 | 1.00 | 0.00 |

65,000.00 | 65.00 | 6.00 | 1.00 | 0.00 |

242,000.00 | 120.00 | 19.00 | 1.00 | 1.00 |

150,000.00 | 80.90 | 2.30 | 1.00 | 1.00 |

155,000.00 | 88.40 | 3.40 | 3.00 | 0.00 |

160,000.00 | 95.10 | 4.90 | 1.00 | 1.00 |

71,000.00 | 75.00 | 22.00 | 1.00 | 0.00 |

200,000.00 | 130.40 | 16.00 | 1.00 | 1.00 |

250,000.00 | 130.00 | 23.00 | 2.00 | 1.00 |

160,000.00 | 150.00 | 30.00 | 2.00 | 1.00 |

202,000.00 | 103.00 | 12.00 | 2.00 | 1.00 |

250,000.00 | 116.40 | 20.18 | 1.00 | 1.00 |

245,000.00 | 115.30 | 10.58 | 2.00 | 1.00 |

250,000.00 | 115.00 | 10.00 | 1.00 | 1.00 |

250,000.00 | 140.00 | 7.40 | 2.00 | 1.00 |

290,000.00 | 104.00 | 18.83 | 2.00 | 1.00 |

270,000.00 | 150.00 | 11.10 | 2.00 | 1.00 |

335,000.00 | 126.00 | 12.50 | 2.00 | 1.00 |

215,000.00 | 135.00 | 12.00 | 2.00 | 1.00 |

270,000.00 | 102.00 | 12.75 | 2.00 | 1.00 |

320,000.00 | 123.00 | 15.00 | 2.00 | 1.00 |

75,000.00 | 65.00 | 3.00 | 1.00 | 1.00 |

300,000.00 | 105.00 | 6.00 | 2.00 | 1.00 |

250,000.00 | 120.00 | 23.00 | 2.00 | 1.00 |

254,000.00 | 121.00 | 16.00 | 2.00 | 1.00 |

240,000.00 | 136.00 | 9.70 | 2.00 | 1.00 |

285,000.00 | 90.00 | 8.50 | 2.00 | 1.00 |

85,000.00 | 75.00 | 8.00 | 2.00 | 1.00 |

217,000.00 | 123.00 | 12.00 | 2.00 | 1.00 |

276,000.00 | 123.00 | 10.00 | 2.00 | 1.00 |

278,000.00 | 129.00 | 19.00 | 2.00 | 1.00 |

274,000.00 | 130.00 | 14.00 | 1.00 | 1.00 |

200,000.00 | 105.00 | 9.00 | 1.00 | 1.00 |

265,000.00 | 116.00 | 10.00 | 2.00 | 1.00 |

280,000.00 | 100.00 | 12.00 | 1.00 | 1.00 |

290,000.00 | 128.00 | 21.00 | 2.00 | 1.00 |

210,000.00 | 130.00 | 7.00 | 1.00 | 1.00 |

235,000.00 | 120.00 | 11.50 | 1.00 | 1.00 |

250,000.00 | 132.00 | 7.00 | 2.00 | 1.00 |

185,000.00 | 110.00 | 15.00 | 2.00 | 1.00 |

200,000.00 | 100.00 | 12.00 | 2.00 | 1.00 |

215,000.00 | 120.00 | 6.00 | 1.00 | 1.00 |

140,000.00 | 100.60 | 19.34 | 1.00 | 1.00 |

110,000.00 | 84.22 | 5.78 | 1.00 | 1.00 |

Sales Price (Euro) PRSs | Size (Square Feet) SIZs | Balconies (Square Feet) BALs | Floor Level (Floor Number) LEVs | Typology (0–1) TYPs |
---|---|---|---|---|

? | 150.00 | 9.00 | 1.00 | 1.00 |

Sales Price (Euro) PRS | Size (Square Feet) SIZ | Balconies (Square Feet) BAL | Bathrooms (Number) BAT | Typology (0–1) TYP |
---|---|---|---|---|

90,000.00 | 93.00 | 6.00 | 1.00 | 1.00 |

120,000.00 | 100.00 | 10.00 | 2.00 | 1.00 |

150,000.00 | 85.00 | 8.00 | 1.00 | 0.00 |

150,000.00 | 70.00 | 8.00 | 1.00 | 0.00 |

Sales Price (Euro) PRS_{S} | Size (Square Feet) SIZ_{S} | Balconies (Square Feet) BAL_{S} | Bathrooms (Number) BAT_{S} | Typology (0–1) TYP_{S} |
---|---|---|---|---|

? | 80.00 | 7.00 | 1.00 | 1.00 |

Characteristics | Formula | Calculation |
---|---|---|

Size SIZ (euro/sqf) | ${p}_{SIZ}=min{\overline{p}}_{SIZ}=min\frac{PR{S}_{i}}{SI{Z}_{i}+{\pi}_{BAL}\times BA{L}_{i}}$ | 949.36 |

Balconies BAL (euro/sqf) | ${p}_{BAL}={\pi}_{BAL}\times {p}_{SIZ}$ | 284.81 |

Bathrooms BAT (euro) | p_{BAT} = detected by market surveys | 7500.00 |

Typology TYP (euro) | q_{TYP} = detected by market surveys | 20,000.00 |

Sale Price Element of Comparison | Comparable A | Subject S |
---|---|---|

Sales price PRS (euro) | 21,000,0,00 | - |

Size SIZ (square feet) | 15,000 | 14,000 |

Balconies BAL (square feet) | 900 | 600 |

Bathrooms BAT (number) | 100 | 200 |

Typology TYP (0–1) | 000 | 100 |

Marginal Price Element of Comparison | Adjustments |
---|---|

p_{SIZ} (euro/sqf) | 1098.25 |

p_{BAL} (euro/sqf) | 362.42 |

p_{BAT} (euro/n) | 7500.00 |

p_{TYP} (euro) | 10,000.00 |

Features | Component of Elements (Euro) | Incidence of Elements (%) |
---|---|---|

Constant (L_{0}) | 34,500.00 | 16.01% |

Size (SIZ) | 153,755.64 | 71.37% |

Balconies (BAL) | 2174.54 | 1.01% |

Bathrooms (BAT) | 15,000.00 | 6.96% |

Typology (TYP) | 10,000.00 | 4.64% |

Total price | 215,430.18 | 100.0% |

Sales Price (Euro) PRS_{S} | Size (Square Feet) SIZ_{S} | Balconies (Square Feet) BAL_{S} | Bathrooms (Number) BAT_{S} | Typology (0–1) TYP_{S} |
---|---|---|---|---|

? | 100.00 | 9.00 | 1.00 | 1.00 |

© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Ciuna, M.; Milazzo, L.; Salvo, F.
A Mass Appraisal Model Based on Market Segment Parameters. *Buildings* **2017**, *7*, 34.
https://doi.org/10.3390/buildings7020034

**AMA Style**

Ciuna M, Milazzo L, Salvo F.
A Mass Appraisal Model Based on Market Segment Parameters. *Buildings*. 2017; 7(2):34.
https://doi.org/10.3390/buildings7020034

**Chicago/Turabian Style**

Ciuna, Marina, Laura Milazzo, and Francesca Salvo.
2017. "A Mass Appraisal Model Based on Market Segment Parameters" *Buildings* 7, no. 2: 34.
https://doi.org/10.3390/buildings7020034