Applied Geographic Solutions, Inc.

The summer months can be a lonely time in many towns. Just over twenty-one million people are enrolled, either part time or full time, at colleges and universities across the country, just over 6% of the population. Many large universities are in small towns, where the exodus of students after final exam week has a major impact on the retail and food service sectors of the town.

As the average family size has declined over the past few decades, many school districts have been dealing with long term declines in enrollment. In the suburban developments of the 1960’s and 1970’s, many elementary schools have been closed or repurposed. Even in current growth areas, the additional student demand may be low and not require the construction of facilities which may be necessary only for a couple of decades. For public schools, the rise of both home schooling and private school alternatives has resulted in declining enrollment even in growth areas.

While our main purpose in building a national parcel database is to enhance our core demographics by tracking change at the address level, along the way we have discovered that we can add to our detail tables with many new data tables. In addition, some of the information available is extremely useful in our current efforts to substantially improve our Consumer Expenditure (CEX) and Household Wealth databases.

In the first two parts of this series on income, we considered the various definitions of income commonly used and how exclusions of capital gains and non-cash payments can affect small area estimates in different ways. Here we consider measures of income that may merit consideration as alternatives.

The first of two inflationary periods of the 1970’s began early in the decade and was particularly hard felt in the hot real estate markets of urban California. Property taxes were completely tied to the annual market valuation conducted by the county assessor. During the initial inflationary period, people rushed to buy into the housing market before it became unaffordable and drove prices through the roof. The rapid population growth at the time put enormous pressure on local governments to provide ever more expensive infrastructure and schools. Many had their property taxes doubled or tripled over just a few short years.

Last week we talked about the complexity of the concept of income. We continue here by focusing on the Census Bureau definition, and how that definition introduces spatial biases that could substantially impact your location decisions. So how does the Census define household income?

Ask 100 users of demographics to name the 5 must-have variables they use in their analyses and income will almost always be listed. Ask those same users to define the term, and you will hear a stunning range of answers. In fairness, if you ask 100 economists to define income, you will get an even larger range. The Mirriam-Webster dictionary defines income as “a gain or recurrent benefit usually measured in money that derives from capital or labor.” This is accurate, but likely not overly helpful. What is income? In the first of a multi-part series, we examine income in demographics and potentially more important, consumer expenditures.

In the summer of 1996, a movie about storm researchers became a hit movie: Twister. It followed a group of storm chasing meteorologists in central Oklahoma as they dodged, sometimes unsuccessfully, a line of storms in a single day. The production crew went as far as chasing tornadoes with researchers from the National Severe Storms Laboratory in Norman, Oklahoma, to fully understand what storm chasing entailed and train the crew on weather safety. This year, the stand-alone sequel, Twisters, is poised to be the movie of the summer. What do we know about tornadoes geographically, and why should tornado risk be taken into consideration for site selection or insurance underwriting?

Just in time to cure the summer slump, the Olympics are here, entertaining us daily for a few weeks with inspiring performances and the chance to bring home some medals. This year, Team USA’s 594 athletes hail from 46 states, so nearly everyone has someone to cheer for (apologies to those in Oklahoma, West Virginia, Wyoming and North Dakota). What do we know about Team USA, and what can we learn from looking at their hometowns?

At the end of each month, the AGS team looks back at articles and blog posts that we saw this month that stood out to us. Some are from news agencies, and many come from our partners, but not all use our data. Here is the round-up from July 2024.