Instandhaltungskosten – wie man Immobilieninvestments schönrechnet

11

Von Jonas Schweizer und Gerd Kommer

Im Jahr 2010 begann der „neue deutsche Wohnimmobilienboom“, der bis heute anhält und in manchen mittelgroßen und großen Städten Deutschlands zu nunmehr stratosphärischen Immobilienbewertungen geführt hat. Neu war dieser Boom vor einem Jahrzehnt insofern als er auf einen langen „Zeitlupen-Crash“ bei Wohnimmobilien von 1981 bis 2009 folgte. Ende 2009 hatten die inflationsbereinigten Preise in Deutschland 30% unterhalb derer von 1980 gelegen. Daran erinnert sich heute kaum noch jemand.

Die Nachfrage nach Wohnimmobilien ist heute nach elf Jahren Preisaufschwung enorm. Sie wird befeuert von der verbreiteten Überschätzung der Rendite der Asset-Klasse Wohnimmobilien, vom Irrglauben Renditen in der jüngsten Vergangenheit seien ein guter Renditeindikator für die Zukunft, von FOMO-Emotionen (Fear of Missing Out), von der „Theorie“ Immobilien seien besonders sichere Investments, von der ambivalenten Annahme, Immobilien schützten gut vor Inflation, vom angeblichen Mangel an attraktiven Anlagealternativen und natürlich von historisch einmalig niedrigen Kreditzinsen. Nachfragebremsend wirken nur die enorm hohen Bewertungen und die Zögerlichkeit vieler Banken, Finanzierungen über 80% bis 90% Fremdkapitalanteil auszureichen.

Doch wie dem auch sei: Am Beginn der meisten Immobilieninvestitionen von Privathaushalten sollte eine Wirtschaftlichkeitskalkulation stehen. Als Minimum ist dabei die Frage zu beantworten, ob der Immobilienkauf – mit oder ohne Fremdfinanzierung – für den Haushalt wirtschaftlich tragfähig ist. In eine solche Kalkulation können Input-Größen einfließen wie beispielsweise die erwartete Wertsteigerung, die erzielbare Miete (die tatsächliche Miete bei einem Vermietungsobjekt oder die eingesparte Miete bei einem selbstgenutzten Objekt), das Mietausfallsrisiko, der Fremdkapitaldienst, die Nebenkosten des Kaufes und die Instandhaltungskosten, um die es in diesem Blog-Beitrag geht.

Nach unserer Erfahrung photoshoppen Verkäufer und Käufer zwei Input-Größen in solchen Kalkulationen besonders häufig: Die prognostizierten Wertsteigerungen und die erwarteten Instandhaltungskosten. Der Grund: Verkäufer und Makler haben ein natürliches Interesse eine angestrebte Verkaufstransaktion mit hohen angenommenen Wertsteigerungen und/oder niedrigen Instandhaltungskosten finanziell aufzuhübschen. Käufer photoshoppen bei solchen Berechnungen, weil viele von ihnen einem inneren Zwang unterliegen, ihr emotionales Traumobjekt vor sich selbst und anderen auch ökonomisch attraktiv zu rechnen.

Darüber Einigkeit zu erzielen, was angemessene Annahmen für die künftige Wertsteigerung einer bestimmten Wohnimmobilie sind, ist deswegen schwierig, weil hier viel Spielraum für völlig konträre Ansichten zu Marktentwicklungen und Nachfrage in der langfristigen Zukunft besteht und speziell, weil hier jeder die Markthistorie nach ganz eigenem Gusto interpretiert. Die inflationsbereinigte Wertsteigerung deutscher Wohnimmobilien in den fünf Jahren von 2016 bis 2020 belief sich auf spektakuläre 7,4% p.a., in den 45 Jahren von 1971 bis 2015 auf kümmerliche minus 0,2% p.a.

Allerdings führt bei Instandhaltungskosten – anders als bei Preissteigerungen – bereits ein bisschen nüchterne Recherche zu gut belegbaren Richtwerten, bei denen relativ wenig subjektiver Diskussionsspielraum besteht. Weil diese aus Sachlogik und Historie abgeleiteten Richtgrößen aber deutlich höher (unattraktiver) sind als das, was die involvierten Parteien aus ihrer oben genannten Interessenlage heraus wollen, werden trotzdem oft niedrigere Zahlen verwendet. Die Hintergründe beleuchten wir nachfolgend.

In Immobilienratgeberbüchern, in Immobilien-Blogs und von Baugeldvermittlern wird für Instandhaltungskosten bei Wohnimmobilien quasi seit Anno Domini die Richtgröße sechs bis zwölf Euro pro Quadratmeter Wohnfläche und Jahr genannt. Woher diese Zahlen kommen und wie sie begründet werden, lässt sich nicht nachvollziehen. Sie wurden wohl irgendwann einmal von einem namenlosen Immobilienexperten postuliert und danach von jeder neuen „Expertengeneration“ ohne Überprüfung weitergeführt. Warum diese Zahlen statisch sein sollen, also im Zeitablauf nicht mit der Baukosteninflation steigen, ist ebenso schleierhaft.

In Köln kostete der Quadratmeter Wohnfläche 2020 durchschnittlich 4.200 Euro. Damit war die Rheinmetropole die günstigste der sieben Städte in Deutschland mit über 500.000 Einwohnern. Unterstellt man, dass 85% dieser Kosten auf das Gebäude entfallen, ergeben sechs Euro pro Jahr eine aberwitzig niedrige Instandhaltungskostenquote von 0,17% pro Jahr. Selbst zwölf Euro wären nur 0,34%.

