Retrospectives: Guinnessometrics: The Economic Foundation of "Student's" t

In economics and other sciences, "statistical significance" is by custom, habit, and education a necessary and sufficient condition for proving an empirical result. The canonical routine is to calculate what's called a t-statistic and then to compare its estimated value against a theoretically expected value of it, which is found in "Student's" t table. A result yielding a t-value greater than or equal to about 2.0 is said to be "statistically significant at the 95 percent level." Alternatively, a regression coefficient is said to be "statistically significantly different from the null, p ≤ .05." Canonically speaking, if a coefficient clears the 95 percent hurdle, it warrants additional scientific attention. If not, not. The first presentation of "Student's" test of significance came a century ago in 1908, in "The Probable Error of a Mean," published by an anonymous "Student." The author's commercial employer required that his identity be shielded from competitors, but we have known for some decades that the article was written by William Sealy Gosset (1876-1937), whose entire career was spent at Guinness's brewery in Dublin, where Gosset was a master brewer and experimental scientist. Perhaps surprisingly, the ingenious "Student" did not give a hoot for a single finding of "statistical" significance, even at the 95 percent level of significance as established by his own tables. Beginning in 1904, "Student," who was a businessman besides a scientist, took an economic approach to the logic of uncertainty, arguing finally that statistical significance is "nearly valueless" in itself.

Self-Reliance Before the Welfare State: Evidence from the Charity Organization Movement in the United States

If replacing welfare with private charity has increased the self-reliance of the poor, the benefits would be observed in the charity organization movement of the late nineteenth century. Inebriation would subside, the heart would be cheered, earnings would rise, the broken would be complete, dependence would wither, and the classes would converge. If the benefits were large, they would have been large in Indianapolis the beacon of charity in a Coasean landscape. The hypotheses are tested in hazard models using a sample from 25 years of household-level caseworker manuscripts. The evidence is not suggestive in the direction of hope.