1# RECORD 30bb06cf60733bf6f9bbacbca2bbc1d2e8d63b852# TITLE: Construction of Residential Property Price Indices Using the Hedonic Approach: An Application to the Residential Real Estate Market in Sri Lanka3# YEAR: 2021.0 VENUE: Staff Studies DOI: 10.4038/ss.v51i1.47294# AUTHORS: S. Gunawardhana5# PAGES: 18 CANDIDATE TABLE PAGES (1-based): []6# ABSTRACT: Monitoring real estate property prices is crucial for policy makers all over the world, particularly for central banks due to their interconnections with the monetary and financial system stability of an economy. As a result, compiling property price indices has increasingly gained attention from policymakers. However, compiling property price indices is believed to be difficult due to the highly heterogeneous nature of properties, requiring reliable data sources and a methodological approach that is different to those used in compiling other price indices. Against this backdrop, this paper attempts to compile price indices for residential properties in Sri Lanka with a view to supporting policymakers to monitor the price movements in the real estate sector. Considering the relatively less heterogenous nature of condominiums and stages of the buying and selling process, price indices are first developed for advertised condominiums and new condominiums using the Hedonic Regression based Rolling Window Time Dummy method, which is identified as the most suited property price index compilation method in the Sri Lankan context. Further, internationally accepted model specification improvement techniques and index smoothing techniques are also used in the study. Upon successful compilation of price indices for condominiums, the compilation process has been extended to cover the house and land markets of Sri Lanka.789===== PAGE 1 (score 2, numeric-paren 0, table-words 0, var-words 2) =====10116112 13 14Construction of Residential Property Price Indices Using the Hedonic Approach: An 15Application to the Residential Real Estate Market in Sri Lanka1 16S R C L Gunawardhana2 17Abstract 18Monitoring real estate property prices is crucial for policy makers all over the world, particularly 19for central banks due to their interconnections with the monetary and financial system stability 20of an economy. As a result, compiling property price indices has increasingly gained attention 21from policymakers. However, compiling property price indices is believed to be difficult due 22to the highly heterogeneous nature of properties, requiring reliable data sources and a 23methodological approach that is different to those used in compiling other price indices. 24Against this backdrop, this paper attempts to compile price indices for residential properties 25in Sri Lanka with a view to supporting policymakers to monitor the price movements in the 26real estate sector. Considering the relatively less heterogenous nature of condominiums and 27stages of the buying and selling process, price indices are first developed for advertised 28condominiums and new condominiums using the Hedonic Regression based Rolling Window 29Time Dummy method, which is identified as the most suited property price index compilation 30method in the Sri Lankan context. Further, internationally accepted model specification 31improvement techniques and index smoothing techniques are also used in the study. Upon 32successful compilation of price indices for condominiums, the compilation process has been 33extended to cover the house and land markets of Sri Lanka. 34Key Words: Residential Property Price Index, Hedonic Regression, Asking Prices, 35Constant Quality Indices 36JEL Classification: C2, C10, C43, C81, C82, C83, D12, E31, R21, R30, R31 37 38 39 401 The author is thankful to Mr. N O’Hanlon, Statistics Department of the International Monetary Fund (IMF) for providing technical assistance 41for this index compilation process and the Data for Decisions (D4D) fund of IMF for funding the technical assistance missions. The author 42is also thankful to Mr. A R K Wijesekara, Former Assistant Governor, Central Bank of Sri Lanka, Mr. G D P D Jayathilake, Former Director, 43Statistics Department of the Central Bank of Sri Lanka, Dr. (Mrs.) H K J Ekanayake, Director, Statistics Department of the Central Bank of 44Sri Lanka, Mrs. D G D I Ekanayake, Additional Director, Statistics Department of the Central Bank of Sri Lanka, Ms. R M M K Rathnayake, 45Deputy Director, Statistics Department of the Central Bank of Sri Lanka, Ms. P I Rupasinghe, Head of Economic Indicators and Statistical 46Investigations Division, Statistics Department of the Central Bank of Sri Lanka for their guidance and support extended throughout this study. 47In addition, the author would like to express her sincere thanks to all the staff members of the Economic Indicators and Statistical Investigations 48Division of Statistics Department of the Central Bank of Sri Lanka for contributing to the index compilation process in various stages. The 49views expressed in this paper are the author’s own and do not necessarily reflect those of the Central Bank of Sri Lanka. 502 Senior Assistant Director, Statistics Department, Central Bank of Sri Lanka (chamili@cbsl.lk) 51 52 53