Thursday, September 24, 2020

C&W Office Forecast

C&W came out with an interesting study on the office asset class. Here's the link:

A few takeaways:

  1. In general, for a brokerage house to publish something with a relatively bearish slant like this is interesting. I say it's a bearish slant just because I think most other shops are saying the recovery will be a bit quicker than this C&W report.
  2. They're forecasting a brutal 2021. Overall, they believe the negative impact on office fundamentals from COVID will be greater than from the great financial crisis.
  3. Post-COVID, C&W is forecasting the share of professionals working from home to double compared to pre-COVID.
  4. C&W thinks it's unlikely that average square foot / employee will increase. If anything, they think it will continue to shrink or hold steady. This is important because some office investors think employees will demand more space in their offices, creating more demand, and potentially offsetting reduced demand due to work from home. C&W doesn't see that being the case.
  5. C&W is forecasting occupancy and rents to not fully recover until 2025.
Investors will read this and then wonder, "When is the correct time to jump in the market?" It's an interesting question. An investor might think, "Gee, I'll just wait until the fundamentals start to improve in the second half of 2022 or early 2023 when prices have hopefully hit bottom and I should make a bunch of money..." This hypothetical investor might be right, but there are a few other factors to consider:
  • Markets are very efficient at pricing in future events. If you wait until the fundamentals turn positive, you might be too late.
  • It's possible prices don't necessarily track fundamentals. For example, in the Bay Area some submarket fundamentals didn't get back to dot-com-bubble highs of 2000 and 2001 until the mid-2010's. Does that mean prices were at their peak in 2000 and 2001 and didn't get back there until the mid-2010's? Nope. Actually, prices were back to their dot-com-bubble highs between 2004-2005. How is that possible? Well, interest rates dropped like crazy. This pushed cap rates down and offset the decline in fundamentals to the point where it actually pushed prices back to dot-com-bubble highs. This means buying opportunities may not be dictated by changes in fundamentals. 

  • Using the great financial crisis as a data point, commercial real estate lagged the overall recovery by a few years. The trough in the overall economy was in 2010 and it wasn't until 2012 that commercial real estate hit its low. The big differences, in my opinion, between then and now is that commercial real estate was overbuilt and there was an issue on the supply side along with the issue on the demand side, and leverage was much more extreme. This cycle, it doesn't seem like there's as much of a supply issue and leverage has overall stayed much more conservative. There is also a lot of dry powder on the sidelines that can come in and recapitalize deals if needed. For those reasons, I think there's a compelling case to be made that prices will not drop dramatically.
It'll be interesting to see how correct this C&W paper turns out to be. It tends to go along with what I think the future of office looks like, but we'll see.

Monday, September 14, 2020

How To Misuse Statistics, Coronavirus and Real Estate

The coronavirus pandemic has been a fascinating case study on how statistics can be used to mislead people. Below I'll show a few examples and connect it with real estate. As a disclaimer, none of this discussion is meant to minimize the tragedy that has been caused by coronavirus, it's just a critique of how the media has been using statistics in a misleading way.

Context Matters When Discussing Statistics

Here are two headlines just from today on CNN:

Let's look at the first headline / article. The writer / editor is clearly trying to generate drama by throwing in the 194,000 number. Most people see 194,000 and they think, "whoa, that is a ton of people, coronavirus is killing people like crazy..." They are, of course, partially right, 194,000 is a lot of people and coronavirus is killing people. However, the headline and even body of the article are missing a lot of the context around that number. Here are just a couple of questions that you should ask to really figure out what this number means. One, over what time period is the 194,000? Is this over two months, three months, nine months? Seems like an important piece of info. Two, what's the typical age of these people dying? Also seems important. I think any reasonable person can agree that an 85-year-old dying in a nursing home from coronavirus is different from a perfectly healthy 20-year-old marathon runner. Three, how many of the 194,000 died OF coronavirus vs WITH coronavirus? I have a brother that's a doctor in a department that treats very old sickly people and something he's told me is a good portion of the patients that die in his department don't have a clear cause of death. Many are so old and sickly that there's any number of things someone could claim they died of. This is an issue that's largely ignored by the media when discussing coronavirus deaths. Four, related to Three, how many of those people would have died from something other than coronavirus, like the flu? The point here is, are these 194,000 causing excess deaths over that period of time, or, put another way, how many more deaths has coronavirus caused over that period of time than you would typically expect based on historical data?

More likely than not, the answers to those four questions would make the 194,000 number less scary. The context matters.

The second headline / article is more or less the same thing. Throw out a big number that sounds scary. Again, context matters. How many of these 45,000 are really sick? How many are false positives? How many have been hospitalized? How many have died? In these cities with the colleges, has there been much spreading of coronavirus off-campus? Have deaths spiked in the cities? Etc... Again, answering these contextual questions would likely give us a better idea of how we should digest the number and I suspect it would make the number seem less scary.

This same principle applies to real estate. Whenever someone gives you a statistic about a market's performance, a property's historical performance, an asset class's historical performance, etc..., you need to be aware of the context surrounding that statement. For example, someone might tell you Submarket X is a great submarket. The demand it's been experiencing is off the charts. In fact, net absorption in the market has been 100k SF / year. You might be tempted to buy a property with a lease-up play in mind based on that info. However, what if I told you that developers have been building at a pace of 200k SF / year, implying vacancy has actually been going up by 100k SF / year. What if there was 500k SF scheduled to deliver over the next 2 years as well? Maybe the 100k SF / year of net absorption isn't that great after all. Make sure you understand the context.

Misidentifying Underlying Driving Forces of Statistics

This is the classic issue that can be exemplified with the following thought process: "Rain dancing at the beginning of April make the Gods happy and brings rain in the following months..." I think we all know at this point that it's not actually the rain dance that brings rain, it's just the natural cycle created by how the Earth works. Even though we understand this silly example, we still fall victim to this issue of confusing underlying causation when statistics are presented.

The media makes this exact mistake repeatedly with the coronavirus. Here's a CNN headline / article from a few weeks ago:

The headline / article suggest students gathering at universities is leading to massive outbreaks and leading to coronavirus spreading like crazy. I.e., people gathering together, even with very strict protocols, is the causation for all of these positive tests. Very scary stuff. However, no where in the article does it mention the fact that every kid at these colleges were getting tested for coronavirus like crazy at the beginning of their semesters (late August, early September every student had to be tested to even go on campus and then once they're on campus there is extremely tight testing for anyone with symptoms and a tracing system). This is an important point. Most college-aged people are asymptomatic, or at most have very mild symptoms and are likely to not get tested. This begs the question, is it really being on college campuses that's driving the increase in cases, or are kids on college campuses just being tested at a much higher rate which is driving case counts. If the latter is true, then colleges aren't necessarily helping spread coronavirus and it might just be that what was always the case (college age kids had a lot of cornoavirus cases) is finally being reflected in official stats.

The same principle applies in real estate. Maybe you're thinking of buying a property and the submarket's two-year historical performance has been great. Vacancy has stayed low, there's been consistent rent growth, etc... At first glance maybe you think it has great demand drivers that will continue into the future. Then maybe you start digging in a bit more. You look at demographic projections and see population, median income and median home price is expected to decline. Well that's not a sign of a healthy submarket. Then you dig in more and figure out that prior to two years ago the submarket actually had increasing vacancy and declining rent rates and that the only reason things started improving two years ago is one of the large buildings in the market was demolished for a new development project, i.e., there was a one-time reduction in supply that caused a bunch of demand in other buildings. Clearly, the underlying demand driver that started two years ago was a one-time reduction in supply, which is not sustainable.


Don't just trust stats that the media tells you and don't just take stats that brokers, colleagues, etc... give you at face value. Be skeptical. Dig in to figure out the context. Reason out in your own mind what the true underlying causations are.

Thursday, August 6, 2020

Real Estate as an Asset Class Post-Coronavirus

The coronavirus pandemic has led to changes in America that we probably never thought possible. One of the most glaring examples of this are lockdowns. If back in 2019 someone told you, "at some point in 2020 the government will force Americans to stay in their homes and only let them leave to go to the grocery store, will mandate Americans to wear masks under the threat of fines and will not let parents send their kids to school for a good portion of the year..." you probably would have thought that person was crazy--that type of stuff happens in China, not America. Putting aside whether the lockdowns were necessary / effective / an overreach of governmental authority, I think an enduring question will be do we now live in a new paradigm where Americans are more comfortable with and will experience more governmental control.

