International Real Estate Review

2006 ◽  
Vol 9 (1) ◽  
pp. 112-131
Author(s):  
Steven Plaut ◽  
◽  
Egita Uzulena ◽  
Keyword(s):  
Architectural Design ◽  
Explanatory Variable ◽  
Housing Stock ◽  
Housing Markets ◽  
Hedonic Pricing ◽  
Housing Values ◽  
Pricing Models ◽  
Explanatory Variables ◽  
Housing Value ◽  
Physical Features

Architectural design has generally not been included in estimations of hedonic pricing models and the reason is no doubt the difficulty in capturing it in a usable measurement variable. It is usually too idiosyncratic and heterogeneous to “sum up” easily and introduce as an explanatory variable. However, in some housing markets, architectural design consists of a limited number of standardized “prototypes”, which can then be used as explanatory variables in hedonic estimations. Such is the case for Riga, Latvia, where almost the entire housing stock fits into about a score of fairly standardized architectural design types. This paper is an empirical analysis of the Riga housing market, which only became a “market” in a meaningful sense after the collapse of the Soviet regime in Latvia. The paper analyzes a set of about 3500 transactions, all from recent years. We estimate the elasticity of housing value with respect to size of housing units and some other physical features, and the value of the different architectural designs, controlling for location. This is one of the first hedonic or microeconomic analyses of housing values in any post-Soviet transitional economy.

scholarly journals A Model of Stress Change under the First COVID-19 Pandemic among the General Public in Japanese Major Cities and Rural Areas

2021 ◽  
Vol 13 (3) ◽  
pp. 1207
Author(s):  
Misato Uehara ◽  
Makoto Fujii ◽  
Kazuki Kobayashi
Keyword(s):  
Rural Areas ◽  
Healthcare Workers ◽  
Explanatory Variable ◽  
Large City ◽  
Stress Change ◽  
Multiple Factor Analysis ◽  
Explanatory Variables ◽  
Private Research ◽  
The Difference ◽  
The Relationship

Research on stress related to the COVID-19 pandemic has been dominated by the cases of healthcare workers, students, patients, and their stress during the COVID-19 pandemic. This study examined the relationship between the amount of stress change under the COVID-19 pandemic and demographic factors (age, sex, occupation, etc.) in residents of a large city and a rural area of Japan. A total of 1331 valid responses were received in June 2020 from residents of Tokyo, Osaka, and Nagano registered with a private research firm. We were able to identify 15 statistically significant variables out of 36 explanatory variables, which explained the significant increase in stress compared to the pre-pandemic period. Multiple-factor analysis showed that the relationship with people is a more significant explanatory variable for the level of increase in stress than the difference in environment between big cities (Tokyo, Osaka) and rural areas (Nagano), the type of housing, and the decrease in income compared to the pre-pandemic period.

scholarly journals Speculative housing markets and rent control: insights from nonlinear economic dynamics

2021 ◽  
Author(s):  
Noemi Schmitt ◽  
Frank Westerhoff
Keyword(s):  
Housing Market ◽  
Housing Stock ◽  
House Price ◽  
Housing Markets ◽  
Market Model ◽  
Market Dynamics ◽  
Rent Control ◽  
Forecasting Accuracy ◽  
Expectation Formation ◽  
Rent Level

AbstractWe propose a novel housing market model to explore the effectiveness of rent control. Our model reveals that the expectation formation and learning behavior of boundedly rational homebuyers, switching between extrapolative and regressive expectation rules subject to their past forecasting accuracy, may create endogenous housing market dynamics. We show that policymakers may use rent control to reduce the rent level, although such policies may have undesirable effects on the house price and the housing stock. However, we are also able to prove that well-designed rent control may help policymakers to stabilize housing market dynamics, even without creating housing market distortions.

scholarly journals Environmental Health Risks and Housing Values: Evidence from 1,600 Toxic Plant Openings and Closings

2015 ◽  
Vol 105 (2) ◽  
pp. 678-709 ◽  
Author(s):  
Janet Currie ◽  
Lucas Davis ◽  
Michael Greenstone ◽  
Reed Walker
Keyword(s):  
Low Birthweight ◽  
Infant Health ◽  
Housing Markets ◽  
Housing Values ◽  
Regulatory Oversight ◽  
Industrial Plants ◽  
Toxic Emissions ◽  
Environmental Health Risks ◽  
Rich Data ◽  
Toxic Plant

