House Price Model Based on Marginal Analysis of House Market

2021 ◽  
Author(s):  
Hay Nong
Keyword(s):  
House Price ◽  
Price Model ◽  
Marginal Analysis ◽  
Model Based

scholarly journals Leverage and the Financial Accelerator in a Liquidity Trap

2011 ◽  
Vol 101 (3) ◽  
pp. 413-416 ◽  
Author(s):  
Karel Mertens ◽  
Morten O Ravn
Keyword(s):  
Lower Bound ◽  
House Price ◽  
Financial Accelerator ◽  
Price Model ◽  
Financial Friction ◽  
Liquidity Trap ◽  
Collateral Constraint ◽  
The Great Depression ◽  
Output Losses ◽  
Large Output

We show that the financial accelerator may be very large in a liquidity trap. We study a sticky price model with real estate and a financial friction specified as a collateral constraint. Expectations can lead the economy to a self-fulfilling liquidity trap equilibrium where the lower bound on the nominal interest rate binds. We model these equilibria as stochastic sunspots. As in the Great Depression, a liquidity trap entails house price depreciation and potentially large output losses. Higher leverage implies much larger output losses but at the same time rules out the existence of short-lived liquidity traps.

scholarly journals Measures of labour market accessibility. What can we learn from observed commuting patterns?

REGION ◽  
2020 ◽  
Vol 7 (1) ◽  
pp. 49-70
Author(s):  
Liv Osland ◽  
Arnstein Gjestland ◽  
Inge Thorsen
Keyword(s):  
Labour Market ◽  
Explanatory Power ◽  
Housing Prices ◽  
House Price ◽  
Price Model ◽  
Market Structures ◽  
Commuting Flows ◽  
Western Norway ◽  
Commuting Time ◽  
Commuting Patterns

It is well known that measures of labour market accessibility explains spatial variation in housing prices even in markets with polycentric labour market structures. This paper examines whether data on observed commuting patterns can replace or supplement gravity-based measures representing the commuting potential at specific locations. We use data from a region in Western Norway,and we find that measures based on observed commuting flows and commuting time cannot replace a gravity-based measure of labour market accessibility. Based on, inter alia, the spatial Durbin estimator we find that measures of observed commuting flows increase the explanatory power of a hedonic house price model.

scholarly journals ENHANCING THE ACCURACY OF MALAYSIAN HOUSE PRICE FORECASTING: A COMPARATIVE ANALYSIS ON THE FORECASTING PERFORMANCE BETWEEN THE HEDONIC PRICE MODEL AND ARTIFICIAL NEURAL NETWORK MODEL

2021 ◽  
Vol 19 (17) ◽  
Author(s):  
Nurul Fazira Sa’at ◽  
Nurul Hana Adi Maimun ◽  
Nurul Hazrina Idris
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Artificial Neural Network Model ◽  
House Price ◽  
Predictive Performance ◽  
Hedonic Price Model ◽  
Price Forecasting ◽  
Hedonic Price ◽  
Price Model ◽  
Forecasting Performance

The Hedonic Price Model (HPM), a prominent model used in real estate appraisal and economics, has been argued to be marred with nonlinearity, multicollinearity and heteroscedasticity problems that affect the accuracy of price predictions. An alternative method called Artificial Neural Network Model (ANN) was identified as capable of addressing the shortcomings of HPM and produces superior predictive performance. Hence, this study aims to evaluate the forecasting performance between HPM and ANN using Malaysian housing transaction data from the period between 2009 to 2018, sourced from the Valuation and Property Service Department, Johor Bahru. The models’ performance was evaluated and compared based on their statistical and predictive performance. Results showed that ANN outperformed HPM in both statistical and predictive performance. This study benefits the expansion of academic and practical knowledge in enhancing the accuracy of house price forecasting.

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