In terms of how this applies to real estate, similar to lockdowns, real estate saw its own government intervention. For several months now in places like SF, NY, the government has made it so landlords can't evict tenants. This is important because this is the landlord's primary form of leverage in the constant tenant vs landlord negotiation / battle. The tenant's primary form of leverage is it can just stop paying rent at some point in time and create a huge headache for the landlord, both financially and in terms of time and effort. Removing the ability to evict tenants (this happened for both commercial and residential tenants, by the way) has given tenants massive leverage over landlords. Put another way, the government has tried to shift the pain that this pandemic has caused within the real estate market onto landlords and ease the burden that tenants feel.

I think in a typical economic downturn, the pain would first be felt by tenants. As their balance sheets eroded, they would then stop paying rent and the pain would start transferring to landlords, but first tenants would have to get to max pain. This is sort of how the free market has decided things should happen. In this pandemic, the government has tried its best to flip the standard order of operations. Again, putting aside whether this is morally correct / okay to disrupt the free market and pick winners and losers, it's just where we are right now. To me, the big question is, will the government make this a common practice going forward?

Let's be honest, landlords aren't exactly a popular group. No one likes their landlord, every article written in the media about landlords casts them in a rent seeking / unethical / Scrooge type light, etc... Probably more to the point, there are a lot more tenants than there are landlords, i.e. tenants as a voting block are more valuable than landlords as a voting block. It's easy to see why politicians would try to transfer economic pain from tenants to landlords. The question as a prudent real estate investor is, if we are in a new paradigm in terms of governments being exceptionally bold and willing to manipulate free markets and assign real estate owners as the primary takers of pain in an economic downturn, how will this change the asset class going forward?

Here are my high level thoughts and, no, I don't really have evidence or stats to support any of these assumptions, these are just my gut feelings on how things will shake out:
  • Less business friendly areas / populations more supportive of government intervention are likely to keep this trend going forward--I think, generally, once you start these government interventions, you tend to not stop. Places like NY, SF, LA, Chicago, Portland, etc... are likely to see different forms of lockdowns in the future, even after the coronavirus pandemic, and are very likely to do eviction moratoriums / shift pain onto landlords during economic downturns.
  • This will lead to less consistent / less durable cash flows for real estate investors in those areas, or, stated another way, real estate as an asset class will have more risk associated with it in those areas.
  • This will lead to less investor appetite, which leads to higher return requirements, which leads to higher cost of capital.
  • Assuming the total dollars chasing real estate deals remains relatively fixed (a big assumption, but one that seems somewhat supports by fund raising data), areas that were less prone to government intervention during this pandemic (FL, TX, sunbelt in general, WI, etc...) will become more attractive.
To put in a more relatable way, if I had $5 million that I wanted to invest in an apartment deal and I'm relatively agnostic to location (I don't only want to invest in CA because I live in CA and want to manage it myself--I'm willing to put my money with an operator anywhere in the country), then I would would be much more inclined to put my money into a deal in TX vs NY or CA than I would have been pre-coronavirus.

It'll be interesting to see if this really does play out in a more macro sense. Will LPs start allocating less to areas with more aggressive local and state governments? 

Tuesday, August 4, 2020

COVID Impact on Office Real Estate

The big question in commercial real estate markets is what will COVID's lasting impact be on how commercial real estate is utilized going forward? In particular, office real estate is facing an existential crisis of sorts. White collar workers have been working from home since March. Has productivity dropped much? Are teams still able to collaborate effectively? Will people want to go back to the office even after this all settles down?

If the answer is working from home is going to be a big part of the future, then that means office could be facing a permanent drop in demand. If true, then many, if not most, markets would be oversupplied, and landlords could face years of high vacancy and lack of rent growth. The deterioration of fundamentals would lead to less investor demand / capital flows and more unattractive debt which would increase the cost of capital. 


Based on what I've seen and heard, managers are fairly shocked at how productive their teams have been working from home. There seems to have been little productivity loss. Even if there was productivity loss, from a managers perspective, if I have a 10-person team that requires 1,500 SF of office space that costs $50k / year, if I can let half my team work from home and drop the office cost down to $25k / year and my team's still 90% as productive...then that might be a decent trade-off.

Some of the counters to the "there hasn't been productivity loss" arguments are:

  • "There's nothing to do right now. People can't travel, go to bars, etc... When that starts up again, there will be a big productivity loss."
  • "People have been predicting the demise of the office for years. It hasn't happened yet. Why would it be different this time?"
I think both arguments have merit. The first certainly has some truth, but at the same time, anyone with an internet connection and a computer has access to a lot of entertainment options that didn't exist 10 years ago (Amazon Prime, Netflix, computer games, social media, etc...). The second is also true but I think there is an argument that things are different this time. For example, take a look at this chart showing internet speeds from 2007-2017 (couldn't find anything that went to 2020...):

From 2007 to 2017, the average internet speed in US households increased 10x. I'm sure now in 2020 the average is well over 20 mbps. Just think of how much better working remotely would be with 2020 internet speeds vs 2007. Similarly, we just have better tools to enable working remotely than we did in the past. Dropbox has made VPNs somewhat obsolete for many businesses. We have programs like Zoom and Teams, combined with improved household internet speeds, that enable 20+ person video meetings. There are many more examples...


From my work-from-home experience, I've found collaboration to be more challenging. Anecdotally I've heard the same thing from other managers. It just is easier to walk into someones office / cube and ask them a question vs calling or emailing. Communication is also just easier, in my experience, in-person vs over the phone / video call. People are more likely to interject and contribute to a 5-person meeting that's happening in-person vs over a video call.

To me, the bigger problem is that you lose the relationship building / human element of the work experience. I think it's important to get reminders that your boss / people you manage / colleagues are human beings and not just work robots. I don't think you get those kind of reminders unless you're in the office, going to lunch together, doing team building events, etc... One of the perks of working for a company is you get to meet people, build a work relationship and expand your network. I just don't think that growth is happening without going into the office.

A compelling counter to the above argument is "well, it sort of levels the playing field on company culture. A company with a crappy culture that made going into the office unpleasant now isn't that different than a company that had a great office culture. It's actually giving employees more / better work options. Likewise, should people really be getting jobs / ahead in their careers because of networking? Doesn't that just encourage frat-guys to keep hiring each other?" As I said, I think this argument actually does have some merit, but I think the positive aspects of office collaboration still outweigh these downsides.

Do People Want to Go Back to the Office?

Anecdotally, here's what I've heard:
  • People with living situations non-conducive to working from home (live in a small apartment in a big urban city with lots of street noise with 2 young kids, for example) can't wait to go back to the office
  • People with really bad commutes like working from home and want it to continue
  • People with very isolated job roles that don't require collaboration like working from home
There are obviously many other situations and an infinite number of combinations that aren't as black and white. There's also the whole COVID issue and whether or not people will have a major mindset change regarding their willingness to be in crowds. Will people just be more skeptical / unwilling to be in a crowded office even after the COVID pandemic is over? Will people want to jump on a crowded train to go to the urban core and go stand in a crowded elevator to get to the 10th floor of their office where they share a bathroom with a hundred other people? My gut says things will more or less go back to the way they were on this front, but who knows...

Conclusion / My Thoughts

Given the above discussion, here are my thoughts on how things will shake out:
  • Working from home is a better / more accessible experience than it was
  • Employers are much less skeptical of working from home than they were in the past
  • Employers are more likely to let employees work from home going forward
  • Some people will decide to make working from home a more permanent thing post-COVID
  • This goes back to my post on forecasting future events--when predicting tomorrow's weather, the most accurate prediction is that it will be the same as the previous day--applying that principle to office in the post-COVID world, things will likely revert back to how they were--people will be okay using public transportation and crowded elevators and there won't be a major behavioral shift
  • Taking the above into consideration, there will likely be a long term shift of the demand curve for office
  • I don't think it will be a major shift that will destroy the asset class, like what happened with online shopping and big box retail, but there will a demand hit and the asset class will under perform vs historically for the next handful of years--this will create opportunity for smart allocators

Monday, July 16, 2018

How Interest Rates Affect Real Estate Values / Pricing

Interest Rates and Real Estate Pricing

Real estate investors are facing rising interest rates. Below is a graph with the 1-month forward LIBOR curve:

As demonstrated above, 1-month LIBOR, a benchmark rate commonly used in setting total interest rates for real estate loans, is currently at ~2.1%, which is just about equal to the 52 week high, and is expected to increase to about ~2.8% a year from now. The 52 week low, for comparison, is 1.2%. Let's create an example to see how rising interest rates affect real estate pricing.

