# Tag: real estate appraisal

## The Single-Family Home as a Rental Property Investment — Using Regression to Estimate Value

Regression – no, it’s not what your family and friends accuse you of when you want to trade in the mini-van for a two-seater stick-shift convertible (well, maybe it is, but that’s a topic for a different article).

If you’re familiar with our RealData software, my online video courses, and my other blog posts here, then you know that I’m usually talking about income-producing property like multi-family, retail, office, or the like — seldom about single-family homes. And when we estimate the value of most income properties, we typically do so by looking at their income stream.

Recently, many investors (both big and small) have been buying up single-family homes to hold as rental properties, and that presents something of a conundrum: We still want to analyze cash flows and returns as any investor should, but when we think about the price we pay to acquire a home or the price we’ll get when we sell, our usual income-capitalization may not be the best approach.

Simply put, that’s because most single-family residences are bought and sold based on the price of comparable sales, not on their ability to produce rental income. Often, our comparable sales approach is informal and unscientific. The neighbor got \$250k, so I guess this house is worth the same. Or not.

Linear regression is a statistical technique we can use to approach this with more rigor. To put it into non-technical terms, it lets us look at a situation where we can take some facts that we know (dare we call them real data?) and use them to identify a trend. If a trend really does exist, that trend, in turn, allows us to predict the value of something otherwise unknown.

Let’s look at some examples. Five years ago my property taxes were \$1,000. Four years ago they were \$1,100. Three years ago, \$1,200. Two years ago, \$1,300 and last year \$1,400. Given this trend, what can we reasonably predict we’ll pay this year? Right. \$1,500.

How did we guess? We probably had a flashback to our junior high school algebra class (talk about regression!). In the graph paper of our mind, we plotted a perfectly straight line. The line was formed by a series of data points and it clearly suggested a trend.

Each data point on this graph represents two pieces of information, or “variables:” an independent variable (time) plotted along the horizontal x-axis and a dependent variable (the tax amount) plotted along the vertical or y-axis. The first data point, therefore, is a dot that appears where “5 yrs ago” and “\$1,000” intersect. The second point lands where “4 yrs ago” and “\$1,100” intersect and so on. The tax amount is the dependent variable because it changes as a function of time. In other words the tax bill depends on the year, not the other way around.

When we play connect-the-dots as in the graphic above (hence the name linear regression), we see that those dots form a perfectly straight line. If we extend that line beyond our known data points a bit, we can see that in the current year, assuming that the trend holds up, we could reasonably expect the taxes to be \$1,500. Of course, in real life our ducks don’t always line up so nicely in a row. When they look like the graphic below, we’ll probably need computer software to fit the best possible line to the series of points. Then we can use the resulting straight line to make our predictions.

There are numerous ways that we can use linear regression in real property analysis. We invite you to download a RealData® model to give the concept a spin. “Real estate value by linear regression” is a Microsoft Excel® workbook designed to help us estimate a property’s worth using the market data, or comparable sales, approach to valuation. This approach assumes that recent sales of properties that are nearby and are comparable to the subject provide the best indicators as to the value of the subject.

While we might sometimes use this model with other types of real estate, let’s assume for the sake of example that we want to estimate the value of a single-family residence. Although previously sold homes may be comparable they are unlikely to be identical, either to each other or to the subject being appraised. One may have more land; another may offer more interior space; a third may boast a better layout and so on.

As a rule such differences are generally reflected in the selling prices of the homes. Properties that are otherwise similar sell for more or less as a function of their distinguishing features. If we can identify some measure (index) of the appeal or amenities of the properties in a given neighborhood, then we may also be able to discern a pattern between that measure and the value of the properties — our trend line again. We can then use the pattern to predict the values of other properties in the same locale.

Our model will permit us to determine by regression analysis whether or not a linear relationship exists between selling price and some independent variable that we define. One possible technique is to use the property tax assessment as an index of value. Although assessments seldom reflect true market price, they often provide a good indication of relative value, so they’re worth a try. If the assessments and prices from a number of recent home sales in a neighborhood define a linear relationship, our model can measure the strength of that relationship and use it to estimate the worth of a home not yet sold.

