The recent draft of the Go Big Green Bay 2050 Comprehensive Plan seems to indicate
that Green Bay’s population may decrease in the next twenty-five years. Yet, what
goes into forecasting this type of figure? Here are some insights into what makes a
projection plausible.

Forecasting the population of a city like Green Bay isn’t about predicting one fixed
number — it’s about understanding the forces that will shape who lives, works, and
raises families here. City planners, businesses, and community leaders need these
projections to guide investments in housing, schools, healthcare, and infrastructure.
Here are the key methods — and emerging signals — that can help us anticipate what
Green Bay might look like in 2040.

1. The Cohort-Component Method
The backbone of population forecasting is the cohort-component method, which
projects how many people will be in each age group in the future. For Green Bay, this
means:

• Tracking births, as Wisconsin has seen declining fertility rates.
• Estimating deaths, with an aging Baby Boomer population that will reshape the region’s age structure.
•  Monitoring migration, which may be the biggest wildcard — will young
  professionals move here for affordable housing, or will they leave for bigger metros?

2. Trend Extrapolation
Looking at past patterns can provide clues. Green Bay’s steady but modest growth
could be extended forward using census data and housing permits. But trend
extrapolation alone may miss major shifts, like the impact of remote work allowing
professionals to live in smaller cities, or economic downturns that push people away.

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For a more detailed document describing what may shape the future of Greater Green Bay 2025-2040, click Drivers of Change PDF

Nan Nelson, Economic Transformations

Futurist Andrew Curry is recommending we check out an interview with the social philosopher Roman Krznaric on Five Books about how the lessons of history might help us navigate the present. It’s prompted by Krznaric’s recent book History for Tomorrow.  There’s a long tradition that we can’t learn from history, and there’s another one that says that we tend to draw the wrong conclusions because we use history metaphorically and then choose the wrong metaphors. Krznaric is interested in patterns, which Curry thinks is an underlying principle of futures work: patterns exist.

Krznaric has a chapter in his book on artificial intelligence, which seems essentially modern. “Reading Why History Matters made me think,” Curry says. “Have we ever created large-scale systems which could potentially get out of control, which is one of the potential risks of AI?”

And he answers, “Yes, we have. We invented the instruments of financial capitalism in the Netherlands in the early 17th century: the first stock exchanges, the first public limited companies, marine insurance. It was a human-created system that very quickly got out of control, with the advent of multiple financial crashes.

As the futurist Wendy Schultz says from time to time: to be a good futurist you also need to be a good historian. Deep structures matter.