Which Valuation Metrics You Use Matter

The first important point here is that interest rates only impact certain return / valuation metrics. Unlevered metrics, almost definitionally, will not be impacted by changes in interest rates, insomuch as things like the purchase price and forecasted exit price are not impacted by interest rates (a big assumption, but necessary for our example). However, levered metrics (levered IRR, equity multiple, total profit to equity holders, etc...) are impacted by interest rates in 2 ways:

1. The size of loan that can be obtained
2. The cost of borrowing, i.e. the cost of debt, i.e. the cost of capital, i.e. the profit from operating cash flows received over the project

Loan Sizing

Lenders often utilize debt service coverage ratio (DSCR) as a way to size the loan they are willing to issue a borrower for a particular property. DSCR is defined as (Adjusted Stabilized NOI / Total Loan Payment).

Adjusted Stabilized NOI = Stabilized NOI - (typically) a capex reserve

Total Loan Payment = Total Payment (both interest and principal) based on a given loan size (this is what we're trying to solve for)

A lender might set the ratio at 1.20x, which implies the ANOI must be 20% more than the total payment. The lender will have a interest rate and number of amortization periods that they will base the total payment off of. Again, total payment is a function of loan size, but we're trying to solve for the loan size, so it seems like we're stuck. Fortunately, we actually do know the biggest payment amount that we can afford which will then allow us to back into a loan size.

The max payment, based on a 1.20x DSCR, is then equal to our ANOI / 1.20. The example in our Excel sheet has a stabilized ANOI of $975k. ANOI of $975k would imply a total payment of $812,500. Note that our total payment is a composed of an interest payment (derived from the interest rate the lender sets for the DSCR test) and an amortization payment (based on the amortization periods the lender sets for the test). Since we have interest rate, amortization periods and total payment amount, we can then back into the loan size.

For our Excel example, I've assumed the lender is applying a 30-year amortization period to the DSCR test. The interest rate used for the DSCR test is where it becomes applicable to our discussion on interest rates. In one case, I've assumed the lender is using the 52 week low 1-month LIBOR  rate of 1.2% plus a made-up spread of 4.0% for a total rate of  5.2%. In another case, I've used next year's projected 2.8% 1-month LIBOR rate plus the same made-up spread of 4.0% for a total rate of 6.8%.

Plugging these 2 cases into the PV calculation on Excel (=-PV(monthly interest rate, number of amo periods in months, the total payment amount) yields:

Total loan size of $12.3 million in case 1 with the 5.2% total interest rate


Total loan size of $10.4 million in case 2 with a 6.8% total interest rate.

As we see here, the loan size a lender is willing to provide changes drastically with the interest rate that is used in the test. Of course, there are several overly simplistic assumptions built in here for demonstration purposes (lender keeps the same spread in the interest rate, DSCR is the only loan sizing tool, etc...), but the main point / takeaway is that there is less cushion between NOI and debt service which will make lenders more conservative with loan sizing.

The amount of debt in a project will have a big impact on the project's cost of capital. Less debt = higher cost of capital, which hurts levered return metrics.

Net Cash Flow

Simplistically, net cash flow is (NOI - Cost of Debt). Definitionally, if Cost of Debt increases (higher interest rate), then net cash flow will decrease.

Excel Example Explained

In our Excel example, let's assume there is an investor looking at acquiring a hypothetical property. This investor needs to acheive a 15% levered IRR to make it an attractive investment for its risk level. The first set of levered cash flows, the 1.20% LIBOR cash flows, suggest a 15% levered IRR can be achieved at a $16.4 million purchase price.

In the next scenario, 2.80% LIBOR cash flows, all assumptions are the same. The only change is the loan amount and debt service payments. This scenario suggests that to achieve the same 15% levered IRR, the investor can now only pay $15.2 million.

Of course, this brings up the question of whether or not it's realistic to assume the same exit price as the first scenario. If the increase in interest rates have made this buyer only able to acquire this property for $1.2 million less than before, isn't it reasonable to expect that the exit buyer is also only able to buy at a lower purchase price?

The third scenario, 2.80% LIBOR and 7.00% exit cap rate cash flows, demonstrates what happens if we take all the assumptions from the above example, but adjust our exit price expectations to reflect this rising interest rate environment. As we can see, the hypothetical investor's purchase price must now be $14.5 million to achieve the 15% levered IRR.

The increase in LIBOR from its recent extreme low to its projected 2019 level has adversely affected the value of this hypothetical asset by almost $2 million, about 12% of its value. Of course we've made many simplifying assumptions for this demonstration. For example, higher / rising interest rates tend to imply higher inflation which would imply rents growing faster and NOI growing faster.

But also keep in mind that this recent increase in interest rates is occurring at the tail-end of the longest commercial real estate bull market in history. Are investors really going to underwrite higher rent growth than they have in the past? Do investors really believe we're in a more inflationary environment now than in the past couple of years? I tend to think not.

Wednesday, November 16, 2016

Trump Presidency and Real Estate

Trump, a billionaire real estate developer, becoming president of the US has to be a good thing for real estate, right? I mean, what could go wrong?

In reality, I think people tend to overrate just how much change a president can affect. For better or worse, the Founding Fathers intentionally structured our government to be sluggish, or inept to a degree. I doubt Trump will be especially nimble when navigating the political  waters and, subsequently, probably won't end up changing a whole lot.

Something that is relevant to real estate and had shifted drastically since Trump's election is the Treasury yield curve, which has simultaneously shifted upward and has gotten flatter. Yields are a function of the "real interest rate" and inflation expectations. Yields moving higher would imply higher inflation expectations. More inflation is generally a great thing for real estate as it boosts real estate values while decreasing the real cost of servicing debt. The curve flattening is a bit worrisome though as that's generally a negative indicator for the economy. Well, we'll see what happens. Should be a fun / entertaining 4 years...

Monday, November 14, 2016

The Myth of the Charitable Property Owner

To make money on a real estate deal, the deal must typically have at least one of the following characteristics:
  1. Below market rent - Some properties might have leases that were signed during a downturn, or might might have been signed prior to a rapid improvement / change in the market. When these old leases roll and renewals or new leases are negotiated, there should be a bump in property revenue, resulting in a higher NOI and higher property value.
  2. Above market vacancy - Another way for entrepreneurial landlords to increase NOI is by improving the occupancy level of a property. If a property is 50% occupied, increasing the occupancy to 90% will have a dramatic impact on NOI.
When brokers pitch my company deals, they almost always claim the property has one of the above characteristics. Most of the time it's actually true. A lot of properties do have below market rents. A lot of properties do have above market vacancy. Unfortunately, most of the time properties have one of these characteristics for a reason!

Think Like a Sophisticated Investor

Whenever you start analyzing a property with below market rent or significant vacancy, the very first question to the broker should be: "Why?" Why would a property not be performing well, especially in a booming market like the one we're experiencing right now (in most cities, anyway)? Almost universally, brokers will tell you the property is under-performing for one of the following reasons:
  1. The owner / landlord isn't willing to invest in capex / tenant improvement allowances, which is driving tenants away.
  2. The owner / landlord wants to "drive occupancy" and isn't "pushing rents" because they're afraid of losing tenants.
Talk to enough brokers about potential deals and you hear the above answers so much, you'd believe the real estate world is just full of owners / landlords that just don't care all that much about making money! I call this phenomenon, the curious case of the "mythical charitable real estate owner."

Charitable Real Estate Owners

Brokers would have us sophisticated investors believe there are just oodles and oodles of landlords out there that just don't like making money very much. In fact, they dislike making money so much that they're willing to put almost no effort and resources into increasing NOI, even when it's really easy (increasing a property's NOI is always easy according to brokers)!

Now, you might be thinking to yourself, "But wait, commercial real estate landlords are the greediest bunch of bastards I've ever met. In fact, they're just about the greediest people I've ever met! How come my apartment landlord isn't one of the charitable ones?????"

Some Properties are Just Inferior

The fact is, most landlords are smart and money-hungry. In my experience, most are pretty darn good at maximizing their property's NOI and, subsequently, market value. The vast majority of properties suffering from below market rent or above market vacancy do so for a reason. In a given market, there are a subset of properties that are just inferior, or below average. I mean, almost by definition roughly half of all properties in a submarket must be below average and will under-perform the properties that are above average.

Identifying Those Rare Properties that Can Be Improved

Most properties under-perform because they're inferior, but rare gems do exist that just need a bit of polishing from the right landlord to really shine. If you think you've found a property with under market rents or above market vacancy that can be improved via capital investment or "sophisticated management," just make sure you can answer the following questions:
  1. Why does this opportunity exist?
  2. Why am I the right person / company to capitalize on this opportunity? What unique expertise do I bring to the table that would allow me to add more value than my competitor?
  3. What is the catalyst for this change at the property? Is it simply renovating the exterior and interior? Has the submarket gone through a dramatic change that other investors are yet to identify?
These questions might seem simple, but they shouldn't be if you're being as thorough of an investor as you should be. Just to provide some context, my company recently decided to invest in an asset. In order to get approval for the investment, the investment team had to prepare a 200 +/- page investment thesis to sufficiently answer the above 3 questions...

