What Newton’s first law says

Newton’s first law states that a body on which no net force acts stays at rest or keeps moving in a straight line at constant speed (Newton 1687). It is often shortened to “bodies like to stay as they are”, but the “as they are” covers two states: rest, and motion already under way. A person already doing something also has “inertia” in continuing to do it. When this book speaks of keeping to the status quo, it means both: being slow to start something new, and being unable to stop something old.

Note also that strict Newtonian inertia has no tendency to “return to the start”: push a puck on smooth ice and it slides on indefinitely. When people say “I pushed, and it went straight back”, they describe a different kind of system: one with a resting point, a restoring force that pulls it back after any displacement, and damping that soaks up the extra motion. A ball on a spring and a marble in a bowl behave this way. When keeping to the status quo is compared with inertia, the closer model is this kind of damped restoring system, not pure inertia.

Evidence for status quo bias

Both findings show that the status quo carries weight of its own. The second also reminds us that keeping to it is not just “not bothering to move”: a default carries information (“the experts presumably recommend this”) and shifts the reference point. The two models below capture only part of this.

Model 1: a hard push versus a steady force

# A damped "state" variable x pulled back to its old set point x0 = 0 (status quo).
#   m x'' + c x' + k x = F(t)
# A short push, however hard, decays away; only a force that is sustained shifts the resting point.
# Cross-disciplinary analogy / simplified model: x is not a measured psychological quantity.
m, c, k = 1.0, 0.8, 1.0
dt = 0.001

def run(force, t_end=40.0):
    x = v = 0.0
    t = 0.0
    peak = 0.0
    while t < t_end:
        a = (force(t) - c * v - k * x) / m
        v += a * dt
        x += v * dt
        peak = max(peak, x)
        t += dt
    return peak, x

cases = [("short hard push   (F = 5 for 0.5)", lambda t: 5.0 if t < 0.5 else 0.0),
         ("weekend burst     (F = 1 for 3)",   lambda t: 1.0 if t < 3.0 else 0.0),
         ("small but steady  (F = 0.5 always)", lambda t: 0.5)]
for label, f in cases:
    peak, end = run(f)
    print(f"{label}: peak displacement {peak:4.2f}, position after 40 time units {end:5.2f}")
print("steady state under a constant force F is x = F/k: the set point moves only while the force lasts")
# short hard push   (F = 5 for 0.5): peak displacement 1.49, position after 40 time units -0.00
# weekend burst     (F = 1 for 3): peak displacement 1.23, position after 40 time units -0.00
# small but steady  (F = 0.5 always): peak displacement 0.63, position after 40 time units  0.50
# steady state under a constant force F is x = F/k: the set point moves only while the force lasts

The meaning is simple. The hard push and the weekend burst both move the state well away from the origin, but once the force stops, restoring force and damping pull it back; after forty time units it is at zero again. Only the small steady force changes the final position, and as long as it acts, the resting point sits at $F/k$. In this model, what moves the resting point is persistence, not intensity.

The conclusion holds only under the model’s assumption that the restoring coefficient $k$ stays the same. Real habits change: sustained practice may reshape the “bowl” itself, which is what the double-well model of Chapter 3 deals with.

Model 2: switching cost and defaults

# Status-quo choice with a switching (activation) cost. Simplified model.
# Option B's advantage over option A, d, varies across people: d ~ Normal(0.3, 1).
# A person leaves whichever option is the default only if the gain exceeds the cost c
# of deciding and acting. Without a cost, the default would not matter at all.
from statistics import NormalDist

D = NormalDist(0.3, 1.0)
print("cost c   chose B when A was default   chose B when B was default   gap")
for c in (0.0, 0.25, 0.5, 1.0, 1.5):
    b_if_a_default = 1 - D.cdf(c)      # switch A -> B only if d > c
    b_if_b_default = 1 - D.cdf(-c)     # switch B -> A only if -d > c, so B kept if d > -c
    gap = b_if_b_default - b_if_a_default
    print(f"{c:6.2f}   {100*b_if_a_default:22.1f} %   {100*b_if_b_default:24.1f} %   {100*gap:4.1f} points")
# cost c   chose B when A was default   chose B when B was default   gap
#   0.00                     61.8 %                       61.8 %    0.0 points
#   0.25                     52.0 %                       70.9 %   18.9 points
#   0.50                     42.1 %                       78.8 %   36.7 points
#   1.00                     24.2 %                       90.3 %   66.1 points
#   1.50                     11.5 %                       96.4 %   84.9 points

With no switching cost, the default makes no difference at all: 61.8 % choose B in both framings. As soon as there is a cost, the same people with the same preferences differ by tens of percentage points according to which option is the default. With a cost of one standard deviation, the gap reaches 66 points. A fairly small start-up cost is enough to give the status quo an overwhelming advantage across a population, without assuming any special love of the status quo.

Limits of the analogy

The inertia analogy has two limits that are easy to overlook. First, a body does not judge whether a force is worth yielding to, but a person does: sometimes a person keeps to the status quo precisely because, having considered it, they judge it better, and calling that a “bias” is unfair. Samuelson and Zeckhauser themselves noted that part of the tendency is rational, since gathering information and deciding both have costs (Samuelson and Zeckhauser 1988). Second, mass in physics is a fixed number, while a person’s “inertia” varies greatly with circumstances: “breaks” such as moving house, changing jobs or a new year temporarily loosen the hold of old habits, which behavioural science calls the habit discontinuity hypothesis, supported by a field experiment (Verplanken and Roy 2016).

Summary

The inertia analogy has one useful lesson: a short burst rarely changes a system with a restoring force, while a steady force, however small, moves the resting point. It also has something that must be said plainly: people are not passive bodies, keeping to the status quo is sometimes a reasonable choice, and the power of defaults does not come only from “not bothering to move”. The next chapter takes up another physical effect tied directly to starting: static friction.