(For most postings in the series see: <kymhorsell.com/UFO/Archive>).

EXECUTIVE SUMMARY:

- Carefully comparing UFO sightings of various types shows US military
spending seems to deter subsequent activity.
- It also seems certain types of activity see increased military
spending subsequently.
- The result appears to be either a knowing or unknowing low-level
cold war between the US military and UFO's.
- Results seem to be consistent across the various datasets subject to
some countries living inside the US military umbrella and some
outside; some countries have a more favored position under the
umbrella than others, possibly relating to assets on the relevant
national territories.
- There is preliminary data showing there has been a "gear change" in
the past 10-20y. Where increased military spending might have
deterred certain activity in the previous 50y more recently it can
have the opposite effect.
- The data seems to support oftentimes unattributed claims or rumors
of confrontations since at least the 1930s between military or
civilian aircraft and unknown objects and even close-order
"fistfights" between various militaries and UFO's or unidentified groups.


We've looked at the relationship between US military spending and
patterns in UFO sightings before. At one point we found military
spending seems to predict certain types of sighting in certain
locations, suggesting UFO sighting data does seem to include aircraft
the US military may have been developing over the past 50+years. There
was no indication the suspected aircraft used any unconventional
technology, but this might be another thing to examine at a later date. :)

After the AI s/w threw up an anomaly I've managed to smooth out the
results linking military spending on UFO sightings in several
countries, and UFO sightings on military spending.

It seems there is a consistent effect of military spending on UFO
sightings -- it generally declines in parallel to increasing in
spending and increased when spending decreases. Whether this is a
deliberate strategy is not clear. But there seems to be a de facto
cold war between the US military and UFOs of almost all kinds.

A wrinkle in the pattern comes from the US's close military ties with
some countries and lesser ties with others. "Allied" countries
generally see the same reduction in UFO activity when US military
spend goes up. But we can also detect a "move on" effect where the
opposite is true for some countries that don't apparently come under
the US military umbrella.

On the flip side we can see increased sightings of certain types are
apparently treated as "threats" by the US govt and invariable result
in greater military spending in later years. When sightings go down as
a result of "whatever" that spending goes toward, then spending tends
to relax again.

These patterns are very consistent across all types of UFO's -- I
generally divide them up by location-of-observation (state or country),
color of whatever lights are seen, and shape of whatever objects. The
time of day (in my work generally "dawn" aka eastern sky, "dust" aka
western sky, "daylight" and "nighttime") is another way the classify
sightings that produce interesting groups of events.

In the work below I'm mostly using the NUFORC dataset upto the end of
2021 now. Some other data comes from curated data series for the UK,
Canada and France (GEIPAN).

As this project proceeds -- it's only approx 1y old now :) -- I'll
continue to comb the 'net for sources of other sightings or category
of event. As we know, many unusual things tend to link up and are
suspected of being connected in one way or another with UFO activity.

The s/w I'm using here takes year-by-year event counts of various
classes of UFO sightings and compares them with US military spending
as a% of GDP. The data is massaged to remove various problems
(e.g. the NUFORC dataset changes gears in March 2006 when it moved
from telephone/mail reporting to a web-based report form; not only did
report numbers go up almost immediately an order of magnitude but the
type of things reported radically changed) and the resulting files
compared using very severe statistical s/w. If a result is not
better than 99% statistically certain the s/w will ignore it.

The s/w allows for a final level of "noisy data" (i.e. years that seem
to be much different from the overall trends are dropped, making sure
only a small proportion is finally ignored) and time-shifts data to
find the best alignment. The effect of some change may take several
years to show up to full effect; the s/w tends to ignore the
time-shifts that are less than the best it can find.

The best way to rank results is by the so-called "explanation power"
of the underlying statistical model. The "R2" statistic shows what
proportion of the "effect" variable is predicted by the "cause"
variable (possibly time-shifted).

Let's first look at the best overall results here.

Model Lag R2 Beta (90% CI)
(mil spending vs:)
Other 4 0.81047451 -0.224577 0.0226569
white 1 0.79688464 -0.235496 0.0242267
AUSTRALIA 6 0.74702442 -1.31413 0.287154
gr[ae]y 3 0.73177617 -0.202808 0.0258248
dusk 2 0.71641154 -0.166723 0.0217102
AZ 9 0.67127955 -0.268146 0.0444731
Circle 1 0.65660639 -0.183243 0.0276467
Sphere 4 0.65109060 -0.150306 0.0229554
MO 5 0.61291093 -0.163303 0.029277
notlight 1 0.61047755 -0.172894 0.0277193

We first note the top10 results include sightings based on US states,
one is the national total for Australia compiled from the independent assessments of groups in each state, some are based on (mostly
US-based) NUFORC object color (incl US and UK spellings) or shape, and
the last is a category that excludes from the NUFORC annual totals
those objects curators classified as "lights in the sky" -- supposedly
the most error-prone UFO type.

We see in all cases that increases in US mil spending are associated
with decreases in those types of sighting. The Beta shows approx what percent/fraction reduction is associated with a 1% GDP increase in US
military spending. E.g. for 1% GDP extra US military spending the
category "Other" (any shape that doesn't fit a usual NUFORC shape
category) sees a 22% decline after 4 years (the Lag column).
Contrariwise a decline of US spending generally sees an increase in
those kinds of sightings.

The effect of US military spending on sightings in Australia is even
more profound. The Beta of "-1.3" actually indicates an almost 4-fold
decline for each 1% of GDP in spending or similar increase for reduced spending. The lag for this link is around 6 y. It seems Australia

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--- SoupGate-Win32 v1.05
* Origin: you cannot sedate... all the things you hate (1:229/2)