Saturday, October 22, 2016

The Bay Area Housing Crisis

Does the Bay Area Have a Housing Crisis?

When people refer to the "Bay Area Housing Crisis," they're usually referring to 2 things:

  1. The cost of owning a home relative to median income for the area is so high that a large percentage of people can't afford a home.
  2. The cost of renting as a percentage of median income is high, making it difficult for people to save money.
Paragon RE, a residential real estate brokerage with a large presence in SF, has some interesting info on the topic in this post. All graphs I insert below are courtesy of Paragon RE's website.

This chart shows the household income needed to purchase a home in each of the respective cities. As you can see, an income well into 6 figures is needed to purchase a home in most Bay Area cities.

This chart shows what percentage of household can actually afford to buy a house. As you can see, less than 30% can afford a home in most Bay Area cities. The income requirements are obviously a major factor, but even more so is being able to come up with a 10-20% down payment on a $1M+ home.

Okay, so we see from the charts above that it's very difficult to buy a house in the Bay Area and not a lot of residents have the necessary financial strength. However, going back to the original question, does the Bay Area really have a housing crisis? Due to the reasons mentioned above, yes, but in other ways, no. I mean, the housing market is still as hot as ever and houses are still being listed and sold at record prices, sometimes with multiple bids above asking price. How is this possible? How can the Bay Area, on one hand, have an affordability crisis limiting the buyer pool, yet not see a slowdown in sale volume and price?

The Issue No One Wants to Discuss Regarding the Bay Area "Housing Crisis"

I was at an industry event this past week and everyone had their own opinion on why the housing crisis started and how we should fix it. Answers ranged from the lack of density at job centers, to unreasonable mortgage standards, particularly the down payment requirements. Certainly increasing density is a reasonable solution, but as a developer that is constantly hunting for development opportunities in major Bay Area urban centers, I can tell you it's very, very hard to find feasible development opportunities (both financially and practically) and then execute on them. Of course lowering mortgage standards is just ridiculous as it will just serve to increase buyer demand, raise housing prices further and make the Bay Area even more less affordable (didn't we try this a few years ago???). I guess this panelist wasn't familiar with the laws of supply and demand). There were other ideas mentioned as well that have merit, such as improving commute options from outlying communities, like Livermore.

One topic that was absent from the conversation on Bay Area affordability is something we've been conditioned not to talk about--immigration. The most obvious answer to why we have this insatiable demand for housing that doesn't seem to be slowing down anytime soon in the face of decreasing affordability is really quite simple: California continues to simultaneously rapidly increase its population and depress wage growth by allowing up to 65,000 H1B visa workers into the state each year, many of which will work at Bay Area tech companies, and allowing illegal immigrants to pour in. Both have the effect of boosting population growth that the housing supply can't keep up with, resulting in upward pressure on housing prices. Both also increase the supply of labor, which allows corporations to keep wages lower than they'd otherwise be able to. Just based on the equation "Housing Affordability = Cost to Own a Home / Median Wage" we can see that immigration is hurting affordability, both by keeping the median wage artificially low and increasing home prices.

So What?

The point of this post is that immigration is a primary driver of California's housing crisis and any meaningful discussion about how to fix the affordability crisis must include immigration. In the United States, discussion about immigration has devolved to the point where anyone who doesn't support unlimited immigration, from anywhere in the world, at any time is deemed a racist, redneck, bigot that likely has an incestuous relationship with his / her sibling. There's no middle ground. Unfortunately, the fact is housing supply has no chance of keeping up with our population growth due to immigration. Likewise, wages don't have a chance to grow because of immigration. If we actually want to fix these problems, we have to put limits on immigration.

We can't continue to call everyone that wants to curb immigration a racist. There are valid, reasonable arguments for why we should limit it, especially in a place like the Bay Area. It's time to stop with the rhetoric and come up with actual solutions. Mass immigration might have worked at certain times and places in the country, but that doesn't mean it needs to continue into perpetuity all over the United States.

Tuesday, August 9, 2016

What is Replacement Cost?

What is Replacement Cost?

Replacement cost is a metric often used by commercial real estate professionals as a way to measure whether an asset is under or overvalued. The actual replacement cost of a property is what it would cost to rebuild the property and then what you would need to spend in order to re-tenant it. If a property's value is below its replacement cost, that's generally a sign that it's not overvalued.

For example, let's assume we're analyzing an existing 20,000 square foot office building in Downtown San Francisco that's valued at $700 PSF. Here's a spreadsheet showing an example of calculating a replacement cost for the target property. In the spreadsheet I've assumed it would cost $300 PSF for land, $400 PSF for hard costs (actual cost to purchase building materials and construct it), $100 PSF for soft costs (architectural, city, permitting, entitlement fees, etc... necessary to get the building constructed), $100 PSF for tenant improvement allowances (what the landlord is expected to provide a prospective tenant in that market) and a leasing commission of $20 PSF. Based on these assumptions, it would cost $920 PSF to recreate the target property.

So what does this mean exactly? Are we getting a screaming deal because we have the opportunity to buy the building for $700 PSF? That's what brokers would have you believe, but it's only a half truth.

Go to the download page to download a more polished replacement cost spreadsheet or click this button:

Replacement Cost is a Tool to Measure Development Risk

Commercial real estate is subject to the same laws of supply and demand as every other good. Supply outpacing demand will decrease prices and supply not keeping up with demand will increase prices. In commercial real estate, the supply side of the equation is determined by development of new buildings and redevelopment of existing building (changing their use to a different use--re-purposing a building from retail to general office, for example, increases the supply of general office in that market while reducing the supply of retail). Clearly, when making a multi-million dollar investment, it's important to understand what is happening on the supply side in the market as that will have a big impact on the value of the investment.

In our San Francisco example let's assume there are no buildings currently being constructed and no buildings being planned for construction. Why would that be? Well, it's because, based on our replacement cost calculation above, it's actually cheaper to buy existing buildings as an investment than it is to build a new one. Also consider that there is substantial risk attached to developing a new building from raw dirt, implying there's an additional risk premium associated with developing a new building versus buying an existing one.

What replacement cost really tells you is whether or not your property is subject to development risk in the near future or not. In our example, we're buying the building at a 25% discount to replacement cost. This implies rents would have to increase an additional 25% while the cost of developing a replacement building remains static in order to justify developing a new, competing building (or cap rates compress). In theory that threshold where asset prices are higher than replacement cost shouldn't happen for a good amount of time. The subject property should be in good shape on the supply side for the foreseeable future.

If the opposite were true, i.e. asset values were higher than replacement cost on a PSF basis, then you need to be worried about new buildings being developed and competing with the subject property. That parking lot kitty corner to your building--that could become a shiny new building that steals all your tenants. You better make sure there's enough demand from tenants to sustain additional square footage in the market or your property has some unique feature / competitive advantage that will help it maintain its occupancy and rents.

Replacement Cost has a catch...

The interesting thing about replacement cost is that it is sort of a proxy for how healthy a market is. In the real world, San Francisco has gone through a huge construction boom over the last few years due to crazy demand from the booming tech sector. Clearly asset values have gone well above replacement cost and developers are taking advantage of it. A similar phenomenon is happening in Seattle where it seems like a new skyscraper is being built on every street corner right now.

In spite of this massive construction boom, the demand has been so strong that the markets have soaked up all the new supply and rental rates / occupancy have held strong. Imagine you own an office building in Downtown Seattle. During this construction frenzy, a developer builds a huge office building across the street from you with class A retail on the first floor. At first you're scared, but then Amazon comes in and pre-leases the entire building and a premier restaurateur plans on opening a high-end steakhouse on the ground floor. Then, another block over, a hotel developer builds a brand new luxury hotel. Imagine how much more valuable your building is now. It's across the street from a big Amazon campus--many tech tenants will want close proximity to Amazon and will pay good money to be in your building--it's across the street from one of the city's newest and best restaurants, and there's a brand new luxury hotel a block away that will substantially increase the amenity base in the immediate area.

These are the kinds of things that are happening right now in these cities. If you're a property owner there, yes, there's supply side risk, but as in the example above, as that new supply is soaked up the entire area is transformed, increasing the value of your property. While replacement cost can be a worrisome indicator for the near term, in some ways you want own property in a city that will get more development in the future.

