Unlike most zoning rules, minimum lot size rules have been around for centuries. Indeed, unlike many design rules, they serve a clear purpose in many cases: In urban areas, tiny or highly irregular lots can make property rights fuzzy. In rural areas, you need a large lot to safely accommodate things like septic tanks and wells for drinking water. But like many zoning rules, these historically reasonable rules have often transformed to serve dubious ends: in most US cities, large minimum lot sizes are used to drive up housing prices or mandate spread-out development.

But do minimum lot size rules in fact increase lot sizes? On the face of it, this might seem like a weird question: why, after all, would cities have these rules on the books if they weren’t increasing lot sizes? But it could be the case that planners (or more accurately, planning consultants) are simply rulemaking for the sake of rulemaking, setting minimum lot sizes at roughly what the market already wants to provide. If that’s the case, all the research about how minimum lot sizes increase home prices or drive sprawl could be misdirected.

To answer this question, we looked at four Texas suburbs which have experienced explosive growth and development over the past 30 years: Round Rock, Pflugerville, Frisco and Pearland. We picked these cities because each had clear minimum lot size rules, high quality parcel data, recent population growth, and undeveloped land that remains available for development.

With parcel data in hand, we then compared the actual size of every single parcel to its zoned legal minimum size. What we were looking for was an unusual concentration of lots whose size was exactly, or very close to, the legal minimum.

The logic behind this can be illustrated by analogy. Imagine a grocery store that sells apples, and you can go in and pick them out a la carte and buy whatever number you like. If you were to survey customers who bought apples on how many apples they bought and graph the results, you might expect to see a pretty diverse distribution of results. On the other hand, suppose for some reason that this store imposed a minimum purchase of three apples. You can buy as many as you like beyond that, but the store will not sell you any apples at all unless you buy at least three. We would now expect to see an unusual concentration of customers buying exactly three apples, because that number would include those who might otherwise have opted for one or two apples.

In the same way, if there is a concentration of homes built on lots that are almost precisely the legal minimum area, that is a sign that developers might otherwise have chosen to develop smaller lots, but were legally barred from doing so.

If a lot’s area was below or just barely above (less than 110 percent) the legal minimum, we inferred that the minimum lot size regulation had a binding effect on the lot’s size. These cases indicated either that the developer had to pursue regulatory relief (e.g., a variance) or just barely met the minimum requirements. The developer presumably might have opted for a smaller lot absent the rules. If a lot was slightly above (110 to 120 percent) the minimum, we interpreted the rule as potentially binding. If a lot was well above the minimum (over 120 percent), we interpreted this as evidence that the rule wasn’t binding; i.e. it was not likely the deciding factor in lot size.