After we open this model we can enter the address, an index and an adjusted selling price for as many as fifteen comparable sold properties. (Regarding the term “adjusted:” We may want to correct for price inflation whenever a sale is more than a few months old.) At the bottom (after #15), we’ll enter the address and the index amount of the subject property. The program will fill in the field for the number of comparables used and compute the subject property’s estimated selling price.

The results appear in a report and graph, in the section below.

Notice that the program will specify a correlation coefficient. This is a new bit of terminology we didn’t see in our simplified explanation above. This number is a statistical measurement of the reliability of the relationship between the index and the adjusted selling price. To put it another way, it’s a numerical way of expressing how straight our dots line up. A correlation of 1.00 is a perfect relationship, while zero indicates that we have completely random data. In most cases, we would like to see a correlation coefficient of at least 0.80 to believe that there is a strong enough relationship between the index and selling price to use that relationship as the basis of a prediction.

As an interesting sidebar, we can see how accurately this regression analysis would have predicted the values of the homes whose actual selling prices we know. That is because the program computes and displays the selling prices that the analysis would have predicted for each of the comparables. We also see the dollar and percentage differences between the projected and actual prices. This section provides a very graphic demonstration of the accuracy — or inaccuracy — of our model’s prediction.

We need to keep in mind that, as with most projections, the quality of our output is entirely dependent on the quality of our input. We certainly have to make appropriate choices for our comparables. Otherwise we can’t reasonably expect to achieve meaningful results. In addition, the kind of index we select must relate consistently to value. If we find tax assessments to be unreliable, we may want to try gross living area or experiment with a scoring system (X points for each bedroom, Y points for each bath, etc.). We may also want to consider trying for even greater accuracy in our predictions by advancing to what’s called “multiple linear regression,” a similar technique where we consider two or more independent variables as possible predictors of an outcome (i.e., a dependent variable).

A regression analysis like the one provided in this model can be very useful because of its ability to provide statistical support to what might otherwise be a subjective estimate of value. Property sellers and buyers can use it to support price negotiations; and agents can use it to enhance the effectiveness of their listing presentations. And of course, investors can estimate the initial cost and ultimate reversion value of a single-family home bought and held as a rental property. With a bit of imagination, linear regression can be used in many ways to poke and prod our analyses and projections. It’s name notwithstanding, it can take us a big step forward.

The information presented in this article represents the opinions of the author and does not necessarily reflect the opinions of RealData® Inc. The material contained in articles that appear on realdata.com is not intended to provide legal, tax or other professional advice or to substitute for proper professional advice and/or due diligence. We urge you to consult an attorney, CPA or other appropriate professional before taking any action in regard to matters discussed in any article or posting. The posting of any article and of any link back to the author and/or the author’s company does not constitute an endorsement or recommendation of the author’s products or services.

## New Podcast: Investing in Income-Producing Real Estate

I had the privilege recently of recording a video podcast with REICLub, where we discussed investing in income-producing real estate: deciding what kind of property you should buy, how to begin the analysis process, understanding the income stream, estimating value or worth, dealing with long-term projections, recognizing common pitfalls, investing with partners.

I invite you to view it here:

http://www.REIClub.com/FrankGallinelli

—Frank Gallinelli

## How to Look at Reserves for Replacement When You Invest in Income-Property

It may sound like a nit-picking detail: Where and how do you account for “reserves for replacement” when you try to value – and evaluate – a potential income-property investment? Isn’t this something your accountant sorts out when it’s time to do your tax return? Not really, and how you choose to handle it may have a meaningful impact on your investment decision-making process.

What are “Reserves for Replacement?”

Nothing lasts forever. While that observation may seem to be better suited to a discourse in philosophy, it also has practical application in regard to your property. Think HVAC system, roof, paving, elevator, etc. The question is simply when, not if, these and similar items will wear out.

A prudent investor may wish to put money away for the eventual rainy day (again, the roof comes to mind) when he or she will have to incur a significant capital expense. That investor may plan to move a certain amount of the property’s cash flow into a reserve account each year. Also, a lender may require the buyer of a property to fund a reserve account at the time of acquisition, particularly if there is an obvious need for capital improvements in the near future.

Such an account may go by a variety of names, the most common being “reserves for replacement,” “funded reserves,” or “capex (i.e., capital expenditures) reserves.”

Where do “Reserves for Replacement” Fit into Your Property Analysis?