Let's take an example from the opposite end of the spectrum: Detroit. Unfortunately over the past few decades, Detroit has gone from one of America's premier cities to one of its worst in terms of crime, property values, population growth and economic growth. Subsequently, there has been little to no new construction over the past few decades. There's just no need to build another skyscraper in Downtown Detroit when so many of the existing buildings are likely struggling as is. I don't have exact numbers, but I would guess buildings in Downtown Detroit are well, well below replacement cost. That's great and all, there's probably no near term supply risk, but it's also a bad indicator for the future health of that market.

Sunday, August 7, 2016

How to Calculate an Interest Reserve

In this post we'll look at how to calculate an interest reserve for a construction / bridge loan. Here's a link to the spreadsheet that actually performs the interest reserve calculation:  interest reserve calculator.

What is an interest reserve?

Some deals might not generate enough cash flow to cover the interest payment on the loan. Development deals, redevelopment deals, or deals where there's a large tenant rolling in the near-term are examples where cash flow might not cover interest payments. Banks, thankfully, will still make loans on these types of deals. On the months where the cash flow is projected to not fully cover the interest payment, the bank will actually lend you the money to pay the interest. Yes, that's right, the bank will let you draw on the loan to pay the interest. The amount you draw will then be added to your loan balance.

What's so difficult about the calculation?

It would seem that the interest reserve calculation is pretty simple, right? Just take the amount of the interest payment not covered by operating cash flow and that's your interest reserve for the period. That amount is then added to your new loan balance and the next interest payment is calculated off this new balance. While that's all true, the real tricky part is the loan sizing.

A lender will often size a loan based on loan-to-cost (LTC). LTC is simply the Loan Size / Total Project Cost. If the loan size is $1.5M and the total project cost is $2.0M, then the LTC is 75%. Now, the tricky part is the interest reserve is often factored into the lender's total project cost calculation, creating an iterative calculation.

What is an iterative calculation?

An iterative calculation is summarized by the following: calculation A's answer depends on the answer of calculation B, but calculation B's answer depends on calculation A's. A more specific example would be the following: Function A = Function B + 1 and Function B = Function A + 1.

In our interest reserve calculation, we have an iterative function because our loan size is dependent on the size of the interest reserve, but the interest reserve depends on the size of the loan. We already saw how the interest reserve size affects the loan size above, but how does the loan size affect the interest reserve size?

Loan holdbacks and loan proceeds at acquisition.

Typically a construction / bridge loan is funded in two portions. The first portion is funded at acquisition. The other portion is funded for costs associated with improving the property, called the holdback. A holdback is literally what it sounds like: the bank will have the money sitting in an account that they control and will hold it back until the property owner has an approved use for the money. An approved use could be capital improvements, tenant improvement allowances, leasing commissions, or the interest reserve.

In our previous example we had a $1.5M loan which was 75% of the total project cost of $2.0M. Let's assume our costs for the deal break out the following way:

Land: $1,000,000
CapEx: $500,000
TI's: $250,000
LC's: $125,000
Interest reserve: $125,000

In this example, the total loan size is $1.5M. The size of the holdback is the sum of the CapEx, TI's, LC's and interest reserve, or $1.0M. We can then infer that the loan proceeds issued at acquisition is $500k ($1.5M - $1.0M).

Our first interest payment is then the interest rate multiplied by the loan amount at acquisition ($500k). Assuming we don't have sufficient cash flow, the interest payment for that month will be covered by the interest reserve.

However, if the total interest reserve is only $100,000, but we still have a 75% LTC loan, then the total loan size is 75% of ($2,000,000 - $25,000), which is $1,481,250. Our holdback is then ($1,000,000 - $25,000) = $975,000. Our proceeds funded at acquisition is then $1,481,250 - $975,000 = $506,250. That's $6,250 more than the previous version. Since this loan balance at acquisition is different than above, the interest payment is going to be different than above, resulting in a different interest reserve!

Hopefully this example wasn't too confusing and demonstrated why the interest reserve calculation is iterative.

How to handle iterative calculations.

Luckily, excel can handle iterative calculations. To enable excel to handle iterative calculations, click on File -> Options -> Formulas -> check Enable Iterative Calculation. Excel can now handle the iterative calculations we'll throw at it.

For a full interest reserve calculation example, click on the link above and take a look at the spreadsheet. It should give you a basic understanding of how to calculate an interest reserve.

Monday, July 11, 2016

Back of the Envelope Pro Forma

Sometimes before fully analyzing a deal via ARGUS or a complicated excel model (similar to the one we built here), you'll want a quick, dirty way to filter out bad deals. The goal of the initial filter is to save your valuable time by limiting the deals you underwrite. Here's a link to an example of a quick back of the envelope pro forma that we sometimes use at our company for that initial filter. Notice how simple, quick, and easy to use it is. It only has a couple of inputs and shouldn't take more than 15 minutes to populate and spit out some rough metrics.

The model linked here was used to analyze a vacant building which is why we have carrying cost reserves, debt service reserves, and such high TI's and LC's per square foot budgeted for the project. Note that we also have $0 of net cash flow being added to the project profit. That's because we were assuming we'd sell the building as soon as it was leased up. For a building that's not vacant, in the cost section you should budget what costs would be necessary to stabilize the building and bring it up to market.

For example, say a 100,000 square foot building is 70% occupied. Let's assume a market TI per square foot is $20 and we'll have to pay about $5 per square foot in leasing commissions for new deals. That $20 and $5 is only over 30,000 square feet though, so to convert them to a number over the entire building square footage we'll take 30,000 and divide it by the total building square footage, 100,000, and then multiply that fraction by $20 and then multiply the same fraction by $5. We get $6 in TI's over the entire building square footage to get the building stabilized. Then we get $1.5 in LC's over the entire building square footage to get the building stabilized.

To reiterate, this is just a quick back of the envelope calculation. When we first look at a deal, we run some numbers through here. If the equity multiple is 1.5x or more we'll generally take it to the next level of underwriting and do a full ARGUS run. Please don't go around making multi-million dollar offers on properties without doing a more thorough underwriting!

Friday, July 8, 2016

Using Price Per Square Foot as a Valuation Metric

Recently my company hired a new senior level acquisitions person with about 30 years of experience to head up our general office division. I work under a few different VP level acquisitions guys and each has their own style, own types of deals they like and key in on different valuation metrics. Some lean heavily on IRR to evaluate their deals. Others use net cash flow, others focus on the going in cap rate to measure their deals, and others yet, like this new senior level acquisition person at my company, really focus on price per square foot--the going in amount and exit amount.

I've never really thought of price per square foot as a very relevant valuation metric, to be honest. so it was a little weird seeing such a seasoned pro rely on it. The reason I've never found it all that relevant is because in pure finance type thinking, it's basically useless. Finance, at its most basic level, says that an asset is worth the stream of cash flows that it will generate while you own it, discounted based on a specified rate. In that sense, the purest, most financially sound method of valuing a property is to project the cash flow it will generate and then discount the cash flows with your desired rate of return, sum up the present values of those cash flows, and that's what the asset's worth. Nowhere in that process does price per square foot factor in.

Of course there's some issues with using the discounted cash flow method to value a property, the primary reason being estimating your cost of capital or cost of equity for a project is actually very, very challenging. That's why IRR is so popular. It's basically using the same method as the discounted cash flow method, but instead of feeding a discount rate into a calculation, IRR just spits out a percentage that you can use to compare investments without feeding it a discount rate.

Back to price per square foot. I've always looked at price per square foot as a gut check, secondary metric that helps justify the purchase price calculated from a DCF or IRR. For example, I'd calculate a purchase price based on a needed IRR. Then I'd take that purchase price, divide it by the property square footage to arrive at a price per square foot. Then it's just a matter of finding comparable sales and seeing what price per square foot they traded at. If the comparables are relatively close to what I calculated, great. If they're way far off, maybe it's worth taking a look at the pro forma again to see if there's a misguided assumption baked in.

This senior level acquisitions guy, for the most part, doesn't need all of that fancy ARGUS / excel pro forma wizardry to arrive at a valuation of a property. A broker will pitch him a deal, he'll think about it for a few minutes, and then do the following type of back-of-the-envelope calculation. He'll say, okay, properties in this market, fully stabilized, are worth $300 per square foot. Then he'll say, this property is for sale for $175 per square foot. However, to stabilize the property, it'll cost $50 per square foot in capex, another $40 per square foot over the whole property in TI's, and maybe another $10 per square foot in leasing commission costs over the whole property. In this scenario, we'd be into the project for a total of $275 per square foot. If we sell at $325 per square foot, that leaves the company a profit of $50 per square foot. If the property is 100,000 square feet, then the total profit we make is $5M.

