Analysis of Factors Influencing Reported Housing Maintenance Costs in Sweden’s Public and Private Rental Sectors

Abstract

The reported maintenance costs per unit area within the public rental housing sector in Sweden are consistently higher than those within the private rental sector. This paper uses crosssectional panel data analysis as well as a questionnaire survey sent to 196 managers in the private and public housing sectors to identify the factors that might explain this divergence. The findings indicate that “fundamental” factors such as the age of the houses or the composition of the tenants cannot explain the observed difference. However how the activities are classified and the timing of the measures are factors that can. The conclusions from the study are that the public companies should act more as the private sector in their accounting; wait longer than they currently do before carrying out some renovations; and that they should be more stringent when determining the resources to spend on large-scale maintenance and/or renovation projects.

Development of a Long-Term Repair Allowance Estimation Model for Apartments Based on Multiple Regression Analysis in Korea

“…To address these problems, various LTRA estimation models have been developed in previous studies (shown in Table 1), which can be classified as (1) LCC-based total LTRA estimation methods [22,23]; (2) simulation-based total LTRA estimation methods [24][25][26]; and (3) total LTRA estimation methods based on the data from similar cases [11,27,28,30]. First, in the case of the LCC-based total amount estimation method, previous studies [19,20] developed an LCC-based LTRA estimation model that considers time value and annual LTRA based on the quantity and unit price for each item in the long-term repair program.…”

“…In addition, a probabilistic model was developed to derive the long-term repairs allowance using MCS [24,25]. Third, in the case of the total LTRA estimation method based on the data from similar cases, previous studies developed and verified various models using maintenance expense performance data (LTRA and other facility maintenance expenses) or LTRA data based on the multiple regression analysis [11,28,30], genetic algorithm (GA), and CBR [27]. The LCC-based total LTRA estimation methods proposed in previous studies can consider the time value for the estimated total LTRA but require considerable effort and resources.…”

Motivations of tenancy and the diversity of tenants: the case of Ankara, Turkey

“…The choices made will depend on household income, wealth and household characteristics as well as the relative costs associated with renting compared with owner-occupation. There are also other financial reasons, such as the desire to avoid the long-term commitments arising from purchasing a house or the desire to avoid the long-run maintenance costs of a house (Muyingo 2017;Pawson et al, 2017;William & Altes, 2016).…”

Probabilistic Maintenance Cost Analysis for Aged Multi-Family Housing

“…Goodman [28] analyzed the decisive factors of the operating costs for rental housing by classifying the quality of housing, number of elapsed years, number of households, and area according to the operating and maintenance costs. Muyingo [29] investigated and analyzed the maintenance costs of public rental housing in Sweden and derived the maintenance costs per unit area of private and public rental through a survey with experts.…”