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Factor-Specific Productivity
Author(s) -
Brian Piper
Publication year - 2014
Publication title -
ssrn electronic journal
Language(s) - English
Resource type - Journals
ISSN - 1556-5068
DOI - 10.2139/ssrn.2383892
Subject(s) - factor (programming language) , productivity , business , economics , computer science , economic growth , programming language
Economists examine two types of variables when studying aggregate production and economic growth. Some of these variables are directly productive factors (physical capital, labor and human capital), while other variables aren’t productive themselves, but affect production indirectly. I introduce an approach for studying indirect inputs by allowing them to affect output in three ways: by changing TFP, by changing the productivity of individual productive factors (Factor-Specific Productivity), and by changing the rates at which productive factors are accumulated. My model finds that indirect inputs have strong effects on the productivity of specific productive factors. My model outperforms a model which includes the same indirect inputs only as determinants of TFP. Increases in indirect inputs are found to lead to future growth in the supply of direct inputs. Additionally, my model has more empirically realistic implications for returns to scale and convergence than traditional neo-classical models.

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