Then he does one more calculation. He analyzes if that's enough profit for the risk level of the deal and the amount of company time it'll take to successfully execute the project. I have no clue what exactly goes into that part of his analysis, but sometimes $5M is enough profit to justify a deal, and other times it's not. Overall, it's been interesting to him operate and it gave me a new way to think about real estate valuation. Do I think it's better? No, but then again, I'm a total finance nerd and don't have 30 years of experience. In general, I think my generation is of real estate professionals is much more analytically oriented and prefers that type of heavy lifting analysis, but that's another post for another day.

Monday, July 4, 2016

Comparing Lease Terms

A common problem landlords face is deciding between competing lease offers between prospective tenants for a vacant space. For example, let's say a developer builds a 60k square foot office building in Silicon Valley. Let's assume the landlord leases the 30k square foot ground floor space and is now left with 30k square feet on the second floor. After a few months, the developer might have a few different offers from tenants for the vacant space. Each offer could have different terms. One offer might require more months of free rent, lower tenant improvement allowance, and a higher rent rate. Another might be a lower rent, but with less months of free rent. One tenant might have better credit which would lower the exit cap rate for the project. So how should a landlord decide which offer to run with?

Here's a link to a spreadsheet with an example of a lease comparison. The goal of the spreadsheet is to compare two lease offers with different terms by generating a single metric that will tell the landlord which lease is better for its project. The metric I decided to generate is an unlevered IRR. You might be confused on how it's possible to calculate an IRR for a lease, but when you think about it, a lease has all the ingredients needed to calculate an IRR, from the landlord's perspective. First, a lease transaction will usually have a large initial negative cash flow due to the landlord needing to pay a leasing commission and tenant improvement allowance (we'll also include the project cost per square foot multiplied by the suite square footage and add that to our initial cash outlay). Second, there's a stream of cash flows generated by the lease which is calculated by taking the rent payments minus the cost to operate the suite. Lastly, a lease will contribute to the overall value of a building when it's sold and we can estimate that contribution by taking the NOI the lease adds to the project and then dividing it by the exit cap rate. Once we calculate these three portions of the unlevered cash flows, we can then generate an IRR. The IRR can then be compared to the other lease terms and whichever has the higher IRR is probably the better deal.

The landlord's initial cash outlay includes a leasing commission, tenant improvement allowance, and we also include the suite's portion of the total project cost. Leasing commission can be tough to calculate. See this previous post to get a refresher on leasing commissions. I've included a somewhat automated way to calculate leasing commission in the spreadsheet. Just enter the lease terms for each lease and then create a leasing commission structure in the top right of the sheet. Once each leasing commission is calculated, we then need to calculate the tenant improvement allowance. Luckily this portion is much simpler and is just calculated as the suite square footage multiplied by the TI per square foot. Lastly, since we're factoring in the leases' contribution to the exit value of the project, we also need to factor in the how much it cost to purchase that suite, per se. That calculation is done by taking the overall project cost per square foot (not including TI's and LC's) and multiplying it by the suite size. We now have all three parts that make up the initial cash outlay for our IRR calculation.

The stream of cash flows generated by the lease is a fairly straightforward calculation, but there are a few wrinkles that need to be considered. The main assumptions for the calculation are the months of free rent, the initial rent rate, the yearly increase %, and the actual lease term. Take a look at the spreadsheet to see how the rent cash flow streams are calculated. The other part of it that needs to be calculated is the cost of operating the occupied suite. To factor it in, we take the stabilized project operating cost per square foot and multiply it by the suite square footage. We then need to net that opex out of the rent, giving us the lease's contribution to the project NOI for each period of our analysis.

Finally, we need to calculate the project's contribution to the exit value. This should be pretty simple and straightforward. We've already calculated the lease's contribution to NOI, so now we just take that NOI in our exit period and divide by the assumed project exit cap rate. There is one important wrinkle that should be noted. Different leases will affect the project's exit cap rate. A lease with an investment grade credit tenant, such as Apple, will lower the project's exit cap rate, so when comparing two leases, we need to adjust the exit cap rate for how the different leases might affect it.

Once you calculate the the unlevered cash flows for each lease, you can then calculate an IRR which will tell you which deal is more accretive to your project.

Friday, June 17, 2016

How to Calculate an Amortized Tenant Improvement Allowance

(High-end restaurant interior)

For some tenants, it can cost a lot of money to establish a new place of business. A high-end restaurant, for example, will require a lot of expensive kitchen equipment and top notch interior finishes throughout their space. These build outs can easily cost upwards of $100 per square foot. Based on a $100 per square foot tenant improvement allowance, a 3,000 square foot restaurant could require $300,000 or more in order to get the space ready for operations. That money will need to be invested upfront and won't see a return for a decent amount of time.

Tenants might not have that kind of money on hand. Not all hope is lost though, they have a couple of options:
  1. Go get SBA financing. This is a great option, but might not cover all the costs.
  2. Landlords will often offer to cover a portion of the tenant improvements needed for the space as a way to entice prospective tenants to their building. A tenant might be able to negotiate for the landlord to cover a good amount of the upfront money needed.
  3. Workout an arrangement with the landlord where the landlord actually acts as a bank and issues a loan to the tenant for any needed money that won't be provided by the landlord or tenant. Typically, the loan payment is made monthly by the tenant and is included with their rent payment. This structure is called amortizing a tenant improvement allowance into the rent.

In our restaurant example above, if the landlord is willing to cover $50 per square foot of the needed TI allowance and the tenant provides $20 per square foot, then there's a $30 per square foot delta that needs to be bridged. Let's assume the landlord agrees to issue a loan to the tenant for the $30 per square foot and the tenant agrees to pay it back over the term of their lease. Here's a spreadsheet that calculates exactly how it affects the monthly rent payment for the tenant.

Click the button below for a comprehensive rent schedule generator and TI amortization calculator. This tool includes both a comprehensive rent schedule generator that can incorporate several rent increase structures and free rent schedules, and a TI amortization calculator where you can quickly analyze a TI amortization scenario. With this tool, you'll be able to create a professional looking rent schedule with the TI amortization included in a matter of minutes. A download link will be sent to your email address. 

Using excel, we start by laying out our assumptions. The important assumptions for this calculation are the interest rate the landlord and tenant agree on for the loan, the lease term that the TI will be amortized over, and the total dollar amount of TI that's to be amortized. The other assumptions are just there so we can see the total rent payment the tenant will make each month. Excel makes it easy to calculate how much rent the amortized TI adds to the rent. Using the PMT function, we calculate how much additional rent is created by the amortized TI.

In our example, you can see that the amortized TI adds $0.36 per square foot per month to the rent. By the end of the lease term, the tenant will have paid the landlord back completely for the $30 TI per square foot that the landlord fronted for the tenant.

From the landlord's perspective, the amortized TI is a good option for two reason. First, and most importantly, it will attract more tenants. High upfront cost users will view a landlord offering to cover more of the TI more favorably.

Second, from the landlord's perspective, there's always a risk that the tenant will run out of money during their high-cost build out if they are funding it themselves. Tenants don't always have the best liquidity and they can underestimate the amount of money it will take to make their space operational. If they are relying on that space to generate their income, don't finish it, and run out of savings / SBA financing, then they're going BK. The landlord is left with a half built out space that they've likely contributed money to that will likely need to be completely redone for a different user. Not a good spot to be in, obviously. By funding the build out, the landlord is reducing this risk (assuming the landlord is in a better financial position) and will help assure the tenant is able to complete their build out, start operations and begin making money.

Tuesday, June 14, 2016

Home Price Inflation: Good for Some, Not so Much for Others

(Random Housing Development)

According to this article on GlobeSt, homeowners are doing well, very well:
Nationwide home equity increased year-over-year by $762 billion in Q1, bringing the number of mortgaged residential properties with equity at the end of the quarter to 92% of all mortgaged properties, according to CoreLogic.
It shouldn't surprise anyone that home equity is increasing. You have 2 factors contributing to the substantial increase:

  1. Home prices have appreciated over the same time period by 6.2%, according to CoreLogic. Note that any increase in the price of a home (assuming a standard mortgage structure) all goes to equity and most people only put in 10-20% of equity into their home purchase. Let's take the purchase of a 500k home as an example to see how an increase in home prices has a levered effect. If you put in 20% of equity, then you've invested 100k into the home. If that home increases in price by 6.2%, it's now worth 531k. That's a 31k increase in value in just a year, which is a 31% return on equity! Not a bad deal, right? As you can see, homeowners have a very strong interest in seeing home prices appreciate year-over-year. By the way, They forecast a 5.3% increase over 2016...
  2. Loans are getting paid down which increases homeowner's equity. Most mortgage payments are composed of both interest and amortization. The amortization portion of the payment goes towards paying down the loan, thereby decreasing the loan balance and increasing the owner's equity. Employment is doing great. People are flush with cash right now, paychecks are stable, and people are making their loan payments.
The article continues:
In addition, negative equity—often referred to as “underwater” or “upside down” and applying to borrowers who owe more on their mortgages than their homes are worth—decreased 6.2% quarter-over-quarter from 5.1 million homes (10.3% of total mortgage inventory), in Q4 2015 to 4.3 million homes (8% of total mortgage inventory) at the end of Q1 2016. These findings bode well for the housing industry.
Interesting how these articles always seemingly have a very positive bias towards home price appreciation. It makes sense--more likely than not the person writing the article and the person from CoreLogic being interviewed own homes and have a strong interest in seeing the value of their most important investments increase. There are other less cynical reasons as well, of course. The single family home industry supports several million construction related jobs and a multitude of non-construction related jobs as well--think of how many neighbors / acquaintances you have who worked as a realtor or mortgage lender at some point in their life.