Doch damit hört das Photoshoppen bei Instandhaltungskostenschätzungen nicht auf. In den Marketingpublikationen der Immobilienbranche kursieren Empfehlungen zur Höhe der Instandhaltungskostenrücklage für Wohnungen in Mehrfamilienhäusern, die noch einmal unterhalb der oben genannten sechs bis zwölf Euro liegen. Dann spielt auch das regelmäßige Fehlen des Hinweises keine Rolle mehr, dass sich die an die Wohneigentümergemeinschaft zu zahlende Rücklage nur auf das Gemeineigentum (Außenmauern, Dach, Treppenhaus etc.) bezieht – exklusive Sondereigentum (der wertmäßig größere Teil).

Absolute Instandhaltungskostenrichtgrößen in „soundso viel Euro pro Quadratmeter“ sind schon deswegen abwegig, weil sie weder Rücksicht auf den altersbedingten Zustand, noch auf die Wertigkeit der Immobilie nehmen. Man kann sich beispielsweise zwei neue, unterschiedliche 180 qm-Einfamilienhäuser in der gleichen Mikrolage vorstellen. Die Baukosten des einen betrugen 400.000 Euro, die des anderen 800.000 Euro. Die erste Immobilie wurde einfach und günstig, die zweite hochwertig und teuer gebaut. Es liegt auf der Hand, dass zwei gleich große aber qualitätsmäßig sehr unterschiedliche Häuser in der Zukunft nicht die gleichen Instandhaltungskosten haben werden, wenn man annimmt, dass der Eigentümer bei beiden Wohnungen den gleichen prozentualen physischen Wertverlust pro Jahr ausgleichen will.

Eine schon etwas realistischere Peilgröße für Instandhaltungskosten ist die in der Ratgeberliteratur manchmal genannte Zahl „1% per annum“, bezogen auf den Anteil des Immobilienwertes, der auf das Gebäude entfällt. Häufig wird dabei jedoch im Ungefähren gelassen, dass mit Gebäudewert hier der allmählich zunehmende Zeitwert gemeint ist, nicht statische Wert beim Kauf. Dessen ungeachtet sind auch diese 1% sehr wahrscheinlich noch zu niedrig. Warum, das lässt sich folgendermaßen plausibilisieren.

(1) Beginnen wir mit dem gesunden Menschenverstand: Bei 1% p.a. müsste das Gebäude (unterstellt man einen vollen Ausgleich des Wertverlustes durch die Instandhaltung) ohne diese Instandhaltung 100 Jahre bewohnbar sein (1% linearer Wertverlust pro Jahr = 100 Jahre bis der Wert auf null gesunken ist). Die Absurdität dieser Annahme bezogen auf die Qualität eines durchschnittlichen Wohngebäudes der heutigen Zeit, ganz zu schweigen von den sich über die Jahrzehnte hinweg ändernden Grundrisspräferenzen von Menschen, braucht nicht weiter bewiesen zu werden.

(2) In Deutschland sind bei Vermietungsimmobilien die „Absetzung für Abnutzung“ (AfA) von linear 2,0% p.a. und die tatsächlichen jährlichen Instandhaltungskosten steuerlich abzugsfähig. Die Summe dieser beiden Positionen liegt langfristig über 3,0%. Das ist kein Zufall. Vielmehr ist es das politische Verhandlungsergebnis zwischen Immobilieneigentümern, die aus naheliegenden Gründen möglichst hohe Absetzungssätze wollen, und dem Staat, der aus ebenso naheliegenden Gründen möglichst niedrige Werte will. Man trifft sich dort, wo die Argumente beider Seiten ungefähr gleich gut sind, d. h. in der Nähe der Realität des tatsächlichen jährlichen Wertverlusts aus physischer Abnutzung und Alterung.

(3) Nach der in der Immobilienwirtschaft bekannten „Petersschen Formel“, betragen die geschätzten jährlichen Instandhaltungskosten in einem normalen Mehrfamilienhaus 1,88%, bezogen auf den anfänglichen Wert des Gebäudeteils (Herstellungskosten). Freistehende Häuser (Einfamilienhäuser, Doppelhäuser, Reihenhäuser) unterliegen technisch und konstruktionsbedingt durchschnittlich einem höheren physischen Wertverlust (siehe Stichwort „Peterssche Formel“ in der deutschen Wikipedia).

(4) Die Vonovia SE, Düsseldorf, mit knapp 500.000 Einheiten per Ende 2019 Deutschlands größter Wohnungseigentümer und DAX-Mitglied, wies im Durchschnitt der fünf Geschäftsjahre 2015 bis 2019 eine Instandhaltungskostenquote von 1,2% p.a. auf. Legt man der Kalkulation der Quote nicht den im Geschäftsbericht angegebenen „normalen Verkehrswert“ des Wohnungsbestandes zugrunde, sondern den dort ebenfalls genannten deutlich niedrigeren „bereinigten Verkehrswert“, erhöht sich die durchschnittliche Instandhaltungsquote auf 2,4% p.a. Die Wahrheit dürfte wohl irgendwo zwischen 1,2% und 2,4% liegen. Man kann davon ausgehen, dass die Vonovia aufgrund ihrer Größe Instandhaltung um mindestens ein Drittel kosteneffizienter als ein einzelner Eigenheimbesitzer betreiben kann. Dem steht ein erhöhter Abnutzungsverlust bei vermieteten Wohnungen gegenüber selbstgenutzten Eigenheimen gegenüber, aber dieser dürfte weitgehend dadurch ausgeglichen werden, dass die Vonovia-Wohnungen baulich viel schlichter sind, als das durchschnittliche Eigenheim in Deutschland. (Je schlichter eine Wohnung ist, desto niedriger sind tendenziell die prozentualen Instandhaltungskosten.) Hinzukommt: Wohnungen in Mehrfamilienhäusern (der größte Teil des Vonovia-Bestands) verursachen geringere Instandhaltungskosten als freistehende Einfamilienhäuser, Doppelhaushälften oder Reihenhäuser. Würde man alle genannten Anpassungsfaktoren relativ zur Situation von Kleinvermietern oder Selbstnutzern quantifizieren würden die Spanne von 1,2% bis 2,4% eher noch nach oben gehen.

