Tenant satisfaction in housing real estate – an empirical analysis

1. Tenant satisfaction in housing real estate – an empirical analysis ERES 2009 – Doctoral Session 2.4 Jens Pozimski 24.07.2009

2. Tenant satisfaction in housing real estate– an empirical analysis Table of Contents Introduction Data Description Database of a listed housing company Data from a questionnaire Research Design

3. Tenant satisfaction in housing real estate– an empirical analysis Introduction • Former subject: determinantes of residence time • The multiplicative inverse of residence time is fluctuation • Results of fluctuation for the owner are • direct costs: administration costs, (temporary) loss of rent appox. 2.000 – 2.500 Euro / dwelling • indirect costs: refurbishment appox. 15.000 – 20.000 Euro / dwelling • Purpose of business: maximise profits by optimising revenues and costs • Which factors cause fluctuation (costs)? • To what extent rent increase will affect fluctuation (revenues)?

4. Tenant satisfaction in housing real estate– an empirical analysis Introduction • New subject: tenant satisfaction (satisfaction reduces fluctuation) • What are the main drivers to enhance tenant satisfaction • Rental fee • Operating costs • Quality of dwelling • Rental space

5. Tenant satisfaction in housing real estate– an empirical analysis Data Database of a listed housing company with a stock of 35.000 dwellings in the southern part of Germany • Start and end of the term of lease -> residence time • Rental fee • Local index rent • (non-recoverable) operating costs • Quality of flats • Location • Living space • Number of rooms

6. Tenant satisfaction in housing real estate– an empirical analysis Data Data from a questionnaire. The Questionnaireincludes data from the database • Rental fee • Local rent level (index rent) • Operating costs • Quality of the dwelling (cluster) • Quality of the environment (cluster) • Living space and number of rooms

7. Tenant satisfaction in housing real estate– an empirical analysis Data Data from a questionnaire. Questions: • Level of satisfaction (1-6) – dependent variable • What is the fair rental fee for this flat? • How much are you willing to pay? • Income of household • What could be improved? • Did the level of the comparable local rental fee surprise you?

8. Tenant satisfaction in housing real estate– an empirical analysis Data Data from a questionnaire. Does Satisfaction has an influence on residence time/fluctuation? Questions about changing the dwelling: • Low satisfaction • Rental fee • Size • Employment • Personal or family reasons • Other reasons

9. Tenant satisfaction in housing real estate– an empirical analysis Research Design Simple Regression Model Dependent variable (level of satisfaction) = α+β(1)*(rental fee)+β(2)*(affordability)+β(n)*(…)+E • Building of clusters to reduce bias • regarding the quality of dwellings • regarding the location • regarding the size of the dwelling • Different specifications • rental fee (absolute, relative to average rent of appartment complex, relative to local index rent) • operating costs (absolute, relative to rental fee)

10. Tenant satisfaction in housing real estate– an empirical analysis Research Design Results of the regression • Significant variables -> find a breakeven-equation to optimise the maximum profit using the obtained parameters from the regression max (P) -> R – C P = profit R = revenue (from rental income) C = Costs (operating costs, fluctuation costs)