Ethnic social network in public housing market in Singapore

• Main Authors: AGARWAL, Sumit, CHOI, Hyunsoo, HE, Jia, SING, Tien Foo
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: Social Interactions; Cultural Affinity; Ethnicity Quota; Public Housing; Cash-Over-Valuation (COV); Asian Studies; Finance and Financial Management; Real Estate
• Online Access: https://ink.library.smu.edu.sg/lkcsb_research/5385; https://ink.library.smu.edu.sg/context/lkcsb_research/article/6384/viewcontent/COV_28APR2017.pdf
• Institution: Singapore Management University

This paper investigates the ethnic social network in Singapore's resale public housing market using a unique dataset containing the Cash-Over-Valuation (COV) information for a sample of 73,107 resale public housing transactions from 2007 to 2012. We find that the COV per square meter (psm), which represents a premium above the "objective" housing value, significantly increases with the concentration of buyers' own ethnic group at a housing block level. The results imply that buyers value housing blocks with higher concentration of the same ethnicity group of households. However, the convexity in COV premium suggests that the premium is too large to be fully explained by usual ethnicity related factors, such as cultural amenities, preference for the own ethnicity group, and supply constraint. We find significant evidence supporting the preference matching between buyer and seller reinforced through the ethnic social network as a key factor explaining the incremental COV premiums. The ethnic social network value is only found in transaction prices, if buyers and sellers of the same ethnic group sharing a common preference to trade with each other. We also find a high volume of the within-ethnicity-group transactions both in the own-ethnicity concentrated blocks and the other-ethnicity concentrated blocks, which is consistent with the ethnic social network hypothesis. A potential disconnection due to ethnic-based matching in the search process may cause segregation in the housing market.