(5) In einem Aufsatz von zwei Ökonomen der Federal Reserve Bank of Cleveland, einer regionalen amerikanischen Zentralbank, die – anders als Banken, Bausparkassen und Baugeldvermittler – keinem Interessenkonflikt unterliegt, wird eine jährliche Instandhaltungsquote von 2,0% bezogen auf den Immobilienzeitwert einschließlich Grundstück als „gute Peilgröße“ vorgeschlagen (Ergungor/Zaman 2011). Da die durchschnittliche Gebäudequalität wie auch die Baukosten in den USA vermutlich niedriger sind als in Deutschland, kann man für Deutschland – bezogen auf den Gebäudeteil – näherungsweise einen um etwa ein Drittel niedrigeren Satz annehmen (bei einem Gebäudeteilanteil von 85% wäre das 1,57% (= 2% ÷ 85% × ⅔). Zur etwa gleichen Zahl gelangten zwei akademische US-Immobilienökonomen (Aked/Masturzo 2016) in einem Aufsatz für vermietete Immobilien (Büros, Einzelhandel, Gastronomie, Wohnen) in den USA. Ganz ähnlich auch die britischen Immobilienökonomen Chambers u. a. 2020 für Wohnimmobilien in Großbritannien.

Verwendet man als mittlere Peilgröße für eine normale Wohnung eine Kostenquote von 1,5% p.a. auf den Zeitwert der Immobilie und unterstellt, dass das Gebäude 90% der Gesamtkosten ausmacht, dann muss der Eigentümer pro Jahr mit durchschnittlich 1,5% × 90% ≈ 1,4% Instandhaltungskosten rechnen. Über einen Zeitraum von 30 Jahren also noch einmal rund 40% des Zeitwertes für Reparaturen aufwenden.

Diese Kostenquote schließt alles mit ein, was in Reparatur und Instandhaltung fließt – bei einer Wohnung auch eine etwaige Instandhaltungsrücklage, nicht jedoch Ausgaben für einen Verwalter. Ausgaben für Modernisierung oder Erweiterung sind keine Instandhaltung, weil sie ja etwas „Neues“ oder „Verbessertes“ schaffen.

Natürlich ist es möglich für beispielsweise 20 Jahre nur durchschnittlich ein halbes Prozent pro Jahr oder noch weniger für Instandhaltung auszugeben. Dann ist allerdings die zwingende Konsequenz, dass die physische Qualität, und damit der Wohnnutzen der Immobilie, in diesen 20 Jahren merklich abnehmen wird. Soweit das der Fall ist, muss, in einer in die Zukunft gerichteten Wirtschaftlichkeitsrechnung, der Schätzwert für die Wertentwicklung der Immobilie entsprechend nach unten korrigiert werden. Die Schätzwerte für die Immobilienpreisentwicklung und für die Höhe der Nebenkosten hängen also direkt und eng miteinander zusammen. Setzt man die Instandhaltung zu tief an, muss man auch den Preissteigerungsschätzwert entsprechend nach unten reduzieren.

Welche Eigenschaften beeinflussen bei einer spezifischen Wohnimmobilie die Instandhaltungskostenquote oder die Instandhaltungskosten pro Quadratmeter Wohnfläche innerhalb der in diesem Abschnitt genannten allgemeinen, mittleren Größenordnungen nach oben oder unten?

- Freistehende Häuser haben um 10% bis 30% höhere Instandhaltungskostenquoten als Wohnungen.

- Sehr alte Gebäude haben, unter sonst gleichen Umständen, eine rund 10% bis 20% höhere Instandhaltungskostenquote als jüngere Gebäude.

- Gebäude in schlechtem baulichem Zustand haben – solange dieser Zustand nicht durch eine umfassende Sanierung behoben wird – eine 10% bis 30% höhere Instandhaltungskostenquote als Gebäude in gutem baulichem Zustand ohne Instandhaltungsrückstau.

- Hochwertige, teure Gebäude haben eine etwas höhere prozentuale Instandhaltungskostenquote als einfache, günstige Gebäude.

- Gebäude in Gegenden mit hoher Luftfeuchtigkeit, z. B. nahe einer Meeresküste, haben höhere Instandhaltungskostenquoten als Gebäude in Gegenden mit niedriger Luftfeuchtigkeit.

- Gebäude in Großstädten haben höhere Instandhaltungskostenquoten als Gebäude auf dem Land, da die Lohnkosten für Handwerker in Städten höher sind.

- Denkmalgeschütze Gebäude haben deutlich höhere Instandhaltungskostenquoten als nicht denkmalgeschützte Gebäude.

Für die langfristige Zukunft ist tendenziell mit einem, über die allgemeine Produktionsgüterinflation hinausgehenden, Anstieg von Instandhaltungskosten zu rechnen, weil der deutsche Staat beinahe jährlich die baurechtlichen Auflagen im Bereich Energetik, Umweltschutz, Gesundheitsschutz und Behindertengerechtigkeit von Wohnraum verschärft.

