For the final part of this Data Dialogue Series, Markerr’s Chief Marketing Officer Erin Crapser asked Brad Dillman, Chief Economist at Cortland, about how he selects data sources to create Cortland’s “secret sauce” for forecasting and what the future might look like when the global pandemic is behind us. Part 1 and Part 2 of this conversation are also on the Markerr website.
Erin Crapser: Can you talk a little bit about some of the other data that you use when you want to assess what’s going to happen in a certain market or submarket?
Brad Dillman: Yeah, so of course we’re bringing in the standard data sets. We pull in data en masse from the St. Louis Federal Reserve (FRED) website to get things like employment and permitting and things like this at the county level. We do pull files from the Census related to metro-level migration and immigration and this kind of thing. We actually have projections for that that help inform our models. So technically, Cortland has a view on how many domestic migrants will move to Palm Beach, say, over the next five years. All this can form our metro-level forecast, which then go on to form the submarket-level forecast.
But of course we’re relying very heavily on data sources like Axiometrics and Real Capital Analytics. And I think groups that are in the market to actually sell the data – as there’s more and more data scientists in the world, more and more people with technical skills – the need to have a system that just lives online where I have an analyst go in there and punch around is a lot less than what we can do when we actually have the data. And so I think companies like Axiometrics (which is, of course, owned by RealPage now), or Real Capital Analytics that will now sell you the data and allow you build your own models in your own system definitely have an advantage.
Of course Markerr does this as well and the data source that we get from you guys we rely heavily on your local level employment calculations that’s based on [Markerr’s Income & Employment Data] and also the gross personal income, which we have found to be an incredible predictor of rent growth. I mean it’s intuitive but it’s statistically very important, too, at the local level. So we look at things like submarkets and we have this historical characterization of gross personal income and then assumptions about how that’s going to grow based on employment trends at the metropolitan level, we actually get a very informative metric for our rent growth projection.
EC: When you think about the non-traditional, the non-CoStar data that you’re bringing in, how do you think that allows you and your team to be more powerful? What’s the role for that non-traditional data overall?
BD: That’s a great question. It’s allowing us to add in a secret sauce, as it were, and the metrics that we think are important. I mean, there is a lot of data out there and you can’t include everything in a model. Not only is it cost prohibitive, but it runs into the quantitative issues associated with having simply too much information. So we have to pick and choose the metrics that we think are important and something, of course, like gross personal income is intuitively something we thought was important. Of course we were very happy to see that it did work and that it did give us this extra insight at what we can call the local level. (I’ll call that the submarket level). And the employment metrics the same way.
It also gives us something that is more timely and it gives us something that a lot of other people don’t have. Anybody, (and a lot of people don’t know how to do this), but anybody can go to the Census and pull down the migration data. They can go though, they can do interpolations, they can characterize the past and then project it. Not everybody has [Markerr Income & Employment] local-level gross income information. So that really gives us some extra information that others don’t have, gives us an edge. Then, of course, we have the design of our models. We’re choosing to forecast first at the metropolitan level and then have submarkets informed by that metro-level projection. Other people might begin with some sort of submarket-based forecast, roll it up, roll it back down. There’s no real right answer to this. But we do, of course, have our way that we want to think about how the world works and what works for us and our thinking and that’s an important thing, too.
EC: We all hope that the coronavirus is not a part of our lives to this degree forever. So, when you think six, twelve, eighteen or more months out, what are some of the other things that your team is thinking about, is working on or that you’re excited about right now?
BD: I’m very focused right now, actually, on what we’re going to see on the fiscal spending side. Right now a lot of people are talking about the infrastructure bill. We’re also going to get some kind of bill in December that’s probably going to be more what we’d call “confiscatory” meaning it’s going to be taking money supply off the table in all likelihood and it’s going to be in relation to tax increases. So you’ve got this spending on the one hand coming upfront, confiscatory later in the year and then, at the same time, the implications for all of that on Fed policy.
And, of course, one of the things we’ve been thinking really heavy about is the potential for a taper. And that being the Fed has been buying all kinds of assets (largely treasuries) but as they go to slow that down, the margin will increase and the Fed’s balance sheet is going to slow down as well. And the real issue there is that if we look back at the past, this was last done in 2013, it was announced. We had the “taper tantrum,” which was a significant increase in the 10-year treasury rate. And if you go back and look at the performance of multifamily, that was followed by “the Golden Age of Rent Growth,” as we’ve called it, really due to a reduction in mortgage affordability. So you had excellent rent growth at the time. All of this in an oversupply housing market, I’ll add. We still had an excess supply of homes because of the various mistakes of the housing bubble.
But now we are in an environment that by virtually everybody is estimated to be physically under-built. So if we run into a situation where we do have a taper tantrum, let’s say, and a big increase in the 10-year treasury rate and resulting decline in mortgage affordability, we’ll be in a situation that should be quite bullish for multi-family.