OK, but crime is going up, right?

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Last week we saw that crime -- property crime in particular -- is actually pretty low in Los Altos. Sure, okay. But look around, right? Crime is up, up, up! It's so much worse than it was a few years ago, right?

Is it, though?

Let's address this in two parts:

  1. What are the crime trends in Los Altos and the Peninsula?
  2. Why do our perceptions deviate from reality?
Again, let's start with California. A certain former president recently called for the summary execution of shoplifters as the only way to stop the California crime wave.

So, property crime is down almost 7-fold since its peak in the early 80s! I guess the good old days were not as good as we remember.

How about local crime? I wish I had data for Los Altos going back to 1960, but this is the best I can do:


Bottom line, property crime went up a little, down a little, but overall is pretty much the same over the last 5 years. Property crime in this graph is the defined the same as it was in the previous post: Breaking & Entering, Theft, Vehicle Theft, and Property Crime in the CityProtect database.

How can this be? I keep reading about how crime is up!

There are a couple of reasons, but here is the biggest:
The media reports the percentage increase of some slice of crime, one month over the previous, or one year over the previous.

For example, in that same Public Policy institute paper, they say: 
  • "[property crime] has ticked up 2.4% from 2020" 
  • "California’s violent crime rate increased by 6.0% [in 2021"
  • "Auto theft continued its 2020 climb, up an additional 7.6%—now up by 28.4% compared to 2019."
These kinds of statements are good for one thing only: stoking outrage. They don't give a clear picture at all about the amount of crime, or the trend in crime. Let me give you an example.

Let's say you normally have a couple of glasses of wine with dinner every Saturday night. Two weeks ago, though, you were at the kids' soccer game and didn't drink anything. Last week you didn't have any wine, but you had a beer at the barbeque. This week, you had your regular two glasses.

Here's the headlines:
  • Alcohol consumption up 100% over last week! Now up infinity percent compared to two weeks ago!
  • Beer consumption up infinity percent over last week!
  • Last week saw a huge increase in beer drinking. This week showed a huge increase in wine drinking!
Time for prohibition to stop this crisis!

This kind of analysis fails to put the numbers in the larger context. Comparing one period to the previous period emphasizes the regular random noise, and hides the real trends. And as this example shows, the smaller the actual numbers, the easier it is to have eye-popping percentage changes!

So which one is right?

Technically, both the graph and the statements from the Public Policy institute are correct. It's just that the facts about period-over-period increases don't tell us anything about the real situation.* We need the context that the full graph gives us.

In our local graph, I've used a 6-month rolling average. That means that for each month, I use the average of the last 6 months. Rolling averages tend to smooth out the random noise so it's easier to see the trend.

However, rolling average graphs don't get as many clicks; they are hard to build into panicky headlines.

So keep an eye out when you hear about crime statistics. If they aren't giving you context, then you should discount them -- at best, they are a prompt to go find the real numbers in context.


*In many cases, those increases change dramatically when you change the endpoints. For example, if instead of using the 1st of the month to the 1st of the next month, you added up the data from the 15th of one month to the 15th of the next month, you'll get a very different answer. If the arbitrary endpoints of your month definitions change the outcome of your analysis, you probably aren't seeing a real effect.







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