The concept of ‘demographic efficiency’ is proposed and data envelopment analysis (DEA) is introduced as a method for determining which countries are demographically efficient. While the purpose of the paper is primarily to introduce the concept and the method, several simple examples are used for purposes of illustration. The first two explore how efficiently countries have converted their level of development (the ‘input’) into male and female life expectancy at birth (the ‘outputs’). The second two reverse the postulated relationship, treating life expectancies as inputs reflecting general health status of a population, and level of development as the output. Countries are said to be efficient if they have achieved the maximum output observable for a given level of input, or if they have minimized the inputs needed to achieve a prescribed level of output. Together, the efficient cases form an ‘efficiency frontier.’ DEA, a form of linear programming, also permits the degree of inefficiency of countries lying behind this frontier to be measured by calculating the extent of the ‘output slacks’ that are present. Output slacks are the shortfalls in the level of performance that could have been achieved given the inputs available, and may themselves be treated as independent variables in explorations of the sources of demographic inefficiency. One example of such an exploration is offered—an attempt to account for shortfalls in female life expectancy, given levels of development.

Modern digital spectral analysis confirms that very noisy inflation and economic growth series share ∼9- and ∼18-year business and building cycle signals, but that inflation alone displays the additional ∼28- and ∼56-year rhythms of the long wave. The growth cycle that accounts for the greatest variance is one of ∼6 years, probably associated with El Niño-Southern Oscillation (ENSO) fluctuations. Discussion of these results leads to clarification of major sources of confusion in the long-wave literature, and to confirmation of the hypothesis that mode-locked endogenous rhythms may have their timing controlled by an exogenous pacemaker that links inflation and growth.

Data envelopment analysis (DEA) is proposed as an alternative to ordinary least squares (OLS) in the explanation of cause-effect/input-output relationships. Use of DEA permits efficiency frontiers to be located and the magnitudes of inefficiencies to be estimated, as raw materials for further exploratory inquiry. The method is applied to the relationships between personal computer deployment, urbanization, and economic development.

The mean rate of innovation diffusion in the U.S. is compared with the long wave of prices. A clear relationship is evident, with the long waves led by the innovation waves. Kondratiev peaks mark the periods of instability that accompany market saturation and the onset of technological restructuring.

The central theses of William Strauss and Neil Howe's book Generations are reviewed and data they present on national leadership shares of successive cohort generations are analyzed. Their generational cycles are shown to repeat with Kuznets cycle/Kondratiev wave rhythmicity, and generational shifts to coincide with long-wave crises. This discovery leads to a reevaluation of their generational typology from the Civil War to the Great Depression and a reformulation of the generational characterizations in a format consistent with long-wave relationships of polity and economy. The effect is to enrich and generalize both generational and long-wave theory.