Beer consumption is generally treated as a matter of intuition. This seems surprising. The activity is common, repeatable, measurable, and exhibits an obvious diminishing-marginal-returns curve. It should therefore admit of optimization.
Let U(n) denote the utility of consuming n beers over the course of an evening. I model this as:
U(n) = S(n) + E(n) + C(n) − H(n) − R(n)
S = sociability benefit
E = euphoria
C = conversational fluidity
H = hangover cost
R = probability-weighted regrettable behavior
A major complication is that “one beer” is not a stable unit. A 12 oz lager and a 16 oz 9% double IPA plainly cannot both count as n = 1. I therefore normalize all intake into Standardized Beer Equivalents (SBEs).
Early result:
ΔU1 > 0
ΔU2 > 0
ΔU3 > 0
ΔU4 ≈ 0
ΔU7 << 0
(“Texting ex” becomes endogenous.)
The folk heuristic “a couple” turns out to be surprisingly robust, but too vague for high-stakes use. My current best estimate is that the optimal intake is n* ≈ 2.7 beers. Since fractional beers are physically realizable, I see no reason to round.
Some readers will object that this model does not sufficiently weight tail risks. I disagree. After a decade of field research, several lost jackets, one misdemeanor, and a continuing ban from McGlinchy’s, I have unusually high confidence in my calibration.
Update: multiple commenters persuaded me that drinks/hour may matter more than drinks/night. I therefore tentatively endorse the policy: “Know your limit, then exceed it by 0.7.”