Regulatory oversight of toxic emissions from industrial plants and understanding about these emissions' impacts are in their infancy. Applying a research design based on the openings and closings of 1,600 industrial plants to rich data on housing markets and infant health, we find that: toxic air emissions affect air quality only within 1 mile of the plant; plant openings lead to 11 percent declines in housing values within 0.5 mile or a loss of about $4.25 million for these households; and a plant's operation is associated with a roughly 3 percent increase in the probability of low birthweight within 1 mile. (JEL I12, L60, Q52, Q53, Q58, R23, R31)

The Composition of Hedonic Pricing Models

2005 ◽  
Vol 13 (1) ◽  
pp. 1-44 ◽  
Author(s):  
Stacy Sirmans ◽  
David Macpherson ◽  
Emily Zietz
Keyword(s):  
Hedonic Pricing ◽  
Pricing Models

Analysis of variance (ANOVA).

2021 ◽  
pp. 155-165
Author(s):  
Donald Quicke ◽  
Buntika A. Butcher ◽  
Rachel Kruft Welton
Keyword(s):  
Linear Model ◽  
Analysis Of Variance ◽  
Explanatory Variable ◽  
T Test ◽  
Specific Function ◽  
Real Numbers ◽  
Response Variable ◽  
Explanatory Variables ◽  
Student’S T ◽  
One Way Anova

Abstract Analysis of variance is used to analyze the differences between group means in a sample, when the response variable is numeric (real numbers) and the explanatory variable(s) are all categorical. Each explanatory variable may have two or more factor levels, but if there is only one explanatory variable and it has only two factor levels, one should use Student's t-test and the result will be identical. Basically an ANOVA fits an intercept and slopes for one or more of the categorical explanatory variables. ANOVA is usually performed using the linear model function lm, or the more specific function aov, but there is a special function oneway.test when there is only a single explanatory variable. For a one-way ANOVA the non-parametric equivalent (if variance assumptions are not met) is the kruskal.test.

More generalized linear modelling.

2021 ◽  
pp. 171-186
Author(s):  
Donald Quicke ◽  
Buntika A. Butcher ◽  
Rachel Kruft Welton
Keyword(s):  
Generalized Linear Models ◽  
Count Data ◽  
Binary Data ◽  
Linear Models ◽  
Explanatory Variable ◽  
Response Variable ◽  
Explanatory Variables ◽  
Continuous Response ◽  
Generalized Linear Modelling ◽  
Linear Modelling

Abstract This chapter employs generalized linear modelling using the function glm when we know that variances are not constant with one or more explanatory variables and/or we know that the errors cannot be normally distributed, for example, they may be binary data, or count data where negative values are impossible, or proportions which are constrained between 0 and 1. A glm seeks to determine how much of the variation in the response variable can be explained by each explanatory variable, and whether such relationships are statistically significant. The data for generalized linear models take the form of a continuous response variable and a combination of continuous and discrete explanatory variables.

scholarly journals Influence of sex-specific concurrent changes in age, maturity status, and morphological covariates on the development of peak ventilatory variables in 10–17-year-olds

2020 ◽  
Author(s):  
Neil Armstrong ◽  
Jo Welsman
Keyword(s):  
Oxygen Uptake ◽  
Tidal Volume ◽  
Body Mass ◽  
Explanatory Variable ◽  
Multilevel Modelling ◽  
Peak Oxygen Uptake ◽  
Anthropometric Measures ◽  
Allometric Models ◽  
Explanatory Variables ◽  
Temporal Spacing

Abstract Purposes (i) To investigate the influence of concurrent changes in age, maturity status, stature, body mass, and skinfold thicknesses on the development of peak ventilatory variables in 10–17-year-olds; and, (ii) to evaluate the interpretation of paediatric norm tables of peak ventilatory variables. Methods Multiplicative multilevel modelling which allows both the number of observations per individual and the temporal spacing of the observations to vary was used to analyze the expired ventilation (peak $${\dot{\mathrm{V}}}_{\mathrm{E}}$$ V ˙ E ) and tidal volume (peak VT) at peak oxygen uptake of 420 (217 boys) 10–17-year-olds. Models were founded on 1053 (550 from boys) determinations of peak ventilatory variables supported by anthropometric measures and maturity status. Results In sex-specific, multiplicative allometric models, concurrent changes in body mass and skinfold thicknesses (as a surrogate of FFM) and age were significant (p < 0.05) explanatory variables of the development of peak $${\dot{\mathrm{V}}}_{\mathrm{E}}$$ V ˙ E , once these covariates had been controlled for stature had no additional, significant (p > 0.05) effect on peak $${\dot{\mathrm{V}}}_{\mathrm{E}}$$ V ˙ E . Concurrent changes in age, stature, body mass, and skinfold thicknesses were significant (p < 0.05) explanatory variables of the development of peak VT. Maturity status had no additional, significant (p > 0.05) effect on either peak $${\dot{\mathrm{V}}}_{\mathrm{E}}$$ V ˙ E or peak VT once age and morphological covariates had been controlled for. Conclusions Elucidation of the sex-specific development of peak $${\dot{\mathrm{V}}}_{\mathrm{E}}$$ V ˙ E requires studies which address concurrent changes in body mass, skinfold thicknesses, and age. Stature is an additional explanatory variable in the development of peak VT, in both sexes. Paediatric norms based solely on age or stature or body mass are untenable.

