POLITICS
Here’s why rare bills that fail are as interesting as the ones that succeed
Why experts should care about state legislative bill failure, and how to observe it
On May 22, the Pennsylvania House of Representatives took a final passage vote on HB 338, a gun control bill relating to lost or stolen firearms. At the time, Democrats had a slim 101–100 (with two vacancies) majority in the PA House, and by scheduling the vote, it’s fair to assume the Democratic party leadership knew what its members wanted and the bill would have passed. But in an unlikely turn of events, the bill failed, after Rep. Frank Burns (D) joined every Republican in voting against it.
This is quite rare.
I didn’t realize quite how rare though, until a reporter from the PA Spotlight asked if I had any data on the question. Luckily, I do, as I recently published new data on legislative histories (that is described in my recent article in Legislative Studies Quarterly, featured in the Data is Plural newsletter, and is available for download on the Harvard University Dataverse), to help answer this question.
I’ll detail where this dataset came from and how it works in the next section. But first let’s take a look at just how a bill failing on a final vote is. I told the reporter, Stephen Caruso, that about two percent of the bills considered for final passage in the PA legislature from 2009–2018 failed. You can see this in Table 1 below:
This table first shows that 97 percent of bills that receive a final passage do indeed pass. Beyond that, the vast majority of bills that do not pass initially are “reconsidered,” or sent back to committee to be reformulated, and then eventually do pass the chamber that granted them final consideration.
However, there were a handful of bills that had the same text from the legislative history as HB 338, such as 2018’s HB 1037 that was also: “Defeated on Final Passage.” These bills did actually die. Compared to the tens of thousands of bills that were initially introduced, maybe it is fair to call something that only happened ten times a “lightning strike.”
These data beg the question, how can bill failure happen when the Majority Party controls which bills come to a vote?
The answer is that it can be either intentional or unintentional. From an outside view, the failed 2023 gun control bill appears to be unintentional. The Democratic majority in the PA House is so slim right now that only a single defection can sink a bill. That is a tall task for even the sharpest whip counters.
But there is also an intentional logic for party leaders to advance legislation that will fall. In Legislative Studies Quarterly, Jeremy Gelman describes the logic of “Dead on Arrival” bills, which are advanced by party leaders with the full knowledge they will not become law, either because they are opposed by a majority in the other chamber or face an executive branch veto.
For a contemporary example, consider the Congressional Republican’s “Limit, Save, Grow” act designed to putatively raise the debt ceiling, but which lacks support in the US Senate, nevermind from President Joe Biden. Gelman, though, argues these bills can serve a separate purpose, which is to demonstrate to allied interest groups where their support is in the chamber. His argument fits the case of gun control well, as there are a number of active gun control advocacy groups watching such a bill, including CeaseFirePA which releases a legislative scorecard based on votes like these. I am sure the defection from Rep. Burns will not go unnoticed.
Tracking Legislative Progression
In general, this case demonstrates the value in the systematic analysis of state legislative bill histories. My Legislative Progression dataset allows researchers, advocates, and the public to conduct analysis like I did above.
The dataset presents estimates of every step taken by every state legislative bill in the US from about 2009–2018, and is drawn from millions of bill actions collected by the OpenStates project. Specifically, I attempted to put all of the states into a common space. The goal was to see how bills follow a similar structure, where they are read “three times” in each chamber, the third time being the “floor consideration” or final passage as discussed in Pennsylvania.
I must admit that putting this dataset together revealed that each state’s process is more unique than I would have assumed initially. Nonetheless, this dataset represents my best effort to line the states up. Bills receive an “Lpcode” corresponding to each step along the line, which allows researchers to identify similar situations across all the chambers.
For example, the Pennsylvania “third reading”, or final consideration in a chapter is 30 (or 60 if it’s the second chamber), and passage from that chamber is 38 (or 68 for the second chamber). So I started the analysis above by looking for bills that met those criteria.
There’s much more under the hood and I would encourage any researchers interested in state legislative bill histories to read the description (.pdf) on Dataverse to better understand how to analyze these data. Because as we saw in Pennsylvania, sometimes bills that fail can be just as interesting as bills that pass.
