00010.01 - The INPAT SOLVER Dataset

“One of the main determinants of your Quality of Life on a day to day
basis is the genetic quality (or lack thereof) of the humanoids within
a 5-mile radius of where you choose to sleep at night, as such it is
crucial to GET RIGHT, especially now as we head toward the waterfall
segment of the energy per capita availability phase of our long past
peak post-Oil Age civilization.”

A 100% human developed quantitative model with no AI slop or gimping
involved is generating real-time crafted output that identifies precisely
where the best current real estate values are with exact coefficients
enabling accurate valuation models directly comparable throughout CONUS.

If you are in a sub-optimal location, moving elsewhere is usually referred
to as ‘White Flight’ or on a higher grade of refinement ‘Strategic Relocation’ (full credit goes to author Joel Skousen for writing the 1st - and best - Edition that coined the term.)

The INPAT SOLVER model is subtitled Strategic Relocation Done Right.

A model, in order to have value must a) be accurate and b) the developer
must use it themselves, putting their own money where their mouth is. Contra if it is SOLD yet not USED, that’s the tell it has little real-world value.

A dashboard post, updating the current numbers several times per month
as new data is added and updated, is the bottom line, providing the end
results with the lower rated areas free and top ranking areas available
via subscription.

Qualifying zip codes must clear several uncorrelated hurdles, including market health and price action, entry discipline is especially important in a high interest rate, difficult economic environment with the era of easy housing market gains (and non-losses) likely over for the foreseeable future.

Jumping ahead straight to that may disorient or confuse the Reader, the
whys and wherefores are delineated in a multi-part series documenting the background and methodology with select indicator coefficients published and available for evaluation in order to assess whether this dataset is compatible with your use case.

Needless to say, ratings of golf courses, restaurants and public schools and similar metrics comprising mainstream, orthodox ‘Best Places’ lists is irrelevant to this purpose, the INPAT SOLVER model discerns the factors that really matter when you are exiting an area that has been demographically and socially damaged beyond repair and looking for an area with a future, a future where you and your children won’t have to move again in 20 years as the area sprawls out rinse repeat where those children will be able to afford the same kind of house you bought 20 years earlier.

The goal isn’t to flip houses or be a slumlord, the goal is to find blue chip areas that will stand the test of time, suitable to set down roots on a multi-generational basis.

I developed this for personal use, if the published version benefits others that’s a byproduct of the research not the primary purpose. That said, the model output - once the aim of the project is understood - passes my smell test, does it pass yours?

Part I provides the overview and background context:

https://utmensa2.substack.com/p/0001001-the-inpat-solver-dataset