2008Unpublished venueRequires access

THE DETERMINATION OF MARKET RENTS FOR HOUSES IN THE NETHERLANDS

Marc Francke, Philip W. Koppels

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Abstract

Housing corporations are willing to partly adjust rents to market conditions. At the moment rental prices in the social subsidised housing sector in the Netherlands are regulated and only partly reflect the underlying house values. On the other hand the Dutch commercial rental housing sector is relatively small and information on commercial rents is hardly available. In this paper a method of determining ëmarket rentsí is presented, that is based on the number of reactions, i.e. people that showed interest in a house conditional on the non-negotiatiable asking rent. When the number of reactions is relatively high (low), it is assumed that the fixed asking rent is lower (higher) than the market rent. The number of reactions is explained by 1) the ratio of the house value and the rental price, 2) the ratio of a house quality rating and the rental price, 3) the rental price itself and 4) the rental date, where the house value is the yearly apprai sed value used for the property tax. The market rent is defined such that the probability of not renting the house is small, say 5%. Rents can be adjusted based on the outcomes of the model, such that the probability of not renting the house is 5%. Results are presented for different regions in the Netherlands, based on a large database containing rents, values and reactions. The results are compared to market rents that are determined by user costs of housing.

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What this paper is about

Housing corporations are willing to partly adjust rents to market conditions. At the moment rental prices in the social subsidised housing sector in the Netherlands are regulated and only partly reflect the underlying house values. On the other hand the Dutch commercial rental housing sector is relatively small and information on commercial rents is hardly available. In this paper a method of determining ëmarket rentsí is presented, that is based on the number of reactions, i.e. people that showed interest in a house conditional on the non-negotiatiable asking rent. When the number of reactions is relatively high (low), it is assumed that the fixed asking rent is lower (higher) than the market rent. The number of reactions is explained by 1) the ratio of the house value and the rental price, 2) the ratio of a house quality rating and the rental price, 3) the rental price itself and 4) the rental date, where the house value is the yearly apprai sed value used for the property tax. The market rent is defined such that the probability of not renting the house is small, say 5%. Rents can be adjusted based on the outcomes of the model, such that the probability of not renting the house is 5%. Results are presented for different regions in the Netherlands, based on a large database containing rents, values and reactions. The results are compared to market rents that are determined by user costs of housing.

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Available abstract

Housing corporations are willing to partly adjust rents to market conditions. At the moment rental prices in the social subsidised housing sector in the Netherlands are regulated and only partly reflect the underlying house values. On the other hand the Dutch commercial rental housing sector is relatively small and information on commercial rents is hardly available. In this paper a method of determining ëmarket rentsí is presented, that is based on the number of reactions, i.e. people that showed interest in a house conditional on the non-negotiatiable asking rent. When the number of reactions is relatively high (low), it is assumed that the fixed asking rent is lower (higher) than the market rent. The number of reactions is explained by 1) the ratio of the house value and the rental price, 2) the ratio of a house quality rating and the rental price, 3) the rental price itself and 4) the rental date, where the house value is the yearly apprai sed value used for the property tax. The market rent is defined such that the probability of not renting the house is small, say 5%. Rents can be adjusted based on the outcomes of the model, such that the probability of not renting the house is 5%. Results are presented for different regions in the Netherlands, based on a large database containing rents, values and reactions. The results are compared to market rents that are determined by user costs of housing.

Key concepts: Economic rent, Renting, Microeconomics, Economics, Rental housing, Value (mathematics), Market value, Labour economics

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