Fazit

Der von Vertretern der Immobilienbranche gegenüber Selbstnutzern oder Kleinvermietern gerne verbreitete Nebenkostenrichtwert von sechs bis zwölf Euro pro Quadratmeter pro Jahr oder 1% pro Jahr mögen gutes Immobilien-Marketing sein, kaum jedoch realistische Schätzwerte für eine in die Zukunft gerichtete Wirtschaftlichkeitskalkulation oder Renditeberechnung bei einer typischen Wohnung mittlerer Qualität. Für diese sollten wir einen Satz von nicht unter 1,5% auf den Zeitwert des Gebäudeteils ansetzen. Bei einer Immobilie in schlechtem Bauzustand, bei sehr hochwertigen Immobilien sowie bei freistehenden Häusern dürfte ein Instandhaltungskostensatz von 1,7% bis 2,5% p.a. auf den Gebäudeteil im Allgemeinen eher angemessen sein.

Research Affiliates: Next Season's Meager Harvest In Commercial Real Estate

August 30, 2016

Michael Aked, Jim Masturzo

Key Points

Investing when prices are low and reinvesting to maintain (and upgrade) value are both necessary requisites for successful property investment. Changing fundamentals, such as new construction spend and the vacancy rate, also impact commercial property investments' real return.

Over the last 5 years, US commercial property investors have earned a real return of nearly 10% a year, surpassing the returns of the previous three decades. We estimate a much lower real return for the next 10 years, similar to the returns earned in the 1990s.

We analyze two scenarios over the next decade—one with property prices sticky at current high levels and one with prices that revert to lower norms. Under both, the annualized expected real return is far lower than property investors earned over the last 35 years: 1.4% and 2.6%, respectively.

I made hay while the sun shone. My work sold. Now, if the harvest is over And the world cold, Give me the bonus of laughter As I lose hold.

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—"The Last Laugh" by John Betjeman

The dog days of summer are here. The garden is ripe with the tomatoes, cucumbers, and peppers we have dutifully tended. The summer season is truly a time of gastronomical delight, tempting us to try to extend the period of harvest. Should we leave the fruits longer on the vine? Should we plant more seeds? No. The time of planting and toiling is past. Now is the time to enjoy the fruit of our labor, just as the owners of direct property in the United States, who braved the winter winds of 2008–09, are enjoying today. Their efforts are being handsomely rewarded with a real return of nearly 10% a year since 2010, surpassing any of the three decades following the late 1970s when good recordkeeping began. Unfortunately, we do not expect the strong harvest from commercial property to continue in the decade ahead.

The Past Harvest

Capitalization rates (income per unit of price) of commercial properties have declined over the last 35 years. The average capitalization rate in the 1980s was 7.0%, in the 1990s 7.8%, in the 2000s 6.8%, but in the 5 years ending 2015 only 5.5%. High prices and high capital returns—although great for owners who wish to sell—when unsupported by income lead to low current yields and inevitably to lower long-term returns as capital price gains outstrip the necessary support of cash flows.

We define cash flow as net operating income following the definition used by the National Council of Real Estate Investment Fiduciaries (NCREIF),1 which is the gross income earned from rent and amenities (e.g., parking, laundry facilities, and vending machines) reduced by operating expenses (e.g., repairs and maintenance, insurance, and property taxes). We define price return as the real capital return, or the real appreciation in average market value per square foot.

These income and price change series are probably the easiest and most accessible judgments of the health and return of direct investment in commercial property. Unfortunately, the gross real return of investing in direct property has fallen far short of the promises of income and price. From 2010 to 2015, the investor real return experience in US commercial property has been 9.8% a year, a lofty number and substantially higher than in the preceding decades, but nonetheless 5.3% a year short of that implied by the income and price appreciation of the properties. The average shortfall for the 35-year period beginning in 1980 is 4.1%.

Next Season's Meager Harvest

For a larger view, please click on the image above.

Like a garden, commercial property is expensive and time consuming to maintain, resulting in a real return shortfall. The constant toil of maintaining a property, not only to the expectations of the current pool of renters but also to compete with newer and upper-scale properties being built, can be a daunting task. We explain how the less obvious costs of being a landlord are important in generating robust forward return expectations. First, we consider the direct costs of property ownership, or the toil of constant property maintenance. Second, we turn our attention to the climate, or the impact of unpredictable property price fluctuations.

The Necessary Toil

The largest and most obvious advantage of property investing is the tangible income, or rent, an owner receives. Gross rents, usually a surprisingly large number relative to a property's value, can be a deceptive indicator of a property's income generation. Landlords face numerous calls on cash for capital expenditures (budgeted as reserves for replacement) to repair a building as well as to maintain its competitiveness with newer, cleaner, and better-built structures constantly entering the market. Vacancy, the loss of income from empty offices and apartments, can also be extremely costly.

The amount of reinvestment the owners/investors in a property are willing to make in that property determines the longevity of its income-generating potential. Essentially, three options are available to owners/investors:

1. Maintain minimum quality (i.e., little to no reserves for replacement = maximum aging). The owner undertakes the minimum amount of capital investment in the property to maximize the income yield. The property will, however, suffer the maximum amount of degradation, known as aging, pushing the quality of the building over time into a cohort of lower-quality buildings, and in turn lowering its cash flow potential. Although the investor initially receives the maximum amount of income per year, the value of the building quickly declines over time.

