Сравнение методов

	Growth Accounting	Solow Residual
Область	Экономика	Экономика
Семейство	Regression model	Regression model
Год появления	1957	1957
Автор метода	Robert Solow; Dale Jorgenson & Zvi Griliches	Robert Solow
Тип	Production-function-based decomposition of output growth	Residual measure of total factor productivity growth
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	Sources of Growth Analysis, Solow Growth Accounting, Production Function Decomposition, Total Factor Productivity Accounting	TFP Residual, Measure of Our Ignorance, Technical Change Residual, Multifactor Productivity Residual
Связанные	3	3
Сводка	Growth accounting is a production-function-based framework that decomposes the growth rate of aggregate output into the contributions of growth in measured inputs — typically capital and labour — and a residual that captures the growth in total factor productivity (TFP). Building on Robert Solow's 1957 derivation and refined by Dale Jorgenson and Zvi Griliches in 1967, it weights each input's growth rate by its share of national income and attributes whatever output growth is left unexplained to improvements in productivity, technology, and efficiency.	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.