Panning For Rental Property

MD new housing starts 2000-2011Gullgraver_1850_California

I know.  In today’s modern world, that’s a pretty goofy mental image: some old-timer crouching over a stream and sifting for that one gold nugget.  And yet, that’s kind of what we did when we looked for our first rental property.  I estimated that we spent ~200 hours screening properties to find The One.

Now that we’re officially on the hunt again, I figured I would detail the process we’ve used previously and are planning to use (and evolve) again.  Although, this time we’re looking for something a bit different.

So let’s start with the master plan:

  1. We have a 2br/2ba condo that is a pure investment property.
  2. We live in a 4br/2.5ba townhouse with a low enough cost structure and in a very desirable neighborhood that it should also make for a good rental.
  3. We want a single family house close to my wife’s employer, in a neighborhood with good public schools, and with a dedicated rental space.

So, the goal is to keep house #2, rent it out, and add a third rental to offset the cost of our next place.  As always, our general philosophy is buy and hold.  I guess that means we have some pretty specific requirements.  Perhaps some of these characteristics reflect others’:

  • “Class A” (lots of folks have different definitions; this is close enough for my purpose)
  • Good k-12 public schools (7+ on
  • Close (<2 miles) to public transit (for us that means trains into DC)
  • Close (<1/2 miles) to a community park, ideally with running/biking trails
  • Because we’re looking to use part of our house as a rental (e.g. a big chunk of a finished basement), we need to be near our target tenants’ desired location, have a separate access, and have utilities available for the rental space
  • We’re looking to offer our tenants a studio or 1br space for between $750 and $1000 a month
  • Modest appreciation, at least keeping up with inflation.  We’re in the buy and hold space, so we’re not looking for anything that requires huge increases in value to make our investment pay off.

I’ve been doing some digging on this topic since I listened to a podcast by Paula Pant over at Afford Anything where she outlined some of the key factors she uses to invest in real estate:

  • Price to rent ratios
  • Building permits (new starts and renovations)
  • Job creation
  • Infrastructure development

Over the next few posts, I’d like to dig into some of these factors a bit as I’ll be exploring them in more depth as part of our own search.  I know there’s lots of discussion out there about “big” data.  My goal isn’t to make this into a science project, but I do believe there’s some useful data available for real estate investors, and it is not limited to subscription only sources.

Let’s start with an example.  We currently live in MD, and we’re looking for our next property in MD.  So, I started at Maryland’s open data site.  There’s a bunch of data sets to geek out with.

I’ll pick the new residential housing units data set to start.  In theory, a county with lots of growth, would be likely to offer a good opportunity.  Here’s a quick snapshot of the 24 MD counties, their total new residential housing starts from 2000 through 2011 (I couldn’t find a more recent data source).  I also included a line chart view of each county over that time period to illustrate any trends.

It looks like the top three counties from this time period were Montgomery, Prince George’s, and Anne Arundel.  On each of their trendlines, you can see upticks in the last 3-4 years.   Thinking back to that era, the 2005 BRAC was in full swing.  While it may have caused significant challenges around the country, the Ft. Meade area and it’s surrounding counties (those three) benefited from a significant influx of DOD related jobs.

What do you think?  Do new residential starts portend a good rental real estate market?  Will this trend continue in the future?  There’s always talk of the DC “bubble,” although with the current president working to limit federal government employees, the real estate sector may be in for another shake-up in this area.  Drop me a line and let me know.

Would You Bet Your Life On It?

Look Out!

Look Out!

I’m betting that I won’t live to see my 55th birthday.

Ugh, that was a tough sentence to write.

But, in a way, it’s true: now that my wife and I have a little girl, we’re thinking about buying life insurance.

Which really makes me grouchy!

Why on earth would I dump money into something where I hope I never get paid back!?  Shouldn’t I just put money into an asset that may appreciate?  Won’t my family be better off just cashing out my investments once they’ve had a chance to grow?


Unfortunately, there’s a lot of buses out there, and you just never know if one has your name printed on the front of it.  And, that’s why we carry insurance: to protect us from low probability, high risk events.

  • The house burning to the ground.
  • Someone smashing into our beloved (parked) Scion xB.
  • A sudden stop to the journey we know as life.

Unless you’re already loaded, it’s tough to be completely self-insured (not us, by the way).  So, we’re back to buying life insurance.

More specifically, I’m looking to buy a 20 year term policy.  Let’s keep the math simple and say that we’ll buy a $500,000 policy (we don’t want her to grow up wanting).  I’m almost 35.  With a term policy, the bet that I’m making is that I will die sometime in the next 20 years.  If I do, my girls get $500,000 (assuming my path to the Big Dog Park in the sky met the predefined criteria).  Some really smart mathematicians have figured out the risk (or probability) of someone within my demographics suffering a similar fate.  Using some complex statistics and math, the insurance companies have figured out what premiums (small, routine payments) each person in the population would need to make in order to work out to a profitable business for them.  Their goal is to have more money coming in through premiums than money being paid out in claims.  For an insurance company the aggregate difference between the two is called the loss ratio.

Back to my bet against the insurance company’s…  I received a quote from an insurance company for monthly premiums.  They quoted roughly $20/mo for the first 5 years, and $25/mo for the remaining 15.  In exchange, were I to meet an untimely demise within the 20 year period, the insurance company would pay out the benefit value of $500,000 to my family.  And that’s the bet we’re each making.  The insurance company is betting I’ll outlive my policy so they don’t have to pay up.  I’m making sure my family is covered in the unlikely (I hope!) event of an early ascension (or a bus ride to someplace warm).

So, what are the odds in this particular bet?  In my mind, the insurance company knows the odds of an individual passing, and they set the premiums accordingly.  So I’ll assume that the:

 Payout x Probability Of Dying can be no more than the Cumulative Premiums.

What I think that means is that:

The Probability of Dying <= Cumulative Premiums / Payout

I said I was going to keep it simple.  That’s all the math I’m going to throw at you for this post!

What are the odds? In whose favor are they?

What are the odds? In whose favor are they?

The less than condition is there to cover profit, overhead, etc. that the insurance company factors in to their math (and I don’t have access to that stuff).  Let’s look at the “best” case where I’ve spent the least and receive the payout: tomorrow.  I’ve paid my first month’s premium, and wham!  Fortunately for me that works out to a 0.004% or smaller chance of occurring.  But it could happen, and that’s exactly why I want to “invest” in life insurance.  Our investments haven’t had enough time to grow to cover the costs of raising our daughter, paying for college, etc.  It’s tough to find a $500,000 return for on an investment of $20 anywhere else (25,000:1).

Now fast forward to the last month of the 20 year term.  I’ve successfully dodged buses, riots, airplane crashes, and all other manner of unexpected hazards.  I’ve paid in $5,700 in cumulative premiums (without adjusting for inflation).  Then a slip in the shower and wham!  That < 1.14% chance of death somewhere within the 20 year term worked out in my favor … I guess.  My family still gets the payout, but it cost me the full premium amount.  That’s still almost an 88:1 return.

Let’s look at the most likely case: everyone lives happily ever after.  This is the one that keeps insurance companies in business.  It’s also the one that feels like a warm blanket.  My girls were covered for some of the most vulnerable years of our lives.  I slept better knowing that they would be taken care of in case of unlikely events.  And that’s well worth $5,700 spread out over twenty years to me.


I should mention that in no way should you use any of this to make any life insurance decisions of your own!  Do you homework.  That said, what do you think?  Are the odds worth the expense?  How much insurance do you carry?  What type(s)?