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Paper eres2017_156:
Loss Aversion and Residential Property Development Decisions in China: A Semi-Parametric Estimation

id eres2017_156
authors Bao, Helen; Chunming (Charlotte) Meng
year 2017
title Loss Aversion and Residential Property Development Decisions in China: A Semi-Parametric Estimation
source 24th Annual European Real Estate Society Conference in Delft, Netherlands
summary Loss aversion is a core concept in prospect theory that refers to people’s asymmetric attitudes with respect to gains and losses. More specifically, losses loom larger than gains. With the capability of loss aversion to explain economic phenomena, some of which are puzzling under expected utility theory, this concept has received significant attention. This study develops a behavioral model of loss aversion to explain the development decisions by residential property developers in the People’s Republic of China. Under the leasehold property right system, real estate development has two stages—first to lease land from the government, and then to develop the property according to the lease terms. This presents a unique opportunity to test the presence and effect of loss aversion in real estate development decisions. More specifically, this study determines when the land premium paid by a developer is substantially higher than the market value, whether and how this “paper loss” will affect the pricing of the housing products and development time of the project in future development. We use a sample of land and house transaction records from Beijing to test the hypothesis. This is the first study to use a semi-parametric model in estimating developers’ loss aversion. Results show that developers are most prone to loss aversion bias around the reference point or when facing large losses. The results also suggest that loss aversion contributes to the cyclical trading pattern in housing markets.
keywords housing; behavioural economics; loss aversion; China
series ERES:conference
type paper session
discussion No discussions. Post discussion ...
session Doctoral session B
last changed 2017/11/18 16:20
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