Сравнение методов

	Solow Residual	Total Factor Productivity
Область	Экономика	Экономика
Семейство	Regression model	Regression model
Год появления	1957	1957
Автор метода	Robert Solow	Robert Solow; Caves, Christensen & Diewert
Тип	Residual measure of total factor productivity growth	Productivity measurement via index numbers and production functions
Основополагающий источник	Solow, R. M. (1957). Technical change and the aggregate production function. The Review of Economics and Statistics, 39(3), 312–320.	Solow, R. M. (1957). Technical change and the aggregate production function. The Review of Economics and Statistics, 39(3), 312–320.
Другие названия	TFP Residual, Measure of Our Ignorance, Technical Change Residual, Multifactor Productivity Residual	TFP, Multifactor Productivity, MFP, Joint Factor Productivity
Связанные	3	4
Сводка	The Solow residual is the portion of output growth that is not explained by the growth of measured inputs — capital and labour — after each input's growth is weighted by its share of national income. Introduced by Robert Solow in 1957, it is the empirical counterpart of total factor productivity (TFP) growth and is computed by subtraction rather than measured directly. Because it captures everything that raises output without raising measured inputs, it has been famously described as a 'measure of our ignorance': it labels what we cannot otherwise account for, lumping together genuine technical change, efficiency gains, and pure measurement error.	Total factor productivity (TFP), also called multifactor productivity, measures how much output an economic unit produces from a given bundle of all its inputs taken together — capital, labour, and often intermediate materials. It is the efficiency with which inputs are jointly transformed into output, and it captures everything that raises output without raising measured inputs: technology, organization, and the reallocation of resources. TFP is measured in two broad ways: the index-number approach, which forms the ratio of an aggregate output index to an aggregate input index using economically justified (superlative) weights, and the econometric production-function approach, which estimates the technology and recovers productivity as an unobserved term.