The valuation of intangibles for hotel investments

2004 ◽  
Vol 22 (5) ◽  
pp. 410-423 ◽  
Author(s):  
Sherif Roubi
Keyword(s):  
Hedonic Pricing ◽  
Total Asset ◽  
Hedonic Price ◽  
Pricing Models ◽  
Physical Location ◽  
Ex Post ◽  
Asset Value ◽  
Ex Ante ◽  
Using Data

Reviews the literature on the valuation of intangibles for hotel investments. Contrary to the sceptical outlook portrayed in the literature, demonstrates the effectiveness of ex‐post models and hedonic pricing models (HPM) as an objective and robust tool in separating and measuring intangible hotel property and decomposing total asset value. Develops two HPM models using data on 50 hotel properties appraised in 1997. All hotels are owned and managed by the same hotel company and affiliated with the same brand. Some 58 per cent of the properties are freeholds and the rest are leaseholds. Estimates the hedonic price equations by regressing appraised values on physical, location and economic characteristics of the properties. Results confirm the effectiveness of HPM and in fact its relative superiority to traditional ex‐ante modelling in measuring and decomposing intangible property. As expected at the outset, comparable‐leases and excess‐profits‐based models produced similar results.

scholarly journals Money Supply Determinants in Nepal: A Macro Analysis

2018 ◽  
Vol 13 ◽  
pp. 55
Author(s):  
Saraswoti Tiwari
Keyword(s):  
Money Supply ◽  
Explanatory Variable ◽  
Economic Literature ◽  
Explanatory Variables ◽  
Money Multiplier ◽  
The Past ◽  
Time Deposits ◽  
Demand Deposits ◽  
Proximate Determinants ◽  
Net Foreign Asset

<p>This paper analyzes the major money supply determinants in Nepal in the past 10 years from FY 2004/05 - FY 20014/15. In this study monetary base is determined by two explanatory variables (i.e. NFA and NDC) and are called the 'proximate' determinants of the base money. Among the explanatory variables, the net foreign asset (NFA) is found as better determinant than net domestic assets (NDA) in Nepalese economy. For the analysis of determinants of money multiplier (MM), the three explanatory variables i.e., reserve to total deposits ratio (r), time deposits to demand deposits ratio (t) and currency to demand deposits ratio (c) have been used. The model applied in this study shows that explanatory variable of time deposits to demand deposits ratio is the best determinant of money multiplier. The reserve money (RM) is analyzed as the best determinant of money supply, net foreign assets (NFA) is the major determinant of reserve money and time deposits to demand deposits ratio is the significant determinant of money multiplier.</p><p> <strong><em>Economic Literature</em></strong><em>, </em>Vol. XIII August 2016, page 55-60</p>

Property valuation: the hedonic pricing model: the application of search-and-matching models

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gaetano Lisi
Keyword(s):  
Hedonic Pricing ◽  
Matching Theory ◽  
Hedonic Price ◽  
Search And Matching ◽  
Pricing Models ◽  
Content Type ◽  
Price Function ◽  
Hedonic Price Function ◽  
Search And Matching Models ◽  
Matching Models

PurposeThe aim of this education briefing is to comment upon how basic hedonic pricing models for the valuation of property can be expanded and developed. In this case, the briefing illustrates the use of the new economic approach to the analysis of housing markets, namely the search-and-matching models.Design/methodology/approachThis education briefing discusses the connection of two important economic theories: the hedonic price theory and the search-and-matching theory.FindingsThis education briefing gives an example of a (non-linear) form of the hedonic price function.Practical implicationsIn cases of mass appraisals, hedonic pricing models can provide a broad indication of value across submarkets and this education briefing demonstrates a theoretical model that can be used to provide a theoretical groundwork for the use of a concave hedonic price function in empirical estimates.Originality/valueThis education briefing shows how basic hedonic pricing models can be enhanced by a search-and-matching approach to determine property values.

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