This apparently simple concept gets tricky when we raise the question, “Where do we put these reserves in our property’s financial analysis?” More specifically, should these reserves be a part of the Net Operating Income calculation, or do they belong below the NOI line? Let’s take a look at examples of these two scenarios.

Now let’s move the reserves above the NOI line.

The math here is pretty basic. Clearly, the NOI is lower in the second case because we are subtracting an extra item. Notice that the cash flow stays the same because the reserves are above the cash flow line in both cases.

Which Approach is Correct?

There is, for want of a better term, a standard approach to the handling capital reserves, although it may not be the preferred choice in every situation.

That approach, which you will find in most real estate finance texts (including mine), in the CCIM courses on commercial real estate, and in our Real Estate Investment Analysis software, is to put the reserves below the NOI – in other words, not to treat reserves as having any effect on the Net Operating Income.

This makes sense, I believe, for a number of reasons. First, NOI by definition is equal to revenue minus operating expenses, and it would be a stretch to classify reserves as an operating expense. Operating expenses are costs incurred in the day-to-day operation of a property, costs such as property taxes, insurance, and maintenance. Reserves don’t fit that description, and in fact would not be treated as a deductible expense on your taxes.

Perhaps even more telling is the fact that we expect the money spent on an expense to leave our possession and be delivered to a third party who is providing some product or service. Funds placed in reserve are not money spent, but rather funds taken out of one pocket and put into another. It is still our money, unspent.

What Difference Does It Make?

Why do we care about the NOI at all? One reason is that it is common to apply a capitalization rate to the NOI in order to estimate the property’s value at a given point in time. The formula is familiar to most investors:

Value = Net Operating Income / Cap Rate

Let’s assume that we’re going to use a 7% market capitalization rate and apply it to the NOI. If reserves are below the NOI line, as in the first example above, then this is what we get:

Value = 55,000 / 0.07

Value = 785,712

Now let’s move the reserves above the NOI line, as in the second example.

Value = 45,000 / 0.07

Value = 642,855

With this presumably non-standard approach, we have a lower NOI, and when we capitalize it at the same 7% our estimate of value drops to \$642,855. Changing how we account for these reserves has reduced our estimate of value by a significant amount, \$142,857.

Is Correct Always Right?

I invite you now to go out and get an appraisal on a piece of commercial property. Examine it, and there is a very good chance you will find the property’s NOI has been reduced by a reserves-for-replacement allowance. Haven’t these people read my books?

The reality, of course, is that diminishing the NOI by an allowance for reserves is a more conservative approach to valuation. Given the financial meltdown of 2008 and its connection to real estate lending, it is not at all surprising that lenders and appraisers prefer an abundance of caution. Constraining the NOI not only has the potential to reduce valuation, but also makes it more difficult to satisfy a lender’s required Debt Coverage Ratio. Recall the formula:

Debt Coverage Ratio = Net Operating Income / Annual Debt Service

In the first case, with a NOI of \$55,000, the DCR would equal 1.41. In the second, it would equal 1.15. If the lender required a DCR no less than 1.25 (a fairly common benchmark), the property would qualify in the first case, but not in the second.

It is worth keeping in mind that the estimate of value that is achieved by capitalizing the NOI depends, of course, on the cap rate that is used. Typically it is the so-called “market cap rate,” i.e., the rate at which similar properties in the same market have sold. It is essential to know the source of this cap rate data. Has it been based on NOIs that incorporate an allowance for reserves, or on the more standard approach, where the NOI is independent of reserves?

Obviously, there has to be consistency. If one chooses to reduce the NOI by the reserves, then one must use a market cap rate that is based on that same approach. If the source of market cap rate data is the community of brokers handling commercial transactions, then the odds are strong that the NOI used to build that market data did not incorporate reserves. It is likely that the brokers were trained to put reserves below the NOI line; in addition, they would have little incentive to look for ways to diminish the NOI and hence the estimate of market value.

The Bottom Line – One Investor’s Opinion

What I have described as the standard approach – where reserves are not a part of NOI – has stood for a very long time, and I would be loath to discard it. Doing so would seem to unravel the basic concept that Net Operating Income equals revenue net of operating expenses. It would also leave unanswered the question of what happens to the money placed in reserves. If it wasn’t spent then it still belongs to us, so how do we account for it?

