The Production Function for Manufacturing in the United States, 1904

1943 ◽  
Vol 51 (1) ◽  
pp. 61-65 ◽  
Author(s):  
Patricia Daly ◽  
Ernest Olson ◽  
Paul H. Douglas
Keyword(s):  
United States ◽  
Production Function ◽  
The United States

Productivity in the pulp and paper industries of the United States and Canada: a nonparametric analysis

1994 ◽  
Vol 24 (12) ◽  
pp. 2353-2361 ◽  
Author(s):  
Jiing-Shyang Hseu ◽  
Joseph Buongiorno
Keyword(s):  
United States ◽  
Total Factor Productivity ◽  
Production Function ◽  
The United States ◽  
Pulp And Paper ◽  
Distance Functions ◽  
Theil Index ◽  
Factor Productivity ◽  
Economic Significance ◽  
Pulp And Paper Industries

Partial and total measures of factor productivity are presented for the pulp and paper industries of the United States and Canada, from 1959 to 1987. Total factor productivity was measured with (1) a Tornqvist–Theil index, (2) a nonparametric index with translating hypothesis, and (3) a nonparametric index with distance functions. Method 1 implied a constant return to scale translog production function. Methods 2 and 3 removed any assumption on the functional form of the production function. Furthermore, method 3 allowed for fully disaggregated outputs. Methods 1 and 3 gave similar results within countries: an increase in total factor productivity of 0.7% per year in the United States and of 0.5% per year in Canada. Method 2 gave rates of growth of total factor productivity that were twice as high, but unreliable because of the assumptions of the method. From 1961 to 1984, when comparable data are available, methods 1 and 3 gave growth rates of total factor productivity that were significantly higher, statistically, in the United States than in Canada. Nevertheless, the differences seem to be too small to be of economic significance.

Birth Outcome Production Function in the United States

1987 ◽  
Vol 22 (3) ◽  
pp. 339 ◽  
Author(s):  
Hope Corman ◽  
Theodore J. Joyce ◽  
Michael Grossman
Keyword(s):  
United States ◽  
Production Function ◽  
Birth Outcome ◽  
The United States

The Neural Network Production Function: Panel Evidence for the United States

2019 ◽  
pp. 953-978
Author(s):  
Mike G. Tsionas ◽  
Konstantinos N. Konstantakis ◽  
Panayotis G. Michaelides
Keyword(s):  
Neural Network ◽  
United States ◽  
Production Function ◽  
The United States ◽  
The Neural Network

scholarly journals Estimating Effects of Agricultural Research and Extension Expenditures on Productivity: A Translog Production Function Approach

1984 ◽  
Vol 16 (2) ◽  
pp. 1-8 ◽  
Author(s):  
Syu-Jyun Larry Lyu ◽  
Fred C. White ◽  
Yao-Chi Lu
Keyword(s):  
United States ◽  
Production Function ◽  
Agricultural Research ◽  
The United States ◽  
Rate Of Return ◽  
Internal Rate Of Return ◽  
Cross Sectional ◽  
Internal Rate ◽  
Production Function Approach ◽  
Using Data

AbstractThe effects of agricultural research and extension expenditures on productivity in the United States are estimated during the period 1949-81 using data for ten production regions. The large time-series cross-sectional data base allows the translog production function to be estimated directly. Results from the translog and Cobb-Douglas production functions are compared. The results indicate that use of the Cobb-Douglas production function would overestimate the internal rate of return of agricultural research and extension expenditures in the United States and eight production regions. The total marginal product and internal rate of return for the United States are $8.11 and 66 percent, respectively.

Technological Change in the Machine Tool Industry, 1840–1910

1963 ◽  
Vol 23 (4) ◽  
pp. 414-443 ◽  
Author(s):  
Nathan Rosenberg
Keyword(s):  
United States ◽  
Machine Tool ◽  
Technological Change ◽  
Production Function ◽  
The United States ◽  
Technological Changes ◽  
Machine Tool Industry ◽  
Labor Inputs ◽  
Per Capita ◽  
Quantitative Importance

Technological change has come to absorb an increasing share of the attention of the economist in recent years. Several attempts have been made to assess the quantitative importance of technological change, as opposed to increases in factor supplies, in accounting for the secular rise in per capita incomes in the United States. It appears, in all these studies, that technological changes (shifts in the production function) have been far more important than has the mere growth in the supplies of capital and labor inputs, as conventionally measured (movement along an existing production function). In a sense, this should be cause for deep concern, since the comparative neglect of the process of technological change (with the major exceptions until very recent years, of the works of Marx, Schumpeter, and Usher) suggests a serious malallocation of our intellectual resources. If the studies of such people as Abramovitz and Solow are even approximately correct with respect to orders of magnitude, then the contribution of technological change to rising per capita incomes absolutely dwarfs the contribution from a rising but qualitatively unchanging stock of capital. It would appear that we have indeed been playing Hamlet without the Prince.

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