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Total factor productivity is commonly recognized as a variable that represents the amount of output not directly related to the amount of inputs, such as materials and capital. Total factor productivity is part of a larger idea of multi-factor productivity, where economic planners look at all of the factors in the growth of a corporate or national economy. In these kinds of appraisals, total factor productivity (TFP) addresses the kinds of growth that can’t be linked to a corresponding rise in concrete input. For example, if two companies, company A and company B, have the same amounts of materials and resources, but one produces more than the other, someone might attribute the better output of the winner to hiring more skilled labor, or having a more educated middle management. That's how total factor productivity helps to explain the "big picture" in corporate activities.
Total factor productivity uses something called the “Solow residual” to assess outputs. The Solow residual, named after economist Robert Solow, works on the principle that greater productivity of labor will affect the Gross Domestic Product (GDP) of a country’s economy, along with concrete factors like capital allocation and available amount of labor. Some aspects of total factor productivity, and the use of the Solow residual, are controversial in the community of economists because of disagreements on the accuracy of certain variables.
As mentioned, part of the idea of total factors for productivity is the study of how an abundance of skilled labor changes outputs in a local economy. Assessments of these kinds of economic changes are often linked to specific Research and Development (R&D) efforts on the part of a business or other party. Considering how innovation changes productivity is very relevant to how the use of total factor productivity works.
Critics of total factors for productivity methods also talk about the differences between different types of developing economies. Different nations develop their economies at very different rates according to their unique situations and the timelines for their growth. All of this makes concrete assessment somewhat subjective, and limits the power of equation based analysis to these sorts of situations.
Total factor productivity may be uniquely useful in dealing with local economies or small scale models. Simplified production models can also be good resources for learning more about a larger macroeconomic model. Many economists still consider TFP and related ideas to be helpful in assessing growth on various scales, or for some types of predictive modeling. In some national economic models, experts say TFP may be responsible for up to 60% of growth, demonstrating that the relation of concrete investment and labor to an end result is widely variable.
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