At the same time, it would be foolish to ignore the reality that capital expenditures are likely to occur in the future, whether for improvements, replacement of equipment, or leasing costs.

For investors, perhaps the resolution is to recognize that, unlike an appraiser, we are not strictly concerned with nailing down a market valuation at a single point in time. Our interests extend beyond the closing and so perhaps we should broaden our field of vision. We should be more focused on the long term, the entire expected holding period of our investment – how will it perform, and does the price we pay justify the overall return we achieve?

Rather than a simple cap rate calculation, we may be better served by a Discounted Cash Flow analysis, where we can view that longer term, taking into account our financing costs, our funding of reserves, our utilization of those funds when needed, and the eventual recovery of unused reserves upon sale of the property.

In short, as investors, we may want not just to ask, “What is the market value today, based on capitalized NOI?” but rather, “What price makes sense in order to achieve the kind of return over time that we’re seeking?”

How do you treat reserves when you evaluate an income-property investment?

—-Frank Gallinelli

####

Your time and your investment capital are too valuable to risk on a do-it-yourself investment spreadsheet. For more than 30 years, RealData has provided the best and most reliable real estate investment software to help you make intelligent investment decisions and to create presentations you can confidently show to lenders, clients, and equity partners. Learn more at www.realdata.com.

## Podcast: “Learn the key principles to effectively analyzing and evaluating your real estate deals”

I had the pleasure of recording a podcast recently with real estate entrepreneur Kevin Bupp. We discussed what I feel are some of the key principles that every real estate investor ought to understand — and so, I invite you to listen to that podcast here.

## Using Cap Rate to Estimate the Value of an Investment Property

In recent posts I’ve been revisiting some key real estate investment metrics. Last time I discussed the finer points of Net Operating Income, and that topic should serve as an appropriate run-up to the subject of capitalization rates (aka cap rates). What are they and how do you use them?

Income capitalization is the technique typically used by commercial appraisers, and is a part of the decision-making process for most real estate investors as well. I invite you to jog over to an article I’ve written on the subject:

Estimating the Value of a Real Estate Investment Using Cap Rate

In addition, you can download Chapter 10 of my book, Mastering Real Estate Investment, which discusses cap rates and gives you several examples you can work through.

—Frank Gallinelli

####

Your time and your investment capital are too valuable to risk on a do-it-yourself investment spreadsheet. For more than 30 years, RealData has provided the best and most reliable real estate investment software to help you make intelligent investment decisions and to create presentations you can confidently show to lenders, clients, and equity partners. Learn more at www.realdata.com.

## Refi Existing Investment Property to Purchase Another?

One of our Facebook fans, Tony Margiotta, posed this question, which I’m happy to try my hand at answering here:

“Could you talk about refinancing an income property in order to purchase a second income property? I’m trying to understand the refinance process and how you can use it to your advantage in order to build a real estate portfolio. Thanks Frank!”

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The Good News

Your plan – to extract some of the equity from an investment property you already own and use that cash as down payment to purchase another – is fundamentally sound. In fact, that’s exactly what I did when I started investing back in the ‘70s, so to me at least, it seems like a brilliant idea.

Of course, you need to have enough equity in your current property. How much is enough? That will depend on the Loan-to-Value Ratio required by your lender. The refi loan has to be small enough to satisfy the LTV required on the current property, but big enough to give you sufficient cash to use as the down payment on the new property.

For example, let’s say your bank will loan 70% of the value of your strip shopping center, which is appraised at \$1 million. So, you expect to obtain a \$700,000 mortgage. Your current loan is \$550,000, which would leave you with \$150,000 to use as a down payment on another property.

Given the same 70% LTV, \$150,000 would be a sufficient down payment for a \$500,000 property, i.e. 70% of \$500,000 = \$350,000 mortgage plus \$150,000 cash.

