Okay, this is neat. Stanford has created what is effectively Google Maps for the Roman Empire.

What it shows you is the principal routes of the Roman World: the road network, the main navigable rivers, and the hundreds of sea routes that crossed the Mediterranean, the Black Sea, and the coastal Atlantic.

The tool then attaches both time and expense to these routes (which would have been used for the transportation of goods and people, but also for general communication across the Roman Empire).

So if, for example, you are curious about how many days and how many denarii it would have cost you to deliver an important dinner invitation from Roma to Alexandria during the summer months of antiquity, you now have an online tool. It's about 14 days.

This recent paper by Miyuki Hino (University of North Carolina) and Marshall Burke (Stanford) makes the case that US homes situated within floodplains are currently overvalued by a total of $34 billion. And that's because the associated risks are not being properly accounted for in the value of these homes.

The problem, it would seem, comes down to information. Because the discount for flood risk was found to be higher (1) for commercial buyers (presumably because they're more sophisticated and/or have better access to information) and (2) in states where sellers must disclose flood risk (Louisiana is probably the most stringent about this).

This feels a bit like one of those realtor commercials that tries to scare you into using one. But it does appear to demonstrate just how opaque the market can be and how information asymmetries potentially distort asset prices. Perhaps most importantly, I wonder when climate risk will get fully valued.

A couple of months ago I wrote about the relationship between IPOs and home prices. It was in response to the current wave of tech companies -- most of which are headquartered in San Francisco -- that have gone public or are expected to go public this year (2019). What impact will this have on the city's housing market?

I cited this academic study on the topic, which already discovered a "positive and significant association between local house price changes and firms going public." But today I stumbled upon another interesting study by a San Francisco real estate agent, name Deniz Kahramaner, who happens to also be a Stanford-trained data scientist.

What Kahramaner wanted to figure out was, who tends to buy residential real estate in San Francisco?

So he started with title data and then scraped the internet to try and match up individual buyer names with specific companies and industries. Since not everyone has some sort of public profile and because real estate is sometimes held within a company, he was only able to traceback about 55% of home purchases in San Francisco last year.

Still, the data looks pretty clear. About half of the homes bought in 2018 were by individuals whose employment has roots in "software." The next biggest buyer segment was "finance."

The other interesting thing about this data set is that it shows where people have been buying (at least last year). Historically, the north end of the city has been the wealthiest, but the above data shows things moving in a southeasterly direction. Though, it remains to be seen what all of this will look like when the dust settles after this current crop of tech IPOs.

Chart: The Atlantic