2. Maintain constant quality (i.e., average reserves for replacement = average aging). The owner undertakes enough capital investment to keep the building at a constant-quality level defined as the level of quality on the day the property was completed. By doing so, the investor receives less income because of the reinvestment, but the building suffers less aging. Nevertheless, the property effectively depreciates relative to newer buildings being constructed with fancier bells and whistles, and is therefore no longer considered as desirable as it once was.

3. Maintain current quality (i.e., maximum reserves for replacement = little to no aging). The investor undertakes the level of investment necessary to keep the property at the most current level of quality, including integrating new technology and building standards as they are developed. In this case, an A-grade building can maintain its rating, and thus stem the tide of aging, by constantly upgrading to match the current definition of an A-grade building. This level of investment, however, is usually much greater than the benefits available from rent increases over the building's lifetime.

For our analysis, we consider the constant-quality scenario in estimating reserves for replacement and aging because it is the most common of the three scenarios. In property investment, capital expenditures are lumpy over time because upgrades—a new HVAC system or new roof, for example—may require a large capital outlay one year, followed by much lower expenditures in subsequent years. Over the last 35 years, the average capital investment required to maintain buildings in a state of constant quality was roughly 2% of market value.

Next Season's Meager Harvest

For a larger view, please click on the image above.

The Unpredictable Climate

Properties maintained at the quality of their construction cohort (constant quality) are less desirable to renters as time goes on. The difference in the property price appreciation of a portfolio of current-quality properties compared to a portfolio of aging constant-quality properties can be dramatic. Over the period from 1980 through 2015, on a year-by-year basis, this difference ranged from a high of nearly 15% in the early 1980s to less than 5% today. However, on a decade-by-decade basis, the average has been between 1% and 4%.

Next Season's Meager Harvest

For a larger view, please click on the image above.

For an owner/investor, the level of expenditure required to keep a property at current quality is financially inefficient; however, investors do have other options. The ability to turn over properties in a portfolio, by adding higher-grade properties and selling lower-grade properties, keeps the overall quality of the portfolio from slipping. Of course, such portfolio upgrades come at a cost because buyers of older buildings demand a price discount to compensate for aging. Therefore, from an investor's standpoint, assessing the return prospects of the real constant-quality series is of greatest practical interest because it is actually owned, rather than aspired to.

Property investors can relatively easily invest in both new construction and existing properties, making the buy-versus-build decision a plausible tradeoff. Although new property development opportunities are plentiful around the world, the market is not without barriers to entry. Location, zoning laws, taxes, higher building standards and new regulations, among other considerations, are all tangible factors in the buy/build decision. Over a full cycle, property values are thus rooted to replacement costs, but at different times in the cycle more or less strongly.

Real constant-quality prices for commercial property have moved cyclically around a stable level for close to 40 years. Using long-term average valuation, we determine that current constant-quality property prices are now 20% above trend. This is decidedly a rough method to determine an equilibrium price, and more complex methods are available. One such method would be to utilize Tobin's Q. As measured by Nordby and Taylor (2013), average Tobin's Q ratios across major US markets were in the range of 0.85–1.36 (1.0 = indifference) over the period 2000–2012, with cities such as New York and San Francisco at the upper end of the range. Evaluating ongoing changes in Q ratios could provide a better metric to evaluate current valuation levels; however, we believe our trend method, although a rough approximation, leads to a similar conclusion as more complex methods.

Next Season's Meager Harvest

For a larger view, please click on the image above.

Over the last 35 years, accounting for the reserves for replacement and aging that are necessary to maintain a building at constant quality (constant-quality capital), we can fully account for differences in value between the return expected based on a property's fundamentals and the return realized.

Next Season's Meager Harvest

For a larger view, please click on the image above.

The Current Season

Low property cap rates, barely above reserves for replacement plus aging, and driven by a low-income-to-price relationship that has been falling for quite a few years, indicate the extreme expensiveness of commercial property in the current market. Current levels of overvaluation therefore imply a correction and may even imply a crash, as intimated by the Wall Street Journal in a recent article tagline: "As valuations of stocks and property swell, a sudden shift in sentiment could destabilize growth" (Ip, 2016). We say, not necessarily. Although we would not be surprised by a future correction, fundamentals other than price must be considered.

Two fundamental drivers of property prices—construction spend and vacancy rate—determine both the new buildings to come online and the amount of wasted space in the current collection of properties. Both fundamentals display a cyclicality whose direction abruptly changes during recessionary periods: higher then lower for construction spend, and lower then higher for vacancy rate. Since the last recessionary period ending in 2009, the growth rate of spend has been lower compared to the previous two nadirs, implying fewer new buildings being added to the mix. One reason could be decreased lending after the great financial crisis. The low level of real construction spend is unusual considering vacancy rates are near all-time lows. The combination of building leasable space at near capacity and fewer new buildings suggest that even though property prices are high, a lack of longer-term capacity might hold them there.

Next Season's Meager Harvest

For a larger view, please click on the image above.

The Next Season

The Research Affiliates model uses a building-block approach to estimate global asset class expected returns.2 For commercial property, we estimate expected real return beginning with the anticipated capitalization rate adjusted for our assumptions about reserve requirements and the expected constant-quality price change.

Let's consider two possible future scenarios for the property market. In Scenario A, property prices stay near the current cap-rate multiple of 4.6% (i.e., prices remain high over the next 10 years). Considering a 2.0% reserve and 0.0% price change, the expected real return is an annualized 2.6%. Scenario B assumes a reversion of cap rates to more normal levels over the next 10 years, implying income of 5.4%. Assuming a 2.0% reserve and −2.0% price change, under this scenario the annualized real return is 1.4%. The important takeaway is that, under both scenarios, the expected real return over the next decade is far lower than property investors have realized over the last 35 years.