But Wait… Some Issues and Considerations

Unfortunately, it’s not the ’70s or even ’07 anymore, so while the plan is sound, the execution may present a few challenges. Best to be prepared, so here are some issues to consider:

• In the current lending environment, financing can be hard to find, and the terms may be more restrictive than what you experienced in the past. Notice that I used a 70% LTV in the example above. You might even encounter 60-65% today, while a few years ago it could have been 75-80%.  In order to obtain the loan, you might also have to show a higher Debt Coverage Ratio than you would have in the past – perhaps 1.25 or higher, compared to the 1.20 that was common before.
• How long have you had the mortgage on the current property?  Some lenders will not let you refinance if the mortgage isn’t “seasoned” for a year or even longer.
• How long have you owned the property? A track record of stable or growing NOIs over time will support your request for a new loan.  You need to make a clear and effective presentation to the lender showing that the refi makes sense, especially in a tight lending environment.
• You need to run your numbers and not take anything for granted. For example, will your current property have a cash flow sufficient to cover the increased debt?
• Keep in mind that you’re adding more debt to the first property, so the return on the new property has to be strong enough to justify the diminution of the return on the first.
• Have you compared the overall return you would achieve from the two properties using the refi plan as opposed to the return you might get if you brought in some equity partners to help you buy the new property?

In a nutshell, refinancing an existing income property to purchase another is a time-honored and proven technique, but it in a challenging lending environment be certain you do your due diligence and run your numbers with care.

Of course I never miss an opportunity to promote my company’s software, so consider using that not only to analyze the deal and its variations, but also to build the presentations that will optimize your chances of obtaining the financing and/or the equity investors.

Frank Gallinelli

## My latest: Mastering Real Estate Investment

I’m hoping that, by now, you’ve heard I have a new book out: “Mastering Real Estate Investment: Examples, Metrics and Case Studies.” It was released just a few weeks ago, and like any proud author I’m pleased to say it’s doing well.

And so…  what’s it’s all about?  An why did I think anyone would read it?

I’d probably describe it best as being two books in one.  Quite a few readers of my first book, “What Every Real Estate Investor Needs to Know About Cash Flow…,” told me they wanted to see more examples of the 37 key calculations I discussed there. That’s an entirely reasonable request; most of us learn better from examples.

So, I began with the idea of creating a workbook of sorts.  For each of my 37 metrics I created a series of sample problems that the reader could work through.  And, of course, I provided the step-by-solution for every problem.

I would humbly submit (all right, maybe not so humbly) that this was a good idea, because to master anything you have to roll up your sleeves and get involved with it.  You can’t just read about these concepts, you have to practice them if you expect to internalize them as part of your approach to investing.  And that, by the way, is how “Mastering” got into the title.

It’s one thing to master these concepts, but it’s yet another to understand how to integrate them and apply them — and that’s why I wrote the second part of the book, the case studies.  I took four different type of properties — a single-family rental, a development project, and apartment building, and a commercial property.

What I tried to do here was to take real-life situations, where you have to deal with asking prices that may be realistic or not; where you encounter seller representations that may be accurate or not; where you have to make judgments and forecasts using imperfect current knowledge.

One of my goals in this part of the book was to show you how to play, “What if…” with your forecasts so as to give you a sense of the range of possible outcomes for your investment if things like rent projections, interest rates, resale costs varied.  Also, in a departure from some of my usual topics, I tried to show how to look at a re-hab project — specifically, how to estimate an appropriate price for a property that you plan to re-develop into an income-producing investment.

Part 2 of the book can stand on its own, so if you’re comfortable with concepts like NOI, cap rate, discounted cash flow and IRR, go ahead an read this part first.

## Welcome, Real Estate Investors and Developers

… to RealData’s blog. You probably know that we’ve always tried to provide a lot of useful content on this site, with educational articles, newsletters, and the like.  We want this blog to be a logical extension of that mission, but we also want it to be a place for more informal discussion.

This is a place that welcomes beginners, experience investors, and real estate professionals alike.  If a topic is pertinent and meaningful to you as a real estate investor, developer, appraiser, consultant, or educator, then it belongs in this blog.

So we may talk about where we think the real estate market is headed.  We’ll certainly discuss  nuts-and-bolts topics, like, “What exactly is a profitability index?” and “What’s a back-door approach and when do you use it?”

We want to tell you about useful resources as soon as we discover them (and so you won’t have to wait for our not-so-rigorously scheduled newsletter).  We definitely will talk about technology.  Do you know about the hidden gotchas lurking in Excel 2007?  And there are plenty of useful tips we can give you about using our RealData software to best advantage.

We’ll do our best to keep the conga line moving, but urge you to jump in with your comments.

Welcome aboard.