Economic Productivity Growth Rate
An Economic Productivity Growth Rate is an economic growth rate for an economic productivity measure.
- Context:
- It can range from being a Labor Productivity Growth Rate to being ...
- Example(s):
- Counter-Example(s):
- See: Technological Innovation Rate, Technological Stagnation.
References
2012
- http://en.wikipedia.org/wiki/Productivity#Growth_accounting_model
- Growth accounting model is used in economics to account the contribution of different factors of production to economic growth.
The idea of growth accounting is to decompose the growth rate of economy's total output into that which is due to increases in the amount of inputs used and that which cannot be accounted for by observable changes in input utilization. The unexplained part of growth is then taken to represent increases in productivity.
The growth accounting model is normally expressed in the form of the exponential growth function. It can also be expressed in the form of the arithmetical model, which way is used here because it is more descriptive and understandable. The principle of the accounting model is simple. The weighted growth rates of inputs (factors of production) are subtracted from the weighted growth rates of outputs. Because the accounting result is obtained by subtracting it is often called a “residual”. The residual is often defined as the growth rate of output not explained by the share-weighted growth rates of the inputs (Hulten 2009, 6).
We can use the real process data of the productivity model (above) in order to show the logic of the growth accounting model and identify possible differences in relation to the productivity model. When the production data is the same in the model comparison the differences in the accounting results are only due to accounting models. We get the following growth accounting from the production data.
- Growth accounting model is used in economics to account the contribution of different factors of production to economic growth.
1998
- (Brynjolfsson et al., 1998) ⇒ Erik Brynjolfsson, and Lorin M. Hitt. (1998). “Beyond the Productivity Paradox.” In: Communications of the ACM Journal, 41(8). doi:10.1145/280324.280332
- QUOTE: An important question that has been debated for almost a decade is whether computers contribute to productivity growth. Productivity isn't everything. However, as noted by the economist Paul Krugman, in the long run it is almost everything. Productivity growth determines our living standards and the wealth of nations. This is because the amount a nation can consume is ultimately closely tied to what it produces. By the same token, the success of a business generally depends on its ability to deliver more real value for consumers without using more labor, capital or other inputs.
1987
- (Krugman, 1987) ⇒ Paul Krugman. (1987). “The narrow moving band, the Dutch disease, and the competitive consequences of Mrs. Thatcher: Notes on trade in the presence of dynamic scale economies.” In: Journal of Development Economics, 27. doi:10.1016/0304-3878(87)90005-8
- ABSTRACT: This paper presents a model of trade in which comparative advantage, instead of being determined by underlying attributes of countries, evolves over time through learning-by-doing. In this model, arbitrary patterns of specialization, once established, tend to become entrenched over time. The model sheds light on three widely held views that do not make sense in more conventional models. First is the view that temporary protection of selected sectors can permanently alter the pattern of comparative advantage in the protecting country's favor. Second is the view that seemingly favorable developments, such as the discovery of exportable natural resources, may lead to a permanent loss of other sectors and reduce welfare in the longrun. Third is the possibility that a temporary overvaluation of a currency due to tight money can lead to a permanent loss of competitiveness in some sectors.
1986
- (Baumol, 1986) ⇒ William J. Baumol. (1986). “Productivity Growth, Convergence, and Welfare: What the Long-Run Data Show.” In: The American Economic Review, 76(5).