Next Season's Meager Harvest

For a larger view, please click on the image above.

We can add granularity to Scenario B by extrapolating our assumptions to the return prospects of 16 property type and regional segments and examining their respective weights in the total property portfolio. Apartments appear to be an attractive segment of the market with an aggregate 3% real expected return, but as only a small part of the value-weighted portfolio, consequently adds little to total expected return. The Office segment, with an aggregate real expected return of zero from the heavy weight in the negative-expected-return East Coast region, has a much greater impact in the value-weighted portfolio, depressing the overall expected return for US commercial property over the next decade.

Next Season's Meager Harvest

For a larger view, please click on the image above.

Prospects For The Future Harvest

Investing in property is similar to the widespread practice of gardening in northern latitudes: seasonal and full of hard toil, but at harvest time often reflected upon as a less demanding endeavor than it actually was. Likewise, after a period of great returns (similar to the abundance of the harvest), it is tempting to believe property investments will provide in the future as plentifully as they have in the past. Acknowledging that planting when the weather is cold (cheap prices), toiling is necessary to encourage growth (reinvestment), and the presence of a variable climate (randomness) all impact our ability to produce future excess return, we might assess our investment prospects with greater skepticism and more realism.

Similar to the foolishness of planting summer crops as the air starts to cool in the hope of repeating the rich harvest, expecting today a rerun of the amazing 9.8% a year real return from commercial property earned over the last 5 years should draw mirth from our neighbors. Heeding this practical lesson, we estimate an expected real return for US commercial property of 1.4% a year over the next decade. Under a scenario in which price and yield reversion in current cash flows are sticky around current levels, we estimate an average annualized expected real return of 2.6% over the next 10 years. Both estimates are in line with the exiguous returns of the 1990s. Prices today might appear high, but due to fundamentals—including new construction spend and vacancy rate—high prices, like an extended summer season, may be around longer than would otherwise be expected.

References

Ip, Greg. 2016. "The Economy Is Again under the Sway of Asset Prices." Wall Street Journal, July 27.

Nordby, Hans, and Michael Taylor. 2013. "The Price per Pound and Replacement Cost: The Effects of Q on Office Investment." Journal of Portfolio Management, vol. 39, no 5 (Special Real Estate Issue): 76–88.

Endnotes

The full list of income and expense items contained in the NCREIF data is available at https://www.ncreif.org/documents/event_docs/ StPeteBeach2014/GlossaryofTermsv2TH.pdf.

All of our asset class returns are available on our Asset Allocation site.

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Michael Aked, CFA, Director, Head of Asset Allocation, Research Affiliates, LLC

Jim Masturzo, Vice President, Asset Allocation, Research Affiliates, LLC

Buy a Home or Rent: A Better Way to Choose

- O. Emre Ergungor

- Saeed Zaman

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Knowing whether buying a home is a better financial move for a family than renting requires a consideration of costs and options that people often neglect to factor in. One aspect of the calculation that is almost always overlooked is uncertainty—the fact that no matter how good one’s estimates of the future are, the future can turn out differently than projected. Incorporating uncertainty into the rent-or-buy calculation gives potential homebuyers information that can improve their decisions. While incorporating uncertainty is complicated, it’s made easier with the Cleveland Fed’s online calculator.

04.28.2011EC 2011-06DOI 10.26509/frbc-ec-201106

Knowing whether buying a home is a better financial move for a family than renting requires a consideration of costs and options that people often neglect to factor in. One aspect of the calculation that is almost always overlooked is uncertainty—the fact that no matter how good one’s estimates of the future are, the future can turn out differently than projected. Incorporating uncertainty into the rent-or-buy calculation gives potential homebuyers information that can improve their decisions. While incorporating uncertainty is complicated, it’s made easier with the Cleveland Fed’s online calculator.

Buying a home is the largest and most complex financial decision an average family will make in its lifetime. Even with the recent decline in home prices, the share of net worth that a typical U.S. household invests in its home equity—12 percent—is sizeable. Such a large investment requires careful consideration.

What makes the decision complex is the large number of variables that must be taken into account. Of course when buying a home there are choices to make on location, nearby amenities, school systems, and so on, but the financial decision itself involves a host of other variables.

While the basic questions might seem simple—“how much can I afford?” and “will the home be worth more than I paid for it when I sell it?”—the answers depend partly on other choices being made. Do you go for a 15-year mortgage or a 30-year? Do you choose a fixed rate or an adjustable rate? The answers also depend on conditions outside of a homeowner’s control. If you choose an adjustable rate, for example, what is the likely future path of your rate? Will you be able to handle it in 5 or 10 years? How much is the home you might buy likely to appreciate? How will the economy be doing in 5, 10, or 20 years?

So the decision process around buying a home requires making some good guesses about the future. And while most people can come up with guesses for all of these questions, taking the forecasting process one step further could help them improve their results. Even the most sophisticated forecasts can diverge in the end from what actually happens. By taking that uncertainty into account, homebuyers can see what outcomes their choices might lead to if conditions turn out differently than they expect. For example, what would the impact on a family’s wealth be if the actual appreciation rate of their home is lower or higher than anticipated? What would their mortgage payments be if their adjustable rate happens to be lower or higher than the forecast?

Our goal in this Commentary is to show how this uncertainty can affect the decision to buy a home. We describe the ways in which some important factors influence the possible financial outcomes of owning a home, and we introduce a tool for working through the decision.

