# How is Location Measured in Housing Valuation? A Systematic Review of Accessibility Specifications in Hedonic Price Models

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## Abstract

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## 1. Introduction

## 2. Literature Review

#### Operationalizing Accessibility Measures and Perception

## 3. Materials and Methods

#### 3.1. Searching

#### 3.2. Screening and Filtering

- We excluded all articles that did not use the hedonic price methodology.
- We excluded all articles that did not use residential sale price as its dependent variable. As a result, we excluded all articles that used non-residential sales price. The reason being that these other uses would value accessibility differently with a different set of methods.
- We similarly excluded all articles that looked at inter-metropolitan hedonic price researches. Different sets of accessibility variables are used when we are comparing which city to live rather than which parts of the city to live in.
- We also excluded meta-studies. The reason is that meta-studies can have different search criteria and search periods, which might result in mismatches between the articles we found and the articles used.
- We did not include studies that used land use transportation model (Luti). The reason being that the output of accessibility measures hold potential for a particular origin rather than the actual flows between a pair of origin and destination, as in a Luti model. However, we do note that the two are highly related.
- We also excluded studies pertaining to housing submarkets. These sets of literature had become a sub-domain within the housing literature and they would require a separate review to understand how accessibility influences the definition of the housing submarket.

#### 3.3. Reviewing

#### 3.3.1. Opportunities and Impedance

#### 3.3.2. Type

_{i}= min c

_{ij},

_{i}is the measure of accessibility and c

_{ij}is the distance or cost of travel between i and j.

_{i}=∑D

_{j}if d

_{ij}≤ r,

_{i}is the measure of accessibility in location i to all opportunities D

_{j}and r is the threshold radius for which the number of opportunities are summed.

_{i}=∑D

_{j}exp

^{−βc}

_{ij},

_{i}is the measure of accessibility in zone i to all opportunities D in zone j, c

_{ij}is the cost of travel between i and j, and beta is the cost sensitivity parameter. The impedance function can take a different functional form.

_{i}=ln ∑exp(V

_{ij}),

_{i}is the accessibility at the individual or homogenous population level i and V

_{ij}is the perceived utility. The perceived utility (V

_{ij}) is the sum of the utility derived from the transport mode in accessing the specific destination. The differences in utility between different scenarios can then be used to derive consumer surpluses and thus the monetary value. Empirically, this is done by multiplying the logsum accessibility by an income coefficient.

## 4. Results

## 5. Discussion

## Supplementary Materials

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 1.**Scheme over search and filtering process. Starting from search of two databases for publications between 2000 and mid-2016 to screening and filtering before final review. From 120 articles in the initial search, the final number of articles included was 54.

**Figure 2.**The three aspects of accessibility measures that are investigated is type, opportunity, and impedance. This figure shows the aspects and their units.

**Figure 3.**The frequency of the use of the specific combination of opportunities and types of accessibility measures in the reviewed sample of papers. The numbers in the figure represent the amount of times the combination opportunity-type is used; the darker blue, the more frequent this combination is used; the sum shows the total amount of times that the opportunity or type is used, irrespective of the other aspect.

**Figure 4.**

**The frequency of the use of the specific combination of opportunities and impedance in the reviewed sample of papers**. The numbers in the figure represent the amount of times the combination opportunity-type is used; the darker blue, the more frequent this combination is used; the sum shows the total amount of times the opportunity or impedance is used, irrespective of the other aspect.

**Figure 5.**

**The frequency of the use of the specific combination of impedance and type in the reviewed sample of papers**. The numbers in the figure represent the amount of times the combination opportunity-type is used; the darker blue, the more frequent this combination is used; the sum shows the total amount of times the impedance or type is used, irrespective of the other aspect. The list “Dummies” show how many times type and impedance variables actually are dummy variables.

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**MDPI and ACS Style**

Heyman, A.V.; Law, S.; Berghauser Pont, M.
How is Location Measured in Housing Valuation? A Systematic Review of Accessibility Specifications in Hedonic Price Models. *Urban Sci.* **2019**, *3*, 3.
https://doi.org/10.3390/urbansci3010003

**AMA Style**

Heyman AV, Law S, Berghauser Pont M.
How is Location Measured in Housing Valuation? A Systematic Review of Accessibility Specifications in Hedonic Price Models. *Urban Science*. 2019; 3(1):3.
https://doi.org/10.3390/urbansci3010003

**Chicago/Turabian Style**

Heyman, Axel Viktor, Stephen Law, and Meta Berghauser Pont.
2019. "How is Location Measured in Housing Valuation? A Systematic Review of Accessibility Specifications in Hedonic Price Models" *Urban Science* 3, no. 1: 3.
https://doi.org/10.3390/urbansci3010003