Governments also have a strong interest in seeing home prices increase. Most counties reassess home values periodically. I don't know any tax assessors personally, but I would guess they're big fans of being able to justify jacking up their respective county's home values as much as possible and generating a lot more tax revenue.
On the sales side, Khater says most people roll over their equity into the next home they buy, which serves as the down payment, and they then don’t have to pay anything as a down payment; this makes increased equity a motivating and enabling factor in people putting up their homes for sale. “Also, if they want to refinance, and they were previously unable to do so because of negative or not enough equity, they are now able to do so.”
Homeowners are almost forced into rolling the money from selling their houses into their new purchase. That's obviously where a lot of their money is tied up, but they're also heavily incentivized to roll all the money into the purchase of a new home because of tax laws. The government has decided it'd be a great idea to allow homeowners to roll all that money, including the gain over the original purchase price, into the new home, tax free. I'd bet many people defer gains on their houses indefinitely and let their kids deal with it when they die.

Home price appreciation certainly is great and benefits the economy in the short term, but if the appreciation rate, largely driven by existing homeowners taking advantage of the increased equity in their homes trading up and up and up in home size / value, exceeds wage growth, then all you're left with is a bunch of asset holders pricing out the non-asset holders and creating this sort of self-contained speculative bubble with nothing supporting it (note the government's complicit role in the bubble by not taxing the gains on these investments as well).

The reasons above are why I always cringe a little bit on the inside when I see an article cheerlead for enormous home price growth. A healthy housing market should be supported by both the improved financial position of non-asset holders (primarily the younger generation as they climb the ranks in their careers and make more money) and the improved financial standing of asset holders (job promotions, but also increases in their investments). If you agree with the previous sentence, then you should also agree that housing prices should more or less track wage growth.

Over the last 10 years, the BLS reports that wage growth has averaged approximately 2% per year and hasn't exceeded 4% in any of those years. Meanwhile, the housing market has had unbelievable double digit price appreciation in several of those years and mid to high single digit appreciation in many of the others. Of course, there was the housing crash of 2008 that has skewed things. Even if you look at from 2014 and on though (hard to argue the economy wasn't stabilized by 2014...), home price appreciation has been mid to high single digits in many markets, far outpacing wage growth.

To me, this suggests there's a certain amount of speculative behavior as discussed above taking place. Homeowners are using the increased value of their homes to trade-up into bigger, more expensive homes, which then gives another homeowner a fresh injection of money that they then need to put into a bigger, better house. The cycle continues, driving up the price of homes. None of those investment gains are taxed, by the way. Have I mentioned that yet? These speculative conditions are preparing the foundation for, not necessarily an '08 magnitude crash, but certainly a volatile market in the medium / long term that will financially devastate thousands and thousands of people participating in the speculation.

Besides the market volatility created by rapid price appreciation, it also adversely affects the younger generation that doesn't own a home. They are systematically getting priced out of the housing market which hurts household formation, deprives them of being able to establish roots in a community, takes away the opportunity to invest a good portion of their net worth in a home, and forces them to rent and face ever increasing rent prices (owning a home provides a certain amount of protection against increases in the cost of housing--mortgage payments are fixed and property taxes are capped at 2% growth per year--rent can growth exponentially unless your unit is rent controlled).

Not only does rapid price appreciation hurt the younger generation, but it hurts the asset holders as well by keeping fresh blood / capital out of the housing market. As mentioned above, a healthy housing market needs new participants to enter driven by their wage growth surpassing or matching home price appreciation. At some point, existing home owners will want to sell their McMansion and downgrade their home. There better be someone there to buy the home or else they're taking a hit financially.

Maybe we shouldn't be cheerleading every time housing prices increase by a huge percentage. Maybe it's not a good thing for home prices to far outpace wages as they've done over the last 10 years. Maybe it's actually not a good thing for first-time buyers to be priced out of the market. The issue, of course, is decision makers own homes and the government wants higher home prices, so don't expect much to change. Expect volatility, boom / bust cycles to persist in the single family home market as speculative behavior is encouraged.

Friday, June 10, 2016

San Diego Suburban vs. General Office

(Downtown San Diego)
The San Diego office market has always fascinated me. What's interesting is so much of the office space is located in the suburbs and the Downtown, although very nice just doesn't have that much office space. In fact, before Sempra Engergy built their brand new office tower in Downtown, there really wasn't a major company headquartered there.

When you think of the major San Diego based companies, you probably think of Qualcomm, Jack in the Box, and maybe a biotech like Illumina. It's probably surprising to find out that none of these companies are Downtown.

Qualcomm is in Sorrento Valley which is probably about 15 miles north of Downtown. Sorrento Valley is pretty nice, but there's certainly nothing there that would make it an especially attractive place to work. Scenery isn't that great, not a lot of amenities nearby and infrastructure is pretty awful. Around 5pm it can take 30-45 minutes just to get on the nearby freeway. There's very little in the way of public transportation supporting that submarket to boot.

Jack in the Box is, rather bizarrely, in the Serra Mesa neighborhood of San Diego, which is probably 10 miles north of Downtown. Again, terrible traffic, no amenities, and the surrounding area is old and rundown.

Illumina is in University City, which is about 10 miles north of Downtown. University City is actually pretty awesome. Close to the beaches, great restaurants, awesome scenery, and a very desirable place to live.

I don't know exact percentages, but a majority of office space is located in University City, Del Mar, Carlsbad, Sorrento Valley, with just a small percentage left in Downtown. I'd guess a few factors led to office space being developed in those markets vs. Downtown:

  1. Downtown San Diego, prior to the mid-2000's was kind of a crap hole. It was old, rundown, had a major homeless problem, and wasn't all that desirable of a place to live. Petco Park getting built and a number of city initiatives combined with the urbanization trend have really revitalized the Downtown area over the last 10 years. In my opinion, it's now one of the most desirable and live-able Downtowns on the West Coast. 
  2. C-level executives decide where companies establish offices. Along with having offices in nice locations, they want them close to where they live. Well, in San Diego, C-level executives are likely to live in University City, Del Mar, and Carlsbad. It's then no wonder so many offices are in those locations.
  3. San Diego has a driving culture. In San Diego, you just drive everywhere. No one takes public transportation, People are just used to spending an hour or more commuting each day. I don't have a great explanation for why this culture exists, but it just does. Having offices in suburban locations away from population centers that require substantial commutes just isn't that big of a deal.
Here's an interesting article from Globe St. discussing this exact phenomenon in San Diego. I have one major point of disagreement with the interviewee though when he says: Do you see this amount decreasing as the market becomes more urbanized and the demand for Downtown office space increases?

Brant: I don’t [think] that composition is going to skew more toward urban for San Diego. Downtown is going to grow, but I don’t think that’s going to stop the suburbs from growing. There’s a lot of office proposed for Downtown, but we’ve got over 1 million square feet of office proposed in the Highway 56 corridor alone. I think Downtown will definitely grow, but it’s [not] going to outpace the suburbs.

His thesis that the composition of suburban vs urban office isn't going to change might be correct in the short term, but I think it's going to skew heavily to Downtown in the medium to long term. When you look at Downtown San Diego right now, it seems like every professional between 25-40 lives there. Condos and apartments are being built at a furious pace to keep up with the demand. Not only is the Downtown seeing a boom in the construction of dwellings, but the formerly blighted neighborhoods to the south and east are rapidly being revitalized, largely as a residual effect from the improving demographics of the Downtown area.

When these 25-40 year old yuppies grow in their careers and either start their own companies or move up to the C-suite, where do you think they'll wan their offices? My guess is they've spent 10 or more years living in a gorgeous Downtown, their favorite restaurants are all there, their girlfriend / wife / boyfriend / husband wants to be there, their friends are all there--chances are they're going to want their offices Downtown as well.