A Framework for Thinking through the Home-buying Decision

A good way to get a handle on the financial implications of buying a home is to calculate the costs and potential gains of owning a home for some period of time and compare them to those for renting. People typically compare monthly mortgage payments and rents, but many more factors figure into the financial equation. Taking more of those factors into account can give a potential homebuyer a much better idea of which option will really cost less in the end or which will provide greater financial gain.

To illustrate the complexity of the buy versus rent decision, we start by examining the underlying costs and potential gains involved in owning and renting (table 1). Then we consider some of the factors that can affect those costs and gains. On the homeownership side, the key potential gain is the equity the owner extracts from the house when he sells the property. From that equity we subtract the cost of maintenance and property taxes as well as other homeowner expenses such as insurance. The federal tax code allows some homeowners to deduct their mortgage interest and property tax payments from their taxable income, which results in significant tax savings. The tax benefits are added as a plus that reduces the net cost of homeownership.

Table 1. Comparison of Costs

Table 1. Comparison of Costs

However, the potential tax savings from owning the home depend in part on whether or not you are itemizing your deductions at tax time, your marginal tax rate, and whether or not you are subject to the Alternative Minimum Tax. While mortgage interest and property tax payments can be deducted from taxable income, this deduction does not make sense for everyone. For many moderate-income individuals, the standard deduction is greater than their itemized deductions. Therefore these individuals do not receive the tax-benefit of their housing expenses.

On the rental side, the key cost is the aggregate rent payment. To see the potential gains, consider a renter’s ability to save money and invest. Because people tend to move into larger houses with more amenities when they buy a home relative to the property they have been renting, the mortgage payment plus property taxes and maintenance costs will typically be larger than the rent payment. This means that if a family chooses to remain renters, they could be saving the difference between the rent and the money they would have spent as homeowners, and that savings could be invested and earn income over time. The value of the savings is the potential financial gain of renting, and the difference between it and the total rent expense is the net cost of renting.

Considering all of these costs and gains gives a more accurate estimate of the potential gain (or loss) of owning and renting, and that information can help people decide between the two options. However, while these potential gains and losses can be estimated into the future, they cannot be known for certain. That uncertainty can impact the homeownership decision as well.

To see how uncertainty affects the cost of either option, let us suppose you are considering the purchase of a $100,000 house with a $10,000 down payment and a fixed-rate mortgage. All the details of the purchase are in table 2.

TABLE 2. DATA FOR SCENARIO ANALYSIS

Home details

Purchase price

$100,000

Estimated annual appreciation

2%

Length of time you will own the home

15 years

Property tax

1.8% of home value per year

Maintenance costs

2% of home value per year

Homeowner’s insurance (HOI)

0.25% of home value per year

Mortgage details

Down payment

$10,000

Closing costs

$2,500

Length of mortgage

30 years

Fixed or adjustable

Fixed

Mortgage rate

5%

Points

0

Rent and anticipated rent inflation

Rent

$700

Renter’s insurance

4% of monthly rent

Rent inflation

2%

Other assumptions

Itemize mortgage interest for tax deductions?

Yes

Marginal income tax rate

25%

Savings rate

50%

CPI Inflation

2% per year

Alternative investment yield

6%

To calculate the equity that you will extract, we need to estimate the home’s appreciation during the time you own it. Over the last 100 years, with the exception of the boom in the last decade, home prices grew on average at the rate of inflation. So let us assume that home prices will grow, on average, 2 percent per year for the next 15 years, which we will say is the expected duration of ownership in this case. Next, we assume that your marginal tax rate is 25 percent and that you will itemize. Going back to the example in table 2, our calculations suggest that the inflation-adjusted value of your tax savings over 15 years is about $20,000. With these assumptions, your house will be worth almost $135,000 15 years from now.

Let us suppose now that your anticipated appreciation rate turns out to be off by 0.1 percent, which we would consider a minor error. If the actual appreciation is 2.1 percent, the home is worth almost $137,000 in 15 years; if the appreciation is 1.9 percent, the future value of the house is close to $133,000. The $4,000 difference between the two valuations 15 years from now is equivalent to $2,941 in today’s dollars (adjusting for 2 percent inflation). In other words, the financial impact of a very small deviation in the actual appreciation rate from your expected rate could be as large as 2.9 percent of your home’s eventual value. The major uncertainty on the rental side is around the returns that can be earned with the rent-and-invest option. Those returns depend significantly on the particular alternative uses people choose for the money they’re not spending on a house. Their investment choices will be based on guesses about future returns, but those guesses could easily be wrong.

Most people look at the long-term performance of various asset classes to form their expectations about future returns. For example, the average return on stocks from 1950 to 2008 was 11 percent. Average inflation over this period was only 3.5 percent. In other words, stocks delivered returns that outpaced the decline in the purchasing power of the dollar. But assuming that returns in some particular period in the future will be similar to that average ignores the possibility of a decade of flat real returns (like the 1970s), two decades of double-digit returns (like the 1980s and 1990s), or a decade of negative returns (like the first decade of this century). These kind of fluctuating conditions can have a significant impact on the decision to purchase a home.

