Economists call a key part of growth a measure of ignorance
When economists subtract the growth explained by extra workers and extra machines, a stubborn remainder is left over, called total factor productivity. It is supposed to capture innovation and better organisation. Yet because it is only what remains after everything measurable is removed, the economist Moses Abramovitz memorably described it in 1956 as a measure of our ignorance.
Productivity is output divided by input over a period, and the version people quote most is labour productivity: a measure of output such as gross domestic product, divided by hours worked or by the number of people employed. Hours are usually preferred, because a simple headcount hides part-time contracts, overtime and paid leave. Output is counted as value added, the worth of what is produced minus the materials bought in, so that one firm's product is not counted again when another firm uses it.
Robert Solow gave the leftover its best-known description in 1957, saying he used technical change as shorthand for any shift in how inputs turn into output. Slowdowns, speed-ups and a better educated workforce would all show up under that label. The residual therefore bundles welcome things, like new techniques, with unwelcome ones, like measurement error and faulty models, which is why its link to real productivity remains unclear.
Why care? One widely quoted argument says that, over the long haul, productivity comes close to being the whole story, because a nation can only lift living standards by raising output per worker. More value added means more income to share. The gains can reach workers through higher pay, owners through bigger returns, customers through lower prices, governments through taxes and even the environment when less material or pollution goes into each unit. Simply piling on more inputs without getting better at using them tends instead to squeeze wages and returns.
Measurement itself has been transformed. Firms once tracked output in tables and hand-drawn graphs, then with tabulating machines from the 1920s, mainframes later, and cheap computers by the late 1970s; today nearly any figure can be watched live. The biggest leaps come from new ways of organising work, and the classic example is the assembly line that followed the car into commercial production.
Source: Productivity
