Fair lending and discrimination

If a lender offered the same price (i.e. interest rate or APR) to every borrower, then it would only be a good deal for the riskiest borrowers. Lenders would have to raise prices to match the risk, and then it would only be a good deal for the riskiest of the riskiest borrowers. Lenders would have to raise prices further and further until there are no takers. This is called an adverse selection death spiral.

Therefore, lending fundamentally relies on offering different prices to different borrowers—and refusing some borrowers entirely. In other words, lending fundamentally relies on discrimination.

Lenders assess the risk of each borrower, in a process called underwriting, and make the decision whether to decline or approve, and at what price. Traditionally, underwriting has been done manually by human experts. It has also been performed by following pre-determined rules. More recently, many lenders are using machine learning to make underwriting decisions.

When we talk about discrimination, usually we’re talking about “bad” discrimination, such as sexism or racism. But in general, discrimination is just about treating different people differently, and that in itself is not bad. Nonetheless, legitimate discrimination can be used to conceal bad discrimination. Bad discrimination can also occur unintentionally, being concealed even to its purveyors. Fair lending regulations try to delineate and mitigate bad discrimination in lending.

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Not for Broadcast’s bizarre politics

Not for Broadcast is a comedy FMV game about managing a television broadcast. This essay is emphatically not a review, meaning that I have no intention of recommending one way or another whether you ought to play it. Rather, I’m interested in discussing its story about liberal fascists. I will also get into spoilers—warnings when I get there.

What is Not for Broadcast?

Not for Broadcast is at its core a multi-tasking game. You must divide your attention between cutting between multiple cameras, bleeping out swear words on a two second delay, adjusting for interference, and don’t forget to actually pay attention to the show that you’re editing, so you can follow the story.

There’s no mechanical benefit to following the story, so in my experience, it got lowest priority. The game delivers a unique experience where the narrative is delivered through a fog of distraction. This aligns with the narrative of the game, which is about a government that distracts from the real issues by filling broadcast news with fluff. Of course, to actually appreciate what the game was doing, I watched the archived footage afterwards. Paying attention would often cast segments in a whole new light.

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Mixed race in the 2020 US Census

TL;DR: The 2020 US Census shows a very large increase in the “Two or More Races” group. However, at least some of this likely has to do with changes in the question design and coding procedures, and shifting constructions of race.

The US Census construction of Race

When the US Census asks about race and ethnicity, it tries to reflect the way that racial/ethnic identity is constructed in the United States, but it also has to obey certain constraints. As a result there are some outstanding differences between race as it is constructed by US residents, and race as it is constructed by the US Census. For example, Middle Eastern Americans often do not identify as White, and are not perceived as White (and I suspect this perception has increased since 9/11), but in the US Census they are still classified as white.

Another outstanding difference is in how the US Census defines “race” vs “ethnicity”. According to the Census, “Hispanic, Latino, or Spanish origin” and its negation are the only ethnic categories, and are excluded from the racial categories. I can say from my own experience with surveys, that this system is really weird, and causes no end of confusion among respondents.

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2021 California Election positions

Hey, remember in 2020, when I said vote, but not just today? I’m going to keep citing that.

Starting today, California voters are getting mailed ballots for the gubernatorial recall election. As far as I know, this is a uniquely Californian process, where if opponents gather enough signatures, they can initiate an election to end the governor’s term early. This ballot has only two questions, but I still going through the usual exercise of stating my positions.  (The point is not to share heavy amounts of research, which I do not do, it is to normalize the process of just looking things up and voting.)

No on recall

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From the Archives: Evaluating FiveThirtyEight

This is a repost of a simple analysis I did in 2012, evaluating the presidential predictions of FiveThirtyEight.  What a different time it was.  If readers are interested, I could try to repeat the analysis for 2020.

The news is saying that Nate Silver (who does election predictions at FiveThirtyEight) got fifty states out of fifty. It’s being reported as a victory of math nerds over pundits.

In my humble opinion, getting 50 out of 50 is somewhat meaningless. A lot of those states weren’t exactly swing states! And if he gets some of them wrong, that doesn’t mean his probabilistic predictions were wrong. Likewise, if he gets them right, that doesn’t mean he was right.

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A 2D voting sim

I made a Monte Carlo voting simulation. No particular reason, I just think it’s neat.

Okay, so I was thinking about the Median Voter Theorem, which says that the winning position in an election is the position of the median voter. Of course, this conclusion only holds under certain assumptions, and none of those assumptions are actually true. And yet the conclusion is approximately correct in many situations. That’s why we care disproportionately about the median congress members (like Susan Collins), the median Supreme Court Justices (like Roberts), and the median “swing” states (like Pennsylvania).

But it should be obvious that the median voter fails in a lot of ways. In particular, it doesn’t predict the political polarization that occurs in US politics. And there are plenty of possible explanations: voter turnout, third parties, primary elections, politician’s charisma factors, multidimensional political spectra, and so on. But I’m not sure which among those explanations are most important.

The voting simulation won’t answer any of these questions, I’m just setting the context. One of the assumptions of the Median Voter Theorem is that political preferences exist along only one dimension. I thought I’d try running simulations with two dimensions to see what would happen, and to make some pretty graphs.

Plot showing all the voters and candidates along a two dimensional spectrum.

Voters and candidates in a 2D space

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Vote, but not just today

Justice Amy Coney Barrett was confirmed to the Supreme Court of the United States yesterday. This makes the current Supreme court one of the most conservative in ages, with a 6 to 3 majority. Previously, some cases would be ruled in favor of the liberal judges, because one of the conservative judges would agree with the liberal judges (and often they would dictate the terms of the opinion). Now this is much more unlikely, as it requires two conservative judges to side with the liberals.

This will have wide-reaching consequences. One of the most immediate consequences is on the current case arguing against the constitutionality of Obamacare.

If you’re a US citizen, you’ve likely been told to vote a hundred times already. Even if you’re not a US citizen, you’ve seen it, and are probably sick of it. This is, of course, because Trump is an extraordinarily dangerous president. But I want to point out the obvious: this whole situation with the Supreme Court did not arise from Trump shenanigans, it arose from plain old Republican shenanigans. Amy Coney Barrett is a judge that any Republican president could have nominated, and any Republican senate could have confirmed.

So don’t just vote out Trump, vote them all out. Note, senators are only reelected every 6 years, so this requires sustained commitment–voting in every election, including midterms. This year, everyone is anxious about the election and feeling a bit powerless. Channel that anxiety into a commitment to exercise your voting power at every opportunity.

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