This is where demographics trends and household formation come into play as well. You might say these people are going to eventually want to move to the suburbs as they have kids, but the fact is the current trend suggests 25-40 year olds aren't going to have as many kids as previous generations and won't need as much space. A family of 3 or 4 can pretty comfortably live in a 1k SF condo or house. They don't need 4 bedrooms, the huge yard, etc..., allowing these families to remain Downtown.

Long story short, the future leaders of San Diego business all live Downtown and they're going to want their offices there. Don't be surprised if we start seeing major office developments taking place in Downtown to keep up with the demand.

Millennials and their Shopping Preferences

Somewhat interesting article on Bloomberg from the other day discussing millennials and their spending habits. Couple of excerpts:

Millennials have a higher “experience-to-stuff” ratio for their disposable income than members of the baby boomer and Gen X groups had when they were 24 to 35 years old, MetLife Investment Management said Thursday in a report.

Baby boomers and gen x'rs, as a general rule, were married and had a kid or two between 24-35. Millenials, however, are delaying household formation until their late 30's or 40's. A family of 4 consumes a lot more than a single adult. Families of 4 are going to have a tougher time finding enjoyable "experiences" for their whole family as well. As someone with a couple of kids, it's hard enough to corral everyone down to the park a mile away from our house--going to a trendy restaurant for an "experience" is simply out of the question.

I'd propose another reason millenials have a lot less "stuff" is because their "stuff" is just so darn cool. If you have a smartphone, laptop and an internet connection you have unlimited entertainment options. What else do you really need stuff-wise to be content in the modern world? Baby boomers and gen x'rs obviously didn't have access to these types of toys.

Still, shopping locations can thrive when consumers find an attractive mix of stores, restaurants and entertainment, said Melissa Reagen, head of research at MIM for real estate.

“We’re very bullish that those retail centers will actually do quite well,” she said in an interview. Places “that can do all those things really well will be able to compete against e-commerce.”

This is a pretty common theme in retail commercial real estate right now. The idea is that restaurants, grocery stores, and other retail uses that currently can't be replaced by a website will continue to do well. That's probably true for the short term, but if I had to bet money, I'd say in another 10 years no one will shop at grocery stores.

We'll probably be able to send our driver-less car to a warehouse, it'll stop at a window, and then a robot will gather all the groceries you ordered online and put them in your car. The care will then drive them to your house and you just go outside and grab them. That's just one technological advancement I could see wiping out the grocery store concept. The other is even more obvious--Amazon. I think it's entirely possible that in a few years you'll be able to place a grocery order on Amazon and a fleet of drones will deliver all the groceries within an hour.

The point is, technology is advancing so rapidly that even these supposed solid retail concepts will most likely face severe challenges sooner rather than later. The other point is invest in industrial real estate for the long term, not retail. Supply chains expansion driven by the constant need to be able to deliver goods faster is going to, I believe, create a huge demand for industrial for the foreseeable future.

Wednesday, March 30, 2016

Analyzing a Property's Cash Flow Statement & How to Create a Real Estate Pro Forma (part 13 of pro forma building series)

Here's a list of everything we've covered so far:

Part 1 - Overview on how to calculate down to the NOI line item.
Part 2 - Intro to lease structures and calculating the gross potential revenue line item.
Part 3 - A look at reimbursement methods and how to calculate reimbursement income.
Part 4 - How to calculate the other income line item and an intro to income adjustments.
Part 5 - Rent abatements overview and calculation example.
Part 6 - Absorption and turnover vacancy explanation and intro to tenant improvements.
Part 7 - General vacancy allowance explanation and calculation example.
Part 8 - Operating expenses explanation.
Part 9 - Constructing a sources and uses table.
Part 10 - Building a debt schedule.
Part 11 - Calculating levered IRR.
Part 12 - DCF analysis.
Part 13 - Loan sizing.

Here's our simple example pro forma spreadsheet to follow along with as well.

Click this button to download the spreadsheet:

In part 13, we're going to look at loan sizing, which helps us determine what kind of loan we can get on the property.

What is Loan Sizing?

As we've seen in other parts of this pro forma building series, debt plays a very important role in real estate. The interest rate, interest only periods, and actual loan amount have a big impact on the cash flows and return metrics. Before, we just assumed a loan size. There wasn't anything scientific about it, I just picked the number because it seemed reasonable. In reality, we should attempt to calculate how much debt we could get on the property by looking at it from a lender's perspective. This process of trying to predict how much debt a lender will provide on a property is called loan sizing.

How a Lender Sizes a Loan

There are 4 calculations lenders rely on to size a loan. They are:
  1. Debt Service Coverage Ratio (DSCR) - DSCR is calculated by taking the (NOI - CapEx Reserve) / Total Debt Payment. A lender will specify what month this test will occur. The lender might also have specific ways the NOI, CapEx Reserve, and Total Debt Payment are calculated. For example, if the month of the DSCR test is month 36, they might define NOI as the trailing 3 months NOI annualized, which in this case would be months 34-36 NOI multiplied by 4. They might define Total Debt Payment as the total payment amount, but assuming an interest rate of 6.5% and 25 year amortization period, even if the actual loan terms are a 4% interest rate and 30 year amortization period.
  2. Debt Yield - Debt yield is calculated by taking the (NOI - CapEx Reserve) / Outstanding Loan Balance. Again, a month for the test is specified and NOI can be defined however the lender would like.
  3. Loan to Cost (LTC) Ratio - LTC is calculated by taking the Loan Amount / Total Project Cost. Note that Total Project Cost includes most costs associated with acquiring the property, such as the loan origination fee, cost of 3rd party reports, etc...
  4. Loan to Stabilized Value (LTV) Ratio - LTV is calculated by taking the Loan Amount / Stabilized Property Value. Stabilized Property Value is usually provided in the appraisal, which is always required for loans, and is the appraiser's opinion of the property's value once it is fully stabilized.
These statistics can be used to see how big of a loan the lender is willing to provide. For example, if the lender has a DSCR test of 1.12x in month 36, then we know that the NOI must be at least 1.12x the total debt payment. If it's not, then we need to reduce the size of the loan until the payment is small enough to satisfy the 1.12x DSCR test.

Similarly on the debt yield test, if a lender has a 9.1% debt yield hurdle in month 36 then we need to make sure our projected NOI is at least 9.1% yield on the outstanding loan balance. If it's not, then we need to reduce the loan size or increase the amortization on the loan so that we meet the test minimum in month 36.

The LTC and LTV tests are a lot easier and more straightforward. LTC is usually defined by the lender by saying "loan amount not to exceed 80% of project costs" in the term sheet, for example. Likewise, LTV is defined by the lender by saying "loan amount not to exceed 70% of stabilized property value" in the term sheet.

How to Size the Loan in the Pro Forma

Now that we've reviewed the important lender stats and how they can be used to size a loan, let's look at how to actually size the loan for our pro forma. Notice that I've added rows 34-41 on the General Assumptions tab with some inputs that will help us size the loan. For the pro forma, I've assumed our debt yield and DSCR tests happen at the end of year 3.

The debt yield test is actually pretty simple. We know that our year 3 NOI is $586,507. Now we can back into what our loan size can be based on that NOI and our debt yield test assumption (9.1% in the pro forma). To caclulate the max loan size given the debt yield test, we just take the NOI and divide it by the debt yield test assumption of 9.1%. This gives us a max loan amount of $6.4M based on the debt yield test.

The DSCR test is a bit trickier. To calculate the max loan size given a DSCR test, we need to utilize Excel's PV formula. The PV formula has a couple of inputs. First is the interest rate. Second is the amortization periods. Last is the total payment amount. We know the interest rate and amortization periods--these are just assumptions we made earlier. The total payment amount is the tricky part. Basically, we calculate what our max payment amount could be given the DSCR constraint and our year 3 NOI. Our year 3 NOI, as stated above, is $586,507. Our DSCR test is 1.12x. That means, given our year 3 NOI, the max loan payment amount that still satisfies our DSCR test is 586,507 / 1.12 = $523,667. We then use that calculated amount as the total payment amount in the PV formula. This gives us a max loan size of $8.5M.

LTC and LTV tests are pretty easy. For the LTC, our max loan size is just the LTC assumption (75% in the pro forma) and multiply it by the total project cost which is calculated lower on the same sheet. For the LTV, our max loan size is the LTV assumption (70% in the pro forma) multiplied by a stabilized value assumption. For our pro forma, I've just used our exit price as the stabilized value.

Now that we've calculated the max loan size that satisfies each lender test we can see what our max loan size is. The debt yield test is the lowest max loan size, so based on all the tests our max loan size is the $6.4M.

Loan sizing is a surprisingly difficult but important part of the pro forma. Hopefully this exercise helped explain the concept and make it a bit more clear.