Let’s say you choose an alternative investment with an expected yield of 6 percent (table 2). Instead of buying a house, if you could invest everything you would have spent on the home—your down payment, closing costs, the difference between your rent and your mortgage payment, the property taxes, and the expected maintenance costs—in this alternative, you would have significant savings in the bank at the end of 15 years. Of course, most people will not save everything they can, so we assume that you will realize only 50 percent of your savings potential when you are renting. For example, your $100,000 home with a $90,000 mortgage will have an initial monthly principal and interest payment of $483. In addition, you will pay $39 for private mortgage insurance (until you have 20 percent equity) and $250 for property taxes and homeowner’s insurance, which brings the total up to $772. In table 1 we assumed that your rent is $700, which means you save $72 a month by renting. Half of that equals $36 a month, which translates into $28,000 in savings at the end of 15 years in today’s dollars. This amount assumes that you saved all of the money you would have spent on down payment and closing costs.

The uncertainty that investment returns are subject to could affect these calculations considerably. If your expectation is off by 1 percent (up or down), for example, your savings could be as high as $32,000 or as low as $24,000. The difference, $8,000, is equivalent to 8 percent of the value of our hypothetical home.

The rent-or-buy comparison gets even more complex if we work with an adjustable-rate mortgage. Consider the mortgage described in table 3. The mortgage rate is 4 percent. It is constant for two years, but it can be contractually reset to as high as 12 percent. Under the worst-case scenario, the rates will adjust higher at the maximum possible increments, and a 12 percent mortgage rate will be reached in the sixth year. While the first principal and interest payment on the mortgage was $430, the payment may adjust to as high as $883, more than a 100 percent increase in six years.

TABLE 3. ARM CHARACTERISTICS

Mortgage details

Initial mortgage rate

4%

Points

0

Initial fixed rate period

2 years

Adjustment period after initial fixed

1 year

Floor

3%

Initial adjustment cap

2%

Rate adjustment cap

2%

Lifetime cap

12%

Accounting for Uncertainty

The discussion so far shows that deviations from expectations on home appreciation rates, investment returns, and adjustments to mortgage rates all have a significant impact on the homebuyer’s welfare. We have considered slight deviations from forecasts in these variables, but the deviations can be much greater in actuality. We also considered each factor in isolation, but more than one can deviate from expectations at a time, and the results can be unexpected. Allowing these factors to change randomly rather than being fixed at their expected levels and observing how they interact would be informative.

Using the home purchase calculator on Clevelandfed.org, we ran an experiment in which home appreciation rates could be anywhere between −2 percent and 6 percent, with the most likely outcomes concentrated around 2 percent. This gave us an expected appreciation rate of 2 percent but with a lot of volatility. Similarly, we assumed that the alternative investment yield varied between 0 percent and 12 percent, with the most likely outcomes concentrated around the middle point, 6 percent. For additional flavor, we adopted the adjustable-rate mortgage and assumed that over the life of the loan, interest rates could vary between 4 percent and 12 percent.

To incorporate uncertainty into our calculations, we have to repeat this experiment multiple times, observing a different outcome for home appreciation, the mortgage rate, and asset returns each time. The home-purchase calculator lets us do this complex task easily. Using the parameters in tables 1 and 2 with the uncertain outcomes above, the calculator repeats our experiment 1,500 times and counts the number of times the net cost of homeownership is lower than the net cost of renting. In this case, homeownership is the better choice.

Figure 1 illustrates why this is so, by assigning the relative homeownership gain or loss obtained from each simulation to one of 4 bins. The label under each bin denotes the range of the outcomes it contains. For example, a gain of $2,000 from homeownership relative to renting would be counted in the third bin, which covers the $0 to $5,000 range. Of the 1,500 simulations that we ran, 45.8 percent fell into that range. Similarly, a loss of $8,000 would go into the first bin. The height of each bar represents the frequency with which outcomes fell into a particular bin. For example, 6.87 percent of our outcomes were in the −$5,000 (loss) to $0 range.

Figure 1. Outcome Distributions

Figure 1. Outcome Distributions

Source: Authors’ calculations.

Two important observations can be made from figure 1. First, given our parameter choices, losses from homeownership up to $10,000 and gains up to $10,000 are possible. And second, 92.7 percent of the experiments lead to a positive outcome for homeownership. We deduce that the probability of a gain from homeownership is 92.7 percent given our parameter choices. Keep in mind that if we chose different parameter values, the probability of a gain to home ownership could be very different, even the opposite. But wouldn’t that be good to know before deciding to buy a home?

Buy or Rent?

Just like any other investment, there are risks associated with a home purchase. Understanding the nature and magnitude of the risks is a crucial first step in making an informed decision about whether you are comfortable with the potential returns of buying a home. People differ in their risk tolerance, so we cannot tell you if the purchase is the right move for you.

Furthermore, financial concerns are clearly not the only driver of home purchases. There are many benefits and costs associated with homeownership that cannot be expressed in dollars. For example, on the benefit side, people like to have a home they can call their own, they like to work in their yards, and so on. On the cost side, some people don’t like to spend their time mowing the lawn or shoveling snow.

We realize that the decision to buy or rent goes beyond a consideration of financial outcomes. But taking them into account is the only way to get an accurate idea of whether buying a home is really a better choice for a family financially than renting. And while it can be difficult to calculate the likely future outcomes, a tool like the Cleveland Fed’s home purchase calculator can make it easier.

The views authors express in Economic Commentary are theirs and not necessarily those of the Federal Reserve Bank of Cleveland or the Board of Governors of the Federal Reserve System. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. This paper and its data are subject to revision; please visit clevelandfed.org for updates.

Suggested Citation

Ergungor, O. Emre, and Saeed Zaman. 2011. “Buy a Home or Rent: A Better Way to Choose.” Federal Reserve Bank of Cleveland, Economic Commentary 2011-06. https://doi.org/10.26509/frbc-ec-201106