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Does Property Segment Distribution Affect the Capital Structure of Real Estate Companies?

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Does Property Segment Distribution Affect the Capital Structure of Real Estate Companies? DEGREE PROJECT REAL ESTATE AND CONSTRUCTION MANAGEMENT MASTER OF SCIENCE, 30 CREDITS, SECOND LEVEL STOCKHOLM, SWEDEN 2021 Does property segment distribution affect the capital structure of real estate companies? An investigative study of the operational risk within different property segments and its effect on the debt ratio in a company Daniel Kamali, Sebastian Rose ROYAL TECHNOLOGY INSTITUTE OF TECHNOLOGY DEPARDEPARTMENTTMENT OF OF REAL REAL ESTATE ESTATE AND AND CONSTRU CONSTRACTIONCTION MANAGEMENT MANAGEMENT Master of Science thesis Title Does property segment distribution affect the capital structure of real estate companies? Author(s) Daniel Kamali, Sebastian Rose Department Real Estate and Construction Management TRITA number: TRITA-ABE-MBT-21399 Supervisor Andreas Fili Keywords Commercial Real Estate, Property segment, Risk, Loan-to-value, Debt, Trade-off theory, Pecking order theory Abstract The real estate sector is a capital-intensive industry, where the combination of debt and equity is used to finance the property investment. Companies tend to increase the loan-to-value ratio, to use financial leverage. However due to banks being more restrictive with their lending as well as having different ways of assessing risk in different property companies, there is a belief that the loan-to-value ratio is affected by the property segment distribution in a company. Based on previous research, there are many factors that could affect the loan-to-value (LTV) in a company such as size, profitability, revenue growth and cost of debt. This paper aims to examine these factors, as well as the operational risk that might be visible in the property segment distribution. The study was done through using a quantitative approach by investigating the largest real estate companies in each Swedish municipality. 614 Swedish real estate companies were investigated and pooled into an OLS regression model. Based on the regression, there is enough evidence in this paper that shows that factors such as size, profitability, revenue growth and cost of debt all have significant impact on the LTV. Furthermore, no general conclusion regarding the relationship between property segment distribution and LTV was found in this paper. Although, there is evidence that residentials- and small house units affect the LTV positively while industrial units affect the LTV negatively. Acknowledgement This thesis is written at the Department of Real Estate and Construction Management, at the Royal Institute of Technology in Stockholm during the spring of 2021. The thesis is a compulsory part of the master’s programme in Real Estate and Construction Management. The choice of subject is based on our interest in the finance and real estate industry. This thesis has given us a deeper understanding of the financing structure in companies, its interaction with the real estate market and the factors that affect the LTV. This was done through a quantitative approach using an OLS multiple regression model. We would like to thank our supervisor Andreas Fili who has been an important factor in the completion of the thesis. Stockholm, 2021 Daniel Kamali & Sebastian Rose Examensarbete Titel Påverkar fördelningen av fastighetssegment kapitalstrukturen i fastighetsbolag? Författare Daniel Kamali, Sebastian Rose Institution Fastigheter och Byggande TRITA nummer: TRITA-ABE-MBT-21399 Handledare Andreas Fili Nyckelord Kommersiella fastigheter, Fastighetssegment, Risk, Belåningsgrad, Skuld, Trade-off teori, Pecking order teori Sammanfattning Fastighetssektorn är en kapitalintensiv bransch där kombinationen av skuld och eget kapital används för att finansiera fastighetsinvesteringar. Företag tenderar att öka belåningsgraden för att använda finansiell hävstång. Däremot på grund av att bankerna på senare år blivit mer restriktiva med sin utlåning och att de har olika sätt att bedöma risker på i olika fastighetsbolag, finn fog att förutsätta att belåningsgraden påverkas av fördelningen av fastighetssegment i ett företag. Baserat på tidigare forskning finns det många faktorer som kan påverka belåningsgraden (LTV) i ett företag, såsom storlek, lönsamhet, intäktsökning och kostnad för lånat kapital. Denna uppsats syftar till att undersöka dessa faktorer samt den operativa risk som kan synliggöras i fördelningen av fastighetssegment. Studien gjordes via ett kvantitativt tillvägagångssätt genom att undersöka de största fastighetsbolagen i alla Sveriges kommuner. 614 svenska fastighetsbolag undersöktes och analyserades i en OLS- regressionsmodell. Baserat på regressionen finns det tillräckligt med bevis i denna uppsats på att faktorer som storlek, lönsamhet, inkomsttillväxt och kostnad för lånat kapital har en betydande inverkan på LTV. Vidare hittades ingen allmän slutsats angående sambandet mellan fördelning av fastighetssegment och LTV i denna uppsats. Det finns dock bevis för att bostäder och småhusenheter påverkar LTV positivt medan industriella enheter påverkar LTV negativt. Förord Denna uppsats är skriven vid Institutionen för Fastigheter- och Byggande vid Kungliga Tekniska Högskolan i Stockholm under våren 2021. Avhandlingen är en obligatorisk del av masterprogrammet i Fastigheter- och Byggande. Valet av ämne baseras på vårt intresse för finans- och fastighetsbranschen. Denna avhandling har gett oss en djupare förståelse för finansieringsstruktur i företag, dess interaktion med fastighetsmarknaden och vilka faktorer som påverkar belåningsgrad. Detta gjordes genom ett kvantitativt tillvägagångssätt med en multipel OLS regressionsmodell. Vi vill tacka vår handledare Andreas Fili som har varit en viktig faktor i slutförandet av denna uppsats. Stockholm, 2021 Daniel Kamali & Sebastian Rose 1. Introduction ............................................................................................................................. 8 1.1 Background ......................................................................................................................... 8 1.2 Problematisation ................................................................................................................ 9 1.3 Purpose and contribution ................................................................................................ 10 1.4 Delimitation ...................................................................................................................... 10 1.5 Disposition ........................................................................................................................ 10 2. Literature review ..................................................................................................................... 11 2.1 Introduction ...................................................................................................................... 11 2.2 Theoretical framework ...................................................................................................... 11 2.2.1 The Miller and Modigliani theorem ........................................................................... 11 2.2.2 The trade-off theory .................................................................................................. 12 2.2.3 The pecking order theory .......................................................................................... 12 2.3 Previous research ............................................................................................................. 12 3. Method ................................................................................................................................... 16 3.1 Quantitative approach ...................................................................................................... 16 3.2 Selection criteria and investigated real estate companies .............................................. 16 3.3 Methodological delimitations .......................................................................................... 18 3.4 Variables included in the analysis ................................................................................... 18 3.5 Quality of research ........................................................................................................... 19 3.5.1 Reliability ................................................................................................................... 19 3.5.2 Validity ...................................................................................................................... 19 3.5.3 Critical discussion ..................................................................................................... 19 3.6 Regression model ............................................................................................................. 20 3.6.1 The regression model ................................................................................................ 20 3.6.2 Assumptions of the multiple regression model ........................................................ 22 Econometric model ........................................................................................................ 22 Strict exogeneity ............................................................................................................. 24 Homoscedasticity ........................................................................................................... 25 Uncorrelated errors ........................................................................................................ 26 No exact relationship between explanatory variables
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