How long does it take to build a house in 2017?

Andrey Kamenov

Andrey Kamenov, Ph.D. Probability and Statistics

Ever wonder how long, on average, it takes to build a house? According to the most recent data from the U.S. Census Bureau’s Survey of Construction, it takes nearly seven months on average. More than half (52.4 percent) of all new housings are finished within five months (compared to just 46.7 percent 10 years ago), and 93 percent are completed within one year.

Of course, these numbers don’t come close to telling the whole story. Let’s see what the primary factors are that influence the duration of construction.

Of course, the size of the house — both the number of stories and floor area — have major impacts. Whether the house is attached and site-built is a statistically significant factor as well.

Last but not least, location matters a lot. In the end, we are talking about real estate. Unfortunately, detailed data for each state is not available publicly, with the lowest geography being census division.

How can you visualize so many variables at once? To simplify things a bit, let’s focus on several imaginary new houses. These are chosen to represent the most commonly observed characteristics:

  • “Small” — Single-story, 1800 square feet.
  • “Large” — Two stories, 3000 square feet
  • “Attached” — Two stories, 2000 square feet

The map below shows the time that it will take to complete the construction, predicted by our simple linear model.

Predicted construction time for sample house types

The New England division is where the highest numbers are observed. It would take more than 10 months to build a small single-story house here. In contrast, the same house would be built in just four months in the South Atlantic states.

Construction also takes a notoriously long time in California and other Pacific states. For a simple attached house, it would likely take close to a year.

Source(s):

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About Andrey Kamenov

Andrey Kamenov

Andrey Kamenov, Ph.D. Probability and Statistics


Andrey Kamenov is a data scientist working for Advameg Inc. His background includes teaching statistics, stochastic processes and financial mathematics in Moscow State University and working for a hedge fund. His academic interests range from statistical data analysis to optimal stopping theory. Andrey also enjoys his hobbies of photography, reading and powerlifting.


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