Proximity to Natural Amenities: A Seemingly Unrelated Hedonic Regression Model with Spatial Durbin and Spatial Error Processes

2016 ◽  
Vol 47 (4) ◽  
pp. 461-480 ◽  
Author(s):  
Germán M. Izón ◽  
Michael S. Hand ◽  
Daniel W. Mccollum ◽  
Jennifer A. Thacher ◽  
Robert P. Berrens
Keyword(s):  
Regression Model ◽  
Hedonic Regression ◽  
Spatial Error ◽  
Natural Amenities

SPATIAL AUTOREGRESSIVE (SAR) MODEL WITH ENSEMBLE LEARNING-MULTIPLICATIVE NOISE WITH LOGNORMAL DISTRIBUTION (CASE ON POVERTY DATA IN EAST JAVA)

2021 ◽  
Vol 14 (1) ◽  
pp. 89-97
Author(s):  
Dewi Retno Sari Saputro ◽  
Sulistyaningsih Sulistyaningsih ◽  
Purnami Widyaningsih
Keyword(s):  
Regression Model ◽  
Ensemble Learning ◽  
Spatial Data ◽  
Lognormal Distribution ◽  
Multiplicative Noise ◽  
Spatial Regression ◽  
Spatial Error ◽  
Spatial Regression Model ◽  
Sar Model ◽  
Spatial Autoregressive

The regression model that can be used to model spatial data is Spatial Autoregressive (SAR) model. The level of accuracy of the estimated parameters of the SAR model can be improved, especially to provide better results and can reduce the error rate by resampling method. Resampling is done by adding noise (noise) to the data using Ensemble Learning (EL) with multiplicative noise. The research objective is to estimate the parameters of the SAR model using EL with multiplicative noise. In this research was also applied a spatial regression model of the ensemble non-hybrid multiplicative noise which has a lognormal distribution of cases on poverty data in East Java in 2016. The results showed that the estimated value of the non-hybrid spatial ensemble spatial regression model with multiplicative noise with a lognormal distribution was obtained from the average parameter estimation of 10 Spatial Error Model (SEM) resulting from resampling. The multiplicative noise used is generated from lognormal distributions with an average of one and a standard deviation of 0.433. The Root Mean Squared Error (RMSE) value generated by the non-hybrid spatial ensemble regression model with multiplicative noise with a lognormal distribution is 22.99.

A Bayesian Dynamic Hedonic Regression Model for Art Prices

2019 ◽  
Author(s):  
Urbi Garay ◽  
Gavino Puggioni ◽  
German Molina ◽  
Enrique ter Horst
Keyword(s):  
Regression Model ◽  
Hedonic Regression ◽  
Art Prices

scholarly journals Benchmark for REIT Performance in Malaysia Using Hedonic Regression Model

2014 ◽  
Vol 6 (9) ◽  
Author(s):  
Olusegun Olaopin Olanrele ◽  
Rosli Said ◽  
Mohd Nasir Daud
Keyword(s):  
Regression Model ◽  
Hedonic Regression

Performance analysis of investing in Chinese oil paintings based on a hedonic regression model of price index

2017 ◽  
Vol 7 (3) ◽  
pp. 323-342
Author(s):  
Fang Wang ◽  
Xu Zheng
Keyword(s):  
Regression Model ◽  
Price Index ◽  
Portfolio Diversification ◽  
Hedonic Regression ◽  
Oil Painting ◽  
Content Type ◽  
Oil Paintings ◽  
Auction Houses ◽  
Capm Model ◽  
Diversification Benefit

Purpose The purpose of this paper is to construct a price index for Chinese oil paintings and analyze the financial performance of investing in Chinese oil paintings and its potential for portfolio diversification in Chinese financial markets. Design/methodology/approach A hedonic regression model is applied to construct a semiannual price index for Chinese oil paintings from 2000 to 2014. The CAPM model, downside β and standard portfolio optimization are used for analyzing portfolio diversification. Findings The hedonic regression shows that the majority of hedonic variables, such as dimension, artist’s reputation, living status, medium and auction houses, are statistically significant in estimation. Not only the return from oil painting investments is higher than other equities, but also the β coefficient of the CAPM model and downside β indicate that Chinese oil painting may be a good hedging instrument against stock market risk. Furthermore, the portfolio optimizations under standard assumptions suggest that oil paintings as an alternative investment provide diversification benefit. Originality/value This paper provides a new and comprehensive analysis of characteristics and risks of investing in the Chinese oil paintings.

Sign in / Sign up

Export Citation Format

Share Document